India's Economic Data

GDP2011

This series was estimated using data that was found on the Data.gov website for India's data. The original state level GDP data is in a 2004-2005 base year and was in ten million rupees (crore). There is not GDP data for union territories available. The 2004-2005 base year data was rebased using a deflator from WDI for India, which was applied to all states and the national data for all of India. The rebased national data was used to estimate the union territory GDP by using the proportion of each territory's population relative to the national population for each year. The population weighted GDP is the best GDP estimates that have been generated thus far. Telangana and Andhra Pradesh's GDP was estimated using a population weight. The data is normalized using ApplyMultAll. 

There was a series of subnational GDP in at 2010-2011 base year, but that data was not used for several reasons. First, the 2010-2011 data lacked data for all union territories, like the other series, and it lacked data for West Bengal. West Begal is a large state with a substantial proportion of national GDP and estimating the data would both complicated and likely inaccurate with the data available. Second, the methods used for estimating subnational GDP changed significantly between the 2004-2005 base year data and the 2010-2011 base year data. It is not only the base year that had changed between those years, and the data is fundamentally uncomparable. The goal in the updated GDP estimation methodologies was to include more informal economic activities and to account for capital more accurately. For instance, previous GDP estimates treated all vehicles as of equal value, which is an inaccurate measure of capital. However, the third problem with the 2010-2011 base year data is that inflation has not been tracked properly over time in India. Even the Central Bank of India has publicly admitted that their inflation rates are inaccurate. The reason for this inaccuracy is that the consumer price index and the industrial price index have been used interchangably to calculate rates of inflation in India, and historically the two indices were positively correlated. In recent years the consumer price index has risen significantly and the industrial price index has decreased, the two indices have converged. Thus, India reports more economic growth than what has actually been occuring and inflation is lower than it is in reality. Therefore, rebasing West Bengal's 2004-2005 data into 2010-2011 data and using the rest of the 2010-2011 base year data is impossible because the WDI deflators are not the same that are used by the Central Bank in India, but are likely more accurate. Thus, the current methods have been used. 

There was a previous GDP2011 series that was used in the earliest iterations of this model. This series was simply population weighted national GDP for 2010. This gave a single year of data for model initialization and it was an estimation based upon the 186-model India data. This is no longer used because the data is ultimately not GDP and inaccurate. The current series, although estimated, is more accurate. 

GDP2011PCPPP

This series was estimated using the GDP2011 data and population data. This series is not in PPP, rather it is in 2011 rupees, thus ApplyMultAll is used to normalize the data to get the data into the proper units. 

GDPCurDol

GDP in current ten million (crore) rupees was found at the NITI Aayog website. The series runs from 2004-2014. 

GovtCurRev%GDP

This data was found in the Report of the Comptroller and Auditor General of India on State Finances and was collected from all available recent state level reports. The series was estimated using Revenues minus Grants from the Central Government divided by GDP from the same source. 

GovtCalcExpendTot%GDP

This series was found in the 

GovtPensions%GDP

This series was estimated using data from the State Finances Reports 2011-2014 using provident funds relative to GDP in current rupees from NITI Aayog.

TaxGoodSer%CurRev

This series was estimated by using data from the [[Report_of_the_Comptroller_and_Auditor_General_of_India_on_State_Finances

||Report of the Comptroller and Auditor General of India on State Finances]]. This series was estimated using taxes on sales and goods as a percentage of revenues minus grants from the Government of India relative to current revenues. 

GovtDebt%GDP

This series was found at the [[NITI_Aayog

|NITI Aayog]] website in the needed units from 2000-2015.

Xdebt

This series was estimated using data from the State Finances Reports 2011-2014 that were published by the Ministry of Finance of India and the Reserve Bank using total debt. This data is in Indian rupees and is normalized using ApplyMultAll.

XDebtPPG%GDP

Public and publicly guaranteed debt relative to GDP was estimated using data from the State Finances Reports 2011-2014 that were published by the Ministry of Finance of India and the Reserve Bank. This was estimated using table 7.14 by summing SDLs, Power Bonds, Compensation and other bonds, NSSF, and WMA from RBI relative to GDP in current rupees. Telangana and Andhra Pradesh were estimated using the 58/42 rule, which is a rule that was used to split the government debt between the two states when they were bifurcated in 2014, where 58% of the debt was attributed to Andhra Pradesh and 42% to Telangana. 

XDebtPri%TotalXDEBT

This series was estimated using data from the State Finances Reports 2011-2014 using data in table 7.14. This was estimated using the sum of Loans from Banks and other FI to total debt. Telangana and Andhra Pradesh were estimated using the 58/42 rule, which is the rule that was used to split the government debt between the two states when they were bifurcated in 2014, where 58% of the debt was attributed to Andhra Pradesh and 42% to Telangana. 

XReserves%GDP

India's subnational reserves were estimated using data from the State Finances Reports 2011-2014 using reserves and the GDP in current dollars from NITI Aayog. The reserve data in this series does not include gold reserves from the central bank, which is what this series is supposed to include, and because of this the series is normalized using ApplyMultAll to give an improved estimate of reserves. Telangana and Andhra Pradesh were estimated by the 58/42 split that was used to split the state's debt.