Pardee Wiki - User contributions [en]

World Development Indicators, World Bank

2026-04-25T01:14:21Z

Norah.Shamin:

__FORCETOC__

= Summary =
The World Bank's Open Data is an initiative from the the World Bank Group to produce reliable data about its member countries, including a number of macro, financial, and sector databases. Their datasets include ones focused on development, aid effectiveness, climate change, economy, education, debt, infrastructure, etc. The World Bank also has a World Development Indicators (WDI) database, which is the premier compilation of cross country comparable data on development and is the primary collection of development indicators. WDI specifically contains 1,400 time series indicators from 217 economies, with much of that data going back more than 50 years. Data for Open Data and WDI is compiled from statistical systems of member countries and officially recognized international sources. Most social and economic data are updated annually or less often and some economic and financial data are updated quarterly. The WDI database is updated quarterly, sometimes more often.

The data team uses World Bank Open Data and WDI for a number of series about education, agriculture, aid, gender issues, environment, finances, economics, and development. Most importantly, WB databases are used for GDP and GDPPC. Example series from the World Bank include but are not limited to, SeriesAgFoodProductIndex, SeriesAidRec%GNI, SeriesCompanyValue%GDP, SeriesExportImport%GDP.

For series GovWBDoingBusinessCostofStarting, the source (Doing Business) has been discontinued now.

The last update was in July 2025.

= Tables in IFs =
{| class="wikitable"
|Variable
|Definition
|Units
|UsedInPreprocessor
|UsedInPreprocessorFileName
|Code in Source
|Decimal Places
|Formula
|-
|ArmsImp%TotImp
|Arms imports (SIPRI trend indicator values)
|Percent
|1
|ECONOMY
|MS.MIL.MPRT.KD
|3
|%'NE.IMP.GNFS.CD'
|-
|XDebtPNG%GDP
|External debt, private non-guaranteed, as percentage of gross domestic product
|Percent
|1
|ECONOMY
|DT.DOD.DPNG.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XDebtPPG%GDP
|External debt, public and publicly guaranteed, as percentage of gross domestic product
|Percent
|1
|ECONOMY
|DT.DOD.DPPG.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XFlowsIDA%GDP
|Net flows from IDA as % of GDP
|Percent
|1
|ECONOMY
|DT.NFL.MIDA.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XFlowsIMFNonCon%GDP
|Net nonconcessional flows from IMF as % of GDP
|Percent
|1
|ECONOMY
|DT.NFL.IMFN.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XIMFCredit%GDP
|IMF credits as % of GDP
|Percent
|1
|ECONOMY
|DT.DOD.DIMF.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XIncPayments%GDP
|Income payments as % of GDP
|Percent
|1
|ECONOMY
|BM.GSR.FCTY.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XPortBonds%GDP
|Portfolio investment in bonds (PPG and PNG) as % of GDP
|Percent
|1
|ECONOMY
|DT.NFL.BOND.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XPortEquity%GDP
|Portfolio investment in equity as % of GDP
|Percent
|1
|ECONOMY
|BX.PEF.TOTL.CD.WD
|4
|%'NY.GDP.MKTP.CD'
|-
|XReserves%GDP
|Gross international reserves as % of GDP
|Percent
|1
|ECONOMY
|FI.RES.TOTL.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XFlowsIMFCon%GDP
|Net concessional flows from IMF as % of GDP
|Percent
|1
|ECONOMY
|DT.NFL.IMFC.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XIncReceipts%GDP
|Income receipts as % of GDP
|Percent
|1
|ECONOMY
|BX.GSR.FCTY.CD
|3
|%'NY.GDP.MKTP.CD'
|-
|XFlowsIBRD%GDP
|Net flows from IBRD as % of GDP
|Percent
|1
|ECONOMY
|DT.NFL.MIBR.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|XWBLoans%GDP
|IBRD loans and IDA credits as % of GDP
|Percent
|1
|ECONOMY
|DT.DOD.MWBG.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|GovtCurRev%GDP
|Current government revenue as % of GDP
|Percent
|1
|ECONOMY
|GC.REV.XGRT.GD.ZS
|3
|%'NY.GDP.MKTP.CD'
|-
|ExportServices%GDP
|Exports of services as % of GDP
|Percent
|1
|ECONOMY
|BX.GSR.NFSV.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|ExportsMerchandise%GDP
|Exports of merchandise as % of GDP
|Percent
|1
|ECONOMY
|TX.VAL.MRCH.CD.WT
|4
|%'NY.GDP.MKTP.CD'
|-
|ImportServices%GDP
|Imports of Services as % of GDP
|Percent
|1
|ECONOMY
|BM.GSR.NFSV.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|ImportsMerchandise%GDP
|Imports of merchandiseas % of GDP
|Percent
|1
|ECONOMY
|TM.VAL.MRCH.CD.WT
|4
|%'NY.GDP.MKTP.CD'
|-
|XWorkerRemitPaid%GDP
|Worker remittances by country where paid as % of GDP
|Percent
|1
|ECONOMY
|BM.TRF.PWKR.CD.DT
|4
|%'NY.GDP.MKTP.CD'
|-
|XWorkerRemitReceived%GDP
|Worker remittances received by country as % of GDP
|Percent
|1
|ECONOMY
|BX.TRF.PWKR.CD.DT
|4
|%'NY.GDP.MKTP.CD'
|-
|XDebt%GDP
|External debt as percentage of gross domestic product
|Percent
|1
|ECONOMY
|DT.DOD.DECT.CD
|4
|%'NY.GDP.MKTP.CD'
|-
|NetForeignAssets%GDP
|Net Foreign Assets (current LCU) as a percent of GDP.
|Percent
|0
|
|FM.AST.NFRG.CN
|4
|%'NY.GDP.MKTP.CN'
|-
|Labor
|Labor force size
|Millions
|1
|POPULATION
|SL.TLF.TOTL.IN
|4
|/1000000
|-
|PopulationUrban
|Urban population
|Millions
|1
|POPULATION
|SP.URB.TOTL
|4
|/1000000
|-
|GDPCurDol
|Gross Domestic Product in Current US$
|Billion $
|1
|ENERGY
|NY.GDP.MKTP.CD
|4
|/1000000000
|-
|Xdebt
|External long-term (more than 1 year) debt: public, publically guaranteed and priv nonguaranteed
|Billion $
|1
|ECONOMY
|DT.DOD.DLXF.CD
|4
|/1000000000
|-
|LaborFemale%
|Portion of labor force made up by women
|Percent
|1
|POPULATION
|SL.TLF.TOTL.FE.ZS
|4
|
|-
|LaborSecInd%Tot
|Labor in industry as % of total
|Percent
|0
|
|SL.IND.EMPL.ZS
|4
|
|-
|LaborSecSer%Tot
|Labor in services as % of total
|Percent
|0
|
|SL.SRV.EMPL.ZS
|4
|
|-
|VaddInd%
|Value added in industry as percent of GDP
|Percent
|1
|ECONOMY
|NV.IND.TOTL.ZS
|3
|
|-
|OresMetsIm%MerchIm
|Ores and Metals imports as % of merchandise imports
|Percent
|1
|ECONOMY
|TM.VAL.MMTL.ZS.UN
|4
|
|-
|GovtDebt%GDP
|Central government debt as % of GDP
|Percent
|1
|ECONOMY
|GC.DOD.TOTL.GD.ZS
|4
|
|-
|VaddMan%
|Value added in manufacturing as percent of GDP
|Percent
|1
|ECONOMY
|NV.IND.MANF.ZS
|3
|
|-
|PopForeign%
|Foreign population as % of total population
|Percent
|0
|
|SM.POP.TOTL.ZS
|4
|
|-
|LaborAgriSector
|Agricultural labor force as % of total employment, ISIC multiple revisions
|Percent
|1
|ECONOMY
|SL.AGR.EMPL.ZS
|3
|
|-
|GenderUnpaidDomesticWorkTimeFemale
|Proportion of time spent on unpaid domestic and care work, female (% of 24 hour day).
|Percent
|0
|
|SG.TIM.UWRK.FE
|2
|
|-
|GenderUnpaidDomesticWorkTimeMale
|Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day).
|Percent
|1
|POPULATION
|SG.TIM.UWRK.MA
|2
|
|-
|ExportGoodSer%
|Exports of goods and services as % of GDP
|Percent
|1
|ECONOMY
|NE.EXP.GNFS.ZS
|4
|
|-
|EnElecTransLoss%
|Electric power transmission and distribution losses (% of output)
|Percent
|1
|INFRASTRUCTURE
|EG.ELC.LOSS.ZS
|4
|
|-
|GovtEdPub%GDP
|Educational expenditures (public) as percent of GDP
|Percent
|1
|ECONOMY
|SE.XPD.TOTL.GD.ZS
|4
|
|-
|GovWBDoingBusinessCostofStarting
|Cost of registring a business as a percent of per capita income
|Percent
|1
|SOCIOPOL
|IC.REG.COST.PC.ZS
|4
|
|-
|GovtMil%GDPWDI
|Military expenditures (as percent of GDP). Taiwan, China values filled by SIPRI.
|Percent
|1
|ECONOMY
|MS.MIL.XPND.GD.ZS
|4
|
|-
|GovCon%GDP
|Government (general) final consumption as % of GDP
|Percent
|1
|ECONOMY
|NE.CON.GOVT.ZS
|3
|
|-
|GovExpense%GDP
|Government expense as % of GDP (compare with govt expenditures)
|Percent
|1
|ECONOMY
|GC.XPN.TOTL.GD.ZS
|3
|
|-
|ImportGoodSer%
|Imports of goods and services as % of GDP
|Percent
|1
|ECONOMY
|NE.IMP.GNFS.ZS
|4
|
|-
|EnElecConsPerCap
|Electricity consumption per capita
|KWH/Cap
|1
|INFRASTRUCTURE
|EG.USE.ELEC.KH.PC
|4
|
|-
|InvestGrCapForm%GDP
|Gross capital formation (Investment), percent of GDP
|Percent
|1
|ECONOMY
|NE.GDI.TOTL.ZS
|3
|
|-
|XFDIInflows%GDP
|Foreign direct investment net inflow as % of GDP
|Percent
|1
|ECONOMY
|BX.KLT.DINV.WD.GD.ZS
|4
|
|-
|XFDIOutflows%GDP
|Foreign direct investment net outflow as % of GDP
|Percent
|1
|ECONOMY
|BM.KLT.DINV.WD.GD.ZS
|3
|
|-
|IncShareL20%
|Income share of poorest 20% of population
|Percent
|1
|ECONOMY
|SI.DST.FRST.20
|3
|
|-
|LaborUnemploy%
|Labor unemployment, % of labor force
|Percent
|1
|POPULATION
|SL.UEM.TOTL.ZS
|3
|
|-
|TaxImportDuties%Rev
|Customs and other import duties (% of tax revenue)
|Percent
|1
|ECONOMY
|GC.TAX.IMPT.ZS
|4
|
|-
|OresMetsEx%MerchEx
|Ores and Metals exports as % of merchandise exports
|Percent
|1
|ECONOMY
|TX.VAL.MMTL.ZS.UN
|4
|
|-
|PopContrUse%WDI
|Prevalence of contraceptive use
|Percent
|0
|
|SP.DYN.CONU.ZS
|4
|
|-
|EnElecAccess%National
|Access to electric energy National (% of population)
|percentage
|1
|INFRASTRUCTURE
|EG.ELC.ACCS.ZS
|4
|
|-
|EnElecAccess%Rural
|Access to electricity in Rural areas (% of population)
|percentage
|1
|INFRASTRUCTURE
|EG.ELC.ACCS.RU.ZS
|4
|
|-
|EnElecAccess%Urban
|Access to electricity in Urban areas (% of population)
|percentage
|1
|INFRASTRUCTURE
|EG.ELC.ACCS.UR.ZS
|4
|
|-
|MalnChil%WeightWB
|Percentage of children under 5 malnourished based on weight; US benchmark
|Percent
|1
|AGRICULTURE
|SH.STA.MALN.ZS
|4
|
|-
|TaxGoodSer%CurRev
|Taxes on goods and services as % of total govt revenue
|Percent
|1
|ECONOMY
|GC.TAX.GSRV.RV.ZS
|3
|
|-
|TaxSocSec%CurRev
|Social security taxes as % of total govt revenue
|Percent
|1
|ECONOMY
|GC.REV.SOCL.ZS
|3
|
|-
|GiniExtended
|Gini index of income inequality (lower = more equal)
|Index
|1
|ECONOMY
|SI.POV.GINI
|3
|
|-
|ICTInternet%Pop
|Percent of population on-line
|Percent
|1
|SOCIOPOL
|IT.NET.USER.ZS
|4
|
|-
|LaborAgr%TotFemale
|Employees, agriculture, female as % of female employment
|Percent
|1
|POPULATION
|SL.AGR.EMPL.FE.ZS
|4
|
|-
|VaddAg%
|Value added in agriculture as percent of GDP
|Percent
|1
|ECONOMY
|NV.AGR.TOTL.ZS
|3
|
|-
|VaddSer%
|Value added in services as percent of GDP
|Percent
|1
|ECONOMY
|NV.SRV.TOTL.ZS
|3
|
|-
|LaborAgr%TotMale
|Employees, agriculture, males as % of male employment
|Percent
|1
|POPULATION
|SL.AGR.EMPL.MA.ZS
|4
|
|-
|XCurActBal%GDP
|Current account balance (% of GDP)
|Percent
|1
|ECONOMY
|BN.CAB.XOKA.GD.ZS
|3
|
|-
|MaternalMortalityRatio
|Maternal deaths per 100,000 live births
|Ratio
|1
|POPULATION
|SH.STA.MMRT
|2
|
|-
|EnvPMWDI
|PM2.5 air pollution, mean annual exposure (micrograms per cubic meter)
|micrograms per cubic meter
|1
|ENVIRONMENT
|EN.ATM.PM25.MC.M3
|5
|
|-
|ChildStuntingPercentWDI
|Stunting (Height for age) amongst children aged under the age of 5
|Percent
|1
|HEALTH
|SH.STA.STNT.ZS
|5
|
|-
|HealthMalarBedNetsWDI
|Use of insecticide-treated bed nets (% of under-5 population)
|Percent
|1
|HEALTH
|SH.MLR.NETS.ZS
|3
|
|-
|AidRecGrant%TotRev
|Grants and other revenue include grants from other foreign governments, international organizations, and other government units;
|Percent
|1
|ECONOMY
|GC.REV.GOTR.ZS
|3
|
|-
|IncBelowNPL%WDI
|Population below national poverty line
|Percent
|1
|ECONOMY
|SI.POV.NAHC
|1
|
|-
|ICTImport%Imp
|Imports of ICT goods as % of total goods imports
|Percent
|0
|
|TM.VAL.ICTG.ZS.UN
|2
|
|-
|ICTExport%Exp
|Exports of ICT goods as % of total goods exports
|Percent
|0
|
|TX.VAL.ICTG.ZS.UN
|2
|
|-
|HouseCon%GDP
|Households and NPISHs final consumption expenditure (% of GDP)
|Percent
|1
|ECONOMY
|NE.CON.PRVT.ZS
|3
|
|}

= Data Pulling Instructions: World Bank Individual Indicators =
Step 1. To pull data from the world bank, navigate to [https://data.worldbank.org/ data.worldbank.org]

Step 2. To find the series, you can type in the search bar, click <Country> or click <nowiki><Indicator>.</nowiki>

Step 3. Go to step 4 if clicked on <Country> or to step 7 if clicked on <nowiki><Indicator>.</nowiki>
[[File:WBscreenshot10.jpg|center|World Bank Data homepage|thumb|499x499px]]

Step 4. If clicked on <Country>, you can select an individual country or options under various categories, such as <Region> and <Income levels>. This example will use the <High Income> category.
[[File:WB IMG STEP 04.jpg|center|thumb|544x544px|Countries and Economies main page]]

Step 5. If a category is selected, the following example screen of <High Income> will formulate. From here, select the relevant topic/theme/SDG Goal, then click on the desired indicator. Then skip to steps 10-12, which show how to download an indicator.
[[File:WB IMG STEP 05.jpg|center|thumb|504x504px|High Income example page]]
Step 6. If an individual country is selected, the following example screen will formulate. From here, select the relevant topic/theme/SDG Goal, then click on the desired indicator. Then skip to steps 10-12, which show how to download an indicator.

[[File:WBscreenshot15.jpg|center|Afghanistan example page|thumb|507x507px]]
Step 7. If clicked on <nowiki><Indicator>, navigate to the relevant category of the desired indicator or type in the search bar. For this example, click on the <Climate Change> category.</nowiki>
[[File:WB IMG STEP 07.jpg|center|Indicators main page|thumb|499x499px]]

Step 8. The following page will populate. Click on <Access to electricity (% of population)> as an indicator example.
[[File:WB IMG STEP 08.jpg|center|Example category from indicators page|thumb|508x508px]]

Step 9. Clicking on <Access to electricity (% of population)> will lead to this page.

[[File:WBscreenshot5.jpg|center|Access to electricity indicator|thumb|502x502px]]

Step 10. If a more specific variable is desired, select one of the options of the right side. As an example, <Access to electricity, urban (% of urban population)> is showed here.

[[File:WBscreenshot12.jpg|center|Access to electricity indicator|thumb|504x504px]]

Step 11. Before downloading, select desired time range on the sliding scale beneath the graph.

Step 12. On the right side of the graph, under <Download>, click <EXCEL>. An excel data set will immediately download. You may also click <WDI Tables> to see the data in a slightly different format.
[[File:WB IMG STEP 12.jpg|center|Download Indicator|thumb|493x493px]]

= Data Pulling Instructions: World Development Indicators Database =
Step 1. To pull data from the World Bank's World Development Indicators database, navigate to https://databank.worldbank.org/source/world-development-indicators

Step 2. In order to pull data, you'll need to first make selections regarding the database to pull from, countries, series, and time. These variables are on the left hand side.
[[File:WBwdiScreenshot9.jpg|center|World Bank WDI main page|thumb|505x505px]]

Step 3. First, select a database. This example will stay with WDI. [[File:WBwdiScreenshot.jpg|center|WDI page with database options|thumb|502x502px]]

Step 4. Second, select the countries to include in the data. To choose all countries, click the checkbox above the list of country names. [[File:WBwdiScreenshot10.jpg|center|WDI page with country options|thumb|509x509px]]

Step 5. Third, select series from keywords or alphabetical list. This example will choose <Access to electricity, (% of population)>.
[[File:WB WDI IMG STEP 05.jpg|center|thumb|508x508px|WDI page with series options]]
Step 6. Finally, select time as range of years. To choose all years, click the checkbox above the list of years.
. [[File:WBwdiScreenshot11.jpg|center|WDI page with year options|thumb|501x501px]]

Step 7. When all variables have been selected, click <Apply Changes>. [[File:WBwdiScreenshot12.jpg|center|WDI page with "Apply Changes"|thumb|499x499px]]

Step 8. The following preview page will formulate. You can also adjust the layout on the left side under the <Layout> tab, and you can preview data in different formats by clicking on <nowiki><Table>, <Chart>, and <Map>. </nowiki>

To download, click <Download Options> in right hand corner. Then click <Excel> and an Excel dataset will immediately download.
[[File:WB WDI IMG STEP 08(2).jpg|center|thumb|501x501px|WDI page with download options]]

= Data Pulling Instructions: World Development Indicators Bulk =

# Navigate to https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators
# Download CSV

= Data Notes =
'''As of April 2026 we added HouseCon%GDP. Make sure to include it in the next update!'''

We updated 82 series from WDI, 71 of them are preprocessors and 11 non preprocessors.
# Download CSV file from https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators
# Open the WDICSV.csv file.
# Use the "'''Code in Source'''" from the DataDict and "'''Indicator Code'''" from WDICSV file to preprare the series.
# Be care of the "Formula", if there is a "%'''XXXX'''"(the XXXX is the "Indicator Code"), then you need to use the series divide the series after "%". The series after "%" also in the WDICSV.
## Please keep in mind *100 after you finish the division to make it in "'''Percent'''" instead of decimal.
## Always applying "'''round'''" function after you applied multiplying 100.
# The "'''Years'''" for some series are discountinued, please remove the years with all "Nulls" before importing.
# Blending with old data in IFsHistSeries:
## A country that has data in the previous release but not anymore. For this case, we need to bring the data in unless we have a solid proof to say they delete a country's data on purpose. For example, in the table GovCon%GDP, Nigeria used to have values, but the new table has all nulls for it because WDI somehow removes values for Nigeria.
## Some historical years of data are missing completely for all countries. WDI does this every now and then. For example, for certain tables, it used to have coverage back to 1960, then along the updates WDI only offers data back to 1980 or even 2000.
# If you want to try to use python scripts to pull the data, you may access the scripts from [https://github.com/n1shamin/World-Development-Indicators-Update-2025 here].

Emissions Database for Global Atmospheric Research (EDGAR)

2026-04-14T15:58:55Z

Norah.Shamin: /* Tables In IFs */

= Summary =
EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the primary system for companies and others submitting documents under the Securities Act of 1933, the Securities Exchange Act of 1934, the Trust Indenture Act of 1939, and the Investment Company Act of 1940.

It includes millions of company and individual filings, EDGAR benefits investors, corporations, and the U.S. economy overall by increasing the efficiency, transparency, and fairness of the securities markets.

= Tables In IFs =
The last update was in April 2026.
{| class="wikitable"
|+
!Variable
!Definition
!UsedInPreprocessor
|-
|EmissionsCH4EntericFermentation
|Methane emissions from enteric fermentation in gigagrams
|0
|-
|EmissionsCH4Oil&Gas
|Methane emissions from Oil and Gas production
|0
|-
|EmissionsCH4SolidFuels
|Methane emissions from solid fuels in gigagrams
|0
|-
|EmissionsCH4Other
|Methane emissions from other sources in gigagrams
|0
|-
|EmissionsCH4RiceCultivation
|Methane emissions from rice cultivation
|0
|-
|EmissionsCH4WasteWater
|Methane emissions from waste water handling
|0
|}

= Data Pulling Instructions =

#Go to https://edgar.jrc.ec.europa.eu/emissions_data_and_maps
#Click the most recent database. For instance in 2026 the latest database is "EDGAR_2025_GHG 1970-2024 (CO2, CH4, N2O, F-gases)"
##Click on this and you will be navigated to the download page
#Under the section "Annual totals by sector and country (1970-2024)" click "EDGAR CH4"[[File:EDGAR CH4 Download Page.png|none|thumb|600x600px]]
#Filter the data and pull the tables using the indicators. You can also use this [https://github.com/n1shamin/EDGAR Github repo].
= Data Notes =

Emissions Database for Global Atmospheric Research (EDGAR)

2026-04-14T15:58:32Z

Norah.Shamin: /* Data Pulling Instructions */

= Summary =
EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the primary system for companies and others submitting documents under the Securities Act of 1933, the Securities Exchange Act of 1934, the Trust Indenture Act of 1939, and the Investment Company Act of 1940.

It includes millions of company and individual filings, EDGAR benefits investors, corporations, and the U.S. economy overall by increasing the efficiency, transparency, and fairness of the securities markets.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Last IFs Update
!UsedInPreprocessor
|-
|EmissionsCH4EntericFermentation
|Methane emissions from enteric fermentation in gigagrams
|7/29/2019
|0
|-
|EmissionsCH4Oil&Gas
|Methane emissions from Oil and Gas production
|7/29/2019
|0
|-
|EmissionsCH4SolidFuels
|Methane emissions from solid fuels in gigagrams
|7/29/2019
|0
|-
|EmissionsCH4Other
|Methane emissions from other sources in gigagrams
|7/29/2019
|0
|-
|EmissionsCH4RiceCultivation
|Methane emissions from rice cultivation
|7/29/2019
|0
|-
|EmissionsCH4WasteWater
|Methane emissions from waste water handling
|7/29/2019
|0
|}

= Data Pulling Instructions =

#Go to https://edgar.jrc.ec.europa.eu/emissions_data_and_maps
#Click the most recent database. For instance in 2026 the latest database is "EDGAR_2025_GHG 1970-2024 (CO2, CH4, N2O, F-gases)"
##Click on this and you will be navigated to the download page
#Under the section "Annual totals by sector and country (1970-2024)" click "EDGAR CH4"[[File:EDGAR CH4 Download Page.png|none|thumb|600x600px]]
#Filter the data and pull the tables using the indicators. You can also use this [https://github.com/n1shamin/EDGAR Github repo].
= Data Notes =

File:EDGAR CH4 Download Page.png

2026-04-14T15:54:56Z

Norah.Shamin:

EDGAR CH4 Download Page

Emissions Database for Global Atmospheric Research (EDGAR)

2026-04-14T15:54:25Z

Norah.Shamin:

= Summary =
EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the primary system for companies and others submitting documents under the Securities Act of 1933, the Securities Exchange Act of 1934, the Trust Indenture Act of 1939, and the Investment Company Act of 1940.

It includes millions of company and individual filings, EDGAR benefits investors, corporations, and the U.S. economy overall by increasing the efficiency, transparency, and fairness of the securities markets.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Last IFs Update
!UsedInPreprocessor
|-
|EmissionsCH4EntericFermentation
|Methane emissions from enteric fermentation in gigagrams
|7/29/2019
|0
|-
|EmissionsCH4Oil&Gas
|Methane emissions from Oil and Gas production
|7/29/2019
|0
|-
|EmissionsCH4SolidFuels
|Methane emissions from solid fuels in gigagrams
|7/29/2019
|0
|-
|EmissionsCH4Other
|Methane emissions from other sources in gigagrams
|7/29/2019
|0
|-
|EmissionsCH4RiceCultivation
|Methane emissions from rice cultivation
|7/29/2019
|0
|-
|EmissionsCH4WasteWater
|Methane emissions from waste water handling
|7/29/2019
|0
|}

= Data Pulling Instructions =

#Go to https://edgar.jrc.ec.europa.eu/emissions_data_and_maps
#Click the most recent database. For instance in 2026 the latest database is "EDGAR_2025_GHG 1970-2024 (CO2, CH4, N2O, F-gases)"
##Click on this and you will be navigated to the download page
#Under the section "Annual totals by sector and country (1970-2024)" click "EDGAR CH4"
#
#
#
= Data Notes =

International Centre for Tax & Development (ICTD)

2026-04-07T16:23:37Z

Norah.Shamin: /* Data Pulling Instructions */

= Summary =
The International Centre for Tax & Development (ICTD) is an independent research center focused on improving tax policy and administration in lower-income countries.

= Tables In IFs =
Last updated in 2026. The striked out rows are no longer found in the dataset.
{| class="wikitable"
|+
!Variable
!Definition
!Name In Source
!UsedInPreprocessor
|-
|GovRevGenGrants%GDPICTD
|Grants, General Government, % of GDP
|Grants
|0
|-
|GovRevGenNonTax%GDPICTD
|General government non-tax revenue
|Tot Non Tax
|0
|-
|GovRevGenProperty%GDPICTD
|Property taxes, General Government, % of GDP
|Taxes on property
|0
|-
|GovRevGenSocSec%GDPICTD
|Social Contributions, General Government, % of GDP
|Social contributions
|0
|-
|GovRevGenTaxDirect%GDPICTD
|General government direct tax revenue % of GDP
|Direct
|0
|-
|GovRevGenTaxGoodSer%GDPICTD
|General government total goods and service tax revenue % of GDP
|GS
|0
|-
|GovRevGenTaxICorporate%GDPICTD
|General government total Corporate tax revenue % of GDP
|Taxes on Income, Profits & Capital Gains, o/w CIT, Total
|0
|-
|GovRevGenTaxIncome%GDPICTD
|General government total income tax revenue % of GDP
|Income
|0
|-
|GovRevGenTaxIndirect%GDPICTD
|General government total indirect tax revenue % of GDP
|Indirect
|0
|-
|<s>GovRevGenTaxIndividual%GDPICTD</s>
|<s>General government total Individual tax revenue % of GDP</s>
|<s>Individual</s>
|<s>0</s>
|-
|GovRevGenTaxTot%GDPICTD
|Total Tax Revenue General government
|Tot Tax
|0
|-
|GovRevGenTaxTrade%GDPICTD
|General government total trade tax revenue % of GDP
|Trade
|0
|-
|GovtCalcRevTot%GDPICTD
|Revenue, government, total, as % of GDP
|
|0
|-
|GovtCurRev%GDPICTD
|Current government revenue as % of GDP
|Total Revenue
|0
|-
|GovtRevCenNonTaxTot%GDPICTD
|Central government total non tax revenue % of GDP
|Non Tax Revenue
|0
|-
|GovtRevCenTaxDirect%GDPICTD
|Central government total direct tax revenue % of GDP
|Total Direct Taxes
|0
|-
|GovtRevCenTaxGoodSer%GDPICTD
|Central government total goods and service tax revenue % of GDP
|Taxes on Goods and Services
|0
|-
|GovtRevCenTaxICorporate%GDPICTD
|Central government total corporate tax revenue % of GDP
|Taxes on Income, Profits & Capital Gains, o/w CIT, Total
|0
|-
|GovtRevCenTaxIncome%GDPICTD
|Central government total income tax revenue % of GDP
|Total Taxes on Income, Profits, Capital Gains
|0
|-
|GovtRevCenTaxIndirect%GDPICTD
|Central government total indirect tax revenue % of GDP
|Indirect Taxes
|0
|-
|<s>GovtRevCenTaxIndividual%GDPICTD</s>
|<s>Central government total individual tax revenue % of GDP</s>
|<s>Individual Taxes</s>
|<s>0</s>
|-
|GovtRevCenTaxTot%GDPICTD
|Central government total tax revenue % of GDP
|Taxes Including SC
|0
|-
|GovtRevCenTaxTrade%GDPICTD
|Central government total trade tax revenue % of GDP
|Taxes on International Trade, Total
|0
|}

= Data Pulling Instructions =

#Go to https://www.ictd.ac/dataset/
#Choose the dataset for the table
##For example revenue tables will be in The Government Revenue Dataset
#Download the set
#Use the name in source to pull the data. Clean the data properly as there is a lot formatting that prohibit using a code. You can a use a script after cleaning it [https://github.com/n1shamin/Taxes-International-Centre-for-Tax-Development-ICTD- here].

= Data Notes =

International Centre for Tax & Development (ICTD)

2026-04-07T16:20:52Z

Norah.Shamin: /* Tables In IFs */

Emissions Data, Climate Watch

2026-04-07T16:13:47Z

Norah.Shamin: /* Tables in IFs */

= Summary =
Climate Watch offers open data, visualizations and analysis to help policymakers, researchers and other stakeholders gather insights on countries' climate progress. Climate Watch is managed by World Resources Institute.

The site brings together dozens of datasets (from ClimateWatch, GCB, PIK, UNFCCC, etc.) to let users analyze and compare the Nationally Determined Contributions under the Paris Agreement, access historical emissions data, discover how countries can leverage their climate goals to achieve their sustainable development objectives, and use models to map new pathways.

The last update was in April 2026, resulting in 57 tables years ranging from 1990-2023.

= Tables in IFs =
{| class="wikitable"
|+
!Variable
!Definition
!UsedInPreprocessor
|-
|EmissionsCH4AgricultureCW
|CH4 emissions for the agriculture sector
|0
|-
|EmissionsCH4BuildingCW
|CH4 emissions for the building sector
|0
|-
|EmissionsCH4BunkerFuelsCW
|CH4 emissions for the bunker fuels sector
|0
|-
|EmissionsCH4ElectHeatCW
|CH4 emissions for the electricity/heat sector
|0
|-
|EmissionsCH4EnergyCW
|CH4 emissions for the energy sector
|0
|-
|EmissionsCH4FugitEmissionCW
|CH4 emissions for the fugitive emission sector
|0
|-
|EmissionsCH4IndProcessCW
|CH4 emissions for the industrial process sector
|0
|-
|EmissionsCH4LandUseCW
|CH4 emissions for the land-use and forestry sector
|0
|-
|EmissionsCH4ManuConstrCW
|CH4 emissions for the manufacturing/construction sector
|0
|-
|EmissionsCH4OtherFuelCW
|CH4 emissions for the other fuel combustion sector
|0
|-
|EmissionsCH4TransportationCW
|CH4 emissions for the transportation sector
|0
|-
|EmissionsCH4WasteCW
|CH4 emissions for the waste sector
|0
|-
|EmissionsCO2BuildingCW
|CO2 emissions for the building sector
|0
|-
|EmissionsCO2BunkerFuelsCW
|CO2 emissions for the bunker fuels sector
|0
|-
|EmissionsCO2ElectHeatCW
|CO2 emissions for the electricity/heat sector
|0
|-
|EmissionsCO2EnergyCW
|CO2 emissions for the energy sector
|0
|-
|EmissionsCO2FugitEmissionCW
|CO2 emissions for the fugitive emission sector
|0
|-
|EmissionsCO2IndProcessCW
|CO2 emissions for the industrial process sector
|0
|-
|EmissionsCO2LandUseCW
|CO2 emissions for the land-use and forestry sector
|0
|-
|EmissionsCO2ManuConstrCW
|CO2 emissions for the manufacturing/construction sector
|0
|-
|EmissionsCO2OtherFuelCW
|CO2 emissions for the other fuel combustion sector
|0
|-
|EmissionsCO2TotCW
|CO2 emissions for the Tot excluding LUCF sector
|0
|-
|EmissionsCO2WithLUCFCW
|CO2 emissions for the Tot including LUCF sector
|0
|-
|EmissionsFgasTotCW
|F gas emissions for the Tot excluding LUCF sector
|0
|-
|EmissionsFgasWithLUCFCW
|F gas emissions for the Tot including LUCF sector
|0
|-
|EmissionsN2OTotCW
|N2O emissions for the Tot excluding LUCF sector
|0
|-
|EmissionsN2OWithLUCFCW
|N2O emissions for the Tot including LUCF sector
|0
|-
|EmissionsTotGHGTotCW
|Tot GHG emissions for the Tot excluding LUCF sector
|0
|-
|EmissionsTotGHGWithLUCFCW
|Tot GHG emissions for the Tot including LUCF sector
|0
|-
|EmissionsCH4TotCW
|CH4 emissions for the Tot excluding LUCF sector
|0
|-
|EmissionsCH4WithLUCFCW
|CH4 emissions for the Tot including LUCF sector
|0
|-
|EmissionsCO2TransportationCW
|CO2 emissions for the transportation sector
|0
|-
|EmissionsFgasIndProcessCW
|F gas emissions for the industrial process sector
|0
|-
|EmissionsN2OAgricultureCW
|N2O emissions for the agriculture sector
|0
|-
|EmissionsN2OBuildingCW
|N2O emissions for the building sector
|0
|-
|EmissionsN2OBunkerFuelsCW
|N2O emissions for the bunker fuels sector
|0
|-
|EmissionsN2OElectHeatCW
|N2O emissions for the electricity/heat sector
|0
|-
|EmissionsN2OEnergyCW
|N2O emissions for the energy sector
|0
|-
|EmissionsN2OFugitEmissionCW
|N2O emissions for the fugitive emission sector
|0
|-
|EmissionsN2OIndProcessCW
|N2O emissions for the industrial process sector
|0
|-
|EmissionsN2OLandUseCW
|N2O emissions for the land-use and forestry sector
|0
|-
|EmissionsN2OManuConstrCW
|N2O emissions for the manufacturing/construction sector
|0
|-
|EmissionsN2OOtherFuelCW
|N2O emissions for the other fuel combustion sector
|0
|-
|EmissionsN2OTransportationCW
|N2O emissions for the transportation sector
|0
|-
|EmissionsN2OWasteCW
|N2O emissions for the waste sector
|0
|-
|EmissionsTotGHGAgricultureCW
|Tot GHG emissions for agriculture
|0
|-
|EmissionsTotGHGBuildingCW
|Tot GHG emissions for the building sector
|0
|-
|EmissionsTotGHGBunkerFuelsCW
|Tot GHG emissions for the bunker fuels sector
|0
|-
|EmissionsTotGHGElectHeatCW
|Tot GHG emissions for the electricity/heat sector
|0
|-
|EmissionsTotGHGEnergyCW
|Tot GHG emissions for the energy sector
|0
|-
|EmissionsTotGHGFugitEmissionCW
|Tot GHG emissions for the fugitive emission sector
|0
|-
|EmissionsTotGHGIndProcessCW
|Tot GHG emissions for the industrial process sector
|0
|-
|EmissionsTotGHGLandUseCW
|Tot GHG emissions for the land-use and forestry sector
|0
|-
|EmissionsTotGHGManuConstrCW
|Tot GHG emissions for the manufacturing/construction sector
|0
|-
|EmissionsTotGHGOtherFuelCW
|Tot GHG emissions for the other fuel combustion sector
|0
|-
|EmissionsTotGHGTransportationCW
|Tot GHG emissions for the transportation sector
|0
|-
|EmissionsTotGHGWasteCW
|Tot GHG emissions for the waste sector
|0
|}

= Data Pulling Instructions =

# Navigate to the [https://www.climatewatchdata.org/data-explorer/historical-emissions?historical-emissions-data-sources=gcp&historical-emissions-gases=co2&historical-emissions-regions=&historical-emissions-sectors=total-fossil-fuels-and-cement&page=1 ClimateWatch Data Explorer]
# This data explorer allows you to filter data sources, sectors, gases, years, and regions. You can visualize this data in a graph or there is an option to download All Data which is what RAs will use when updating these series. [[File:CW Bulk Data.png|none|thumb|600x600px]]
# Downloaded file: [[File:CW Zipped Files.png|none|thumb|600x600px]]
# Once the zip file is downloaded, extract, and open the folders "ClimateWatch_HistoricalEmissions" and under this folder open "CW_HistoricalEmissions_ClimateWatch.csv"
## The csv files only give the Country Code so it is imperative that the country codes match the right country when importing into IFs
# For country codes open the folder "Climate Watch_NDC_Content" and open the "CW_NDC_data_highlevel.csv" file. Use the first two columns (Country and ISO) to build the country concordance for the "CW_HistoricalEmissions_ClimateWatch.csv" data.
# For each series filter the "Sector" and "Gas" for each table. There should be here should be 57 tables in total.

= Data Notes =
# Building the country concordance is an important step! The ISO code and FIPS code are different and data will be missing if you do not build your country concordance with the first two columns.
## Example COD is Congo, Dem. Republic of the in Climate Watch but in IFs with FIPS it is ZAR

International Centre for Tax & Development (ICTD)

2026-03-25T18:21:57Z

Norah.Shamin: /* Tables In IFs */

= Summary =
The International Centre for Tax & Development (ICTD) is an independent research center focused on improving tax policy and administration in lower-income countries.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!LastIFsUpdate
!Name In Source
!UsedInPreprocessor
|-
|GovRevGenGrants%GDPICTD
|Grants, General Government, % of GDP
|2/22/2022
|Grants
|0
|-
|GovRevGenNonTax%GDPICTD
|General government non-tax revenue
|2/22/2022
|Tot Non Tax
|0
|-
|GovRevGenProperty%GDPICTD
|Property taxes, General Government, % of GDP
|2/22/2022
|Taxes on property
|0
|-
|GovRevGenSocSec%GDPICTD
|Social Contributions, General Government, % of GDP
|2/22/2022
|Social contributions
|0
|-
|GovRevGenTaxDirect%GDPICTD
|General government direct tax revenue % of GDP
|2/22/2022
|Direct
|0
|-
|GovRevGenTaxGoodSer%GDPICTD
|General government total goods and service tax revenue % of GDP
|2/22/2022
|GS
|0
|-
|GovRevGenTaxICorporate%GDPICTD
|General government total Corporate tax revenue % of GDP
|2/22/2022
|Corp
|0
|-
|GovRevGenTaxIncome%GDPICTD
|General government total income tax revenue % of GDP
|2/22/2022
|Income
|0
|-
|GovRevGenTaxIndirect%GDPICTD
|General government total indirect tax revenue % of GDP
|2/22/2022
|Indirect
|0
|-
|GovRevGenTaxIndividual%GDPICTD
|General government total Individual tax revenue % of GDP
|2/22/2022
|Individual
|0
|-
|GovRevGenTaxTot%GDPICTD
|Total Tax Revenue General government
|2/22/2022
|Tot Tax
|0
|-
|GovRevGenTaxTrade%GDPICTD
|General government total trade tax revenue % of GDP
|2/22/2022
|Trade
|0
|-
|GovtCalcRevTot%GDPICTD
|Revenue, government, total, as % of GDP
|2/22/2022
|
|0
|-
|GovtCurRev%GDPICTD
|Current government revenue as % of GDP
|2022/01/31
|Total Revenue
|0
|-
|GovtRevCenNonTaxTot%GDPICTD
|Central government total non tax revenue % of GDP
|2022/01/31
|Non Tax Revenue
|0
|-
|GovtRevCenTaxDirect%GDPICTD
|Central government total direct tax revenue % of GDP
|2022/01/31
|Total Direct Taxes
|0
|-
|GovtRevCenTaxGoodSer%GDPICTD
|Central government total goods and service tax revenue % of GDP
|2022/01/31
|Taxes on Goods and Services
|0
|-
|GovtRevCenTaxICorporate%GDPICTD
|Central government total corporate tax revenue % of GDP
|2022/01/31
|Taxes on Income, Profits & Capital Gains, o/w CIT, Total
|0
|-
|GovtRevCenTaxIncome%GDPICTD
|Central government total income tax revenue % of GDP
|2022/01/31
|Total Taxes on Income, Profits, Capital Gains
|0
|-
|GovtRevCenTaxIndirect%GDPICTD
|Central government total indirect tax revenue % of GDP
|2022/01/31
|Indirect Taxes
|0
|-
|GovtRevCenTaxIndividual%GDPICTD
|Central government total individual tax revenue % of GDP
|2022/01/31
|Individual Taxes
|0
|-
|GovtRevCenTaxTot%GDPICTD
|Central government total tax revenue % of GDP
|2022/02/01
|Taxes Including SC
|0
|-
|GovtRevCenTaxTrade%GDPICTD
|Central government total trade tax revenue % of GDP
|2022/01/31
|Taxes on International Trade, Total
|0
|}

= Data Pulling Instructions =

#Go to https://www.ictd.ac/dataset/
#Choose the dataset for the table
##For example revenue tables will be in The Government Revenue Dataset
#Download the set

= Data Notes =

United Nation SDG Indicators Global Database (UNSDG)

2026-03-11T19:01:21Z

Norah.Shamin: /* Tables In IFs */

United Nation SDG Indicators Global Database (UNSDG)

2026-03-11T18:54:22Z

Norah.Shamin: /* Tables In IFs */

= Summary =
SDG Global Database gives you access to data on more than 210 SDG indicators for countries, areas or regions across the globe.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Ext Source Def
!Years
!Last IFs Update
!Name in Source
!Code in Source
|-
|AidDonEdScholar
|Gross disbursements of total ODA from all donors for scholarships
|SDG 4.b.1 Volume of official development assistance flows for scholarships by sector and type of study
|2006-2023
|2026/03/11
|Total official flows for scholarships, by recipient
|DC_TOF_SCHIPSL
|-
|AidHealthcareGross
|Gross disbursements of total ODA from all donors to medical research and basic health sectors
|SDG 3.b.2 Total gross official development assistance to medical research and basic health sectors
|2000-2023
|2026/03/11
|Total gross official disbursements for medical research and basic heath sectors, by recipient
|DC_TOF_HLTHL
|-
|AidHealthcareNet
|Net disbursements of total ODA from all donors to medical research and basic health sectors
|SDG 3.b.2 Total net official development assistance to medical research and basic health sectors
|2010-2023
|2026/03/11
|Total net official disbursements for medical research and basic heath sectors, by recipient
|DC_TOF_HLTHNT
|-
|AidTotFlowsAgSector
|Total official flows (official development assistance plus other official flows) to the agriculture sector
|SDG 2.a.2 Total official flows (official development assistance plus other official flows) to the agriculture sector
|2000-2023
|2026/03/11
|Total official flows to the agriculture sector
|DC_TOF_AGRL
|-
|AidTotalInfrastructure
|Aid received for Infrastructure, total (energy, ICT, water and sanitation and roads)
|SDG 9.a.1 - Total official international support (official development assistance plus other official flows) to infrastructure
|2000-2023
|2026/03/11
|Total official flows for infrastructure, by recipient
|DC_TOF_INFRAL
|-
|AidWaterSanitation
|Amount of water and sanitation-related official development assistance that is part of a governmen tcoordinated spending plan
|SDG 6.a.1 Amount of water- and sanitation- related official development assistance that is part of a government-coordinated spending plan
|2000-2023
|2026/03/11
|Total official flows for water supply and sanitation, by recipient
|DC_TOF_WASHL
|-
|AidforTradeCommitDonor
|The gross commitments of total Official Development Assistance (ODA) from all donors for aid for trade
|SDG 8.a.1 - Aid for Trade commitments and disbursements
|2006-2023
|2026/03/11
|Total official flows commitments for Aid for Trade, by donor
|DC_TOF_TRDCMDL
|-
|AidforTradeCommitRecipient
|The gross commitments of total Official Development Assistance (ODA) from all recipients for aid for trade
|SDG 8.a.1 - Aid for Trade commitments and disbursements
|2006-2023
|2026/03/11
|Total official flows commitments for Aid for Trade, by recipient
|DC_TOF_TRDDBML
|-
|AidforTradeDisburseDonor
|The gross disbursements of total Official Development Assistance (ODA) from all donors for aid for trade
|SDG 8.a.1 - Aid for Trade commitments and disbursements
|2006-2023
|2026/03/11
|Total official flows disbursed for Aid for Trade, by donor
|DC_TOF_TRDDBMDL
|-
|AidforTradeDisburseRecipient
|The gross disbursements of total Official Development Assistance (ODA) from all recipients for aid for trade
|SDG 8.a.1 - Aid for Trade commitments and disbursements
|2006-2023
|2026/03/11
|Total official flows disbursed for Aid for Trade, by recipient
|DC_TOF_TRDCML
|-
|AidtoDevelopingCountriesUSD
|Dollar value of financial and technical assistance (including through North-South, South-South and triangular cooperation) committed to developing countries
|SDG 17.9.1 Dollar value of financial and technical assistance (including through North-South, South-South and triangular cooperation) committed to developing countries
|2000-2023
|2026/03/11
|Dollar value of financial and technical assistance committed to developing countries
|DC_FTA_TOTAL
|-
|BankATMTotl
|The number of automated teller machines (ATMs) per 100,000 adults
|SDG 8.10.1 - (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adults
|2004-2023
|2026/03/11
|Number of automated teller machines (ATMs) per 100,000 adults
|FB_ATM_TOTL
|-
|BankActAdult%
|The percentage of adults (ages 15+) who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or personally using a mobile money service in the past 12 months
|SDG 8.10.2 - Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service provider
|2011-2022
|2026/03/11
|Number of commerical bank branches per 100,000 adults
|FB_BNK_ACCSS
|-
|BankBranchTotl
|The number of commerical bank branches per 100,000 adults
|SDG 8.10.1 - (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adults
|2004-2023
|2026/03/11
|Number of commerical bank branches per 100,000 adults
|FB_CBK_BRCH
|-
|BirthsRegisteredUnder5%
|Proportion of children under 5 years of age whose births have been registered with a civil authority
|SDG 16.9.1 Proportion of children under 5 years of age whose births have been registered with a civil authority, by age
|2006-2024
|2026/03/11
|Proportion of children under 5 years of age whose births have been registered with a civil authority
|SG_REG_BRTH
|-
|ComplianceParisPrinc
|The compliance of existing national human rights institutions with the Principlesrelating to the Status of National Institutions
|SDG 16.a.1: Existence of independent national human rights institutions in compliance with theParis Principles
|2000-2024
|2026/03/11
|Existence ofindependent national human rights institutions in compliance with theParis Principles
|SG_NHR_IMPL
|-
|EdPrePriOrgLearnFemale%
|Percentage of female pre-primary children who participate in one or more organized learning programme, including programmes which offer a combination of education and care
|SDG 4.2.2 Participation rate in organized learning (one year before the official primary entry age), by sex
|2000-2025
|2026/03/11
|Participation rate in organized learning (one year before the official primary entry age) [Female]
|SE_PRE_PARTN
|-
|EdPrePriOrgLearnMale%
|Percentage of male pre-primary children who participate in one or more organized learning programme, including programmes which offer a combination of education and care
|SDG 4.2.2 Participation rate in organized learning (one year before the official primary entry age), by sex
|2000-2025
|2026/03/11
|Participation rate in organized learning (one year before the official primary entry age) [Male]
|SE_PRE_PARTN
|-
|EdPrePriOrgLearnTotal%
|Percentage of all pre-primary children who participate in one or more organized learning programme, including programmes which offer a combination of education and care
|SDG 4.2.2 Participation rate in organized learning (one year before the official primary entry age), by sex
|2000-2025
|2026/03/11
|Participation rate in organized learning (one year before the official primary entry age) [Total]
|SE_PRE_PARTN
|-
|EdPrePriTeachTrainFemale%
|Percentage of female pre-primary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have at least the minimum organized teacher training for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in pre-primary education with training [Female]
|SE_TRA_GRDL
|-
|EdPrePriTeachTrainMale%
|Percentage of male pre-primary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have at least the minimum organized teacher training for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in pre-primary education with training [Male]
|SE_TRA_GRDL
|-
|EdPrePriTeachTrainTotal%
|Percentage of all pre-primary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have at least the minimum organized teacher training for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in pre-primary education with training [Both Sexes]
|SE_TRA_GRDL
|-
|EdPriTeachTrainFemale%
|Percentage of female primary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have at least the minimum organized teacher training for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in primary education with training [Female]
|SE_TRA_GRDL
|-
|EdPriTeachTrainMale%
|Percentage of male primary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have at least the minimum organized teacher training for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in primary education with training [Male]
|SE_TRA_GRDL
|-
|EdPriTeachTrainTotal%
|Percentage of all primary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have at least the minimum organized teacher training for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in primary education with training [Both Sexes]
|SE_TRA_GRDL
|-
|EdSecLowerTeachTrainFemale%
|Percentage of female lower secondary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have at least the minimum organized teacher training for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in lower secondary education with training [Female]
|SE_TRA_GRDL
|-
|EdSecLowerTeachTrainMale%
|Percentage of male lower secondary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have received at least the minimum organized teacher training for teaching (e.g. pedagogical training) pre-service or in-service for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in lower secondary education with training [Male]
|SE_TRA_GRDL
|-
|EdSecLowerTeachTrainTotal%
|Percentage of all lower secondary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have received at least the minimum organized teacher training for teaching (e.g. pedagogical training) pre-service or in-service for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in lower secondary education with training [Both Sexes]
|SE_TRA_GRDL
|-
|EdSecUpperTeachTrainFemale%
|Percentage of female upper secondary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have received at least the minimum organized teacher training for teaching (e.g. pedagogical training) pre-service or in-service for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in upper secondary with training [Female]
|SE_TRA_GRDL
|-
|EdSecUpperTeachTrainMale%
|Percentage of male upper secondary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have received at least the minimum organized teacher training for teaching (e.g. pedagogical training) pre-service or in-service for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in upper secondary with training [Male]
|SE_TRA_GRDL
|-
|EdSecUpperTeachTrainTotal%
|Percentage of all upper secondary teachers who have received at least the minimum organized pedagogical training required by the country to teach at that level
|SDG 4.c.1 Proportion of teachers who have received at least the minimum organized teacher training for teaching (e.g. pedagogical training) pre-service or in-service for teaching at the relevant level in a given country
|2000-2025
|2026/03/11
|Proportion of teachers in upper secondary with training [Both Sexes]
|SE_TRA_GRDL
|-
|EnvBiodiversityAssistanceDonor
|Total official development assistance for biodiversity, by donor
|SDG 15.a.1 Official development assistance and public expenditure on conservation and sustainable use of biodiversity and ecosystems
|2002-2023
|2026/03/11
|Total official development assistance for biodiversity, by donor
|DC_ODA_BDVDL
|-
|EnvBiodiversityAssistanceRecipient
|Total official development assistance for biodiversity, by recipient
|SDG 15.a.1 Official development assistance and public expenditure on conservation and sustainable use of biodiversity and ecosystems
|2002-2023
|2026/03/11
|Total official development assistance for biodiversity, by donor
|DC_ODA_BDVL
|-
|EnvFuelClean%
|Percentage of population with primary reliance on clean fuels and technology
|SDG 7.1.2 Proportion of population with primary reliance on clean fuels and technology
|2000-2023
|2026/03/11
|Proportion of population with primary reliance on clean fuels and technology
|EG_EGY_CLEAN
|-
|EnvOrgCountryParticBasel%
|Compliance with the Basel Convention on hazardous waste and other chemicals
|SDG 12.4.1 Number of parties to international multilateral environmental agreements on hazardous waste, and other chemicals that meet their commitments and obligations in transmitting information as required by each relevant agreement"
|
|2026/03/11
|
|
|-
|EnvOrgCountryParticMontreal%
|Compliance with the Montreal Protocol on hazardous waste and other chemicals
|SDG 12.4.1 Number of parties to international multilateral environmental agreements on hazardous waste, and other chemicals that meet their commitments and obligations in transmitting information as required by each relevant agreement"
|
|2026/03/11
|
|
|-
|EnvOrgCountryParticRotterdam%
|Compliance with the Rotterdam Convention on hazardous waste and other chemicals
|SDG 12.4.1 Number of parties to international multilateral environmental agreements on hazardous waste, and other chemicals that meet their commitments and obligations in transmitting information as required by each relevant agreement"
|2015-2025
|2026/03/11
|Compliance with the Rotterdam Convention on hazardous waste and other chemicals
|SG_HAZ_CMRROTDAM
|-
|EnvOrgCountryParticStockholm%
|Compliance with the Stockholm Convention on hazardous waste and other chemicals
|SDG 12.4.1 Number of parties to international multilateral environmental agreements on hazardous waste, and other chemicals that meet their commitments and obligations in transmitting information as required by each relevant agreement"
|2015-2025
|2026/03/11
|Compliance with the Stockholm Convention on hazardous waste and other chemicals
|SG_HAZ_CMRSTHOLM
|-
|GDPEmpPersGrowthRate%
|Annual growth rate of real GDP per employed person conveys the annual percentage change in real Gross Domestic Product per employed person.
|SDG 8.2.1 Annual growth rate of real GDP per employed person
|2000-2024
|2026/03/11
|Annual growth rate of real GDP per employed person
|SL_EMP_PCAP
|-
|HealthConAlcohol
|Harmful use of alcohol, defined according to the national context as alcohol per capita consumption (aged 15 years and older) within a calendar year in litres of pure alcohol
|SDG 3.5.2 Harmful use of alcohol, defined according to the national context as alcohol per capita consumption (aged 15 years and older) within a calendar year in litres of pure alcohol
|2000-2022
|2026/03/11
|Harmful use of alcohol, defined as alcohol per capita consumption in litres of pure alcohol
|SH_ALC_CONSPT
|-
|HealthFGMFemale15to49%
|The proportion of girls and women aged 15-49 years who have undergone female genital mutilation/cutting
|SDG 5.3.1 Proportion of women aged 20-24 years who were married or in a union before age 15 and before age 18
|2004-2023
|2026/03/11
|Proportion of girls who have undergone FGM/C [15 to 49]
|SH_STA_FGMS
|-
|HealthGBVFemale15to49%
|Percentage of ever-partnered women and girls aged 15-49 years who have experienced physical, sexual or psychological violence by a current or former intimate partner, in the previous 12 months
|SDG 5.2.1 Proportion of ever-partnered women and girls aged 15 years and older subjected to physical, sexual or psychological violence by a current or former intimate partner in the previous 12 months, by form of violence and by age
|2018-2018
|2026/03/11
|Proportion of women and girls subjected to violence by a partner in the last 12 months [15 to 49]
|VC_VAW_MARR
|-
|HealthMortAirPollutionAmbi
|Crude death rate attributed to ambient air pollution
|SDG 3.9.1 Mortality rate attributed to ambient air pollution
|2019-2019
|2026/03/11
|Crude death rate attributed to ambient air pollution
|SH_AAP_ASMORT
|-
|HealthMortAirPollutionHouse
|Crude death rate attributed to household air pollution
|SDG 3.9.1 Mortality rate attributed to household and pollution
|2019-2019
|2026/03/11
|Crude death rate attributed to household air pollution
|SH_HAP_ASMORT
|-
|HealthOccInjuriesFatFemale
|The frequency rates of fatal occupational injuries among female employees
|SDG 8.8.1 Frequency rates of fatal and non- fatal occupational injuries, by sex and migrat status
|2000-2023
|2026/03/11
|Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status"
|SL_EMP_FTLINJUR
|-
|HealthOccInjuriesFatMale
|The frequency rates of fatal occupational injuries among male employees
|SDG 8.8.1 Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|2000-2023
|2026/03/11
|Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|SL_EMP_FTLINJUR
|-
|HealthOccInjuriesFatTotal
|The frequency rates of non-fatal occupational injuries among female employees
|SDG 8.8.1 Frequency rates of fatal and non- fatal occupational injuries, by sex and migran status
|2000-2023
|2026/03/11
|Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status"
|SL_EMP_INJUR
|-
|HealthOccInjuriesNonFatFemale
|The frequency rates of fatal occupational injuries among total employees
|SDG 8.8.1 Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|2000-2023
|2026/03/11
|Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|SL_EMP_INJUR
|-
|HealthOccInjuriesNonFatMale
|The frequency rates of non-fatal occupational injuries among total employees
|SDG 8.8.1 Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|2000-2023
|2026/03/11
|Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|SL_EMP_INJUR
|-
|HealthOccInjuriesNonFatTotal
|The frequency rates of non-fatal occupational injuries among female employees
|SDG 8.8.1 Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|2000-2023
|2026/03/11
|Frequency rates of fatal and non- fatal occupational injuries, by sex and migrant status
|SL_EMP_FTLINJUR
|-
|HealthWrkrDensDentistry
|Number of dentists, dental technician/assistants and related occupation personnel per 1,000 population
|SDG 3.c.1 Health worker density and distribution
|2000-2023
|2026/03/11
|Health worker density of dentistry personnel per 1,000 population
|SH_MED_DEN
|-
|HealthWrkrDensNurseMW
|Number of nursing and midwifery personnel per 1,000 population
|SDG 3.c.1 Health worker density and distribution
|2000-2023
|2026/03/11
|Health worker density of nursing and midwifery personnel per 1,000 population
|SH_MED_DEN
|-
|HealthWrkrDensPharma
|Number of pharmacists, pharmaceutical technicians/assistants and related occupation personnel per 1,000 population
|SDG 3.c.1 Health worker density and distribution
|2000-2023
|2026/03/11
|Health worker density of pharmaceutrical personnel per 1,000 population
|SH_MED_DEN
|-
|HealthWrkrDensPhysician
|Number of physicians, including generalists and specialist medical practitioners per 1,000 population
|SDG 3.c.1 Health worker density and distribution
|2000-2023
|2026/03/11
|Health worker density of physicians per 1,000 population
|SH_MED_DEN
|-
|HealthcareTropDiseaseIntervention
|Number of people requiring interventions against neglected tropical diseases
|SDG 3.3.5 Number of people requiring interventions against neglected tropical diseases
|2010-2023
|2026/03/11
|Number of people requiring interventions against neglected tropical diseases
|SH_TRP_INTVN
|-
|ICTTelephoneMobileCov2g%
|Proportion of population covered by a mobile network, by technology
|SDG 9.c.1 Proportion of population covered by a mobile network, by technology
|2000-2023
|2026/03/11
|Proportion of population covered by a mobile network, 2g
|IT_MOB_2GNTWK
|-
|ICTTelephoneMobileCov3g%
|Proportion of population covered by a mobile network, 3g
|SDG 9.c.1 Proportion of population covered by a mobile network, by technology
|2007-2023
|2026/03/11
|Proportion of population covered by a mobile network, 3g
|IT_MOB_3GNTWK
|-
|ICTTelephoneMobileCov4g%
|Proportion of population covered by a mobile network, 4g
|SDG 9.c.1 Proportion of population covered by a mobile network, by technology
|2012-2023
|2026/03/11
|Proportion of population covered by a mobile network, 4g
|IT_MOB_4GNTWK
|-
|ICTTelephoneMobileOwnFemale%
|The proportion of females who own a mobile telephone
|SDG 5.b.1 Proportion of individuals who own a mobile telephone, by sex
|2013-2024
|2026/03/11
|Proportion of individuals who own a mobile telephone [Female]
|IT_MOB_OWN
|-
|ICTTelephoneMobileOwnMale%
|The proportion of males who own a mobile telephone
|SDG 5.b.1 Proportion of individuals who own a mobile telephone, by sex
|2013-2024
|2026/03/11
|Proportion of individuals who own a mobile telephone [Male]
|IT_MOB_OWN
|-
|ICTTelephoneMobileOwnTotal%
|The proportion of individuals who own a mobile telephone
|SDG 5.b.1 Proportion of individuals who own a mobile telephone, by sex
|2013-2024
|2026/03/11
|Proportion of individuals who own a mobile telephone [Both sexes]
|IT_MOB_OWN
|-
|IncBelow1D90c%Working15+Female
|Percentage of females 15 and older living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [15 and over Female]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working15+Male
|Percentage of males 15 and older living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [15 and over Male]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working15+Total
|Percentage of people 15 and older living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2022
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [15 and over Total]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working15to24Female
|Percentage of female 15 to 24 year olds living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [15 to 24 Female]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working15to24Male
|Percentage of male 15 to 24 year olds living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [15 to 24 Male]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working15to24Total
|Percentage of all 15 to 24 year olds living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [15 to 24 Total]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working25+Female
|Percentage of females 25 and older living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [25 and over Female]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working25+Male
|Percentage of males 25 and older living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [25 and over Male]
|SI_POV_EMP1
|-
|IncBelow1D90c%Working25+Total
|Percentage of people 25 and older living on less than $1.90 a day at 2011 international prices
|SDG 1.1.1 Proportion of population below the international poverty line, by sex, age, employment status and geographical location (urban/rural)
|2000-2019
|2026/03/11
|Proportion of employed population below the poverty line of US$1.90 per day [25 and over Total]
|SI_POV_EMP1
|-
|IncNatlPovertyTotal
|Proportion of population living below the national poverty line, by sex and age; Total
|SDG 1.2.1 Proportion of total population living below the national poverty line, by sex and age
|2000-2024
|2026/03/11
|Proportion of total population living below the national poverty line
|SI_POV_NAHC
|-
|IncNatlPovertyUrban
|Proportion of population living below the national poverty line, by sex and age; Urban
|SDG 1.2.1 Proportion of urban population living below the national poverty line, by sex and age
|2016-2023
|2026/03/11
|Proportion of urban population living below the national poverty line
|SI_POV_NAHC
|-
|IncomepercapitaGrowthLo40%
|Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population
|SDG 10.1.1 Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population and the total population
|2010-2024
|2026/03/11
|Growth rates of household expenditure or income per capita among the bottom 40 per cent of pop
|SI_HEI_TOTL
|-
|IncomepercapitaGrowthTotal%
|Total growth rates of household expenditure or income per capita
|SDG 10.1.1 Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population and the total population
|2010-2024
|2026/03/11
|Growth rates of household expenditure or income per capita among the bottom 40 per cent of pop
|SI_HEI_TOTL
|-
|LaborChild%
|The number of children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|2010-2023
|2026/03/11
|Proportion of children aged 5-17 years engaged in labour (both sexes or no breakdown by sex)
|SL_TLF_CHLDEA
|-
|LaborChildFemale%
|The number of female children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|2010-2023
|2026/03/11
|Proportion of children aged 5-17 years engaged in labour (Female)
|SL_TLF_CHLDEA
|-
|LaborChildMale%
|The number of male children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|2010-2023
|2026/03/11
|Proportion of children aged 5-17 years engaged in labour (Male)
|SL_TLF_CHLDEA
|-
|LaborUnemployedFemale15AndOver%
|Percentage of the female labor force that is 15 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Female - 15 years old and over]
|SL_TLF_UEM
|-
|LaborUnemployedFemale15to24%
|Percentage of the female labor force that is 15 to 24 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Female - 15 to 24]
|SL_TLF_UEM
|-
|LaborUnemployedFemale25AndOver%
|Percentage of the female labor force that is 25 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Female - 25 years old and over]
|SL_TLF_UEM
|-
|LaborUnemployedMale15AndOver%
|Percentage of the male labor force that is 15 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Male - 15 years old and over]
|SL_TLF_UEM
|-
|LaborUnemployedMale15to24%
|Percentage of the male labor force that is 15 to 24 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Male - 15 to 24]
|SL_TLF_UEM
|-
|LaborUnemployedMale25AndOver%
|Percentage of the male labor force that is over 25 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Male - 25 years old and over]
|SL_TLF_UEM
|-
|LaborUnemployedTotal15AndOver%
|Percentage of the total labor force that is 15 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Both sexes - 15 years old and over]
|SL_TLF_UEM
|-
|LaborUnemployedTotal15to24%
|Percentage of the total labor force that is 15 to 24 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Both sexes - 15 to 24]
|SL_TLF_UEM
|-
|LaborUnemployedTotal25AndOver%
|Percentage of the total labor force that is 25 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|2000-2024
|2026/03/11
|Unemployment rate [Both sexes - 25 years old and over]
|SL_TLF_UEM
|-
|LaborUnpdCareFemale%
|Average time women spend on household provision of care services (e.g. childcare and care of sick, elderly, or disabled household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|2000-2024
|2026/03/11
|Proportion of time spent on unpaid care work [Female]
|SL_DOM_TSPDCW
|-
|LaborUnpdCareMale%
|Average time men spend on household provision of care services (e.g. childcare and care of sick, elderly, or disabled household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|2000-2024
|2026/03/11
|Proportion of time spent on unpaid care work [Male]
|SL_DOM_TSPDCW
|-
|LaborUnpdDomCareFemale%
|Average time women spend on provision of services for household consumption (e.g. food preparation, dishwashing, cleaning, childcare, and care of sick or elderly household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|2000-2024
|2026/03/11
|Proportion of time spent on unpaid domestic and care work [Female]
|SL_DOM_TSPD
|-
|LaborUnpdDomCareMale%
|Average time men spend on provision of services for household consumption (e.g. food preparation, dishwashing, cleaning, childcare, and care of sick or elderly household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|2000-2024
|2026/03/11
|Proportion of time spent on unpaid domestic and care work [Male]
|SL_DOM_TSPD
|-
|LaborUnpdDomFemale%
|Average time women spend on provision of non-care-related services for household consumption (e.g. food preparation, dishwashing, cleaning, and shopping)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|2000-2024
|2026/03/11
|Proportion of time spent on unpaid domestic chores [Female]
|SL_DOM_TSPDDC
|-
|LaborUnpdDomMale%
|Average time men spend on provision of non-care-related services for household consumption (e.g. food preparation, dishwashing, cleaning, and shopping)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|2000-2024
|2026/03/11
|Proportion of time spent on unpaid domestic chores [Male]
|SL_DOM_TSPDDC
|-
|LaborYouthInactive%
|Proportion of youth not in education, employment or training (NEET), as a percentage of the total youth population
|SDG 8.6.1 Proportion of youth (aged 15-24 years) not in education, employment or training
|2000-2024
|2026/03/11
|Proportion of youth (aged 15-24 years) not in education, employment or training
|SL_TLF_NEET
|-
|LaborYouthInactiveFemale%
|Proportion of young females not in education, employment or training (NEET), as a percentage of the total youth population
|SDG 8.6.1 Proportion of youth (aged 15-24 years) not in education, employment or training
|2000-2024
|2026/03/11
|Proportion of youth (aged 15-24 years) not in education, employment or training
|SL_TLF_NEET
|-
|LaborYouthInactiveMale%
|Proportion of young males not in education, employment or training (NEET), as a percentage of the total youth population
|SDG 8.6.1 Proportion of youth (aged 15-24 years) not in education, employment or training
|2000-2024
|2026/03/11
|Proportion of youth (aged 15-24 years) not in education, employment or training
|SL_TLF_NEET
|-
|PopFoodInsecFemale%FIES
|Proportion of the female population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|2015-2023
|2026/03/11
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent Female]
|AG_PRD_FIESMS
|-
|PopFoodInsecMale%FIES
|Proportion of the male population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|2015-2023
|2026/03/11
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent Male]
|AG_PRD_FIESMS
|-
|PopFoodInsecSevFemale%FIES
|Proportion of the female population that has experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|2015-2023
|2026/03/11
|Estimated prevalence of severe food insecurity in the population [Total Percent Female]
|AG_PRD_FIESS
|-
|PopFoodInsecSevMale%FIES
|Proportion of the male population that has experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|2015-2023
|2026/03/11
|Estimated prevalence of severe food insecurity in the population [Total Percent Male]
|AG_PRD_FIESS
|-
|PopFoodInsecSevTotalFIES
|Number of people who have experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|2015-2023
|2026/03/11
|Estimated number of population in severe food insecurity [Total Number]
|AG_PRD_FIESSN
|-
|PopFoodInsecTotal%FIES
|Proportion of the population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|2015-2023
|2026/03/11
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent]
|AG_PRD_FIESMS
|-
|PopFoodInsecTotalFIES
|Number of people who have experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|2015-2023
|2026/03/11
|Estimated number of population in moderate or severe food insecurity [Total Number]
|AG_PRD_FIESMSN
|-
|PopMarried15Fem20to24%
|Proportion of women aged 20-24 years who were married or in a union before age 15
|SDG 5.3.2 Proportion of girls and women aged 15-49 years who have undergone female genital mutilation/cutting, by age
|2006-2024
|2026/03/11
|Proportion of women aged 20-24 years who were married by age 15
|SP_DYN_MRBF15
|-
|PopMarried18Fem20to24%
|Proportion of women aged 20-24 years who were married or in a union before age 18
|SDG 5.3.2 Proportion of girls and women aged 15-49 years who have undergone female genital mutilation/cutting, by age
|2006-2024
|2026/03/11
|Proportion of women aged 20-24 years who were married by age 18
|SP_DYN_MRBF18
|-
|PopPrisonersUnsentenced%
|Unsentenced detainees as a proportion of overall prison population
|SDG 16.3.2 Unsentenced detainees as a proportion of overall prison population
|2001-2024
|2026/03/11
|Unsentenced detainees as a proportion of overall prison population
|VC_PRS_UNSNT
|-
|TransRoadFreight
|The sum of the freight volumes reported for the air carriers in terms of metric tonnes of cargo respectively
|SDG 9.1.2 - Passenger and freight volumes, by mode of transport
|2017-2022
|2026/03/11
|Freight volume (tonne kilometres), by road transport
|IS_RDP_FRGVOL
|-
|TransRoadPassengers
|The sum of the passenger reported for the air carriers in terms of number of people respectively
|SDG 9.1.2 - Passenger and freight volumes, by mode of transport
|2017-2022
|2026/03/11
|Passenger volume (passenger kilometres), by road transport
|IS_RDP_PFVOL
|-
|UniHealthCoverageIndex
|Coverage of essential health services (Index)
|SDG 3.8.1 Coverage of essential health services
|2000-2023
|2026/03/11
|Universal health coverage (UHC) service coverage index
|SH_ACS_UNHC_25
|-
|UrbanPopulationSlums%
|The proportion of urban population living in slums, informal settlements or inadequate housing as measured by proportion of urban population living in slums.
|SDG 11.1.1 Proportion of urban population living in slums, informal settlements or inadequate housing
|1999-2024
|2026/03/11
|Proportion of urban population living in slums, informal settlements or inadequate housing
|EN_LND_SLUM
|-
|WomManagerialSenMidUN%
|The proportion of females in the total number of persons employed in senior and middle mangement positions
|SDG 5.5.2 Proportion of women in managerial positions
|2000-2024
|2026/03/11
|Proportion of women in senior and middle managment positions
|IC_GEN_MGTN
|-
|WomManagerialUN%
|The proportion of females in the total number of persons employed in managerial positions
|SDG 5.5.2 Proportion of women in managerial positions
|2000-2024
|2026/03/11
|Proportion of women in managerial positions
|IC_GEN_MGTL
|-
|WomRepHealthDecision15to49%
|Proportion of women aged 15-49 years (married or in union) who make their own decisions on sexual relations, use of contraception, and reproductive healthcare
|SDG 5.6.1 Proportion of women aged 15-49 years who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health care
|2006-2024
|2026/03/11
|Women who make their own informed decisions about sexual and reproductive matters [15 to 49]
|SH_FPL_INFM
|-
|IODvlpngCountryVotingFSB%
|Proportion of voting rights of developing countries in the Financial Stability Board
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the Financial Stability Board
|0
|
|
|-
|IODvlpngCountryVotingIADB%
|Proportion of voting rights of developing countries in the Inter-American Development Bank
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the Inter-American Development Bank
|0
|
|
|-
|IODvlpngCountryVotingIBRD%
|Proportion of voting rights of developing countries in the International Bank for Reconstruction and Development
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Voting rights of developing countries in the International Bank for Reconstruction and Development
|0
|
|
|-
|IODvlpngCountryVotingIFC%
|Proportion of voting rights of developing countries in the International Finance Corporation
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the International Finance Corporation
|0
|
|
|-
|IODvlpngCountryVotingIMF%
|Proportion of voting rights of developing countries in the International Monetary Fund
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the International Monetary Fund
|0
|
|
|-
|IODvlpngCountryVotingUNEcoSoc%
|Proportion of voting rights of developing countries in the UN Economic and Social Council
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the UN Economic and Social Council
|0
|
|
|-
|IODvlpngCountryVotingUNGA%
|Proportion of voting rights of developing countries in the United Nations General Assembly
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the UN General Assembly
|0
|
|
|-
|IODvlpngCountryVotingUNSC%
|Proportion of voting rights of developing countries in the United Nations Security Council
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the United Nations Security Council
|0
|
|
|-
|IODvlpngCountryVotingWTO%
|Proportion of voting rights of developing countries in the World Trade Organization
|SDG 10.6.1 Proportion of members and voting rights of developing countries in international organizations
|Proportion of voting rights of developing countries in the World Trade Organization
|0
|
|
|-
|LaborChild%
|The number of children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|Proportion of children aged 5-17 years engaged in labour (both sexes or no breakdown by sex)
|0
|
|
|-
|LaborChildFemale%
|The number of female children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|Proportion of children aged 5-17 years engaged in labour (Female)
|0
|
|
|-
|LaborChildMale%
|The number of male children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|Proportion of children aged 5-17 years engaged in labour (Male)
|0
|
|
|-
|LaborNumChild
|The number of children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|Number of children aged 5-17 years engaged in labour (both sexes or no breakdown by sex)
|0
|
|
|-
|LaborNumFemale
|The number of female children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|Number of children aged 5-17 years engaged in labour (Female)
|0
|
|
|-
|LaborNumMale
|The number of male children aged 5-17 years who are reported to have been engaged in child labour in the past week divided by the total number of children aged 5-17 in the population
|SDG 8.7.1 - Proportion and number of children aged 5-17 years engaged in child labour, by sex and age
|Number of children aged 5-17 years engaged in labour (Male)
|0
|
|
|-
|LaborUnemployedFemale15AndOver%
|Percentage of the female labor force that is 15 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Female - 15 years old and over]
|0
|
|
|-
|LaborUnemployedFemale15to24%
|Percentage of the female labor force that is 15 to 24 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Female - 15 to 24]
|0
|
|
|-
|LaborUnemployedFemale25AndOver%
|Percentage of the female labor force that is 25 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Female - 25 years old and over]
|0
|
|
|-
|LaborUnemployedMale15AndOver%
|Percentage of the male labor force that is 15 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Male - 15 years old and over]
|0
|
|
|-
|LaborUnemployedMale15to24%
|Percentage of the male labor force that is 15 to 24 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Male - 15 to 24]
|0
|
|
|-
|LaborUnemployedMale25AndOver%
|Percentage of the male labor force that is over 25 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Male - 25 years old and over]
|0
|
|
|-
|LaborUnemployedTotal15AndOver%
|Percentage of the total labor force that is 15 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Both sexes - 15 years old and over]
|0
|
|
|-
|LaborUnemployedTotal15to24%
|Percentage of the total labor force that is 15 to 24 years old and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Both sexes - 15 to 24]
|0
|
|
|-
|LaborUnemployedTotal25AndOver%
|Percentage of the total labor force that is 25 years old and over and unemployed
|SDG 8.5.2 Unemployment rate, by sex, age and persons with disabilities
|Unemployment rate [Both sexes - 25 years old and over]
|0
|
|
|-
|LaborUnpdCareFemale%
|Average time women spend on household provision of care services (e.g. childcare and care of sick, elderly, or disabled household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|Proportion of time spent on unpaid care work [Female]
|0
|
|
|-
|LaborUnpdCareMale%
|Average time men spend on household provision of care services (e.g. childcare and care of sick, elderly, or disabled household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|Proportion of time spent on unpaid care work [Male]
|0
|
|
|-
|LaborUnpdDomCareFemale%
|Average time women spend on provision of services for household consumption (e.g. food preparation, dishwashing, cleaning, childcare, and care of sick or elderly household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|Proportion of time spent on unpaid domestic and care work [Female]
|0
|
|
|-
|LaborUnpdDomCareMale%
|Average time men spend on provision of services for household consumption (e.g. food preparation, dishwashing, cleaning, childcare, and care of sick or elderly household members)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|Proportion of time spent on unpaid domestic and care work [Male]
|0
|
|
|-
|LaborUnpdDomFemale%
|Average time women spend on provision of non-care-related services for household consumption (e.g. food preparation, dishwashing, cleaning, and shopping)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|Proportion of time spent on unpaid domestic chores [Female]
|0
|
|
|-
|LaborUnpdDomMale%
|Average time men spend on provision of non-care-related services for household consumption (e.g. food preparation, dishwashing, cleaning, and shopping)
|SDG 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location
|Proportion of time spent on unpaid domestic chores [Male]
|0
|
|
|-
|LaborYouthInactive%
|Proportion of youth not in education, employment or training (NEET), as a percentage of the total youth population
|SDG 8.6.1 Proportion of youth (aged 15-24 years) not in education, employment or training
|Proportion of youth (aged 15-24 years) not in education, employment or training
|0
|
|
|-
|LaborYouthInactiveFemale%
|Proportion of young females not in education, employment or training (NEET), as a percentage of the total youth population
|SDG 8.6.1 Proportion of youth (aged 15-24 years) not in education, employment or training
|Proportion of youth (aged 15-24 years) not in education, employment or training
|0
|
|
|-
|LaborYouthInactiveMale%
|Proportion of young males not in education, employment or training (NEET), as a percentage of the total youth population
|SDG 8.6.1 Proportion of youth (aged 15-24 years) not in education, employment or training
|Proportion of youth (aged 15-24 years) not in education, employment or training
|0
|
|
|-
|ManufacturingPropEmploy%
|The share of manufacturing employment in total employment
|SDG 9.2.2 - Manufacturing employment as a proportion of total employment
|Manufacturing value added share in GDP at constant 2010 United States dollars
|0
|
|
|-
|PopFoodInsecFemale%FIES
|Proportion of the female population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent Female]
|0
|
|
|-
|PopFoodInsecMale%FIES
|Proportion of the male population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent Male]
|0
|
|
|-
|PopFoodInsecRural%FIES
|Proportion of the rural population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent Rural]
|0
|
|
|-
|PopFoodInsecSevFemale%FIES
|Proportion of the female population that has experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of severe food insecurity in the population [Total Percent Female]
|0
|
|
|-
|PopFoodInsecSevFemaleFIES
|Number of females who have experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number of population in severe food insecurity [Total Number Female]
|0
|
|
|-
|PopFoodInsecSevMale%FIES
|Proportion of the male population that has experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of severe food insecurity in the population [Total Percent Male]
|0
|
|
|-
|PopFoodInsecSevMaleFIES
|Number of males who have experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number of population in severe food insecurity [Total Number Male]
|0
|
|
|-
|PopFoodInsecSevRural%FIES
|Proportion of the rural population that has experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of severe food insecurity in the population [Total Percent Rural]
|0
|
|
|-
|PopFoodInsecSevRuralFIES
|Number of people in rural areas who have experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number of population in severe food insecurity [Total Number Rural]
|0
|
|
|-
|PopFoodInsecSevTotal%FIES
|Proportion of the population that has experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of severe food insecurity in the population [Total Percent]
|0
|
|
|-
|PopFoodInsecSevTotalFIES
|Number of people who have experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number of population in severe food insecurity [Total Number]
|0
|
|
|-
|PopFoodInsecSevUrban%FIES
|Proportion of the urban population that has experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of severe food insecurity in the population [Total Percent Urban]
|0
|
|
|-
|PopFoodInsecSevUrbanFIES
|Number of people in urban areas who have experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number of population in severe food insecurity [Total Number Urban]
|0
|
|
|-
|PopFoodInsecTotal%FIES
|Proportion of the population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent]
|0
|
|
|-
|PopFoodInsecTotalFIES
|Number of people who have experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number of population in moderate or severe food insecurity [Total Number]
|0
|
|
|-
|PopFoodInsecUrban%FIES
|Proportion of the urban population that has experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated prevalence of moderate or severe food insecurity in the population [Total Percent Urban]
|0
|
|
|-
|PopHHFoodInsecSevTotalFIES
|Number of people living in households where at least one adult experienced severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number living in HHs where one+ adult experienced severe food insecurity [Total Number]
|0
|
|
|-
|PopHHFoodInsecTotalFIES
|Number of people living in households where at least one adult experienced moderate or severe food insecurity in the last year as measured on the Food Insecurity Experience Scale
|SDG 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
|Estimated number living in households where one+ adult experienced food insecurity [Total Number]
|0
|
|
|-
|PopMarried15Fem20to24%
|Proportion of women aged 20-24 years who were married or in a union before age 15
|SDG 5.3.2 Proportion of girls and women aged 15-49 years who have undergone female genital mutilation/cutting, by age
|Proportion of women aged 20-24 years who were married by age 15
|0
|
|
|-
|PopMarried18Fem20to24%
|Proportion of women aged 20-24 years who were married or in a union before age 18
|SDG 5.3.2 Proportion of girls and women aged 15-49 years who have undergone female genital mutilation/cutting, by age
|Proportion of women aged 20-24 years who were married by age 18
|0
|
|
|-
|PopPrisonersUnsentenced%
|Unsentenced detainees as a proportion of overall prison population
|SDG 16.3.2 Unsentenced detainees as a proportion of overall prison population
|Unsentenced detainees as a proportion of overall prison population
|0
|
|
|-
|PopUrbanPopulationSlums
|The number of urban population living in slums, informal settlements or inadequate housing as measured by proportion of urban population living in slums.
|SDG 11.1.1 Proportion of urban population living in slums, informal settlements or inadequate housing
|Proportion of urban population living in slums, informal settlements or inadequate housing
|0
|
|
|-
|SanitationClearProcRural
|Countries with clearly defined procedures in law or policy for participation by service users/communities in planning program in sanitation (Rural)
|SDG 6.b.1 Proportion of local administrative units with established and operational policies and procedures for participation of local communities in water and sanitation management
|Countries with clear procedures for participation in planning programs in sanitation
|0
|
|
|-
|SanitationClearProcUrban
|Countries with clearly defined procedures in law or policy for participation by service users/communities in planning program in sanitation (Urban)
|SDG 6.b.1 Proportion of local administrative units with established and operational policies and procedures for participation of local communities in water and sanitation management
|Countries with clear procedures for participation in planning programs in sanitation
|0
|
|
|-
|SanitationParticRural
|The level of rural users/communities participating in planning programs in sanitation
|SDG 6.b.1 Proportion of local administrative units with established and operational policies and procedures for participation of local communities in water and sanitation management
|The level of rural users/communities participating in planning programs in sanitation
|0
|
|
|-
|SanitationParticUrban
|The level of urban users/communities participating in planning programs in sanitation
|SDG 6.b.1 Proportion of local administrative units with established and operational policies and procedures for participation of local communities in water and sanitation management
|The level of urban users/communities participating in planning programs in sanitation
|0
|
|
|-
|TransMailVolbyAir
|The volume of mail carried by air transport
|SDG 9.1.2 - Passenger and freight volumes, by mode of transport
|Mail volume (tonne kilometres), by air transport
|0
|
|
|-
|TransRoadFreight
|The sum of the freight volumes reported for the air carriers in terms of metric tonnes of cargo respectively
|SDG 9.1.2 - Passenger and freight volumes, by mode of transport
|Freight volume (tonne kilometres), by road transport
|0
|
|
|-
|TransRoadPassengers
|The sum of the passenger reported for the air carriers in terms of number of people respectively
|SDG 9.1.2 - Passenger and freight volumes, by mode of transport
|Passenger volume (passenger kilometres), by road transport
|0
|
|
|-
|UniHealthCoverageIndex
|Coverage of essential health services (Index)
|SDG 3.8.1 Coverage of essential health services
|Universal health coverage (UHC) service coverage index
|0
|
|
|-
|UrbanPopulationSlums%
|The proportion of urban population living in slums, informal settlements or inadequate housing as measured by proportion of urban population living in slums.
|SDG 11.1.1 Proportion of urban population living in slums, informal settlements or inadequate housing
|Proportion of urban population living in slums, informal settlements or inadequate housing
|0
|
|
|-
|WomManagerialSenMidUN%
|The proportion of females in the total number of persons employed in senior and middle mangement positions
|SDG 5.5.2 Proportion of women in managerial positions
|Proportion of women in senior and middle managment positions
|0
|
|
|-
|WomManagerialUN%
|The proportion of females in the total number of persons employed in managerial positions
|SDG 5.5.2 Proportion of women in managerial positions
|Proportion of women in managerial positions
|0
|
|
|-
|WomRepHealthDecision15to49%
|Proportion of women aged 15-49 years (married or in union) who make their own decisions on sexual relations, use of contraception, and reproductive healthcare
|SDG 5.6.1 Proportion of women aged 15-49 years who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health care
|Women who make their own informed decisions about sexual and reproductive matters [15 to 49]
|0
|
|
|}

= Data Pulling Instructions =

# Navigate to https://unstats.un.org/sdgs/dataportal
# Click the search bar and look up each indicator listed in Name in Source

OR

# Navigate to https://unstats.un.org/sdgs/dataportal/database
# Select the SDG indicators found in Ext Source Def
# Select Countries or areas and select all of them
# Select all years in Period
# Download

= Data Notes =

Statistical Review of World Energy, Energy Institute

2026-03-11T17:05:33Z

Norah.Shamin:

= Summary =
The Statistical Review analyzes data on world energy markets and provides data to the energy community since 1952. Data compilation is done by the Centre for Energy Economics Research and Policy at Heriot-Watt University. An advisory board has also been established, bringing together leaders and experts to provide strategic oversight of the publication.

There are 18 tables from the Statistical Review of World Energy, Energy Institute. 8 are preprocessor and 10 are not.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Years
!UsedInPreprocesspr
!UsedInPreprocessorFileName
!Name In Source
!Formula
!Extended Source Definition/Units
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
|-
|EnConBioEI
|SeriesEnConBioEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Biofuels Consumption
|Data in Petajoules
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Biofuels consumption
|0
|
|0
|biofuels_cons_pj
|5
|IFs Country
|*0.000163456
|-
|EnConCoalEI
|SeriesEnConCoalEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Coal Consumption
|Data in Exajoules
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Coal - Consumption
|0
|
|0
|coalcons_ej
|5
|IFs Country
|*0.163456
|-
|EnConElecHydroEI
|SeriesEnConElecHydroEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Hydro-electricity Consumption
|Data in Exajoules
|BBOE
|
|1965-2023
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Hydro-electricity - Consumption
|0
|
|0
|hydro_ej
|5
|IFs Country
|*0.1634
|-
|EnConGasEI
|SeriesEnConGasEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Natural gas Consumption
|Data in Billion cubic metres
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Gas - Consumption
|0
|
|0
|gascons_bcm
|5
|IFs Country
|*0.006373
|-
|EnConGeothBioEI
|SeriesEnConGeothBioEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Geothermal, biomass and other renewable energy Consumption
|Data in Exajoules
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Geothermal, Biomass and Other
|0
|
|0
|biogeo_ej
|5
|IFs Country
|*0.163456
|-
|EnConNucEI
|SeriesEnConNucEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Nuclear-electricity Consumption
|Data in Exajoules
|BBOE
|
|1965-2023
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Nuclear Energy - Consumption
|0
|
|0
|nuclear_ej
|5
|IFs Country
|*0.1634
|-
|EnConOilEI
|SeriesEnConOilEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Oil Consumption
|Data in Million tonnes of Oil Equivalent
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Oil - Consumption
|0
|
|0
|oilcons_mt
|5
|IFs Country
|*0.006842
|-
|EnConRenewEI
|SeriesEnConRenewEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Renewable energy Consumption
|Data in Exajoules
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Consumption
|0
|
|0
|renewables_ej
|5
|IFs Country
|*0.163456
|-
|EnConSolarEI
|SeriesEnConSolarEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Solar energy Consumption
|Data in Exajoules
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Solar Consumption
|0
|
|0
|solar_ej
|5
|IFs Country
|*0.163456
|-
|EnConWindEI
|SeriesEnConWindEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Wind energy Consumption
|Data in Exajoules
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Wind Consumption
|0
|
|0
|wind_ej
|5
|IFs Country
|*0.163456
|-
|EnElecGenCoalEI
|SeriesEnElecGenCoalEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Electricity Generated by from Coal
|Data in TWh
|GWh
|
|1985-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Elec Gen from Coal
|0
|
|0
|electbyfuel_coal
|5
|IFs Country
|*1000
|-
|EnElecGenGasEI
|SeriesEnElecGenGasEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Electricity Generated by from Gas
|Data in TWh
|GWh
|
|1985-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Elec Gen from Gas
|0
|
|0
|electbyfuel_gas
|5
|IFs Country
|*1000
|-
|EnElecGenHydroEI
|SeriesEnElecGenHydroEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Electricity Generated by from Hydro
|Data in TWh
|GWh
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Elec Gen from Hydro
|0
|
|0
|electbyfuel_hydro
|5
|IFs Country
|*1000
|-
|EnElecGenNucEI
|SeriesEnElecGenNucEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Electricity Generated by from Nuclear
|Data in TWh
|GWh
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Elec Gen from Nuclear
|0
|
|0
|electbyfuel_nuclear
|5
|IFs Country
|*1000
|-
|EnElecGenOilEI
|SeriesEnElecGenOilEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Electricity Generated by from Oil
|Data in TWh
|GWh
|
|1985-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Elec Gen from Oil
|0
|
|0
|electbyfuel_oil
|5
|IFs Country
|*1000
|-
|EnElecGenOtherEI
|SeriesEnElecGenOtherEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Electricity Generated by from Other
|Data in TWh
|GWh
|
|1985-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Elec Gen from Other
|0
|
|0
|electbyfuel_other
|5
|IFs Country
|*1000
|-
|EnElecGenRenewEI
|SeriesEnElecGenRenewEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Electricity Generated by from Renewables
|Data in TWh
|GWh
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Elec Gen from Renewables
|0
|
|0
|electbyfuel_ren_power
|5
|IFs Country
|*1000
|-
|EnElecGenTotEI
|SeriesEnElecGenTotEI
|Energy, Infrastructure
|Consumption
|Yes
|No
|No
|Total Electricity Generation
|Data in TWh
|GWh
|
|1985-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Electricity Generation
|0
|
|0
|electbyfuel_total
|5
|IFs Country
|*1000
|-
|EnInstSolarEI
|SeriesEnInstSolarEI
|Energy, Infrastructure
|Capacity
|Yes
|No
|No
|Cumulative installed photovoltaic (PV) power
|Data in Megawatts
|MW
|
|1996-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewable energy - solar (Installed capacity)
|0
|
|0
|Solar Capacity
|5
|IFs Country
|
|-
|EnInstWindEI
|SeriesEnInstWindEI
|Energy, Infrastructure
|Capacity
|Yes
|No
|No
|Cumulative installed wind turbine capacity
|Data in Megawatts
|MW
|
|1997-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewable energy - wind (Installed capacity)
|0
|
|0
|Wind Capacity
|5
|IFs Country
|
|-
|EnProdBioEI
|SeriesEnProdBioEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Biofuels Production
|Data in Petajoules
|BBOE
|
|1990-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Biofuels production
|0
|
|0
|biofuels_prod_pj
|5
|IFs Country
|*0.000163456
|-
|EnProdCoalEI
|SeriesEnProdCoalEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Coal Production
|Data in Million tonnes of Coal Equivalent
|BBOE
|
|1981-2023
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Coal - Production
|0
|
|0
|coalprod_mt
|5
|IFs Country
|*0.004789
|-
|EnProdElecHydroEI
|SeriesEnProdElecHydroEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Hydro-electricity Production
|Data in TWh
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Hydro-electricity - Generation
|0
|
|0
|hydro_twh
|5
|IFs Country
|*0.000588235
|-
|EnProdGasEI
|SeriesEnProdGasEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Natural gas Production
|Data in Billion cubic metres
|BBOE
|
|1970-2023
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Gas - Production
|0
|
|0
|gasprod_bcm
|5
|IFs Country
|*0.006373
|-
|EnProdGeothBioEI
|SeriesEnProdGeothBioEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Geothermal, biomass and other renewable energy Production
|Data in TWh
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Geothermal, Biomass and Other generation
|0
|
|0
|biogeo_twh
|5
|IFs Country
|*0.000588235
|-
|EnProdNucEI
|SeriesEnProdNucEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Nuclear-electricity Production
|Data in TWh
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Nuclear Energy - Generation
|0
|
|0
|nuclear_twh
|5
|IFs Country
|*0.000588235
|-
|EnProdOilEI
|SeriesEnProdOilEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Oil Production
|Data in Million tonnes of Oil Equivalent
|BBOE
|
|1965-2023
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Oil - Production
|0
|
|0
|oilprod_mt
|5
|IFs Country
|*0.00684
|-
|EnProdRenewEI
|SeriesEnProdRenewEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Renewable energy Production
|Data in TWh
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Renewable Power
|0
|
|0
|ren_power_twh
|5
|IFs Country
|*0.000588235
|-
|EnProdSolarEI
|SeriesEnProdSolarEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Solar energy Production
|Data in TWh
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Solar Generation
|0
|
|0
|solar_twh
|5
|IFs Country
|*0.000588235
|-
|EnProdWindEI
|SeriesEnProdWindEI
|Energy, Infrastructure
|Production
|Yes
|No
|No
|Wind energy Production
|Data in TWh
|BBOE
|
|1965-2022
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Renewables - Wind Generation
|0
|
|0
|wind_twh
|5
|IFs Country
|*0.000588235
|-
|EnResGasEI
|SeriesEnResGasEI
|Energy, Infrastructure
|Resources
|Yes
|No
|No
|Natural gas Reserves
|Data in Trillion cubic metres
|BBOE
|
|1980-2020
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Gas - Proved Reserves
|0
|
|0
|Gas - Proved reserves history
|5
|IFs Country
|*6.373
|-
|EnResOilEI
|SeriesEnResOilEI
|Energy, Infrastructure
|Resources
|Yes
|No
|No
|Oil Reserves
|Data in Thousand million barrels
|BBOE
|
|1980-2020
|BP's Statistical Review of World Energy
|<nowiki>https://www.energyinst.org/statistical-review/resources-and-data-downloads</nowiki>
|[[Statistical Review of World Energy, Energy Institute|https://pardeewiki.du.edu/index.php?title=Statistical_Review_of_World_Energy,_Energy_Institute]]
|2026/03/04
|SUM
|GDP
|0
|0
|Oil - Proved Reserves
|0
|
|0
|Oil - Proved reserves history
|5
|IFs Country
|
|}

= Data Pulling Instructions =

#For the BP energy data, pull it from the BP website [https://www.energyinst.org/statistical-review/resources-and-data-downloads Resources and data downloads | Statistical Review of World Energy (energyinst.org)]
#*Download: Statistical Review of World Energy Data
#The Name in Source is the sheet name that the data will be in. In the "Contents" tab each type of energy is linked.
##For example, Hydroelectricity - Consumption is under "Hydroelectricity - Consumption - Exajoules (from 1965)" in the Contents tab and the sheet name is Hydro Consumption - EJ.
#When preparing the data, please compare the units from the original source and the units in the DataDict. Use the BBOE_UnitConversions.xlsx to transform the data to unified units (BBOE) in IFs. The latest update date for the BBOE_UnitConversion was 2024/02/12.
#*For example, the unit for oil production is in MTOE (Million tonnes of oil equivalent). It needs to convert that to BBOE (Billion Barrels of Oil Equivalent), which is why it needs to be multiply by those numbers in the Formula.
#*The conversion factors can be found here: [https://www.iea.org/data-and-statistics/data-tools/unit-converter Unit Converter – Data Tools - IEA] or [Https://www.convert-me.com/en/convert/energy/?u=bboe&v=1 https://www.convert-me.com/en/convert/energy/?u=bboe&v=1]

= Data Notes =
*''Russian Federation, it was called the USSR before 1991 and we need to consolidate it into one country when pulling the data.''

Energy Data, BGR

2026-03-11T17:03:32Z

Norah.Shamin:

= Summary =
The Federal Institute for Geosciences and Natural Resources, or BGR, is a German Agency which publishes data on oil and gas resources and reserves. BGR data can be accessed [https://www.bgr.bund.de/EN/Themen/Energie/Produkte/produkte_node_en.html?tab=Energy+Studies here]. This data is useful because resources and reserves are broken into their unconventional sub-components such as shale gas, tight oil, and coalbed methane. This is important in initializing total resources and reserves in the model, especially with the rise in unconventional gas and oil production in North America.

= Tables In IFs =
{| class="wikitable"
!Variable
!Definition
!Units
!Years
!Last IFs Update
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|EnReserOilSandsBGR
|Oil Sands Reserves
|Mt
|2011-2016, 2023
|2026/02/20
|1
|ENERGY
|-
|EnResorOilSandsBGR
|Oil sands resources
|Mt
|2011-2016, 2023
|2026/02/20
|1
|ENERGY
|-
|EnCumProdGasBGR
|Natural Gas Cumulative Production
|BCM
|2009-2018, 2020-2023
|2026/02/20
|0
|
|-
|EnCumProdOilBGR
|Cumulative Production Oil
|Mt
|2009-2018, 2020-2023
|2026/02/20
|0
|
|-
|EnReserCBMBGR
|Coalbed methane reserves
|BCM
|2010-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnReserGasBGR
|Natural gas reserves
|BCM
|2009-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnReserShaleGasBGR
|Shale Gas Reserves
|BCM
|2010-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnResorCBMBGR
|Coalbed methane Resources
|BCM
|2010-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnResorGasBGR
|Natural gas resources
|BCM
|2009-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnResorShaleGasBGR
|Shale Gas Resources
|BCM
|2010-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnResorTightGasBGR
|Tight Gas Resources
|BCM
|2011-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnReserHeavyOilBGR
|Heavy Oil Reserves
|Mt
|2010-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnReserOilBGR
|Crude oil reserves
|Mt
|2009-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnReserShaleOilBGR
|Shale Oil Reserves
|Mt
|2011-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnResorHeavyOilBGR
|Heavy Oil Resources
|Mt
|2010-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnResorOilBGR
|Crude oil resources
|Mt
|2009-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnResorShaleOilBGR
|Shale Oil resources
|Mt
|2011-2018, 2020-2023
|2026/02/20
|1
|ENERGY
|-
|EnReserHardCoalBGR
|Hard coal reserves
|mt
|2020-2023
|2026/02/20
|0
|
|-
|EnResorHardCoalBGR
|Hard coal resources
|mt
|2020-2023
|2026/02/20
|0
|
|-
|EnReserLigniteBGR
|Lignite reserves
|mt
|2020-2023
|2026/02/20
|0
|
|-
|EnResorLigniteBGR
|Lignite resources
|mt
|2020-2023
|2026/02/20
|0
|
|-
|EnReserUraniumBGR
|Uranium reserves
|kt
|2020-2023
|2026/02/20
|0
|
|-
|EnResorUraniumBGR
|Uranium resouces
|kg
|2020-2023
|2026/02/20
|0
|
|}
= Data Pulling Instructions =

'''Process of importing and blending:'''

In preparing these series, first downloaded the relevant energy data from the [https://www.bgr.bund.de/EN/Themen/Energie/Produkte/produkte_node_en.html?tab=Energy+Studies BGR website], or are available through a google search of "BGR Energy Resources [YEAR]".

* The study reports data in previous year.
* '''Missing BGR Energy Study 2020, thus, we don't have data in 2019.'''
* Starting from 2019, BGR also provided data in excel spreadsheet. Thus, the data after 2018 can be extracted from excel, not pdf.
* The data before 2018 need to be extracted from BGR reports in pdf.
* '''The most recent data can be downloaded in BGR Energy Study in Germany version from [https://www.bgr.bund.de/DE/Themen/Rohstoffe/Produkte/Energiedaten/energiedaten_node.html here].'''
** The latest update was in April, 2024. The data in 2021 and 2022 were downloaded from the BGR Energy Study in Germany version.

Remember to combine the new data and current data in IFsHistSeries.db.

Below in Data Notes it showcases what sheets correspend to which tables. There is a code attached in this [https://github.com/n1shamin/BGR/tree/main Github repo]. The data has to be cleaned beforehand to use this script.

= Data Notes =
'''Some notes on the formatting process:'''

In 2014, term changed from Shale Oil to Tight Oil (applies to Series EnReserShaleOil and EnResourceShaleOil) not to be confused with Tight Gas.

Table numbers don’t stay the same over different years in the energy reports.

Differences between resources and reserves: “…[That] part of a mineral resource, which has been fully evaluated and is deemed commercially viable to work, is called a mineral reserve [in effect, resources will always be larger than resources]” In effect, resources shouldn’t change over time, while reserves can.

''-Source: ''[http://www.bgs.ac.uk/mineralsUK/mineralsYou/resourcesReserves.html ''http://www.bgs.ac.uk/mineralsUK/mineralsYou/resourcesReserves.html'']''; Accessed 3/6/16''

Sudan and South Sudan: Most of the time, BGR lists reserve and resource values for "Sudan" and "South Sudan" individually. On occasion though, BGR will use "Sudan and South Sudan" as a composite, representing aggregated data for both of the countries but not providing it on an individual basis. This is rare, and only takes place in series EnReserGasBGR and EnResorGasBGR. In these cases, I calculated the values for "Sudan" and "South Sudan" by taking the value of "Sudan and South Sudan" and dividing it by the ratio of land mass between Sudan (728,215 sqm) and South Sudan (239,285 sqm). Also, per Steve Hedden, we don't enter values for Sudan in the series EnCumProdGas and EnCumProdOil.

Another issue that needs mentioning is BGR's usage of dashes ("-" or "—") in its Energy Reports. Dashes are intrepreted as 0's based on the definition given by BGR in the Energy Reports.

BGR occasionally uses "n.s." (or "n. s.") in its data, which is intrepreted as a null value. In the German translation, "k. A." is used instead of "n.s.".

If there is a less than sign in the data, it is dropped and the value preceding it is entered as is. Eg. <0.05 is entered as 0.05.

'''Reference Data''''': Listed below is each BGR series updated, all with the name of the table in the Energy Report pdf, and the column of the table used before 2018 or with the sheet name in the Excel, and the column of the table used after 2018''
{| class="wikitable"
|
|
|
! colspan="8" |''Data after 2018 from Excel''
|-
|
! colspan="2" |''Data Before 2018 from pdf''
! colspan="2" |''2018''
! colspan="2" |''2020''
! colspan="2" |''2021''
! colspan="2" |''2022, 2023''
|-
|''Variable''
|''Table Name''
|''Column''
|''Sheet Name''
|''Column''
|''Sheet Name''
|''Column''
|''Sheet Name''
|''Column''
|''Sheet Name''
|''Column''
|-
|''EnCumProdGasBGR''
|''Natural Gas in XXXX (year)''
|''Cum. Production''
|''s. A-15, Natural Gas, 2018 ...''
|''Cum. Production''
|''s. A-15, Natural Gas, 2020 ...''
|''Cum. Production''
|''s. A-15, Übersicht Erdgas, ...''
|''Kum. Förderung''
|''s. A-15, Übersicht Erdgas, ...''
|''Kum. Förderung''
|-
|''EnReserCBMBGR''
|''Natural Gas Reserves in XXXX (year)''
|''CBM''
|''A-17, Natural gas reserves 2018''
|''CBM: proved reserves''
|''A-17, Natural gas reserves ...''
|''CBM: proved reserves''
|''A-17, Erdgasreserven 2021 (...''
|''CBM, Reserven''
|''A-17, Erdgasreserven 2022 (...''
|''CBM, Reserven''
|-
|''EnReserGasBGR''
|''Natural Gas in XXXX (year)''
|''Reserves''
|''s. A-15, Natural Gas, 2018 ...''
|''Reserves''
|''s. A-15, Natural Gas, 2020 ...''
|''Reserves''
|''s. A-15, Übersicht Erdgas, ...''
|''Reserven''
|''s. A-15, Übersicht Erdgas, ...''
|''Reserven''
|-
|''EnReserShaleGasBGR''
|''Natural Gas Reserves in XXXX (year)''
|''shale gas''
|''A-17, Natural gas reserves 2018''
|''shale gas: proved reserves''
|''A-17, Natural gas reserves ...''
|''shale gas: proved reserves''
|''A-17, Erdgasreserven 2021 (...''
|''Schiefer Gas: Reserven''
|''A-17, Erdgasreserven 2022 (...''
|''Schiefer Gas: Reserven''
|-
|''EnResorCBMBGR''
|''Natural Gas Resources in XXXX (year)''
|''CBM''
|''A-16, Natural gas resources...''
|''CBM: ressources''
|''A-16, Natural gas resources...''
|''CBM: ressources''
|''A-16, Erdgasressourcen 2021...''
|''CBM, Ressourcen''
|''A-16, Erdgasressourcen 2022...''
|''CBM, Ressourcen''
|-
|''EnResorGasBGR''
|''Natural Gas in XXXX (year)''
|''Remaining Potential''
|''s. A-15, Natural Gas, 2018 ...''
|''Remaining Potential''
|''s. A-15, Natural Gas, 2020 ...''
|''Remaining Potential''
|''s. A-15, Übersicht Erdgas, ...''
|''Verbl. Potenzial''
|''s. A-15, Übersicht Erdgas, ...''
|''Verbl. Potenzial''
|-
|''EnResorShaleGasBGR''
|''Natural Gas Resources in XXXX (year)''
|''shale gas''
|''A-16, Natural gas resources...''
|''shale gas: resources''
|''A-16, Natural gas resources...''
|''shale gas: resources''
|''A-16, Erdgasressourcen 2021...''
|''Schiefer Gas, Ressourcen''
|''A-16, Erdgasressourcen 2022...''
|''Schiefer Gas, Ressourcen''
|-
|''EnResorTightGasBGR''
|''Natural Gas Resources in XXXX (year)''
|''tight gas''
|''A-16, Natural gas resources...''
|''tight gas: resources''
|''A-16, Natural gas resources...''
|''tight gas: resources''
|''A-16, Erdgasressourcen 2021...''
|''Tight Gas, Ressourcen''
|''A-16, Erdgasressourcen 2022...''
|''Tight Gas, Ressourcen''
|-
|''EnCumProdOilBGR''
|''Crude Oil in XXXX (year)''
|''Cum. Production''
|''s. A-8, Crude oil, 2018 (Mt)''
|''Cum. Production''
|''s. A-8, Crude oil, 2020 (Mt)''
|''Cum. Production''
|''s. A-8, Übersicht Erdöl, 20...''
|''Kum. Förderung''
|''s. A-8, Übersicht Erdöl, 20...''
|''Kum. Förderung''
|-
|''EnReserHeavyOilBGR''
|''Crude Oil Reserves in XXXX (year)''
|''extra heavy oil''
|''A-10, Crude oil reserves 2018''
|''extra heavy oil: proved reserves''
|''A-10, Crude oil reserves 20...''
|''extra heavy oil: proved reserves''
|''A-10, Erdölreserven 2021 (Mt)''
|''Schwerstöl, Reserven''
|''A-10, Erdölreserven 2022 (Mt)''
|''Schwerstöl, Reserven''
|-
|''EnReserOilBGR''
|''Crude Oil in XXXX (year)''
|''Reserves''
|''s. A-8, Crude oil, 2018 (Mt)''
|''Reserves''
|''s. A-8, Crude oil, 2020 (Mt)''
|''Reserves''
|''s. A-8, Übersicht Erdöl, 20...''
|''Reserven''
|''s. A-8, Übersicht Erdöl, 20...''
|''Reserven''
|-
|''EnReserOilSandsBGR''
|''Crude Oil Reserves in XXXX (year)''
|''oil sand''
|''A-10, Crude oil reserves 2018''
|''Oil Sand: Proved reserves''
|''A-10, Crude oil reserves 20...''
|''Oil Sand: Proved reserves''
|''A-10, Erdölreserven 2021 (Mt)''
|''Ölsandreserven''
|''A-10, Erdölreserven 2022 (Mt)''
|''Ölsandreserven''
|-
|''EnReserShaleOilBGR''
|''Crude Oil Reserves in XXXX (year)''
|''shale oil''
|''A-10, Crude oil reserves 2018''
|''shale oil: reserves''
|''A-10, Crude oil reserves 20...''
|''shale oil: reserves''
|''A-10, Erdölreserven 2021 (Mt)''
|''Schieferöl: Reserven''
|''A-10, Erdölreserven 2022 (Mt)''
|''Schieferöl: Reserven''
|-
|''EnResorHeavyOilBGR''
|''Crude Oil Resources in XXXX (year)''
|''extra heavy oil''
|''A-9, Crude oil resources 2018''
|''extra heavy oil: resources''
|''A-9, Crude oil resources 20...''
|''extra heavy oil: resources''
|''A-9, Erdölressourcen 2021 (Mt)''
|''Schwerstöl, Ressourcen''
|''A-9, Erdölressourcen 2022 (Mt)''
|''Schwerstöl, Ressourcen''
|-
|''EnResorOilBGR''
|''Crude Oil in XXXX (year)''
|''Remaining Potential''
|''s. A-8, Crude oil, 2018 (Mt)''
|''Remaining Potential''
|''s. A-8, Crude oil, 2020 (Mt)''
|''Remaining Potential''
|''s. A-8, Übersicht Erdöl, 20...''
|''Verbl. Potenzial''
|''s. A-8, Übersicht Erdöl, 20...''
|''Verbl. Potenzial''
|-
|''EnResorOilSandsBGR''
|''Crude Oil Resources in XXXX (year)''
|''oil sand''
|''A-9, Crude oil resources 2018''
|''oil sand: resources''
|''A-9, Crude oil resources 20...''
|''oil sand: resources''
|''A-9, Erdölressourcen 2021 (Mt)''
|''Ölsand, Ressourcen''
|''A-9, Erdölressourcen 2022 (Mt)''
|''Ölsand, Ressourcen''
|-
|''EnResorShaleOilBGR''
|''Crude Oil Resources in XXXX (year)''
|''shale oil''
|''A-9, Crude oil resources 2018''
|''shale oil: resources''
|''A-9, Crude oil resources 20...''
|''shale oil: resources''
|''A-9, Erdölressourcen 2021 (Mt)''
|''Schieferöl: Ressourcen''
|''A-9, Erdölressourcen 2022 (Mt)''
|''Schieferöl: Ressourcen''
|}
Note: Data in 2021 and 2022 were downloaded from https://www.bgr.bund.de/DE/Themen/Energie/Produkte/produkte_node.html?tab=Energiestudien<ol style="list-style-type: lower-alpha;">

Diabetes Atlas, International Diabetes Federation

2026-03-03T19:24:28Z

Norah.Shamin:

= Summary =
The International Diabetes Federation (IDF) is an umbrella organization of over 230 national diabetes associations in 170 countries and territories. It represents the interests of the growing number of people with diabetes and those at risk. The Federation has been leading the global diabetes community since 1950.

= Tables In IFs =
Currently there is only new data for HealthIGTPrev% and HealthDiabetesPrev%. Check each update to see if the outdated tables have any new data.
{| class="wikitable"
|+
!Variable
!Definition
!Years
!Last IFs Update
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|'''<big>HealthDiabetesPrev%</big>'''
|<big>'''Prevalence of diabetes'''</big>
|<big>'''2003,2013-2015,2017,2019,2021,2025,2035,2040, 2050'''</big>
|<big>'''2/12/2026'''</big>
|<big>'''1'''</big>
|<big>'''HEALTH'''</big>
|-
|'''<big>HealthIGTPrev%</big>'''
|<big>'''Prevalence of impaired glucose intolerance'''</big>
|<big>'''2003,2013-2015,2017,2019,2021,2025,2035,2040, 2050'''</big>
|<big>'''2/12/2026'''</big>
|<big>'''1'''</big>
|<big>'''HEALTH'''</big>
|-
|''HealthDiabetesPrevFemale''
|''Prevalence of diabetes among females aged 20-79.''
|''2003, 2025''
|''3/28/2009''
|''0''
|
|-
|''HealthDiabetesPrevMale''
|''Prevalence of diabetes among males aged 20-79.''
|''2003, 2025''
|''3/28/2009''
|''0''
|
|-
|''HealthIGTPrevFemale''
|''Prevalence of impaired glucose intolerance among females aged 20-79.''
|''2003, 2025''
|''3/28/2009''
|''0''
|
|-
|''HealthIGTPrevMale''
|''Prevalence of impaired glucose intolerence among males aged 20-79.''
|''2003, 2025''
|''3/28/2009''
|''0''
|
|-
|''HealthDiabetesPrev20-39''
|''Average number of people per million, between the ages 20-39, with diabetes''
|''2003, 2025''
|''1/7/2009''
|''0''
|
|-
|''HealthDiabetesPrev40-59''
|''Average number of people per million, between the ages 40-59, with diabetes''
|''2003, 2025''
|''1/7/2009''
|''0''
|
|-
|''HealthDiabetesPrev60-79''
|''Average number of people per million, between the ages 60-79, with diabetes''
|''2003, 2025''
|''1/7/2009''
|''0''
|
|-
|''HealthIGTPrev20-39''
|''Average number of people per million, between the ages 20-39, with Impaired Glucose Intolerence''
|''2003, 2025''
|''1/7/2009''
|''0''
|
|-
|''HealthIGTPrev40-59''
|''Average number of people per million, between the ages 40-59, with Impaired Glucose Intolerence''
|''2003, 2025''
|''1/7/2009''
|''0''
|
|-
|''HealthIGTPrev60-79''
|''Average number of people per million. between the ages 60-79, with Impaired Glucose Intolerence''
|''2003, 2025''
|''1/7/2009''
|''0''
|
|}

= Data Pulling Instructions =

The current update came from International Diabetes Federation's Diabetes Atlas; https://diabetesatlas.org/

Step 1: access https://diabetesatlas.org/resources/

Step 2: access the various editions of the atlas and gather data from pdf files.
[[File:Image IDF 1.png|none|thumb|616x616px]]

Step 3: For data in the excel format navigate to: https://diabetesatlas.org/
[[File:Diabetes Altas Indicators.png|none|thumb|600x600px]]
Step 4: Once you click the boxed indicators make sure you select "Age-standardised prevalence of diabetes, %" and "Age-standardised prevalence of IGT, %" respectively.

Prevalence of diabetes ('''SeriesHealthDiabetesPrev%'''): 2014, 2015 and 2040 were added for prevalence of diabetes. The data for 2014 came from an atlas poster for 6th edition and all other data came from a tool on the site.

Prevalence of impaired glucose intolerance ('''SeriesHealthIGTPrev%'''): 2015 and 2040 were added for the prevalence of impaired glucose intolerance.

These were national prevalences and not age adjusted.

= Data Notes =

=== '''SeriesHealthDiabetesPrev%''' ===

=== '''SeriesHealthIGTPrev%''' ===
Only find "Age-adjusted comparative prevalance" from https://diabetesatlas.org/data/en/indicators/2/.

The data could be found in 6th edition.
[[File:Image idf 2.png|none|thumb|486x486px]]
However, it was not accessible from 7th edition in pdf. No actual update. In the next few releases this is present.

=== [https://diabetesatlas.org/faqs/ What is the difference between prevalence and age-adjusted comparative prevalence in the IDF Diabetes Atlas?] ===
National or regional prevalence is the actual percentage of the adult population (20-79 years) in a country or region that has diabetes. It is calculated by taking the estimated number of cases in adults and dividing by the total population in adults. The national prevalence should be used when reporting statistics for just one country or region, or when the statistics being reported are not for comparison.

Age-adjusted comparative prevalence, also referred to as comparative prevalence, is the prevalence calculated by adjusting to the age structure of a standard population. In the ''IDF Diabetes Atlas 10th Edition'', the standard population is the UN population for 2021, 2030 or 2045. Adjusting rates is a way to make fairer comparisons between groups with different distributions. Age-adjusted rates are rates that would have existed if the population under study had the same age distribution as the “standard” population.

File:Diabetes Altas Indicators.png

2026-03-03T19:22:26Z

Norah.Shamin:

Diabetes Altas Indicators

The Political Constraint Index (POLCON), University of Pennsylvania

2026-02-28T21:37:06Z

Norah.Shamin: /* Data Notes */

= Summary =
The POLCON measure, developed by Vice Dean and Faculty Director of the ESG Initiative Witold Henisz, is a quantitative measure of institutional constraints that uses a spatial model of political interaction and measures the feasibility of a change in policy given the structure of a nation’s political institutions.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Last IFs Update
!UsedInPreprocessor
|-
|GovPolConstraintsMain
|Measure of the amount of constraints on a leader through vetoes
|2026/02/26
|0
|-
|GovPolConstraintsPlus
|Measure of the amount of constraints on a leader through vetoes (also vetoes from the judiciary and sub-federal actors)
|2026/02/26
|0
|}

= Data Pulling Instructions =

#Navigate to https://mgmt.wharton.upenn.edu/faculty/heniszpolcon/polcondataset/
#Click the most recent excel file (right now it is 2025 Data release (see Key Sheet for Variable Key including important updates to construction of veto point data)
#Use the indicator POLCONIII_2025 for GovPolConstraintsMain and POLCONV_2025 for GovPolConstraintsPlus.

= Data Notes =

# For country concordances only use "cnts_country" the other country columns are missing countries for certain rows.
# A repo for a script is here: https://github.com/n1shamin/POLCON
# There are countries that should be merged together such as:

{| class="wikitable"
|+
!Country
!cnts-country
|-
| rowspan="4" |Yemen
|YEMEN
|-
|YEMEN AR
|-
|YEMEN REP
|-
|YEMEN PDR
|-
| rowspan="2" |Viet Nam
|VIETNAM REP
|-
|VIETNAM
|-
| rowspan="3" |Ethiopia
|ABYSSINIA
|-
|ETHIOPIA
|-
|ETH'PIA PDR
|-
| rowspan="2" |Cote D'Ivoire
|COTE D'IVOR
|-
|IVORY COAST
|-
| rowspan="4" |Congo
|CONGO
|-
|CONGO (BRA)
|-
|CONGO REP
|-
|CONGO Republic
|}

The Political Constraint Index (POLCON), University of Pennsylvania

2026-02-28T21:36:38Z

Norah.Shamin:

= Summary =
The POLCON measure, developed by Vice Dean and Faculty Director of the ESG Initiative Witold Henisz, is a quantitative measure of institutional constraints that uses a spatial model of political interaction and measures the feasibility of a change in policy given the structure of a nation’s political institutions.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Last IFs Update
!UsedInPreprocessor
|-
|GovPolConstraintsMain
|Measure of the amount of constraints on a leader through vetoes
|2026/02/26
|0
|-
|GovPolConstraintsPlus
|Measure of the amount of constraints on a leader through vetoes (also vetoes from the judiciary and sub-federal actors)
|2026/02/26
|0
|}

= Data Pulling Instructions =

#Navigate to https://mgmt.wharton.upenn.edu/faculty/heniszpolcon/polcondataset/
#Click the most recent excel file (right now it is 2025 Data release (see Key Sheet for Variable Key including important updates to construction of veto point data)
#Use the indicator POLCONIII_2025 for GovPolConstraintsMain and POLCONV_2025 for GovPolConstraintsPlus.

= Data Notes =

# For country concordances only use "cnts_country" the other country columns are missing countries for certain rows.
# There are countries that should be merged together such as:

{| class="wikitable"
|+
!Country
!cnts-country
|-
| rowspan="4" |Yemen
|YEMEN
|-
|YEMEN AR
|-
|YEMEN REP
|-
|YEMEN PDR
|-
| rowspan="2" |Viet Nam
|VIETNAM REP
|-
|VIETNAM
|-
| rowspan="3" |Ethiopia
|ABYSSINIA
|-
|ETHIOPIA
|-
|ETH'PIA PDR
|-
| rowspan="2" |Cote D'Ivoire
|COTE D'IVOR
|-
|IVORY COAST
|-
| rowspan="4" |Congo
|CONGO
|-
|CONGO (BRA)
|-
|CONGO REP
|-
|CONGO Republic
|}

World Tourism Organization (UN Tourism)

2026-02-28T21:17:55Z

Norah.Shamin: /* Tables In IFs */

= Summary =
UN Tourism is the United Nations agency responsible for the promotion of responsible, sustainable and universally accessible tourism.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Last IFs Update
!UsedInPreprocessor
|-
|GovIOTourstRevenue
|Tourism expenditure in the country of reference (excluding international transport)
|2026/02/26
|0
|-
|GovIOTourstVisitors
|Tourist arrivals in thousands, non-resident tourists/visitors
|2026/02/26
|0
|}

= Data Pulling Instructions =

# Navigate to https://www.unwto.org/tourism-statistics
#For general downloads:
##Select the Tourism Statistics Database[[File:UN Tourism Home Page.png|none|thumb|600x600px]]
##Either select the bulk download or choose one of the bottom indicators. Bulk downloads will be easier for filtering and scripts. [[File:UN Tourism Data Page.png|none|thumb|600x600px]]
#For the specific tables navigate to the "Inbound" section https://www.untourism.int/tourism-statistics/tourism-data-inbound-tourism
#Download the following indicators:[[File:Un Tourism Indicators.png|none|thumb|500x500px]]
#Once downloaded use indicator "inbound - trips - total - total - overnight visitors (tourists)" from Total Arrivals for GovIOTourstVisitors and "inbound - expenditure - balance of payments - travel - visitors" from Expenditure for GovIOTourstRevenue

= Data Notes =
Use UN country concordances.

World Tourism Organization (UN Tourism)

2026-02-28T21:17:34Z

Norah.Shamin: /* Data Pulling Instructions */

= Summary =
UN Tourism is the United Nations agency responsible for the promotion of responsible, sustainable and universally accessible tourism.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Last IFs Update
!UsedInPreprocessor
|-
|GovIOTourstRevenue
|Tourism expenditure in the country of reference (excluding international transport)
|5/3/2010
|0
|-
|GovIOTourstVisitors
|Tourist arrivals in thousands, non-resident tourists/visitors
|5/3/2010
|0
|}

= Data Pulling Instructions =

# Navigate to https://www.unwto.org/tourism-statistics
#For general downloads:
##Select the Tourism Statistics Database[[File:UN Tourism Home Page.png|none|thumb|600x600px]]
##Either select the bulk download or choose one of the bottom indicators. Bulk downloads will be easier for filtering and scripts. [[File:UN Tourism Data Page.png|none|thumb|600x600px]]
#For the specific tables navigate to the "Inbound" section https://www.untourism.int/tourism-statistics/tourism-data-inbound-tourism
#Download the following indicators:[[File:Un Tourism Indicators.png|none|thumb|500x500px]]
#Once downloaded use indicator "inbound - trips - total - total - overnight visitors (tourists)" from Total Arrivals for GovIOTourstVisitors and "inbound - expenditure - balance of payments - travel - visitors" from Expenditure for GovIOTourstRevenue

= Data Notes =
Use UN country concordances.

File:Un Tourism Indicators.png

2026-02-28T21:15:10Z

Norah.Shamin:

Un Tourism Indicators

Diabetes Atlas, International Diabetes Federation

2026-02-28T20:34:42Z

Norah.Shamin: /* Tables In IFs */

= Summary =
The International Diabetes Federation (IDF) is an umbrella organization of over 230 national diabetes associations in 170 countries and territories. It represents the interests of the growing number of people with diabetes and those at risk. The Federation has been leading the global diabetes community since 1950.

= Tables In IFs =
Currently there is only new data for HealthIGTPrev% and HealthDiabetesPrev%
{| class="wikitable"
|+
!Variable
!Definition
!Years
!Last IFs Update
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|HealthDiabetesPrev%
|Prevalence of diabetes
|2003,2013-2015,2017,2019,2021,2025,2035,2040, 2050
|2/12/2026
|1
|HEALTH
|-
|HealthDiabetesPrevFemale
|Prevalence of diabetes among females aged 20-79.
|2003, 2025
|3/28/2009
|0
|
|-
|HealthDiabetesPrevMale
|Prevalence of diabetes among males aged 20-79.
|2003, 2025
|3/28/2009
|0
|
|-
|HealthIGTPrev%
|Prevalence of impaired glucose intolerance
|2003,2013-2015,2017,2019,2021,2025,2035,2040, 2050
|2/12/2026
|1
|HEALTH
|-
|HealthIGTPrevFemale
|Prevalence of impaired glucose intolerance among females aged 20-79.
|2003, 2025
|3/28/2009
|0
|
|-
|HealthIGTPrevMale
|Prevalence of impaired glucose intolerence among males aged 20-79.
|2003, 2025
|3/28/2009
|0
|
|-
|HealthDiabetesPrev20-39
|Average number of people per million, between the ages 20-39, with diabetes
|2003, 2025
|1/7/2009
|0
|
|-
|HealthDiabetesPrev40-59
|Average number of people per million, between the ages 40-59, with diabetes
|2003, 2025
|1/7/2009
|0
|
|-
|HealthDiabetesPrev60-79
|Average number of people per million, between the ages 60-79, with diabetes
|2003, 2025
|1/7/2009
|0
|
|-
|HealthIGTPrev20-39
|Average number of people per million, between the ages 20-39, with Impaired Glucose Intolerence
|2003, 2025
|1/7/2009
|0
|
|-
|HealthIGTPrev40-59
|Average number of people per million, between the ages 40-59, with Impaired Glucose Intolerence
|2003, 2025
|1/7/2009
|0
|
|-
|HealthIGTPrev60-79
|Average number of people per million. between the ages 60-79, with Impaired Glucose Intolerence
|2003, 2025
|1/7/2009
|0
|
|}

= Data Pulling Instructions =

The current update came from International Diabetes Federation's Diabetes Atlas; https://diabetesatlas.org/

Step 1: access https://diabetesatlas.org/resources/

Step 2: access the various editions of the atlas and gather data from pdf files.
[[File:Image IDF 1.png|none|thumb|616x616px]]

Prevalence of diabetes ('''SeriesHealthDiabetesPrev%'''): 2014, 2015 and 2040 were added for prevalence of diabetes. The data for 2014 came from an atlas poster for 6th edition and all other data came from a tool on the site.

Prevalence of impaired glucose intolerance ('''SeriesHealthIGTPrev%'''): 2015 and 2040 were added for the prevalence of impaired glucose intolerance.

These were national prevalences and not age adjusted. All this data can be located in the 5th, 6th and 7th edition of the Atlas.

= Data Notes =

=== '''SeriesHealthDiabetesPrev%''' ===
=== '''SeriesHealthIGTPrev%''' ===
Only find "Age-adjusted comparative prevalance" from https://diabetesatlas.org/data/en/indicators/2/.

The data could be found in 6th edition.
[[File:Image idf 2.png|none|thumb|486x486px]]
However, it was not accessible from 7th edition in pdf. No actual update. In the next few releases this is present.

=== [https://diabetesatlas.org/faqs/ What is the difference between prevalence and age-adjusted comparative prevalence in the IDF Diabetes Atlas?] ===
National or regional prevalence is the actual percentage of the adult population (20-79 years) in a country or region that has diabetes. It is calculated by taking the estimated number of cases in adults and dividing by the total population in adults. The national prevalence should be used when reporting statistics for just one country or region, or when the statistics being reported are not for comparison.

Age-adjusted comparative prevalence, also referred to as comparative prevalence, is the prevalence calculated by adjusting to the age structure of a standard population. In the ''IDF Diabetes Atlas 10th Edition'', the standard population is the UN population for 2021, 2030 or 2045. Adjusting rates is a way to make fairer comparisons between groups with different distributions. Age-adjusted rates are rates that would have existed if the population under study had the same age distribution as the “standard” population.

Institute for Statistics, UNESCO (UIS)

2026-01-24T21:41:21Z

Norah.Shamin:

= Summary =
The United Nations Statistics Division, UIS Education Database is the most comprehensive education databse in the world, containing data from more than 200 countries and territories. The UIS has the mandate to monitor progress towards Education for All and education-related Millennium Development Goals. The statistics, which are updated twice a year, are used by diverse partners, including governments, donor agencies and other UN organizations. In particular, the UIS is the primary education data source for the Education for All Global Monitoring Report, the World Development Indicators and the Human Development Report Data is collected through the UIS annual education survey, which covers all education levels and a range of issues such as enrolment rate, gender parity, teachers, and financing.

The IFs system uses data from the UIS Education Database on a wide variety of topics relating to education. The following sections provide instructions for pulling data from the UIS Education Database for IFs pre-processor series in the Education submodule.

= Tables In IFs =

==== Preprocessors ====
{| class="wikitable"
|+
!Table
!Definition
!Name in Source
!UsedInPreprocessorFileName
!Source in Code
|-
|EDPriPTR
|Primary pupil-teacher ratio
|Enrolment in primary education, both sexes (number)/Teachers in primary education, both sexes (number)
|EDUCATION
|20062/20162
|-
|EdPriAIRFemale%
|Education, Primary, Apparent (gross) intake rate in grade 1, female (% of relevant age group)
|Gross intake ratio to the last grade of primary education, female (%)
|EDUCATION
|AIR.1.GLAST.F
|-
|EdPriAIRMale%
|Education, Primary, Apparent (gross) intake rate in grade 1, male (% of relevant age group)
|Gross intake ratio to the last grade of primary education, male (%)
|EDUCATION
|AIR.1.GLAST.M
|-
|EdPriAIRTotal%
|Education, Primary, Apparent (gross) intake rate in grade 1, total (% of relevant age group)
|Gross intake ratio to the last grade of primary education, both sexes (%)
|EDUCATION
|AIR.1.GLAST
|-
|EdPriCompletionFemale%
|Education, Primary, completion rate (school graduation age), gross, Female
|Completion rate, primary education, female (%)
|EDUCATION
|CR.1.F
|-
|EdPriCompletionMale%
|Education, Primary, completion rate (school graduation age), gross, Male
|Completion rate, primary education, male (%)
|EDUCATION
|CR.1.M
|-
|EdPriCompletionTotal%
|Education, Primary, completion rate (graduation ratio), gross, both sexes
|Completion rate, primary education, both sexes (%)
|EDUCATION
|CR.1
|-
|EdPriDuration
|Education, Primary, completion rate (graduation ratio), gross, total
|Theoretical duration of primary education (years)
|EDUCATION
|299932
|-
|EdPriEnrollGrossFemalePcnt
|Education, Primary, Enrollment Rate Gross, female
|Gross enrolment ratio, primary, female (%)
|EDUCATION
|GER.1.F
|-
|EdPriEnrollGrossMalePcnt
|Education, Primary, Enrollment Rate Gross, male
|Gross enrolment ratio, primary, male (%)
|EDUCATION
|GER.1.M
|-
|EdPriEnrollGrossTotalPcnt
|Education, Primary, Enrollment Rate Gross (% Total)
|Gross enrolment ratio, primary, both sexes (%)
|EDUCATION
|GER.1
|-
|EdPriEnrollNetFemalePcnt
|Education, Primary, Net Enrollment Rate, Female
|Total net enrolment rate, primary, female (%)
|EDUCATION
|NERT.1.F.CP
|-
|EdPriEnrollNetMalePcnt
|Education, Primary, Net Enrollment Rate, Male
|Total net enrolment rate, primary, male (%)
|EDUCATION
|NERT.1.M.CP
|-
|EdPriEnrollNetTotalPcnt
|Education, Primary, Net Enrollment Rate, Total
|Total net enrolment rate, primary, both sexes (%)
|EDUCATION
|NERT.1.CP
|-
|EdPriEntranceAge
|Education Primary Entrance Age
|Official entrance age to primary education (years)
|EDUCATION
|299905
|-
|EdPriSurvivalFemale%
|Education, Primary, percentage of entrants persisting to last grade, female
|Survival rate to the last grade of primary education, female (%)
|EDUCATION
|SR.1.GLAST.F.CP
|-
|EdPriSurvivalMale%
|Education, Primary, percentage of entrants persisting to last grade, male
|Survival rate to the last grade of primary education, male (%)
|EDUCATION
|SR.1.GLAST.M.CP
|-
|EdPriSurvivalTotal%
|Education, Primary, percentage of entrants persisting to last grade, total
|Survival rate to the last grade of primary education, both sexes (%)
|EDUCATION
|SR.1.GLAST.CP
|-
|EdSecEnrollGross%Female
|Education, Secondary, gross enrollment rate, female
|Gross enrolment ratio, secondary, female (%)
|EDUCATION
|GER.2T3.F
|-
|EdSecEnrollGross%Male
|Education, Secondary, gross enrollment rate, male
|Gross enrolment ratio, secondary, male (%)
|EDUCATION
|GER.2T3.M
|-
|EdSecEnrollGross%Total
|Education, Secondary, gross enrollment rate, total
|Gross enrolment ratio, secondary, both sexes (%)
|EDUCATION
|GER.2T3
|-
|EdSecLowerDuration
|Education Duration of Lower Secondary
|Theoretical duration of lower secondary education (years)
|EDUCATION
|999976
|-
|EdSecLowerEnrollGross%Female
|Education, Secondary, Lower, Gross Enrollment Rate All Programs, Female
|Gross enrolment ratio, lower secondary, female (%)
|EDUCATION
|GER.2.F
|-
|EdSecLowerEnrollGross%Male
|Education, Secondary, Lower, Gross Enrollment Rate All Programs, Male
|Gross enrolment ratio, lower secondary, male (%)
|EDUCATION
|GER.2.M
|-
|EdSecLowerEnrollGross%Total
|Education, Secondary, Lower, Gross Enrollment Rate, Total
|Gross enrolment ratio, lower secondary, both sexes (%)
|EDUCATION
|GER.2
|-
|EdSecLowerVoc%AllTotal
|Education, Secondary, Lower, Vocational as % of All Program Enrollments, Total
|Share of all students in lower secondary education enrolled in vocational programmes (%)
|EDUCATION
|GTVP.2.V
|-
|EdSecUpperDuration
|Education, Secondary, Upper, Duration of Upper Secondary
|Theoretical duration of upper secondary education (years)
|EDUCATION
|999978
|-
|EdSecUpperEnrollGross%Female
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Female
|Gross enrolment ratio, upper secondary, female (%)
|EDUCATION
|GER.3.F
|-
|EdSecUpperEnrollGross%Male
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Male
|Gross enrolment ratio, upper secondary, male (%)
|EDUCATION
|GER.3.M
|-
|EdSecUpperEnrollGross%Total
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Total
|Gross enrolment ratio, upper secondary, both sexes (%)
|EDUCATION
|GER.3
|-
|EdSecUpperVoc%AllTotal
|Education, Secondary, Upper, Vocational as % of All Program Enrollments, Total
|Share of all students in upper secondary education enrolled in vocational programmes (%)
|EDUCATION
|GTVP.3.V
|-
|EdTerEnrollGross%Female
|Education, Tertiary, Gross Enrollment Rate, Female
|Gross enrolment ratio for tertiary education, female (%)
|EDUCATION
|GER.5T8.F
|-
|EdTerEnrollGross%Male
|Education, Tertiary, Gross Enrollment Rate, Male
|Gross enrolment ratio for tertiary education, male (%)
|EDUCATION
|GER.5T8.M
|-
|EdTerEnrollGross%Total
|Education, Tertiary, Gross Enrollment Rate, Total
|Gross enrolment ratio for tertiary education, both sexes (%)
|EDUCATION
|GER.5T8
|-
|EdTerGradRate1stDegreeFemale%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, female
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, female (%)
|EDUCATION
|GGR.6T7.F
|-
|EdTerGradRate1stDegreeMale%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, male
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, male (%)
|EDUCATION
|GGR.6T7.M
|-
|EdTerGradRate1stDegreeTotal%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, total
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, both sexes (%)
|EDUCATION
|GGR.6T7
|-
|EdTerGrads%SciEngg
|Education, Tertiary, Science and Enginnering Graduates as % of Total Graduates
|Percentage of graduates from tertiary education graduating from Natural Sciences, Mathematics and Statistics programmes, both sexes (%)
|EDUCATION
|FOSGP.5T8.F500
|-
|GovtEdPub%GDP
|Educational expenditures (public) as percent of GDP
|Government expenditure on pre-primary education as a percentage of GDP (%) + Government expenditure on primary education as a percentage of GDP (%) + Government expenditure on lower secondary education as a percentage of GDP (%) + Government expenditure on upper secondary education as a percentage of GDP (%) + Government expenditure on post-secondary non-tertiary education as a percentage of GDP (%) + Government expenditure on tertiary education as a percentage of GDP (%)
|ECONOMY
|XGDP.02.FSGOV + XGDP.1.FSGOV + XGDP.2.FSGOV + XGDP.3.FSGOV + XGDP.4.FSGOV + XGDP.5T8.FSGOV
|-
|R&DGovt%GDP
|Gross R&D expenditure by government
|GERD as a percentage of GDP
|ECONOMY
|EXPGDP.TOT
|-
|EdExpPri%GDPPC
|Expenditure per student in primary education (% of GDP/capita)
|Initial government funding per primary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.1.FSGOV.FFNTR
|-
|EdExpSec%GDPPC
|Expenditure per student in secondary education (% of GDP/capita)
|Initial government funding per secondary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.2T3.FSGOV.FFNTR
|-
|EdExpSecLowr%GDPPC
|Expenditure per student in lower secondary education (% of GDP/capita)
|Initial government funding per lower secondary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.2.FSGOV.FFNTR
|-
|EdExpSecUppr%GDPPC
|Expenditure per student in upper secondary education (% of GDP/capita)
|Initial government funding per upper secondary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.3.FSGOV.FFNTR
|-
|EdExpTer%GDPPC
|Expenditure per student in tertiary education (% of GDP/capita)
|Initial government funding per tertiary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.5T8.FSGOV.FFNTR
|-
|EdSecLowerVoc%AllFemale
|Percentage of female students in lower secondary education enrolled in vocational programmes, female (%)
|Percentage of females in lower secondary education enrolled in vocational programs (%)
|EDUCATION
|GTVP.2.V.F
|-
|EdSecLowerVoc%AllMale
|Percentage of male students in lower secondary education enrolled in vocational programmes, male (%)
|Percentage of males in lower secondary education enrolled in vocational programs (%)
|EDUCATION
|GTVP.2.V.M
|-
|EdSecUpperGradRateAllFem
|Gross Upper Secondary Graduation Ratio, All Programmes. Female
|Completion rate, upper secondary education, female (%)
|EDUCATION
|CR.3.F
|-
|EdSecUpperGradRateAllMal
|Gross Upper Secondary Graduation Ratio, All Programmes. Male
|Completion rate, upper secondary education, male (%)
|EDUCATION
|CR.3.M
|-
|EdSecUpperGradRateAllTot
|Gross Upper Secondary Graduation Ratio, All Programmes. Total
|Completion rate, upper secondary education, both sexes (%)
|EDUCATION
|CR.3
|-
|EdSecUpperVoc%AllFemale
|Percentage of female students in upper secondary education enrolled in vocational programmes, female (%)
|Percentage of females in upper secondary enrolled in vocational programs (%)
|EDUCATION
|GTVP.3.V.F
|-
|EdSecUpperVoc%AllMale
|Percentage of male students in upper secondary education enrolled in vocational programmes, male (%)
|Percentage of males in upper secondary education enrolled in vocational programs (%)
|EDUCATION
|GTVP.3.V.M
|}

==== Non-preprocessors ====
{| class="wikitable"
|+
!Table
!Definition
!Name in Source
!Source in Code
!Formula
|-
|EdBasicEnrollGross%Female
|Education, Basic, Enrollment Rate, Gross, Female
|Gross enrolment ratio, primary and lower secondary, female (%)
|GER.1T2.F
|
|-
|EdBasicEnrollGross%Male
|Education, Basic, Enrollment Rate, Gross, Male
|Gross enrolment ratio, primary and lower secondary, male (%)
|GER.1T2.M
|
|-
|EdBasicEnrollGross%Total
|Education, Basic, Enrollment Rate, Gross, Total
|Gross enrolment ratio, primary and lower secondary, both sexes (%)
|GER.1T2
|
|-
|EdEnrollPrivate%Lower2ndaryGeneral
|Education enrollments private as % of lower secondary general
|Percentage of enrolment in lower secondary education in private institutions (%)
|PRP.2
|
|-
|EdEnrollPrivate%Primary
|Education enrollment private as % of primary
|Percentage of enrolment in primary education in private institutions (%)
|PRP.1
|
|-
|EdEnrollPrivate%Upper2ndaryGeneral
|Education enrollments private as % of upper secondary general
|Percentage of enrolment in upper secondary education in private institutions (%)
|PRP.3
|
|-
|EdEnrollPrivateAll2ndaryCombined
|Education enrollment private all secondary combined
|Percentage of enrolment in secondary education in private institutions (%)
|PRP.2T3
|
|-
|EdEnrollPrivateUpper2ndaryGeneral
|Education enrollment private upper secondary general
|Percentage of enrolment in upper secondary education in private institutions (%)
|PRP.3
|
|-
|EdExpISCED1-4Cap%
|Education expenditures, ISCED 1-4, capital portion
|Capital expenditure as a percentage of total expenditure in primary public institutions (%) + Capital expenditure as a percentage of total expenditure in lower secondary public institutions (%) + Capital expenditure as a percentage of total expenditure in upper-secondary public institutions (%) + Capital expenditure as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNCAP + XSPENDP.2.FDPUB.FNCAP + XSPENDP.3.FDPUB.FNCAP + XSPENDP.4.FDPUB.FNCAP
|
|-
|EdExpISCED1-4NonSalCur%
|Education expenditures, ISCED 1-4, non-salary current portion
|Current expenditure other than staff compensation as a percentage of total expenditure in primary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in lower secondary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in upper secondary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNNONS + XSPENDP.2.FDPUB.FNNONS + XSPENDP.3.FDPUB.FNNONS + XSPENDP.4.FDPUB.FNNONS
|
|-
|EdExpISCED1-4Sal%
|Education expenditures, ISCED 1-4, salary portion
|All staff compensation as a percentage of total expenditure in primary public institutions (%) + All staff compensation as a percentage of total expenditure in lower secondary public institutions (%) + All staff compensation as a percentage of total expenditure in upper secondary public institutions (%) + All staff compensation as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNS + XSPENDP.2.FDPUB.FNS + XSPENDP.3.FDPUB.FNS + XSPENDP.4.FDPUB.FNS
|
|-
|EdExpISCED1-4TotalCur%
|Education expenditures, ISCED 1-4, total current portion
|Current expenditure as a percentage of total expenditure in primary public institutions (%) + Current expenditure as a percentage of total expenditure in lower secondary public institutions (%) + Current expenditure as a percentage of total expenditure in upper-secondary public institutions (%) + Current expenditure as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNCUR + XSPENDP.2.FDPUB.FNCUR + XSPENDP.3.FDPUB.FNCUR + XSPENDP.4.FDPUB.FNCUR
|
|-
|EdExpPrePri%EducTot
|Educational expenditure in pre-primary as % of total educational expenditure
|Government expenditure on pre-primary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.02.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpPri%EducTot
|Education expenditure in primary as % of total educational expenditure
|Government expenditure on primary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.1.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSec%EducTot
|Education Expenditure Secondary as % of Total Educational Expenditure
|Government expenditure on secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.2T3.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSecLowr%EducTot
|Educational expenditure in lower secondary as % of total educational expenditure
|Government expenditure on lower secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.2.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSecUppr%EducTot
|Educational expenditure in upper secondary as % of total educational expenditure
|Government expenditure on upper secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.3.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpTer%EducTot
|Education Expenditure Tertiary as % of Total Educational Expenditure
|Government expenditure on tertiary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.5T8.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpTerCap%
|Education expenditures, tertiary, capital portion
|Capital expenditure as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNCAP
|
|-
|EdExpTertNonSalCur%
|Education expenditures, tertiary, non-salary current portion
|Current expenditure other than staff compensation as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNNONS
|
|-
|EdExpTertSal%
|Education expenditures, tertiary, salary portion
|All staff compensation as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNS
|
|-
|EdExpTertTotalCur%
|Education expenditures, tertiary, total current portion
|Current expenditure as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNCUR
|
|-
|EdExpectedYearsofSchooling
|Expected years of schooling for a child of school entering age
|School life expectancy, primary to tertiary, both sexes (years)
|SLE.1T8
|
|-
|EdExpectedYearsofSchoolingFemale
|Expected years of schooling for a child of school entering age, female
|School life expectancy, primary to tertiary, female (years)
|SLE.1T8.F
|
|-
|EdExpectedYearsofSchoolingMale
|Expected years of education for a child of school going age, male
|School life expectancy, primary to tertiary, male (years)
|SLE.1T8.M
|
|-
|EdPostSecDuration
|Education, Post-Secondary Non-Tertiary, Cycle Length
|Theoretical duration of post-secondary non-tertiary education (years)
|999988
|
|-
|EdPrePriDuration
|Education, Pre-Primary, Cycle Length
|Theoretical duration of pre-primary education (years)
|299929
|
|-
|EdPrePriParityGenderTeachers
|Ratio of female to male teachers in pre-primary education who are trained
|Pupil-trained teacher ratio in pre-primary education (headcount basis)
|PTRHC.02.TRAINED
|
|-
|EdPri2and3ParityGenderMath
|Ratio of girls' to boys' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.G2.GPIA + MATH.G3.GPIA
|
|-
|EdPri2and3ParityGenderRead
|Ratio of girls' to boys' reading achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.G2.GPIA + READ.G3.GPIA
|
|-
|EdPri2and3ParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.G2.LPIA + MATH.G3.LPIA
|
|-
|EdPri2and3ParityRurUrbRead
|Ratio of rural to urban students' reading achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.G2.LPIA + READ.G3.LPIA
|
|-
|EdPri2and3ParitySocioeconMath
|Ratio of students from low to high socio-economic groups' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.G2.WPIA + MATH.G3.WPIA
|
|-
|EdPri2and3ParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.G2.WPIA + READ.G3.WPIA
|
|-
|EdPriAIRParity
|Education, Primary, Apparent(gross) Intake Rate, Gender Parity Index
|Gross intake ratio to the last grade of primary education, adjusted gender parity index (GPIA)
|AIR.1.GLAST.GPIA
|
|-
|EdPriCompletionFemale
|Education, primary, completion rate from household survey data, female
|Completion rate, primary education, female (%)
|CR.1.F
|
|-
|EdPriCompletionFemale%BL
|Education, Primary, completion rate (graduation ratio), gross, Female
|Completion rate, primary education, female (%)
|CR.1.F
|
|-
|EdPriCompletionMale
|Education, primary, completion rate from household survey data, male
|Completion rate, primary education, male (%)
|CR.1.M
|
|-
|EdPriCompletionMale%BL
|Education, Primary, completion rate (graduation ratio), gross, Male
|Completion rate, primary education, male (%)
|CR.1.M
|
|-
|EdPriCompletionParity
|Education, Primary, Completion Rate, Gender Parity, New
|Completion rate, primary education, adjusted gender parity index (GPIA)
|CR.1.GPIA
|
|-
|EdPriCompletionTotal
|Education, primary, completion rate from household survey data, total
|Completion rate, primary education, both sexes (%)
|CR.1
|
|-
|EdPriCompletionTotal%BL
|Education, Primary, completion rate (graduation ratio), gross, total
|Completion rate, primary education, both sexes (%)
|CR.1
|
|-
|EdPriEnrollHeadCountTtl
|Education, Primary, Total Enrollment (male plus female)
|Enrolment in primary education, both sexes (number)
|20062
|*0.000001
|-
|EdPriEnrollHeadcountFem
|Female enrollment at primary level, in both public and private institutions
|Enrolment in primary education, female (number)
|20063
|*0.000001
|-
|EdPriEnrollHeadcountMal
|Male enrollment, primary level, in both public and private institutions
|Enrolment in primary education, male (number)
|40035
|*0.000001
|-
|EdPriEnrollNetParity
|Education, Primary, Net Enrollment Rate, Gender Parity Index
|Total net enrolment rate, primary, adjusted gender parity index (GPIA)
|NERT.1.GPIA
|
|-
|EdPriOutofSchoolFemale%
|Education primary, percentage of primary age children who are out of school, Female
|Out-of-school rate for children of primary school age, female (%)
|ROFST.1.F.CP
|
|-
|EdPriOutofSchoolMale%
|Education primary, percentage of primary age children who are out of school, Male
|Out-of-school rate for children of primary school age, male (%)
|ROFST.1.M.CP
|
|-
|EdPriOutofSchoolTotal%
|Education primary, percentage of primary age children who are out of school, total
|Out-of-school rate for children of primary school age, both sexes (%)
|ROFST.1.CP
|
|-
|EdPriParityGenderMath
|Ratio of girls' to boys' mathematics achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.PRIMARY.GPIA
|
|-
|EdPriParityGenderRead
|Ratio of girls' to boys' reading achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.PRIMARY.GPIA
|
|-
|EdPriParityGenderTeachers
|Ratio of female to male teachers in primary education who are trained
|Pupil-trained teacher ratio in primary education (headcount basis)
|PTRHC.1.TRAINED
|
|-
|EdPriParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.PRIMARY.LPIA
|
|-
|EdPriParityRurUrbRead
|Ratio of rural to urban students' reading achievement by the end of primary
|Proportion of students at the end of primary education achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.PRIMARY.LPIA
|
|-
|EdPriParitySocioeconMath
|Ratio of students from low to high socio-economic groups' achievement in mathematics by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.PRIMARY.WPIA
|
|-
|EdPriParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading by the end of primary
|Proportion of students at the end of primary education achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.PRIMARY.WPIA
|
|-
|EdPriRepeater1stYearFemale%
|Percentage of repeaters in primary. Grade 1.Female
|Repetition rate in Grade 1 of primary education, female (%)
|REPR.1.G1.F.CP
|
|-
|EdPriRepeater1stYearMale%
|Percentage of repeaters in primary. Grade 1.Male
|Repetition rate in Grade 1 of primary education, male (%)
|REPR.1.G1.M.CP
|
|-
|EdPriRepeater1stYearTotal%
|Percentage of repeaters in primary. Grade 1. Total
|Repetition rate in Grade 1 of primary education, both sexes (%)
|REPR.1.G1.CP
|
|-
|EdPriRepeaterFemale%
|Education Primary Percentage of Repeaters, all grades, female
|Repetition rate in primary education (all grades), female (%)
|REPR.1.F.CP
|
|-
|EdPriRepeaterMale%
|Education Primary Percentage of Repeaters, all grades, male
|Repetition rate in primary education (all grades), male (%)
|REPR.1.M.CP
|
|-
|EdPriRepeaterTotal%
|Education Primary Percentage of Repeaters, all grades, total
|Repetition rate in primary education (all grades), both sexes (%)
|REPR.1.CP
|
|-
|EdPriSurvivalParity
|Education, Primary, Survival to Last Grade, Gender Parity, New
|Survival rate to the last grade of primary education,adjusted gender parity index (GPIA)
|SR.1.GLAST.GPIA
|
|-
|EdSecDuration
|Duration of education, secondary
|Theoretical duration of secondary education (years)
|THDUR.2T3
|
|-
|EdSecEnrNoFem
|Education, secondary Enrollment Number, Female
|Enrolment in secondary education, female (number)
|20083
|*0.000001
|-
|EdSecEnrNoMal
|Education, secondary Enrollment Number, Male
|Enrolment in secondary education, male (number)
|40044
|*0.000001
|-
|EdSecEnrNoTot
|Education, Total Secondary, Total Enrollment (male plus female)
|Enrolment in secondary education, both sexes (number)
|20082
|*0.000001
|-
|EdSecEnrollGross%Parity
|secondary gross enrollment rate, all programs, Gender Parity Index, new data
|Gross enrolment ratio, secondary, adjusted gender parity index (GPIA)
|GER.2T3.GPIA
|
|-
|EdSecLowerAdultGrads25Female%
|Adult population (25 and over) with lower secondary (or more) education, female%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, female (%)
|EA.2T8.AG25T99.F
|
|-
|EdSecLowerAdultGrads25Male%
|Adult population (25 and over) with lower secondary (or more) education, male%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, male (%)
|EA.2T8.AG25T99.M
|
|-
|EdSecLowerAdultGrads25Total%
|Adult population (25 and over) with lower secondary (or more) education, total%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, both sexes (%)
|EA.2T8.AG25T99
|
|-
|EdSecLowerEnrollGrossParity
|Gender parity index for gross enrolment ratio. Lower secondary. All programmes
|Gross enrolment ratio, lower secondary, adjusted gender parity index (GPIA)
|GER.2.GPIA
|
|-
|EdSecLowerEnrollHeadcountFemale
|Education, lower secondary, headcount enrollment number, female
|Enrolment in lower secondary education, female (number)
|20065
|*0.000001
|-
|EdSecLowerEnrollHeadcountMale
|Education, lower secondary, headcount enrollment number , male
|Enrolment in lower secondary education, male (number)
|40038
|*0.000001
|-
|EdSecLowerEnrollHeadcountTotal
|Education, Lower Secondary, Total Enrollment (male plus female)
|Enrolment in lower secondary education, both sexes (number)
|20064
|*0.000001
|-
|EdSecLowerNetEnrollFemale%
|Net Lower Secondary Enrollment Rate, Female
|Total net enrolment rate, lower secondary, female (%)
|NERT.2.F.CP
|
|-
|EdSecLowerNetEnrollMale%
|Net Lower Secondary Enrollment Rate, Male
|Total net enrolment rate, lower secondary, male (%)
|NERT.2.M.CP
|
|-
|EdSecLowerNetEnrollTot%
|Net Lower Secondary Enrollment Rate, Total
|Total net enrolment rate, lower secondary, both sexes (%)
|NERT.2.CP
|
|-
|EdSecLowrCompletionFemale
|Education, lower secondary, completion rate from household survey data, female
|Completion rate, lower secondary education, female (%)
|CR.2.F
|
|-
|EdSecLowrCompletionMale
|Education, lower secondary, completion rate from household survey data, male
|Completion rate, lower secondary education, male (%)
|CR.2.M
|
|-
|EdSecLowrCompletionTotal
|Education, lower secondary, completion rate from household survey data, total
|Completion rate, lower secondary education, both sexes (%)
|CR.2
|
|-
|EdSecLowrPTR
|Education, lower secondary, pupil teacher ratio
|Enrolment in lower secondary education, both sexes (number)/Teachers in lower secondary education, both sexes (number)
|20064/20164
|
|-
|EdSecLwrParityGenderMath
|Ratio of girls' to boys' mathematics achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.LOWERSEC.GPIA
|
|-
|EdSecLwrParityGenderRead
|Ratio of girls' to boys' reading achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.LOWERSEC.GPIA
|
|-
|EdSecLwrParityGenderTeachers
|Ratio of female to male teachers in lower secondary who are trained
|Pupil-trained teacher ratio in lower secondary education (headcount basis)
|PTRHC.2.TRAINED
|
|-
|EdSecLwrParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.LOWERSEC.LPIA
|
|-
|EdSecLwrParityRurUrbRead
|Ratio of rural to urban students' reading achievement by the end of lower secondary
|Proportion of students at the end of lower secondary education achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.LOWERSEC.LPIA
|
|-
|EdSecLwrParitySocioeconMath
|Ratio of students from low to high socio-economic groups' achievement in mathematics by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.LOWERSEC.WPIA
|
|-
|EdSecLwrParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading by the end of lower secondary
|Proportion of students at the end of lower secondary education achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.LOWERSEC.WPIA
|
|-
|EdSecUpperEnrollGrossParity
|Gender parity index for gross enrolment ratio. Upper secondary. All programmes
|Gross enrolment ratio, upper secondary, adjusted gender parity index (GPIA)
|GER.3.GPIA
|
|-
|EdSecUpperEnrollGrossParityNew
|Gender parity index for gross enrolment ratio. Upper secondary. All programmes
|Gross enrolment ratio, upper secondary, adjusted gender parity index (GPIA)
|GER.3.GPIA
|
|-
|EdSecUpperEnrollHeadCountMale
|Education, upper secondary, headcount enrollment number , male
|Enrolment in upper secondary education, male (number)
|40041
|*0.000001
|-
|EdSecUpperEnrollHeadcountFemale
|Education, upper secondary, headcount enrollment number, female
|Enrolment in upper secondary education, female (number)
|20071
|*0.000001
|-
|EdSecUpperEnrollHeadcountTotal
|Education, Upper Secondary, Total Enrollment (male plus female)
|Enrolment in upper secondary education, both sexes (number)
|20070
|*0.000001
|-
|EdSecUpperNetEnrollFemale%
|Net Upper Secondary Enrollment, Female
|Total net enrolment rate, upper secondary, female (%)
|NERT.3.F.CP
|
|-
|EdSecUpperNetEnrollMale%
|Net Upper Secondary Enrollment Rate, Male
|Total net enrolment rate, upper secondary, male (%)
|NERT.3.M.CP
|
|-
|EdSecUpperNetEnrollTot%
|Net Upper Secondary Enrollment Rate, Total
|Total net enrolment rate, upper secondary, both sexes (%)
|NERT.3.CP
|
|-
|EdSecUpperParityGenderTeachers
|Ratio of female to male teachers in upper secondary education who are trained
|Pupil-trained teacher ratio in upper secondary education (headcount basis)
|PTRHC.3.TRAINED
|
|-
|EdSecUpprCompletionFemale
|Education, upper secondary, completion rate from household survey data, female
|Completion rate, upper secondary education, female (%)
|CR.3.F
|
|-
|EdSecUpprCompletionMale
|Education, upper secondary, completion rate from household survey data, male
|Completion rate, upper secondary education, male (%)
|CR.3.M
|
|-
|EdSecUpprCompletionTotal
|Education, upper secondary, completion rate from household survey data, total
|Completion rate, upper secondary education, both sexes (%)
|CR.3
|
|-
|EdSecVoc%Tot
|Education Secondary, technical or vocational enrollment as percentage of all programs, total
|Share of all students in secondary education enrolled in vocational programmes (%)
|GTVP.2T3.V
|
|-
|EdTerEnrISCED6HdctFem
|Education, 6 Tertiary, Enrollment headcount, Female
|Enrolment in tertiary education, ISCED 6 programmes, female (number)
|42635
|*0.000001
|-
|EdTerEnrISCED6HdctMale
|Education, 6 Tertiary, Enrollment headcount, Male
|Enrolment in tertiary education, ISCED 6 programmes, male (number)
|42615
|*0.000001
|-
|EdTerEnrISCED6HdctTot
|Education, 6 Tertiary, Enrollment headcount, Total
|Enrolment in tertiary education, ISCED 6 programmes, both sexes (number)
|42654
|*0.000001
|-
|EdTerEnrollHeadcountFem
|Education, Tertiary, Enrollment Headcount, Female
|Enrolment in tertiary education, all programmes, female (number)
|25057
|*0.000001
|-
|EdTerEnrollHeadcountMale
|Education, Tertiary, Enrollment Headcount, Male
|Enrolment in tertiary education, all programmes, male (number)
|42620
|*0.000001
|-
|EdTerEnrollHeadcountTotal
|Education, Tertiary, Enrollment Headcount, Total
|Enrolment in tertiary education, all programmes, both sexes (number)
|25053
|*0.000001
|-
|EdTerFemaleMaleRatio
|Ratio of females to males in tertiary education
|Gross enrolment ratio for tertiary education, adjusted gender parity index (GPIA)
|GER.5T8.GPIA
|
|-
|EdTerGrads%Ag
|Education, Tertiary, Agriculture Graduates as % of total graduates
|Percentage of graduates from tertiary education graduating from Agriculture, Forestry, Fisheries and Veterinary programmes, both sexes (%)
|FOSGP.5T8.F800
|
|-
|EdTerGrads%Engg
|Education, Tertiary, Engineering, Manufacturing and Construction as % of total graduates
|Percentage of graduates from tertiary education graduating from Engineering, Manufacturing and Construction programmes, both sexes (%)
|FOSGP.5T8.F700
|
|-
|EdTerGrads%Health
|Education, Tertiary, Health and Welfare Graduates as % of total graduates
|Percentage of graduates from tertiary education graduating from Health and Welfare programmes, both sexes (%)
|FOSGP.5T8.F900
|
|-
|EdTerGrads%Sci
|Education, Tertiary, Science Graduates as % of total graduates
|Percentage of graduates from Science, Technology, Engineering and Mathematics programmes in tertiary education, both sexes (%) + Percentage of graduates from tertiary education graduating from Information and Communication Technologies programmes, both sexes (%)
|FOSGP.5T8.F500 + FOSGP.5T8.F600
|
|-
|PupilTeacherRatioUISPrimary
|Pupil teacher ratio in primary education
|Enrolment in primary education, both sexes (number)/Teachers in primary education, both sexes (number)
|20062/20162
|
|-
|PupilTeacherRatioUISSecondary
|Pupil teacher ratio in secondary education
|Enrolment in secondary education, both sexes (number)/Teachers in secondary education, both sexes (number)
|20082/20182
|
|-
|PupilTrainedTeacherRatioUISPrimary
|Pupil to trained teacher ratio in primary education
|Pupil-trained teacher ratio in primary education (headcount basis)
|PTRHC.1.TRAINED
|
|-
|PupilTrainedTeacherRatioUISSecondary
|Pupil toTrained teacher ratio in secondary education
|Pupil-trained teacher ratio in secondary education (headcount basis)
|PTRHC.2T3.TRAINED
|
|-
|EdSecLowrRpt%Gr1BothSexes
|Repetition rate in Grade 1 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 1 of lower secondary general education, both sexes (%)
|REPR.2.G1.CP
|
|-
|EdSecLowrRpt%Gr1Female
|Repetition rate in Grade 1 of lower secondary general education, female (%)
|Repetition rate in Grade 1 of lower secondary general education, female (%)
|REPR.2.G1.F.CP
|
|-
|EdSecLowrRpt%Gr1Male
|Repetition rate in Grade 1 of lower secondary general education, male (%)
|Repetition rate in Grade 1 of lower secondary general education, male (%)
|REPR.2.G1.M.CP
|
|-
|EdSecLowrRpt%Gr2BothSexes
|Repetition rate in Grade 2 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 2 of lower secondary general education, both sexes (%)
|REPR.2.G2.CP
|
|-
|EdSecLowrRpt%Gr2Female
|Repetition rate in Grade 2 of lower secondary general education, female (%)
|Repetition rate in Grade 2 of lower secondary general education, female (%)
|REPR.2.G2.F.CP
|
|-
|EdSecLowrRpt%Gr2Male
|Repetition rate in Grade 2 of lower secondary general education, male (%)
|Repetition rate in Grade 2 of lower secondary general education, male (%)
|REPR.2.G2.M.CP
|
|-
|EdSecLowrRpt%Gr3BothSexes
|Repetition rate in Grade 3 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 3 of lower secondary general education, both sexes (%)
|REPR.2.G3.CP
|
|-
|EdSecLowrRpt%Gr3Female
|Repetition rate in Grade 3 of lower secondary general education, female (%)
|Repetition rate in Grade 3 of lower secondary general education, female (%)
|REPR.2.G3.F.CP
|
|-
|EdSecLowrRpt%Gr3Male
|Repetition rate in Grade 3 of lower secondary general education, male (%)
|Repetition rate in Grade 3 of lower secondary general education, male (%)
|REPR.2.G3.M.CP
|
|-
|EdSecLowrRpt%Gr4BothSexes
|Repetition rate in Grade 4 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 4 of lower secondary general education, both sexes (%)
|REPR.2.G4.CP
|
|-
|EdSecLowrRpt%Gr4Female
|Repetition rate in Grade 4 of lower secondary general education, female (%)
|Repetition rate in Grade 4 of lower secondary general education, female (%)
|REPR.2.G4.F.CP
|
|-
|EdSecLowrRpt%Gr4Male
|Repetition rate in Grade 4 of lower secondary general education, male (%)
|Repetition rate in Grade 4 of lower secondary general education, male (%)
|REPR.2.G4.M.CP
|
|-
|EdSecLowrRpt%Gr5BothSexes
|Repetition rate in Grade 5 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 5 of lower secondary general education, both sexes (%)
|REPR.2.G5.CP
|
|-
|EdSecLowrRpt%Gr5Female
|Repetition rate in Grade 5 of lower secondary general education, female (%)
|Repetition rate in Grade 5 of lower secondary general education, female (%)
|REPR.2.G5.F.CP
|
|-
|EdSecLowrRpt%Gr5Male
|Repetition rate in Grade 5 of lower secondary general education, male (%)
|Repetition rate in Grade 5 of lower secondary general education, male (%)
|REPR.2.G5.M.CP
|
|-
|EdSecLowrRpt%GrAllBothSexes
|Repetition rate in lower secondary general education (all grades), both sexes (%)
|Repetition rate in lower secondary general education (all grades), both sexes (%)
|REPR.2.CP
|
|-
|EdSecLowrRpt%GrAllFemale
|Repetition rate in lower secondary general education (all grades), female (%)
|Repetition rate in lower secondary general education (all grades), female (%)
|REPR.2.F.CP
|
|-
|EdSecLowrRpt%GrAllMale
|Repetition rate in lower secondary general education (all grades), male (%)
|Repetition rate in lower secondary general education (all grades), male (%)
|REPR.2.M.CP
|
|-
|add calebs tables here
|
|
|
|
|}
= Data Pulling Instructions =

# Go to https://databrowser.uis.unesco.org/resources/bulk
# Download Education SDG, Education Other Policy Relevant Indicators, and R&D SDG
## Under SDG 4 Education - Global and Thematic Indicators find file: SDG
## Under Other Policy Relevant Indicators (OPRI) find file: OPRI
## Under SDG 9.5 - Research and Development (R&D) find file: SCN-SDG
## Upzip the downloaded files.
### Use {File name}_COUNTRY.csv to prepare country concordance table.
### Use {File name}_NATIONAL.csv to extract series.
### Use {File name}_LABEL.csv to check the definition of the "INDICATOR_ID" listed below.[[File:Files in Zipped Folder.png|none|thumb|600x600px]]
##You can use the code in this GitHub to help pull the data: https://github.com/n1shamin/UIS-UNESCO

= Data Notes =
#As of May 2016, there was no data for 2015 for the LowerVoc series, only 1999-2014. However, there was 2015 data for the UpperVoc series.
#Country Concordance: UNESCO countries.
##As of March 2017, UIS utilizes "Cabo Verde" instead of "Cape Verde." The UNESCO Country Concordance utilizes "Cape Verde. "'''You thus must replace "Cabo Verde" with "Cape Verde" in UIS data prior to importing into IFs.'''
#Below are the coding for each table; i.e. source in code and files each tables is in.
= Coding =
Notes:

2. Series need to be calculated: PupilTeacherRatioUISPrimary, PupilTeacherRatioUISSecondary, EDPriPTR, EdSecLowrPTR, EdExpPrePri%EducTot, EdExpPri%EducTot, EdExpSecLowr%EducTot, EdExpSec%EducTot, EdExpSecUppr%EducTot, EdExpTer%EducTot, EdTerGrads%Sci, GovtEdPub%GDP, EdExpISCED1-4Cap%, EdExpISCED1-4TotalCur%, EdExpISCED1-4NonSalCur%, EdExpISCED1-4Sal%

3. All the series in "Enrollment Headcount" need to *0.000001 to convert to "Millions".

4. Item Understanding in INDICATOR_ID:
{| class="wikitable"
|Item
|Meaning
|-
|02
|pre-primary
|-
|1
|primary
|-
|2
|lower secondary
|-
|3
|upper secondary
|-
|2T3
|secondary
|-
|4
|post-secondary non-tertiary
|-
|5T8
|tertiary
|-
|6T7
|ISCED 6 and 7
|-
|1T8
|primary to tertiary
|-
|F
|female
|-
|M
|male
|-
|GPIA
|adjusted gender parity index
|-
|LPIA
|adjusted location parity index
|-
|WPIA
|adjusted wealth parity index
|-
|G1
|Grade 1
|-
|G2T3
|Grade 2 or 3
|-
|GLAST
|last grade
|-
|F500
|Natural Sciences, Mathematics and Statistics
|-
|F600
|Information and Communication Technologies
|-
|F700
|Engineering, Manufacturing and Construction
|-
|F800
|Agriculture, Forestry, Fisheries and Veterinary
|-
|F900
|Health and Welfare
|}
{| class="wikitable"
|Variable
|Type
|File
|INDICATOR_ID
|UsedInPreprocessor
|UsedInPreprocessorFileName
|-
|EdPriCompletionTotal%
|Completion rate
|SDG
|CR.1
|1
|EDUCATION
|-
|EdPriCompletionFemale%
|Completion rate
|SDG
|CR.1.F
|1
|EDUCATION
|-
|EdPriCompletionMale%
|Completion rate
|SDG
|CR.1.M
|1
|EDUCATION
|-
|EdPriCompletionTotal
|Completion rate
|SDG
|CR.1
|0
|
|-
|EdPriCompletionTotal%BL
|Completion rate
|SDG
|CR.1
|0
|
|-
|EdPriCompletionFemale
|Completion rate
|SDG
|CR.1.F
|0
|
|-
|EdPriCompletionFemale%BL
|Completion rate
|SDG
|CR.1.F
|0
|
|-
|EdPriCompletionParity
|Completion rate
|SDG
|CR.1.GPIA
|0
|
|-
|EdPriCompletionMale
|Completion rate
|SDG
|CR.1.M
|0
|
|-
|EdPriCompletionMale%BL
|Completion rate
|SDG
|CR.1.M
|0
|
|-
|EdSecLowrCompletionTotal
|Completion rate
|SDG
|CR.2
|0
|
|-
|EdSecLowrCompletionFemale
|Completion rate
|SDG
|CR.2.F
|0
|
|-
|EdSecLowrCompletionMale
|Completion rate
|SDG
|CR.2.M
|0
|
|-
|EdSecUpprCompletionTotal
|Completion rate
|SDG
|CR.3
|0
|
|-
|EdSecUpprCompletionFemale
|Completion rate
|SDG
|CR.3.F
|0
|
|-
|EdSecUpprCompletionMale
|Completion rate
|SDG
|CR.3.M
|0
|
|-
|EdPriDuration
|Duration
|OPRI
|299932
|1
|EDUCATION
|-
|EdSecLowerDuration
|Duration
|OPRI
|999976
|1
|EDUCATION
|-
|EdSecUpperDuration
|Duration
|OPRI
|999978
|1
|EDUCATION
|-
|EdPrePriDuration
|Duration
|OPRI
|299929
|0
|
|-
|EdPostSecDuration
|Duration
|OPRI
|999988
|0
|
|-
|EdSecDuration
|Duration
|OPRI
|THDUR.2T3
|0
|
|-
|EdExpISCED1-4Cap%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNCAP + XSPENDP.2.FDPUB.FNCAP + XSPENDP.3.FDPUB.FNCAP + XSPENDP.4.FDPUB.FNCAP
|0
|
|-
|EdExpISCED1-4TotalCur%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNCUR + XSPENDP.2.FDPUB.FNCUR + XSPENDP.3.FDPUB.FNCUR + XSPENDP.4.FDPUB.FNCUR
|0
|
|-
|EdExpISCED1-4NonSalCur%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNNONS + XSPENDP.2.FDPUB.FNNONS + XSPENDP.3.FDPUB.FNNONS + XSPENDP.4.FDPUB.FNNONS
|0
|
|-
|EdExpISCED1-4Sal%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNS + XSPENDP.2.FDPUB.FNS + XSPENDP.3.FDPUB.FNS + XSPENDP.4.FDPUB.FNS
|0
|
|-
|EdExpTerCap%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNCAP
|0
|
|-
|EdExpTertTotalCur%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNCUR
|0
|
|-
|EdExpTertNonSalCur%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNNONS
|0
|
|-
|EdExpTertSal%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNS
|0
|
|-
|EdSecLowerAdultGrads25Total%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99
|0
|
|-
|EdSecLowerAdultGrads25Female%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99.F
|0
|
|-
|EdSecLowerAdultGrads25Male%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99.M
|0
|
|-
|EdPriEnrollHeadCountTtl
|Enrollment Headcount
|OPRI
|20062
|0
|
|-
|EdPriEnrollHeadcountFem
|Enrollment Headcount
|OPRI
|20063
|0
|
|-
|EdSecLowerEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|20064
|0
|
|-
|EdSecLowerEnrollHeadcountFemale
|Enrollment Headcount
|OPRI
|20065
|0
|
|-
|EdSecUpperEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|20070
|0
|
|-
|EdSecUpperEnrollHeadcountFemale
|Enrollment Headcount
|OPRI
|20071
|0
|
|-
|EdSecEnrNoTot
|Enrollment Headcount
|OPRI
|20082
|0
|
|-
|EdSecEnrNoFem
|Enrollment Headcount
|OPRI
|20083
|0
|
|-
|EdTerEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|25053
|0
|
|-
|EdTerEnrollHeadcountFem
|Enrollment Headcount
|OPRI
|25057
|0
|
|-
|EdPriEnrollHeadcountMal
|Enrollment Headcount
|OPRI
|40035
|0
|
|-
|EdSecLowerEnrollHeadcountMale
|Enrollment Headcount
|OPRI
|40038
|0
|
|-
|EdSecUpperEnrollHeadCountMale
|Enrollment Headcount
|OPRI
|40041
|0
|
|-
|EdSecEnrNoMal
|Enrollment Headcount
|OPRI
|40044
|0
|
|-
|EdTerEnrISCED6HdctMale
|Enrollment Headcount
|OPRI
|42615
|0
|
|-
|EdTerEnrollHeadcountMale
|Enrollment Headcount
|OPRI
|42620
|0
|
|-
|EdTerEnrISCED6HdctFem
|Enrollment Headcount
|OPRI
|42635
|0
|
|-
|EdTerEnrISCED6HdctTot
|Enrollment Headcount
|OPRI
|42654
|0
|
|-
|GovtEdPub%GDP
|Government Expenditure
|OPRI
|XGDP.02.FSGOV + XGDP.1.FSGOV + XGDP.2.FSGOV + XGDP.3.FSGOV + XGDP.4.FSGOV + XGDP.5T8.FSGOV
|1
|ECONOMY
|-
|EdExpPrePri%EducTot
|Government Expenditure
|OPRI
|X.USCONST.02.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpPri%EducTot
|Government Expenditure
|OPRI
|X.USCONST.1.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSecLowr%EducTot
|Government Expenditure
|OPRI
|X.USCONST.2.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSec%EducTot
|Government Expenditure
|OPRI
|X.USCONST.2T3.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSecUppr%EducTot
|Government Expenditure
|OPRI
|X.USCONST.3.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpTer%EducTot
|Government Expenditure
|OPRI
|X.USCONST.5T8.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdPriEnrollGrossTotalPcnt
|Gross enrolment ratio
|OPRI
|GER.1
|1
|EDUCATION
|-
|EdPriEnrollGrossFemalePcnt
|Gross enrolment ratio
|OPRI
|GER.1.F
|1
|EDUCATION
|-
|EdPriEnrollGrossMalePcnt
|Gross enrolment ratio
|OPRI
|GER.1.M
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.2
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.2.F
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.2.M
|1
|EDUCATION
|-
|EdSecEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.2T3
|1
|EDUCATION
|-
|EdSecEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.2T3.F
|1
|EDUCATION
|-
|EdSecEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.2T3.M
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.3
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.3.F
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.3.M
|1
|EDUCATION
|-
|EdTerEnrollGross%Total
|Gross enrolment ratio
|SDG
|GER.5T8
|1
|EDUCATION
|-
|EdTerEnrollGross%Female
|Gross enrolment ratio
|SDG
|GER.5T8.F
|1
|EDUCATION
|-
|EdTerEnrollGross%Male
|Gross enrolment ratio
|SDG
|GER.5T8.M
|1
|EDUCATION
|-
|EdBasicEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.1T2
|0
|
|-
|EdBasicEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.1T2.F
|0
|
|-
|EdBasicEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.1T2.M
|0
|
|-
|EdSecLowerEnrollGrossParity
|Gross enrolment ratio
|OPRI
|GER.2.GPIA
|0
|
|-
|EdSecEnrollGross%Parity
|Gross enrolment ratio
|OPRI
|GER.2T3.GPIA
|0
|
|-
|EdSecUpperEnrollGrossParity
|Gross enrolment ratio
|OPRI
|GER.3.GPIA
|0
|
|-
|EdSecUpperEnrollGrossParityNew
|Gross enrolment ratio
|OPRI
|GER.3.GPIA
|0
|
|-
|EdTerFemaleMaleRatio
|Gross enrolment ratio
|SDG
|GER.5T8.GPIA
|0
|
|-
|EdTerGradRate1stDegreeTotal%
|Gross graduation ratio
|OPRI
|GGR.6T7
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeFemale%
|Gross graduation ratio
|OPRI
|GGR.6T7.F
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeMale%
|Gross graduation ratio
|OPRI
|GGR.6T7.M
|1
|EDUCATION
|-
|EdPriAIRTotal%
|Gross intake ratio
|SDG
|AIR.1.GLAST
|1
|EDUCATION
|-
|EdPriAIRFemale%
|Gross intake ratio
|SDG
|AIR.1.GLAST.F
|1
|EDUCATION
|-
|EdPriAIRMale%
|Gross intake ratio
|SDG
|AIR.1.GLAST.M
|1
|EDUCATION
|-
|EdPriAIRParity
|Gross intake ratio
|SDG
|AIR.1.GLAST.GPIA
|0
|
|-
|EdPri2and3ParityGenderMath
|MATH
|SDG
|MATH.G2T3.GPIA
|0
|
|-
|EdPri2and3ParityRurUrbMath
|MATH
|SDG
|MATH.G2T3.LPIA
|0
|
|-
|EdPri2and3ParitySocioeconMath
|MATH
|SDG
|MATH.G2T3.WPIA
|0
|
|-
|EdSecLwrParityGenderMath
|MATH
|SDG
|MATH.LOWERSEC.GPIA
|0
|
|-
|EdSecLwrParityRurUrbMath
|MATH
|SDG
|MATH.LOWERSEC.LPIA
|0
|
|-
|EdSecLwrParitySocioeconMath
|MATH
|SDG
|MATH.LOWERSEC.WPIA
|0
|
|-
|EdPriParityGenderMath
|MATH
|SDG
|MATH.PRIMARY.GPIA
|0
|
|-
|EdPriParityRurUrbMath
|MATH
|SDG
|MATH.PRIMARY.LPIA
|0
|
|-
|EdPriParitySocioeconMath
|MATH
|SDG
|MATH.PRIMARY.WPIA
|0
|
|-
|EdPriEntranceAge
|Official entrance age
|OPRI
|299905
|1
|EDUCATION
|-
|EdPriOutofSchoolTotal%
|Out-of-school rate
|SDG
|ROFST.1.CP
|0
|
|-
|EdPriOutofSchoolFemale%
|Out-of-school rate
|SDG
|ROFST.1.F.CP
|0
|
|-
|EdPriOutofSchoolMale%
|Out-of-school rate
|SDG
|ROFST.1.M.CP
|0
|
|-
|EdEnrollPrivate%Primary
|Percentage of enrolment in private
|OPRI
|PRP.1
|0
|
|-
|EdEnrollPrivate%Lower2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.2
|0
|
|-
|EdEnrollPrivateAll2ndaryCombined
|Percentage of enrolment in private
|OPRI
|PRP.2T3
|0
|
|-
|EdEnrollPrivate%Upper2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.3
|0
|
|-
|EdEnrollPrivateUpper2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.3
|0
|
|-
|EdTerGrads%SciEngg
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F500
|1
|EDUCATION
|-
|EdTerGrads%Sci
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F500 + FOSGP.5T8.600
|0
|
|-
|EdTerGrads%Engg
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F700
|0
|
|-
|EdTerGrads%Ag
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F800
|0
|
|-
|EdTerGrads%Health
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F900
|0
|
|-
|EDPriPTR
|PTR
|OPRI
|20062/20162
|1
|EDUCATION
|-
|PupilTeacherRatioUISPrimary
|PTR
|OPRI
|20062/20162
|0
|
|-
|EdSecLowrPTR
|PTR
|OPRI
|20064/20164
|0
|
|-
|PupilTeacherRatioUISSecondary
|PTR
|OPRI
|20082/20182
|0
|
|-
|EdPrePriParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.02.TRAINED
|0
|
|-
|EdPriParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.1.TRAINED
|0
|
|-
|PupilTrainedTeacherRatioUISPrimary
|Pupil-trained teacher ratio
|SDG
|PTRHC.1.TRAINED
|0
|
|-
|EdSecLwrParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.2.TRAINED
|0
|
|-
|PupilTrainedTeacherRatioUISSecondary
|Pupil-trained teacher ratio
|SDG
|PTRHC.2T3.TRAINED
|0
|
|-
|EdSecUpperParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.3.TRAINED
|0
|
|-
|R&DGovt%GDP
|R&D%GDP
|SCN-SDG
|EXPGDP.TOT
|1
|ECONOMY
|-
|EdPri2and3ParityGenderRead
|READ
|SDG
|READ.G2T3.GPIA
|0
|
|-
|EdPri2and3ParityRurUrbRead
|READ
|SDG
|READ.G2T3.LPIA
|0
|
|-
|EdPri2and3ParitySocioeconRead
|READ
|SDG
|READ.G2T3.WPIA
|0
|
|-
|EdSecLwrParityGenderRead
|READ
|SDG
|READ.LOWERSEC.GPIA
|0
|
|-
|EdSecLwrParityRurUrbRead
|READ
|SDG
|READ.LOWERSEC.LPIA
|0
|
|-
|EdSecLwrParitySocioeconRead
|READ
|SDG
|READ.LOWERSEC.WPIA
|0
|
|-
|EdPriParityGenderRead
|READ
|SDG
|READ.PRIMARY.GPIA
|0
|
|-
|EdPriParityRurUrbRead
|READ
|SDG
|READ.PRIMARY.LPIA
|0
|
|-
|EdPriParitySocioeconRead
|READ
|SDG
|READ.PRIMARY.WPIA
|0
|
|-
|EdPriRepeaterTotal%
|Repetition rate
|OPRI
|REPR.1.CP
|0
|
|-
|EdPriRepeaterFemale%
|Repetition rate
|OPRI
|REPR.1.F.CP
|0
|
|-
|EdPriRepeater1stYearTotal%
|Repetition rate
|OPRI
|REPR.1.G1.CP
|0
|
|-
|EdPriRepeater1stYearFemale%
|Repetition rate
|OPRI
|REPR.1.G1.F.CP
|0
|
|-
|EdPriRepeater1stYearMale%
|Repetition rate
|OPRI
|REPR.1.G1.M.CP
|0
|
|-
|EdPriRepeaterMale%
|Repetition rate
|OPRI
|REPR.1.M.CP
|0
|
|-
|EdExpectedYearsofSchooling
|School life expectancy
|OPRI
|SLE.1T8
|0
|
|-
|EdExpectedYearsofSchoolingFemale
|School life expectancy
|OPRI
|SLE.1T8.F
|0
|
|-
|EdExpectedYearsofSchoolingMale
|School life expectancy
|OPRI
|SLE.1T8.M
|0
|
|-
|EdSecLowerVoc%AllTotal
|Share of all students in vocational programmes
|OPRI
|GTVP.2.V
|1
|EDUCATION
|-
|EdSecUpperVoc%AllTotal
|Share of all students in vocational programmes
|OPRI
|GTVP.3.V
|1
|EDUCATION
|-
|EdSecVoc%Tot
|Share of all students in vocational programmes
|OPRI
|GTVP.2T3.V
|0
|
|-
|EdPriSurvivalTotal%
|Survival rate
|OPRI
|SR.1.GLAST.CP
|1
|EDUCATION
|-
|EdPriSurvivalFemale%
|Survival rate
|OPRI
|SR.1.GLAST.F.CP
|1
|EDUCATION
|-
|EdPriSurvivalMale%
|Survival rate
|OPRI
|SR.1.GLAST.M.CP
|1
|EDUCATION
|-
|EdPriSurvivalParity
|Survival rate
|OPRI
|SR.1.GLAST.GPIA
|0
|
|-
|EdPriEnrollNetTotalPcnt
|Total net enrolment rate
|OPRI
|NERT.1.CP
|1
|EDUCATION
|-
|EdPriEnrollNetFemalePcnt
|Total net enrolment rate
|OPRI
|NERT.1.F.CP
|1
|EDUCATION
|-
|EdPriEnrollNetMalePcnt
|Total net enrolment rate
|OPRI
|NERT.1.M.CP
|1
|EDUCATION
|-
|EdPriEnrollNetParity
|Total net enrolment rate
|OPRI
|NERT.1.GPIA
|0
|
|-
|EdSecLowerNetEnrollTot%
|Total net enrolment rate
|OPRI
|NERT.2.CP
|0
|
|-
|EdSecLowerNetEnrollFemale%
|Total net enrolment rate
|OPRI
|NERT.2.F.CP
|0
|
|-
|EdSecLowerNetEnrollMale%
|Total net enrolment rate
|OPRI
|NERT.2.M.CP
|0
|
|-
|EdSecUpperNetEnrollTot%
|Total net enrolment rate
|OPRI
|NERT.3.CP
|0
|
|-
|EdSecUpperNetEnrollFemale%
|Total net enrolment rate
|OPRI
|NERT.3.F.CP
|0
|
|-
|EdSecUpperNetEnrollMale%
|Total net enrolment rate
|OPRI
|NERT.3.M.CP
|0
|
|}

== Pulling Data on Enrollment in Vocational Programmes: ==
The pre-processor series in IFs relating to enrollment in vocational programmes are:

#EdSecUpperVoc%AllMale
#EdSecUpperVoc%AllFemale
#EdSecUpperVoc%AllTotal
#EdSecLowerVoc%AllMale
#EdSecLowerVoc%Allfemale
#EdSecLowerVoc%AllTotal

Data for these series was obtained from the UIS Education Database in the following drop down menu sequence: Education>Participation>Distribution of Enrollment>Distribution of Enrollment by Programme Orientation.

Because these particular series contain confusing wording, the full names in UIS of each fo the six series are provided below.

#'''Percentage of male students in lower secondary education enrolled in vocational programmes, male (%)'''
#'''Percentage of female students in lower secondary education enrolled in vocational programmes, female (%)'''
#'''Percentage of students in lower secondary education enrolled in vocational programmes, both sexes (%)'''
#'''Percentage of male students in upper secondary education enrolled in vocational programmes, male (%)'''
#'''Percentage of female students in upper secondary education enrolled in vocational programmes, female (%)'''
#'''Percentage of students in upper secondary education enrolled in vocational programmes, both sexes (%)'''

== Pulling Data on Educational Expenditure: ==
The pre-processor series in IFs relating to educational expenditure are:

#EdExpPri%GDPPC
#EdExpSec%GDPPC
#EdExpSecLowr%GDPPC
#EdExpSecUppr%GDPPC
#EdExpTer%GDPP

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Financial Resources>Government Expenditure per Student>Government Expenditure per Student as Percentage of GDP per capita. 

Once here, the following 5 sheets were used: '''Government expenditure per (primary/secondary/lower seconday/upper seconday/tertiary) student as percentage of GDP per capita.'''

== Pulling Data on Graduation Rates: ==
The pre-processor series in IFs relating to graduation rates are:

#EdTerGradRate1stDegreeFemale% 
#EdterGradRate1stDegreeMale%
#EdTerGradRate1stDegreeTotal%
#EdTerGrad%SciEngg
#EdPriCompletionFemale%
#EdPriCompletionMale%
#EdPriCompletionTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Completion and Graduation Ratios>Gross Graduation Ratio.

Once here, the following 4 sheets were used: '''Gross Graduation Ratio from First Degree Programmes (ISCED 6 & 7) in Tertiary Education, (Female (%)/Male (%)/Both Sexes (%)).'''

For 5-7 above, the following 3sheets were used:'''(Gross Graduation Ratio from Primary Education, (Female(%)/Male(%)/Both Sexes (%)).'''

== Pulling Data on Completion Rates: ==
The pre-processor series in IFs relating to graduation rates are:

#EdSecLowrCompletionFemale
#EdSecLowrCompletionMale
#EdSecLowrCompletionTotal
#EdSecUpprCompletionFemale
#EdSecUpprCompletionMale
#EdSecUpprCompletionTotal

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following dropdown menu sequence: Education>Education>Completion>Completion and graduation ratios. The specific location for each series is as follows.

*EdPriCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), select female (%) from dropdown
*EdPriCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), select male (%) from dropdown
*EdPriCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), Both Sexes (%)
*EdSecLowrCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select female (%) from dropdown
*EdSecLowrCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select male (%) from dropdown
*EdSecLowrCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select both sexes (%) from dropdown
*EdSecUpprCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select female (%) from dropdown
*EdSecUpprCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select male (%) from dropdown
*EdSecUpprCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select both sexes (%) from dropdown

== Pulling Data on Intake Rates: ==
The pre-processor series in IFs relating to apparent (gross) intake rates are:

#EdPriAIRFemale%
#EdPriAIRMale%
#EdPriAIRParity
#EdPriAIRTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Entry>Gross (Apparent) Intake Ratio to Primary and Lower Secondary Education.

Once here, the following three sheets were used: '''Gross Intake Rate to Grade 1 of Primary Education, (Female%/Male%/Total/GenderParityIndex (GPI)).'''

The pre-processor series in IFs relating to net (adjusted) intake rates are:

#EdPriNIRFemale%
#EdPriNIRMale%
#EdPriNIRTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Entry>Gross (Apparent) Intake Ratio to Primary and Lower Secondary Education.

Once here, the following three sheets were used: Adjusted Net Intake Rate to Grade 1 of Primary Education, '''(Female/Male/Total).'''

'''Net Intake Rate to Grade1 of Primary Education'''

EDPRINIRENTRNFemale

EDPRINIRENTRNMale

EDPRINIRENTRNTotal

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education, female (%)
*education>entry>net intake rate to primary education> Net Intake Rate to Grade1 of Primary Education male (%)
*education>entry>net intake rate to primary education> Net Intake Rate to Grade1 of Primary Education both sexes (%)

'''Net Intake Rate to Grade1 of Primary Education (over-age by +1 year)'''

EDPRINIRENTRNP1Male

EDPRINIRENTRNP1Female

EDPRINIRENTRNP1Total

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), male (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), female (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), both sexes (%) 
'''Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), male (%)'''

EDPRINIRENTRNM1Male

EDPRINIRENTRNM1Female

EDPRINIRENTRNM1Total

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), male (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), female (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), both sexes (%) 
'''Adjusted Net Intake Rate to Grade1 of Primary Education'''

EDPRINIRADJFemale

EDPRINIRADJMale

EDPRINIRADJTotal

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, female (%)
*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, male (%)
*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, both sexes (%)

== Pulling Data on Survival Rates: ==
The pre-processor series in IFs relating to survival rates are:

#EdPriSurvivalFemale%
#EdPriSurvivalMale%
#EdPriSurvivalTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Progression>Survival Rates>Survival Rate to Last Grade of Primary Education.

Once here, the following three sheets were used: '''Survival Rate to the Last Grade of Primary Education, (Female%/Male%/Total%).'''

== Pulling Data on Duration: ==
The pre-processor series in IFs relating to survival rates are:

#EdPriDuration
#EdSecLowerDuration
#EdSecUpperDuration

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>System>Duration>Duration by Level of Education.

Once here, the following three sheets were used: '''Theoretical Duration of (Primary/Lower Seconday/Upper Secondary) Education.'''

== Pulling Data on Transition Rates: ==
The pre-processor series in IFs relating to transition rates are:

#EdPriTransition2Sec%Female
#EdPriTransition2Sec%Male
#EdPriTransition2SecTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Progression>Transition Rates.

Once here, the following three sheets were used: '''Effective Transition Rate from Primary to Lower Secondary General Education, (Female%/Male%/Total%).'''

Institute for Statistics, UNESCO (UIS)

2026-01-24T21:39:46Z

Norah.Shamin: /* Tables In IFs */

= Summary =
The United Nations Statistics Division, UIS Education Database is the most comprehensive education databse in the world, containing data from more than 200 countries and territories. The UIS has the mandate to monitor progress towards Education for All and education-related Millennium Development Goals. The statistics, which are updated twice a year, are used by diverse partners, including governments, donor agencies and other UN organizations. In particular, the UIS is the primary education data source for the Education for All Global Monitoring Report, the World Development Indicators and the Human Development Report Data is collected through the UIS annual education survey, which covers all education levels and a range of issues such as enrolment rate, gender parity, teachers, and financing.

The IFs system uses data from the UIS Education Database on a wide variety of topics relating to education. The following sections provide instructions for pulling data from the UIS Education Database for IFs pre-processor series in the Education submodule.

= Tables In IFs =

==== Preprocessors ====
{| class="wikitable"
|+
!Table
!Definition
!Name in Source
!UsedInPreprocessorFileName
!Source in Code
|-
|EDPriPTR
|Primary pupil-teacher ratio
|Enrolment in primary education, both sexes (number)/Teachers in primary education, both sexes (number)
|EDUCATION
|20062/20162
|-
|EdPriAIRFemale%
|Education, Primary, Apparent (gross) intake rate in grade 1, female (% of relevant age group)
|Gross intake ratio to the last grade of primary education, female (%)
|EDUCATION
|AIR.1.GLAST.F
|-
|EdPriAIRMale%
|Education, Primary, Apparent (gross) intake rate in grade 1, male (% of relevant age group)
|Gross intake ratio to the last grade of primary education, male (%)
|EDUCATION
|AIR.1.GLAST.M
|-
|EdPriAIRTotal%
|Education, Primary, Apparent (gross) intake rate in grade 1, total (% of relevant age group)
|Gross intake ratio to the last grade of primary education, both sexes (%)
|EDUCATION
|AIR.1.GLAST
|-
|EdPriCompletionFemale%
|Education, Primary, completion rate (school graduation age), gross, Female
|Completion rate, primary education, female (%)
|EDUCATION
|CR.1.F
|-
|EdPriCompletionMale%
|Education, Primary, completion rate (school graduation age), gross, Male
|Completion rate, primary education, male (%)
|EDUCATION
|CR.1.M
|-
|EdPriCompletionTotal%
|Education, Primary, completion rate (graduation ratio), gross, both sexes
|Completion rate, primary education, both sexes (%)
|EDUCATION
|CR.1
|-
|EdPriDuration
|Education, Primary, completion rate (graduation ratio), gross, total
|Theoretical duration of primary education (years)
|EDUCATION
|299932
|-
|EdPriEnrollGrossFemalePcnt
|Education, Primary, Enrollment Rate Gross, female
|Gross enrolment ratio, primary, female (%)
|EDUCATION
|GER.1.F
|-
|EdPriEnrollGrossMalePcnt
|Education, Primary, Enrollment Rate Gross, male
|Gross enrolment ratio, primary, male (%)
|EDUCATION
|GER.1.M
|-
|EdPriEnrollGrossTotalPcnt
|Education, Primary, Enrollment Rate Gross (% Total)
|Gross enrolment ratio, primary, both sexes (%)
|EDUCATION
|GER.1
|-
|EdPriEnrollNetFemalePcnt
|Education, Primary, Net Enrollment Rate, Female
|Total net enrolment rate, primary, female (%)
|EDUCATION
|NERT.1.F.CP
|-
|EdPriEnrollNetMalePcnt
|Education, Primary, Net Enrollment Rate, Male
|Total net enrolment rate, primary, male (%)
|EDUCATION
|NERT.1.M.CP
|-
|EdPriEnrollNetTotalPcnt
|Education, Primary, Net Enrollment Rate, Total
|Total net enrolment rate, primary, both sexes (%)
|EDUCATION
|NERT.1.CP
|-
|EdPriEntranceAge
|Education Primary Entrance Age
|Official entrance age to primary education (years)
|EDUCATION
|299905
|-
|EdPriSurvivalFemale%
|Education, Primary, percentage of entrants persisting to last grade, female
|Survival rate to the last grade of primary education, female (%)
|EDUCATION
|SR.1.GLAST.F.CP
|-
|EdPriSurvivalMale%
|Education, Primary, percentage of entrants persisting to last grade, male
|Survival rate to the last grade of primary education, male (%)
|EDUCATION
|SR.1.GLAST.M.CP
|-
|EdPriSurvivalTotal%
|Education, Primary, percentage of entrants persisting to last grade, total
|Survival rate to the last grade of primary education, both sexes (%)
|EDUCATION
|SR.1.GLAST.CP
|-
|EdSecEnrollGross%Female
|Education, Secondary, gross enrollment rate, female
|Gross enrolment ratio, secondary, female (%)
|EDUCATION
|GER.2T3.F
|-
|EdSecEnrollGross%Male
|Education, Secondary, gross enrollment rate, male
|Gross enrolment ratio, secondary, male (%)
|EDUCATION
|GER.2T3.M
|-
|EdSecEnrollGross%Total
|Education, Secondary, gross enrollment rate, total
|Gross enrolment ratio, secondary, both sexes (%)
|EDUCATION
|GER.2T3
|-
|EdSecLowerDuration
|Education Duration of Lower Secondary
|Theoretical duration of lower secondary education (years)
|EDUCATION
|999976
|-
|EdSecLowerEnrollGross%Female
|Education, Secondary, Lower, Gross Enrollment Rate All Programs, Female
|Gross enrolment ratio, lower secondary, female (%)
|EDUCATION
|GER.2.F
|-
|EdSecLowerEnrollGross%Male
|Education, Secondary, Lower, Gross Enrollment Rate All Programs, Male
|Gross enrolment ratio, lower secondary, male (%)
|EDUCATION
|GER.2.M
|-
|EdSecLowerEnrollGross%Total
|Education, Secondary, Lower, Gross Enrollment Rate, Total
|Gross enrolment ratio, lower secondary, both sexes (%)
|EDUCATION
|GER.2
|-
|EdSecLowerVoc%AllTotal
|Education, Secondary, Lower, Vocational as % of All Program Enrollments, Total
|Share of all students in lower secondary education enrolled in vocational programmes (%)
|EDUCATION
|GTVP.2.V
|-
|EdSecUpperDuration
|Education, Secondary, Upper, Duration of Upper Secondary
|Theoretical duration of upper secondary education (years)
|EDUCATION
|999978
|-
|EdSecUpperEnrollGross%Female
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Female
|Gross enrolment ratio, upper secondary, female (%)
|EDUCATION
|GER.3.F
|-
|EdSecUpperEnrollGross%Male
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Male
|Gross enrolment ratio, upper secondary, male (%)
|EDUCATION
|GER.3.M
|-
|EdSecUpperEnrollGross%Total
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Total
|Gross enrolment ratio, upper secondary, both sexes (%)
|EDUCATION
|GER.3
|-
|EdSecUpperVoc%AllTotal
|Education, Secondary, Upper, Vocational as % of All Program Enrollments, Total
|Share of all students in upper secondary education enrolled in vocational programmes (%)
|EDUCATION
|GTVP.3.V
|-
|EdTerEnrollGross%Female
|Education, Tertiary, Gross Enrollment Rate, Female
|Gross enrolment ratio for tertiary education, female (%)
|EDUCATION
|GER.5T8.F
|-
|EdTerEnrollGross%Male
|Education, Tertiary, Gross Enrollment Rate, Male
|Gross enrolment ratio for tertiary education, male (%)
|EDUCATION
|GER.5T8.M
|-
|EdTerEnrollGross%Total
|Education, Tertiary, Gross Enrollment Rate, Total
|Gross enrolment ratio for tertiary education, both sexes (%)
|EDUCATION
|GER.5T8
|-
|EdTerGradRate1stDegreeFemale%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, female
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, female (%)
|EDUCATION
|GGR.6T7.F
|-
|EdTerGradRate1stDegreeMale%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, male
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, male (%)
|EDUCATION
|GGR.6T7.M
|-
|EdTerGradRate1stDegreeTotal%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, total
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, both sexes (%)
|EDUCATION
|GGR.6T7
|-
|EdTerGrads%SciEngg
|Education, Tertiary, Science and Enginnering Graduates as % of Total Graduates
|Percentage of graduates from tertiary education graduating from Natural Sciences, Mathematics and Statistics programmes, both sexes (%)
|EDUCATION
|FOSGP.5T8.F500
|-
|GovtEdPub%GDP
|Educational expenditures (public) as percent of GDP
|Government expenditure on pre-primary education as a percentage of GDP (%) + Government expenditure on primary education as a percentage of GDP (%) + Government expenditure on lower secondary education as a percentage of GDP (%) + Government expenditure on upper secondary education as a percentage of GDP (%) + Government expenditure on post-secondary non-tertiary education as a percentage of GDP (%) + Government expenditure on tertiary education as a percentage of GDP (%)
|ECONOMY
|XGDP.02.FSGOV + XGDP.1.FSGOV + XGDP.2.FSGOV + XGDP.3.FSGOV + XGDP.4.FSGOV + XGDP.5T8.FSGOV
|-
|R&DGovt%GDP
|Gross R&D expenditure by government
|GERD as a percentage of GDP
|ECONOMY
|EXPGDP.TOT
|-
|EdExpPri%GDPPC
|Expenditure per student in primary education (% of GDP/capita)
|Initial government funding per primary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.1.FSGOV.FFNTR
|-
|EdExpSec%GDPPC
|Expenditure per student in secondary education (% of GDP/capita)
|Initial government funding per secondary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.2T3.FSGOV.FFNTR
|-
|EdExpSecLowr%GDPPC
|Expenditure per student in lower secondary education (% of GDP/capita)
|Initial government funding per lower secondary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.2.FSGOV.FFNTR
|-
|EdExpSecUppr%GDPPC
|Expenditure per student in upper secondary education (% of GDP/capita)
|Initial government funding per upper secondary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.3.FSGOV.FFNTR
|-
|EdExpTer%GDPPC
|Expenditure per student in tertiary education (% of GDP/capita)
|Initial government funding per tertiary student as a percentage of GDP per capita
|EDUCATION
|XUNIT.GDPCAP.5T8.FSGOV.FFNTR
|-
|EdSecLowerVoc%AllFemale
|Percentage of female students in lower secondary education enrolled in vocational programmes, female (%)
|Percentage of females in lower secondary education enrolled in vocational programs (%)
|EDUCATION
|GTVP.2.V.F
|-
|EdSecLowerVoc%AllMale
|Percentage of male students in lower secondary education enrolled in vocational programmes, male (%)
|Percentage of males in lower secondary education enrolled in vocational programs (%)
|EDUCATION
|GTVP.2.V.M
|-
|EdSecUpperGradRateAllFem
|Gross Upper Secondary Graduation Ratio, All Programmes. Female
|Completion rate, upper secondary education, female (%)
|EDUCATION
|CR.3.F
|-
|EdSecUpperGradRateAllMal
|Gross Upper Secondary Graduation Ratio, All Programmes. Male
|Completion rate, upper secondary education, male (%)
|EDUCATION
|CR.3.M
|-
|EdSecUpperGradRateAllTot
|Gross Upper Secondary Graduation Ratio, All Programmes. Total
|Completion rate, upper secondary education, both sexes (%)
|EDUCATION
|CR.3
|-
|EdSecUpperVoc%AllFemale
|Percentage of female students in upper secondary education enrolled in vocational programmes, female (%)
|Percentage of females in upper secondary enrolled in vocational programs (%)
|EDUCATION
|GTVP.3.V.F
|-
|EdSecUpperVoc%AllMale
|Percentage of male students in upper secondary education enrolled in vocational programmes, male (%)
|Percentage of males in upper secondary education enrolled in vocational programs (%)
|EDUCATION
|GTVP.3.V.M
|}

==== Non-preprocessors ====
{| class="wikitable"
|+
!Table
!Definition
!Name in Source
!Source in Code
!Formula
|-
|EdBasicEnrollGross%Female
|Education, Basic, Enrollment Rate, Gross, Female
|Gross enrolment ratio, primary and lower secondary, female (%)
|GER.1T2.F
|
|-
|EdBasicEnrollGross%Male
|Education, Basic, Enrollment Rate, Gross, Male
|Gross enrolment ratio, primary and lower secondary, male (%)
|GER.1T2.M
|
|-
|EdBasicEnrollGross%Total
|Education, Basic, Enrollment Rate, Gross, Total
|Gross enrolment ratio, primary and lower secondary, both sexes (%)
|GER.1T2
|
|-
|EdEnrollPrivate%Lower2ndaryGeneral
|Education enrollments private as % of lower secondary general
|Percentage of enrolment in lower secondary education in private institutions (%)
|PRP.2
|
|-
|EdEnrollPrivate%Primary
|Education enrollment private as % of primary
|Percentage of enrolment in primary education in private institutions (%)
|PRP.1
|
|-
|EdEnrollPrivate%Upper2ndaryGeneral
|Education enrollments private as % of upper secondary general
|Percentage of enrolment in upper secondary education in private institutions (%)
|PRP.3
|
|-
|EdEnrollPrivateAll2ndaryCombined
|Education enrollment private all secondary combined
|Percentage of enrolment in secondary education in private institutions (%)
|PRP.2T3
|
|-
|EdEnrollPrivateUpper2ndaryGeneral
|Education enrollment private upper secondary general
|Percentage of enrolment in upper secondary education in private institutions (%)
|PRP.3
|
|-
|EdExpISCED1-4Cap%
|Education expenditures, ISCED 1-4, capital portion
|Capital expenditure as a percentage of total expenditure in primary public institutions (%) + Capital expenditure as a percentage of total expenditure in lower secondary public institutions (%) + Capital expenditure as a percentage of total expenditure in upper-secondary public institutions (%) + Capital expenditure as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNCAP + XSPENDP.2.FDPUB.FNCAP + XSPENDP.3.FDPUB.FNCAP + XSPENDP.4.FDPUB.FNCAP
|
|-
|EdExpISCED1-4NonSalCur%
|Education expenditures, ISCED 1-4, non-salary current portion
|Current expenditure other than staff compensation as a percentage of total expenditure in primary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in lower secondary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in upper secondary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNNONS + XSPENDP.2.FDPUB.FNNONS + XSPENDP.3.FDPUB.FNNONS + XSPENDP.4.FDPUB.FNNONS
|
|-
|EdExpISCED1-4Sal%
|Education expenditures, ISCED 1-4, salary portion
|All staff compensation as a percentage of total expenditure in primary public institutions (%) + All staff compensation as a percentage of total expenditure in lower secondary public institutions (%) + All staff compensation as a percentage of total expenditure in upper secondary public institutions (%) + All staff compensation as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNS + XSPENDP.2.FDPUB.FNS + XSPENDP.3.FDPUB.FNS + XSPENDP.4.FDPUB.FNS
|
|-
|EdExpISCED1-4TotalCur%
|Education expenditures, ISCED 1-4, total current portion
|Current expenditure as a percentage of total expenditure in primary public institutions (%) + Current expenditure as a percentage of total expenditure in lower secondary public institutions (%) + Current expenditure as a percentage of total expenditure in upper-secondary public institutions (%) + Current expenditure as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNCUR + XSPENDP.2.FDPUB.FNCUR + XSPENDP.3.FDPUB.FNCUR + XSPENDP.4.FDPUB.FNCUR
|
|-
|EdExpPrePri%EducTot
|Educational expenditure in pre-primary as % of total educational expenditure
|Government expenditure on pre-primary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.02.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpPri%EducTot
|Education expenditure in primary as % of total educational expenditure
|Government expenditure on primary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.1.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSec%EducTot
|Education Expenditure Secondary as % of Total Educational Expenditure
|Government expenditure on secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.2T3.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSecLowr%EducTot
|Educational expenditure in lower secondary as % of total educational expenditure
|Government expenditure on lower secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.2.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSecUppr%EducTot
|Educational expenditure in upper secondary as % of total educational expenditure
|Government expenditure on upper secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.3.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpTer%EducTot
|Education Expenditure Tertiary as % of Total Educational Expenditure
|Government expenditure on tertiary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.5T8.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpTerCap%
|Education expenditures, tertiary, capital portion
|Capital expenditure as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNCAP
|
|-
|EdExpTertNonSalCur%
|Education expenditures, tertiary, non-salary current portion
|Current expenditure other than staff compensation as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNNONS
|
|-
|EdExpTertSal%
|Education expenditures, tertiary, salary portion
|All staff compensation as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNS
|
|-
|EdExpTertTotalCur%
|Education expenditures, tertiary, total current portion
|Current expenditure as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNCUR
|
|-
|EdExpectedYearsofSchooling
|Expected years of schooling for a child of school entering age
|School life expectancy, primary to tertiary, both sexes (years)
|SLE.1T8
|
|-
|EdExpectedYearsofSchoolingFemale
|Expected years of schooling for a child of school entering age, female
|School life expectancy, primary to tertiary, female (years)
|SLE.1T8.F
|
|-
|EdExpectedYearsofSchoolingMale
|Expected years of education for a child of school going age, male
|School life expectancy, primary to tertiary, male (years)
|SLE.1T8.M
|
|-
|EdPostSecDuration
|Education, Post-Secondary Non-Tertiary, Cycle Length
|Theoretical duration of post-secondary non-tertiary education (years)
|999988
|
|-
|EdPrePriDuration
|Education, Pre-Primary, Cycle Length
|Theoretical duration of pre-primary education (years)
|299929
|
|-
|EdPrePriParityGenderTeachers
|Ratio of female to male teachers in pre-primary education who are trained
|Pupil-trained teacher ratio in pre-primary education (headcount basis)
|PTRHC.02.TRAINED
|
|-
|EdPri2and3ParityGenderMath
|Ratio of girls' to boys' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.G2.GPIA + MATH.G3.GPIA
|
|-
|EdPri2and3ParityGenderRead
|Ratio of girls' to boys' reading achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.G2.GPIA + READ.G3.GPIA
|
|-
|EdPri2and3ParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.G2.LPIA + MATH.G3.LPIA
|
|-
|EdPri2and3ParityRurUrbRead
|Ratio of rural to urban students' reading achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.G2.LPIA + READ.G3.LPIA
|
|-
|EdPri2and3ParitySocioeconMath
|Ratio of students from low to high socio-economic groups' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.G2.WPIA + MATH.G3.WPIA
|
|-
|EdPri2and3ParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.G2.WPIA + READ.G3.WPIA
|
|-
|EdPriAIRParity
|Education, Primary, Apparent(gross) Intake Rate, Gender Parity Index
|Gross intake ratio to the last grade of primary education, adjusted gender parity index (GPIA)
|AIR.1.GLAST.GPIA
|
|-
|EdPriCompletionFemale
|Education, primary, completion rate from household survey data, female
|Completion rate, primary education, female (%)
|CR.1.F
|
|-
|EdPriCompletionFemale%BL
|Education, Primary, completion rate (graduation ratio), gross, Female
|Completion rate, primary education, female (%)
|CR.1.F
|
|-
|EdPriCompletionMale
|Education, primary, completion rate from household survey data, male
|Completion rate, primary education, male (%)
|CR.1.M
|
|-
|EdPriCompletionMale%BL
|Education, Primary, completion rate (graduation ratio), gross, Male
|Completion rate, primary education, male (%)
|CR.1.M
|
|-
|EdPriCompletionParity
|Education, Primary, Completion Rate, Gender Parity, New
|Completion rate, primary education, adjusted gender parity index (GPIA)
|CR.1.GPIA
|
|-
|EdPriCompletionTotal
|Education, primary, completion rate from household survey data, total
|Completion rate, primary education, both sexes (%)
|CR.1
|
|-
|EdPriCompletionTotal%BL
|Education, Primary, completion rate (graduation ratio), gross, total
|Completion rate, primary education, both sexes (%)
|CR.1
|
|-
|EdPriEnrollHeadCountTtl
|Education, Primary, Total Enrollment (male plus female)
|Enrolment in primary education, both sexes (number)
|20062
|*0.000001
|-
|EdPriEnrollHeadcountFem
|Female enrollment at primary level, in both public and private institutions
|Enrolment in primary education, female (number)
|20063
|*0.000001
|-
|EdPriEnrollHeadcountMal
|Male enrollment, primary level, in both public and private institutions
|Enrolment in primary education, male (number)
|40035
|*0.000001
|-
|EdPriEnrollNetParity
|Education, Primary, Net Enrollment Rate, Gender Parity Index
|Total net enrolment rate, primary, adjusted gender parity index (GPIA)
|NERT.1.GPIA
|
|-
|EdPriOutofSchoolFemale%
|Education primary, percentage of primary age children who are out of school, Female
|Out-of-school rate for children of primary school age, female (%)
|ROFST.1.F.CP
|
|-
|EdPriOutofSchoolMale%
|Education primary, percentage of primary age children who are out of school, Male
|Out-of-school rate for children of primary school age, male (%)
|ROFST.1.M.CP
|
|-
|EdPriOutofSchoolTotal%
|Education primary, percentage of primary age children who are out of school, total
|Out-of-school rate for children of primary school age, both sexes (%)
|ROFST.1.CP
|
|-
|EdPriParityGenderMath
|Ratio of girls' to boys' mathematics achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.PRIMARY.GPIA
|
|-
|EdPriParityGenderRead
|Ratio of girls' to boys' reading achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.PRIMARY.GPIA
|
|-
|EdPriParityGenderTeachers
|Ratio of female to male teachers in primary education who are trained
|Pupil-trained teacher ratio in primary education (headcount basis)
|PTRHC.1.TRAINED
|
|-
|EdPriParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.PRIMARY.LPIA
|
|-
|EdPriParityRurUrbRead
|Ratio of rural to urban students' reading achievement by the end of primary
|Proportion of students at the end of primary education achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.PRIMARY.LPIA
|
|-
|EdPriParitySocioeconMath
|Ratio of students from low to high socio-economic groups' achievement in mathematics by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.PRIMARY.WPIA
|
|-
|EdPriParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading by the end of primary
|Proportion of students at the end of primary education achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.PRIMARY.WPIA
|
|-
|EdPriRepeater1stYearFemale%
|Percentage of repeaters in primary. Grade 1.Female
|Repetition rate in Grade 1 of primary education, female (%)
|REPR.1.G1.F.CP
|
|-
|EdPriRepeater1stYearMale%
|Percentage of repeaters in primary. Grade 1.Male
|Repetition rate in Grade 1 of primary education, male (%)
|REPR.1.G1.M.CP
|
|-
|EdPriRepeater1stYearTotal%
|Percentage of repeaters in primary. Grade 1. Total
|Repetition rate in Grade 1 of primary education, both sexes (%)
|REPR.1.G1.CP
|
|-
|EdPriRepeaterFemale%
|Education Primary Percentage of Repeaters, all grades, female
|Repetition rate in primary education (all grades), female (%)
|REPR.1.F.CP
|
|-
|EdPriRepeaterMale%
|Education Primary Percentage of Repeaters, all grades, male
|Repetition rate in primary education (all grades), male (%)
|REPR.1.M.CP
|
|-
|EdPriRepeaterTotal%
|Education Primary Percentage of Repeaters, all grades, total
|Repetition rate in primary education (all grades), both sexes (%)
|REPR.1.CP
|
|-
|EdPriSurvivalParity
|Education, Primary, Survival to Last Grade, Gender Parity, New
|Survival rate to the last grade of primary education,adjusted gender parity index (GPIA)
|SR.1.GLAST.GPIA
|
|-
|EdSecDuration
|Duration of education, secondary
|Theoretical duration of secondary education (years)
|THDUR.2T3
|
|-
|EdSecEnrNoFem
|Education, secondary Enrollment Number, Female
|Enrolment in secondary education, female (number)
|20083
|*0.000001
|-
|EdSecEnrNoMal
|Education, secondary Enrollment Number, Male
|Enrolment in secondary education, male (number)
|40044
|*0.000001
|-
|EdSecEnrNoTot
|Education, Total Secondary, Total Enrollment (male plus female)
|Enrolment in secondary education, both sexes (number)
|20082
|*0.000001
|-
|EdSecEnrollGross%Parity
|secondary gross enrollment rate, all programs, Gender Parity Index, new data
|Gross enrolment ratio, secondary, adjusted gender parity index (GPIA)
|GER.2T3.GPIA
|
|-
|EdSecLowerAdultGrads25Female%
|Adult population (25 and over) with lower secondary (or more) education, female%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, female (%)
|EA.2T8.AG25T99.F
|
|-
|EdSecLowerAdultGrads25Male%
|Adult population (25 and over) with lower secondary (or more) education, male%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, male (%)
|EA.2T8.AG25T99.M
|
|-
|EdSecLowerAdultGrads25Total%
|Adult population (25 and over) with lower secondary (or more) education, total%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, both sexes (%)
|EA.2T8.AG25T99
|
|-
|EdSecLowerEnrollGrossParity
|Gender parity index for gross enrolment ratio. Lower secondary. All programmes
|Gross enrolment ratio, lower secondary, adjusted gender parity index (GPIA)
|GER.2.GPIA
|
|-
|EdSecLowerEnrollHeadcountFemale
|Education, lower secondary, headcount enrollment number, female
|Enrolment in lower secondary education, female (number)
|20065
|*0.000001
|-
|EdSecLowerEnrollHeadcountMale
|Education, lower secondary, headcount enrollment number , male
|Enrolment in lower secondary education, male (number)
|40038
|*0.000001
|-
|EdSecLowerEnrollHeadcountTotal
|Education, Lower Secondary, Total Enrollment (male plus female)
|Enrolment in lower secondary education, both sexes (number)
|20064
|*0.000001
|-
|EdSecLowerNetEnrollFemale%
|Net Lower Secondary Enrollment Rate, Female
|Total net enrolment rate, lower secondary, female (%)
|NERT.2.F.CP
|
|-
|EdSecLowerNetEnrollMale%
|Net Lower Secondary Enrollment Rate, Male
|Total net enrolment rate, lower secondary, male (%)
|NERT.2.M.CP
|
|-
|EdSecLowerNetEnrollTot%
|Net Lower Secondary Enrollment Rate, Total
|Total net enrolment rate, lower secondary, both sexes (%)
|NERT.2.CP
|
|-
|EdSecLowrCompletionFemale
|Education, lower secondary, completion rate from household survey data, female
|Completion rate, lower secondary education, female (%)
|CR.2.F
|
|-
|EdSecLowrCompletionMale
|Education, lower secondary, completion rate from household survey data, male
|Completion rate, lower secondary education, male (%)
|CR.2.M
|
|-
|EdSecLowrCompletionTotal
|Education, lower secondary, completion rate from household survey data, total
|Completion rate, lower secondary education, both sexes (%)
|CR.2
|
|-
|EdSecLowrPTR
|Education, lower secondary, pupil teacher ratio
|Enrolment in lower secondary education, both sexes (number)/Teachers in lower secondary education, both sexes (number)
|20064/20164
|
|-
|EdSecLwrParityGenderMath
|Ratio of girls' to boys' mathematics achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.LOWERSEC.GPIA
|
|-
|EdSecLwrParityGenderRead
|Ratio of girls' to boys' reading achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.LOWERSEC.GPIA
|
|-
|EdSecLwrParityGenderTeachers
|Ratio of female to male teachers in lower secondary who are trained
|Pupil-trained teacher ratio in lower secondary education (headcount basis)
|PTRHC.2.TRAINED
|
|-
|EdSecLwrParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.LOWERSEC.LPIA
|
|-
|EdSecLwrParityRurUrbRead
|Ratio of rural to urban students' reading achievement by the end of lower secondary
|Proportion of students at the end of lower secondary education achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.LOWERSEC.LPIA
|
|-
|EdSecLwrParitySocioeconMath
|Ratio of students from low to high socio-economic groups' achievement in mathematics by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.LOWERSEC.WPIA
|
|-
|EdSecLwrParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading by the end of lower secondary
|Proportion of students at the end of lower secondary education achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.LOWERSEC.WPIA
|
|-
|EdSecUpperEnrollGrossParity
|Gender parity index for gross enrolment ratio. Upper secondary. All programmes
|Gross enrolment ratio, upper secondary, adjusted gender parity index (GPIA)
|GER.3.GPIA
|
|-
|EdSecUpperEnrollGrossParityNew
|Gender parity index for gross enrolment ratio. Upper secondary. All programmes
|Gross enrolment ratio, upper secondary, adjusted gender parity index (GPIA)
|GER.3.GPIA
|
|-
|EdSecUpperEnrollHeadCountMale
|Education, upper secondary, headcount enrollment number , male
|Enrolment in upper secondary education, male (number)
|40041
|*0.000001
|-
|EdSecUpperEnrollHeadcountFemale
|Education, upper secondary, headcount enrollment number, female
|Enrolment in upper secondary education, female (number)
|20071
|*0.000001
|-
|EdSecUpperEnrollHeadcountTotal
|Education, Upper Secondary, Total Enrollment (male plus female)
|Enrolment in upper secondary education, both sexes (number)
|20070
|*0.000001
|-
|EdSecUpperNetEnrollFemale%
|Net Upper Secondary Enrollment, Female
|Total net enrolment rate, upper secondary, female (%)
|NERT.3.F.CP
|
|-
|EdSecUpperNetEnrollMale%
|Net Upper Secondary Enrollment Rate, Male
|Total net enrolment rate, upper secondary, male (%)
|NERT.3.M.CP
|
|-
|EdSecUpperNetEnrollTot%
|Net Upper Secondary Enrollment Rate, Total
|Total net enrolment rate, upper secondary, both sexes (%)
|NERT.3.CP
|
|-
|EdSecUpperParityGenderTeachers
|Ratio of female to male teachers in upper secondary education who are trained
|Pupil-trained teacher ratio in upper secondary education (headcount basis)
|PTRHC.3.TRAINED
|
|-
|EdSecUpprCompletionFemale
|Education, upper secondary, completion rate from household survey data, female
|Completion rate, upper secondary education, female (%)
|CR.3.F
|
|-
|EdSecUpprCompletionMale
|Education, upper secondary, completion rate from household survey data, male
|Completion rate, upper secondary education, male (%)
|CR.3.M
|
|-
|EdSecUpprCompletionTotal
|Education, upper secondary, completion rate from household survey data, total
|Completion rate, upper secondary education, both sexes (%)
|CR.3
|
|-
|EdSecVoc%Tot
|Education Secondary, technical or vocational enrollment as percentage of all programs, total
|Share of all students in secondary education enrolled in vocational programmes (%)
|GTVP.2T3.V
|
|-
|EdTerEnrISCED6HdctFem
|Education, 6 Tertiary, Enrollment headcount, Female
|Enrolment in tertiary education, ISCED 6 programmes, female (number)
|42635
|*0.000001
|-
|EdTerEnrISCED6HdctMale
|Education, 6 Tertiary, Enrollment headcount, Male
|Enrolment in tertiary education, ISCED 6 programmes, male (number)
|42615
|*0.000001
|-
|EdTerEnrISCED6HdctTot
|Education, 6 Tertiary, Enrollment headcount, Total
|Enrolment in tertiary education, ISCED 6 programmes, both sexes (number)
|42654
|*0.000001
|-
|EdTerEnrollHeadcountFem
|Education, Tertiary, Enrollment Headcount, Female
|Enrolment in tertiary education, all programmes, female (number)
|25057
|*0.000001
|-
|EdTerEnrollHeadcountMale
|Education, Tertiary, Enrollment Headcount, Male
|Enrolment in tertiary education, all programmes, male (number)
|42620
|*0.000001
|-
|EdTerEnrollHeadcountTotal
|Education, Tertiary, Enrollment Headcount, Total
|Enrolment in tertiary education, all programmes, both sexes (number)
|25053
|*0.000001
|-
|EdTerFemaleMaleRatio
|Ratio of females to males in tertiary education
|Gross enrolment ratio for tertiary education, adjusted gender parity index (GPIA)
|GER.5T8.GPIA
|
|-
|EdTerGrads%Ag
|Education, Tertiary, Agriculture Graduates as % of total graduates
|Percentage of graduates from tertiary education graduating from Agriculture, Forestry, Fisheries and Veterinary programmes, both sexes (%)
|FOSGP.5T8.F800
|
|-
|EdTerGrads%Engg
|Education, Tertiary, Engineering, Manufacturing and Construction as % of total graduates
|Percentage of graduates from tertiary education graduating from Engineering, Manufacturing and Construction programmes, both sexes (%)
|FOSGP.5T8.F700
|
|-
|EdTerGrads%Health
|Education, Tertiary, Health and Welfare Graduates as % of total graduates
|Percentage of graduates from tertiary education graduating from Health and Welfare programmes, both sexes (%)
|FOSGP.5T8.F900
|
|-
|EdTerGrads%Sci
|Education, Tertiary, Science Graduates as % of total graduates
|Percentage of graduates from Science, Technology, Engineering and Mathematics programmes in tertiary education, both sexes (%) + Percentage of graduates from tertiary education graduating from Information and Communication Technologies programmes, both sexes (%)
|FOSGP.5T8.F500 + FOSGP.5T8.F600
|
|-
|PupilTeacherRatioUISPrimary
|Pupil teacher ratio in primary education
|Enrolment in primary education, both sexes (number)/Teachers in primary education, both sexes (number)
|20062/20162
|
|-
|PupilTeacherRatioUISSecondary
|Pupil teacher ratio in secondary education
|Enrolment in secondary education, both sexes (number)/Teachers in secondary education, both sexes (number)
|20082/20182
|
|-
|PupilTrainedTeacherRatioUISPrimary
|Pupil to trained teacher ratio in primary education
|Pupil-trained teacher ratio in primary education (headcount basis)
|PTRHC.1.TRAINED
|
|-
|PupilTrainedTeacherRatioUISSecondary
|Pupil toTrained teacher ratio in secondary education
|Pupil-trained teacher ratio in secondary education (headcount basis)
|PTRHC.2T3.TRAINED
|
|-
|EdSecLowrRpt%Gr1BothSexes
|Repetition rate in Grade 1 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 1 of lower secondary general education, both sexes (%)
|REPR.2.G1.CP
|
|-
|EdSecLowrRpt%Gr1Female
|Repetition rate in Grade 1 of lower secondary general education, female (%)
|Repetition rate in Grade 1 of lower secondary general education, female (%)
|REPR.2.G1.F.CP
|
|-
|EdSecLowrRpt%Gr1Male
|Repetition rate in Grade 1 of lower secondary general education, male (%)
|Repetition rate in Grade 1 of lower secondary general education, male (%)
|REPR.2.G1.M.CP
|
|-
|EdSecLowrRpt%Gr2BothSexes
|Repetition rate in Grade 2 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 2 of lower secondary general education, both sexes (%)
|REPR.2.G2.CP
|
|-
|EdSecLowrRpt%Gr2Female
|Repetition rate in Grade 2 of lower secondary general education, female (%)
|Repetition rate in Grade 2 of lower secondary general education, female (%)
|REPR.2.G2.F.CP
|
|-
|EdSecLowrRpt%Gr2Male
|Repetition rate in Grade 2 of lower secondary general education, male (%)
|Repetition rate in Grade 2 of lower secondary general education, male (%)
|REPR.2.G2.M.CP
|
|-
|EdSecLowrRpt%Gr3BothSexes
|Repetition rate in Grade 3 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 3 of lower secondary general education, both sexes (%)
|REPR.2.G3.CP
|
|-
|EdSecLowrRpt%Gr3Female
|Repetition rate in Grade 3 of lower secondary general education, female (%)
|Repetition rate in Grade 3 of lower secondary general education, female (%)
|REPR.2.G3.F.CP
|
|-
|EdSecLowrRpt%Gr3Male
|Repetition rate in Grade 3 of lower secondary general education, male (%)
|Repetition rate in Grade 3 of lower secondary general education, male (%)
|REPR.2.G3.M.CP
|
|-
|EdSecLowrRpt%Gr4BothSexes
|Repetition rate in Grade 4 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 4 of lower secondary general education, both sexes (%)
|REPR.2.G4.CP
|
|-
|EdSecLowrRpt%Gr4Female
|Repetition rate in Grade 4 of lower secondary general education, female (%)
|Repetition rate in Grade 4 of lower secondary general education, female (%)
|REPR.2.G4.F.CP
|
|-
|EdSecLowrRpt%Gr4Male
|Repetition rate in Grade 4 of lower secondary general education, male (%)
|Repetition rate in Grade 4 of lower secondary general education, male (%)
|REPR.2.G4.M.CP
|
|-
|EdSecLowrRpt%Gr5BothSexes
|Repetition rate in Grade 5 of lower secondary general education, both sexes (%)
|Repetition rate in Grade 5 of lower secondary general education, both sexes (%)
|REPR.2.G5.CP
|
|-
|EdSecLowrRpt%Gr5Female
|Repetition rate in Grade 5 of lower secondary general education, female (%)
|Repetition rate in Grade 5 of lower secondary general education, female (%)
|REPR.2.G5.F.CP
|
|-
|EdSecLowrRpt%Gr5Male
|Repetition rate in Grade 5 of lower secondary general education, male (%)
|Repetition rate in Grade 5 of lower secondary general education, male (%)
|REPR.2.G5.M.CP
|
|-
|EdSecLowrRpt%GrAllBothSexes
|Repetition rate in lower secondary general education (all grades), both sexes (%)
|Repetition rate in lower secondary general education (all grades), both sexes (%)
|REPR.2.CP
|
|-
|EdSecLowrRpt%GrAllFemale
|Repetition rate in lower secondary general education (all grades), female (%)
|Repetition rate in lower secondary general education (all grades), female (%)
|REPR.2.F.CP
|
|-
|EdSecLowrRpt%GrAllMale
|Repetition rate in lower secondary general education (all grades), male (%)
|Repetition rate in lower secondary general education (all grades), male (%)
|REPR.2.M.CP
|
|-
|add calebs tables here
|
|
|
|
|}
= Data Pulling Instructions =

# Go to https://databrowser.uis.unesco.org/resources/bulk
# Download Education SDG, Education Other Policy Relevant Indicators, and R&D SDG
## Under SDG 4 Education - Global and Thematic Indicators find file: SDG
## Under Other Policy Relevant Indicators (OPRI) find file: OPRI
## Under SDG 9.5 - Research and Development (R&D) find file: SCN-SDG
## Upzip the downloaded files.
### Use {File name}_COUNTRY.csv to prepare country concordance table.
### Use {File name}_NATIONAL.csv to extract series.
### Use {File name}_LABEL.csv to check the definition of the "INDICATOR_ID" listed below.[[File:Files in Zipped Folder.png|none|thumb|600x600px]]
##You can use the code in this GitHub to help pull the data: https://github.com/n1shamin/UIS-UNESCO

= Coding =
Notes:

2. Series need to be calculated: PupilTeacherRatioUISPrimary, PupilTeacherRatioUISSecondary, EDPriPTR, EdSecLowrPTR, EdExpPrePri%EducTot, EdExpPri%EducTot, EdExpSecLowr%EducTot, EdExpSec%EducTot, EdExpSecUppr%EducTot, EdExpTer%EducTot, EdTerGrads%Sci, GovtEdPub%GDP, EdExpISCED1-4Cap%, EdExpISCED1-4TotalCur%, EdExpISCED1-4NonSalCur%, EdExpISCED1-4Sal%

3. All the series in "Enrollment Headcount" need to *0.000001 to convert to "Millions".

4. Item Understanding in INDICATOR_ID:
{| class="wikitable"
|Item
|Meaning
|-
|02
|pre-primary
|-
|1
|primary
|-
|2
|lower secondary
|-
|3
|upper secondary
|-
|2T3
|secondary
|-
|4
|post-secondary non-tertiary
|-
|5T8
|tertiary
|-
|6T7
|ISCED 6 and 7
|-
|1T8
|primary to tertiary
|-
|F
|female
|-
|M
|male
|-
|GPIA
|adjusted gender parity index
|-
|LPIA
|adjusted location parity index
|-
|WPIA
|adjusted wealth parity index
|-
|G1
|Grade 1
|-
|G2T3
|Grade 2 or 3
|-
|GLAST
|last grade
|-
|F500
|Natural Sciences, Mathematics and Statistics
|-
|F600
|Information and Communication Technologies
|-
|F700
|Engineering, Manufacturing and Construction
|-
|F800
|Agriculture, Forestry, Fisheries and Veterinary
|-
|F900
|Health and Welfare
|}
{| class="wikitable"
|Variable
|Type
|File
|INDICATOR_ID
|UsedInPreprocessor
|UsedInPreprocessorFileName
|-
|EdPriCompletionTotal%
|Completion rate
|SDG
|CR.1
|1
|EDUCATION
|-
|EdPriCompletionFemale%
|Completion rate
|SDG
|CR.1.F
|1
|EDUCATION
|-
|EdPriCompletionMale%
|Completion rate
|SDG
|CR.1.M
|1
|EDUCATION
|-
|EdPriCompletionTotal
|Completion rate
|SDG
|CR.1
|0
|
|-
|EdPriCompletionTotal%BL
|Completion rate
|SDG
|CR.1
|0
|
|-
|EdPriCompletionFemale
|Completion rate
|SDG
|CR.1.F
|0
|
|-
|EdPriCompletionFemale%BL
|Completion rate
|SDG
|CR.1.F
|0
|
|-
|EdPriCompletionParity
|Completion rate
|SDG
|CR.1.GPIA
|0
|
|-
|EdPriCompletionMale
|Completion rate
|SDG
|CR.1.M
|0
|
|-
|EdPriCompletionMale%BL
|Completion rate
|SDG
|CR.1.M
|0
|
|-
|EdSecLowrCompletionTotal
|Completion rate
|SDG
|CR.2
|0
|
|-
|EdSecLowrCompletionFemale
|Completion rate
|SDG
|CR.2.F
|0
|
|-
|EdSecLowrCompletionMale
|Completion rate
|SDG
|CR.2.M
|0
|
|-
|EdSecUpprCompletionTotal
|Completion rate
|SDG
|CR.3
|0
|
|-
|EdSecUpprCompletionFemale
|Completion rate
|SDG
|CR.3.F
|0
|
|-
|EdSecUpprCompletionMale
|Completion rate
|SDG
|CR.3.M
|0
|
|-
|EdPriDuration
|Duration
|OPRI
|299932
|1
|EDUCATION
|-
|EdSecLowerDuration
|Duration
|OPRI
|999976
|1
|EDUCATION
|-
|EdSecUpperDuration
|Duration
|OPRI
|999978
|1
|EDUCATION
|-
|EdPrePriDuration
|Duration
|OPRI
|299929
|0
|
|-
|EdPostSecDuration
|Duration
|OPRI
|999988
|0
|
|-
|EdSecDuration
|Duration
|OPRI
|THDUR.2T3
|0
|
|-
|EdExpISCED1-4Cap%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNCAP + XSPENDP.2.FDPUB.FNCAP + XSPENDP.3.FDPUB.FNCAP + XSPENDP.4.FDPUB.FNCAP
|0
|
|-
|EdExpISCED1-4TotalCur%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNCUR + XSPENDP.2.FDPUB.FNCUR + XSPENDP.3.FDPUB.FNCUR + XSPENDP.4.FDPUB.FNCUR
|0
|
|-
|EdExpISCED1-4NonSalCur%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNNONS + XSPENDP.2.FDPUB.FNNONS + XSPENDP.3.FDPUB.FNNONS + XSPENDP.4.FDPUB.FNNONS
|0
|
|-
|EdExpISCED1-4Sal%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNS + XSPENDP.2.FDPUB.FNS + XSPENDP.3.FDPUB.FNS + XSPENDP.4.FDPUB.FNS
|0
|
|-
|EdExpTerCap%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNCAP
|0
|
|-
|EdExpTertTotalCur%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNCUR
|0
|
|-
|EdExpTertNonSalCur%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNNONS
|0
|
|-
|EdExpTertSal%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNS
|0
|
|-
|EdSecLowerAdultGrads25Total%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99
|0
|
|-
|EdSecLowerAdultGrads25Female%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99.F
|0
|
|-
|EdSecLowerAdultGrads25Male%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99.M
|0
|
|-
|EdPriEnrollHeadCountTtl
|Enrollment Headcount
|OPRI
|20062
|0
|
|-
|EdPriEnrollHeadcountFem
|Enrollment Headcount
|OPRI
|20063
|0
|
|-
|EdSecLowerEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|20064
|0
|
|-
|EdSecLowerEnrollHeadcountFemale
|Enrollment Headcount
|OPRI
|20065
|0
|
|-
|EdSecUpperEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|20070
|0
|
|-
|EdSecUpperEnrollHeadcountFemale
|Enrollment Headcount
|OPRI
|20071
|0
|
|-
|EdSecEnrNoTot
|Enrollment Headcount
|OPRI
|20082
|0
|
|-
|EdSecEnrNoFem
|Enrollment Headcount
|OPRI
|20083
|0
|
|-
|EdTerEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|25053
|0
|
|-
|EdTerEnrollHeadcountFem
|Enrollment Headcount
|OPRI
|25057
|0
|
|-
|EdPriEnrollHeadcountMal
|Enrollment Headcount
|OPRI
|40035
|0
|
|-
|EdSecLowerEnrollHeadcountMale
|Enrollment Headcount
|OPRI
|40038
|0
|
|-
|EdSecUpperEnrollHeadCountMale
|Enrollment Headcount
|OPRI
|40041
|0
|
|-
|EdSecEnrNoMal
|Enrollment Headcount
|OPRI
|40044
|0
|
|-
|EdTerEnrISCED6HdctMale
|Enrollment Headcount
|OPRI
|42615
|0
|
|-
|EdTerEnrollHeadcountMale
|Enrollment Headcount
|OPRI
|42620
|0
|
|-
|EdTerEnrISCED6HdctFem
|Enrollment Headcount
|OPRI
|42635
|0
|
|-
|EdTerEnrISCED6HdctTot
|Enrollment Headcount
|OPRI
|42654
|0
|
|-
|GovtEdPub%GDP
|Government Expenditure
|OPRI
|XGDP.02.FSGOV + XGDP.1.FSGOV + XGDP.2.FSGOV + XGDP.3.FSGOV + XGDP.4.FSGOV + XGDP.5T8.FSGOV
|1
|ECONOMY
|-
|EdExpPrePri%EducTot
|Government Expenditure
|OPRI
|X.USCONST.02.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpPri%EducTot
|Government Expenditure
|OPRI
|X.USCONST.1.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSecLowr%EducTot
|Government Expenditure
|OPRI
|X.USCONST.2.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSec%EducTot
|Government Expenditure
|OPRI
|X.USCONST.2T3.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSecUppr%EducTot
|Government Expenditure
|OPRI
|X.USCONST.3.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpTer%EducTot
|Government Expenditure
|OPRI
|X.USCONST.5T8.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdPriEnrollGrossTotalPcnt
|Gross enrolment ratio
|OPRI
|GER.1
|1
|EDUCATION
|-
|EdPriEnrollGrossFemalePcnt
|Gross enrolment ratio
|OPRI
|GER.1.F
|1
|EDUCATION
|-
|EdPriEnrollGrossMalePcnt
|Gross enrolment ratio
|OPRI
|GER.1.M
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.2
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.2.F
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.2.M
|1
|EDUCATION
|-
|EdSecEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.2T3
|1
|EDUCATION
|-
|EdSecEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.2T3.F
|1
|EDUCATION
|-
|EdSecEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.2T3.M
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.3
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.3.F
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.3.M
|1
|EDUCATION
|-
|EdTerEnrollGross%Total
|Gross enrolment ratio
|SDG
|GER.5T8
|1
|EDUCATION
|-
|EdTerEnrollGross%Female
|Gross enrolment ratio
|SDG
|GER.5T8.F
|1
|EDUCATION
|-
|EdTerEnrollGross%Male
|Gross enrolment ratio
|SDG
|GER.5T8.M
|1
|EDUCATION
|-
|EdBasicEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.1T2
|0
|
|-
|EdBasicEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.1T2.F
|0
|
|-
|EdBasicEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.1T2.M
|0
|
|-
|EdSecLowerEnrollGrossParity
|Gross enrolment ratio
|OPRI
|GER.2.GPIA
|0
|
|-
|EdSecEnrollGross%Parity
|Gross enrolment ratio
|OPRI
|GER.2T3.GPIA
|0
|
|-
|EdSecUpperEnrollGrossParity
|Gross enrolment ratio
|OPRI
|GER.3.GPIA
|0
|
|-
|EdSecUpperEnrollGrossParityNew
|Gross enrolment ratio
|OPRI
|GER.3.GPIA
|0
|
|-
|EdTerFemaleMaleRatio
|Gross enrolment ratio
|SDG
|GER.5T8.GPIA
|0
|
|-
|EdTerGradRate1stDegreeTotal%
|Gross graduation ratio
|OPRI
|GGR.6T7
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeFemale%
|Gross graduation ratio
|OPRI
|GGR.6T7.F
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeMale%
|Gross graduation ratio
|OPRI
|GGR.6T7.M
|1
|EDUCATION
|-
|EdPriAIRTotal%
|Gross intake ratio
|SDG
|AIR.1.GLAST
|1
|EDUCATION
|-
|EdPriAIRFemale%
|Gross intake ratio
|SDG
|AIR.1.GLAST.F
|1
|EDUCATION
|-
|EdPriAIRMale%
|Gross intake ratio
|SDG
|AIR.1.GLAST.M
|1
|EDUCATION
|-
|EdPriAIRParity
|Gross intake ratio
|SDG
|AIR.1.GLAST.GPIA
|0
|
|-
|EdPri2and3ParityGenderMath
|MATH
|SDG
|MATH.G2T3.GPIA
|0
|
|-
|EdPri2and3ParityRurUrbMath
|MATH
|SDG
|MATH.G2T3.LPIA
|0
|
|-
|EdPri2and3ParitySocioeconMath
|MATH
|SDG
|MATH.G2T3.WPIA
|0
|
|-
|EdSecLwrParityGenderMath
|MATH
|SDG
|MATH.LOWERSEC.GPIA
|0
|
|-
|EdSecLwrParityRurUrbMath
|MATH
|SDG
|MATH.LOWERSEC.LPIA
|0
|
|-
|EdSecLwrParitySocioeconMath
|MATH
|SDG
|MATH.LOWERSEC.WPIA
|0
|
|-
|EdPriParityGenderMath
|MATH
|SDG
|MATH.PRIMARY.GPIA
|0
|
|-
|EdPriParityRurUrbMath
|MATH
|SDG
|MATH.PRIMARY.LPIA
|0
|
|-
|EdPriParitySocioeconMath
|MATH
|SDG
|MATH.PRIMARY.WPIA
|0
|
|-
|EdPriEntranceAge
|Official entrance age
|OPRI
|299905
|1
|EDUCATION
|-
|EdPriOutofSchoolTotal%
|Out-of-school rate
|SDG
|ROFST.1.CP
|0
|
|-
|EdPriOutofSchoolFemale%
|Out-of-school rate
|SDG
|ROFST.1.F.CP
|0
|
|-
|EdPriOutofSchoolMale%
|Out-of-school rate
|SDG
|ROFST.1.M.CP
|0
|
|-
|EdEnrollPrivate%Primary
|Percentage of enrolment in private
|OPRI
|PRP.1
|0
|
|-
|EdEnrollPrivate%Lower2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.2
|0
|
|-
|EdEnrollPrivateAll2ndaryCombined
|Percentage of enrolment in private
|OPRI
|PRP.2T3
|0
|
|-
|EdEnrollPrivate%Upper2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.3
|0
|
|-
|EdEnrollPrivateUpper2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.3
|0
|
|-
|EdTerGrads%SciEngg
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F500
|1
|EDUCATION
|-
|EdTerGrads%Sci
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F500 + FOSGP.5T8.600
|0
|
|-
|EdTerGrads%Engg
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F700
|0
|
|-
|EdTerGrads%Ag
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F800
|0
|
|-
|EdTerGrads%Health
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F900
|0
|
|-
|EDPriPTR
|PTR
|OPRI
|20062/20162
|1
|EDUCATION
|-
|PupilTeacherRatioUISPrimary
|PTR
|OPRI
|20062/20162
|0
|
|-
|EdSecLowrPTR
|PTR
|OPRI
|20064/20164
|0
|
|-
|PupilTeacherRatioUISSecondary
|PTR
|OPRI
|20082/20182
|0
|
|-
|EdPrePriParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.02.TRAINED
|0
|
|-
|EdPriParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.1.TRAINED
|0
|
|-
|PupilTrainedTeacherRatioUISPrimary
|Pupil-trained teacher ratio
|SDG
|PTRHC.1.TRAINED
|0
|
|-
|EdSecLwrParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.2.TRAINED
|0
|
|-
|PupilTrainedTeacherRatioUISSecondary
|Pupil-trained teacher ratio
|SDG
|PTRHC.2T3.TRAINED
|0
|
|-
|EdSecUpperParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.3.TRAINED
|0
|
|-
|R&DGovt%GDP
|R&D%GDP
|SCN-SDG
|EXPGDP.TOT
|1
|ECONOMY
|-
|EdPri2and3ParityGenderRead
|READ
|SDG
|READ.G2T3.GPIA
|0
|
|-
|EdPri2and3ParityRurUrbRead
|READ
|SDG
|READ.G2T3.LPIA
|0
|
|-
|EdPri2and3ParitySocioeconRead
|READ
|SDG
|READ.G2T3.WPIA
|0
|
|-
|EdSecLwrParityGenderRead
|READ
|SDG
|READ.LOWERSEC.GPIA
|0
|
|-
|EdSecLwrParityRurUrbRead
|READ
|SDG
|READ.LOWERSEC.LPIA
|0
|
|-
|EdSecLwrParitySocioeconRead
|READ
|SDG
|READ.LOWERSEC.WPIA
|0
|
|-
|EdPriParityGenderRead
|READ
|SDG
|READ.PRIMARY.GPIA
|0
|
|-
|EdPriParityRurUrbRead
|READ
|SDG
|READ.PRIMARY.LPIA
|0
|
|-
|EdPriParitySocioeconRead
|READ
|SDG
|READ.PRIMARY.WPIA
|0
|
|-
|EdPriRepeaterTotal%
|Repetition rate
|OPRI
|REPR.1.CP
|0
|
|-
|EdPriRepeaterFemale%
|Repetition rate
|OPRI
|REPR.1.F.CP
|0
|
|-
|EdPriRepeater1stYearTotal%
|Repetition rate
|OPRI
|REPR.1.G1.CP
|0
|
|-
|EdPriRepeater1stYearFemale%
|Repetition rate
|OPRI
|REPR.1.G1.F.CP
|0
|
|-
|EdPriRepeater1stYearMale%
|Repetition rate
|OPRI
|REPR.1.G1.M.CP
|0
|
|-
|EdPriRepeaterMale%
|Repetition rate
|OPRI
|REPR.1.M.CP
|0
|
|-
|EdExpectedYearsofSchooling
|School life expectancy
|OPRI
|SLE.1T8
|0
|
|-
|EdExpectedYearsofSchoolingFemale
|School life expectancy
|OPRI
|SLE.1T8.F
|0
|
|-
|EdExpectedYearsofSchoolingMale
|School life expectancy
|OPRI
|SLE.1T8.M
|0
|
|-
|EdSecLowerVoc%AllTotal
|Share of all students in vocational programmes
|OPRI
|GTVP.2.V
|1
|EDUCATION
|-
|EdSecUpperVoc%AllTotal
|Share of all students in vocational programmes
|OPRI
|GTVP.3.V
|1
|EDUCATION
|-
|EdSecVoc%Tot
|Share of all students in vocational programmes
|OPRI
|GTVP.2T3.V
|0
|
|-
|EdPriSurvivalTotal%
|Survival rate
|OPRI
|SR.1.GLAST.CP
|1
|EDUCATION
|-
|EdPriSurvivalFemale%
|Survival rate
|OPRI
|SR.1.GLAST.F.CP
|1
|EDUCATION
|-
|EdPriSurvivalMale%
|Survival rate
|OPRI
|SR.1.GLAST.M.CP
|1
|EDUCATION
|-
|EdPriSurvivalParity
|Survival rate
|OPRI
|SR.1.GLAST.GPIA
|0
|
|-
|EdPriEnrollNetTotalPcnt
|Total net enrolment rate
|OPRI
|NERT.1.CP
|1
|EDUCATION
|-
|EdPriEnrollNetFemalePcnt
|Total net enrolment rate
|OPRI
|NERT.1.F.CP
|1
|EDUCATION
|-
|EdPriEnrollNetMalePcnt
|Total net enrolment rate
|OPRI
|NERT.1.M.CP
|1
|EDUCATION
|-
|EdPriEnrollNetParity
|Total net enrolment rate
|OPRI
|NERT.1.GPIA
|0
|
|-
|EdSecLowerNetEnrollTot%
|Total net enrolment rate
|OPRI
|NERT.2.CP
|0
|
|-
|EdSecLowerNetEnrollFemale%
|Total net enrolment rate
|OPRI
|NERT.2.F.CP
|0
|
|-
|EdSecLowerNetEnrollMale%
|Total net enrolment rate
|OPRI
|NERT.2.M.CP
|0
|
|-
|EdSecUpperNetEnrollTot%
|Total net enrolment rate
|OPRI
|NERT.3.CP
|0
|
|-
|EdSecUpperNetEnrollFemale%
|Total net enrolment rate
|OPRI
|NERT.3.F.CP
|0
|
|-
|EdSecUpperNetEnrollMale%
|Total net enrolment rate
|OPRI
|NERT.3.M.CP
|0
|
|}

== Pulling Data on Enrollment in Vocational Programmes: ==
The pre-processor series in IFs relating to enrollment in vocational programmes are:

#EdSecUpperVoc%AllMale
#EdSecUpperVoc%AllFemale
#EdSecUpperVoc%AllTotal
#EdSecLowerVoc%AllMale
#EdSecLowerVoc%Allfemale
#EdSecLowerVoc%AllTotal

Data for these series was obtained from the UIS Education Database in the following drop down menu sequence: Education>Participation>Distribution of Enrollment>Distribution of Enrollment by Programme Orientation.

Because these particular series contain confusing wording, the full names in UIS of each fo the six series are provided below.

#'''Percentage of male students in lower secondary education enrolled in vocational programmes, male (%)'''
#'''Percentage of female students in lower secondary education enrolled in vocational programmes, female (%)'''
#'''Percentage of students in lower secondary education enrolled in vocational programmes, both sexes (%)'''
#'''Percentage of male students in upper secondary education enrolled in vocational programmes, male (%)'''
#'''Percentage of female students in upper secondary education enrolled in vocational programmes, female (%)'''
#'''Percentage of students in upper secondary education enrolled in vocational programmes, both sexes (%)'''

== Pulling Data on Educational Expenditure: ==
The pre-processor series in IFs relating to educational expenditure are:

#EdExpPri%GDPPC
#EdExpSec%GDPPC
#EdExpSecLowr%GDPPC
#EdExpSecUppr%GDPPC
#EdExpTer%GDPP

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Financial Resources>Government Expenditure per Student>Government Expenditure per Student as Percentage of GDP per capita. 

Once here, the following 5 sheets were used: '''Government expenditure per (primary/secondary/lower seconday/upper seconday/tertiary) student as percentage of GDP per capita.'''

== Pulling Data on Graduation Rates: ==
The pre-processor series in IFs relating to graduation rates are:

#EdTerGradRate1stDegreeFemale% 
#EdterGradRate1stDegreeMale%
#EdTerGradRate1stDegreeTotal%
#EdTerGrad%SciEngg
#EdPriCompletionFemale%
#EdPriCompletionMale%
#EdPriCompletionTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Completion and Graduation Ratios>Gross Graduation Ratio.

Once here, the following 4 sheets were used: '''Gross Graduation Ratio from First Degree Programmes (ISCED 6 & 7) in Tertiary Education, (Female (%)/Male (%)/Both Sexes (%)).'''

For 5-7 above, the following 3sheets were used:'''(Gross Graduation Ratio from Primary Education, (Female(%)/Male(%)/Both Sexes (%)).'''

== Pulling Data on Completion Rates: ==
The pre-processor series in IFs relating to graduation rates are:

#EdSecLowrCompletionFemale
#EdSecLowrCompletionMale
#EdSecLowrCompletionTotal
#EdSecUpprCompletionFemale
#EdSecUpprCompletionMale
#EdSecUpprCompletionTotal

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following dropdown menu sequence: Education>Education>Completion>Completion and graduation ratios. The specific location for each series is as follows.

*EdPriCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), select female (%) from dropdown
*EdPriCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), select male (%) from dropdown
*EdPriCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), Both Sexes (%)
*EdSecLowrCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select female (%) from dropdown
*EdSecLowrCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select male (%) from dropdown
*EdSecLowrCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select both sexes (%) from dropdown
*EdSecUpprCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select female (%) from dropdown
*EdSecUpprCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select male (%) from dropdown
*EdSecUpprCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select both sexes (%) from dropdown

== Pulling Data on Intake Rates: ==
The pre-processor series in IFs relating to apparent (gross) intake rates are:

#EdPriAIRFemale%
#EdPriAIRMale%
#EdPriAIRParity
#EdPriAIRTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Entry>Gross (Apparent) Intake Ratio to Primary and Lower Secondary Education.

Once here, the following three sheets were used: '''Gross Intake Rate to Grade 1 of Primary Education, (Female%/Male%/Total/GenderParityIndex (GPI)).'''

The pre-processor series in IFs relating to net (adjusted) intake rates are:

#EdPriNIRFemale%
#EdPriNIRMale%
#EdPriNIRTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Entry>Gross (Apparent) Intake Ratio to Primary and Lower Secondary Education.

Once here, the following three sheets were used: Adjusted Net Intake Rate to Grade 1 of Primary Education, '''(Female/Male/Total).'''

'''Net Intake Rate to Grade1 of Primary Education'''

EDPRINIRENTRNFemale

EDPRINIRENTRNMale

EDPRINIRENTRNTotal

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education, female (%)
*education>entry>net intake rate to primary education> Net Intake Rate to Grade1 of Primary Education male (%)
*education>entry>net intake rate to primary education> Net Intake Rate to Grade1 of Primary Education both sexes (%)

'''Net Intake Rate to Grade1 of Primary Education (over-age by +1 year)'''

EDPRINIRENTRNP1Male

EDPRINIRENTRNP1Female

EDPRINIRENTRNP1Total

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), male (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), female (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), both sexes (%) 
'''Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), male (%)'''

EDPRINIRENTRNM1Male

EDPRINIRENTRNM1Female

EDPRINIRENTRNM1Total

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), male (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), female (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), both sexes (%) 
'''Adjusted Net Intake Rate to Grade1 of Primary Education'''

EDPRINIRADJFemale

EDPRINIRADJMale

EDPRINIRADJTotal

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, female (%)
*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, male (%)
*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, both sexes (%)

== Pulling Data on Survival Rates: ==
The pre-processor series in IFs relating to survival rates are:

#EdPriSurvivalFemale%
#EdPriSurvivalMale%
#EdPriSurvivalTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Progression>Survival Rates>Survival Rate to Last Grade of Primary Education.

Once here, the following three sheets were used: '''Survival Rate to the Last Grade of Primary Education, (Female%/Male%/Total%).'''

== Pulling Data on Duration: ==
The pre-processor series in IFs relating to survival rates are:

#EdPriDuration
#EdSecLowerDuration
#EdSecUpperDuration

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>System>Duration>Duration by Level of Education.

Once here, the following three sheets were used: '''Theoretical Duration of (Primary/Lower Seconday/Upper Secondary) Education.'''

== Pulling Data on Transition Rates: ==
The pre-processor series in IFs relating to transition rates are:

#EdPriTransition2Sec%Female
#EdPriTransition2Sec%Male
#EdPriTransition2SecTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Progression>Transition Rates.

Once here, the following three sheets were used: '''Effective Transition Rate from Primary to Lower Secondary General Education, (Female%/Male%/Total%).'''

= Data Notes =

#As of May 2016, there was no data for 2015 for the LowerVoc series, only 1999-2014. However, there was 2015 data  for the UpperVoc series.
#Country Concordance: UNESCO countries. 
##As of March 2017, UIS utilizes "Cabo Verde" instead of "Cape Verde." The UNESCO Country Concordance utilizes "Cape Verde." '''You thus must replace "Cabo Verde" with "Cape Verde" in UIS data prior to importing into IFs.'''

File:Files in Zipped Folder.png

2026-01-24T21:38:32Z

Norah.Shamin:

Files in Zipped Folder

Institute for Statistics, UNESCO (UIS)

2026-01-24T21:30:14Z

Norah.Shamin:

= Summary =
The United Nations Statistics Division, UIS Education Database is the most comprehensive education databse in the world, containing data from more than 200 countries and territories. The UIS has the mandate to monitor progress towards Education for All and education-related Millennium Development Goals. The statistics, which are updated twice a year, are used by diverse partners, including governments, donor agencies and other UN organizations. In particular, the UIS is the primary education data source for the Education for All Global Monitoring Report, the World Development Indicators and the Human Development Report Data is collected through the UIS annual education survey, which covers all education levels and a range of issues such as enrolment rate, gender parity, teachers, and financing.

The IFs system uses data from the UIS Education Database on a wide variety of topics relating to education. The following sections provide instructions for pulling data from the UIS Education Database for IFs pre-processor series in the Education submodule.

= Tables In IFs =
Preprocessors
{| class="wikitable"
|+
!Table
!Definition
!Name in Source
!UsedInPreprocessorFileName
!Source in Code
|-
|EDPriPTR
|Primary pupil-teacher ratio
|Enrolment in primary education, both sexes (number)/Teachers in primary education, both sexes (number)
|EDUCATION
|20062/20162
|-
|EdPriAIRFemale%
|Education, Primary, Apparent (gross) intake rate in grade 1, female (% of relevant age group)
|Gross intake ratio to the last grade of primary education, female (%)
|EDUCATION
|AIR.1.GLAST.F
|-
|EdPriAIRMale%
|Education, Primary, Apparent (gross) intake rate in grade 1, male (% of relevant age group)
|Gross intake ratio to the last grade of primary education, male (%)
|EDUCATION
|AIR.1.GLAST.M
|-
|EdPriAIRTotal%
|Education, Primary, Apparent (gross) intake rate in grade 1, total (% of relevant age group)
|Gross intake ratio to the last grade of primary education, both sexes (%)
|EDUCATION
|AIR.1.GLAST
|-
|EdPriCompletionFemale%
|Education, Primary, completion rate (school graduation age), gross, Female
|Completion rate, primary education, female (%)
|EDUCATION
|CR.1.F
|-
|EdPriCompletionMale%
|Education, Primary, completion rate (school graduation age), gross, Male
|Completion rate, primary education, male (%)
|EDUCATION
|CR.1.M
|-
|EdPriCompletionTotal%
|Education, Primary, completion rate (graduation ratio), gross, both sexes
|Completion rate, primary education, both sexes (%)
|EDUCATION
|CR.1
|-
|EdPriDuration
|Education, Primary, completion rate (graduation ratio), gross, total
|Theoretical duration of primary education (years)
|EDUCATION
|299932
|-
|EdPriEnrollGrossFemalePcnt
|Education, Primary, Enrollment Rate Gross, female
|Gross enrolment ratio, primary, female (%)
|EDUCATION
|GER.1.F
|-
|EdPriEnrollGrossMalePcnt
|Education, Primary, Enrollment Rate Gross, male
|Gross enrolment ratio, primary, male (%)
|EDUCATION
|GER.1.M
|-
|EdPriEnrollGrossTotalPcnt
|Education, Primary, Enrollment Rate Gross (% Total)
|Gross enrolment ratio, primary, both sexes (%)
|EDUCATION
|GER.1
|-
|EdPriEnrollNetFemalePcnt
|Education, Primary, Net Enrollment Rate, Female
|Total net enrolment rate, primary, female (%)
|EDUCATION
|NERT.1.F.CP
|-
|EdPriEnrollNetMalePcnt
|Education, Primary, Net Enrollment Rate, Male
|Total net enrolment rate, primary, male (%)
|EDUCATION
|NERT.1.M.CP
|-
|EdPriEnrollNetTotalPcnt
|Education, Primary, Net Enrollment Rate, Total
|Total net enrolment rate, primary, both sexes (%)
|EDUCATION
|NERT.1.CP
|-
|EdPriEntranceAge
|Education Primary Entrance Age
|Official entrance age to primary education (years)
|EDUCATION
|299905
|-
|EdPriSurvivalFemale%
|Education, Primary, percentage of entrants persisting to last grade, female
|Survival rate to the last grade of primary education, female (%)
|EDUCATION
|SR.1.GLAST.F.CP
|-
|EdPriSurvivalMale%
|Education, Primary, percentage of entrants persisting to last grade, male
|Survival rate to the last grade of primary education, male (%)
|EDUCATION
|SR.1.GLAST.M.CP
|-
|EdPriSurvivalTotal%
|Education, Primary, percentage of entrants persisting to last grade, total
|Survival rate to the last grade of primary education, both sexes (%)
|EDUCATION
|SR.1.GLAST.CP
|-
|EdSecEnrollGross%Female
|Education, Secondary, gross enrollment rate, female
|Gross enrolment ratio, secondary, female (%)
|EDUCATION
|GER.2T3.F
|-
|EdSecEnrollGross%Male
|Education, Secondary, gross enrollment rate, male
|Gross enrolment ratio, secondary, male (%)
|EDUCATION
|GER.2T3.M
|-
|EdSecEnrollGross%Total
|Education, Secondary, gross enrollment rate, total
|Gross enrolment ratio, secondary, both sexes (%)
|EDUCATION
|GER.2T3
|-
|EdSecLowerDuration
|Education Duration of Lower Secondary
|Theoretical duration of lower secondary education (years)
|EDUCATION
|999976
|-
|EdSecLowerEnrollGross%Female
|Education, Secondary, Lower, Gross Enrollment Rate All Programs, Female
|Gross enrolment ratio, lower secondary, female (%)
|EDUCATION
|GER.2.F
|-
|EdSecLowerEnrollGross%Male
|Education, Secondary, Lower, Gross Enrollment Rate All Programs, Male
|Gross enrolment ratio, lower secondary, male (%)
|EDUCATION
|GER.2.M
|-
|EdSecLowerEnrollGross%Total
|Education, Secondary, Lower, Gross Enrollment Rate, Total
|Gross enrolment ratio, lower secondary, both sexes (%)
|EDUCATION
|GER.2
|-
|EdSecLowerVoc%AllTotal
|Education, Secondary, Lower, Vocational as % of All Program Enrollments, Total
|Share of all students in lower secondary education enrolled in vocational programmes (%)
|EDUCATION
|GTVP.2.V
|-
|EdSecUpperDuration
|Education, Secondary, Upper, Duration of Upper Secondary
|Theoretical duration of upper secondary education (years)
|EDUCATION
|999978
|-
|EdSecUpperEnrollGross%Female
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Female
|Gross enrolment ratio, upper secondary, female (%)
|EDUCATION
|GER.3.F
|-
|EdSecUpperEnrollGross%Male
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Male
|Gross enrolment ratio, upper secondary, male (%)
|EDUCATION
|GER.3.M
|-
|EdSecUpperEnrollGross%Total
|Education, Secondary, Upper, Gross Enrollment Rate All Programs, Total
|Gross enrolment ratio, upper secondary, both sexes (%)
|EDUCATION
|GER.3
|-
|EdSecUpperVoc%AllTotal
|Education, Secondary, Upper, Vocational as % of All Program Enrollments, Total
|Share of all students in upper secondary education enrolled in vocational programmes (%)
|EDUCATION
|GTVP.3.V
|-
|EdTerEnrollGross%Female
|Education, Tertiary, Gross Enrollment Rate, Female
|Gross enrolment ratio for tertiary education, female (%)
|EDUCATION
|GER.5T8.F
|-
|EdTerEnrollGross%Male
|Education, Tertiary, Gross Enrollment Rate, Male
|Gross enrolment ratio for tertiary education, male (%)
|EDUCATION
|GER.5T8.M
|-
|EdTerEnrollGross%Total
|Education, Tertiary, Gross Enrollment Rate, Total
|Gross enrolment ratio for tertiary education, both sexes (%)
|EDUCATION
|GER.5T8
|-
|EdTerGradRate1stDegreeFemale%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, female
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, female (%)
|EDUCATION
|GGR.6T7.F
|-
|EdTerGradRate1stDegreeMale%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, male
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, male (%)
|EDUCATION
|GGR.6T7.M
|-
|EdTerGradRate1stDegreeTotal%
|Education, Tertiary, Gross Graduation Ratio, ISCED 6 and 7, first degree, total
|Gross graduation ratio from first degree programmes (ISCED 6 and 7) in tertiary education, both sexes (%)
|EDUCATION
|GGR.6T7
|-
|EdTerGrads%SciEngg
|Education, Tertiary, Science and Enginnering Graduates as % of Total Graduates
|Percentage of graduates from tertiary education graduating from Natural Sciences, Mathematics and Statistics programmes, both sexes (%)
|EDUCATION
|FOSGP.5T8.F500
|-
|GovtEdPub%GDP
|Educational expenditures (public) as percent of GDP
|Government expenditure on pre-primary education as a percentage of GDP (%) + Government expenditure on primary education as a percentage of GDP (%) + Government expenditure on lower secondary education as a percentage of GDP (%) + Government expenditure on upper secondary education as a percentage of GDP (%) + Government expenditure on post-secondary non-tertiary education as a percentage of GDP (%) + Government expenditure on tertiary education as a percentage of GDP (%)
|ECONOMY
|XGDP.02.FSGOV + XGDP.1.FSGOV + XGDP.2.FSGOV + XGDP.3.FSGOV + XGDP.4.FSGOV + XGDP.5T8.FSGOV
|-
|R&DGovt%GDP
|Gross R&D expenditure by government
|GERD as a percentage of GDP
|ECONOMY
|EXPGDP.TOT
|}
Non-preprocessors
{| class="wikitable"
|+
!Table
!Definition
!Name in Source
!Source in Code
!Formula
|-
|EdBasicEnrollGross%Female
|Education, Basic, Enrollment Rate, Gross, Female
|Gross enrolment ratio, primary and lower secondary, female (%)
|GER.1T2.F
|
|-
|EdBasicEnrollGross%Male
|Education, Basic, Enrollment Rate, Gross, Male
|Gross enrolment ratio, primary and lower secondary, male (%)
|GER.1T2.M
|
|-
|EdBasicEnrollGross%Total
|Education, Basic, Enrollment Rate, Gross, Total
|Gross enrolment ratio, primary and lower secondary, both sexes (%)
|GER.1T2
|
|-
|EdEnrollPrivate%Lower2ndaryGeneral
|Education enrollments private as % of lower secondary general
|Percentage of enrolment in lower secondary education in private institutions (%)
|PRP.2
|
|-
|EdEnrollPrivate%Primary
|Education enrollment private as % of primary
|Percentage of enrolment in primary education in private institutions (%)
|PRP.1
|
|-
|EdEnrollPrivate%Upper2ndaryGeneral
|Education enrollments private as % of upper secondary general
|Percentage of enrolment in upper secondary education in private institutions (%)
|PRP.3
|
|-
|EdEnrollPrivateAll2ndaryCombined
|Education enrollment private all secondary combined
|Percentage of enrolment in secondary education in private institutions (%)
|PRP.2T3
|
|-
|EdEnrollPrivateUpper2ndaryGeneral
|Education enrollment private upper secondary general
|Percentage of enrolment in upper secondary education in private institutions (%)
|PRP.3
|
|-
|EdExpISCED1-4Cap%
|Education expenditures, ISCED 1-4, capital portion
|Capital expenditure as a percentage of total expenditure in primary public institutions (%) + Capital expenditure as a percentage of total expenditure in lower secondary public institutions (%) + Capital expenditure as a percentage of total expenditure in upper-secondary public institutions (%) + Capital expenditure as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNCAP + XSPENDP.2.FDPUB.FNCAP + XSPENDP.3.FDPUB.FNCAP + XSPENDP.4.FDPUB.FNCAP
|
|-
|EdExpISCED1-4NonSalCur%
|Education expenditures, ISCED 1-4, non-salary current portion
|Current expenditure other than staff compensation as a percentage of total expenditure in primary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in lower secondary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in upper secondary public institutions (%) + Current expenditure other than staff compensation as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNNONS + XSPENDP.2.FDPUB.FNNONS + XSPENDP.3.FDPUB.FNNONS + XSPENDP.4.FDPUB.FNNONS
|
|-
|EdExpISCED1-4Sal%
|Education expenditures, ISCED 1-4, salary portion
|All staff compensation as a percentage of total expenditure in primary public institutions (%) + All staff compensation as a percentage of total expenditure in lower secondary public institutions (%) + All staff compensation as a percentage of total expenditure in upper secondary public institutions (%) + All staff compensation as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNS + XSPENDP.2.FDPUB.FNS + XSPENDP.3.FDPUB.FNS + XSPENDP.4.FDPUB.FNS
|
|-
|EdExpISCED1-4TotalCur%
|Education expenditures, ISCED 1-4, total current portion
|Current expenditure as a percentage of total expenditure in primary public institutions (%) + Current expenditure as a percentage of total expenditure in lower secondary public institutions (%) + Current expenditure as a percentage of total expenditure in upper-secondary public institutions (%) + Current expenditure as a percentage of total expenditure in post-secondary non-tertiary public institutions (%)
|XSPENDP.1.FDPUB.FNCUR + XSPENDP.2.FDPUB.FNCUR + XSPENDP.3.FDPUB.FNCUR + XSPENDP.4.FDPUB.FNCUR
|
|-
|EdExpPrePri%EducTot
|Educational expenditure in pre-primary as % of total educational expenditure
|Government expenditure on pre-primary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.02.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpPri%EducTot
|Education expenditure in primary as % of total educational expenditure
|Government expenditure on primary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.1.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSec%EducTot
|Education Expenditure Secondary as % of Total Educational Expenditure
|Government expenditure on secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.2T3.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSecLowr%EducTot
|Educational expenditure in lower secondary as % of total educational expenditure
|Government expenditure on lower secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.2.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpSecUppr%EducTot
|Educational expenditure in upper secondary as % of total educational expenditure
|Government expenditure on upper secondary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.3.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpTer%EducTot
|Education Expenditure Tertiary as % of Total Educational Expenditure
|Government expenditure on tertiary education, constant US$ (millions)/Government expenditure on education, constant US$ (millions)
|X.USCONST.5T8.FSGOV/X.USCONST.FSGOV
|
|-
|EdExpTerCap%
|Education expenditures, tertiary, capital portion
|Capital expenditure as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNCAP
|
|-
|EdExpTertNonSalCur%
|Education expenditures, tertiary, non-salary current portion
|Current expenditure other than staff compensation as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNNONS
|
|-
|EdExpTertSal%
|Education expenditures, tertiary, salary portion
|All staff compensation as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNS
|
|-
|EdExpTertTotalCur%
|Education expenditures, tertiary, total current portion
|Current expenditure as a percentage of total expenditure in tertiary public institutions (%)
|XSPENDP.5T8.FDPUB.FNCUR
|
|-
|EdExpectedYearsofSchooling
|Expected years of schooling for a child of school entering age
|School life expectancy, primary to tertiary, both sexes (years)
|SLE.1T8
|
|-
|EdExpectedYearsofSchoolingFemale
|Expected years of schooling for a child of school entering age, female
|School life expectancy, primary to tertiary, female (years)
|SLE.1T8.F
|
|-
|EdExpectedYearsofSchoolingMale
|Expected years of education for a child of school going age, male
|School life expectancy, primary to tertiary, male (years)
|SLE.1T8.M
|
|-
|EdPostSecDuration
|Education, Post-Secondary Non-Tertiary, Cycle Length
|Theoretical duration of post-secondary non-tertiary education (years)
|999988
|
|-
|EdPrePriDuration
|Education, Pre-Primary, Cycle Length
|Theoretical duration of pre-primary education (years)
|299929
|
|-
|EdPrePriParityGenderTeachers
|Ratio of female to male teachers in pre-primary education who are trained
|Pupil-trained teacher ratio in pre-primary education (headcount basis)
|PTRHC.02.TRAINED
|
|-
|EdPri2and3ParityGenderMath
|Ratio of girls' to boys' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.G2.GPIA + MATH.G3.GPIA
|
|-
|EdPri2and3ParityGenderRead
|Ratio of girls' to boys' reading achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.G2.GPIA + READ.G3.GPIA
|
|-
|EdPri2and3ParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.G2.LPIA + MATH.G3.LPIA
|
|-
|EdPri2and3ParityRurUrbRead
|Ratio of rural to urban students' reading achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.G2.LPIA + READ.G3.LPIA
|
|-
|EdPri2and3ParitySocioeconMath
|Ratio of students from low to high socio-economic groups' mathematics achievement in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.G2.WPIA + MATH.G3.WPIA
|
|-
|EdPri2and3ParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading in grades 2 & 3
|Proportion of students in Grade 2 or 3 achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.G2.WPIA + READ.G3.WPIA
|
|-
|EdPriAIRParity
|Education, Primary, Apparent(gross) Intake Rate, Gender Parity Index
|Gross intake ratio to the last grade of primary education, adjusted gender parity index (GPIA)
|AIR.1.GLAST.GPIA
|
|-
|EdPriCompletionFemale
|Education, primary, completion rate from household survey data, female
|Completion rate, primary education, female (%)
|CR.1.F
|
|-
|EdPriCompletionFemale%BL
|Education, Primary, completion rate (graduation ratio), gross, Female
|Completion rate, primary education, female (%)
|CR.1.F
|
|-
|EdPriCompletionMale
|Education, primary, completion rate from household survey data, male
|Completion rate, primary education, male (%)
|CR.1.M
|
|-
|EdPriCompletionMale%BL
|Education, Primary, completion rate (graduation ratio), gross, Male
|Completion rate, primary education, male (%)
|CR.1.M
|
|-
|EdPriCompletionParity
|Education, Primary, Completion Rate, Gender Parity, New
|Completion rate, primary education, adjusted gender parity index (GPIA)
|CR.1.GPIA
|
|-
|EdPriCompletionTotal
|Education, primary, completion rate from household survey data, total
|Completion rate, primary education, both sexes (%)
|CR.1
|
|-
|EdPriCompletionTotal%BL
|Education, Primary, completion rate (graduation ratio), gross, total
|Completion rate, primary education, both sexes (%)
|CR.1
|
|-
|EdPriEnrollHeadCountTtl
|Education, Primary, Total Enrollment (male plus female)
|Enrolment in primary education, both sexes (number)
|20062
|*0.000001
|-
|EdPriEnrollHeadcountFem
|Female enrollment at primary level, in both public and private institutions
|Enrolment in primary education, female (number)
|20063
|*0.000001
|-
|EdPriEnrollHeadcountMal
|Male enrollment, primary level, in both public and private institutions
|Enrolment in primary education, male (number)
|40035
|*0.000001
|-
|EdPriEnrollNetParity
|Education, Primary, Net Enrollment Rate, Gender Parity Index
|Total net enrolment rate, primary, adjusted gender parity index (GPIA)
|NERT.1.GPIA
|
|-
|EdPriOutofSchoolFemale%
|Education primary, percentage of primary age children who are out of school, Female
|Out-of-school rate for children of primary school age, female (%)
|ROFST.1.F.CP
|
|-
|EdPriOutofSchoolMale%
|Education primary, percentage of primary age children who are out of school, Male
|Out-of-school rate for children of primary school age, male (%)
|ROFST.1.M.CP
|
|-
|EdPriOutofSchoolTotal%
|Education primary, percentage of primary age children who are out of school, total
|Out-of-school rate for children of primary school age, both sexes (%)
|ROFST.1.CP
|
|-
|EdPriParityGenderMath
|Ratio of girls' to boys' mathematics achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.PRIMARY.GPIA
|
|-
|EdPriParityGenderRead
|Ratio of girls' to boys' reading achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.PRIMARY.GPIA
|
|-
|EdPriParityGenderTeachers
|Ratio of female to male teachers in primary education who are trained
|Pupil-trained teacher ratio in primary education (headcount basis)
|PTRHC.1.TRAINED
|
|-
|EdPriParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.PRIMARY.LPIA
|
|-
|EdPriParityRurUrbRead
|Ratio of rural to urban students' reading achievement by the end of primary
|Proportion of students at the end of primary education achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.PRIMARY.LPIA
|
|-
|EdPriParitySocioeconMath
|Ratio of students from low to high socio-economic groups' achievement in mathematics by the end of primary
|Proportion of students at the end of primary achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.PRIMARY.WPIA
|
|-
|EdPriParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading by the end of primary
|Proportion of students at the end of primary education achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.PRIMARY.WPIA
|
|-
|EdPriRepeater1stYearFemale%
|Percentage of repeaters in primary. Grade 1.Female
|Repetition rate in Grade 1 of primary education, female (%)
|REPR.1.G1.F.CP
|
|-
|EdPriRepeater1stYearMale%
|Percentage of repeaters in primary. Grade 1.Male
|Repetition rate in Grade 1 of primary education, male (%)
|REPR.1.G1.M.CP
|
|-
|EdPriRepeater1stYearTotal%
|Percentage of repeaters in primary. Grade 1. Total
|Repetition rate in Grade 1 of primary education, both sexes (%)
|REPR.1.G1.CP
|
|-
|EdPriRepeaterFemale%
|Education Primary Percentage of Repeaters, all grades, female
|Repetition rate in primary education (all grades), female (%)
|REPR.1.F.CP
|
|-
|EdPriRepeaterMale%
|Education Primary Percentage of Repeaters, all grades, male
|Repetition rate in primary education (all grades), male (%)
|REPR.1.M.CP
|
|-
|EdPriRepeaterTotal%
|Education Primary Percentage of Repeaters, all grades, total
|Repetition rate in primary education (all grades), both sexes (%)
|REPR.1.CP
|
|-
|EdPriSurvivalParity
|Education, Primary, Survival to Last Grade, Gender Parity, New
|Survival rate to the last grade of primary education,adjusted gender parity index (GPIA)
|SR.1.GLAST.GPIA
|
|-
|EdSecDuration
|Duration of education, secondary
|Theoretical duration of secondary education (years)
|THDUR.2T3
|
|-
|EdSecEnrNoFem
|Education, secondary Enrollment Number, Female
|Enrolment in secondary education, female (number)
|20083
|*0.000001
|-
|EdSecEnrNoMal
|Education, secondary Enrollment Number, Male
|Enrolment in secondary education, male (number)
|40044
|*0.000001
|-
|EdSecEnrNoTot
|Education, Total Secondary, Total Enrollment (male plus female)
|Enrolment in secondary education, both sexes (number)
|20082
|*0.000001
|-
|EdSecEnrollGross%Parity
|secondary gross enrollment rate, all programs, Gender Parity Index, new data
|Gross enrolment ratio, secondary, adjusted gender parity index (GPIA)
|GER.2T3.GPIA
|
|-
|EdSecLowerAdultGrads25Female%
|Adult population (25 and over) with lower secondary (or more) education, female%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, female (%)
|EA.2T8.AG25T99.F
|
|-
|EdSecLowerAdultGrads25Male%
|Adult population (25 and over) with lower secondary (or more) education, male%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, male (%)
|EA.2T8.AG25T99.M
|
|-
|EdSecLowerAdultGrads25Total%
|Adult population (25 and over) with lower secondary (or more) education, total%
|Educational attainment rate, completed lower secondary education or higher, population 25+ years, both sexes (%)
|EA.2T8.AG25T99
|
|-
|EdSecLowerEnrollGrossParity
|Gender parity index for gross enrolment ratio. Lower secondary. All programmes
|Gross enrolment ratio, lower secondary, adjusted gender parity index (GPIA)
|GER.2.GPIA
|
|-
|EdSecLowerEnrollHeadcountFemale
|Education, lower secondary, headcount enrollment number, female
|Enrolment in lower secondary education, female (number)
|20065
|*0.000001
|-
|EdSecLowerEnrollHeadcountMale
|Education, lower secondary, headcount enrollment number , male
|Enrolment in lower secondary education, male (number)
|40038
|*0.000001
|-
|EdSecLowerEnrollHeadcountTotal
|Education, Lower Secondary, Total Enrollment (male plus female)
|Enrolment in lower secondary education, both sexes (number)
|20064
|*0.000001
|-
|EdSecLowerNetEnrollFemale%
|Net Lower Secondary Enrollment Rate, Female
|Total net enrolment rate, lower secondary, female (%)
|NERT.2.F.CP
|
|-
|EdSecLowerNetEnrollMale%
|Net Lower Secondary Enrollment Rate, Male
|Total net enrolment rate, lower secondary, male (%)
|NERT.2.M.CP
|
|-
|EdSecLowerNetEnrollTot%
|Net Lower Secondary Enrollment Rate, Total
|Total net enrolment rate, lower secondary, both sexes (%)
|NERT.2.CP
|
|-
|EdSecLowrCompletionFemale
|Education, lower secondary, completion rate from household survey data, female
|Completion rate, lower secondary education, female (%)
|CR.2.F
|
|-
|EdSecLowrCompletionMale
|Education, lower secondary, completion rate from household survey data, male
|Completion rate, lower secondary education, male (%)
|CR.2.M
|
|-
|EdSecLowrCompletionTotal
|Education, lower secondary, completion rate from household survey data, total
|Completion rate, lower secondary education, both sexes (%)
|CR.2
|
|-
|EdSecLowrPTR
|Education, lower secondary, pupil teacher ratio
|Enrolment in lower secondary education, both sexes (number)/Teachers in lower secondary education, both sexes (number)
|20064/20164
|
|-
|EdSecLwrParityGenderMath
|Ratio of girls' to boys' mathematics achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted gender parity index (GPIA)
|MATH.LOWERSEC.GPIA
|
|-
|EdSecLwrParityGenderRead
|Ratio of girls' to boys' reading achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in reading, adjusted gender parity index (GPIA)
|READ.LOWERSEC.GPIA
|
|-
|EdSecLwrParityGenderTeachers
|Ratio of female to male teachers in lower secondary who are trained
|Pupil-trained teacher ratio in lower secondary education (headcount basis)
|PTRHC.2.TRAINED
|
|-
|EdSecLwrParityRurUrbMath
|Ratio of rural to urban students' mathematics achievement by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted location parity index (LPIA)
|MATH.LOWERSEC.LPIA
|
|-
|EdSecLwrParityRurUrbRead
|Ratio of rural to urban students' reading achievement by the end of lower secondary
|Proportion of students at the end of lower secondary education achieving at least a minimum proficiency level in reading, adjusted location parity index (LPIA)
|READ.LOWERSEC.LPIA
|
|-
|EdSecLwrParitySocioeconMath
|Ratio of students from low to high socio-economic groups' achievement in mathematics by the end of lower secondary
|Proportion of students at the end of lower secondary achieving at least a minimum proficiency level in mathematics, adjusted wealth parity index (WPIA)
|MATH.LOWERSEC.WPIA
|
|-
|EdSecLwrParitySocioeconRead
|Ratio of students from low to high socio-economic groups' achievement in reading by the end of lower secondary
|Proportion of students at the end of lower secondary education achieving at least a minimum proficiency level in reading, adjusted wealth parity index (WPIA)
|READ.LOWERSEC.WPIA
|
|-
|EdSecUpperEnrollGrossParity
|Gender parity index for gross enrolment ratio. Upper secondary. All programmes
|Gross enrolment ratio, upper secondary, adjusted gender parity index (GPIA)
|GER.3.GPIA
|
|-
|EdSecUpperEnrollGrossParityNew
|Gender parity index for gross enrolment ratio. Upper secondary. All programmes
|Gross enrolment ratio, upper secondary, adjusted gender parity index (GPIA)
|GER.3.GPIA
|
|-
|EdSecUpperEnrollHeadCountMale
|Education, upper secondary, headcount enrollment number , male
|Enrolment in upper secondary education, male (number)
|40041
|*0.000001
|-
|EdSecUpperEnrollHeadcountFemale
|Education, upper secondary, headcount enrollment number, female
|Enrolment in upper secondary education, female (number)
|20071
|*0.000001
|-
|EdSecUpperEnrollHeadcountTotal
|Education, Upper Secondary, Total Enrollment (male plus female)
|Enrolment in upper secondary education, both sexes (number)
|20070
|*0.000001
|-
|EdSecUpperNetEnrollFemale%
|Net Upper Secondary Enrollment, Female
|Total net enrolment rate, upper secondary, female (%)
|NERT.3.F.CP
|
|-
|EdSecUpperNetEnrollMale%
|Net Upper Secondary Enrollment Rate, Male
|Total net enrolment rate, upper secondary, male (%)
|NERT.3.M.CP
|
|-
|EdSecUpperNetEnrollTot%
|Net Upper Secondary Enrollment Rate, Total
|Total net enrolment rate, upper secondary, both sexes (%)
|NERT.3.CP
|
|-
|EdSecUpperParityGenderTeachers
|Ratio of female to male teachers in upper secondary education who are trained
|Pupil-trained teacher ratio in upper secondary education (headcount basis)
|PTRHC.3.TRAINED
|
|-
|EdSecUpprCompletionFemale
|Education, upper secondary, completion rate from household survey data, female
|Completion rate, upper secondary education, female (%)
|CR.3.F
|
|-
|EdSecUpprCompletionMale
|Education, upper secondary, completion rate from household survey data, male
|Completion rate, upper secondary education, male (%)
|CR.3.M
|
|-
|EdSecUpprCompletionTotal
|Education, upper secondary, completion rate from household survey data, total
|Completion rate, upper secondary education, both sexes (%)
|CR.3
|
|-
|EdSecVoc%Tot
|Education Secondary, technical or vocational enrollment as percentage of all programs, total
|Share of all students in secondary education enrolled in vocational programmes (%)
|GTVP.2T3.V
|
|-
|EdTerEnrISCED6HdctFem
|Education, 6 Tertiary, Enrollment headcount, Female
|Enrolment in tertiary education, ISCED 6 programmes, female (number)
|42635
|*0.000001
|-
|EdTerEnrISCED6HdctMale
|Education, 6 Tertiary, Enrollment headcount, Male
|Enrolment in tertiary education, ISCED 6 programmes, male (number)
|42615
|*0.000001
|-
|EdTerEnrISCED6HdctTot
|Education, 6 Tertiary, Enrollment headcount, Total
|Enrolment in tertiary education, ISCED 6 programmes, both sexes (number)
|42654
|*0.000001
|-
|EdTerEnrollHeadcountFem
|Education, Tertiary, Enrollment Headcount, Female
|Enrolment in tertiary education, all programmes, female (number)
|25057
|*0.000001
|-
|EdTerEnrollHeadcountMale
|Education, Tertiary, Enrollment Headcount, Male
|Enrolment in tertiary education, all programmes, male (number)
|42620
|*0.000001
|-
|EdTerEnrollHeadcountTotal
|Education, Tertiary, Enrollment Headcount, Total
|Enrolment in tertiary education, all programmes, both sexes (number)
|25053
|*0.000001
|-
|EdTerFemaleMaleRatio
|Ratio of females to males in tertiary education
|Gross enrolment ratio for tertiary education, adjusted gender parity index (GPIA)
|GER.5T8.GPIA
|
|-
|EdTerGrads%Ag
|Education, Tertiary, Agriculture Graduates as % of total graduates
|Percentage of graduates from tertiary education graduating from Agriculture, Forestry, Fisheries and Veterinary programmes, both sexes (%)
|FOSGP.5T8.F800
|
|-
|EdTerGrads%Engg
|Education, Tertiary, Engineering, Manufacturing and Construction as % of total graduates
|Percentage of graduates from tertiary education graduating from Engineering, Manufacturing and Construction programmes, both sexes (%)
|FOSGP.5T8.F700
|
|-
|EdTerGrads%Health
|Education, Tertiary, Health and Welfare Graduates as % of total graduates
|Percentage of graduates from tertiary education graduating from Health and Welfare programmes, both sexes (%)
|FOSGP.5T8.F900
|
|-
|EdTerGrads%Sci
|Education, Tertiary, Science Graduates as % of total graduates
|Percentage of graduates from Science, Technology, Engineering and Mathematics programmes in tertiary education, both sexes (%) + Percentage of graduates from tertiary education graduating from Information and Communication Technologies programmes, both sexes (%)
|FOSGP.5T8.F500 + FOSGP.5T8.F600
|
|-
|PupilTeacherRatioUISPrimary
|Pupil teacher ratio in primary education
|Enrolment in primary education, both sexes (number)/Teachers in primary education, both sexes (number)
|20062/20162
|
|-
|PupilTeacherRatioUISSecondary
|Pupil teacher ratio in secondary education
|Enrolment in secondary education, both sexes (number)/Teachers in secondary education, both sexes (number)
|20082/20182
|
|-
|PupilTrainedTeacherRatioUISPrimary
|Pupil to trained teacher ratio in primary education
|Pupil-trained teacher ratio in primary education (headcount basis)
|PTRHC.1.TRAINED
|
|-
|PupilTrainedTeacherRatioUISSecondary
|Pupil toTrained teacher ratio in secondary education
|Pupil-trained teacher ratio in secondary education (headcount basis)
|PTRHC.2T3.TRAINED
|
|}
{| class="wikitable"
|Variable
|UsedInPreprocessor
|UsedInPreprocessorFileName
|-
|EdPriCompletionTotal%
|1
|EDUCATION
|-
|EdPriCompletionFemale%
|1
|EDUCATION
|-
|EdPriCompletionMale%
|1
|EDUCATION
|-
|EdPriCompletionTotal
|0
|
|-
|EdPriCompletionTotal%BL
|0
|
|-
|EdPriCompletionFemale
|0
|
|-
|EdPriCompletionFemale%BL
|0
|
|-
|EdPriCompletionParity
|0
|
|-
|EdPriCompletionMale
|0
|
|-
|EdPriCompletionMale%BL
|0
|
|-
|EdSecLowrCompletionTotal
|0
|
|-
|EdSecLowrCompletionFemale
|0
|
|-
|EdSecLowrCompletionMale
|0
|
|-
|EdSecUpprCompletionTotal
|0
|
|-
|EdSecUpprCompletionFemale
|0
|
|-
|EdSecUpprCompletionMale
|0
|
|-
|EdPriDuration
|1
|EDUCATION
|-
|EdSecLowerDuration
|1
|EDUCATION
|-
|EdSecUpperDuration
|1
|EDUCATION
|-
|EdPrePriDuration
|0
|
|-
|EdPostSecDuration
|0
|
|-
|EdSecDuration
|0
|
|-
|EdExpISCED1-4Cap%
|0
|
|-
|EdExpISCED1-4TotalCur%
|0
|
|-
|EdExpISCED1-4NonSalCur%
|0
|
|-
|EdExpISCED1-4Sal%
|0
|
|-
|EdExpTerCap%
|0
|
|-
|EdExpTertTotalCur%
|0
|
|-
|EdExpTertNonSalCur%
|0
|
|-
|EdExpTertSal%
|0
|
|-
|EdSecLowerAdultGrads25Total%
|0
|
|-
|EdSecLowerAdultGrads25Female%
|0
|
|-
|EdSecLowerAdultGrads25Male%
|0
|
|-
|EdPriEnrollHeadCountTtl
|0
|
|-
|EdPriEnrollHeadcountFem
|0
|
|-
|EdSecLowerEnrollHeadcountTotal
|0
|
|-
|EdSecLowerEnrollHeadcountFemale
|0
|
|-
|EdSecUpperEnrollHeadcountTotal
|0
|
|-
|EdSecUpperEnrollHeadcountFemale
|0
|
|-
|EdSecEnrNoTot
|0
|
|-
|EdSecEnrNoFem
|0
|
|-
|EdTerEnrollHeadcountTotal
|0
|
|-
|EdTerEnrollHeadcountFem
|0
|
|-
|EdPriEnrollHeadcountMal
|0
|
|-
|EdSecLowerEnrollHeadcountMale
|0
|
|-
|EdSecUpperEnrollHeadCountMale
|0
|
|-
|EdSecEnrNoMal
|0
|
|-
|EdTerEnrISCED6HdctMale
|0
|
|-
|EdTerEnrollHeadcountMale
|0
|
|-
|EdTerEnrISCED6HdctFem
|0
|
|-
|EdTerEnrISCED6HdctTot
|0
|
|-
|GovtEdPub%GDP
|1
|ECONOMY
|-
|EdExpPrePri%EducTot
|0
|
|-
|EdExpPri%EducTot
|0
|
|-
|EdExpSecLowr%EducTot
|0
|
|-
|EdExpSec%EducTot
|0
|
|-
|EdExpSecUppr%EducTot
|0
|
|-
|EdExpTer%EducTot
|0
|
|-
|EdPriEnrollGrossTotalPcnt
|1
|EDUCATION
|-
|EdPriEnrollGrossFemalePcnt
|1
|EDUCATION
|-
|EdPriEnrollGrossMalePcnt
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Total
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Female
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Male
|1
|EDUCATION
|-
|EdSecEnrollGross%Total
|1
|EDUCATION
|-
|EdSecEnrollGross%Female
|1
|EDUCATION
|-
|EdSecEnrollGross%Male
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Total
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Female
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Male
|1
|EDUCATION
|-
|EdTerEnrollGross%Total
|1
|EDUCATION
|-
|EdTerEnrollGross%Female
|1
|EDUCATION
|-
|EdTerEnrollGross%Male
|1
|EDUCATION
|-
|EdBasicEnrollGross%Total
|0
|
|-
|EdBasicEnrollGross%Female
|0
|
|-
|EdBasicEnrollGross%Male
|0
|
|-
|EdSecLowerEnrollGrossParity
|0
|
|-
|EdSecEnrollGross%Parity
|0
|
|-
|EdSecUpperEnrollGrossParity
|0
|
|-
|EdSecUpperEnrollGrossParityNew
|0
|
|-
|EdTerFemaleMaleRatio
|0
|
|-
|EdTerGradRate1stDegreeTotal%
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeFemale%
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeMale%
|1
|EDUCATION
|-
|EdPriAIRTotal%
|1
|EDUCATION
|-
|EdPriAIRFemale%
|1
|EDUCATION
|-
|EdPriAIRMale%
|1
|EDUCATION
|-
|EdPriAIRParity
|0
|
|-
|EdPri2and3ParityGenderMath
|0
|
|-
|EdPri2and3ParityRurUrbMath
|0
|
|-
|EdPri2and3ParitySocioeconMath
|0
|
|-
|EdSecLwrParityGenderMath
|0
|
|-
|EdSecLwrParityRurUrbMath
|0
|
|-
|EdSecLwrParitySocioeconMath
|0
|
|-
|EdPriParityGenderMath
|0
|
|-
|EdPriParityRurUrbMath
|0
|
|-
|EdPriParitySocioeconMath
|0
|
|-
|EdPriEntranceAge
|1
|EDUCATION
|-
|EdPriOutofSchoolTotal%
|0
|
|-
|EdPriOutofSchoolFemale%
|0
|
|-
|EdPriOutofSchoolMale%
|0
|
|-
|EdEnrollPrivate%Primary
|0
|
|-
|EdEnrollPrivate%Lower2ndaryGeneral
|0
|
|-
|EdEnrollPrivateAll2ndaryCombined
|0
|
|-
|EdEnrollPrivate%Upper2ndaryGeneral
|0
|
|-
|EdEnrollPrivateUpper2ndaryGeneral
|0
|
|-
|EdTerGrads%SciEngg
|1
|EDUCATION
|-
|EdTerGrads%Sci
|0
|
|-
|EdTerGrads%Engg
|0
|
|-
|EdTerGrads%Ag
|0
|
|-
|EdTerGrads%Health
|0
|
|-
|EDPriPTR
|1
|EDUCATION
|-
|PupilTeacherRatioUISPrimary
|0
|
|-
|EdSecLowrPTR
|0
|
|-
|PupilTeacherRatioUISSecondary
|0
|
|-
|EdPrePriParityGenderTeachers
|0
|
|-
|EdPriParityGenderTeachers
|0
|
|-
|PupilTrainedTeacherRatioUISPrimary
|0
|
|-
|EdSecLwrParityGenderTeachers
|0
|
|-
|PupilTrainedTeacherRatioUISSecondary
|0
|
|-
|EdSecUpperParityGenderTeachers
|0
|
|-
|R&DGovt%GDP
|1
|ECONOMY
|-
|EdPri2and3ParityGenderRead
|0
|
|-
|EdPri2and3ParityRurUrbRead
|0
|
|-
|EdPri2and3ParitySocioeconRead
|0
|
|-
|EdSecLwrParityGenderRead
|0
|
|-
|EdSecLwrParityRurUrbRead
|0
|
|-
|EdSecLwrParitySocioeconRead
|0
|
|-
|EdPriParityGenderRead
|0
|
|-
|EdPriParityRurUrbRead
|0
|
|-
|EdPriParitySocioeconRead
|0
|
|-
|EdPriRepeaterTotal%
|0
|
|-
|EdPriRepeaterFemale%
|0
|
|-
|EdPriRepeater1stYearTotal%
|0
|
|-
|EdPriRepeater1stYearFemale%
|0
|
|-
|EdPriRepeater1stYearMale%
|0
|
|-
|EdPriRepeaterMale%
|0
|
|-
|EdExpectedYearsofSchooling
|0
|
|-
|EdExpectedYearsofSchoolingFemale
|0
|
|-
|EdExpectedYearsofSchoolingMale
|0
|
|-
|EdSecLowerVoc%AllTotal
|1
|EDUCATION
|-
|EdSecUpperVoc%AllTotal
|1
|EDUCATION
|-
|EdSecVoc%Tot
|0
|
|-
|EdPriSurvivalTotal%
|1
|EDUCATION
|-
|EdPriSurvivalFemale%
|1
|EDUCATION
|-
|EdPriSurvivalMale%
|1
|EDUCATION
|-
|EdPriSurvivalParity
|0
|
|-
|EdPriEnrollNetTotalPcnt
|1
|EDUCATION
|-
|EdPriEnrollNetFemalePcnt
|1
|EDUCATION
|-
|EdPriEnrollNetMalePcnt
|1
|EDUCATION
|-
|EdPriEnrollNetParity
|0
|
|-
|EdSecLowerNetEnrollTot%
|0
|
|-
|EdSecLowerNetEnrollFemale%
|0
|
|-
|EdSecLowerNetEnrollMale%
|0
|
|-
|EdSecUpperNetEnrollTot%
|0
|
|-
|EdSecUpperNetEnrollFemale%
|0
|
|-
|EdSecUpperNetEnrollMale%
|0
|
|}

= Data Pulling Instructions =

# Go to https://databrowser.uis.unesco.org/resources/bulk
# Download Education SDG, Education Other Policy Relevant Indicators, and R&D SDG
## Education SDG - File name: SDG
## Education Other Policy Relevant Indicators - File name: OPRI
## R&D SDG - File name: SCN-SDG[[File:Image download uis.png|none|thumb|563x563px]]
## Upzipp the downloaded files.
### Use {File name}_COUNTRY.csv to prepare country concordance table.
### Use {File name}_NATIONAL_DATA.csv to extract series.
### Use {File name}_LABEL.csv to check the definition of the "INDICATOR_ID" listed below.
##You can use the code in this GitHub to help pull the data: https://github.com/n1shamin/UIS-UNESCO

= Coding =
Notes:

2. Series need to be calculated: PupilTeacherRatioUISPrimary, PupilTeacherRatioUISSecondary, EDPriPTR, EdSecLowrPTR, EdExpPrePri%EducTot, EdExpPri%EducTot, EdExpSecLowr%EducTot, EdExpSec%EducTot, EdExpSecUppr%EducTot, EdExpTer%EducTot, EdTerGrads%Sci, GovtEdPub%GDP, EdExpISCED1-4Cap%, EdExpISCED1-4TotalCur%, EdExpISCED1-4NonSalCur%, EdExpISCED1-4Sal%

3. All the series in "Enrollment Headcount" need to *0.000001 to convert to "Millions".

4. Item Understanding in INDICATOR_ID:
{| class="wikitable"
|Item
|Meaning
|-
|02
|pre-primary
|-
|1
|primary
|-
|2
|lower secondary
|-
|3
|upper secondary
|-
|2T3
|secondary
|-
|4
|post-secondary non-tertiary
|-
|5T8
|tertiary
|-
|6T7
|ISCED 6 and 7
|-
|1T8
|primary to tertiary
|-
|F
|female
|-
|M
|male
|-
|GPIA
|adjusted gender parity index
|-
|LPIA
|adjusted location parity index
|-
|WPIA
|adjusted wealth parity index
|-
|G1
|Grade 1
|-
|G2T3
|Grade 2 or 3
|-
|GLAST
|last grade
|-
|F500
|Natural Sciences, Mathematics and Statistics
|-
|F600
|Information and Communication Technologies
|-
|F700
|Engineering, Manufacturing and Construction
|-
|F800
|Agriculture, Forestry, Fisheries and Veterinary
|-
|F900
|Health and Welfare
|}
{| class="wikitable"
|Variable
|Type
|File
|INDICATOR_ID
|UsedInPreprocessor
|UsedInPreprocessorFileName
|-
|EdPriCompletionTotal%
|Completion rate
|SDG
|CR.1
|1
|EDUCATION
|-
|EdPriCompletionFemale%
|Completion rate
|SDG
|CR.1.F
|1
|EDUCATION
|-
|EdPriCompletionMale%
|Completion rate
|SDG
|CR.1.M
|1
|EDUCATION
|-
|EdPriCompletionTotal
|Completion rate
|SDG
|CR.1
|0
|
|-
|EdPriCompletionTotal%BL
|Completion rate
|SDG
|CR.1
|0
|
|-
|EdPriCompletionFemale
|Completion rate
|SDG
|CR.1.F
|0
|
|-
|EdPriCompletionFemale%BL
|Completion rate
|SDG
|CR.1.F
|0
|
|-
|EdPriCompletionParity
|Completion rate
|SDG
|CR.1.GPIA
|0
|
|-
|EdPriCompletionMale
|Completion rate
|SDG
|CR.1.M
|0
|
|-
|EdPriCompletionMale%BL
|Completion rate
|SDG
|CR.1.M
|0
|
|-
|EdSecLowrCompletionTotal
|Completion rate
|SDG
|CR.2
|0
|
|-
|EdSecLowrCompletionFemale
|Completion rate
|SDG
|CR.2.F
|0
|
|-
|EdSecLowrCompletionMale
|Completion rate
|SDG
|CR.2.M
|0
|
|-
|EdSecUpprCompletionTotal
|Completion rate
|SDG
|CR.3
|0
|
|-
|EdSecUpprCompletionFemale
|Completion rate
|SDG
|CR.3.F
|0
|
|-
|EdSecUpprCompletionMale
|Completion rate
|SDG
|CR.3.M
|0
|
|-
|EdPriDuration
|Duration
|OPRI
|299932
|1
|EDUCATION
|-
|EdSecLowerDuration
|Duration
|OPRI
|999976
|1
|EDUCATION
|-
|EdSecUpperDuration
|Duration
|OPRI
|999978
|1
|EDUCATION
|-
|EdPrePriDuration
|Duration
|OPRI
|299929
|0
|
|-
|EdPostSecDuration
|Duration
|OPRI
|999988
|0
|
|-
|EdSecDuration
|Duration
|OPRI
|THDUR.2T3
|0
|
|-
|EdExpISCED1-4Cap%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNCAP + XSPENDP.2.FDPUB.FNCAP + XSPENDP.3.FDPUB.FNCAP + XSPENDP.4.FDPUB.FNCAP
|0
|
|-
|EdExpISCED1-4TotalCur%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNCUR + XSPENDP.2.FDPUB.FNCUR + XSPENDP.3.FDPUB.FNCUR + XSPENDP.4.FDPUB.FNCUR
|0
|
|-
|EdExpISCED1-4NonSalCur%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNNONS + XSPENDP.2.FDPUB.FNNONS + XSPENDP.3.FDPUB.FNNONS + XSPENDP.4.FDPUB.FNNONS
|0
|
|-
|EdExpISCED1-4Sal%
|Education Expenditure
|OPRI
|XSPENDP.1.FDPUB.FNS + XSPENDP.2.FDPUB.FNS + XSPENDP.3.FDPUB.FNS + XSPENDP.4.FDPUB.FNS
|0
|
|-
|EdExpTerCap%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNCAP
|0
|
|-
|EdExpTertTotalCur%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNCUR
|0
|
|-
|EdExpTertNonSalCur%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNNONS
|0
|
|-
|EdExpTertSal%
|Education Expenditure
|OPRI
|XSPENDP.5T8.FDPUB.FNS
|0
|
|-
|EdSecLowerAdultGrads25Total%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99
|0
|
|-
|EdSecLowerAdultGrads25Female%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99.F
|0
|
|-
|EdSecLowerAdultGrads25Male%
|Educational attainment rate
|SDG
|EA.2T8.AG25T99.M
|0
|
|-
|EdPriEnrollHeadCountTtl
|Enrollment Headcount
|OPRI
|20062
|0
|
|-
|EdPriEnrollHeadcountFem
|Enrollment Headcount
|OPRI
|20063
|0
|
|-
|EdSecLowerEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|20064
|0
|
|-
|EdSecLowerEnrollHeadcountFemale
|Enrollment Headcount
|OPRI
|20065
|0
|
|-
|EdSecUpperEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|20070
|0
|
|-
|EdSecUpperEnrollHeadcountFemale
|Enrollment Headcount
|OPRI
|20071
|0
|
|-
|EdSecEnrNoTot
|Enrollment Headcount
|OPRI
|20082
|0
|
|-
|EdSecEnrNoFem
|Enrollment Headcount
|OPRI
|20083
|0
|
|-
|EdTerEnrollHeadcountTotal
|Enrollment Headcount
|OPRI
|25053
|0
|
|-
|EdTerEnrollHeadcountFem
|Enrollment Headcount
|OPRI
|25057
|0
|
|-
|EdPriEnrollHeadcountMal
|Enrollment Headcount
|OPRI
|40035
|0
|
|-
|EdSecLowerEnrollHeadcountMale
|Enrollment Headcount
|OPRI
|40038
|0
|
|-
|EdSecUpperEnrollHeadCountMale
|Enrollment Headcount
|OPRI
|40041
|0
|
|-
|EdSecEnrNoMal
|Enrollment Headcount
|OPRI
|40044
|0
|
|-
|EdTerEnrISCED6HdctMale
|Enrollment Headcount
|OPRI
|42615
|0
|
|-
|EdTerEnrollHeadcountMale
|Enrollment Headcount
|OPRI
|42620
|0
|
|-
|EdTerEnrISCED6HdctFem
|Enrollment Headcount
|OPRI
|42635
|0
|
|-
|EdTerEnrISCED6HdctTot
|Enrollment Headcount
|OPRI
|42654
|0
|
|-
|GovtEdPub%GDP
|Government Expenditure
|OPRI
|XGDP.02.FSGOV + XGDP.1.FSGOV + XGDP.2.FSGOV + XGDP.3.FSGOV + XGDP.4.FSGOV + XGDP.5T8.FSGOV
|1
|ECONOMY
|-
|EdExpPrePri%EducTot
|Government Expenditure
|OPRI
|X.USCONST.02.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpPri%EducTot
|Government Expenditure
|OPRI
|X.USCONST.1.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSecLowr%EducTot
|Government Expenditure
|OPRI
|X.USCONST.2.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSec%EducTot
|Government Expenditure
|OPRI
|X.USCONST.2T3.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpSecUppr%EducTot
|Government Expenditure
|OPRI
|X.USCONST.3.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdExpTer%EducTot
|Government Expenditure
|OPRI
|X.USCONST.5T8.FSGOV/X.USCONST.FSGOV
|0
|
|-
|EdPriEnrollGrossTotalPcnt
|Gross enrolment ratio
|OPRI
|GER.1
|1
|EDUCATION
|-
|EdPriEnrollGrossFemalePcnt
|Gross enrolment ratio
|OPRI
|GER.1.F
|1
|EDUCATION
|-
|EdPriEnrollGrossMalePcnt
|Gross enrolment ratio
|OPRI
|GER.1.M
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.2
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.2.F
|1
|EDUCATION
|-
|EdSecLowerEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.2.M
|1
|EDUCATION
|-
|EdSecEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.2T3
|1
|EDUCATION
|-
|EdSecEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.2T3.F
|1
|EDUCATION
|-
|EdSecEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.2T3.M
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.3
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.3.F
|1
|EDUCATION
|-
|EdSecUpperEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.3.M
|1
|EDUCATION
|-
|EdTerEnrollGross%Total
|Gross enrolment ratio
|SDG
|GER.5T8
|1
|EDUCATION
|-
|EdTerEnrollGross%Female
|Gross enrolment ratio
|SDG
|GER.5T8.F
|1
|EDUCATION
|-
|EdTerEnrollGross%Male
|Gross enrolment ratio
|SDG
|GER.5T8.M
|1
|EDUCATION
|-
|EdBasicEnrollGross%Total
|Gross enrolment ratio
|OPRI
|GER.1T2
|0
|
|-
|EdBasicEnrollGross%Female
|Gross enrolment ratio
|OPRI
|GER.1T2.F
|0
|
|-
|EdBasicEnrollGross%Male
|Gross enrolment ratio
|OPRI
|GER.1T2.M
|0
|
|-
|EdSecLowerEnrollGrossParity
|Gross enrolment ratio
|OPRI
|GER.2.GPIA
|0
|
|-
|EdSecEnrollGross%Parity
|Gross enrolment ratio
|OPRI
|GER.2T3.GPIA
|0
|
|-
|EdSecUpperEnrollGrossParity
|Gross enrolment ratio
|OPRI
|GER.3.GPIA
|0
|
|-
|EdSecUpperEnrollGrossParityNew
|Gross enrolment ratio
|OPRI
|GER.3.GPIA
|0
|
|-
|EdTerFemaleMaleRatio
|Gross enrolment ratio
|SDG
|GER.5T8.GPIA
|0
|
|-
|EdTerGradRate1stDegreeTotal%
|Gross graduation ratio
|OPRI
|GGR.6T7
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeFemale%
|Gross graduation ratio
|OPRI
|GGR.6T7.F
|1
|EDUCATION
|-
|EdTerGradRate1stDegreeMale%
|Gross graduation ratio
|OPRI
|GGR.6T7.M
|1
|EDUCATION
|-
|EdPriAIRTotal%
|Gross intake ratio
|SDG
|AIR.1.GLAST
|1
|EDUCATION
|-
|EdPriAIRFemale%
|Gross intake ratio
|SDG
|AIR.1.GLAST.F
|1
|EDUCATION
|-
|EdPriAIRMale%
|Gross intake ratio
|SDG
|AIR.1.GLAST.M
|1
|EDUCATION
|-
|EdPriAIRParity
|Gross intake ratio
|SDG
|AIR.1.GLAST.GPIA
|0
|
|-
|EdPri2and3ParityGenderMath
|MATH
|SDG
|MATH.G2T3.GPIA
|0
|
|-
|EdPri2and3ParityRurUrbMath
|MATH
|SDG
|MATH.G2T3.LPIA
|0
|
|-
|EdPri2and3ParitySocioeconMath
|MATH
|SDG
|MATH.G2T3.WPIA
|0
|
|-
|EdSecLwrParityGenderMath
|MATH
|SDG
|MATH.LOWERSEC.GPIA
|0
|
|-
|EdSecLwrParityRurUrbMath
|MATH
|SDG
|MATH.LOWERSEC.LPIA
|0
|
|-
|EdSecLwrParitySocioeconMath
|MATH
|SDG
|MATH.LOWERSEC.WPIA
|0
|
|-
|EdPriParityGenderMath
|MATH
|SDG
|MATH.PRIMARY.GPIA
|0
|
|-
|EdPriParityRurUrbMath
|MATH
|SDG
|MATH.PRIMARY.LPIA
|0
|
|-
|EdPriParitySocioeconMath
|MATH
|SDG
|MATH.PRIMARY.WPIA
|0
|
|-
|EdPriEntranceAge
|Official entrance age
|OPRI
|299905
|1
|EDUCATION
|-
|EdPriOutofSchoolTotal%
|Out-of-school rate
|SDG
|ROFST.1.CP
|0
|
|-
|EdPriOutofSchoolFemale%
|Out-of-school rate
|SDG
|ROFST.1.F.CP
|0
|
|-
|EdPriOutofSchoolMale%
|Out-of-school rate
|SDG
|ROFST.1.M.CP
|0
|
|-
|EdEnrollPrivate%Primary
|Percentage of enrolment in private
|OPRI
|PRP.1
|0
|
|-
|EdEnrollPrivate%Lower2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.2
|0
|
|-
|EdEnrollPrivateAll2ndaryCombined
|Percentage of enrolment in private
|OPRI
|PRP.2T3
|0
|
|-
|EdEnrollPrivate%Upper2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.3
|0
|
|-
|EdEnrollPrivateUpper2ndaryGeneral
|Percentage of enrolment in private
|OPRI
|PRP.3
|0
|
|-
|EdTerGrads%SciEngg
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F500
|1
|EDUCATION
|-
|EdTerGrads%Sci
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F500 + FOSGP.5T8.600
|0
|
|-
|EdTerGrads%Engg
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F700
|0
|
|-
|EdTerGrads%Ag
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F800
|0
|
|-
|EdTerGrads%Health
|Percentage of graduates from tertiary
|OPRI
|FOSGP.5T8.F900
|0
|
|-
|EDPriPTR
|PTR
|OPRI
|20062/20162
|1
|EDUCATION
|-
|PupilTeacherRatioUISPrimary
|PTR
|OPRI
|20062/20162
|0
|
|-
|EdSecLowrPTR
|PTR
|OPRI
|20064/20164
|0
|
|-
|PupilTeacherRatioUISSecondary
|PTR
|OPRI
|20082/20182
|0
|
|-
|EdPrePriParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.02.TRAINED
|0
|
|-
|EdPriParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.1.TRAINED
|0
|
|-
|PupilTrainedTeacherRatioUISPrimary
|Pupil-trained teacher ratio
|SDG
|PTRHC.1.TRAINED
|0
|
|-
|EdSecLwrParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.2.TRAINED
|0
|
|-
|PupilTrainedTeacherRatioUISSecondary
|Pupil-trained teacher ratio
|SDG
|PTRHC.2T3.TRAINED
|0
|
|-
|EdSecUpperParityGenderTeachers
|Pupil-trained teacher ratio
|SDG
|PTRHC.3.TRAINED
|0
|
|-
|R&DGovt%GDP
|R&D%GDP
|SCN-SDG
|EXPGDP.TOT
|1
|ECONOMY
|-
|EdPri2and3ParityGenderRead
|READ
|SDG
|READ.G2T3.GPIA
|0
|
|-
|EdPri2and3ParityRurUrbRead
|READ
|SDG
|READ.G2T3.LPIA
|0
|
|-
|EdPri2and3ParitySocioeconRead
|READ
|SDG
|READ.G2T3.WPIA
|0
|
|-
|EdSecLwrParityGenderRead
|READ
|SDG
|READ.LOWERSEC.GPIA
|0
|
|-
|EdSecLwrParityRurUrbRead
|READ
|SDG
|READ.LOWERSEC.LPIA
|0
|
|-
|EdSecLwrParitySocioeconRead
|READ
|SDG
|READ.LOWERSEC.WPIA
|0
|
|-
|EdPriParityGenderRead
|READ
|SDG
|READ.PRIMARY.GPIA
|0
|
|-
|EdPriParityRurUrbRead
|READ
|SDG
|READ.PRIMARY.LPIA
|0
|
|-
|EdPriParitySocioeconRead
|READ
|SDG
|READ.PRIMARY.WPIA
|0
|
|-
|EdPriRepeaterTotal%
|Repetition rate
|OPRI
|REPR.1.CP
|0
|
|-
|EdPriRepeaterFemale%
|Repetition rate
|OPRI
|REPR.1.F.CP
|0
|
|-
|EdPriRepeater1stYearTotal%
|Repetition rate
|OPRI
|REPR.1.G1.CP
|0
|
|-
|EdPriRepeater1stYearFemale%
|Repetition rate
|OPRI
|REPR.1.G1.F.CP
|0
|
|-
|EdPriRepeater1stYearMale%
|Repetition rate
|OPRI
|REPR.1.G1.M.CP
|0
|
|-
|EdPriRepeaterMale%
|Repetition rate
|OPRI
|REPR.1.M.CP
|0
|
|-
|EdExpectedYearsofSchooling
|School life expectancy
|OPRI
|SLE.1T8
|0
|
|-
|EdExpectedYearsofSchoolingFemale
|School life expectancy
|OPRI
|SLE.1T8.F
|0
|
|-
|EdExpectedYearsofSchoolingMale
|School life expectancy
|OPRI
|SLE.1T8.M
|0
|
|-
|EdSecLowerVoc%AllTotal
|Share of all students in vocational programmes
|OPRI
|GTVP.2.V
|1
|EDUCATION
|-
|EdSecUpperVoc%AllTotal
|Share of all students in vocational programmes
|OPRI
|GTVP.3.V
|1
|EDUCATION
|-
|EdSecVoc%Tot
|Share of all students in vocational programmes
|OPRI
|GTVP.2T3.V
|0
|
|-
|EdPriSurvivalTotal%
|Survival rate
|OPRI
|SR.1.GLAST.CP
|1
|EDUCATION
|-
|EdPriSurvivalFemale%
|Survival rate
|OPRI
|SR.1.GLAST.F.CP
|1
|EDUCATION
|-
|EdPriSurvivalMale%
|Survival rate
|OPRI
|SR.1.GLAST.M.CP
|1
|EDUCATION
|-
|EdPriSurvivalParity
|Survival rate
|OPRI
|SR.1.GLAST.GPIA
|0
|
|-
|EdPriEnrollNetTotalPcnt
|Total net enrolment rate
|OPRI
|NERT.1.CP
|1
|EDUCATION
|-
|EdPriEnrollNetFemalePcnt
|Total net enrolment rate
|OPRI
|NERT.1.F.CP
|1
|EDUCATION
|-
|EdPriEnrollNetMalePcnt
|Total net enrolment rate
|OPRI
|NERT.1.M.CP
|1
|EDUCATION
|-
|EdPriEnrollNetParity
|Total net enrolment rate
|OPRI
|NERT.1.GPIA
|0
|
|-
|EdSecLowerNetEnrollTot%
|Total net enrolment rate
|OPRI
|NERT.2.CP
|0
|
|-
|EdSecLowerNetEnrollFemale%
|Total net enrolment rate
|OPRI
|NERT.2.F.CP
|0
|
|-
|EdSecLowerNetEnrollMale%
|Total net enrolment rate
|OPRI
|NERT.2.M.CP
|0
|
|-
|EdSecUpperNetEnrollTot%
|Total net enrolment rate
|OPRI
|NERT.3.CP
|0
|
|-
|EdSecUpperNetEnrollFemale%
|Total net enrolment rate
|OPRI
|NERT.3.F.CP
|0
|
|-
|EdSecUpperNetEnrollMale%
|Total net enrolment rate
|OPRI
|NERT.3.M.CP
|0
|
|}

== Pulling Data on Enrollment in Vocational Programmes: ==
The pre-processor series in IFs relating to enrollment in vocational programmes are:

#EdSecUpperVoc%AllMale
#EdSecUpperVoc%AllFemale
#EdSecUpperVoc%AllTotal
#EdSecLowerVoc%AllMale
#EdSecLowerVoc%Allfemale
#EdSecLowerVoc%AllTotal

Data for these series was obtained from the UIS Education Database in the following drop down menu sequence: Education>Participation>Distribution of Enrollment>Distribution of Enrollment by Programme Orientation.

Because these particular series contain confusing wording, the full names in UIS of each fo the six series are provided below.

#'''Percentage of male students in lower secondary education enrolled in vocational programmes, male (%)'''
#'''Percentage of female students in lower secondary education enrolled in vocational programmes, female (%)'''
#'''Percentage of students in lower secondary education enrolled in vocational programmes, both sexes (%)'''
#'''Percentage of male students in upper secondary education enrolled in vocational programmes, male (%)'''
#'''Percentage of female students in upper secondary education enrolled in vocational programmes, female (%)'''
#'''Percentage of students in upper secondary education enrolled in vocational programmes, both sexes (%)'''

== Pulling Data on Educational Expenditure: ==
The pre-processor series in IFs relating to educational expenditure are:

#EdExpPri%GDPPC
#EdExpSec%GDPPC
#EdExpSecLowr%GDPPC
#EdExpSecUppr%GDPPC
#EdExpTer%GDPP

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Financial Resources>Government Expenditure per Student>Government Expenditure per Student as Percentage of GDP per capita. 

Once here, the following 5 sheets were used: '''Government expenditure per (primary/secondary/lower seconday/upper seconday/tertiary) student as percentage of GDP per capita. '''

== Pulling Data on Graduation Rates: ==
The pre-processor series in IFs relating to graduation rates are:

#EdTerGradRate1stDegreeFemale% 
#EdterGradRate1stDegreeMale%
#EdTerGradRate1stDegreeTotal%
#EdTerGrad%SciEngg
#EdPriCompletionFemale%
#EdPriCompletionMale%
#EdPriCompletionTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Completion and Graduation Ratios>Gross Graduation Ratio.

Once here, the following 4 sheets were used: '''Gross Graduation Ratio from First Degree Programmes (ISCED 6 & 7) in Tertiary Education, (Female (%)/Male (%)/Both Sexes (%)).'''

For 5-7 above, the following 3sheets were used:'''(Gross Graduation Ratio from Primary Education, (Female(%)/Male(%)/Both Sexes (%)).'''

== Pulling Data on Completion Rates: ==
The pre-processor series in IFs relating to graduation rates are:

#EdSecLowrCompletionFemale
#EdSecLowrCompletionMale
#EdSecLowrCompletionTotal
#EdSecUpprCompletionFemale
#EdSecUpprCompletionMale
#EdSecUpprCompletionTotal

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following dropdown menu sequence: Education>Education>Completion>Completion and graduation ratios. The specific location for each series is as follows.

*EdPriCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), select female (%) from dropdown
*EdPriCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), select male (%) from dropdown
*EdPriCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for primary education (household survey data), Both Sexes (%)
*EdSecLowrCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select female (%) from dropdown
*EdSecLowrCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select male (%) from dropdown
*EdSecLowrCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for lower secondary education (household survey data), select both sexes (%) from dropdown
*EdSecUpprCompletionFemale: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select female (%) from dropdown
*EdSecUpprCompletionMale: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select male (%) from dropdown
*EdSecUpprCompletionTotal: Education>Education>Completion>Completion and graduation ratios>Completion rate for upper secondary education (household survey data), select both sexes (%) from dropdown

== Pulling Data on Intake Rates: ==
The pre-processor series in IFs relating to apparent (gross) intake rates are:

#EdPriAIRFemale%
#EdPriAIRMale%
#EdPriAIRParity
#EdPriAIRTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Entry>Gross (Apparent) Intake Ratio to Primary and Lower Secondary Education.

Once here, the following three sheets were used: '''Gross Intake Rate to Grade 1 of Primary Education, (Female%/Male%/Total/GenderParityIndex (GPI)).'''

The pre-processor series in IFs relating to net (adjusted) intake rates are:

#EdPriNIRFemale%
#EdPriNIRMale%
#EdPriNIRTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Entry>Gross (Apparent) Intake Ratio to Primary and Lower Secondary Education.

Once here, the following three sheets were used: Adjusted Net Intake Rate to Grade 1 of Primary Education, '''(Female/Male/Total).'''

'''Net Intake Rate to Grade1 of Primary Education'''

EDPRINIRENTRNFemale

EDPRINIRENTRNMale

EDPRINIRENTRNTotal

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education, female (%)
*education>entry>net intake rate to primary education> Net Intake Rate to Grade1 of Primary Education male (%)
*education>entry>net intake rate to primary education> Net Intake Rate to Grade1 of Primary Education both sexes (%)

'''Net Intake Rate to Grade1 of Primary Education (over-age by +1 year)'''

EDPRINIRENTRNP1Male

EDPRINIRENTRNP1Female

EDPRINIRENTRNP1Total

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), male (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), female (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by over-age entrants (+1 year), both sexes (%) 
'''Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), male (%)'''

EDPRINIRENTRNM1Male

EDPRINIRENTRNM1Female

EDPRINIRENTRNM1Total

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), male (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), female (%)
*education>entry>net intake rate to primary education> Net intake rate to Grade 1 of primary education by under-age entrants (-1 year), both sexes (%) 
'''Adjusted Net Intake Rate to Grade1 of Primary Education'''

EDPRINIRADJFemale

EDPRINIRADJMale

EDPRINIRADJTotal

[http://data.uis.unesco.org/ http://data.uis.unesco.org/]

*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, female (%)
*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, male (%)
*education>entry>net intake rate to primary education> Adjusted net intake rate to Grade 1 of primary education, both sexes (%)

== Pulling Data on Survival Rates: ==
The pre-processor series in IFs relating to survival rates are:

#EdPriSurvivalFemale%
#EdPriSurvivalMale%
#EdPriSurvivalTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Progression>Survival Rates>Survival Rate to Last Grade of Primary Education.

Once here, the following three sheets were used: '''Survival Rate to the Last Grade of Primary Education, (Female%/Male%/Total%).'''

== Pulling Data on Duration: ==
The pre-processor series in IFs relating to survival rates are:

#EdPriDuration
#EdSecLowerDuration
#EdSecUpperDuration

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>System>Duration>Duration by Level of Education.

Once here, the following three sheets were used: '''Theoretical Duration of (Primary/Lower Seconday/Upper Secondary) Education.'''

== Pulling Data on Transition Rates: ==
The pre-processor series in IFs relating to transition rates are:

#EdPriTransition2Sec%Female
#EdPriTransition2Sec%Male
#EdPriTransition2SecTotal%

Data for these series was obtained from the UNESCO Institute for Statistics ([http://data.uis.unesco.org/ http://data.uis.unesco.org/]). Specifically, they are found in the following drop down menu sequence: Education>Progression>Transition Rates.

Once here, the following three sheets were used: '''Effective Transition Rate from Primary to Lower Secondary General Education, (Female%/Male%/Total%).'''

= Data Notes =

#As of May 2016, there was no data for 2015 for the LowerVoc series, only 1999-2014. However, there was 2015 data  for the UpperVoc series.
#Country Concordance: UNESCO countries. 
##As of March 2017, UIS utilizes "Cabo Verde" instead of "Cape Verde." The UNESCO Country Concordance utilizes "Cape Verde." '''You thus must replace "Cabo Verde" with "Cape Verde" in UIS data prior to importing into IFs.'''

Global Burdens of Disease (GBD), Institute for Health Metrics and Evaluation (IHME)

2026-01-09T23:06:03Z

Norah.Shamin: /* Calculations: */

= Summary =
The Institute for Health Metrics and Evaluation (IHME) provides data on the Global Burdens of Disease that can be accessed here http://ghdx.healthdata.org/gbd-results-tool. IHME provides data on multiple metrics that we pull into IFs, including deaths, DALYs, incidence, prevalence, violence and forecasts for each.

= Table In IFs =

=== Preprocessors on Prevalence and Incidence ===
The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series.
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|DrOpiodPrevIHME
|Opiod Prevalence Rate
|Prevalence; Percent: Opioid use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceAmphetaminesIHME
|Drug prevalence rate, Amphetamines
|Prevalence; Percent: Amphetamine use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceCocaineIHME
|Drug prevalence rate, Cocaine
|Prevalence; Percent: Cocaine use disorders
|1
|SOCIOPOL
|-
|IHMEInciHIVNumber
|Number of new cases of HIV in the population per year
|HIV, Incidence, Number
|1
|HEALTH
|-
|IHMEInciMalariaNumber
|Number of new cases of Malaria in the population per year
|Malaria, Incidence, Number
|1
|HEALTH
|-
|IHMEPrevHIV
|HIV Prevalence Rate
|Prevalence; Percent: HIV/AIDS
|1
|HEALTH
|-
|IHMEPrevHIVNumber
|Number of cases in the population; HIV; Headcount
|HIV, Prevalence, Number
|1
|HEALTH
|-
|IHMEPrevMalariaNumber
|Number of cases in the population; Malaria, Headcount
|Malaria, Prevalence, Number
|1
|HEALTH
|-
|SocietalViolenceDeathsTotal
|Societal violence deaths total (Interpersonal+Conflict+Policeexecutions)
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonChild
|Interpersonal violence against all children death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonOther
|Death rate from Interpersonal violence for males aged over 15
|
|0
|
|-
|ViolenceInterpersonWomenAdult
|Interpersonal violence against adult women death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonWomenChild
|Deaths from interpersonal violence (Violence against vulnerable populations)
|
|0
|
|-
|ViolencePoliticalConflictTerror
|Death rate from conflict and terrorism IHME
|
|1
|SOCIOPOL
|-
|ViolencePoliticalPoliceExecution
|Death rate from police executions and conflict IHME
|
|1
|SOCIOPOL
|-
|ViolenceSelfHarm
|Death rate from self harm IHME
|
|1
|SOCIOPOL
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|Malaria
|1
|HEALTH
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|HIV/AIDS
|1
|HEALTH, POPULATION
|}

=== Tables Used in Hist+Forecast Display ===
There are 45 tables in total related to detailed death tables in IFs. For each of 15 death causes in IFs, we have a total death table and two tables by sex group. These 45 tables can be searched by using the following naming conventions IHMEDths___, IHMEDths___Females, and IHMEDths___Males, where ___ denotes the cause of death in IFs. These 15 causes are, Cardio, Diabet, Diarrh, Digest, HIV, Intlj, Malar, MalNeopl, MentHlth, OthCD, OthNCD, OthUnintlj, Respinfec, Respiratory, Roadacc. Below is the causes used for each table:

The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Note that a detailed death cause mapping table can be found [[IFs.db#HealthDetailedDeathsCtry|here]].
{| class="wikitable"
!Table
!Definition
!UsedInPreprocessor
!UsedInPreprocessorFileName
!Name in Source
|-
|IHMEDthsCardio
|Deaths from cardiovascular disease in millions from IHME for both sexes
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Deaths from cardiovascular disease in millions from IHME for females
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Deaths from cardiovascular disease in millions from IHME for males
|0
|
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Deaths from diabetes in millions from IHME for both sexes
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Deaths from diabetes in millions from IHME for females
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Deaths from diabetes in millions from IHME for males
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Deaths from diarrhoea in millions from IHME for both sexes
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Deaths from diarrhoea in millions from IHME for females
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Deaths from diarrhoea in millions from IHME for males
|0
|
|Diarrheal diseases
|-
|IHMEDthsDigest
|Deaths from digestive diseases in millions from IHME for both sexes
|0
|
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Deaths from digestive diseases in millions from IHME for females
|0
|
|Digestive diseases
|-
|IHMEDthsDigestMales
|Deaths from digestive diseases in millions from IHME for males
|0
|
|Digestive diseases
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|1
|HEALTH, POPULATION
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|Deaths from HIV in millions from IHME for females
|0
|
|HIV/AIDS
|-
|IHMEDthsHIVMales
|Deaths from HIV in millions from IHME for males
|0
|
|HIV/AIDS
|-
|IHMEDthsIntIj
|Deaths from Intentional injuries in millions from IHME for both sexes
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Deaths from Intentional injuries in millions from IHME for females
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Deaths from Intentional injuries in millions from IHME for males
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|1
|HEALTH
|Malaria
|-
|IHMEDthsMalarFemales
|Deaths from malaria in millions from IHME for females
|0
|
|Malaria
|-
|IHMEDthsMalarMales
|Deaths from malaria in millions from IHME for males
|0
|
|Malaria
|-
|IHMEDthsMalNeopl
|Deaths from cancers in millions from IHME for both sexes
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Deaths from cancers in millions from IHME for females
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Deaths from cancers in millions from IHME for males
|0
|
|Neoplasms
|-
|IHMEDthsMentHlth
|Deaths from mental health in millions from IHME for both sexes
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Deaths from mental health in millions from IHME for females
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Deaths from mental health in millions from IHME for males
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Deaths from other CD in millions from IHME for both sexes
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Deaths from other CD in millions from IHME for females
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Deaths from other CD in millions from IHME for males
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Deaths from other NCD in millions from IHME for both sexes
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Deaths from other NCD in millions from IHME for females
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Deaths from other NCD in millions from IHME for males
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Deaths from other unintentional injuries in millions from IHME for both sexes
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Deaths from other unintentional injuries in millions from IHME for females
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Deaths from other unintentional injuries in millions from IHME for males
|0
|
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Deaths from respiratory infections in millions from IHME for both sexes
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Deaths from respiratory infections in millions from IHME for females
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Deaths from respiratory infections in millions from IHME for males
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Deaths from respiratory diseases in millions from IHME for both sexes
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Deaths from respiratory diseases in millions from IHME for females
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Deaths from respiratory diseases in millions from IHME for males
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Deaths from road accidents in millions from IHME for both sexes
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Deaths from road accidents in millions from IHME for females
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Deaths from road accidents in millions from IHME for males
|0
|
|Transport injuries
|}

=== Life Expectancy ===
{| class="wikitable"
|+
!Variable
!Definition
!UsedInPreprocessor
|-
|LifeExpectIHMEBothSexesHistOnly
|Average life expectancy values (history only) for both sexes for ages 0-6 days.
|0
|-
|LifeExpectIHMEFemaleHistOnly
|Average life expectancy values (history only) for female for ages 0-6 days.
|0
|-
|LifeExpectIHMEMaleHistOnly
|Average life expectancy values (history only) for male for ages 0-6 days.
|0
|}

=== Infant Mortality ===
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
|-
|InfMortRateIHME
|Infant Mortality Rate from IHME GBD project. Summation of mortality categories: 0-6 Days; 7-28 Days; 29-365 Days.
|Probability of death; >1 year
|0
|-
|Under5MortRateIHME
|Under 5 mortality Rate from IHME GBD Project, all causes
|Probability of death; sum of >1 years, 2-4 years
|0
|}

=== Tables in IFs.db ===
'''HealthDetailedDeathsCtry'''

Detailed instruction on pulling number of deaths for IFs death categories can be found [[IFs.db|here]].

= Data Pulling Instructions =

=== Preprocessors on Prevalence and Incidence ===
[https://github.com/shangkexin/The_Institute_for_Health_Metrics_and_Evaluation_IHME Python scripts] used from last data pull can be accessed and adjusted for future data pulls. An updated country concordance table can be found [https://1drv.ms/x/c/64a1920f95dbe644/EWHhcKUK3ldEoIgMqLc6O0QB5ylEO7D509sB2273fFWu-g?e=vbtEsa here]. There are different country concordance for each set of indicators. Double check what format of country concordance you need for each section.

Use these filters:
{| class="wikitable"
|Variable
|GBD Estimate
|Measure
|Metric
|Cause
|Location
|Age
|Sex
|Year
|Decimal Places
|-
|ViolencePoliticalConflictTerror
|Cause of death or injury
|Deaths
|Rate
|Conflict and terrorism
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolencePoliticalPoliceExecution
|Cause of death or injury
|Deaths
|Rate
|Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceSelfHarm
|Cause of death or injury
|Deaths
|Rate
|Self-harm
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|SocietalViolenceDeathsTotal
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence + Conflict and terrorism + Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceInterpersonChild
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence against all children death rate
|Select all countries and territories
|0-14
|Both
|Select all
|4
|-
|ViolenceInterpersonWomenAdult
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence
|Select all countries and territories
|>= 15
|Female
|Select all
|4
|-
|DrOpiodPrevIHME
|Cause of death or injury
|Prevalence
|Percent
|Opioid Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|DrugPrevalenceAmphetaminesIHME
|Cause of death or injury
|Prevalence
|Percent
|Amphetamine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|DrugPrevalenceCocaineIHME
|Cause of death or injury
|Prevalence
|Percent
|Cocaine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsHIV
|Cause of death or injury
|Deaths
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsMalar
|Cause of death or injury
|Deaths
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEInciHIVNumber
|Cause of death or injury
|Incidence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEInciMalariaNumber
|Cause of death or injury
|Incidence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevHIV
|Cause of death or injury
|Prevalence
|Percent
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|3
|-
|IHMEPrevHIVNumber
|Cause of death or injury
|Prevalence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevMalariaNumber
|Cause of death or injury
|Prevalence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|ViolenceInterpersonOther
|Cause of death or injury
|Deaths
|Rate
|Death rate from Interpersonal violence for males aged over 15
|Select all countries and territories
|>= 15
|Both
|Select all
|
|-
|ViolenceInterpersonWomenChild
|Cause of death or injury
|Deaths
|Rate
|Deaths from interpersonal violence (Violence against women and children)
|Select all countries and territories
|Sum of Child and WomenAdult
|Both
|Select all
|
|}

=== Tables Used in Hist+Forecast Display ===
[https://vizhub.healthdata.org/gbd-results/ Use the filters]:

GBD Estimate Cause of death or injury

Measure Deaths

Metric Rate

Location All territories and countries

Age All ages

Sex Both, Female, Male

Year All

Use the causes below:
{| class="wikitable"
!Table
!Cause
|-
|IHMEDthsCardio
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Diarrheal diseases
|-
|IHMEDthsDigest
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Digestive diseases
|-
|IHMEDthsDigestMales
|Digestive diseases
|-
|IHMEDthsHIV
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|HIV/AIDS
|-
|IHMEDthsHIVMales
|HIV/AIDS
|-
|IHMEDthsIntIj
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Malaria
|-
|IHMEDthsMalarFemales
|Malaria
|-
|IHMEDthsMalarMales
|Malaria
|-
|IHMEDthsMalNeopl
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Neoplasms
|-
|IHMEDthsMentHlth
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Transport injuries
|}

=== Life Expectancy ===
Navigate to: https://vizhub.healthdata.org/gbd-results/

Use the filters:
GBD Estimate All-cause mortality

Measure Life Expectancy

Metric Years

Location All territories and countries

Age Stated below

Sex Stated below

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Metric Name
|Decimal Places
|-
|LifeExpectIHMEBothSexesHistOnly
|0-6 days
|Both
|1950-2023
|Years
|3
|-
|LifeExpectIHMEMaleHistOnly
|0-6 days
|Male
|1950-2023
|Years
|3
|-
|LifeExpectIHMEFemaleHistOnly
|0-6 days
|Female
|1950-2023
|Years
|3
|}

=== Infant Mortality ===
Life expectancy data can be pulled from http://ghdx.healthdata.org/gbd-results-tool. The filters should be:

GBD Estimate All-cause mortality

Measure Life Tables

Metric Probability of death

Location All territories and countries

Age Stated below

Sex Both

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Decimal Places
|-
|InfMortRateIHME
|< 1 year
|Both
|1950-2023
|4
|-
|Under5MortRateIHME
|Calculation of < 1 year, 12-23 months, and 2-4 year
|Both
|1950-2023
|4
|}
'''Calculations:'''

In order to get the right value for Under5MortRateIHME, we have to calculate it. It should be:

PoD under 5 = PoD under 1 + PoD 12-23 months * Probability of not dying under 1+ PoD 2-4 years * Probability of not dying under 2.

An example is posted below for Iraq:
{| class="wikitable"
|Age
|Metric
|Year
|Value
|-
|<1 year
|Probability of death
|2019
|0.019244
|-
|12-23 months
|Probability of death
|2019
|0.001482
|-
|2-4 years
|Probability of death
|2019
|0.002298
|}

The PoD for under 2 would be = 0.019244 + 0.001482 * ( 1 - 0.019244) = 0.020698;

The PoD for under 5 would be = 0.020698 + 0.002298 * ( 1 - 0.020698) = 0.022948.

The final data point is '''0.022948'''.

= Data Notes =

* ViolenceInterpersonChild & ViolenceInterpersonWomenAdult have changed a lot, we identify the Age by comparing the trend of old data in IFsHistSeries and the new data from GBD.
** In March 2025, the ages have shifted from >20 for adults to >15. To get this data, do a summation of 15-19 and 20+

* Be aware of the definition of each preprocessor and its unit so that you can find the exact match in the IHME GBD variables.

=== Proxies ===
* Some regions in IFs are not provided by IHME yet, we are encouraged to use proxies. For example, use Singapore, Albania, and Mali for Hong Kong, Kosovo, and Sahrawi respectively. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally.
** For instance, LifeExpectIHMEBothSexesHistOnly would not use a calculation, but IHMEDthsHIV will.
** To do this use SeriesPopulation. For instance, Kosovo’s number of deaths = Albania’s number of deaths * Kosovo’s Population / Albania’s Population.

Global Burdens of Disease (GBD), Institute for Health Metrics and Evaluation (IHME)

2026-01-09T23:04:40Z

Norah.Shamin: /* HealthDetailedDeathsCtry */

= Summary =
The Institute for Health Metrics and Evaluation (IHME) provides data on the Global Burdens of Disease that can be accessed here http://ghdx.healthdata.org/gbd-results-tool. IHME provides data on multiple metrics that we pull into IFs, including deaths, DALYs, incidence, prevalence, violence and forecasts for each.

= Table In IFs =

=== Preprocessors on Prevalence and Incidence ===
The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series.
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|DrOpiodPrevIHME
|Opiod Prevalence Rate
|Prevalence; Percent: Opioid use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceAmphetaminesIHME
|Drug prevalence rate, Amphetamines
|Prevalence; Percent: Amphetamine use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceCocaineIHME
|Drug prevalence rate, Cocaine
|Prevalence; Percent: Cocaine use disorders
|1
|SOCIOPOL
|-
|IHMEInciHIVNumber
|Number of new cases of HIV in the population per year
|HIV, Incidence, Number
|1
|HEALTH
|-
|IHMEInciMalariaNumber
|Number of new cases of Malaria in the population per year
|Malaria, Incidence, Number
|1
|HEALTH
|-
|IHMEPrevHIV
|HIV Prevalence Rate
|Prevalence; Percent: HIV/AIDS
|1
|HEALTH
|-
|IHMEPrevHIVNumber
|Number of cases in the population; HIV; Headcount
|HIV, Prevalence, Number
|1
|HEALTH
|-
|IHMEPrevMalariaNumber
|Number of cases in the population; Malaria, Headcount
|Malaria, Prevalence, Number
|1
|HEALTH
|-
|SocietalViolenceDeathsTotal
|Societal violence deaths total (Interpersonal+Conflict+Policeexecutions)
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonChild
|Interpersonal violence against all children death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonOther
|Death rate from Interpersonal violence for males aged over 15
|
|0
|
|-
|ViolenceInterpersonWomenAdult
|Interpersonal violence against adult women death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonWomenChild
|Deaths from interpersonal violence (Violence against vulnerable populations)
|
|0
|
|-
|ViolencePoliticalConflictTerror
|Death rate from conflict and terrorism IHME
|
|1
|SOCIOPOL
|-
|ViolencePoliticalPoliceExecution
|Death rate from police executions and conflict IHME
|
|1
|SOCIOPOL
|-
|ViolenceSelfHarm
|Death rate from self harm IHME
|
|1
|SOCIOPOL
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|Malaria
|1
|HEALTH
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|HIV/AIDS
|1
|HEALTH, POPULATION
|}

=== Tables Used in Hist+Forecast Display ===
There are 45 tables in total related to detailed death tables in IFs. For each of 15 death causes in IFs, we have a total death table and two tables by sex group. These 45 tables can be searched by using the following naming conventions IHMEDths___, IHMEDths___Females, and IHMEDths___Males, where ___ denotes the cause of death in IFs. These 15 causes are, Cardio, Diabet, Diarrh, Digest, HIV, Intlj, Malar, MalNeopl, MentHlth, OthCD, OthNCD, OthUnintlj, Respinfec, Respiratory, Roadacc. Below is the causes used for each table:

The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Note that a detailed death cause mapping table can be found [[IFs.db#HealthDetailedDeathsCtry|here]].
{| class="wikitable"
!Table
!Definition
!UsedInPreprocessor
!UsedInPreprocessorFileName
!Name in Source
|-
|IHMEDthsCardio
|Deaths from cardiovascular disease in millions from IHME for both sexes
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Deaths from cardiovascular disease in millions from IHME for females
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Deaths from cardiovascular disease in millions from IHME for males
|0
|
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Deaths from diabetes in millions from IHME for both sexes
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Deaths from diabetes in millions from IHME for females
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Deaths from diabetes in millions from IHME for males
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Deaths from diarrhoea in millions from IHME for both sexes
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Deaths from diarrhoea in millions from IHME for females
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Deaths from diarrhoea in millions from IHME for males
|0
|
|Diarrheal diseases
|-
|IHMEDthsDigest
|Deaths from digestive diseases in millions from IHME for both sexes
|0
|
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Deaths from digestive diseases in millions from IHME for females
|0
|
|Digestive diseases
|-
|IHMEDthsDigestMales
|Deaths from digestive diseases in millions from IHME for males
|0
|
|Digestive diseases
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|1
|HEALTH, POPULATION
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|Deaths from HIV in millions from IHME for females
|0
|
|HIV/AIDS
|-
|IHMEDthsHIVMales
|Deaths from HIV in millions from IHME for males
|0
|
|HIV/AIDS
|-
|IHMEDthsIntIj
|Deaths from Intentional injuries in millions from IHME for both sexes
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Deaths from Intentional injuries in millions from IHME for females
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Deaths from Intentional injuries in millions from IHME for males
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|1
|HEALTH
|Malaria
|-
|IHMEDthsMalarFemales
|Deaths from malaria in millions from IHME for females
|0
|
|Malaria
|-
|IHMEDthsMalarMales
|Deaths from malaria in millions from IHME for males
|0
|
|Malaria
|-
|IHMEDthsMalNeopl
|Deaths from cancers in millions from IHME for both sexes
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Deaths from cancers in millions from IHME for females
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Deaths from cancers in millions from IHME for males
|0
|
|Neoplasms
|-
|IHMEDthsMentHlth
|Deaths from mental health in millions from IHME for both sexes
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Deaths from mental health in millions from IHME for females
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Deaths from mental health in millions from IHME for males
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Deaths from other CD in millions from IHME for both sexes
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Deaths from other CD in millions from IHME for females
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Deaths from other CD in millions from IHME for males
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Deaths from other NCD in millions from IHME for both sexes
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Deaths from other NCD in millions from IHME for females
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Deaths from other NCD in millions from IHME for males
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Deaths from other unintentional injuries in millions from IHME for both sexes
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Deaths from other unintentional injuries in millions from IHME for females
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Deaths from other unintentional injuries in millions from IHME for males
|0
|
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Deaths from respiratory infections in millions from IHME for both sexes
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Deaths from respiratory infections in millions from IHME for females
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Deaths from respiratory infections in millions from IHME for males
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Deaths from respiratory diseases in millions from IHME for both sexes
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Deaths from respiratory diseases in millions from IHME for females
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Deaths from respiratory diseases in millions from IHME for males
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Deaths from road accidents in millions from IHME for both sexes
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Deaths from road accidents in millions from IHME for females
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Deaths from road accidents in millions from IHME for males
|0
|
|Transport injuries
|}

=== Life Expectancy ===
{| class="wikitable"
|+
!Variable
!Definition
!UsedInPreprocessor
|-
|LifeExpectIHMEBothSexesHistOnly
|Average life expectancy values (history only) for both sexes for ages 0-6 days.
|0
|-
|LifeExpectIHMEFemaleHistOnly
|Average life expectancy values (history only) for female for ages 0-6 days.
|0
|-
|LifeExpectIHMEMaleHistOnly
|Average life expectancy values (history only) for male for ages 0-6 days.
|0
|}

=== Infant Mortality ===
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
|-
|InfMortRateIHME
|Infant Mortality Rate from IHME GBD project. Summation of mortality categories: 0-6 Days; 7-28 Days; 29-365 Days.
|Probability of death; >1 year
|0
|-
|Under5MortRateIHME
|Under 5 mortality Rate from IHME GBD Project, all causes
|Probability of death; sum of >1 years, 2-4 years
|0
|}

=== Tables in IFs.db ===
'''HealthDetailedDeathsCtry'''

Detailed instruction on pulling number of deaths for IFs death categories can be found [[IFs.db|here]].

= Data Pulling Instructions =

=== Preprocessors on Prevalence and Incidence ===
[https://github.com/shangkexin/The_Institute_for_Health_Metrics_and_Evaluation_IHME Python scripts] used from last data pull can be accessed and adjusted for future data pulls. An updated country concordance table can be found [https://1drv.ms/x/c/64a1920f95dbe644/EWHhcKUK3ldEoIgMqLc6O0QB5ylEO7D509sB2273fFWu-g?e=vbtEsa here]. There are different country concordance for each set of indicators. Double check what format of country concordance you need for each section.

Use these filters:
{| class="wikitable"
|Variable
|GBD Estimate
|Measure
|Metric
|Cause
|Location
|Age
|Sex
|Year
|Decimal Places
|-
|ViolencePoliticalConflictTerror
|Cause of death or injury
|Deaths
|Rate
|Conflict and terrorism
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolencePoliticalPoliceExecution
|Cause of death or injury
|Deaths
|Rate
|Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceSelfHarm
|Cause of death or injury
|Deaths
|Rate
|Self-harm
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|SocietalViolenceDeathsTotal
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence + Conflict and terrorism + Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceInterpersonChild
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence against all children death rate
|Select all countries and territories
|0-14
|Both
|Select all
|4
|-
|ViolenceInterpersonWomenAdult
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence
|Select all countries and territories
|>= 15
|Female
|Select all
|4
|-
|DrOpiodPrevIHME
|Cause of death or injury
|Prevalence
|Percent
|Opioid Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|DrugPrevalenceAmphetaminesIHME
|Cause of death or injury
|Prevalence
|Percent
|Amphetamine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|DrugPrevalenceCocaineIHME
|Cause of death or injury
|Prevalence
|Percent
|Cocaine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsHIV
|Cause of death or injury
|Deaths
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsMalar
|Cause of death or injury
|Deaths
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEInciHIVNumber
|Cause of death or injury
|Incidence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEInciMalariaNumber
|Cause of death or injury
|Incidence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevHIV
|Cause of death or injury
|Prevalence
|Percent
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|3
|-
|IHMEPrevHIVNumber
|Cause of death or injury
|Prevalence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevMalariaNumber
|Cause of death or injury
|Prevalence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|ViolenceInterpersonOther
|Cause of death or injury
|Deaths
|Rate
|Death rate from Interpersonal violence for males aged over 15
|Select all countries and territories
|>= 15
|Both
|Select all
|
|-
|ViolenceInterpersonWomenChild
|Cause of death or injury
|Deaths
|Rate
|Deaths from interpersonal violence (Violence against women and children)
|Select all countries and territories
|Sum of Child and WomenAdult
|Both
|Select all
|
|}

=== Tables Used in Hist+Forecast Display ===
[https://vizhub.healthdata.org/gbd-results/ Use the filters]:

GBD Estimate Cause of death or injury

Measure Deaths

Metric Rate

Location All territories and countries

Age All ages

Sex Both, Female, Male

Year All

Use the causes below:
{| class="wikitable"
!Table
!Cause
|-
|IHMEDthsCardio
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Diarrheal diseases
|-
|IHMEDthsDigest
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Digestive diseases
|-
|IHMEDthsDigestMales
|Digestive diseases
|-
|IHMEDthsHIV
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|HIV/AIDS
|-
|IHMEDthsHIVMales
|HIV/AIDS
|-
|IHMEDthsIntIj
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Malaria
|-
|IHMEDthsMalarFemales
|Malaria
|-
|IHMEDthsMalarMales
|Malaria
|-
|IHMEDthsMalNeopl
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Neoplasms
|-
|IHMEDthsMentHlth
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Transport injuries
|}

=== Life Expectancy ===
Navigate to: https://vizhub.healthdata.org/gbd-results/

Use the filters:
GBD Estimate All-cause mortality

Measure Life Expectancy

Metric Years

Location All territories and countries

Age Stated below

Sex Stated below

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Metric Name
|Decimal Places
|-
|LifeExpectIHMEBothSexesHistOnly
|0-6 days
|Both
|1950-2023
|Years
|3
|-
|LifeExpectIHMEMaleHistOnly
|0-6 days
|Male
|1950-2023
|Years
|3
|-
|LifeExpectIHMEFemaleHistOnly
|0-6 days
|Female
|1950-2023
|Years
|3
|}

=== Infant Mortality ===
Life expectancy data can be pulled from http://ghdx.healthdata.org/gbd-results-tool. The filters should be:

GBD Estimate All-cause mortality

Measure Life Tables

Metric Probability of death

Location All territories and countries

Age Stated below

Sex Both

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Decimal Places
|-
|InfMortRateIHME
|< 1 year
|Both
|1950-2021
|4
|-
|Under5MortRateIHME
|Calculation of < 1 year, 12-23 months, and 2-4 year
|Both
|1950-2021
|4
|}

==== Calculations: ====
In order to get the right value for Under5MortRateIHME, we have to calculate it. It should be:

PoD under 5 = PoD under 1 + PoD 12-23 months * Probability of not dying under 1+ PoD 2-4 years * Probability of not dying under 2.

An example is posted below for Iraq:
{| class="wikitable"
|Age
|Metric
|Year
|Value
|-
|<1 year
|Probability of death
|2019
|0.019244
|-
|12-23 months
|Probability of death
|2019
|0.001482
|-
|2-4 years
|Probability of death
|2019
|0.002298
|}

The PoD for under 2 would be = 0.019244 + 0.001482 * ( 1 - 0.019244) = 0.020698;

The PoD for under 5 would be = 0.020698 + 0.002298 * ( 1 - 0.020698) = 0.022948.

The final data point is '''0.022948'''.

= Data Notes =

* ViolenceInterpersonChild & ViolenceInterpersonWomenAdult have changed a lot, we identify the Age by comparing the trend of old data in IFsHistSeries and the new data from GBD.
** In March 2025, the ages have shifted from >20 for adults to >15. To get this data, do a summation of 15-19 and 20+

* Be aware of the definition of each preprocessor and its unit so that you can find the exact match in the IHME GBD variables.

=== Proxies ===
* Some regions in IFs are not provided by IHME yet, we are encouraged to use proxies. For example, use Singapore, Albania, and Mali for Hong Kong, Kosovo, and Sahrawi respectively. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally.
** For instance, LifeExpectIHMEBothSexesHistOnly would not use a calculation, but IHMEDthsHIV will.
** To do this use SeriesPopulation. For instance, Kosovo’s number of deaths = Albania’s number of deaths * Kosovo’s Population / Albania’s Population.

Global Burdens of Disease (GBD), Institute for Health Metrics and Evaluation (IHME)

2026-01-09T23:04:22Z

Norah.Shamin: /* Life Expectancy */

= Summary =
The Institute for Health Metrics and Evaluation (IHME) provides data on the Global Burdens of Disease that can be accessed here http://ghdx.healthdata.org/gbd-results-tool. IHME provides data on multiple metrics that we pull into IFs, including deaths, DALYs, incidence, prevalence, violence and forecasts for each.

= Table In IFs =

=== Preprocessors on Prevalence and Incidence ===
The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series.
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|DrOpiodPrevIHME
|Opiod Prevalence Rate
|Prevalence; Percent: Opioid use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceAmphetaminesIHME
|Drug prevalence rate, Amphetamines
|Prevalence; Percent: Amphetamine use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceCocaineIHME
|Drug prevalence rate, Cocaine
|Prevalence; Percent: Cocaine use disorders
|1
|SOCIOPOL
|-
|IHMEInciHIVNumber
|Number of new cases of HIV in the population per year
|HIV, Incidence, Number
|1
|HEALTH
|-
|IHMEInciMalariaNumber
|Number of new cases of Malaria in the population per year
|Malaria, Incidence, Number
|1
|HEALTH
|-
|IHMEPrevHIV
|HIV Prevalence Rate
|Prevalence; Percent: HIV/AIDS
|1
|HEALTH
|-
|IHMEPrevHIVNumber
|Number of cases in the population; HIV; Headcount
|HIV, Prevalence, Number
|1
|HEALTH
|-
|IHMEPrevMalariaNumber
|Number of cases in the population; Malaria, Headcount
|Malaria, Prevalence, Number
|1
|HEALTH
|-
|SocietalViolenceDeathsTotal
|Societal violence deaths total (Interpersonal+Conflict+Policeexecutions)
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonChild
|Interpersonal violence against all children death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonOther
|Death rate from Interpersonal violence for males aged over 15
|
|0
|
|-
|ViolenceInterpersonWomenAdult
|Interpersonal violence against adult women death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonWomenChild
|Deaths from interpersonal violence (Violence against vulnerable populations)
|
|0
|
|-
|ViolencePoliticalConflictTerror
|Death rate from conflict and terrorism IHME
|
|1
|SOCIOPOL
|-
|ViolencePoliticalPoliceExecution
|Death rate from police executions and conflict IHME
|
|1
|SOCIOPOL
|-
|ViolenceSelfHarm
|Death rate from self harm IHME
|
|1
|SOCIOPOL
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|Malaria
|1
|HEALTH
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|HIV/AIDS
|1
|HEALTH, POPULATION
|}

=== Tables Used in Hist+Forecast Display ===
There are 45 tables in total related to detailed death tables in IFs. For each of 15 death causes in IFs, we have a total death table and two tables by sex group. These 45 tables can be searched by using the following naming conventions IHMEDths___, IHMEDths___Females, and IHMEDths___Males, where ___ denotes the cause of death in IFs. These 15 causes are, Cardio, Diabet, Diarrh, Digest, HIV, Intlj, Malar, MalNeopl, MentHlth, OthCD, OthNCD, OthUnintlj, Respinfec, Respiratory, Roadacc. Below is the causes used for each table:

The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Note that a detailed death cause mapping table can be found [[IFs.db#HealthDetailedDeathsCtry|here]].
{| class="wikitable"
!Table
!Definition
!UsedInPreprocessor
!UsedInPreprocessorFileName
!Name in Source
|-
|IHMEDthsCardio
|Deaths from cardiovascular disease in millions from IHME for both sexes
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Deaths from cardiovascular disease in millions from IHME for females
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Deaths from cardiovascular disease in millions from IHME for males
|0
|
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Deaths from diabetes in millions from IHME for both sexes
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Deaths from diabetes in millions from IHME for females
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Deaths from diabetes in millions from IHME for males
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Deaths from diarrhoea in millions from IHME for both sexes
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Deaths from diarrhoea in millions from IHME for females
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Deaths from diarrhoea in millions from IHME for males
|0
|
|Diarrheal diseases
|-
|IHMEDthsDigest
|Deaths from digestive diseases in millions from IHME for both sexes
|0
|
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Deaths from digestive diseases in millions from IHME for females
|0
|
|Digestive diseases
|-
|IHMEDthsDigestMales
|Deaths from digestive diseases in millions from IHME for males
|0
|
|Digestive diseases
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|1
|HEALTH, POPULATION
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|Deaths from HIV in millions from IHME for females
|0
|
|HIV/AIDS
|-
|IHMEDthsHIVMales
|Deaths from HIV in millions from IHME for males
|0
|
|HIV/AIDS
|-
|IHMEDthsIntIj
|Deaths from Intentional injuries in millions from IHME for both sexes
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Deaths from Intentional injuries in millions from IHME for females
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Deaths from Intentional injuries in millions from IHME for males
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|1
|HEALTH
|Malaria
|-
|IHMEDthsMalarFemales
|Deaths from malaria in millions from IHME for females
|0
|
|Malaria
|-
|IHMEDthsMalarMales
|Deaths from malaria in millions from IHME for males
|0
|
|Malaria
|-
|IHMEDthsMalNeopl
|Deaths from cancers in millions from IHME for both sexes
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Deaths from cancers in millions from IHME for females
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Deaths from cancers in millions from IHME for males
|0
|
|Neoplasms
|-
|IHMEDthsMentHlth
|Deaths from mental health in millions from IHME for both sexes
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Deaths from mental health in millions from IHME for females
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Deaths from mental health in millions from IHME for males
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Deaths from other CD in millions from IHME for both sexes
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Deaths from other CD in millions from IHME for females
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Deaths from other CD in millions from IHME for males
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Deaths from other NCD in millions from IHME for both sexes
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Deaths from other NCD in millions from IHME for females
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Deaths from other NCD in millions from IHME for males
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Deaths from other unintentional injuries in millions from IHME for both sexes
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Deaths from other unintentional injuries in millions from IHME for females
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Deaths from other unintentional injuries in millions from IHME for males
|0
|
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Deaths from respiratory infections in millions from IHME for both sexes
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Deaths from respiratory infections in millions from IHME for females
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Deaths from respiratory infections in millions from IHME for males
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Deaths from respiratory diseases in millions from IHME for both sexes
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Deaths from respiratory diseases in millions from IHME for females
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Deaths from respiratory diseases in millions from IHME for males
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Deaths from road accidents in millions from IHME for both sexes
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Deaths from road accidents in millions from IHME for females
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Deaths from road accidents in millions from IHME for males
|0
|
|Transport injuries
|}

=== Life Expectancy ===
{| class="wikitable"
|+
!Variable
!Definition
!UsedInPreprocessor
|-
|LifeExpectIHMEBothSexesHistOnly
|Average life expectancy values (history only) for both sexes for ages 0-6 days.
|0
|-
|LifeExpectIHMEFemaleHistOnly
|Average life expectancy values (history only) for female for ages 0-6 days.
|0
|-
|LifeExpectIHMEMaleHistOnly
|Average life expectancy values (history only) for male for ages 0-6 days.
|0
|}

=== Infant Mortality ===
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
|-
|InfMortRateIHME
|Infant Mortality Rate from IHME GBD project. Summation of mortality categories: 0-6 Days; 7-28 Days; 29-365 Days.
|Probability of death; >1 year
|0
|-
|Under5MortRateIHME
|Under 5 mortality Rate from IHME GBD Project, all causes
|Probability of death; sum of >1 years, 2-4 years
|0
|}

=== Tables in IFs.db ===

==== HealthDetailedDeathsCtry ====
Detailed instruction on pulling number of deaths for IFs death categories can be found [[IFs.db|here]].

= Data Pulling Instructions =

=== Preprocessors on Prevalence and Incidence ===
[https://github.com/shangkexin/The_Institute_for_Health_Metrics_and_Evaluation_IHME Python scripts] used from last data pull can be accessed and adjusted for future data pulls. An updated country concordance table can be found [https://1drv.ms/x/c/64a1920f95dbe644/EWHhcKUK3ldEoIgMqLc6O0QB5ylEO7D509sB2273fFWu-g?e=vbtEsa here]. There are different country concordance for each set of indicators. Double check what format of country concordance you need for each section.

Use these filters:
{| class="wikitable"
|Variable
|GBD Estimate
|Measure
|Metric
|Cause
|Location
|Age
|Sex
|Year
|Decimal Places
|-
|ViolencePoliticalConflictTerror
|Cause of death or injury
|Deaths
|Rate
|Conflict and terrorism
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolencePoliticalPoliceExecution
|Cause of death or injury
|Deaths
|Rate
|Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceSelfHarm
|Cause of death or injury
|Deaths
|Rate
|Self-harm
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|SocietalViolenceDeathsTotal
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence + Conflict and terrorism + Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceInterpersonChild
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence against all children death rate
|Select all countries and territories
|0-14
|Both
|Select all
|4
|-
|ViolenceInterpersonWomenAdult
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence
|Select all countries and territories
|>= 15
|Female
|Select all
|4
|-
|DrOpiodPrevIHME
|Cause of death or injury
|Prevalence
|Percent
|Opioid Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|DrugPrevalenceAmphetaminesIHME
|Cause of death or injury
|Prevalence
|Percent
|Amphetamine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|DrugPrevalenceCocaineIHME
|Cause of death or injury
|Prevalence
|Percent
|Cocaine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsHIV
|Cause of death or injury
|Deaths
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsMalar
|Cause of death or injury
|Deaths
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEInciHIVNumber
|Cause of death or injury
|Incidence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEInciMalariaNumber
|Cause of death or injury
|Incidence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevHIV
|Cause of death or injury
|Prevalence
|Percent
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|3
|-
|IHMEPrevHIVNumber
|Cause of death or injury
|Prevalence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevMalariaNumber
|Cause of death or injury
|Prevalence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|ViolenceInterpersonOther
|Cause of death or injury
|Deaths
|Rate
|Death rate from Interpersonal violence for males aged over 15
|Select all countries and territories
|>= 15
|Both
|Select all
|
|-
|ViolenceInterpersonWomenChild
|Cause of death or injury
|Deaths
|Rate
|Deaths from interpersonal violence (Violence against women and children)
|Select all countries and territories
|Sum of Child and WomenAdult
|Both
|Select all
|
|}

=== Tables Used in Hist+Forecast Display ===
[https://vizhub.healthdata.org/gbd-results/ Use the filters]:

GBD Estimate Cause of death or injury

Measure Deaths

Metric Rate

Location All territories and countries

Age All ages

Sex Both, Female, Male

Year All

Use the causes below:
{| class="wikitable"
!Table
!Cause
|-
|IHMEDthsCardio
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Diarrheal diseases
|-
|IHMEDthsDigest
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Digestive diseases
|-
|IHMEDthsDigestMales
|Digestive diseases
|-
|IHMEDthsHIV
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|HIV/AIDS
|-
|IHMEDthsHIVMales
|HIV/AIDS
|-
|IHMEDthsIntIj
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Malaria
|-
|IHMEDthsMalarFemales
|Malaria
|-
|IHMEDthsMalarMales
|Malaria
|-
|IHMEDthsMalNeopl
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Neoplasms
|-
|IHMEDthsMentHlth
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Transport injuries
|}

=== Life Expectancy ===
Navigate to: https://vizhub.healthdata.org/gbd-results/

Use the filters:
GBD Estimate All-cause mortality

Measure Life Expectancy

Metric Years

Location All territories and countries

Age Stated below

Sex Stated below

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Metric Name
|Decimal Places
|-
|LifeExpectIHMEBothSexesHistOnly
|0-6 days
|Both
|1950-2023
|Years
|3
|-
|LifeExpectIHMEMaleHistOnly
|0-6 days
|Male
|1950-2023
|Years
|3
|-
|LifeExpectIHMEFemaleHistOnly
|0-6 days
|Female
|1950-2023
|Years
|3
|}

=== Infant Mortality ===
Life expectancy data can be pulled from http://ghdx.healthdata.org/gbd-results-tool. The filters should be:

GBD Estimate All-cause mortality

Measure Life Tables

Metric Probability of death

Location All territories and countries

Age Stated below

Sex Both

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Decimal Places
|-
|InfMortRateIHME
|< 1 year
|Both
|1950-2021
|4
|-
|Under5MortRateIHME
|Calculation of < 1 year, 12-23 months, and 2-4 year
|Both
|1950-2021
|4
|}

==== Calculations: ====
In order to get the right value for Under5MortRateIHME, we have to calculate it. It should be:

PoD under 5 = PoD under 1 + PoD 12-23 months * Probability of not dying under 1+ PoD 2-4 years * Probability of not dying under 2.

An example is posted below for Iraq:
{| class="wikitable"
|Age
|Metric
|Year
|Value
|-
|<1 year
|Probability of death
|2019
|0.019244
|-
|12-23 months
|Probability of death
|2019
|0.001482
|-
|2-4 years
|Probability of death
|2019
|0.002298
|}

The PoD for under 2 would be = 0.019244 + 0.001482 * ( 1 - 0.019244) = 0.020698;

The PoD for under 5 would be = 0.020698 + 0.002298 * ( 1 - 0.020698) = 0.022948.

The final data point is '''0.022948'''.

= Data Notes =

* ViolenceInterpersonChild & ViolenceInterpersonWomenAdult have changed a lot, we identify the Age by comparing the trend of old data in IFsHistSeries and the new data from GBD.
** In March 2025, the ages have shifted from >20 for adults to >15. To get this data, do a summation of 15-19 and 20+

* Be aware of the definition of each preprocessor and its unit so that you can find the exact match in the IHME GBD variables.

=== Proxies ===
* Some regions in IFs are not provided by IHME yet, we are encouraged to use proxies. For example, use Singapore, Albania, and Mali for Hong Kong, Kosovo, and Sahrawi respectively. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally.
** For instance, LifeExpectIHMEBothSexesHistOnly would not use a calculation, but IHMEDthsHIV will.
** To do this use SeriesPopulation. For instance, Kosovo’s number of deaths = Albania’s number of deaths * Kosovo’s Population / Albania’s Population.

Global Burdens of Disease (GBD), Institute for Health Metrics and Evaluation (IHME)

2026-01-09T17:24:11Z

Norah.Shamin:

= Summary =
The Institute for Health Metrics and Evaluation (IHME) provides data on the Global Burdens of Disease that can be accessed here http://ghdx.healthdata.org/gbd-results-tool. IHME provides data on multiple metrics that we pull into IFs, including deaths, DALYs, incidence, prevalence, violence and forecasts for each. The latest IFs data update for this series was in March 2025, covering 188 economies over the years 198/90-2021. There have been major changes in this update which will be noted below.

= Table In IFs =

=== Preprocessors on Prevalence and Incidence ===
The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series.
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|DrOpiodPrevIHME
|Opiod Prevalence Rate
|Prevalence; Percent: Opioid use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceAmphetaminesIHME
|Drug prevalence rate, Amphetamines
|Prevalence; Percent: Amphetamine use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceCocaineIHME
|Drug prevalence rate, Cocaine
|Prevalence; Percent: Cocaine use disorders
|1
|SOCIOPOL
|-
|IHMEInciHIVNumber
|Number of new cases of HIV in the population per year
|HIV, Incidence, Number
|1
|HEALTH
|-
|IHMEInciMalariaNumber
|Number of new cases of Malaria in the population per year
|Malaria, Incidence, Number
|1
|HEALTH
|-
|IHMEPrevHIV
|HIV Prevalence Rate
|Prevalence; Percent: HIV/AIDS
|1
|HEALTH
|-
|IHMEPrevHIVNumber
|Number of cases in the population; HIV; Headcount
|HIV, Prevalence, Number
|1
|HEALTH
|-
|IHMEPrevMalariaNumber
|Number of cases in the population; Malaria, Headcount
|Malaria, Prevalence, Number
|1
|HEALTH
|-
|SocietalViolenceDeathsTotal
|Societal violence deaths total (Interpersonal+Conflict+Policeexecutions)
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonChild
|Interpersonal violence against all children death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonOther
|Death rate from Interpersonal violence for males aged over 15
|
|0
|
|-
|ViolenceInterpersonWomenAdult
|Interpersonal violence against adult women death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonWomenChild
|Deaths from interpersonal violence (Violence against vulnerable populations)
|
|0
|
|-
|ViolencePoliticalConflictTerror
|Death rate from conflict and terrorism IHME
|
|1
|SOCIOPOL
|-
|ViolencePoliticalPoliceExecution
|Death rate from police executions and conflict IHME
|
|1
|SOCIOPOL
|-
|ViolenceSelfHarm
|Death rate from self harm IHME
|
|1
|SOCIOPOL
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|Malaria
|1
|HEALTH
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|HIV/AIDS
|1
|HEALTH, POPULATION
|}

=== Tables Used in Hist+Forecast Display ===
There are 45 tables in total related to detailed death tables in IFs. For each of 15 death causes in IFs, we have a total death table and two tables by sex group. These 45 tables can be searched by using the following naming conventions IHMEDths___, IHMEDths___Females, and IHMEDths___Males, where ___ denotes the cause of death in IFs. These 15 causes are, Cardio, Diabet, Diarrh, Digest, HIV, Intlj, Malar, MalNeopl, MentHlth, OthCD, OthNCD, OthUnintlj, Respinfec, Respiratory, Roadacc. Below is the causes used for each table:

The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Note that a detailed death cause mapping table can be found [[IFs.db#HealthDetailedDeathsCtry|here]].
{| class="wikitable"
!Table
!Definition
!UsedInPreprocessor
!UsedInPreprocessorFileName
!Name in Source
|-
|IHMEDthsCardio
|Deaths from cardiovascular disease in millions from IHME for both sexes
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Deaths from cardiovascular disease in millions from IHME for females
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Deaths from cardiovascular disease in millions from IHME for males
|0
|
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Deaths from diabetes in millions from IHME for both sexes
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Deaths from diabetes in millions from IHME for females
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Deaths from diabetes in millions from IHME for males
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Deaths from diarrhoea in millions from IHME for both sexes
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Deaths from diarrhoea in millions from IHME for females
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Deaths from diarrhoea in millions from IHME for males
|0
|
|Diarrheal diseases
|-
|IHMEDthsDigest
|Deaths from digestive diseases in millions from IHME for both sexes
|0
|
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Deaths from digestive diseases in millions from IHME for females
|0
|
|Digestive diseases
|-
|IHMEDthsDigestMales
|Deaths from digestive diseases in millions from IHME for males
|0
|
|Digestive diseases
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|1
|HEALTH, POPULATION
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|Deaths from HIV in millions from IHME for females
|0
|
|HIV/AIDS
|-
|IHMEDthsHIVMales
|Deaths from HIV in millions from IHME for males
|0
|
|HIV/AIDS
|-
|IHMEDthsIntIj
|Deaths from Intentional injuries in millions from IHME for both sexes
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Deaths from Intentional injuries in millions from IHME for females
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Deaths from Intentional injuries in millions from IHME for males
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|1
|HEALTH
|Malaria
|-
|IHMEDthsMalarFemales
|Deaths from malaria in millions from IHME for females
|0
|
|Malaria
|-
|IHMEDthsMalarMales
|Deaths from malaria in millions from IHME for males
|0
|
|Malaria
|-
|IHMEDthsMalNeopl
|Deaths from cancers in millions from IHME for both sexes
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Deaths from cancers in millions from IHME for females
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Deaths from cancers in millions from IHME for males
|0
|
|Neoplasms
|-
|IHMEDthsMentHlth
|Deaths from mental health in millions from IHME for both sexes
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Deaths from mental health in millions from IHME for females
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Deaths from mental health in millions from IHME for males
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Deaths from other CD in millions from IHME for both sexes
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Deaths from other CD in millions from IHME for females
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Deaths from other CD in millions from IHME for males
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Deaths from other NCD in millions from IHME for both sexes
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Deaths from other NCD in millions from IHME for females
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Deaths from other NCD in millions from IHME for males
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Deaths from other unintentional injuries in millions from IHME for both sexes
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Deaths from other unintentional injuries in millions from IHME for females
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Deaths from other unintentional injuries in millions from IHME for males
|0
|
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Deaths from respiratory infections in millions from IHME for both sexes
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Deaths from respiratory infections in millions from IHME for females
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Deaths from respiratory infections in millions from IHME for males
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Deaths from respiratory diseases in millions from IHME for both sexes
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Deaths from respiratory diseases in millions from IHME for females
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Deaths from respiratory diseases in millions from IHME for males
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Deaths from road accidents in millions from IHME for both sexes
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Deaths from road accidents in millions from IHME for females
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Deaths from road accidents in millions from IHME for males
|0
|
|Transport injuries
|}

=== Life Expectancy ===
{| class="wikitable"
|+
!Variable
!Definition
!Years
!UsedInPreprocessor
|-
|LifeExpectIHMEBothSexesHistOnly
|Average life expectancy values from IHME GBD 2019. History only, Both Sexe, Use Age Group < 1
|1950-2019
|0
|-
|LifeExpectIHMEFemaleHistOnly
|Average life expectancy values from IHME GBD 2019. History only, Female, , Use Age Group < 1
|1950-2019
|0
|-
|LifeExpectIHMEMaleHistOnly
|Average life expectancy values from IHME GBD 2019. History only, Male, Use Age Group < 1
|1950-2019
|0
|}

=== Infant Mortality ===
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
|-
|InfMortRateIHME
|Infant Mortality Rate from IHME GBD project. Summation of mortality categories: 0-6 Days; 7-28 Days; 29-365 Days.
|Probability of death; >1 year
|0
|-
|Under5MortRateIHME
|Under 5 mortality Rate from IHME GBD Project, all causes
|Probability of death; sum of >1 years, 2-4 years
|0
|}

=== Tables in IFs.db ===

==== HealthDetailedDeathsCtry ====
Detailed instruction on pulling number of deaths for IFs death categories can be found [[IFs.db|here]].

= Data Pulling Instructions =

=== Preprocessors on Prevalence and Incidence ===
[https://github.com/shangkexin/The_Institute_for_Health_Metrics_and_Evaluation_IHME Python scripts] used from last data pull can be accessed and adjusted for future data pulls. An updated country concordance table can be found [https://1drv.ms/x/c/64a1920f95dbe644/EWHhcKUK3ldEoIgMqLc6O0QB5ylEO7D509sB2273fFWu-g?e=vbtEsa here].

Use these filters:
{| class="wikitable"
|Variable
|GBD Estimate
|Measure
|Metric
|Cause
|Location
|Age
|Sex
|Year
|Decimal Places
|-
|ViolencePoliticalConflictTerror
|Cause of death or injury
|Deaths
|Rate
|Conflict and terrorism
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolencePoliticalPoliceExecution
|Cause of death or injury
|Deaths
|Rate
|Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceSelfHarm
|Cause of death or injury
|Deaths
|Rate
|Self-harm
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|SocietalViolenceDeathsTotal
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence + Conflict and terrorism + Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceInterpersonChild
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence against all children death rate
|Select all countries and territories
|0-14
|Both
|Select all
|4
|-
|ViolenceInterpersonWomenAdult
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence
|Select all countries and territories
|>= 15
|Female
|Select all
|4
|-
|DrOpiodPrevIHME
|Cause of death or injury
|Prevalence
|Percent
|Opioid Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|DrugPrevalenceAmphetaminesIHME
|Cause of death or injury
|Prevalence
|Percent
|Amphetamine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|DrugPrevalenceCocaineIHME
|Cause of death or injury
|Prevalence
|Percent
|Cocaine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsHIV
|Cause of death or injury
|Deaths
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsMalar
|Cause of death or injury
|Deaths
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEInciHIVNumber
|Cause of death or injury
|Incidence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEInciMalariaNumber
|Cause of death or injury
|Incidence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevHIV
|Cause of death or injury
|Prevalence
|Percent
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|3
|-
|IHMEPrevHIVNumber
|Cause of death or injury
|Prevalence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevMalariaNumber
|Cause of death or injury
|Prevalence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|ViolenceInterpersonOther
|Cause of death or injury
|Deaths
|Rate
|Death rate from Interpersonal violence for males aged over 15
|Select all countries and territories
|>= 15
|Both
|Select all
|
|-
|ViolenceInterpersonWomenChild
|Cause of death or injury
|Deaths
|Rate
|Deaths from interpersonal violence (Violence against women and children)
|Select all countries and territories
|Sum of Child and WomenAdult
|Both
|Select all
|
|}

=== Tables Used in Hist+Forecast Display ===
[https://vizhub.healthdata.org/gbd-results/ Use the filters]:

GBD Estimate Cause of death or injury

Measure Deaths

Metric Rate

Location All territories and countries

Age All ages

Sex Both, Female, Male

Year All

Use the causes below:
{| class="wikitable"
!Table
!Cause
|-
|IHMEDthsCardio
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Diarrheal diseases
|-
|IHMEDthsDigest
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Digestive diseases
|-
|IHMEDthsDigestMales
|Digestive diseases
|-
|IHMEDthsHIV
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|HIV/AIDS
|-
|IHMEDthsHIVMales
|HIV/AIDS
|-
|IHMEDthsIntIj
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Malaria
|-
|IHMEDthsMalarFemales
|Malaria
|-
|IHMEDthsMalarMales
|Malaria
|-
|IHMEDthsMalNeopl
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Neoplasms
|-
|IHMEDthsMentHlth
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Transport injuries
|}

=== Life Expectancy ===
Use the filters:
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Metric Name
|Decimal Places
|-
|LifeExpectIHMEBothSexesHistOnly
|0-6 days
|Both
|1950-2021
|Years
|3
|-
|LifeExpectIHMEMaleHistOnly
|0-6 days
|Male
|1950-2021
|Years
|3
|-
|LifeExpectIHMEFemaleHistOnly
|0-6 days
|Female
|1950-2021
|Years
|3
|}

=== Infant Mortality ===
Life expectancy data can be pulled from http://ghdx.healthdata.org/gbd-results-tool. The filters should be:

GBD Estimate All-cause mortality

Measure Life Tables

Metric Years

Location All territories and countries

Age Stated below

Sex Both

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Decimal Places
|-
|InfMortRateIHME
|< 1 year
|Both
|1950-2021
|4
|-
|Under5MortRateIHME
|Calculation of < 1 year, 12-23 months, and 2-4 year
|Both
|1950-2021
|4
|}

==== CALCULATIONS: ====
In order to get the right value for Under5MortRateIHME, we have to calculate it. It should be:

PoD under 5 = PoD under 1 + PoD 12-23 months * Probability of not dying under 1+ PoD 2-4 years * Probability of not dying under 2.

An example is posted below for Iraq:
{| class="wikitable"
|<1 year
|All causes
|Probability of death
|2019
|0.019244
|-
|12-23 months
|All causes
|Probability of death
|2019
|0.001482
|-
|2-4 years
|All causes
|Probability of death
|2019
|0.002298
|}

The PoD for under 2 would be = 0.019244 + 0.001482 * ( 1 - 0.019244) = 0.020698;

The PoD for under 5 would be = 0.020698 + 0.002298 * ( 1 - 0.020698) = 0.022948.

The final data point is '''0.022948'''.

= Data Notes =

* ViolenceInterpersonChild & ViolenceInterpersonWomenAdult have changed a lot, we identify the Age by comparing the trend of old data in IFsHistSeries and the new data from GBD.
** In March 2025, the ages have shifted from >20 for adults to >15. To get this data, do a summation of 15-19 and 20+

* Be aware of the definition of each preprocessor and its unit so that you can find the exact match in the IHME GBD variables.
* Some regions in IFs are not provided by IHME yet, we are encouraged to use proxies. For example, use Singapore, Albania, and Mali for Hong Kong, Kosovo, and Sahrawi respectively. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally.
** To do this use SeriesPopulation. For instance, Kosovo’s number of deaths = Albania’s number of deaths * Kosovo’s Population / Albania’s Population.

Global Burdens of Disease (GBD), Institute for Health Metrics and Evaluation (IHME)

2026-01-09T17:12:54Z

Norah.Shamin:

= Summary =
The Institute for Health Metrics and Evaluation (IHME) provides data on the Global Burdens of Disease that can be accessed here http://ghdx.healthdata.org/gbd-results-tool. IHME provides data on multiple metrics that we pull into IFs, including deaths, DALYs, incidence, prevalence, violence and forecasts for each. The latest IFs data update for this series was in March 2025, covering 188 economies over the years 198/90-2021. There have been major changes in this update which will be noted below.

= Table In IFs =

=== Preprocessors on Prevalence and Incidence ===
The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series.
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|DrOpiodPrevIHME
|Opiod Prevalence Rate
|Prevalence; Percent: Opioid use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceAmphetaminesIHME
|Drug prevalence rate, Amphetamines
|Prevalence; Percent: Amphetamine use disorders
|1
|SOCIOPOL
|-
|DrugPrevalenceCocaineIHME
|Drug prevalence rate, Cocaine
|Prevalence; Percent: Cocaine use disorders
|1
|SOCIOPOL
|-
|IHMEInciHIVNumber
|Number of new cases of HIV in the population per year
|HIV, Incidence, Number
|1
|HEALTH
|-
|IHMEInciMalariaNumber
|Number of new cases of Malaria in the population per year
|Malaria, Incidence, Number
|1
|HEALTH
|-
|IHMEPrevHIV
|HIV Prevalence Rate
|Prevalence; Percent: HIV/AIDS
|1
|HEALTH
|-
|IHMEPrevHIVNumber
|Number of cases in the population; HIV; Headcount
|HIV, Prevalence, Number
|1
|HEALTH
|-
|IHMEPrevMalariaNumber
|Number of cases in the population; Malaria, Headcount
|Malaria, Prevalence, Number
|1
|HEALTH
|-
|SocietalViolenceDeathsTotal
|Societal violence deaths total (Interpersonal+Conflict+Policeexecutions)
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonChild
|Interpersonal violence against all children death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonOther
|Death rate from Interpersonal violence for males aged over 15
|
|0
|
|-
|ViolenceInterpersonWomenAdult
|Interpersonal violence against adult women death rate
|
|1
|SOCIOPOL
|-
|ViolenceInterpersonWomenChild
|Deaths from interpersonal violence (Violence against vulnerable populations)
|
|0
|
|-
|ViolencePoliticalConflictTerror
|Death rate from conflict and terrorism IHME
|
|1
|SOCIOPOL
|-
|ViolencePoliticalPoliceExecution
|Death rate from police executions and conflict IHME
|
|1
|SOCIOPOL
|-
|ViolenceSelfHarm
|Death rate from self harm IHME
|
|1
|SOCIOPOL
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|Malaria
|1
|HEALTH
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|HIV/AIDS
|1
|HEALTH, POPULATION
|}

=== Tables Used in Hist+Forecast Display ===
There are 45 tables in total related to detailed death tables in IFs. For each of 15 death causes in IFs, we have a total death table and two tables by sex group. These 45 tables can be searched by using the following naming conventions IHMEDths___, IHMEDths___Females, and IHMEDths___Males, where ___ denotes the cause of death in IFs. These 15 causes are, Cardio, Diabet, Diarrh, Digest, HIV, Intlj, Malar, MalNeopl, MentHlth, OthCD, OthNCD, OthUnintlj, Respinfec, Respiratory, Roadacc. Below is the causes used for each table:

The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Note that a detailed death cause mapping table can be found [[IFs.db#HealthDetailedDeathsCtry|here]].
{| class="wikitable"
!Table
!Definition
!UsedInPreprocessor
!UsedInPreprocessorFileName
!Name in Source
|-
|IHMEDthsCardio
|Deaths from cardiovascular disease in millions from IHME for both sexes
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Deaths from cardiovascular disease in millions from IHME for females
|0
|
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Deaths from cardiovascular disease in millions from IHME for males
|0
|
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Deaths from diabetes in millions from IHME for both sexes
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Deaths from diabetes in millions from IHME for females
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Deaths from diabetes in millions from IHME for males
|0
|
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Deaths from diarrhoea in millions from IHME for both sexes
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Deaths from diarrhoea in millions from IHME for females
|0
|
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Deaths from diarrhoea in millions from IHME for males
|0
|
|Diarrheal diseases
|-
|IHMEDthsDigest
|Deaths from digestive diseases in millions from IHME for both sexes
|0
|
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Deaths from digestive diseases in millions from IHME for females
|0
|
|Digestive diseases
|-
|IHMEDthsDigestMales
|Deaths from digestive diseases in millions from IHME for males
|0
|
|Digestive diseases
|-
|IHMEDthsHIV
|Deaths from HIV in millions from IHME for both sexes
|1
|HEALTH, POPULATION
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|Deaths from HIV in millions from IHME for females
|0
|
|HIV/AIDS
|-
|IHMEDthsHIVMales
|Deaths from HIV in millions from IHME for males
|0
|
|HIV/AIDS
|-
|IHMEDthsIntIj
|Deaths from Intentional injuries in millions from IHME for both sexes
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Deaths from Intentional injuries in millions from IHME for females
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Deaths from Intentional injuries in millions from IHME for males
|0
|
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Deaths from malaria in millions from IHME for both sexes
|1
|HEALTH
|Malaria
|-
|IHMEDthsMalarFemales
|Deaths from malaria in millions from IHME for females
|0
|
|Malaria
|-
|IHMEDthsMalarMales
|Deaths from malaria in millions from IHME for males
|0
|
|Malaria
|-
|IHMEDthsMalNeopl
|Deaths from cancers in millions from IHME for both sexes
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Deaths from cancers in millions from IHME for females
|0
|
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Deaths from cancers in millions from IHME for males
|0
|
|Neoplasms
|-
|IHMEDthsMentHlth
|Deaths from mental health in millions from IHME for both sexes
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Deaths from mental health in millions from IHME for females
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Deaths from mental health in millions from IHME for males
|0
|
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Deaths from other CD in millions from IHME for both sexes
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Deaths from other CD in millions from IHME for females
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Deaths from other CD in millions from IHME for males
|0
|
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Deaths from other NCD in millions from IHME for both sexes
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Deaths from other NCD in millions from IHME for females
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Deaths from other NCD in millions from IHME for males
|0
|
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Deaths from other unintentional injuries in millions from IHME for both sexes
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Deaths from other unintentional injuries in millions from IHME for females
|0
|
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Deaths from other unintentional injuries in millions from IHME for males
|0
|
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Deaths from respiratory infections in millions from IHME for both sexes
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Deaths from respiratory infections in millions from IHME for females
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Deaths from respiratory infections in millions from IHME for males
|0
|
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Deaths from respiratory diseases in millions from IHME for both sexes
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Deaths from respiratory diseases in millions from IHME for females
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Deaths from respiratory diseases in millions from IHME for males
|0
|
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Deaths from road accidents in millions from IHME for both sexes
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Deaths from road accidents in millions from IHME for females
|0
|
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Deaths from road accidents in millions from IHME for males
|0
|
|Transport injuries
|}

=== Life Expectancy ===
{| class="wikitable"
|+
!Variable
!Definition
!Years
!UsedInPreprocessor
|-
|LifeExpectIHMEBothSexesHistOnly
|Average life expectancy values from IHME GBD 2019. History only, Both Sexe, Use Age Group < 1
|1950-2019
|0
|-
|LifeExpectIHMEFemaleHistOnly
|Average life expectancy values from IHME GBD 2019. History only, Female, , Use Age Group < 1
|1950-2019
|0
|-
|LifeExpectIHMEMaleHistOnly
|Average life expectancy values from IHME GBD 2019. History only, Male, Use Age Group < 1
|1950-2019
|0
|}

=== Infant Mortality ===
{| class="wikitable"
|+
!Variable
!Definition
!Name in Source
!UsedInPreprocessor
|-
|InfMortRateIHME
|Infant Mortality Rate from IHME GBD project. Summation of mortality categories: 0-6 Days; 7-28 Days; 29-365 Days.
|Probability of death; >1 year
|0
|-
|Under5MortRateIHME
|Under 5 mortality Rate from IHME GBD Project, all causes
|Probability of death; sum of >1 years, 2-4 years
|0
|}

=== Tables in IFs.db ===

==== HealthDetailedDeathsCtry ====
Detailed instruction on pulling number of deaths for IFs death categories can be found [[IFs.db|here]].

= Data Pulling Instructions =

=== Preprocessors on Prevalence and Incidence ===
[https://github.com/shangkexin/The_Institute_for_Health_Metrics_and_Evaluation_IHME Python scripts] used from last data pull can be accessed and adjusted for future data pulls. An updated country concordance table can be found [https://1drv.ms/x/c/64a1920f95dbe644/EWHhcKUK3ldEoIgMqLc6O0QB5ylEO7D509sB2273fFWu-g?e=vbtEsa here].

Use these filters:
{| class="wikitable"
|Variable
|GBD Estimate
|Measure
|Metric
|Cause
|Location
|Age
|Sex
|Year
|Decimal Places
|-
|ViolencePoliticalConflictTerror
|Cause of death or injury
|Deaths
|Rate
|Conflict and terrorism
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolencePoliticalPoliceExecution
|Cause of death or injury
|Deaths
|Rate
|Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceSelfHarm
|Cause of death or injury
|Deaths
|Rate
|Self-harm
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|SocietalViolenceDeathsTotal
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence + Conflict and terrorism + Executions and police conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceInterpersonChild
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence against all children death rate
|Select all countries and territories
|0-14
|Both
|Select all
|4
|-
|ViolenceInterpersonWomenAdult
|Cause of death or injury
|Deaths
|Rate
|Interpersonal violence
|Select all countries and territories
|>= 15
|Female
|Select all
|4
|-
|DrOpiodPrevIHME
|Cause of death or injury
|Prevalence
|Percent
|Opioid Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|DrugPrevalenceAmphetaminesIHME
|Cause of death or injury
|Prevalence
|Percent
|Amphetamine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|DrugPrevalenceCocaineIHME
|Cause of death or injury
|Prevalence
|Percent
|Cocaine Use Disorders
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsHIV
|Cause of death or injury
|Deaths
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsMalar
|Cause of death or injury
|Deaths
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEInciHIVNumber
|Cause of death or injury
|Incidence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEInciMalariaNumber
|Cause of death or injury
|Incidence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevHIV
|Cause of death or injury
|Prevalence
|Percent
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|3
|-
|IHMEPrevHIVNumber
|Cause of death or injury
|Prevalence
|Number
|HIV/AIDs
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevMalariaNumber
|Cause of death or injury
|Prevalence
|Number
|Malaria
|Select all countries and territories
|All Ages
|Both
|Select all
|
|-
|ViolenceInterpersonOther
|Cause of death or injury
|Deaths
|Rate
|Death rate from Interpersonal violence for males aged over 15
|Select all countries and territories
|>= 15
|Both
|Select all
|
|-
|ViolenceInterpersonWomenChild
|Cause of death or injury
|Deaths
|Rate
|Deaths from interpersonal violence (Violence against women and children)
|Select all countries and territories
|Sum of Child and WomenAdult
|Both
|Select all
|
|}

=== Tables Used in Hist+Forecast Display ===
[https://vizhub.healthdata.org/gbd-results/ Use the filters]:

GBD Estimate Cause of death or injury

Measure Deaths

Metric Rate

Location All territories and countries

Age All ages

Sex Both, Female, Male

Year All

Use the causes below:
{| class="wikitable"
!Table
!Cause
|-
|IHMEDthsCardio
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Diarrheal diseases
|-
|IHMEDthsDigest
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Digestive diseases
|-
|IHMEDthsDigestMales
|Digestive diseases
|-
|IHMEDthsHIV
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|HIV/AIDS
|-
|IHMEDthsHIVMales
|HIV/AIDS
|-
|IHMEDthsIntIj
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Malaria
|-
|IHMEDthsMalarFemales
|Malaria
|-
|IHMEDthsMalarMales
|Malaria
|-
|IHMEDthsMalNeopl
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Neoplasms
|-
|IHMEDthsMentHlth
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthCDMales
|Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCD
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Transport injuries
|}

=== Life Expectancy ===
Use the filters:
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Metric Name
|Decimal Places
|-
|LifeExpectIHMEBothSexesHistOnly
|<1
|Both
|1950-2021
|Years
|3
|-
|LifeExpectIHMEMaleHistOnly
|<1
|Male
|1950-2021
|Years
|3
|-
|LifeExpectIHMEFemaleHistOnly
|<1
|Female
|1950-2021
|Years
|3
|}

=== Infant Mortality ===
Life expectancy data can be pulled from http://ghdx.healthdata.org/gbd-results-tool. The filters should be:

GBD Estimate All-cause mortality

Measure Life Tables

Metric Years

Location All territories and countries

Age Stated below

Sex Both

Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Decimal Places
|-
|InfMortRateIHME
|< 1 year
|Both
|1950-2021
|4
|-
|Under5MortRateIHME
|Calculation of < 1 year, 12-23 months, and 2-4 year
|Both
|1950-2021
|4
|}

==== CALCULATIONS: ====
In order to get the right value for Under5MortRateIHME, we have to calculate it. It should be:

PoD under 5 = PoD under 1 + PoD 12-23 months * Probability of not dying under 1+ PoD 2-4 years * Probability of not dying under 2.

An example is posted below for Iraq:
{| class="wikitable"
|<1 year
|All causes
|Probability of death
|2019
|0.019244
|-
|12-23 months
|All causes
|Probability of death
|2019
|0.001482
|-
|2-4 years
|All causes
|Probability of death
|2019
|0.002298
|}

The PoD for under 2 would be = 0.019244 + 0.001482 * ( 1 - 0.019244) = 0.020698;

The PoD for under 5 would be = 0.020698 + 0.002298 * ( 1 - 0.020698) = 0.022948.

The final data point is '''0.022948'''.

= Data Notes =

* ViolenceInterpersonChild & ViolenceInterpersonWomenAdult have changed a lot, we identify the Age by comparing the trend of old data in IFsHistSeries and the new data from GBD.
** In March 2025, the ages have shifted from >20 for adults to >15. To get this data, do a summation of 15-19 and 20+

* Be aware of the definition of each preprocessor and its unit so that you can find the exact match in the IHME GBD variables.
* Some regions in IFs are not provided by IHME yet, we are encouraged to use proxies. For example, use Singapore, Albania, and Mali for Hong Kong, Kosovo, and Sahrawi respectively. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally.
** To do this use SeriesPopulation. For instance, Kosovo’s number of deaths = Albania’s number of deaths * Kosovo’s Population / Albania’s Population.

Institute for Statistics, UNESCO (UIS)

2026-01-07T00:36:02Z

Norah.Shamin:

Balance of Payments and International Investment Position statistics (BoP/IIP), IMF

2026-01-02T22:03:51Z

Norah.Shamin:

= Summary =
The Balance of Payments (BoP) provides a framework that is applicable for a range of economies, from the smallest and least developed economies to the more advanced and complex economies. As a result, it is recognized that some items may not be relevant in all cases.

The IMF data on balance of payments and international investment positions is available here- http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1409773422141

The data is prepared in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual. The handbook can be accessed here, http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1390288795525

BoP data is available for approximately 204 economies, while IIP data is available for approximately 143 economies. Data is available for most countries from the year 1945.<ref>Refer About BoP/IIP Geographic,temporal coverage <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&sid=1409773422141&ss=1409773411929></ref>

=== Definitions ===
'''BoP '''is a flow while '''IIP''' is a stock. Although the balance of payments accounts are, in principle, balanced, imbalances result in practice from imperfections in source data and compilation. This imbalance, a usual feature of balance of payments data, is labeled net errors and omissions and is identified separately in published data. It should not be included indistinguishably in other items. Net errors and omissions are derived residually as net lending/net borrowing and can be derived from the financial account minus the same item derived from the current and capital accounts.<ref>Refer to “Balance of Payments and International Investment Positions Manual Version 6.”</ref>

The BoP is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Under the double-entry accounting system that underlines the balance of payments, each transaction is recorded as consisting of two entries and the sum of the credit entries and the sum of the debit entries is the same. The different accounts within the BoP are distinguished according to the nature of the economic resources provided and received.”<ref>See the BoP “about” sheet <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52></ref>

The International Investment Position (IIP) is a statistical statement that shows at a point in time the value of:

Financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents. The difference between the assets and the liabilities is the net position in the IIP and represents either a net claim on or a net liability to the rest of the world. The IIP represents a subset of the assets and liabilities included in the national balance sheet. In addition to the IIP, the national balance sheet incorporates nonfinancial assets as well as financial assets and liabilities positions between residents.

= Tables In IFs =
{| class="wikitable"
!Table
!Definition
!Indicator Name/Name in Source
!Indicator Code
!Formula
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|NetIIP%GDP
|Net International Investment Position as a percent of GDP.
|Net (assets less liabilities); Net International Investment Position, Adjusted using IMF accounting records
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XIncSecPayments%GDP
|Secondary Income payments as % of GDP
|Debit/Expenditure; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XIncSecReceipts%GDP
|Secondary Income receipts as % of GDP
|Credit/Revenue; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XWorkerCompenPaid%GDP
|Worker compensation paid as % of GDP
|Debit/Expenditure; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerCompenReceived%GDP
|Worker compensation received as % of GDP
|Credit/Revenue; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferPaid%GDP
|Worker transfer paid as % of GDP
|Debit/Expenditure; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferReceived%GDP
|Worker transfer received as % of GDP
|Credit/Revenue; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|ExMaintRepair%Ser
|Maintenance and Repair Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Maintenance and repair services n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExManuSer%Ser
|Manufacturing Services on Physical Inputs Owned by Others exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Manufacturing services on physical inputs owned by others
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherBusiness%Ser
|Other Business Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other business services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherConstruction%Ser
|Other Construction Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Construction
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherCulRecreation%Ser
|Personal, Cultural, and Recreational Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Personal, cultural, and recreational services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherFinancial%Ser
|Other Financial Services Exports percentage of Total Service exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Financial services explicitly charged and other financial services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherGovGoodSer%Ser
|Government Goods and Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Government goods and services n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherInsurPen%Ser
|Insurance and Pension Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Insurance and pension services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherIntellectual%Ser
|Charges for the Use of Intellectual Property nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Charges for the use of intellectual property n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherTelCom%Ser
|Other Telecommunication Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Telecommunications, computer, and information services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportFreight%Ser
|Freight Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary FundFreight Transport Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; freight
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportOther%Ser
|Other Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other modes of transport
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportPass%Ser
|Passenger Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; passenger
|
|%'Credit/Revenue; Services'
|0
|
|-
|ImOtherInsurPen%Ser
|The percentage of total service imports on the balance of payments attributed to services such as insurance and pension
|Debit/Expenditure; Insurance and pension services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherIntellectual%Ser
|The percentage of total service imports on the balance of payments attributed to charges for the use of intellectual property
|Debit/Expenditure; Charges for the use of intellectual property n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherTelCom%Ser
|The percentage of total service imports on the balance of payments attributed to telecommunications, computer and information services
|Debit/Expenditure; Telecommunications, computer, and information services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportFreight%Ser
|The percentage of total service imports on the balance of payments attributed to freight transport
|Debit/Expenditure; All modes of transport; freight
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportOther%Ser
|The percentage of total service imports on the balance of payments attributed to postal and courier transport etc.
|Debit/Expenditure; All modes of transport; other than passenger and freight; including postal and courier services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportPass%Ser
|The percentage of total service imports on the balance of payments attributed to the transport of passengers
|Debit/Expenditure; All modes of transport; passenger
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTravelBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business travel
|Debit/Expenditure; Travel; business
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTravelPersonal%Ser
|The percentage of total service imports on the balance of payments attributed to personal travel
|Debit/Expenditure; Travel; personal
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ExTravelBusiness%Ser
|Business Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; business
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTravelPersonal%Ser
|Personal Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; personal
|
|%'Credit/Revenue; Services'
|0
|
|-
|ImMaintRepair%Ser
|The percentage of total service imports on the balance of payments attributed to maintenance and repair services
|Debit/Expenditure; Maintenance and repair services n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImManuSer%Ser
|The percentage of total service imports on the balance of payments attributed to manufacturing services on physical inputs owned by others
|Debit/Expenditure; Manufacturing services on physical inputs owned by others
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business services
|Debit/Expenditure; Other business services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherConstruction%Ser
|The percentage of total service imports on the balance of payments attributed to construction
|Debit/Expenditure; Construction
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherCulRecreation%Ser
|The percentage of total service imports on the balance of payments attributed to personal, cultural, and recreational services
|Debit/Expenditure; Personal, cultural, and recreational services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherFinancial%Ser
|The percentage of total service imports on the balance of payments attributed to financial services
|Debit/Expenditure; Financial services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherGovGoodSer%Ser
|The percentage of total service imports on the balance of payments attributed to government goods and services
|Debit/Expenditure; Government goods and services n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|}

= Data Pulling Instructions =
1. Go to https://data.imf.org/en/datasets/IMF.STA:BOP

2. Click on "Download". Choose the type of file, formatting and metadata. If you would like to use a script found [https://github.com/n1shamin/IMF-BoP-IIP here] download as a '''csv''' and '''observation per row''' file. If you would like to view the data click "View Data"
[[File:IMF BoP Download Page.png|none|thumb|600x600px]]

4. Navigate to this [https://github.com/n1shamin/IMF-BoP-IIP GitHub Repo] and follow instructions to pull the table. Make sure that you check the country concordance and units.

5. If you chose "View Data" ensure that you use the right filters (see below):
[[File:IMF BoP Filters.png|none|thumb|622x622px]]
Choose all countries, Debit/Revenue and Credit/Expenditure, US Dollars, Annual for Frequency, All for Time Period, and then choose the indicators listed in the tables. Then click "Download"

6. Download the GDP data from: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD. Utilize the script to do the calculations.

==== Directions for NetIIP%GDP ====
1. For this table navigate to: https://data.imf.org/Datasets/IIP

2. Click on "Download". Choose the type of file, formatting and metadata. If you would like to use a script found [https://github.com/n1shamin/IMF-BoP-IIP here] download as a '''csv''' and '''observation per row''' file. If you would like to view the data click "View Data"
[[File:IMF BoP Download Page.png|none|thumb|600x600px]]
3. If you chose "View Data" ensure that you follow the filters below. Choose all countries, all years, US Dollars, annual for frequency, and Net International Investment Position, Adjusted using IMF accounting records for the indicator.
[[File:IMF IIP Filters.png|none|thumb|600x600px]]
4. Click "Download"

= Data Notes =

=== Calculations ===
The formula for XWorkerTransferReceived%GDP, XWorkerTransferPaid%GDP, XWorkerCompenPaid%GDP, and XWorkerCompenReceived%GDP from /GDP Current USD (NY.GDP.MKTP.CD to %'NY.GDP.MKTP.CD'. NY.GDP.MKTP.CD are GDP figures in World Bank. They can be found [https://databank.worldbank.org/metadataglossary/africa-development-indicators/series/NY.GDP.MKTP.CD.XD here] .

To complete the calculations: multiply by 1,000,000 to get the same units between IMF and World Bank since IMF unit Millions of U.S. Dollars, divide the sheets from IMF BoP by the GDP figures (NY.GDP.MKTP.CD), then multiple by 100 for the percentage value.

For example, for XWorkerTransferReceived%GDP Algeria 1977 the value is 349.1884 and for the same year the GDP Current USD is 20972113685.

349.1884 x 1,000,000= 349188400

349188400/20972113685 = 0.0166501291 x 100 = 1.665.

For the %Ser tables, you must divide the indicator listed by Services data (Services must align with the indicator; if the indicator is from Credit/Revenue, the services data must as well). The same process is followed as seen above. Take the indicator value divide it by Services and multiply it by 100.

= References =
<references />

Balance of Payments and International Investment Position statistics (BoP/IIP), IMF

2026-01-02T22:00:22Z

Norah.Shamin:

= Summary =
The Balance of Payments (BoP) provides a framework that is applicable for a range of economies, from the smallest and least developed economies to the more advanced and complex economies. As a result, it is recognized that some items may not be relevant in all cases.

The IMF data on balance of payments and international investment positions is available here- http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1409773422141

The data is prepared in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual. The handbook can be accessed here, http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1390288795525

BoP data is available for approximately 204 economies, while IIP data is available for approximately 143 economies. Data is available for most countries from the year 1945.<ref>Refer About BoP/IIP Geographic,temporal coverage <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&sid=1409773422141&ss=1409773411929></ref>

=== Definitions ===
'''BoP '''is a flow while '''IIP''' is a stock. Although the balance of payments accounts are, in principle, balanced, imbalances result in practice from imperfections in source data and compilation. This imbalance, a usual feature of balance of payments data, is labeled net errors and omissions and is identified separately in published data. It should not be included indistinguishably in other items. Net errors and omissions are derived residually as net lending/net borrowing and can be derived from the financial account minus the same item derived from the current and capital accounts.<ref>Refer to “Balance of Payments and International Investment Positions Manual Version 6.”</ref>

The BoP is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Under the double-entry accounting system that underlines the balance of payments, each transaction is recorded as consisting of two entries and the sum of the credit entries and the sum of the debit entries is the same. The different accounts within the BoP are distinguished according to the nature of the economic resources provided and received.”<ref>See the BoP “about” sheet <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52></ref>

The International Investment Position (IIP) is a statistical statement that shows at a point in time the value of:

Financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents. The difference between the assets and the liabilities is the net position in the IIP and represents either a net claim on or a net liability to the rest of the world. The IIP represents a subset of the assets and liabilities included in the national balance sheet. In addition to the IIP, the national balance sheet incorporates nonfinancial assets as well as financial assets and liabilities positions between residents.

= Tables In IFs =
{| class="wikitable"
!Table
!Definition
!Indicator Name/Name in Source
!Indicator Code
!Formula
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|NetIIP%GDP
|Net International Investment Position as a percent of GDP.
|Net (assets less liabilities); Net International Investment Position, Adjusted using IMF accounting records
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XIncSecPayments%GDP
|Secondary Income payments as % of GDP
|Debit/Expenditure; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XIncSecReceipts%GDP
|Secondary Income receipts as % of GDP
|Credit/Revenue; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XWorkerCompenPaid%GDP
|Worker compensation paid as % of GDP
|Debit/Expenditure; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerCompenReceived%GDP
|Worker compensation received as % of GDP
|Credit/Revenue; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferPaid%GDP
|Worker transfer paid as % of GDP
|Debit/Expenditure; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferReceived%GDP
|Worker transfer received as % of GDP
|Credit/Revenue; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|ExMaintRepair%Ser
|Maintenance and Repair Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Maintenance and repair services n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExManuSer%Ser
|Manufacturing Services on Physical Inputs Owned by Others exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Manufacturing services on physical inputs owned by others
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherBusiness%Ser
|Other Business Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other business services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherConstruction%Ser
|Other Construction Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Construction
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherCulRecreation%Ser
|Personal, Cultural, and Recreational Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Personal, cultural, and recreational services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherFinancial%Ser
|Other Financial Services Exports percentage of Total Service exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Financial services explicitly charged and other financial services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherGovGoodSer%Ser
|Government Goods and Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Government goods and services n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherInsurPen%Ser
|Insurance and Pension Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Insurance and pension services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherIntellectual%Ser
|Charges for the Use of Intellectual Property nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Charges for the use of intellectual property n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherTelCom%Ser
|Other Telecommunication Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Telecommunications, computer, and information services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportFreight%Ser
|Freight Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary FundFreight Transport Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; freight
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportOther%Ser
|Other Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other modes of transport
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportPass%Ser
|Passenger Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; passenger
|
|%'Credit/Revenue; Services'
|0
|
|-
|ImOtherInsurPen%Ser
|The percentage of total service imports on the balance of payments attributed to services such as insurance and pension
|Debit/Expenditure; Insurance and pension services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherIntellectual%Ser
|The percentage of total service imports on the balance of payments attributed to charges for the use of intellectual property
|Debit/Expenditure; Charges for the use of intellectual property n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherTelCom%Ser
|The percentage of total service imports on the balance of payments attributed to telecommunications, computer and information services
|Debit/Expenditure; Telecommunications, computer, and information services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportFreight%Ser
|The percentage of total service imports on the balance of payments attributed to freight transport
|Debit/Expenditure; All modes of transport; freight
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportOther%Ser
|The percentage of total service imports on the balance of payments attributed to postal and courier transport etc.
|Debit/Expenditure; All modes of transport; other than passenger and freight; including postal and courier services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportPass%Ser
|The percentage of total service imports on the balance of payments attributed to the transport of passengers
|Debit/Expenditure; All modes of transport; passenger
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTravelBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business travel
|Debit/Expenditure; Travel; business
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTravelPersonal%Ser
|The percentage of total service imports on the balance of payments attributed to personal travel
|Debit/Expenditure; Travel; personal
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ExTravelBusiness%Ser
|Business Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; business
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTravelPersonal%Ser
|Personal Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; personal
|
|%'Credit/Revenue; Services'
|0
|
|-
|ImMaintRepair%Ser
|The percentage of total service imports on the balance of payments attributed to maintenance and repair services
|Debit/Expenditure; Maintenance and repair services n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImManuSer%Ser
|The percentage of total service imports on the balance of payments attributed to manufacturing services on physical inputs owned by others
|Debit/Expenditure; Manufacturing services on physical inputs owned by others
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business services
|Debit/Expenditure; Other business services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherConstruction%Ser
|The percentage of total service imports on the balance of payments attributed to construction
|Debit/Expenditure; Construction
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherCulRecreation%Ser
|The percentage of total service imports on the balance of payments attributed to personal, cultural, and recreational services
|Debit/Expenditure; Personal, cultural, and recreational services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherFinancial%Ser
|The percentage of total service imports on the balance of payments attributed to financial services
|Debit/Expenditure; Financial services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherGovGoodSer%Ser
|The percentage of total service imports on the balance of payments attributed to government goods and services
|Debit/Expenditure; Government goods and services n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|}

= Data Pulling Instructions =
1. Go to https://data.imf.org/en/datasets/IMF.STA:BOP

2. Click on "Download". Choose the type of file, formatting and metadata. If you would like to use a script found [https://github.com/n1shamin/IMF-BoP-IIP here] download as a '''csv''' and '''observation per row''' file. If you would like to view the data click "View Data"
[[File:IMF BoP Download Page.png|none|thumb|600x600px]]

4. Navigate to this [https://github.com/n1shamin/IMF-BoP-IIP GitHub Repo] and follow instructions to pull the table. Make sure that you check the country concordance and units.

5. If you chose "View Data" ensure that you use the right filters (see below):
[[File:IMF BoP Filters.png|none|thumb|622x622px]]
Choose all countries, Debit/Revenue and Credit/Expenditure, US Dollars, Annual for Frequency, All for Time Period, and then choose the indicators listed in the tables. Then click "Download"

==== Directions for NetIIP%GDP ====
1. For this table navigate to: https://data.imf.org/Datasets/IIP

2. Click on "Download". Choose the type of file, formatting and metadata. If you would like to use a script found [https://github.com/n1shamin/IMF-BoP-IIP here] download as a '''csv''' and '''observation per row''' file. If you would like to view the data click "View Data"
[[File:IMF BoP Download Page.png|none|thumb|600x600px]]
3. If you chose "View Data" ensure that you follow the filters below. Choose all countries, all years, US Dollars, annual for frequency, and Net International Investment Position, Adjusted using IMF accounting records for the indicator.
[[File:IMF IIP Filters.png|none|thumb|600x600px]]
4. Click "Download"

= Data Notes =

=== Calculations ===
The formula for XWorkerTransferReceived%GDP, XWorkerTransferPaid%GDP, XWorkerCompenPaid%GDP, and XWorkerCompenReceived%GDP from /GDP Current USD (NY.GDP.MKTP.CD to %'NY.GDP.MKTP.CD'. NY.GDP.MKTP.CD are GDP figures in World Bank. They can be found [https://databank.worldbank.org/metadataglossary/africa-development-indicators/series/NY.GDP.MKTP.CD.XD here] .

To complete the calculations: multiply by 1,000,000 to get the same units between IMF and World Bank since IMF unit Millions of U.S. Dollars, divide the sheets from IMF BoP by the GDP figures (NY.GDP.MKTP.CD), then multiple by 100 for the percentage value.

For example, for XWorkerTransferReceived%GDP Algeria 1977 the value is 349.1884 and for the same year the GDP Current USD is 20972113685.

349.1884 x 1,000,000= 349188400

349188400/20972113685 = 0.0166501291 x 100 = 1.665.

For the %Ser tables, you must divide the indicator listed by Services data (Services must align with the indicator; if the indicator is from Credit/Revenue, the services data must as well). The same process is followed as seen above. Take the indicator value divide it by Services and multiply it by 100.

= References =
<references />

Balance of Payments and International Investment Position statistics (BoP/IIP), IMF

2026-01-02T21:55:57Z

Norah.Shamin: /* Tables In IFs */

= Summary =
The Balance of Payments (BoP) provides a framework that is applicable for a range of economies, from the smallest and least developed economies to the more advanced and complex economies. As a result, it is recognized that some items may not be relevant in all cases.

The IMF data on balance of payments and international investment positions is available here- http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1409773422141

The data is prepared in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual. The handbook can be accessed here, http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1390288795525

BoP data is available for approximately 204 economies, while IIP data is available for approximately 143 economies. Data is available for most countries from the year 1945.<ref>Refer About BoP/IIP Geographic,temporal coverage <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&sid=1409773422141&ss=1409773411929></ref>

=== Definitions ===
'''BoP '''is a flow while '''IIP''' is a stock. Although the balance of payments accounts are, in principle, balanced, imbalances result in practice from imperfections in source data and compilation. This imbalance, a usual feature of balance of payments data, is labeled net errors and omissions and is identified separately in published data. It should not be included indistinguishably in other items. Net errors and omissions are derived residually as net lending/net borrowing and can be derived from the financial account minus the same item derived from the current and capital accounts.<ref>Refer to “Balance of Payments and International Investment Positions Manual Version 6.”</ref>

The BoP is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Under the double-entry accounting system that underlines the balance of payments, each transaction is recorded as consisting of two entries and the sum of the credit entries and the sum of the debit entries is the same. The different accounts within the BoP are distinguished according to the nature of the economic resources provided and received.”<ref>See the BoP “about” sheet <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52></ref>

The International Investment Position (IIP) is a statistical statement that shows at a point in time the value of:

Financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents. The difference between the assets and the liabilities is the net position in the IIP and represents either a net claim on or a net liability to the rest of the world. The IIP represents a subset of the assets and liabilities included in the national balance sheet. In addition to the IIP, the national balance sheet incorporates nonfinancial assets as well as financial assets and liabilities positions between residents.

= Tables In IFs =
{| class="wikitable"
!Table
!Definition
!Indicator Name/Name in Source
!Indicator Code
!Formula
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|NetIIP%GDP
|Net International Investment Position as a percent of GDP.
|Net (assets less liabilities); Net International Investment Position, Adjusted using IMF accounting records
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XIncSecPayments%GDP
|Secondary Income payments as % of GDP
|Debit/Expenditure; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XIncSecReceipts%GDP
|Secondary Income receipts as % of GDP
|Credit/Revenue; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XWorkerCompenPaid%GDP
|Worker compensation paid as % of GDP
|Debit/Expenditure; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerCompenReceived%GDP
|Worker compensation received as % of GDP
|Credit/Revenue; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferPaid%GDP
|Worker transfer paid as % of GDP
|Debit/Expenditure; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferReceived%GDP
|Worker transfer received as % of GDP
|Credit/Revenue; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|ExMaintRepair%Ser
|Maintenance and Repair Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Maintenance and repair services n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExManuSer%Ser
|Manufacturing Services on Physical Inputs Owned by Others exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Manufacturing services on physical inputs owned by others
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherBusiness%Ser
|Other Business Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other business services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherConstruction%Ser
|Other Construction Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Construction
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherCulRecreation%Ser
|Personal, Cultural, and Recreational Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Personal, cultural, and recreational services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherFinancial%Ser
|Other Financial Services Exports percentage of Total Service exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Financial services explicitly charged and other financial services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherGovGoodSer%Ser
|Government Goods and Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Government goods and services n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherInsurPen%Ser
|Insurance and Pension Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Insurance and pension services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherIntellectual%Ser
|Charges for the Use of Intellectual Property nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Charges for the use of intellectual property n.i.e.
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExOtherTelCom%Ser
|Other Telecommunication Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Telecommunications, computer, and information services
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportFreight%Ser
|Freight Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary FundFreight Transport Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; freight
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportOther%Ser
|Other Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other modes of transport
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTransportPass%Ser
|Passenger Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; passenger
|
|%'Credit/Revenue; Services'
|0
|
|-
|ImOtherInsurPen%Ser
|The percentage of total service imports on the balance of payments attributed to services such as insurance and pension
|Debit/Expenditure; Insurance and pension services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherIntellectual%Ser
|The percentage of total service imports on the balance of payments attributed to charges for the use of intellectual property
|Debit/Expenditure; Charges for the use of intellectual property n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherTelCom%Ser
|The percentage of total service imports on the balance of payments attributed to telecommunications, computer and information services
|Debit/Expenditure; Telecommunications, computer, and information services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportFreight%Ser
|The percentage of total service imports on the balance of payments attributed to freight transport
|Debit/Expenditure; All modes of transport; freight
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportOther%Ser
|The percentage of total service imports on the balance of payments attributed to postal and courier transport etc.
|Debit/Expenditure; All modes of transport; other than passenger and freight; including postal and courier services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTransportPass%Ser
|The percentage of total service imports on the balance of payments attributed to the transport of passengers
|Debit/Expenditure; All modes of transport; passenger
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTravelBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business travel
|Debit/Expenditure; Travel; business
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImTravelPersonal%Ser
|The percentage of total service imports on the balance of payments attributed to personal travel
|Debit/Expenditure; Travel; personal
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ExTravelBusiness%Ser
|Business Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; business
|
|%'Credit/Revenue; Services'
|0
|
|-
|ExTravelPersonal%Ser
|Personal Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; personal
|
|%'Credit/Revenue; Services'
|0
|
|-
|ImMaintRepair%Ser
|The percentage of total service imports on the balance of payments attributed to maintenance and repair services
|Debit/Expenditure; Maintenance and repair services n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImManuSer%Ser
|The percentage of total service imports on the balance of payments attributed to manufacturing services on physical inputs owned by others
|Debit/Expenditure; Manufacturing services on physical inputs owned by others
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business services
|Debit/Expenditure; Other business services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherConstruction%Ser
|The percentage of total service imports on the balance of payments attributed to construction
|Debit/Expenditure; Construction
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherCulRecreation%Ser
|The percentage of total service imports on the balance of payments attributed to personal, cultural, and recreational services
|Debit/Expenditure; Personal, cultural, and recreational services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherFinancial%Ser
|The percentage of total service imports on the balance of payments attributed to financial services
|Debit/Expenditure; Financial services
|
|%'Debit/Expenditure; Services'
|0
|
|-
|ImOtherGovGoodSer%Ser
|The percentage of total service imports on the balance of payments attributed to government goods and services
|Debit/Expenditure; Government goods and services n.i.e.
|
|%'Debit/Expenditure; Services'
|0
|
|}

= Data Pulling Instructions =
1. Go to https://data.imf.org/en/datasets/IMF.STA:BOP

2. Click on "Download". Choose the type of file, formatting and metadata. If you would like to use a script found here download as a '''csv''' and '''observation per row''' file. If you would like to view the data click "View Data"
[[File:IMF BoP Download Page.png|none|thumb|600x600px]]

4. Navigate to this GitHub Repo and follow instructions to pull the table. Make sure that you check the country concordance and units.

5. If you chose "View Data" ensure that you use the right filters (see below):
[[File:IMF BoP Filters.png|none|thumb|622x622px]]
Choose all countries, Debit/Revenue and Credit/Expenditure, US Dollars, Annual for Frequency, All for Time Period, and then choose the indicators listed in the tables. Then click "Download"

==== Directions for NetIIP%GDP ====
1. For this table navigate to: https://data.imf.org/Datasets/IIP

2. Click on "Download". Choose the type of file, formatting and metadata. If you would like to use a script found here download as a '''csv''' and '''observation per row''' file. If you would like to view the data click "View Data"
[[File:IMF BoP Download Page.png|none|thumb|600x600px]]
3. If you chose "View Data" ensure that you follow the filters below. Choose all countries, all years, US Dollars, annual for frequency, and Net International Investment Position, Adjusted using IMF accounting records for the indicator.
[[File:IMF IIP Filters.png|none|thumb|600x600px]]
4. Click "Download"

= Data Notes =

=== Calculations ===
The formula for XWorkerTransferReceived%GDP, XWorkerTransferPaid%GDP, XWorkerCompenPaid%GDP, and XWorkerCompenReceived%GDP from /GDP Current USD (NY.GDP.MKTP.CD to %'NY.GDP.MKTP.CD'. NY.GDP.MKTP.CD are GDP figures in World Bank. They can be found [https://databank.worldbank.org/metadataglossary/africa-development-indicators/series/NY.GDP.MKTP.CD.XD here] .

To complete the calculations: multiply by 1,000,000 to get the same units between IMF and World Bank since IMF unit Millions of U.S. Dollars, divide the sheets from IMF BoP by the GDP figures (NY.GDP.MKTP.CD), then multiple by 100 for the percentage value.

For example, for XWorkerTransferReceived%GDP Algeria 1977 the value is 349.1884 and for the same year the GDP Current USD is 20972113685.

349.1884 x 1,000,000= 349188400

349188400/20972113685 = 0.0166501291 x 100 = 1.665.

For the %Ser tables, you must divide the indicator listed by Services data (Services must align with the indicator; if the indicator is from Credit/Revenue, the services data must as well). The same process is followed as seen above. Take the indicator value divide it by Services and multiply it by 100.

= References =
<references />

File:IMF BoP Filters.png

2026-01-02T21:52:39Z

Norah.Shamin:

IMF BoP Filters

File:IMF IIP Filters.png

2026-01-02T21:49:28Z

Norah.Shamin:

IMF IIP Filters

File:IMF BoP Download Page.png

2026-01-02T21:43:13Z

Norah.Shamin:

IMF BoP Download Page

Balance of Payments and International Investment Position statistics (BoP/IIP), IMF

2026-01-02T21:32:19Z

Norah.Shamin: /* Tables In IFs */

= Summary =
The Balance of Payments (BoP) provides a framework that is applicable for a range of economies, from the smallest and least developed economies to the more advanced and complex economies. As a result, it is recognized that some items may not be relevant in all cases.

The IMF data on balance of payments and international investment positions is available here- http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1409773422141

The data is prepared in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual. The handbook can be accessed here, http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1390288795525

BoP data is available for approximately 204 economies, while IIP data is available for approximately 143 economies. Data is available for most countries from the year 1945.<ref>Refer About BoP/IIP Geographic,temporal coverage <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&sid=1409773422141&ss=1409773411929></ref>

=== Definitions ===
'''BoP '''is a flow while '''IIP''' is a stock. Although the balance of payments accounts are, in principle, balanced, imbalances result in practice from imperfections in source data and compilation. This imbalance, a usual feature of balance of payments data, is labeled net errors and omissions and is identified separately in published data. It should not be included indistinguishably in other items. Net errors and omissions are derived residually as net lending/net borrowing and can be derived from the financial account minus the same item derived from the current and capital accounts.<ref>Refer to “Balance of Payments and International Investment Positions Manual Version 6.”</ref>

The BoP is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Under the double-entry accounting system that underlines the balance of payments, each transaction is recorded as consisting of two entries and the sum of the credit entries and the sum of the debit entries is the same. The different accounts within the BoP are distinguished according to the nature of the economic resources provided and received.”<ref>See the BoP “about” sheet <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52></ref>

The International Investment Position (IIP) is a statistical statement that shows at a point in time the value of:

Financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents. The difference between the assets and the liabilities is the net position in the IIP and represents either a net claim on or a net liability to the rest of the world. The IIP represents a subset of the assets and liabilities included in the national balance sheet. In addition to the IIP, the national balance sheet incorporates nonfinancial assets as well as financial assets and liabilities positions between residents.

= Tables In IFs =
{| class="wikitable"
!Table
!Definition
!Indicator Name/Name in Source
!Indicator Code
!Formula
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|NetIIP%GDP
|Net International Investment Position as a percent of GDP.
|Net (assets less liabilities); Net International Investment Position, Adjusted using IMF accounting records
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XIncSecPayments%GDP
|Secondary Income payments as % of GDP
|Debit/Expenditure; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XIncSecReceipts%GDP
|Secondary Income receipts as % of GDP
|Credit/Revenue; Secondary income
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XWorkerCompenPaid%GDP
|Worker compensation paid as % of GDP
|Debit/Expenditure; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerCompenReceived%GDP
|Worker compensation received as % of GDP
|Credit/Revenue; Compensation of employees
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferPaid%GDP
|Worker transfer paid as % of GDP
|Debit/Expenditure; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferReceived%GDP
|Worker transfer received as % of GDP
|Credit/Revenue; Secondary income, Financial corporations, nonfinancial corporations, households, and NPISHs
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|ExMaintRepair%Ser
|Maintenance and Repair Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Maintenance and repair services n.i.e.
|
|
|0
|
|-
|ExManuSer%Ser
|Manufacturing Services on Physical Inputs Owned by Others exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Manufacturing services on physical inputs owned by others
|
|
|0
|
|-
|ExOtherBusiness%Ser
|Other Business Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other business services
|
|
|0
|
|-
|ExOtherConstruction%Ser
|Other Construction Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Construction
|
|
|0
|
|-
|ExOtherCulRecreation%Ser
|Personal, Cultural, and Recreational Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Personal, cultural, and recreational services
|
|
|0
|
|-
|ExOtherFinancial%Ser
|Other Financial Services Exports percentage of Total Service exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Financial services explicitly charged and other financial services
|
|
|0
|
|-
|ExOtherGovGoodSer%Ser
|Government Goods and Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Government goods and services n.i.e.
|
|
|0
|
|-
|ExOtherInsurPen%Ser
|Insurance and Pension Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Insurance and pension services
|
|
|0
|
|-
|ExOtherIntellectual%Ser
|Charges for the Use of Intellectual Property nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Charges for the use of intellectual property n.i.e.
|
|
|0
|
|-
|ExOtherTelCom%Ser
|Other Telecommunication Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Telecommunications, computer, and information services
|
|
|0
|
|-
|ExTransportFreight%Ser
|Freight Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary FundFreight Transport Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; freight
|
|
|0
|
|-
|ExTransportOther%Ser
|Other Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other modes of transport
|
|
|0
|
|-
|ExTransportPass%Ser
|Passenger Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; passenger
|
|
|0
|
|-
|ImOtherInsurPen%Ser
|The percentage of total service imports on the balance of payments attributed to services such as insurance and pension
|Debit/Expenditure; Insurance and pension services
|
|
|0
|
|-
|ImOtherIntellectual%Ser
|The percentage of total service imports on the balance of payments attributed to charges for the use of intellectual property
|Debit/Expenditure; Charges for the use of intellectual property n.i.e.
|
|
|0
|
|-
|ImOtherTelCom%Ser
|The percentage of total service imports on the balance of payments attributed to telecommunications, computer and information services
|Debit/Expenditure; Telecommunications, computer, and information services
|
|
|0
|
|-
|ImTransportFreight%Ser
|The percentage of total service imports on the balance of payments attributed to freight transport
|Debit/Expenditure; All modes of transport; freight
|
|
|0
|
|-
|ImTransportOther%Ser
|The percentage of total service imports on the balance of payments attributed to postal and courier transport etc.
|Debit/Expenditure; All modes of transport; other than passenger and freight; including postal and courier services
|
|
|0
|
|-
|ImTransportPass%Ser
|The percentage of total service imports on the balance of payments attributed to the transport of passengers
|Debit/Expenditure; All modes of transport; passenger
|
|
|0
|
|-
|ImTravelBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business travel
|Debit/Expenditure; Travel; business
|
|
|0
|
|-
|ImTravelPersonal%Ser
|The percentage of total service imports on the balance of payments attributed to personal travel
|Debit/Expenditure; Travel; personal
|
|
|0
|
|-
|ExTravelBusiness%Ser
|Business Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; business
|
|
|0
|
|-
|ExTravelPersonal%Ser
|Personal Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; personal
|
|
|0
|
|-
|ImMaintRepair%Ser
|The percentage of total service imports on the balance of payments attributed to maintenance and repair services
|Debit/Expenditure; Maintenance and repair services n.i.e.
|
|
|0
|
|-
|ImManuSer%Ser
|The percentage of total service imports on the balance of payments attributed to manufacturing services on physical inputs owned by others
|Debit/Expenditure; Manufacturing services on physical inputs owned by others
|
|
|0
|
|-
|ImOtherBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business services
|Debit/Expenditure; Other business services
|
|
|0
|
|-
|ImOtherConstruction%Ser
|The percentage of total service imports on the balance of payments attributed to construction
|Debit/Expenditure; Construction
|
|
|0
|
|-
|ImOtherCulRecreation%Ser
|The percentage of total service imports on the balance of payments attributed to personal, cultural, and recreational services
|Debit/Expenditure; Personal, cultural, and recreational services
|
|
|0
|
|-
|ImOtherFinancial%Ser
|The percentage of total service imports on the balance of payments attributed to financial services
|Debit/Expenditure; Financial services
|
|
|0
|
|-
|ImOtherGovGoodSer%Ser
|The percentage of total service imports on the balance of payments attributed to government goods and services
|Debit/Expenditure; Government goods and services n.i.e.
|
|
|0
|
|}

= Data Pulling Instructions =
#Go to https://data.imf.org/en/datasets/IMF.RES:WEO
#Click on "Download". If you would like to view the data click "View Data"
#All countries is selected by default. Unless you are pulling specific countries, this is correct.
#Click on indicators and select the indicators of interest. The indicators above are all found under the first two tabs. Make sure you deselect the variables that are not of interest.
#Click okay. the download will begin.
#When the download is complete. You will receive an email, or you can click "My Data" in the top right hand corner.
= Data Notes =

=== Calculations ===
The formula for XWorkerTransferReceived%GDP, XWorkerTransferPaid%GDP, XWorkerCompenPaid%GDP, and XWorkerCompenReceived%GDP from /GDP Current USD (NY.GDP.MKTP.CD to %'NY.GDP.MKTP.CD'. NY.GDP.MKTP.CD are GDP figures in World Bank. They can be found [https://databank.worldbank.org/metadataglossary/africa-development-indicators/series/NY.GDP.MKTP.CD.XD here] .

To complete the calculations: multiply by 1,000,000 to get the same units between IMF and World Bank since IMF unit Millions of U.S. Dollars, divide the sheets from IMF BoP by the GDP figures (NY.GDP.MKTP.CD), then multiple by 100 for the percentage value.

For example, for XWorkerTransferReceived%GDP Algeria 1977 the value is 349.1884 and for the same year the GDP Current USD is 20972113685.

349.1884 x 1,000,000= 349188400

349188400/20972113685 = 0.0166501291 x 100 = 1.665.

For the %Ser tables, you must divide the indicator listed by Services data (Services must align with the indicator; if the indicator is from Credit/Revenue, the services data must as well). An example is shown below:

= References =
<references />

Balance of Payments and International Investment Position statistics (BoP/IIP), IMF

2026-01-02T21:21:27Z

Norah.Shamin: /* Tables In IFs */

= Summary =
The Balance of Payments (BoP) provides a framework that is applicable for a range of economies, from the smallest and least developed economies to the more advanced and complex economies. As a result, it is recognized that some items may not be relevant in all cases.

The IMF data on balance of payments and international investment positions is available here- http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1409773422141

The data is prepared in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual. The handbook can be accessed here, http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1390288795525

BoP data is available for approximately 204 economies, while IIP data is available for approximately 143 economies. Data is available for most countries from the year 1945.<ref>Refer About BoP/IIP Geographic,temporal coverage <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&sid=1409773422141&ss=1409773411929></ref>

=== Definitions ===
'''BoP '''is a flow while '''IIP''' is a stock. Although the balance of payments accounts are, in principle, balanced, imbalances result in practice from imperfections in source data and compilation. This imbalance, a usual feature of balance of payments data, is labeled net errors and omissions and is identified separately in published data. It should not be included indistinguishably in other items. Net errors and omissions are derived residually as net lending/net borrowing and can be derived from the financial account minus the same item derived from the current and capital accounts.<ref>Refer to “Balance of Payments and International Investment Positions Manual Version 6.”</ref>

The BoP is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Under the double-entry accounting system that underlines the balance of payments, each transaction is recorded as consisting of two entries and the sum of the credit entries and the sum of the debit entries is the same. The different accounts within the BoP are distinguished according to the nature of the economic resources provided and received.”<ref>See the BoP “about” sheet <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52></ref>

The International Investment Position (IIP) is a statistical statement that shows at a point in time the value of:

Financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents. The difference between the assets and the liabilities is the net position in the IIP and represents either a net claim on or a net liability to the rest of the world. The IIP represents a subset of the assets and liabilities included in the national balance sheet. In addition to the IIP, the national balance sheet incorporates nonfinancial assets as well as financial assets and liabilities positions between residents.

= Tables In IFs =
{| class="wikitable"
!Table
!Definition
!Indicator Name/Name in Source
!Indicator Code
!Formula
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|NetIIP%GDP
|Net International Investment Position as a percent of GDP.
|Net international investment position (with Fund Record), US Dollars
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XIncSecPayments%GDP
|Secondary Income payments as % of GDP
|Current Account, Secondary income, Debit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XIncSecReceipts%GDP
|Secondary Income receipts as % of GDP
|Current Account, Secondary income, Credit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XWorkerCompenPaid%GDP
|Worker compensation paid as % of GDP
|Current Account, Primary Income, Compensation of Employees, Debit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerCompenReceived%GDP
|Worker compensation received as % of GDP
|Current Account, Primary Income, Compensation of Employees, Credit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferPaid%GDP
|Worker transfer paid as % of GDP
|Current Account, Secondary Income, Debits, Financial Corporations, Nonfinancial Corporation, Households, and NPISHs, Personal Transfers
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferReceived%GDP
|Worker transfer received as % of GDP
|Current Account, Secondary Income, Credits, Financial Corporations, Nonfinancial Corporation, Households, and NPISHs, Personal Transfers
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|ExMaintRepair%Ser
|Maintenance and Repair Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Maintenance and repair services n.i.e.
|
|
|0
|
|-
|ExManuSer%Ser
|Manufacturing Services on Physical Inputs Owned by Others exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Manufacturing services on physical inputs owned by others
|
|
|0
|
|-
|ExOtherBusiness%Ser
|Other Business Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other business services
|
|
|0
|
|-
|ExOtherConstruction%Ser
|Other Construction Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Construction
|
|
|0
|
|-
|ExOtherCulRecreation%Ser
|Personal, Cultural, and Recreational Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Personal, cultural, and recreational services
|
|
|0
|
|-
|ExOtherFinancial%Ser
|Other Financial Services Exports percentage of Total Service exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Financial services explicitly charged and other financial services
|
|
|0
|
|-
|ExOtherGovGoodSer%Ser
|Government Goods and Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Government goods and services n.i.e.
|
|
|0
|
|-
|ExOtherInsurPen%Ser
|Insurance and Pension Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Insurance and pension services
|
|
|0
|
|-
|ExOtherIntellectual%Ser
|Charges for the Use of Intellectual Property nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Charges for the use of intellectual property n.i.e.
|
|
|0
|
|-
|ExOtherTelCom%Ser
|Other Telecommunication Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Telecommunications, computer, and information services
|
|
|0
|
|-
|ExTransportFreight%Ser
|Freight Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary FundFreight Transport Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; freight
|
|
|0
|
|-
|ExTransportOther%Ser
|Other Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Other modes of transport
|
|
|0
|
|-
|ExTransportPass%Ser
|Passenger Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; All modes of transport; passenger
|
|
|0
|
|-
|ImOtherInsurPen%Ser
|The percentage of total service imports on the balance of payments attributed to services such as insurance and pension
|Debit/Expenditure; Insurance and pension services
|
|
|0
|
|-
|ImOtherIntellectual%Ser
|The percentage of total service imports on the balance of payments attributed to charges for the use of intellectual property
|Debit/Expenditure; Charges for the use of intellectual property n.i.e.
|
|
|0
|
|-
|ImOtherTelCom%Ser
|The percentage of total service imports on the balance of payments attributed to telecommunications, computer and information services
|Debit/Expenditure; Telecommunications, computer, and information services
|
|
|0
|
|-
|ImTransportFreight%Ser
|The percentage of total service imports on the balance of payments attributed to freight transport
|Debit/Expenditure; All modes of transport; freight
|
|
|0
|
|-
|ImTransportOther%Ser
|The percentage of total service imports on the balance of payments attributed to postal and courier transport etc.
|Debit/Expenditure; All modes of transport; other than passenger and freight; including postal and courier services
|
|
|0
|
|-
|ImTransportPass%Ser
|The percentage of total service imports on the balance of payments attributed to the transport of passengers
|Debit/Expenditure; All modes of transport; passenger
|
|
|0
|
|-
|ImTravelBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business travel
|Debit/Expenditure; Travel; business
|
|
|0
|
|-
|ImTravelPersonal%Ser
|The percentage of total service imports on the balance of payments attributed to personal travel
|Debit/Expenditure; Travel; personal
|
|
|0
|
|-
|ExTravelBusiness%Ser
|Business Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; business
|
|
|0
|
|-
|ExTravelPersonal%Ser
|Personal Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Travel; personal
|
|
|0
|
|-
|ImMaintRepair%Ser
|The percentage of total service imports on the balance of payments attributed to maintenance and repair services
|Debit/Expenditure; Maintenance and repair services n.i.e.
|
|
|0
|
|-
|ImManuSer%Ser
|The percentage of total service imports on the balance of payments attributed to manufacturing services on physical inputs owned by others
|Debit/Expenditure; Manufacturing services on physical inputs owned by others
|
|
|0
|
|-
|ImOtherBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business services
|Debit/Expenditure; Other business services
|
|
|0
|
|-
|ImOtherConstruction%Ser
|The percentage of total service imports on the balance of payments attributed to construction
|Debit/Expenditure; Construction
|
|
|0
|
|-
|ImOtherCulRecreation%Ser
|The percentage of total service imports on the balance of payments attributed to personal, cultural, and recreational services
|Debit/Expenditure; Personal, cultural, and recreational services
|
|
|0
|
|-
|ImOtherFinancial%Ser
|The percentage of total service imports on the balance of payments attributed to financial services
|Debit/Expenditure; Financial services
|
|
|0
|
|-
|ImOtherGovGoodSer%Ser
|The percentage of total service imports on the balance of payments attributed to government goods and services
|Debit/Expenditure; Government goods and services n.i.e.
|
|
|0
|
|}

= Data Pulling Instructions =
#Go to https://data.imf.org/en/datasets/IMF.RES:WEO
#Click on "Download". If you would like to view the data click "View Data"
#All countries is selected by default. Unless you are pulling specific countries, this is correct.
#Click on indicators and select the indicators of interest. The indicators above are all found under the first two tabs. Make sure you deselect the variables that are not of interest.
#Click okay. the download will begin.
#When the download is complete. You will receive an email, or you can click "My Data" in the top right hand corner.
= Data Notes =

=== Calculations ===
The formula for XWorkerTransferReceived%GDP, XWorkerTransferPaid%GDP, XWorkerCompenPaid%GDP, and XWorkerCompenReceived%GDP from /GDP Current USD (NY.GDP.MKTP.CD to %'NY.GDP.MKTP.CD'. NY.GDP.MKTP.CD are GDP figures in World Bank. They can be found [https://databank.worldbank.org/metadataglossary/africa-development-indicators/series/NY.GDP.MKTP.CD.XD here] .

To complete the calculations: multiply by 1,000,000 to get the same units between IMF and World Bank since IMF unit Millions of U.S. Dollars, divide the sheets from IMF BoP by the GDP figures (NY.GDP.MKTP.CD), then multiple by 100 for the percentage value.

For example, for XWorkerTransferReceived%GDP Algeria 1977 the value is 349.1884 and for the same year the GDP Current USD is 20972113685.

349.1884 x 1,000,000= 349188400

349188400/20972113685 = 0.0166501291 x 100 = 1.665.

For the %Ser tables, you must divide the indicator listed by Services data (Services must align with the indicator; if the indicator is from Credit/Revenue, the services data must as well). An example is shown below:

= References =
<references />

Balance of Payments and International Investment Position statistics (BoP/IIP), IMF

2026-01-01T18:48:35Z

Norah.Shamin:

= Summary =
The Balance of Payments (BoP) provides a framework that is applicable for a range of economies, from the smallest and least developed economies to the more advanced and complex economies. As a result, it is recognized that some items may not be relevant in all cases.

The IMF data on balance of payments and international investment positions is available here- http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1409773422141

The data is prepared in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual. The handbook can be accessed here, http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&ss=1390288795525

BoP data is available for approximately 204 economies, while IIP data is available for approximately 143 economies. Data is available for most countries from the year 1945.<ref>Refer About BoP/IIP Geographic,temporal coverage <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52&sid=1409773422141&ss=1409773411929></ref>

=== Definitions ===
'''BoP '''is a flow while '''IIP''' is a stock. Although the balance of payments accounts are, in principle, balanced, imbalances result in practice from imperfections in source data and compilation. This imbalance, a usual feature of balance of payments data, is labeled net errors and omissions and is identified separately in published data. It should not be included indistinguishably in other items. Net errors and omissions are derived residually as net lending/net borrowing and can be derived from the financial account minus the same item derived from the current and capital accounts.<ref>Refer to “Balance of Payments and International Investment Positions Manual Version 6.”</ref>

The BoP is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Under the double-entry accounting system that underlines the balance of payments, each transaction is recorded as consisting of two entries and the sum of the credit entries and the sum of the debit entries is the same. The different accounts within the BoP are distinguished according to the nature of the economic resources provided and received.”<ref>See the BoP “about” sheet <http://data.imf.org/?sk=7A51304B-6426-40C0-83DD-CA473CA1FD52></ref>

The International Investment Position (IIP) is a statistical statement that shows at a point in time the value of:

Financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents. The difference between the assets and the liabilities is the net position in the IIP and represents either a net claim on or a net liability to the rest of the world. The IIP represents a subset of the assets and liabilities included in the national balance sheet. In addition to the IIP, the national balance sheet incorporates nonfinancial assets as well as financial assets and liabilities positions between residents.

= Tables In IFs =
{| class="wikitable"
!Table
!Definition
!Indicator Name/Name in Source
!Indicator Code
!Formula
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|NetIIP%GDP
|Net International Investment Position as a percent of GDP.
|Net international investment position (with Fund Record), US Dollars
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XIncSecPayments%GDP
|Secondary Income payments as % of GDP
|Current Account, Secondary income, Debit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XIncSecReceipts%GDP
|Secondary Income receipts as % of GDP
|Current Account, Secondary income, Credit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|1
|ECONOMY
|-
|XWorkerCompenPaid%GDP
|Worker compensation paid as % of GDP
|Current Account, Primary Income, Compensation of Employees, Debit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerCompenReceived%GDP
|Worker compensation received as % of GDP
|Current Account, Primary Income, Compensation of Employees, Credit, US Dollars
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferPaid%GDP
|Worker transfer paid as % of GDP
|Current Account, Secondary Income, Debits, Financial Corporations, Nonfinancial Corporation, Households, and NPISHs, Personal Transfers
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|XWorkerTransferReceived%GDP
|Worker transfer received as % of GDP
|Current Account, Secondary Income, Credits, Financial Corporations, Nonfinancial Corporation, Households, and NPISHs, Personal Transfers
|
|%'NY.GDP.MKTP.CD'
|0
|
|-
|ExMaintRepair%Ser
|Maintenance and Repair Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue; Maintenance and repair services n.i.e.
|
|
|0
|
|-
|ExManuSer%Ser
|Manufacturing Services on Physical Inputs Owned by Others exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherBusiness%Ser
|Other Business Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherConstruction%Ser
|Other Construction Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherCulRecreation%Ser
|Personal, Cultural, and Recreational Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherFinancial%Ser
|Other Financial Services Exports percentage of Total Service exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherGovGoodSer%Ser
|Government Goods and Services nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherInsurPen%Ser
|Insurance and Pension Services exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherIntellectual%Ser
|Charges for the Use of Intellectual Property nie exports percentage of Total Services Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExOtherTelCom%Ser
|Other Telecommunication Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExTransportFreight%Ser
|Freight Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary FundFreight Transport Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExTransportOther%Ser
|Other Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExTransportPass%Ser
|Passenger Transport Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ImOtherInsurPen%Ser
|The percentage of total service imports on the balance of payments attributed to services such as insurance and pension
|Debit/Expenditure;
|
|
|0
|
|-
|ImOtherIntellectual%Ser
|The percentage of total service imports on the balance of payments attributed to charges for the use of intellectual property
|Debit/Expenditure;
|
|
|0
|
|-
|ImOtherTelCom%Ser
|The percentage of total service imports on the balance of payments attributed to telecommunications, computer and information services
|Debit/Expenditure;
|
|
|0
|
|-
|ImTransportFreight%Ser
|The percentage of total service imports on the balance of payments attributed to freight transport
|Debit/Expenditure;
|
|
|0
|
|-
|ImTransportOther%Ser
|The percentage of total service imports on the balance of payments attributed to postal and courier transport etc.
|Debit/Expenditure;
|
|
|0
|
|-
|ImTransportPass%Ser
|The percentage of total service imports on the balance of payments attributed to the transport of passengers
|Debit/Expenditure;
|
|
|0
|
|-
|ImTravelBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business travel
|Debit/Expenditure;
|
|
|0
|
|-
|ImTravelPersonal%Ser
|The percentage of total service imports on the balance of payments attributed to personal travel
|Debit/Expenditure;
|
|
|0
|
|-
|ExTravelBusiness%Ser
|Business Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ExTravelPersonal%Ser
|Personal Travel Services Exports percentage of Total Service Exports, Balance of Payments from the International Monetary Fund
|Credit/Revenue;
|
|
|0
|
|-
|ImMaintRepair%Ser
|The percentage of total service imports on the balance of payments attributed to maintenance and repair services
|Debit/Expenditure;
|
|
|0
|
|-
|ImManuSer%Ser
|The percentage of total service imports on the balance of payments attributed to manufacturing services on physical inputs owned by others
|Debit/Expenditure;
|
|
|0
|
|-
|ImOtherBusiness%Ser
|The percentage of total service imports on the balance of payments attributed to business services
|Debit/Expenditure;
|
|
|0
|
|-
|ImOtherConstruction%Ser
|The percentage of total service imports on the balance of payments attributed to construction
|Debit/Expenditure;
|
|
|0
|
|-
|ImOtherCulRecreation%Ser
|The percentage of total service imports on the balance of payments attributed to personal, cultural, and recreational services
|Debit/Expenditure;
|
|
|0
|
|-
|ImOtherFinancial%Ser
|The percentage of total service imports on the balance of payments attributed to financial services
|Debit/Expenditure;
|
|
|0
|
|-
|ImOtherGovGoodSer%Ser
|The percentage of total service imports on the balance of payments attributed to government goods and services
|Debit/Expenditure;
|
|
|0
|
|}

= Data Pulling Instructions =
#Go to
#Click on
#Click on the "Bulk Download (entire dataset)" icon
#All countries is selected by default. Unless you are pulling specific countries, this is correct.
#Click on indicators and select the indicators of interest. The indicators above are all found under the first two tabs. Make sure you deselect the variables that are not of interest.
#Click okay. the download will begin.
#When the download is complete. You will receive an email, or you can click "My Data" in the top right hand corner.
= Data Notes =

=== Calculations ===
The formula for XWorkerTransferReceived%GDP, XWorkerTransferPaid%GDP, XWorkerCompenPaid%GDP, and XWorkerCompenReceived%GDP from /GDP Current USD (NY.GDP.MKTP.CD to %'NY.GDP.MKTP.CD'. NY.GDP.MKTP.CD are GDP figures in World Bank. They can be found [https://databank.worldbank.org/metadataglossary/africa-development-indicators/series/NY.GDP.MKTP.CD.XD here] .

To complete the calculations: multiply by 1,000,000 to get the same units between IMF and World Bank since IMF unit Millions of U.S. Dollars, divide the sheets from IMF BoP by the GDP figures (NY.GDP.MKTP.CD), then multiple by 100 for the percentage value.

For example, for XWorkerTransferReceived%GDP Algeria 1977 the value is 349.1884 and for the same year the GDP Current USD is 20972113685.

349.1884 x 1,000,000= 349188400

349188400/20972113685 = 0.0166501291 x 100 = 1.665.
= References =
<references />

GDP & GDPPCPPP from IMF World Economic Outlook & WDI

2025-11-20T18:52:57Z

Norah.Shamin: /* Tables In IFs */

= Summary =
The IMF World Economic Outlook and WDI hold valuable information about countries' GDP, PPP, etc. Therefore IFs contains that information and uses that information to calculate other indicators.

=== Data Collected From Sources ===

* GDP at current prices in local currency (GDP_current_LCU)
* GDP deflator for each year (GDP_deflator_year)
* GDP deflator for your base year (e.g., GDP_deflator_base for 2021)
* Exchange rate for your base year (Exchange_Rate_base; local currency per USD)
* PPP conversion factor for your base year (PPP_conversion_base; local currency per international dollar)
* Population (for each year; can be millions or actual number)

=== Calculation ===
In the calculation of constant GDP MER at constant price (such as tables GDP2021 and GDP2017), the formal process is to

* Get GDP at local currency unit- GDP_current_LCU
* Use GDP deflator to calculate GDP_constant_LCU. Here, you will need to pick a base year. We were using 2017 but are now moving to 2021. Thus, the result would be GDP at constant 2021 LCU.
** GDP_constant_LCU_base = GDP_current_LCU × (GDP_deflator_base / GDP_deflator_year)
* Use the market exchange rate to calculate GDP_constant_USD. Here, you will need the market exchange rate in 2021.
** GDP_constant_USD_base = GDP_constant_LCU_base / Exchange_Rate_base

To calculate GDP PPP at constant price, the formal process is exactly the same, except for step 3 in which instead of using market exchange rate, we apply PPP conversion rate.

* Same as step 1 above.
* Same as step 2 above.
* Use the PPP conversion rate to calculate GDP_PPP_constant_USD. Here, you will need the PPP conversion rate in 2021.
** GDP_PPP_constant_base = GDP_constant_LCU_base / PPP_conversion_base
We can use a shortcuts because each country's GDP at constant price in a selected year equals to that country's GDP at current price in the same year.

# Take a country's GDP at current USD in year 2021 and treat it as its GDP at constant $2021 in year 2021.
## GDP_constant_USD_2021 = GDP_current_USD_2021
# Calculate GDP growth rates measured at constant price.
## Because GDP growth rates measured at constant price remain the same despite of the base year chosen, i.e., a country's GDP growth rates would be the same across table GDP2011, GDP2017, and GDP2021.
### GDP_constant_USD_year = GDP_current_USD_base × (Growth Rate)
# Apply the growth rates to that country's GDP at current USD in 2021 to calculate other years' GDP.

This short cut also works for calculating GDP PPP at constant price.

# We already calculated GDP MER at constant USD in 2021 for each country for all years above.
# Use the ratio between a country's 2021's market exchange rate and its 2021's PPP conversion factor: you can use the following equation: GDP MER at constant $2021 / price ratio to get GDP PPP. Then GDP PPP / Population gets GDP PC PPP.
## GDP_PPP_constant_year = GDP_constant_USD_year / (Exchange_Rate_base / PPP_conversion_base)
## GDP_PC_PPP_constant_year = GDP_PPP_constant_year / Population_year

=== Related Wiki Pages ===
# [https://pardeewiki.du.edu//index.php?title=Core_Series GDP and GDPPC]
# [https://pardeewiki.du.edu/index.php?title=Economy_Data GDP2011]
# [https://pardeewiki.du.edu/index.php?title=Economy_Data GDP2011PCPPP]

= Tables In IFs =
{| class="wikitable"
|Variable
|Table
|Group
|SubGroup
|Definition
|Units
|Years
|UsedInPreprocessor
|UsedInPreprocessorFileName
|-
|GDP2011
|SeriesGDP2011
|Economy
|Aggregate
|IMF 2025 October Release, projection to 2027; WDI 2025 October version, values up to 2024
|Bil 2011$
|1960-2027
|0
|
|-
|GDP2011PCPPP
|SeriesGDP2011PCPPP
|Economic, Favorites
|GDP per Capita
|WDI 2025 October version, values up to 2024
|2011 PPP$
|1960-2024
|1
|Economy
|-
|GDP2017
|SeriesGDP2017
|Economy
|Aggregate
|IMF 2025 October Release, projection to 2027; WDI 2025 October version, values up to 2024
|Bil 2017$
|1960-2027
|0
|
|-
|GDP2017PCPPP
|SeriesGDP2017PCPPP
|Economic, Favorites
|GDP per Capita
|WDI 2025 October version, values up to 2024
|2017 PPP$
|1960-2024
|1
|Economy
|-
|GDP2021
|SeriesGDP2021
|Economy
|Aggregate
|IMF 2025 October Release, projection to 2027; WDI 2025 October version, values up to 2024
|Bil 2021$
|1960-2027
|0
|
|-
|GDP2021PCPPP
|SeriesGDP2021PCPPP
|Economic, Favorites
|GDP per Capita
|WDI 2025 October version, values up to 2024
|2021 PPP$
|1960-2024
|1
|Economy
|}
Most recent update was in November of 2025.

= Data Pulling Instructions =
If you would like a script to pull navigate to https://github.com/n1shamin/GDP-and-GDPPCPPP-IMF-and-WB. This does '''not''' do the special cases.

=== GDP ===
1. Download data

* GDP (current US$): https://data.worldbank.org/indicator/NY.GDP.MKTP.CD
* GDP growth (annual %): https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG
* IMF: entire dataset https://www.imf.org/en/Publications/SPROLLS/world-economic-outlook-databases#sort=%40imfdate%20descending
** Click the most recent WEO database, eg, World Economic Outlook Database, October 2024.
** Select "Entire Dataset"
** Click "By Countires", it will automatically download the entire data. The download file will be in .xls format. Open the file with Excel and Save as .xlsx for future use.
*** We will only use WEO Subject Code in (NGDP_RPCH, NGDPD). NGDP_RPCH is the percent change of GDP, and NGDPD is GDP in current US$ in Billions).
* IFsHistSeries: SeriesGDP2011 and SeriesGDP2017, in current US$ in Billions. We will use '''2011''' as the example in this instruction.

2. Calculate Growth_Rate from SeriesGDP2011. (Growth_Rate in 2011 = (GDP in 2011 - GDP in 2010)/GDP in 2010; The growth_rate need to *100 as percent value.)

3. Change all the data we downloaded and calculated to the format of [Country, Year, VAL]

* GDP (current US$): Country, Year, wb_curr
* GDP growth (annual %): Country, Year, wb_growth
* IMF_ NGDP_RPCH: Country, Year, imf_growth
* IMF_ NGDPD: Country, Year, imf_curr ('''''Note1''''')
* SeriesGDP2011: Country, Year, ifs_gdp ('''''Note1''''')
* Growth_Rate: Country, Year, ifs_growth

'''''Note1: imf_curr and ifs_gdp need to be *''''' '''''1000000000 due to the Billions Unit.'''''

4. Create a new value, '''GDP_curr,''' primarily using wb_curr.

* If there is a null in wb_curr, then use imf_curr to fill the null.
* If there is a null in both wb_curr and imf_curr, then use ifs_gdp to fill the null.

5. Create a new value, '''Growth,''' primarily using wb_growth

* If there is a null in wb_growth, then use imf_growth to fill the null.
* If there is a null in both wb_growth and imf_growth, then use ifs_growth to fill the null.
* After filling nulls, use forward fill to fill the rest of nulls.

6. Create a new value, '''GDP_new,'''

* The base year is 2011 since we use GDP2011 from the IFsHist. It will change to 2017 when we use GDP2017.
* Fill the base year value in GDP_curr to GDP_new for each country.
* After this step, every country will only have 1 value in GDP_new for the base year, e.g. 2011.

7. Fill the rest of the years for '''GDP_new''' using '''Growth''' and '''GDP_curr''':

* For the years before the base year, 2011, we will calculate the value from 2010 to 1960. E.g. GDP_new in 2010 = GDP_new in 2011*100 / (Growth in 2011 + 100). The year will be rolling for the rest of the calculation.
* For the years from the base year to year_end('''''Note2'''''), 2011, we will calculate the value from 2012 to 2026. E.g. GDP_new in 2012 = GDP_new in 2011*(100 + Growth in 2012) / 100. The year will be rolling for the rest of the calculation.

'''''Note2: year_end is 2 years from now.'''''

'''8. GDP_new is the new value for GDP2011. Need to be /1000000000 and be rounded to 5 decimals.'''

=== GDPPCPPP ===
1. Download Data

* GDP per capita (current LCU): https://data.worldbank.org/indicator/NY.GDP.PCAP.CN
* GDP deflator (base year varies by country): https://data.worldbank.org/indicator/NY.GDP.DEFL.ZS
* PPP conversion factor, GDP (LCU per international $): https://data.worldbank.org/indicator/PA.NUS.PPP
* GDP per capita growth (annual %): https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG
* IFsHistSeries: SeriesGDP2011PCPPP and SeriesGDP2017PCPPP. We will use '''2011''' as the example in this instruction.

2. Calculate PCPPP_Growth_Rate from SeriesGDP2011PCPPP. (PCPPP_Growth_Rate in 2011 = (PCPPP in 2011 - PCPPP in 2010)/PCPPP in 2010; The growth_rate need to *100 as percent value.)

3. Change all the data we downloaded and calculated to the format of [Country, Year, VAL]

* GDP per capita (current LCU): Country, Year, wb_curr
* GDP deflator (base year varies by country): Country, Year, wb_deflat
* PPP conversion factor, GDP (LCU per international $): Country, Year, wb_ppp_cov
* GDP per capita growth (annual %): Country, Year, wb_growth
* SeriesGDP2011PCPPP: Country, Year, ifs_pcppp
* PCPPP_Growth_Rate: Country, Year, ifs_pcppp_growth

4. Create a new value, '''pc_growth,''' primarily using wb_growth.

* If there is a null in wb_growth, then use ifs_pcppp_growth to fill the null.

5. Create a new value, '''2011_deflat''' (if use SeriesGDP2017PCPPP, then the new value is 2017_deflat)

* The base year is 2011 since we use GDP2011PCPPP from the IFsHist. It will change to 2017 when we use GDP2017PCPPP.
* Fill the base year value in wb_deflat in 2011_deflat for each country.
* After this step, every country will only have 1 value in 2011_deflat for the base year, e.g. 2011.
* If there is null value for wb_deflat in the base year, then you can leave the 2011_deflat null.

6. Create a new value, '''2011_ppp_cov''' (if use SeriesGDP2017PCPPP, then the new value is 2017_ppp_cov)

* Fill the base year value in wb_ppp_cov in 2011_ppp_cov for each country.
* After this step, every country will only have 1 value in 2011_ppp_cov for the base year, e.g. 2011.

7. Create a '''new''' '''table''' using [Country, Year, wb_curr] and [Country, Year, wb_deflat]

* Find the most recent year for each country as well as the wb_curr and wb_deflat in that most recent year.

8. Merge the new table with 2011_deflat and 2011_ppp_cov only using Country.

* The output table would be
** Country
** Year (the most recent year for the country)
** wb_curr (the wb_curr in the most recent year for the country)
** wb_deflat (the wb_deflat in the most recent year for the country)
** 2011_deflat (the deflator in the base year, 2011)
** 2011_ppp_cov (the ppp_cov in the base year, 2011)
* Calculate a new value, '''2011_const_pcppp''' (if use SeriesGDP2017PCPPP, then the new value is 2017_const_pcppp) using the formula below.
** '''2011_const_pcppp = (wb_curr * (2011_deflat/wb_deflat))/2011_ppp_cov'''

9. There will be countries having 0 or null values for '''2011_const_pcppp'''. We will use the value in ifs_pcppp in the most recent year for these missing countries to fill 2011_const_pcppp. (In this case, the most recent year will change to the most recent year for ifs_pcppp.) Thus, all 188 countries should have a 2011_const_pcppp for its most recent year.

10. Now we have 2011_const_pcppp in the most recent year for each country. We will calculate the 2011_const_pcppp for the rest of the year.

* year_end = 2022 (The most recent year in GDP per capita (current LCU) from WDI).
* Starting from the most recent year to the earliest year. E.g. The most recent year in Afghanistan is 2021, 2021 – 1960, for 2020
** 2011_const_pcppp in 2020 = 100* 2011_const_pcppp in 2021 / (100 + pc_growth in 2021)
* Starting from the most recent year to the year_end. E.g. The most recent year in Afghanistan is 2021, 2021 – 2022, for 2022
** 2011_const_pcppp in 2022 = 2011_const_pcppp in 2021 * (100 + pc_growth in 2022)/100

'''11. The 2011_const_pcppp is the new value for GDP2011PCPPP. Need to be rounded to 5 decimals.'''

=== Special Cases ===

#We want to have as much data for all regions and coverage, we need to make sure that we use proxies and special cases when we can. For Kosovo, Sahrawi Arab Democratic Republic, and South Sudan use Albania, Morocco (and Mali for GDP switch to Mali in 1967), and Sudan as proxies. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally. To do this use SeriesPopulation. For instance, Kosovo’s GDP = Albania’s GDP * Kosovo’s Population / Albania’s Population.
#For Taiwan PC PPP use IMF data ''instead of WDI'' which gives you data from 1980-present year. Then use Singapore as a proxy for years 1960-1979.

= Data Notes =

# The IMF updated their NGDP_RPCH projection for part of the countries in July of 2025 (https://www.imf.org/en/Publications/WEO/Issues/2025/07/29/world-economic-outlook-update-july-2025).
# IMF updated their data structure and codes. The script adapted to this.
# GDP2021 and GDP2021PCPPP are new tables introduced in 2025 because the World Bank introduced 2021 PPP.

GDP & GDPPCPPP from IMF World Economic Outlook & WDI

2025-11-20T18:49:57Z

Norah.Shamin:

= Summary =
The IMF World Economic Outlook and WDI hold valuable information about countries' GDP, PPP, etc. Therefore IFs contains that information and uses that information to calculate other indicators.

=== Data Collected From Sources ===

* GDP at current prices in local currency (GDP_current_LCU)
* GDP deflator for each year (GDP_deflator_year)
* GDP deflator for your base year (e.g., GDP_deflator_base for 2021)
* Exchange rate for your base year (Exchange_Rate_base; local currency per USD)
* PPP conversion factor for your base year (PPP_conversion_base; local currency per international dollar)
* Population (for each year; can be millions or actual number)

=== Calculation ===
In the calculation of constant GDP MER at constant price (such as tables GDP2021 and GDP2017), the formal process is to

* Get GDP at local currency unit- GDP_current_LCU
* Use GDP deflator to calculate GDP_constant_LCU. Here, you will need to pick a base year. We were using 2017 but are now moving to 2021. Thus, the result would be GDP at constant 2021 LCU.
** GDP_constant_LCU_base = GDP_current_LCU × (GDP_deflator_base / GDP_deflator_year)
* Use the market exchange rate to calculate GDP_constant_USD. Here, you will need the market exchange rate in 2021.
** GDP_constant_USD_base = GDP_constant_LCU_base / Exchange_Rate_base

To calculate GDP PPP at constant price, the formal process is exactly the same, except for step 3 in which instead of using market exchange rate, we apply PPP conversion rate.

* Same as step 1 above.
* Same as step 2 above.
* Use the PPP conversion rate to calculate GDP_PPP_constant_USD. Here, you will need the PPP conversion rate in 2021.
** GDP_PPP_constant_base = GDP_constant_LCU_base / PPP_conversion_base
We can use a shortcuts because each country's GDP at constant price in a selected year equals to that country's GDP at current price in the same year.

# Take a country's GDP at current USD in year 2021 and treat it as its GDP at constant $2021 in year 2021.
## GDP_constant_USD_2021 = GDP_current_USD_2021
# Calculate GDP growth rates measured at constant price.
## Because GDP growth rates measured at constant price remain the same despite of the base year chosen, i.e., a country's GDP growth rates would be the same across table GDP2011, GDP2017, and GDP2021.
### GDP_constant_USD_year = GDP_current_USD_base × (Growth Rate)
# Apply the growth rates to that country's GDP at current USD in 2021 to calculate other years' GDP.

This short cut also works for calculating GDP PPP at constant price.

# We already calculated GDP MER at constant USD in 2021 for each country for all years above.
# Use the ratio between a country's 2021's market exchange rate and its 2021's PPP conversion factor: you can use the following equation: GDP MER at constant $2021 / price ratio to get GDP PPP. Then GDP PPP / Population gets GDP PC PPP.
## GDP_PPP_constant_year = GDP_constant_USD_year / (Exchange_Rate_base / PPP_conversion_base)
## GDP_PC_PPP_constant_year = GDP_PPP_constant_year / Population_year

=== Related Wiki Pages ===
# [https://pardeewiki.du.edu//index.php?title=Core_Series GDP and GDPPC]
# [https://pardeewiki.du.edu/index.php?title=Economy_Data GDP2011]
# [https://pardeewiki.du.edu/index.php?title=Economy_Data GDP2011PCPPP]

= Tables In IFs =
{| class="wikitable"
|Variable
|Table
|Group
|SubGroup
|Definition
|Units
|Years
|UsedInPreprocessor
|UsedInPreprocessorFileName
|-
|GDP2011
|SeriesGDP2011
|Economy
|Aggregate
|GDP (MER) at constant 2011 US$, IMF 2024 Apr Release, last year of data is 2026
|Bil 2011$
|1960-2027
|0
|
|-
|GDP2011PCPPP
|SeriesGDP2011PCPPP
|Economic, Favorites
|GDP per Capita
|GDP per capita (constant 2011 PPP International $)
|2011 PPP$
|1960-2023
|1
|Economy
|-
|GDP2017
|SeriesGDP2017
|Economy
|Aggregate
|GDP (MER) at constant 2017 US$, IMF 2024 Apr Release, last year of data is 2026
|Bil 2017$
|1960-2027
|0
|
|-
|GDP2017PCPPP
|SeriesGDP2017PCPPP
|Economic, Favorites
|GDP per Capita
|GDP per capita (constant 2017 PPP International $)
|2017 PPP$
|1960-2023
|1
|Economy
|-
|GDP2021
|SeriesGDP2021
|Economy
|Aggregate
|GDP (MER) at constant 2021 US$, IMF 2025 July Release, last year of data is 2026
|Bil 2021$
|1960-2027
|0
|
|-
|GDP2021PCPPP
|SeriesGDP2021PCPPP
|Economic, Favorites
|GDP per Capita
|GDP per capita (constant 2021 PPP International $)
|2021 PPP$
|1960-2024
|1
|Economy
|}
Most recent update was in November of 2025.

= Data Pulling Instructions =
If you would like a script to pull navigate to https://github.com/n1shamin/GDP-and-GDPPCPPP-IMF-and-WB. This does '''not''' do the special cases.

=== GDP ===
1. Download data

* GDP (current US$): https://data.worldbank.org/indicator/NY.GDP.MKTP.CD
* GDP growth (annual %): https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG
* IMF: entire dataset https://www.imf.org/en/Publications/SPROLLS/world-economic-outlook-databases#sort=%40imfdate%20descending
** Click the most recent WEO database, eg, World Economic Outlook Database, October 2024.
** Select "Entire Dataset"
** Click "By Countires", it will automatically download the entire data. The download file will be in .xls format. Open the file with Excel and Save as .xlsx for future use.
*** We will only use WEO Subject Code in (NGDP_RPCH, NGDPD). NGDP_RPCH is the percent change of GDP, and NGDPD is GDP in current US$ in Billions).
* IFsHistSeries: SeriesGDP2011 and SeriesGDP2017, in current US$ in Billions. We will use '''2011''' as the example in this instruction.

2. Calculate Growth_Rate from SeriesGDP2011. (Growth_Rate in 2011 = (GDP in 2011 - GDP in 2010)/GDP in 2010; The growth_rate need to *100 as percent value.)

3. Change all the data we downloaded and calculated to the format of [Country, Year, VAL]

* GDP (current US$): Country, Year, wb_curr
* GDP growth (annual %): Country, Year, wb_growth
* IMF_ NGDP_RPCH: Country, Year, imf_growth
* IMF_ NGDPD: Country, Year, imf_curr ('''''Note1''''')
* SeriesGDP2011: Country, Year, ifs_gdp ('''''Note1''''')
* Growth_Rate: Country, Year, ifs_growth

'''''Note1: imf_curr and ifs_gdp need to be *''''' '''''1000000000 due to the Billions Unit.'''''

4. Create a new value, '''GDP_curr,''' primarily using wb_curr.

* If there is a null in wb_curr, then use imf_curr to fill the null.
* If there is a null in both wb_curr and imf_curr, then use ifs_gdp to fill the null.

5. Create a new value, '''Growth,''' primarily using wb_growth

* If there is a null in wb_growth, then use imf_growth to fill the null.
* If there is a null in both wb_growth and imf_growth, then use ifs_growth to fill the null.
* After filling nulls, use forward fill to fill the rest of nulls.

6. Create a new value, '''GDP_new,'''

* The base year is 2011 since we use GDP2011 from the IFsHist. It will change to 2017 when we use GDP2017.
* Fill the base year value in GDP_curr to GDP_new for each country.
* After this step, every country will only have 1 value in GDP_new for the base year, e.g. 2011.

7. Fill the rest of the years for '''GDP_new''' using '''Growth''' and '''GDP_curr''':

* For the years before the base year, 2011, we will calculate the value from 2010 to 1960. E.g. GDP_new in 2010 = GDP_new in 2011*100 / (Growth in 2011 + 100). The year will be rolling for the rest of the calculation.
* For the years from the base year to year_end('''''Note2'''''), 2011, we will calculate the value from 2012 to 2026. E.g. GDP_new in 2012 = GDP_new in 2011*(100 + Growth in 2012) / 100. The year will be rolling for the rest of the calculation.

'''''Note2: year_end is 2 years from now.'''''

'''8. GDP_new is the new value for GDP2011. Need to be /1000000000 and be rounded to 5 decimals.'''

=== GDPPCPPP ===
1. Download Data

* GDP per capita (current LCU): https://data.worldbank.org/indicator/NY.GDP.PCAP.CN
* GDP deflator (base year varies by country): https://data.worldbank.org/indicator/NY.GDP.DEFL.ZS
* PPP conversion factor, GDP (LCU per international $): https://data.worldbank.org/indicator/PA.NUS.PPP
* GDP per capita growth (annual %): https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG
* IFsHistSeries: SeriesGDP2011PCPPP and SeriesGDP2017PCPPP. We will use '''2011''' as the example in this instruction.

2. Calculate PCPPP_Growth_Rate from SeriesGDP2011PCPPP. (PCPPP_Growth_Rate in 2011 = (PCPPP in 2011 - PCPPP in 2010)/PCPPP in 2010; The growth_rate need to *100 as percent value.)

3. Change all the data we downloaded and calculated to the format of [Country, Year, VAL]

* GDP per capita (current LCU): Country, Year, wb_curr
* GDP deflator (base year varies by country): Country, Year, wb_deflat
* PPP conversion factor, GDP (LCU per international $): Country, Year, wb_ppp_cov
* GDP per capita growth (annual %): Country, Year, wb_growth
* SeriesGDP2011PCPPP: Country, Year, ifs_pcppp
* PCPPP_Growth_Rate: Country, Year, ifs_pcppp_growth

4. Create a new value, '''pc_growth,''' primarily using wb_growth.

* If there is a null in wb_growth, then use ifs_pcppp_growth to fill the null.

5. Create a new value, '''2011_deflat''' (if use SeriesGDP2017PCPPP, then the new value is 2017_deflat)

* The base year is 2011 since we use GDP2011PCPPP from the IFsHist. It will change to 2017 when we use GDP2017PCPPP.
* Fill the base year value in wb_deflat in 2011_deflat for each country.
* After this step, every country will only have 1 value in 2011_deflat for the base year, e.g. 2011.
* If there is null value for wb_deflat in the base year, then you can leave the 2011_deflat null.

6. Create a new value, '''2011_ppp_cov''' (if use SeriesGDP2017PCPPP, then the new value is 2017_ppp_cov)

* Fill the base year value in wb_ppp_cov in 2011_ppp_cov for each country.
* After this step, every country will only have 1 value in 2011_ppp_cov for the base year, e.g. 2011.

7. Create a '''new''' '''table''' using [Country, Year, wb_curr] and [Country, Year, wb_deflat]

* Find the most recent year for each country as well as the wb_curr and wb_deflat in that most recent year.

8. Merge the new table with 2011_deflat and 2011_ppp_cov only using Country.

* The output table would be
** Country
** Year (the most recent year for the country)
** wb_curr (the wb_curr in the most recent year for the country)
** wb_deflat (the wb_deflat in the most recent year for the country)
** 2011_deflat (the deflator in the base year, 2011)
** 2011_ppp_cov (the ppp_cov in the base year, 2011)
* Calculate a new value, '''2011_const_pcppp''' (if use SeriesGDP2017PCPPP, then the new value is 2017_const_pcppp) using the formula below.
** '''2011_const_pcppp = (wb_curr * (2011_deflat/wb_deflat))/2011_ppp_cov'''

9. There will be countries having 0 or null values for '''2011_const_pcppp'''. We will use the value in ifs_pcppp in the most recent year for these missing countries to fill 2011_const_pcppp. (In this case, the most recent year will change to the most recent year for ifs_pcppp.) Thus, all 188 countries should have a 2011_const_pcppp for its most recent year.

10. Now we have 2011_const_pcppp in the most recent year for each country. We will calculate the 2011_const_pcppp for the rest of the year.

* year_end = 2022 (The most recent year in GDP per capita (current LCU) from WDI).
* Starting from the most recent year to the earliest year. E.g. The most recent year in Afghanistan is 2021, 2021 – 1960, for 2020
** 2011_const_pcppp in 2020 = 100* 2011_const_pcppp in 2021 / (100 + pc_growth in 2021)
* Starting from the most recent year to the year_end. E.g. The most recent year in Afghanistan is 2021, 2021 – 2022, for 2022
** 2011_const_pcppp in 2022 = 2011_const_pcppp in 2021 * (100 + pc_growth in 2022)/100

'''11. The 2011_const_pcppp is the new value for GDP2011PCPPP. Need to be rounded to 5 decimals.'''

=== Special Cases ===

#We want to have as much data for all regions and coverage, we need to make sure that we use proxies and special cases when we can. For Kosovo, Sahrawi Arab Democratic Republic, and South Sudan use Albania, Morocco (and Mali for GDP switch to Mali in 1967), and Sudan as proxies. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally. To do this use SeriesPopulation. For instance, Kosovo’s GDP = Albania’s GDP * Kosovo’s Population / Albania’s Population.
#For Taiwan PC PPP use IMF data ''instead of WDI'' which gives you data from 1980-present year. Then use Singapore as a proxy for years 1960-1979.

= Data Notes =

# The IMF updated their NGDP_RPCH projection for part of the countries in July of 2025 (https://www.imf.org/en/Publications/WEO/Issues/2025/07/29/world-economic-outlook-update-july-2025).
# IMF updated their data structure and codes. The script adapted to this.
# GDP2021 and GDP2021PCPPP are new tables introduced in 2025 because the World Bank introduced 2021 PPP.

Poverty and Inequality Platform, World Bank

2025-11-19T20:07:44Z

Norah.Shamin:

== Summary ==
The [https://pip.worldbank.org/home Poverty and Inequality Platform (PIP)] is an interactive computational tool that offers users quick access to the World Bank’s estimates of poverty, inequality, and shared prosperity. PIP provides a comprehensive view of global, regional, and country-level trends for more than 160 economies around the world. All poverty and inequality indicators are organized under the dropdown “Data”, where users can access the different measures. The visualizations available allow for multiple ways to explore PIP indicators, from cross-country and regional analyses, to country-specific and subnational, while other pages provide in-depth analyses by topic.

The last update was in June 2025. This update brought an additional 74 country-year datapoints (countries such as Barbados and Equatorial Guinea) to the PIP database and improved existing data for another 90 country-years. A detailed update can be found [https://documents1.worldbank.org/curated/en/099510306052516849/pdf/IDU-eb272b02-ecd1-4633-9e37-9297e20a711c.pdf here].

Another update in August 2025 which led to the correction of three new tables. This is due to the World Bank adding a new modeling around 2021 PPP.
== Tables in IFs ==

{| class="wikitable"
|+
!Variable
!Definition
!Name In Source
!UsedInPreprocessor
!UsedInPreprocessorFileName
!UsedInHistAnalog
|-
|IncBelow2D15c%PIP
|Percent of population living on less than $2.15 per day, estimation by PIP
|headcount
|1
|ECONOMY
|TRUE
|-
|IncBelow3D65c%PIP
|Percent of population living on less than $3.65 per day, estimation by PIP
|headcount
|1
|ECONOMY
|TRUE
|-
|IncBelow6D85c%PIP
|Percent of population living on less than $6.85 per day, estimation by PIP
|headcount
|1
|ECONOMY
|TRUE
|-
|IncMedPIP
|Median income estimated by PIP from WorldBank, $2017 PPP per day
|median
|0
|
|FALSE
|-
|PovGap2D15cperDayPIP
|Mean shortfall in income or consumption from the poverty line $2.15 a day, expressed as a percentage of the poverty line. Estimation by PIP
|poverty_gap
|0
|
|FALSE
|-
|PovGap3D55cperDayPIP
|Mean shortfall in income or consumption from the poverty line $3.65 a day, expressed as a percentage of the poverty line. Estimation by PIP
|poverty_gap
|0
|
|FALSE
|-
|PovGap6D85cperDayPIP
|Mean shortfall in income or consumption from the poverty line $6.85 a day, expressed as a percentage of the poverty line. Estimation by PIP
|poverty_gap
|0
|
|FALSE
|-
|IncBelow3D00c%PIP
|Percent of population living on less than $3.00 per day, estimation by PIP
|headcount
|1
|ECONOMY
|TRUE
|-
|IncBelow4D20c%PIP
|Percent of population living on less than $4.20 per day, estimation by PIP
|headcount
|1
|ECONOMY
|TRUE
|-
|IncBelow8D30c%PIP
|Percent of population living on less than $8.30 per day, estimation by PIP
|headcount
|1
|ECONOMY
|TRUE
|-
|IncMed2021PPPPIP
|Median income estimated by PIP from WorldBank, $2021 PPP per day
|median
|0
|
|FALSE
|-
|PovGap3D00cperDayPIP
|Mean shortfall in income or consumption from the poverty line $3.00 a day, expressed as a percentage of the poverty line. Estimation by PIP
|poverty_gap
|0
|
|FALSE
|-
|PovGap4D20cperDayPIP
|Mean shortfall in income or consumption from the poverty line $4.20 a day, expressed as a percentage of the poverty line. Estimation by PIP
|poverty_gap
|0
|
|FALSE
|-
|PovGap8D30cperDayPIP
|Mean shortfall in income or consumption from the poverty line $8.30 a day, expressed as a percentage of the poverty line. Estimation by PIP
|poverty_gap
|0
|
|FALSE
|}

== Data Pulling Instructions ==

# Go to this site (https://pip.worldbank.org/home). Make sure the mode is 2017 PPP or 2021 PPP depending on the tables you are updating. Change this in the top right. [[File:Poverty and Inequality Platform.png|none|thumb|700x700px]]
# Select Interpolated Values
# Select Poverty Rate. The data you need will show up in one excel (ie if you need the poverty rate and gap for $3.00, it will show up in one excel). You do not need to select any other indicator or countries.
# Click download and choose download '''all country data'''. While the excel file has different indicators you do need to download different excels for the different dollar amounts (you will have one excel for $4.20, another for $3.00, etc).
## To select different dollar amounts shift the slider in the top left corner or type in the value.
# Filter your reporting data by national (except for Argentina, we can use urban data. For all the other countries it must be national.), filter survey by consumption [and income separately to blend values], headcount, poverty_gap, and median (median is the same in all excel files) will be the indicators for your data.
# After that select survey type income to blend these values in. Consumption should be the preferred survey type but to make sure we have as many values as possible use income has a backdrop.
# To use a script, navigate to https://github.com/n1shamin/Poverty-and-Inequality-Platform. This does the entire process (including Argentina, blending consumption and income, etc).

== Notes ==
For the series:

* IncBelow2D15c%PIP
* IncBelow3D65c%PIP
* IncBelow6D85c%PIP
* PovGap2D15cperDayPIP
* PovGap3D55cperDayPIP
* PovGap6D85cperDayPIP

Multiply the data points by 100 to get the percentage values.

The survey type must be consumption first then income second.

For Argentina, we can use urban data. For all the other countries it must be national.

Make sure that you choose consumption and not income for type of survey at first.

For a country concordance table for the World Bank check this [https://github.com/n1shamin/World-Development-Indicators-Update-2025 GitHub Repo].

United Nations Population Division Department of Economic and Social Affairs

2025-11-19T18:42:43Z

Norah.Shamin: /* Summary */

= Summary =
The Population Division of the Department of Economic and Social Affairs conducts demographic research, supports intergovernmental processes at the United Nations in the area of population and development, and assists countries in developing their capacity to produce and analyze population data and information.

IFs uses the UN DESA for many tables; the most current is the SeriesHouseholds which utilizes the Household Size and Composition Database. This database presents a compilation of indicators on household size and membership composition around the world, estimated using both tabulated data and household roster micro-data from censuses and household surveys.

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Extended Source Defn
!Last IFs Update
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|SeriesHouseholds
|Number of households (SeriesPopulation/average household size (number of members)
|Most data points up to 2014 are based on SeriesHouseholdsITU2014, with some values before and after 2014 are filled by UNPD
|2025/11/19
|1
|INFRASTRUCTURE, POPULATION
|}

= Data Pulling Instructions =

# Navigate to https://www.un.org/development/desa/pd/household-size-and-composition
# Scroll to '''Data''' and click ''Dataset''
# The indicator is "Average household size (number of members)"
## Change Reference date (dd/mm/yyyy) to an actual date format so it will be read by a code correctly '''or''' to use =YEAR(__). [[File:UN DESA .png|none|thumb|600x600px]]
#If you create a separate column for year using =YEAR(), you cam use this code to pull:https://github.com/n1shamin/UN-DESA-Household-Data/tree/main
##We need to divide the data from UN DESA with SeriesPopulation. The script included in the repo.
#After this, blend the data with SeriesHouseholdsITU2014.

= Notes =

* In Source Ext Definition state: Most data points up to 2014 are based on SeriesHouseholdsITU2014, with some values before and after 2014 are filled by UNPD

United Nations Population Division Department of Economic and Social Affairs

2025-11-19T18:40:58Z

Norah.Shamin: /* Data Pulling Instructions */

= Summary =

= Tables In IFs =
{| class="wikitable"
|+
!Variable
!Definition
!Extended Source Defn
!Last IFs Update
!UsedInPreprocessor
!UsedInPreprocessorFileName
|-
|SeriesHouseholds
|Number of households (SeriesPopulation/average household size (number of members)
|Most data points up to 2014 are based on SeriesHouseholdsITU2014, with some values before and after 2014 are filled by UNPD
|2025/11/19
|1
|INFRASTRUCTURE, POPULATION
|}

= Data Pulling Instructions =

# Navigate to https://www.un.org/development/desa/pd/household-size-and-composition
# Scroll to '''Data''' and click ''Dataset''
# The indicator is "Average household size (number of members)"
## Change Reference date (dd/mm/yyyy) to an actual date format so it will be read by a code correctly '''or''' to use =YEAR(__). [[File:UN DESA .png|none|thumb|600x600px]]
#If you create a separate column for year using =YEAR(), you cam use this code to pull:https://github.com/n1shamin/UN-DESA-Household-Data/tree/main
##We need to divide the data from UN DESA with SeriesPopulation. The script included in the repo.
#After this, blend the data with SeriesHouseholdsITU2014.

= Notes =

* In Source Ext Definition state: Most data points up to 2014 are based on SeriesHouseholdsITU2014, with some values before and after 2014 are filled by UNPD

United Nations Population Division Department of Economic and Social Affairs

2025-11-19T18:36:15Z

Norah.Shamin: /* Data Pulling Instructions */

File:UN DESA .png

2025-11-19T18:29:30Z

Norah.Shamin:

UN DESA

United Nations Population Division Department of Economic and Social Affairs

2025-11-19T18:13:20Z

Norah.Shamin:

United Nations Population Division Department of Economic and Social Affairs

2025-11-19T18:00:25Z

Norah.Shamin: Created blank page

Data Sources

2025-11-19T18:00:18Z

Norah.Shamin: /* United Nations */

=== [[Country Concordances]] ===

=== [[Research Papers/Projects]] ===

=== [[Preprocessor|Preprocessors]] ===

=== [[Template]] ===

== Data Sources ==

===== Barro-Lee =====
* [[Educational Attainment Dataset, Barro-Lee|Education Attainment Dataset]]

===== Bertelsmann Stiftung =====
* [[The Transformation Index (BTI)]]

===== Carbon Dioxide Information and Analysis Center (CDIAC) =====

* [[Carbon Dioxide Information and Analysis Center (CDIAC)|Carbon Emissions Data]]

===== Center for Systemic Peace =====

* [[Polity5]]
* [[Major Episodes of Political Violence (MEPV)]]
* [[State Fragility Index, Center for Systemic Peace|State Fragility Index]]
* [[Political Instability Task Force (PITF), Center for Systematic Peace|Political Instability Task Force (PITF)]]

===== Centre d'Etudes Prospectives et d'Informations Internationales (CEPII) =====

* [[BACI]]
* [[GeoDist, CEPII|GeoDist]]

===== CIA =====

* [[CIA World Factbook]]

===== Climate Watch =====
* [[Emissions Data, Climate Watch|Emissions Data]]

===== Correlates of War =====
* [[The Correlates of War Project, Correlates of War|The Correlates of War Project]]

===== Demographic and Health Surveys (DHS) =====

* [[STATcompiler, Demographic and Health Surveys (DHS)|STATcompiler]]

===== Economist Intelligence Unit (EIU) =====

* [[Economist Intelligence Unit (EIU)|Economist Intelligence Unit (EIU) Data]]
* [[The Political Instability Index, Economist Intelligence Unit (EIU)|The Political Instability Index]]

===== EMBER =====
* [[Electricity Data, EMBER|Electricity Data]]

===== Emissions Database for Global Atmospheric Research =====

* [[Emissions Database for Global Atmospheric Research Data]]

===== Energy Institute =====

* [[Statistical Review of World Energy, Energy Institute|Statistical Review of World Energy]]

===== Europa World Yearbook =====

* [[Europa World Yearbook Data]]

===== European Commission =====

* [[Eurostat European Commission|Eurostat, European Commission]]

===== Federation of American Scientists =====

* [[Federation of American Scientists Data]]

===== Federal Institute for Geosciences and Natural Resources (BGR) =====

* [[Energy Data, BGR|Energy Data]]

===== Food and Agriculture Organization (FAO) =====

* [[AQUASTAT, FAO|AQUASTAT - FAO's Global Information System on Water and Agriculture]]
* [[FishstatJ, FAO|FishStatJ]]
* [[FAOSTAT Food Balance Sheet]]
* [[FAOSTAT Food Security and Nutrition]]
* [[FAOSTAT Land Use|FAOSTAT Land]]
* [[FAOSTAT SDG Indicators]]
* [[FAOSTAT Trade Crops and livestock products]]

===== Fraser Institute =====

* [https://pardeewiki.du.edu//index.php?title=Fraser_International Economic Data]

===== Freedom House =====

* [[Countries at the Crossroads, Freedom House|Countries at the Crossroads]]
* [[FreedomHouse|Freedom in the World]]
* [[Freedom on the Net, Freedom House|Freedom on the Net]]

===== Fund for Peace =====
* [[Fragile States Index, Fund for Peace|Fragile States Index]]

===== Global Carbon Budget (GCB) =====

* [[Carbon Data, Global Carbon Budget (GCB)|Carbon Data]]

===== Global Footprint Network =====

* [[Global Footprint Network|Global Footprint Network Data]]

===== Global Trade Analysis Project (GTAP) =====

* [[Global Trade Analysis Project (GTAP)|Global Trade Analysis Project (GTAP) Data]]

===== Heritage Foundation =====

* [[Heritage Foundation Data]]

===== Institute for Employment Research (IAB) =====

* [[Brain Drain Data, Institute for Employment Research (IAB)|Brain Drain Data]]

===== Inter-American Development Bank (IDB) =====

* [[Database of Political Institutions, World Bank|Database of Political Institutions (DPI)]]

===== International Groundwater Resources Assessment Centre (IGRAC) =====

* [[Global Depletion of Groundwater Resources, International Groundwater Resources Assessment Centre (IGRAC)|Global Depletion of Groundwater Resources]]

===== International Centre for Tax & Development (ICTD) =====

* [[International Centre for Tax & Development (ICTD)|International Centre for Tax & Development (ICTD) Data]]

===== International Diabetes Federation =====

* [[Diabetes Atlas, International Diabetes Federation|Diabetes Atlas]]

===== [[International Energy Agency (IEA)]] =====
* [[End-Use Prices Data Explorer, International Energy Agency (IEA)|End-Use Prices Data Explorer]]
* [[World Energy Balances, International Energy Agency (IEA)|World Energy Balances]]
* [[World Energy Outlook, International Energy Agency (IEA)|World Energy Outlook]]
* [[World Energy Statistics, International Energy Agency (IEA)|World Energy Statistics]]

===== International Food Policy Research Institute =====

* [[International Food Policy Research Institute Data]]

===== Institute for Health Metrics and Evaluation (IHME) =====

* [[IHME|Global Burdens of Disease (GBD)]]

===== International Institute for Applied Systems Analysis (IIASA) =====

* [[Shared Socioeconomic Pathway (SSP) Extensions Explorer, International Institute for Applied Systems Analysis (IIASA)|Shared Socioeconomic Pathway (SSP) Extensions Explorer]]
* [[RCP Representative Concentration Pathways Database|RCP Database]]

===== International Institute for Management Development (IMD) =====

* [[International Institute for Management Development (IMD) Data]]

===== International Labor Organization (ILO) =====
*[[ILOstat]]
*[[ILO-WIEGO Statistical Reports]]

=====International Monetary Fund (IMF)=====

* [[Balance of Payments and International Investment Position statistics (BoP/IIP), IMF|Balance of Payments and International Investment Position statistics (BoP/IIP)]]
* [[Fiscal Monitor, IMF|Fiscal Monitor]]
* [[GDP & GDPPCPPP from IMF World Economic Outlook & WDI|GDP and GDPPCPPP]]
* [[International Financial Statistics, IMF|International Financial Statistics]]
* [[World Economic Outlook, IMF|World Economic Outlook (WEO)]]
* [[IMF GFS Government Finance Statistics|Government Finance Statistics (GFS)]]
* [[IMF COFOG Classifications of Functions of Government|Classification of the Functions of Government (COFOG)]]

===== Inter-Parliamentary Union =====

* [[Women in Parliaments, Inter-Parliamentary Union|Women in Parliaments]]

===== International Renewable Energy Agency (IRENA) =====

* [[Energy Data, International Renewable Energy Agency (IRENA)|Energy Data]]

===== International Research & Exchanges Board (IREX) =====

* [[International Research & Exchanges Board (IREX) Data]]

===== International Study Center, Boston College =====

* [[TIMMS & PIRLS, International Study Center, Boston College|TIMSS & PIRLS]]

===== International Telecommunications Union (ITU) =====

* [[International Telecommunication Union DataHub]]
* [[Global Cybersecurity Index (GCI), ITU|Global Cybersecurity Index (GCI)]]

===== International Organization of Motor Vehicle Manufacturers (OICA) =====

* [[International Organization of Motor Vehicle Manufacturers (OICA) Data]]

===== International Road Federation =====

* [[IRF World Road Statistics|World Road Statistics]]

===== Kellogg Institute For International Studies =====

* [[Kellogg Institute Data]]

===== LIS Cross-National Data Center =====

* [[LIS Cross-National Data Center Data]]

===== Mo Ibrahim Foundation =====

* [[Ibrahim Index of African Governance, Mo Ibrahim Foundation|Ibrahim Index of African Governance]]

===== MyGeoHub =====

* [[MY GEO HUB|Historical Irrigation Dataset (HID)]]

===== National Science Foundation (NSF) =====

* [[Science and Engineering Indicators, National Science Foundation (NSF)|Science and Engineering Indicators]]
* [[Science and Technology Studies (STS), National Science Foundation (NSF)|Science and Technology Studies (STS)]]

===== Organisation of Economic Cooperation and Development (OECD) =====
* International Transport Forum (ITF)
** [[Transport Data and Statistics, International Transport Forum (ITF)|Transport Data and Statistics]]
*[[OECD The Organisation for Economic Co-operation and Development|OECD Data Explorer]]
*[[OECD Education at a glance|OECD Education At a Glance]]
*[[OECD Factbook]]
*[[OECD Information Technology Outlook (ITO)|OECD Information Technology Outlook]]
* [[Measuring the Internet Economy, Organisation for Economic Co-operation and Development (OECD)|Measuring the Internet Economy]]
* [[Pensions at a Glance, Organisation for Economic Co-operation and Development (OECD)|Pensions at a Glance]]
* [[OECD Science & Technology|Science & Technology]]
* [[Social Institutions and Gender Index, OECD|Social Institutions and Gender Index]]
*[[Structural Analysis Database (STAN), OECD|Structural Analysis Database (STAN)]]

===== Political Terror Scale (PTS) =====

* [[Political Terror Scale (PTS) Data]]

===== Population Reference Bureau (PRB) =====

* [[Population Reference Bureau (PRB)|Assorted Annual Population Data Sheets]]

===== Potsdam Institute for Climate Impact Research (PIK) =====

* [[Climate Data, Potsdam Institute for Climate Impact Research (PIK)|Climate Data]]

===== PRIS Project =====

* [[IRIS, PRIS Project|IRIS]]

===== Reporters Without Borders =====

* [[Worldwide Press Freedom Index, Reporters Without Borders|Worldwide Press Freedom Index]]

===== Royal Netherlands Meteorological Institute (WMO KNMI) =====

* [[World Meteorological Organization Climate Explorer Reports]]

===== Stockholm International Peace Research Institute (SIPRI) =====

* [[Stockholm International Peace Research Institute (SIPRI)|Military Expenditure Data]]

===== SpeedTest =====

* [[SpeedTest Data]]

===== The Conference Board =====

* [[Total Economy Database, The Conference Board|Total Economy Database]]

===== Transparency International (TI) =====

* [[Transparency International|Corruption Perceptions Index]]

===== UBS Group AG =====

* [[Global Wealth Report, UBS Group AG|Global Wealth Report]]

===== Uppsala Conflict Data Program (UCDP) =====

* [[Uppsala Conflict Data Program (UCDP) Datasets]]
* [[UCDP/PRIO Armed Conflict Database|Uppsala Conflict Data Program (UCDP)/Peace Research Institute Oslo (PRIO) Armed Conflict Dataset]]

===== United Nations Economic Commission for Europe (UNECE) =====

* [[United Nations Economic Commission for Europe (UNECE) Data|United Nations Economic Commission for Europe Data]]

===== United Nations =====

* [[General Assembly of the United Nations (UNGA)]]
* [[Joint United Nations Programme on HIV/AIDS (UNAIDS)]]
* [[Millennium Development Goals Database, UN|Millennium Development Goals Database]]
* United Nations Department of Economic and Social Affairs
** [[United Nation World Marriage Data, United Nations Department of Economic and Social Affairs|United Nation World Marriage Data]]
* United Nations Educational, Scientific and Cultural Organization (UNESCO)
** [[Institute for Statistics, UNESCO (UIS)]]
* [[United Nations Industrial Development Organization (UNIDO)]]
* United Nations International Children's Emergency Fund (UNICEF)
** [[Child protection and development, UNICEF|Child protection and development]]
*[[United Nations Office of Drug and Crime (UNODC)]]
*United Nations Population Division (UNPD)
** [[United Nations Population Division Department of Economic and Social Affairs]]
** [[World Population Prospects (WPP), United Nations Population Division (UNPD)|World Population Prospects (WPP)]]
** [[UNDP Human Development Reports]]
*[[United Nation SDG Indicators Global Database (UNSDG)]]
*[[United Nations Statistics Division (UNSD)]]
**[[Environmental Indicators, UNSD|Environmental Indicators]]
*[[UN Trade and Development (UNCTAD)|United Nations Trade and Development (UNCTAD)]]
*[[United Nations Treaty Collection]]
*[[World Tourism Organization (UN Tourism)]]

===== University of Maryland =====

* [[Global Terrorism Database, University of Maryland|Global Terrorism Database]]
* [[Peace and Conflict Instability Ledger, University of Maryland/Center for International Development and Conflict Management (CIDCM)|Peace and Conflict Instability Ledger]]
* [[Minorities at risk|All Minorities at Risk (AMAR) Project]]

===== University of Pennsylvania =====

* [[The Political Constraint Index (POLCON), University of Pennsylvania|The Political Constraint Index (POLCON)]]

===== UN University World Institute for Development Economics Research (UNU WIDER) =====

* [[World Income Inequality Database, UN University World Institute for Development Economics Research (UNU WIDER)|World Income Inequality Database]]

===== US Energy Information Administration (EIA) =====

* [[Energy Information Administration (EIA)|Energy Information Administration Data]]

===== US Geological Survey =====

* [[World Petroleum Assessment, U.S. Geological Survey|World Petroleum Assessment]]

===== Vision of Humanity =====

* [[Vision of Humanity Data]]

===== Wittgenstein Centre =====

* [[Wittgenstein Centre Human Capital Data Explorer]]

===== World Bank =====

* [[The Atlas of Social Protection Indicators of Resilience and Equity (ASPIRE), World Bank|Atlas of Social Protection Indicators of Resilience and Equity (ASPIRE)]]
* [[Business Ready (B-READY), World Bank|Business Ready (B-READY)]]
* [[Climate Change Action Plan (CCAP), World Bank|Climate Change Action Plan (CCAP)]]
* [[Climate Change Knowledge Portal, World Bank|Climate Change Knowledge Portal]]
* [[Country Policy and Institutional Assessment (CPIA), World Bank|Country Policy and Institutional Assessment (CPIA)]]
* [[Education Statistics (EdStats), World Bank|Education Statistics (EdStats)]]
* [[GDP & GDPPCPPP from IMF World Economic Outlook & WDI|GDP and GDPPCPPP]]
*[[Gender Statistics, World Bank|Gender Statistics]]
*[[Global Financial Development, World Bank|Global Financial Development]]
*[[Global Integrity Index]]
*[[Informal Economy Database]]
*[[International Development Association, World Bank|International Development Association]]
*[[Poverty and Inequality Platform, World Bank|Poverty and Inequality Platform]]
*[[Private Participation in Infrastructure (PPI) Project Database, World Bank|Private Participation in Infrastructure (PPI) Project Database]]
*[[Road Costs Knowledge System (ROCKS), World Bank|Road Costs Knowledge System (ROCKS)]]
*[[World Development Indicators, World Bank|World Development Indicators (WDI)]]
*[[World Development Report, World Bank|World Development Report]]
*[[Worldwide Governance Indicators|World Governance Indicators (WGI)]]

===== World Democratic Forum (WDF) =====

* [[World Democratic Forum (WDF) Data]]

===== World Economic Forum =====

*[[Global Competitiveness Index, World Economic Forum|Global Competitiveness Index]]

===== [[World Energy Council (WEC)]]=====

* [[Oil & Gas Journal, WEC]]

===== World Health Organization (WHO)=====

*[[Global Health Expenditure Database, WHO|Global Health Expenditure Database]]
*[[Joint Monitoring Programme, WHO/UNICEF|Joint Monitoring Programme (JMP)]]
*[[Surveillance of chronic disease Risk Factors (SuRF), WHO|Surveillance of chronic disease Risk Factors (SuRF)]]
*[[World Malaria Report, WHO|World Malaria Report]]

* [[Global Health Observatory (GHO)]]
** [[Obesity, adult (18+) and child and adolescent (5-19)|Obesity]]
** [[WHO Tobacco Free Initiative (TFI)|Tobacco Free Initiative (TFI)]]

===== World Intellectual Property Organization (WIPO) =====
* [[The Global Innovation Index, World Intellectual Property Organization (WIPO)|The Global Innovation Index]]

===== World Justice Project =====

*[[World Justice Project Rule of Law Index|Rule of Law Index]]

===== World Poverty Clock =====

* [[World Poverty Clock|World Poverty Clock Data]]

=====World Military Expenditures and Arms Transfers (WMEAT)=====

* [[World Military Expenditures and Arms Transfers (WMEAT)|World Military Expenditures and Arms Transfers (WMEAT) Reports]]

=====World Trade Organization (WTO)=====

* [[Dispute Statistics, WTO|Dispute Statistics]]

=====World Value Survey (WVS)=====

* [[World Value Survey|World Value Survey Data]]