IFs Network Diagram

2026-03-23T14:27:51Z

Simon.Kyeremeh:

IFs Network Diagram User Documentation

What is the IFs Network Diagram?
[[File:Picture 1.png ifs.png|border|left|thumb]]

The IFs Network Diagram is an interactive visualization of the internal structure of the International Futures (IFs) model. in IFs and how they influence one another. It is a map of the IFs model’s logic. You can use it to answer questions like “What affects this variable?” or “What does this variable affect?”. Users can explore how major system sectors interact; at the variable level, they can interrogate specific influence pathways by examining drivers (inputs), outcomes (outputs), degrees of separation, and shortest paths between variables. In this way, the IFs Network Diagram functions as a transparency and learning tool, allowing users to inspect and reason about what influences what is within the IFs system, rather than treating the model as a black box.

Views

The diagram has three levels:

* Macro view: Shows the 11 major categories in IFs
[[File:Picture 2.png|left|thumb]]

*
* Use this view to see the big picture of how sectors connect

* Meso view: Shows the subcategories within each meso category and their connections

* Use this view to gain more detail without seeing every variable

* Variable view: Shows all individual variables and parameters (nodes) and their links

* Use this to explore specific variables

Macro & Meso Interactions:

* Hover over a node to see an information box (Tool Box)

* Click and drag a node to better visualize connections or move it around the screen

Basic Controls

These options control what you see in the diagram:

* Search for variables (Top Right Corner):

* Type a variable or parameter name

* Click it in the search box to highlight it in the diagram

* Zoom In / Zoom Out / Fit to Screen (Bottom Left Corner):

* Download:

* Download a .png image of the current view

* Help Panel:

* Opens pop-up with link to full instructions

Variable View

Some features are only available in Variable View:

* Toggle Layouts – switch between:

* Default: shows all selected nodes and their connections

* Shortest Path: shows the shortest path between two nodes, if they’re connected in the model

* If a node was selected in Default view, it becomes the origin node

* Use the search box to choose the end node

* Nearest Neighbor: shows all nodes that are connected to the selected root node, up to three degrees away

* Degree 1 = directly connected

* Degree 2 = connected through one intermediate node

* Degree 3 = connected through two intermediate nodes

* Use the slider to change the number of degrees shown

Interactive Menu

Use the interactive menu to control which parts of the network are visible:

* Show/Hide Interactive Menu: opens or closes the list of all nodes

* Interactive Menu:

* You can check/uncheck:

* Individual nodes

* Submodules

* Major categories

* Checked = visible

* Unchecked = grayed out in the display

* Unselect all: “Hides” (grays out) all nodes at once

* Allows you to select specific nodes of interest

* Reset: Returns to default layout for your current view

Working with Nodes

When you click on a node in the variable view, it becomes the root node. From there, you can explore what drives it and what it influences.

Node information:

* Tool box (hover)

* Appears when you hover over a node

* Shows: node name, display name, explanation, submodule, and segment

* Tool tip (click)

* Appears when you click a node (in Default view)

* Shows:

* All inputs and outputs to/from that node

* Each connection’s segment, name, and display name

* A shortest path button to jump into Shortest Path mode

Directions and degrees:

* When you select a node:

* It becomes the root node

* Drivers = inputs to the root node

* Outcomes = outputs from the root node

* Degrees = how many steps away another node is

* In the tool tip, you can filter connections:

* Both – show both inputs and outputs

* Only <- show only inputs to the selected node

* Only -> show only outputs from the selected node

Typical Workflows

# Find what affects a variable (its drivers)

# Go to variable view

# Search for the variable and click it

# In the Tool Tip, choose Only <- to see its inputs

# Find what a variable influences (its outcomes)

# Go to variable view

# Search for the variable and click it

# In the Tool Tip, choose Only -> to see its outputs

# Trace a chain of influence between two variables

# In Default, click the starting variable

# Click Shortest Path in the Tool Tip

# Use the search box to choose the end variable

# The tool will show the shortest connection pathway between them

# See all neighbors of a key variable

# Switch to Nearest Neighbor layout

# Choose your root node (or click one in Default first)

# Use the degree slider to expand from immediate neighbors to broader connections

Show Parameters

The Show Parameters button controls whether model parameters are displayed alongside variables in the Variable View.

Parameters represent adjustable model inputs that influence how variables behave in the IFs model. While variables represent outcomes calculated by the model, parameters define assumptions, coefficients, or policy settings that affect those outcomes.

When Show Parameters is turned off (default):

* Only variables are displayed in the diagram.

* The network shows relationships between model outcomes.

When Show Parameters is turned on:

* Parameter nodes appear alongside variables.

* Additional links become visible showing how parameters influence variables in the model.

This option is useful when users want to:

* Explore policy levers or assumptions that affect a variable.

* Understand how model parameters feed into the calculation of outcomes.

* Trace the influence of parameters through the network.

When parameters are displayed:

* Parameter nodes appear visually distinct from variable nodes.

* Their positions are determined by the same linkage structure as variables, ensuring that their placement reflects their relationships within the model.

'''Understanding Node Size and Linkages''' (how backward/forward linkages affect node size)

'''Understanding Arrows and Direction of Influence'''

IFs Network Diagram

2026-03-23T14:27:04Z

Simon.Kyeremeh: Images updated

File:Picture 2.png

2026-03-23T14:25:50Z

Simon.Kyeremeh:

IFS network diagram-levels

File:Picture 1.png ifs.png

2026-03-23T14:09:26Z

Simon.Kyeremeh:

This is IFS network diagram

Energy

2026-02-17T15:25:33Z

Simon.Kyeremeh: In- progress

Please cite as: Hughes, B. B., Solórzano, J., & Rothman, D. S., Irfan, R. I., Sahadevan, D. (2025, November 11). IFs energy model documentation. Pardee Center for International Futures, Josef Korbel School of Global and Public Affairs, University of Denver. [[Energy|https://pardeewiki.du.edu/index.php?title=Energy]]

1. Introduction

1.1 Overview

The International Futures system (IFs) represents energy and electricity through integrated dynamics that span multiple IFs models: energy, economy, environment, and infrastructure. It captures patterns of energy consumption and electricity use, the drivers behind them, and the production of energy from both fossil and non-fossil sources using different technologies. IFs also incorporates trade in energy, using both a pooled approach and a bilateral version. The model accounts for the environmental implications of fossil fuel use, while broader development and sustainability outcomes such as access to electricity and improved fuel use, are also represented.

Here we document the IFs energy model - a partial equilibrium model operating on physical energy, balancing consumption and production through a price variable that adjusts in response to supply-demand dynamics, with energy stocks serving as a buffer. Investment decisions are signalled by price and by cost, with cost shaped by resources, reserves, and technologies, and these dynamics in turn inform the treatment of the energy sector in the broader Economic Model. Ultimately, computations in the physical energy model feed into the Economic Model by replacing its sectoral calculations with the corresponding financial variables from the physical energy model.

Gross domestic product (GDP) from the Economic Model provides the basis for energy demand calculations. Energy demand elasticity represents the responsiveness of demand to prices, which evolve over the long run with changes in technology and resource availability. Thus, the physical constraints on the supply side are very important in determining the dynamics of the energy model.

IFs distinguishes nine energy production categories: oil, natural gas, coal, hydropower, nuclear, solar, wind, geothermal and other renewables. The other renewables category includes tidal, wave, biodiesel and biogas. For each category both conventional and unconventional sources are considered, but these have only been fully implemented for oil. Currently, the model does not generate projections for consumption or trade by specific energy types. IFs rather computes aggregated regional or national energy demands and prices, on the assumption of high levels of long-term substitutability across energy types and a highly integrated market. The model also conducts energy trade only in a single, combined energy category. Finally, at the moment, there is no full reconciliation between the production of energy and electricity generation (see the IFs

Infrastructure Model Documentation for a description of the electricity aspects of IFs).

1.2 Dominant Relations

Energy demand (ENDEM) is a function of GDP and the energy demand per unit of GDP (ENRGDP). Energy production (ENP) is a function of capital stock in each energy type, the capital/output ratio (QE) for that energy type, and a capacity utilization factor (CPUTF).

The following key dynamics are directly linked to the dominant relations:

* '''DEMAND:''' Energy demand per unit of GDP depends on GDP per capita, energy prices, and an autonomous trend in energy efficiency. The first two of these are computed endogenously, the latter exogenously. The user can control the price elasticity of energy demand ('''''elasde'''''), speed at which energy price changes affect demand ('''''ehw''''') and the autonomous trend in efficiency of energy use ('''''enrgdpgr'''''). The user can also use an energy demand multiplier ('''''endemm''''') to directly modify energy demand.

* '''PRODUCTION''': For fossil fuels and hydro, there are upper bounds on production. For fossil fuels, these are based on reserve-to-production ratios, as well as user-specified upper bounds ('''''enpoilmax''''', '''''enpgasmax''''', and '''''enpcoalmax'''''). For hydro, the upper bound relates to hydropower potential. The model user can also control production using an energy production multiplier ('''''enpm''''') to directly modify energy production by energy type. The user may also indirectly increase energy production through additional investment ('''''eninvm'''''), which will incorporate economic trade-offs. In contrast, a production multiplier ('''''enpm''''') comes without any cost to increased production.For renewable categories other than hydro, the model uses potential capacity ('''''resor''''') in lieu of reserves or resources. This reflects availability or potential based on data or estimated from drivers such as land area. Unlike fossil fuels, where '''''resor''''' represents finite physical resources that directly constrain production, renewable potentials are effectively unlimited; instead of setting an upper bound, they influence capital costs and investment dynamics.

* '''CAPITAL/OUTPUT RATIO''': The capital/output ratio provides a measure of production cost, with declines reflecting efficiency gains and reduced capital intensity. User-controllable parameters ('''''etechadv''''' and '''''etechadvuncon'''''), applied to each fuel type, implement these cost declines due to technological improvements at the global level. For fossil fuels, this is counteracted by a factor that increases the capital/output ratio as the amount of remaining resources decreases. The user can further modify the capital/output ratios with the multipliers ('''''qem''''' and '''''qeunconm''''').For renewable energy sources such as wind, solar, and geothermal, the capital/output ratio is equivalent to the levelized cost of electricity (LCOE) generation from these sources, though users can still modify capital output ratios with multipliers ('''''qem''''' and '''''qeunconm'''''). These energy sources are primarily used to generate electricity (except for geothermal, which can also provide direct heat).<sup>[1]</sup>

* '''CAPITAL:''' Energy capital, by fuel type, is initialized based on the initial levels of production and capital/output ratios. Energy capital depreciates at a rate determined by the lifetime of energy capital ('''''lke''''') and grows with investment. Total desired investment in energy capital is influenced by many factors, including existing capital, domestic and global energy demand, the production of other renewables, changes in the global capital/output ratio, world and domestic energy stocks, expected overall profits in the energy sector, and imports. Users can control the effect of expected profits ('''''eleniprof''''' and '''''eleniprof2''''') and world energy stocks ('''''elenpr''''' and '''''elenpr2'''''). Desired investment by energy type increases with individual profit expectations, but also by limits related to reserve production factors (for fossil fuels and hydro), any exogenous restrictions on maximum production (for fossil fuels), ultimate potential (for hydro), and other, unspecified factors (nuclear). Users can influence the effect of profit expectations by fuel type (via '''''elass''''') as well as influence the desired investment by energy type ('''''eninvtm'')''', or in the aggregate (via '''''eninvm'''''). The user can also specify an exogenous growth rate for energy investment by fuel type ('''''eprodr'''''). The Economic Model ultimately determines whether all of the investment needs can be met; in case of shortfalls, the investment in each type of energy is reduced proportionately.

* '''RESOURCES/RESERVES/STOCKS''': IFs separately represents ultimate resources and reserves, where the latter are the amount of energy resources available to be produced. Resources and reserves, both conventional and unconventional, are set in the pre-processor. The user can modify the default assumptions on ultimate resources, either directly ('''''resor''''', '''''resoruncon''''') or via the use of multipliers ('''''resorm''''', '''''resorunconm'''''). Reserves decline with production and increase with discoveries. The rate of discovery depends on the ultimate resources remaining, the intensity of current production, world energy prices, and a base rate of discovery ('''''rdi'''''). The user can control the effect of world prices on discovery ('''''elasdi'''''), augment the base rate of discovery ('''''rdinr'''''), and use a multiplier to affect the rates of discovery ('''''rdm'''''). Finally, IFs keeps track of any production not used in the current year, i.e., stocks, and shortages.

* '''ENERGY PRICES''': Domestic energy prices are influenced by world stocks, domestic stocks, and the ratio of capital to production at the global level. The user can control the effect of domestic stocks on prices ('''''epra''''' and '''''eprafs'''''). Users can also include a “cartel premium” ('''''encartpp''''') and a carbon tax ('''''carbtax'''''). More directly users can set domestic energy prices exogenously for just the first year ('''''enprixi''''') or for multiple future years ('''''enprix'''''). The world energy price is calculated as a weighted sum of the domestic prices.

* '''TRADE''': The energy model also provides representation and model-user control over energy trade. The levels of imports (ENM) and exports (ENX), measured in physical terms (bboe), depend upon levels of production and demand, as well as past propensities to import and export energy. The user can set maximum limits on of energy imports ('''''enml''''') and energy exports ('''''enxl'''''), as well as general limits on trade ('''''trademax''''').

----<sup>[1]</sup> Conventional sources refer to oil extracted through standard drilling methods, while unconventional sources include those requiring advanced techniques such as shale oil extraction.

<sup>[2]</sup> LCOE is expressed as the cost per kilowatt-hour of electricity generated and is computed by dividing the total electricity produced over the lifetime of a plant by the sum of its capital costs, operations, and maintenance expenditures (IRENA, 2024). We will revisit the implications of variable renewable energy (VRE), including system integration costs and their effect on capital/output ratios in more detail later.

'''1.3 Structure and Agent System'''

''Table 1: Model Structure and Agent System.''
{| class="wikitable"
|'''System/Subsystem'''
|Energy
|-
|'''Organizing Structure'''
|Partial market
|-
|'''Stocks'''
|Capital, resources, reserves

|-
|'''Flows'''
|Production, consumption, trade, discoveries, investment
|-
|'''Key Aggregate Relationships'''

(Illustrative, not comprehensive)
|Production function with exogenous technology change;

Energy demand relative to GDP;

Price determination
|-
|'''Key Agent-Class'''

'''Behavior Relationships'''

(Illustrative, not comprehensive)
|Government taxes, subsidies
|}

2.'''Flow Charts'''

This section presents several block diagrams that are central to the energy model: an energy system overview, energy production and energy consumption.

2.1 '''Energy Overview'''

The production growth process in energy is simpler than that in Agriculture or the full Economic Model. Because energy is a very capital-intensive sector, production depends only on capital stocks and changes in the capital-output ratio, which represents technological sophistication and other factors (such as decreasing resource bases) that affect production costs.

The key equilibrating variable is again inventories. It works via investment to control capital stock and therefore production, and via prices to control domestic consumption. Production and consumption, in turn, control trade. Specifically, as inventories rise, investment falls, restraining capital stock and energy production, and thus holding down inventory growth. As inventories rise, prices fall, thereby increasing domestic consumption, which also holds down inventory growth.

''Figure 1: IFs Energy Model Overview.''

2.2 '''Energy Production Detail'''

Energy production is computed from the capital stock invested in energy and the capitaloutput ratios, adjusted by a capacity utilization factor and bounded by production limits specific to each energy type. Exogenous parameters allow users to modify both the drivers of production and the production volumes themselves. The capital-output ratios are affected by the amount of remaining resources as a share of the initial levels, technological progress, and user-controlled multipliers. The capacity utilization factor is influenced by domestic stocks and shortages.

''Figure 2: Energy Production in IFs''

2.3 '''Energy Capital and Investment Detail'''

The capital stock by energy type decreases through depreciation and grows with new investment. Investment growth in the capital stock, though influenced by several factors, is driven primarily by energy profits and existing stocks. It can be adjusted through a user-defined scenario multiplier and is capped by production constraints linked to reserves availability for fossil fuels and resource potential for renewables. The user can use a direct multiplier on total energy investment, multipliers on energy investment by energy type to influence investment or specify a desired rate of growth in investment by energy type.

For renewable energy sources like wind, solar and geothermal, the capital-output rations are tied to the levelized cost of electricity (LCOE). In case of variable renewable energy (VRE) sources such as solar and wind, there comes an additional set of challenges associated with intermittency, dispatchability and storage. For renewables, the capital– output ratio corresponds to the LCOE with adjustments for system integration costs such as transmission, storage, and balancing in the case of variable renewables. Addressing these challenges requires additional expenditures on transmission, distribution, and balancing capacity. LCOE data published in the literature does not always incorporate such system integration costs, which can be substantial at higher penetration levels of VRE and also affect production costs (Hirth et al., 2015; Ueckerdt et al., 2013).

If these additional system costs are not considered, the model’s forecasts for such renewable sources may overestimate the pace of cost reductions driven by technological learning and economies of scale, while at the same time underestimating the true investments required for large-scale deployment of wind and solar power.

''Figure 3: Energy Capital and Investment in IFs''

'''2.4 Energy Demand Detail'''

Energy demand is estimated as a function of the energy demand per unit GDP (in PPP terms) and total GDP (in PPP terms), with adjustments related to energy prices and improvements in energy use efficiency. The energy demand per unit GDP depends on GDP per capita (in PPP Terms). The improvement in energy use efficiency is a combination of autonomous trend in efficiency of energy use ('''''enrgdpgr''''') and an additional amount that accelerates the improvements for (non-exporting) countries that have efficiencies below the global average. The price effect takes into account both the domestic and global prices of energy, as well as any carbon tax ('''''carbtax'''''). The user can control the price elasticity of energy demand ('''''elasde''''') and the historical weight used to smooth energy prices ('''''ehw'''''). Finally, the user can also use an energy demand multiplier ('''''endemm''''') to directly modify energy demand.

''Figure 4: Energy Demand in IFs''

2.5 '''Energy Resources and Reserves Detail'''

IFs distinguishes between ultimate resources and reserves, where the latter represent the amount of energy actually discovered and available for production. Ultimate resources are initially determined in the pre-processor, but the user can override these estimates using either absolute values (resor, resoruncon) or multipliers (resorm, resorunconm). There is also a parameter controlling the portion of unconventional oil that is economic to produce (enresunce). For non-renewable energy types, i.e., fossil fuels, reserves increase with discoveries and decrease with production. The rate of discovery includes a base rate (rdi) and an annual increment (rdinr). There are further adjustments related to the world energy price, the remaining resources, and the current rate of production. The user can control the effect of world prices on discovery (elasdi) and can also intervene with a discovery multiplier (rdm).

''Figure 5: Energy Resources and Reserves in IFs''

3.'''Equations'''

This section will present and discuss the equations that are central to the functioning of the energy model: supply, demand, trade, stocks, price, investment, economic linkages, capital, natural resources and energy indicators. Here we follow the order of calculations in all years but the first, noting specific calculations that are made in the first year or preprocessor as necessary. A table has been added as an appendix to this document, linking the variables to the historical data series used to initialize them.

'''3.1''' '''Energy Demand'''

The key energy demand variable in IFs, ENDEM, tracks total primary energy demand. For the most part, IFs does not represent the transformation of this primary energy into final energy forms, or end-user energy demand. The one exception relates to electricity use, which is described in the documentation of the Infrastructure Model.

In the first year, total primary energy demand is calculated as an apparent demand based on a balancing equation that equates energy demand with supply, defined as production plus net trade, and a balancing energy stock. While the supply side is obtained from historical data, the initial value for the stock is estimated from an aggregate stock base, obtained by adding demand and supply, on which a desired stock level (dstlen, 10% by default) is applied and then augmented by the expected growth in production following standard practice in storage planning.

𝐸𝑁𝑆𝑇<sub>𝑟,𝑡=1</sub> = (∑<sub>𝑒</sub> 𝐸𝑁𝑃<sub>𝑟,𝑒,𝑡=1</sub> + 𝐸𝑁𝐷𝐸𝑀𝐸𝑠𝑡<sub>𝑟</sub>) ∗ 𝑑𝑠𝑡𝑙𝑒𝑛 <sup>[1]</sup>

𝐸𝑁𝐷𝐸𝑀𝑟,𝑡=1 = ∑<sub>𝑒</sub> 𝐸𝑁𝑃𝑟,𝑒,𝑡=1 + 𝐸𝑁𝑀𝑟,𝑡=1 − 𝐸𝑁𝑋𝑟,𝑡=1 − 𝐸𝑁𝑆𝑇𝑟,𝑡=1 ∗ 𝐴𝑉𝐸𝑃𝑅𝑟,𝑡=1

''Where,''

• ''ENP'', ''ENM'', ''ENX'', ''ENST'', and ''AVEPR'' are energy production, energy imports, energy exports, estimated energy stocks, and an average of the expected growth in production across all energy types (e) for a country, or region (r) in the first year (t) of the projection horizon. The calculations of the initial values of these variables are described later in the Equations section under the appropriate headings.

Note that this calculation does not directly use the historical data on total primary energy demand and there can be a significant difference between the initialized value of ENDEM and the actual historical data for the base year. This information is used by the variable ENDEMSH, which is described in the Infrastructure documentation.

In future years, the calculation of total primary energy demand begins with an estimate of the predicted amount of energy demand per unit of GDP (in PPP terms), compendemperunit, as a function of GDP per capita (in PPP terms).<sup>[4]</sup> This function is show in the figure below<sup>[5]</sup>
----<sup>[3]</sup> Since energy demand is not yet computed for the first year, an estimate (ENDEMEst) is obtained from the energy balance equation, with the stock term based solely on the supply side.

<sup>[4]</sup> Here, IFs uses GDP from the previous time cycle, with an estimate of growth, to calculate GDPPCP, because the recursive structure of IFs computes current GDP later. The current value of population, POP, has already been computed at this stage.

<sup>[5]</sup> The exact equation is compendemperunit = 0.0023428 -0.0003878*ln(GDPPCP).

''Figure 6: Relationship between compendemperunit and GDP per capita''

A small amount, 0.0005 barrels of oil equivalent (boe), is added to this computed value to account for the fact that the demand data used to estimate the function above is less than apparent demand globally.

The initial data for countries is unlikely to fall exactly on this function. To reconcile this fact, IFs calculates values for both predicted energy demand per unit GDP in the first year, compendemperuniti, and empirical demand per unit GDP (in PPP terms) in the first year, actendemperuniti.<sup>[6]</sup> Over a time period of 75 years, controlled by the parameter '''''enconv''''', IFs gradually adjusts the difference between these two values so that the estimate of energy demand per unit GDP (in PPP terms) eventually does fall on the function.

IFs then calculates an initial estimate of total energy demand, endemba, by multiplying this adjusted value of energy demand per unit GDP (in PPP terms), endemperunit, by GDP (in PPP terms).<sup>[7]</sup>
----<sup>[6]</sup> There is also an adjustment to the empirical demand that occurs during the initialization. Due to data inconsistencies and/or the exclusion of non-traded energy sources such as traditional biomass from production data, energy demand initialized using the balance method described above can turn out to be very low for some countries. The initialization code adjusts the base-year ENDEM for such cases to ensure that energy demand per unit of GDP at PPP is not less than a fifth of the value computed using the energy intensity function.

<sup>[7]</sup> IFs uses GDP from the previous time cycle here, because the recursive structure of IFs computes current GDP later.

IFs then considers the effect of price on total primary energy demand. IFs keeps track of the global energy price as both an index (WEP, base year = 100) and as an actual dollar value (WEPBYEAR, $ per BBOE). It also tracks a country level energy price index<div id="ftn2"><div id="ftn2">
(ENPRI, base year =100). Finally, it can also consider a tax on carbon, expressed by the variable CarTaxEnPriAdd, which has the units $ per BBOE.

The calculation of the effect of prices on total energy begins with the calculation of a variable called renpri. renpri is a moving average country-level price index that starts at the level of the country level price index in the base year, ENPRII, and then tracks changes in world energy prices and country-level carbon taxes. The historical weight is controlled by the parameter ehw, so that:

renpri<sub>𝑟,𝑡</sub> = 𝒆𝒉𝒘 ∗ renpri<sub>𝑟,𝑡−1</sub> + (1 − 𝒆𝒉𝒘)

(𝑊𝐸𝑃𝑡−1+CarTaxEnPriAdd𝑟,𝑡−1∗𝑊𝐸𝑃𝑡=1

𝑊𝐸𝑃𝐵𝑌𝐸𝐴𝑅𝑡=1)
</div></div>''where''

• ''renpri'' is the moving average country level price index

• '''''ehw''''' is the weight given to the historical value of renpri

• ''WEP'' is the global energy price index

• ''WEPBYEAR'' is the global energy price in $ per BBOE

• ''CarTaxEnPriAdd'' is the country level carbon tax in $ per BBOE of total energy and is calculated as the exogenous value of the carbon tax in $ per ton of carbon, '''''carbtax''''', times a production weighted average of the carbon contents of oil, gas, and coal, '''''carfuel<sub>e</sub> , where e is 1-3''''':

∑<sub>𝑒</sub>(𝐸𝑁𝑃<sub>𝑟,𝑒</sub> ∗ 𝒄𝒂𝒓𝒇𝒖𝒆𝒍<sub>𝒆</sub>)

CarTaxEnPriAdd<sub>r</sub> = ∗ 𝒄𝒂𝒓𝒃𝒕𝒂𝒙<sub>𝒓</sub>

<sub> ∑𝑒 𝐸𝑁𝑃𝑟,𝑒</sub>

The parameter specifying the price elasticity of energy demand, '''''elasde''''', is adjusted based on the relationship between renpri and and ENPRII to yield a new parameter, elasadjusted.

𝐸𝑁𝑃𝑅𝐼𝐼<sub>𝑟</sub>

elasadjusted<sub>r</sub> = 𝒆𝒍𝒂𝒔𝒅𝒆<sub>𝒓</sub> ∗

renpri<sub>𝑟</sub>

== <span style="font-size:x-large;">Energy Supply</span> ==

<span>The computation of energy production (ENP) is considerably easier than that of gross sectoral production in the economic model or of agricultural production in the agricultural model.  Only capital is considered important as a factor of production (not labor, land, or even weather).  Energy production is initially estimated by dividing the quotient of capital in each energy category (ken) and the appropriate capital-to-output ratio (QE).  A multiplier, '''''enpm'' ''', can be used to increase or decrease production.  This yields:</span>

:<math>ENP1_{r,e}=\frac{ken_{r,e}}{QE_{r,e}}*\mathbf{enpm_{r,e}}</math>

The dynamics of the capital-to-output ratios, QE, are discussed in [[Energy#Resources_and_Reserves:_Capital-to-Output_Ratios_and_Discoveries|this section]].

<span>Known reserves (RESER) and exogenously specified maximums pose constraints on production of certain energy types.  The affected energy types are oil, gas, coal, and hydro.  The impact of reserves is felt via a limit on the fraction of reserves that can be produce in any year. Specifically, the reserve-to-production ratio may not fall below the value of '''''prodtf'' ''', which is initially set in the pre-processor, but can be overridden by the user.  In addition, as the actual reserve-to-production ratio approaches this limit, its rate of decrease is limited.  The exogenously specified maximums apply only to oil, gas, and coal, and are given by the parameters '''''enpoilmax'' ''', '''''enpgasmax'' ''', and '''''enpcoalmax'' '''.  This yields a second estimate for energy production, given as:</span>

:<math>ENP2_{r,e}=MIN(\frac{RESER_{r,e}}{MAX(\mathbf{prodtf}_{r,e},sResProdR_{r,e}-1)},enpmax_{r,e})</math>

''where''

*e only applies to oil, gas, coal, and hydro
*''enpmax'' takes on the value '''''enpoilmax'' ''', '''''enpgasmax'' ''', and '''''enpcoalmax'' ''',depending upon the fuel.
*sResProdR is the reserve-to-production ratio from the previous year; this limit only takes effect when sResProdR falls below 30 and remains above '''''prodtf'''''

IFs then selects the minimum of ENP1 and ENP2 as the estimate of energy production ENP.  The dynamics of energy reserves are discussed in [[Energy#Resources_and_Reserves:_Capital-to-Output_Ratios_and_Discoveries|this section]].

Two final adjustments are made to energy production.  The first accounts for capacity utilization, ''CPUTF'', and the second only comes into play when a restriction is placed on energy exports.  Since these are not calculated until the calculation of energy stocks and shortages, they are described in the appropriate places in the [[Energy#Domestic_Energy_Stocks|Domestic Energy Stocks]] section and the [[Energy#Energy_Prices_and_Final_Adjustments_to_Domestic_Energy_Stocks_and_Capacity_Utilization|Energy Prices and Final Adjustments]] section. 

== <span style="font-size:x-large;">Energy Trade</span> ==

The energy model in IFs keeps track of trade in energy in physical quantities; the trade in energy in monetary terms is handled in the economic model.  As opposed to the agricultural model, where trade in crops, meat, and fish are treated separately, the energy model considers trade in energy in the aggregate.  Furthermore, it only considers production from oil, gas, coal, and hydro as being available for export.  Finally, as with other aspects of trade, IFs uses a pooled trade model rather than representing bilateral trade.

The first estimate of energy imports and exports by country are determined based upon a country’s propensity to export, propensity to import, and moving averages of its energy production and demand.

The moving average of energy production, identified as smoothentot, is calculated simply as a moving average of production of energy from oil, gas, coal, and hydro. In the first year of the model:

:<math>smoothentot_{r,t=1}=EnTot_{r,t=1}=\sum_eENP_{r,e,t=1}</math>

''where''

*e is oil, gas, coal, and hydro

In future years,

:<math>smoothentot_{r,t}=0.9*smoothentot_{r,t-1}+0.1*\sum_eENP_{r,e,t}</math>

''where''

*e is oil, gas, coal, and hydro

The moving average of energy demand, identified as smoothpendem has a few more nuances, particularly after the first year.  In the first year, IFs calculates:

:<math>smoothpendem_{r,t=1}=ENDEM_{r,t=1}</math>

In future years, rather than using the value of ENDEM calculated earlier, the model uses a slightly different measure of energy demand, referred to as pendem.  pendem differs from ENDEM in two main ways:

1. rather than using the moving average country-level price index, renpri, to calculate the effect of prices on energy demand, it uses only current values:

:<math>PEnPri_{r,t}=WEP_{t-1}+CarTaxEnPriAdd_{r,t-1}*\frac{WEP_{t=1}}{WEPBYEAR_{t=1}}</math>

2. it does not include the additional boost in energy efficiency beyond '''''enrgdpr'' ''' in calculating the autonomous changes in energy efficiency

Thus, in future years, we have

:<math>smoothpendem_{r,t}=0.8*smoothpendem_{r,t-1}+0.2*pendem_{r,t}</math>

A country’s propensities to import and export energy are given by the variables MKAVE and XKAVE.  These are moving averages of the ratios of imports to an import base related to energy demand and exports to an export base related to energy production and demand, respectively.  MKAVE is initialized to the ratio of energy imports to energy demand in the first year.  A maximum value, MKAVMax is also set at this time to the maximum of 1.5 times this initial value or the value of the parameter '''''trademax'' '''.  XKAVE is initialized to the ratio of energy exports to the sum of energy production from oil, gas, coal and hydro and energy demand from all energy types in the first year.  Its maximum value, XKAVMAX is set to the maximum of this initial value and the parameter '''''trademax'' '''.  The updating of MKAVE and XKAVE occur after the calculation of imports and exports, so we will return to that at the end of this section.

The initial estimates of energy exports, ENX, and energy imports, ENM, are calculated as:

:<math>ENX_r=MIN(XKAVE_r,XKAVMAX_r)*exportbase_r</math>

:<math>ENM_r=MIN(MKAVE_r*pendem_r,MKAVMAX_r*smoothpendem_r)</math>

''where''

:<math>exportbase_r=smoothentot_r+smoothpendem_r</math>

At this point, IFs makes some adjustments to energy imports and exports depending upon whether a country is considered in energy surplus or deficit.  Where a country sits in this regard involves considering domestic and global stocks in addition to current production and demand.

Domestic energy stocks are computed as the sum of stocks carried over from the previous year, while also considering any shortages

:<math>stocks_{r,t}=ENST_{r,t-1}-ENSHO_{r,t-1}</math>

A stock base is also calculated as 

<math>StBase_r=smoothpendem_r+smoothpendemr</math>

The ratio of stocks to StBase can be defined as domesticstockratio. A moving average of a trade base, smoothtradebase, is also calculated for each country:

:<math>smoothtradebase_{r,t}=MAX(ENDEM_r,0.9*smoothtradebase_{r,t-1}+0.1*2*(ENX_r+ENM_r))</math>

''where''

:<math>smoothtradbase_{r,t+1}=MAX(ENDEM_{r,t=1},2*(ENX_{r,t=1}+ENM_{r,t=1}))</math>

Global energy stocks, GlobalStocks, and the global stock base, GlobalStBase, are the sum of the domestic stocks and stock bases across countries, and the value of the globalstockratio is defined as GlobalStocks divided by GlobalStBase.

For each country, the level of deficit or surplus, endefsurp, is calculated as:

:<math>endefsurp_r=(globalstockratio-domesticstockratio_r)*StBase_r</math>

This implies that if a countries stock ratio is less (greater) than the global average, it is considered in deficit (surplus).

If a country is in deficit, i.e., endefsurp > 0, IFs will act to reduce its exports and increase its exports.  The recomputed value of exports is:

:<math>ENX_r=MAX(0.5*ENX_r,ENX_r*(1-\frac{endefsurp_r}{smoothtradebase_r}))</math>

In words, the decrease in energy exports is determined by the ratio of the level of deficit to the smoothed trade base, but can be no greater than 50 percent.

The recomputed value of imports is:

:<math>ENM_r=ENM_r*(1+\frac{endefsurp_r}{smoothtradebase_r})</math>

with a maximum level given as:

:<math>ENMMax_r=ENM_r+(\frac{pendem_r*MKAVMAX_r-ENM_r}{5})</math>

Similarly, if a country is in surplus, i.e., endefsurp < 0, IFs will act to increase exports and reduce imports.  The amount of increase in exports is controlled, in part, by the exchange rate for the country, EXRATE, specifically its difference from a target level of 1 and its change from the previous year.  As with other adjustment factors of this type, the ADJSTR function is used, yielding a factor named mul.  After first multiplying ENX by a value that is bound from above by 1.05 and from below by the maximum of 0.95 and mul, the recomputed value of ENX is:

:<math>ENX_r=ENX_r*(1-\frac{endefsurp_r}{smoothtradebase_r})</math>

Here, a maximum level is given as:

:<math>ENXMax_r=ENX_r+(\frac{exportbase_r*XKAVMAX_r-ENX_r}{5})</math>

''where'' this maximum value is computed prior to the adjustments to ENX noted above.

The recomputed value of imports is:

:<math>ENM_r=MAX(0.5*ENM_r,ENM_r*(1+\frac{endefsurp_r}{smoothtradebase_r}))</math>

In words, the decrease in energy imports is determined by the ratio of the level of surplus to the smoothed trade base, but can be no greater than 50 percent.

Because of the frequent use and importance of government trade restrictions in energy trade, model users may want to establish absolute export ('''''enxl'' ''')  or import ('''''enml'' ''') limits, which can further constrain energy exports and imports.  An export constraint may also affect the production of oil and gas as described in the next section.

As it is unlikely that the sums of these values of ENX and ENM across countries will be equal, which is necessary for trade to balance.  To address this, IFs computes actual world energy trade (WET) as the average of the global sums of exports and imports.

:<math>WET=\frac{\sum_rENX_r+\sum_rENM_r}{2}</math>

and recomputes energy exports and imports, as:

:<math>ENX_r=WET*\frac{ENX_r}{\sum_rENX_r}</math>

:<math>ENM_r=WET*\frac{ENM_r}{\sum_rENM_r}</math>

This maintains each country’s share of total global energy exports and imports.

IFs can now update the moving average export (XKAVE) and import (MKAVE) propensities for the next time step.  This requires historic weights for exports ('''''xhw'' ''') and imports ('''''mhw'' '''), yielding the equations:

:<math>XKAVE_{r,t+1}=XKAVE_r*\mathbf{xhw}+(1-\mathbf{xhw})*\frac{ENX_r}{exportbase_r}</math>

:<math>MKAVE_{r,t+1}=MKAVE_r*\mathbf{mhw}+(1-\mathbf{mhw})*\frac{ENM_r}{smoothpendem_r}</math>

A further adjustment is made related to the import propensity, MKAVE, related to the difference between this propensity and a target level, ImportTarget, and the change in this difference since the previous year.  This target starts at the level of MKAVE in the first year and gradually declines to 0 over a 150 year period.  As in many other situations in IFs, this process makes use of the ADJUSTR function to determine the adjustment factor.  The value of mulmlev is not allowed to exceed 1, so its effect can only be to reduce the value of MKAVE.

Finally, XKAVE and MKAVE are checked to make sure that they do not exceed their maximum values, XKAVMAX and MKAVMAX, respectively.

[1] The previous year’s values of WEP and CarTaxEnPriAdd are used as the current year’s values are not calculated until later in the model sequence. 

== <span style="font-size:x-large;">Domestic Energy Stocks</span> ==

<span>IFs sets a target for energy stocks in each country as a fraction of a domestic stock base, StBase, which was defined earlier as the sum of a moving average of energy demand, smoothpendem, and a moving average of the production of oil, gas, coal, and hydro, smoothentot.  This fraction is defined by the parameter '''''dstlen'' '''.</span>

<span>Stocks are initialized in the first year as '''''dstlen'' '''multiplied by the initial domestic stock base, which is the sum of production of all energy types and an estimated value of apparent energy demand.</span>

:<math>ENST_{r,t=1}=\mathbf{dstlen}*(\sum_cENP_{r,e,t=1}+ENDEMEst_{r,t=1})</math>

''where''

*e includes all energy types
*ENDEMEst is calculated as:

:<math>ENDEMEst_r=(1-\mathbf{dstlen}*AVEPR_r)*\sum_eENP_{r,e,t=1}+ENM_{r,t=1}-ENX_{r,t=1})</math>

''where''

*e includes all energy types
*AVEPR is a weighted average energy production growth rate

In future years, IFs begins by summing the moving average energy demand, smoothpendem, across countries, storing this value as WENDEM and the same for moving average energy production from oil, gas, coal, and hydro, smoothentot, which it stores as WorldEnp.  It also sums the moving average energy demand just for countries that have low propensity for exports, XKAVE < 0.2, and stores this value as WEnDemIm.

At this point, IFs adjusts energy production by multiplying by a capacity utilization factor, CPUTF, which is assumed to be the same for all energy types in a country.

:<math>ENP_{r,e}=ENP_{r,e}*CPUTF_r</math> [1]

The value of CPUTF is initialized to 1 in the first year.  How it changes in time is described in the next section after the description of the calculation of the domestic price index.

An initial estimate of energy stocks, ENST, is then calculated as the previous year’s stocks augmented by production and imports and reduced by use and exports

:<math>ENST_r=ENST_{r,t-1}+-ENDEM_r-ENX_r</math>

If after this calculation, there are excess stocks, i.e., ENST > '''''dstlen'' ''' * StBase, and there is an export constraint, given by '''''enxl'' ''', adjustments are made to the production of oil and gas<sup>[2]</sup>, and, in turn, to energy stocks.  The total reduction in oil and gas production is given as the amount of excess stocks, with a maximum reduction being the total amount of oil and gas production.  This total amount of reduced production is then shared proportionately between oil and gas.  The total reduction is also removed from ENST.

Later, after the determination of prices, ENST is modified to: 1) ensure that they are not less than zero and 2) to account for any global shortfalls.  These modifications are described in the next section.
<div>
----
<div id="ftn1">
[1] This is the first of the two adjustments to energy production noted at the end of the [[Energy#Energy_Supply|Energy Supply]] section.

[2] This is the second of the two adjustments to energy production noted at the end of the [[Energy#Energy_Supply|Energy Supply]] section.
</div></div>
== <span style="font-size:x-large;">Energy Prices and Final Adjustments to Domestic Energy Stocks and Capacity Utilization</span> ==

<span>IFs keeps track of separate domestic, ENPRI, and world, WEP, energy price indices, that apply to all forms of energy.  These are initialized to a value of 100 in the first year.  It also tracks the world energy price in terms of dollars per BBOE, WEPBYEAR, which is initialized as a global parameter.</span>

<span>A number of pieces are needed for the calculation of energy prices.  These include a world stock base, wstbase, world energy stocks, wenst, world energy production by energy type, WENP, world energy capital, WorldKen, and a global capital output ratio, wkenenpr.  These are calculated as follows:</span>

:<math>wstkbase=\sum_rStBase_r</math>

:<math>wenstks=\sum_r(ENST_r-ENSHO_{r,t-1})</math>

:<math>WENP_e=\sum_rENP_{r,e}</math>

:<math>WorldKen=\sum_r\sum_e(ken_e*\frac{CPUTF_r}{MAX(5,\mathbf{lke_e})})</math>

:<math>wkenenpr=\frac{WorldKen}{WorldEnp}</math>

''where''

*ENSHO is domestic energy shortage (described below)
*ken is capital for each energy type
*'''''lke'' ''' is the average lifetime of capital for each energy type

<span>In cases when at least one country has an exogenous restriction on the production of oil, i.e., enpm(oil) < 1 for at least one country, a few additional variables are calculated:</span>

:<math>GlobalShortFall=\sum_r\sum_eMax(0,ENP_{r,e,t-1}-1.05*ENP_{r,e,t})</math>

:<math>WorldEnProd=\sum_eWENP_e</math>

:<math>ShortFallSub=GlobalShortFall*MIN(10,\frac{WorldEnProd}{WENP(oil)})</math>

<span>Otherwise these three variables all take on a value of 0.</span>

<span>These values are used to calculate an adjustment factor driven by global energy stocks that affects domestic energy prices.  The effect in the current year, wmul, is calculated using the ADJSTR function, which looks at the difference between world energy stocks, wenstks and the desired level, given by '''''dstlen'' ''' * wstbase, and the change in world energy stocks from the previous year.  The presence of an exogenous restriction on the production of oil has two effects on the calculation of wmul.  First, the value of ShortFallSub affects the two differences that feed into the ADJSTR function.  Second, the elasticities applied in the ADJSTR function are tripled.</span>

<span>The adjustment factor calculated in the current year is not applied directly to the calculation of domestic energy prices.  Rather, a cumulative value, cumwmul, is calculated as:</span>

:<math>cumwmul_t=cumwmul_{t-1}*(1+(wmul-1)*\mathbf{eprohw})</math>

<span>Other factors affect the domestic energy price index – domestic energy stocks, possible cartel price premiums, '''''encartpp'' ''', the first year value of the world energy price index, IWEP, changes in the global capita output ratio from the first year, whether the user has set a global energy price override. '''''enprixi'', '''and whether there are any restriction on oil production.</span>

<span>The domestic energy stocks affect a country-specific “markup” factor, MarkUpEn.  This starts at a value of 1 and changes as a function of the value of mul, which is calculated using the ADJSTR function.  Here the differences are those between domestic energy stocks and desired stocks, given as '''''dstlen'' ''' * StBase, and the changes in energy stocks from the previous year.  Shortages from the previous year are also taken into account.  The user can also control the elasticities used in the ADJSTR function with the parameters '''''epra'' ''' and '''''eprafs'' '''.  This markup evolves over time as</span>

:<math>MarkUpEn_{r,t}=MarkUpEn_{r,t-1}*mu</math>

<span>The domestic energy price index, ENPRI, is first calculated as:</span>

:<math>ENPRI_r=\mathbf{X}*mul_r*cumwmul+\mathbf{encartpp}</math>

''where''

*'''X''' = '''''enprixi'', '''when this parameter is set to a value greater than 1 and IWEP otherwise

It is then recomputed as:

:<math>ENPRI_r=MIN(ENPRI_r,ENPRI_{r,t-1}+\mathbf{encartpp}_t-\mathbf{encartpp}_{t-1}+\mathbf{X})</math>

''where''

*'''X''' is 100 whenthere is a restriction on oil production in at least one country and 20 otherwise

Furthermore, ENPRI is not allowed to fall by more than 10 in a given year.

It is possible for the user to override this price calculation altogether.  Any positive value of the exogenous country-specific energy price specification ('''''enprix'' ''') will do so.

It is only now that a country’s energy stocks and shortages are finalized for the current year.  If ENST is less than 0, then a shortage is recorded as ENSHO = -ENST and ENST is set to 0.  In addition, for countries that have a low propensity for exports, XKAVE < 0.2, a share of any global shortfall is added to their shortage, with the share determined by the country’s share of moving average energy demand among those countries:

:<math>ENSHO_r=ENSHO_r+GlobalShortFall*\frac{smoothpendem_r}{WEnDemIm}</math>

The energy shortage enters the Economic model in the calculation of gross sectoral production.

The same differences in domestic stock from their target level and their change since the previous year, taking into account shortages from the previous year, are used to update the value of capacity utilization in energy, CPUTF, which was introduced earlier.  The multiplier affecting CPUTF, Mul, is calculated using the ADJSTR function, with elasticities given by '''''elenpst'' ''' and '''''elenpst2'' '''.  In addition, the capacity utilization is smoothed over time.

:<math>CPUTF_{r,t}=0.5*CPUTF_{r,t-1}+0.5*Mul</math>

This value is further assumed to converge to a value of 1 over a period of 100 years and is bound to always have a value between 0.2 and 2.

This still leaves the need to calculate the world energy price.  IFs actually tracks a world price including carbon taxes, WEP, and a world price ignoring carbon taxes, WEPNoTax.  Carbon taxes are ignored in cases where the energy price is set exogenously using '''''enprix'' '''.

In both cases, the world energy price is a weighted average of domestic energy prices:

:<math>WEP=\frac{TENP}{TENPRI}</math>

:<math>WEPNoTax=\frac{TENP}{TENPRINoTax}</math>

''where''

:<math>TENP=\sum_r\sum_eENP_{r,e}</math>

:<math>TENPRINoTax=\sum_r\sum_e(ENPRI_r*ENP_{r,e})</math>

:<math>TENPRI=\sum_r\sum_e((ENPRI_r+CarTaxEnPriAdd_r*\frac{WEP_{t=1}}{WEPBYEAR_{t=1}})*ENP_{r,e})</math>

''where''

*WEP and WEPBYEAR convert CarTaxEnPriAdd from $/BBOE to an index value
*the term with CarTaxEnPriAdd is ignored in countries with exogenous energy prices in a given year
*CarTaxEnPriAdd is 

Finally, the value of WEPBYEAR is computed as:

:<math>WEPBYEAR=WEPBYEAR_{t=1}*\frac{WEP}{WEP_{t=1}}</math>

== <span style="font-size:x-large;">Energy Investment</span> ==

Investment in energy is relatively complex in IFs, because changes in investment are the key factor that allows us to clear the energy market in the long term.  It is also different and perhaps slightly more complex in IFs than investment in agriculture.  Whereas the latter involves computing a single investment need for agricultural capital, and subsequently dividing it between land and capital, in energy a separate demand or need is calculated for each energy type, based on profit levels specific to each energy type.

We begin by calculating a total energy investment need (TINEED) to take to the economic model and place into the competition for investment among sectors.  This investment need is a function of energy demand, adjusted by a number of factors, some global and some country-specific. To begin with, TINEED is calculated as

:<math>TINEED_r=ENDEM_r*mulendem*\frac{wkenenpri_t}{wkenenpri_{t-1}}*mulkenenpr*mulwst*mulstocks^{0.5}*mulrprof_r*mulrenew_r*sendeminvr_r</math>

''where''

*mulendem is the ratio of global energy demand per unit GDP in the current year to that in the previous year

:<math>mulkenenpr=\frac{WENDEM_t/WGDP_t}{WENDEM_{t-1}/WGDP_{t-1}}</math>

*wkenenpri is the ratio of global energy capital to global energy production

:<math>wkenenpr=\frac{WorldKen}{WorldEnp}</math>

*mulkenenpr is the ratio of wkenenpr in the current year to that in the previous year

:<math>mulkenenpr=\frac{wkenenpr_t}{wkenenpr_{t-1}}</math>

*mulwst and mulstocks are factors related to global energy stocks. mulwst is calculated using the ADJSTR function, where: the first order difference is that between global energy stocks, wenstks, and desired global energy stocks, DesStocks = '''''dstlen'' ''' * wstbase; the second order difference is between the level of world energy stocks in the current year and those in the past year; and the elasticities are given by the parameters '''''elenpr'' ''' and '''''elenpr2'' '''. mulstocks is also related to global energy stocks, but is more directly related to the desired level of global energy stocks:

:<math>mulstocks=\frac{DesStocks}{MAX(0.5*DesStocks,MIN(4*DesStocks,enstks))}</math>

Note that mulstocks will always take on a value between ¼ and 4.

*mulrprof is a function of the expected level of profits in the energy sector as a whole in a country, EPROFITR.  Energy profits are calculated as the ratio of returns, EnReturn, to costs, ProdCosts.  EPROFITR is actually a moving average of these profits relative to those in the base year, with a historical weighting factor controlled by the parameter '''''eprohw'' '''.  In full, we have:

:<math>EnReturn_r=WEPNoTax*\sum_eENP_{r,e}</math> [1]

:<math>ProdCost_r=\sum_e\frac{ken_{e,r}}{MAX(5,\mathbf{lke_e})}</math>

:<math>EnReturn_r=\frac{EnReturn_r}{ProdCost_r}</math>

:<math>EPROFIT_{r,t}=\mathbf{eprohw}*EPROFIT_{r,t-1}+(1-\mathbf{eprohw})*\frac{EnReturn_{r,t}}{EnReturn_{r,t=1}}</math>

We can now calculate mulrprof using the ADJSTR function.  The first order difference is between the current value of EPROFITR and a target value of 1; the second order difference is the change in the value of EPROFITR from the previous year; the elasticities applied to these differences are given by the parameters '''''eleniprof'' ''' and '''''eleniprof2'' '''.

*mulrenew is a function of the share of other renewables in the energy mix in a country.  It is assigned a value of 1 unless the production of energy from renewables exceeds 70% of total energy demand.  If so, we have:

:<math>mulrenew_r=MAX(0.5,1-(\frac{ENP_{r,renew}}{ENDEM_r}-0.7)*1)</math>

Given these conditions, mulrenew can take on values between 0.5 and 1, with larger values associated with larger amounts of renewable production.

*sendeminvr is a moving average of the ratio of investment need to energy demand in a country, with an accounting for changes in the global capital production ratio since the first year and is updated as<sup>[2]</sup>:

:<math>sendeminvr_{r,t+1}=0.95*sendeminvr_{r,t}+0.05*\frac{TINEED_{r,t}}{ENDEM_{r,t=1}}*\frac{wkenenpr_{t=1}}{wkenenpr_t}</math>

After this initial calculation, two further adjustments are made to TINEED.  The first is a reduction related to a possible reduction of inventory, invreduc, carried over from the previous year.  The calculation of invreduc is described later in this section, where we look at reductions in investment in specific energy types due to resource constraints or other factors. The effect on TINEED is given as:

:<math>TINEED_r=TINEED_r-MIN(0.7*invreduc_{r,t-1},0.6*TINEED_r)</math>

Thus, the reduction in TINEED can be no more than 60 percent.

Finally, the user can adjust TINEED with the use of the multiplier '''''eninvm'' '''.

Before this total investment need, TINEED, is passed to the Economic model, there is a chance that it may need to be further reduced.  This depends on the calculation of a bound, TINeedBound.  TINeedBound arises from a bottom-up calculation of the investment needs for each energy type individually, ineed.  These depend upon the profits for each energy type and any possible bounds on production related to reserves and other factors.

As with the estimate of total profits to energy, the returns by energy type depend upon production and costs. 

:<math>EnReturnS_{r,e}=\frac{ENP_{r,e}}{EnCost_{r,e}}</math>

For the non-fossil fuel energy types – hydro, nuclear, and other renewable – EnCost is based solely on capital depreciation

:<math>EnCost_{r,e}=\frac{ken_{r,e}}{\mathbf{lke_e}}</math>

''where''

*e = hydro, nuclear, renew

For the fossil fuel energy types – oil, gas, and coal – we must also consider any possible carbon taxes. EnCost is calculated as 

:<math>EnCost_{r,e}=\frac{ken_{r,e}}{\mathbf{lke_e}}+ENP_{r,e}*\mathbf{carfuel}_e*\mathbf{carbtax}_r+MAX(-0.5*\frac{ken_{r,e}}{\mathbf{lke_e}},ENP_{r,e}*(\mathbf{carfuel}_e-AvgCarFuel)*emtax_r)</math>

''where''

*e = oil, coal, gas
*'''''carfuel'' ''' is the carbon content of the fuel in tons per BBOE
*AvgCarFuel is the unweighted arithmetic average of the carbon content of oil, gas, and coal
*'''''carbtax'' ''' is an exogenously specified country-specific carbon tax in $ per BBOE
*emtax is the number of years since the first year plus one multiplied by 2

The change in eprofitrs from the first year is then calculated as:

:<math>eprofitrs_{r,e}=\frac{EnReturnS_{r,e,t}}{EnReturnS_{r,e,t=1}}</math>

An average return, avgreturn, is calculated as the weighted sum of the individual returns:

:<math>avgreturn_r=\sum_e(ENP_{r,e}*EnReturnS_{r,e})smoothentot_r</math>

Investment need by energy type, ineed, grows in proportion to capital and as a function of relative profits.

:<math>ineed_{r,e,t}=ineed_{r,e,t=1}*\frac{ken_{r,e,t}}{ken_{r,e,t=1}}*eprofitrs^{elass_{r,e}}_{r,e}</math>

''where''

*'''''elass'' ''' are country and energy-specific user controlled parameters

At this point, ineed is checked to make sure that it does not fall by more than 20% or increase by more than 40% in any single year. 

Also, if the user has set an exogenous target for production growth, i.e., '''''eprodr'' ''' > 0, all of the above is overridden and ineed is calculated as:

:<math>ineed_{r,e}=\frac{ken_{r,e}*(1+\mathbf{enprodr}_e)}{\mathbf{lke}_e}</math>

These investment needs are checked to make sure that they do not exceed what the known reserve base can support.  This applies only to oil, gas, coal, and hydro. An initial estimate of the maximum level of investment is given by:

:<math>maxinv_{r,e}=(\frac{RESER_{r,e}}{\mathbf{prodtf}_{r,e}}-\frac{ken_{r,e}}{QE_{r,e}}+\frac{ENP_{r,e}}{\mathbf{lke}_e})*QE_{r,e}</math>

''where''

*e = oil, gas, coal, or hydro
<div>
The first term in parentheses, when multiplied by QE, indicates the amount of capital that would be necessary in order to yield the maximum level of production given the lower bound of the reserve production ratio, '''''prodtf'' '''. The second term is simply the current level of capital and the third term indicates the level of depreciation of existing capital.  This implies that countries will not make investments beyond those that would give it the maximum possible level of production for a given energy type.

At the same time, IFs assumes there is a minimum level of investment, which is basically 30% of the capital depreciated during the current year:

:<math>mininv_{r,e}=0.3*\frac{ENP_{r,e}}{\mathbf{lke}_e}*QE_{r,e}</math>

''where''

*e = oil, gas, coal, or hydro

In cases where the current production of oil, gas, or coal already equals or exceeds the exogenously specified maximum for a country – '''''enpoilmax'' ''', '''''enpgasmax'' ''', or '''''enpcoalmax'' ''' – maxinv is set equal to mininv.  This again avoids useless investment.

A further constraint is placed on the maximum investment level in capital for hydro production.  This is done by simply replacing RESER/'''''prodtf'' ''' in the calculation of maxinv with the value ENDEM * EnpHydroDemRI * 2, where EnpHydroDemRI is the ratio of energy produced by hydro in the base year to total energy demand in that year.  In other words, the growth in energy production from hydro in the current year from the first year cannot exceed twice the growth in total energy demand over that period, even if reserves are available, and capital investments are restricted accordingly. 

:<math>maxHydroProd_{r,t}=2*\frac{ENDEM_{r,t}}{ENDEM_{r,t=1}}*ENP_{r,Hydro,t=1}</math>

The constraints placed on investment in nuclear energy differ somewhat from these other fuels. IFs does not have an explicit measure of reserves for nuclear.  Rather, it is assumed that the growth in capital in nuclear energy cannot exceed 1 percent of existing capital plus whatever is required to account for depreciation:

:<math>maxinv_{r,e}=(0.01*\frac{ken_{r,e}}{QE_{r,e}}+\frac{ENP_{r,e}}{\mathbf{lke}_e})*QE_{r,e}</math>

''where''

*e = nuclear

Also, the minimum level of investment for nuclear energy is assumed to be 50 percent of the capital depreciated in the current year, rather than 30 percent as with oil, gas, coal, and hydro.

There is no limit to the investments in capital for other renewables.

Given these restrictions, the investment needs for oil, gas, coal, hydro, and nuclear are updated so that mininv <= ineed <= maxinv.  Any reductions from the previous estimates of ineed are summed across energy types to yield the value of invreduc, which will affect the estimate of TINEED in the following year as described earlier.

The final estimates of ineed for each energy type are summed to yield TINeedBound.  If TINEED is greater than TINEEDBOUND, then TINEED is recalculated as the average of the two:

:<math>TINEED_r=0.5*(TINEED_r+TINeedBound_r)</math>

This value of TINEED is passed to the Economic model as IDS<sub>energy</sub>, 

:<math>IDS_{r,s=energy}=sidsf_r*TINEED_r</math>

''where''

*sidsf is an adjustment coefficient converting units of energy capital into monetary values. This gradually converges to a value of 1 after a number of years specified by the parameter '''''enconv'' '''.

In the Economic model, the desired investment in energy must compete with other sectors for investment (see more about linkages between the Energy and Economic models in section 3.7).  Once these sectoral investments are determined, a new value for investments in the energy sector, IDS<sub>s=energy</sub>, is passed back to the Energy model.  The adjustment coefficient is then applied to yield:

:<math>inen_r=\frac{IDS_{r,s=energy}}{sidsf_r}</math>

In the meantime, the desired investment for each energy type can be modified with a country and energy-type specific parameter '''''eninvtm'' ''', and a new value of TINEED is calculated as the sum of these new levels of desired investment.  The amount of the available investment, inen, going to each energy type is then calculated as:

:<math>ineed_{r,e}=inen_r*\frac{ineed_{r,e}*\mathbf{eninvtm}_{r,e}}{TINEED_r}</math>

i.e., all energy types receive the same proportional increase or decrease in investment.

These investments are then translated into units of capital, KEN_Shr,

:<math>KENShr_{r,e}=ineed_{r,e}-\frac{ken_{r,e}}{\mathbf{lke}_e}</math>

The new level of capital is determined as:

:<math>ken_{r,e,t+1}=(ken_{r,e,t}+KENShr_{r,e})*(1-CIVDM_r)</math>

''where''

*CIVDM is an exogenous factor reflecting civilian damage from war

Note that there is no guarantee that KEN_Shr is positive, so it is theoretically possible for ken to fall below 0; IFs checks to make sure that this does not happen.
</div>
----
<div id="ftn1">
[1] World energy price is used to provide stability. The no tax world energy price is used as taxes do not contribute to returns.

[2] Note the careful use of the time subscripts. sendeminvr is not updated until after the computation of the initial value of TINEED, so the initial calculation of TINEED needs to use the previous year’s value of sendeminvr. Furthermore, the updating of sendeminvr occurs after TINEED has been adjusted to reflect any inventory reductions, but before the investment multiplier, '''''eninvm'' ''', is applied.
</div>
== <span style="font-size:x-large;">Economic Linkages</span> ==

The economic model and the two physical models have many variables in common.  As in the agricultural model, IFs generally uses the values in the physical model to override those in the economic model.  To do so, it computes coefficients in the first year that serve to adjust the physical values subsequently. The adjustment coefficients serve double duty - they translate from physical terms to constant monetary ones, and they adjust for discrepancies in initial empirical values between the two models.

[[Energy#Energy_Investment|The Energy Investment section]] already described how desired investment, TINEED, is passed to the Economic model using the adjustment coefficient sidsf.  The adjustment coefficient, ZSR is used to convert production: 

:<math>ZS_{r,s=2}=ZSR_r*WEPBYear_{r,t=1}*\sum^EENP_{r,e}</math>

''where''

:<math>ZSRI_r=\frac{ZS_{r,s=2,t=1}}{WEPBYear_{r,t=1}*\sum^EENP_{r,e,t=1}}</math>

ZSR is a convergence of ZSRI to a value of 1 in 30 years and WEPBYear converts the energy units, which are in BBOE to dollars.

The adjustment coefficient SCSF is used to convert consumption:

:<math>CS_{r,s=2}=SCSF_r*ENDEM_r*0.6</math>

where

:<math>SCSF_r=\frac{CS_{r,s=2,t=1}}{ENDEM_{r,t=1}*0.6}</math>

Note that this assumes that consumer make up a constant 60 percent of consumption of total primary energy.  Also SCSF remains constant over time.

For stocks, imports, and exports, WEBPBYear serves as the adjustment coefficient

:<math>ST_{r,s=2}=WEPBYear_{r,t=1}*ENST_r</math>

:<math>XS_{r,s=2}=WEPBYear_{r,t=1_r}*ENX_r</math>

:<math>MS_{r,s=2}=WEPBYear_{r,t=1}*ENM_r</math>

Finally, the indexed price (with a base of 1) in the energy sector of the economic submodel (PRI) is simply the ratio of current to initial regional energy price (ENPRI) time the value of PRI in the first year.

:<math>PRI_{r,s=2}=PRI_{r,s=2,t=1}*\frac{ENPRI_r}{ENPRI_{r,t=1}}</math>

== <span style="font-size:x-large;">Resources and Reserves: Capital-to-Output Ratios and Discoveries</span> ==

=== Capital-to-Output Ratios ===

Resource base is important in selected energy categories of IFs: conventional oil, natural gas, coal, hydroelectric power, and unconventional oil.  Resources are not important in the nuclear category, which represents an undefined mixture of burner, breeder and fusion power.

Resource costs, as represented by the capital required to exploit them, increase as resource availability in the resource-constrained categories decreases.  The capital-to-output ratio captures the increased cost.  Kalymon (1975) took a similar approach.

More specifically, the capital-to-output ratio (QE) increases in inverse proportion to the remaining resource base (as the base is cut in half, costs double'''; '''as it is cut to one fourth, costs quadruple).  The model multiplies the initial capital output ratio by the initial resource base (RESOR) times a multiplier (RESORM) by which a model user can exogenously increase or decrease model assumptions.  It then divides that product by initial resources minus cumulative production to date (CUMPR).

Total available resources by energy type, ResorTot, are calculated as:

:<math>ResorTot_{r,e}=\mathbf{resorm}_{r,e}*\mathbf{resor}_{r,e}+\mathbf{resorunconm}_{r,e}*\mathbf{resoruncon}_{r,e}</math>

''where''

*'''''resor'' ''' and '''''resoruncon'' ''' are exogenously assumed levels of the ultimate amount of conventional and unconventional forms of each energy type.  There is no assumption about conventional resources for nuclear and only oil and gas include unconventional resources
*'''''resorm'' ''' and '''''resorunconm'' ''' are multipliers that can be used to change the amount of assumed ultimate resources by energy type

All energy types begin with basic capital-to-output ratios, BQE and BQEUC.  These are initially set equal to the same values of QE and QEUNCON, which are derived in the pre-processor, and then evolved according to exogenous assumptions about technological advance for each energy type:

:<math>BQE_{r,e,t}=BQE_{r,e,t-1}*(1-\mathbf{etechadv}_e)</math> [1]

:<math>BQEUNCON_{r,e,t}=BQEUNCON_{r,e,t-1}*(1-\mathbf{etechadvuncon}_e)</math>

Recall that technological improvements result in declining amounts of capital required for each unit of energy produced.

The initial translation of this basic capital-to-output ratio to the value actually used to determine energy production varies by energy type.

This is most straightforward for nuclear and unconventional energy, which do not take into account remaining resources:

:<math>QE_{r,e,t+1}=BQE_{r,e,t}*\mathbf{qem_{r,e}}</math>

''where''

*e is nuclear
*'''''qem'' ''' is an exogenous multiplier

:<math>QEUC_{r,e,t+1}=BQEUC_{r,e,t}*\mathbf{qeunconm_{r,e}}</math>

''where''

*e is oil or gas
*'''''qeunconm'' ''' is an exogenous multiplier

For hydro and other renewables, QE depends upon the remaining resource, which is defined as the difference between the total resource available and a moving average of the difference in production vis-à-vis production in the first year.  In other words, it is not cumulative production that is important, but rather the portion of resources used annually.

:<math>QE_{r,e,t+1}=BQE_{r,e,t}*\frac{ResorTot_{r,e}}{resorrem_{r,e}}*\mathbf{qem_{r,e}}</math>

''where''

:<math>resorrem_{r,e}=ResorTot_{r,e}-ENPGR_{r,e}</math>

:<math>ENPGR_{r,e}=SmoothENP_{r,e}-ENP_{r,e,t=1}</math>

:<math>SmoothENP_{r,e,t}=0.8*SmoothENP_{r,e,t-1}+0.2*ENP_{r,e}</math>

*e = hydro or renew

For oil, gas, and coal, the logic is similar, but the definition of remaining resources is somewhat different: 

:<math>resorrem_{r,e}=MAX(ResorTot_{r,e}-CUMPR_{r,e},MaxFac_{r,e})</math>

:<math>CUMPR_{r,e,t}=CUMPR_{r,e,t-1}+ENP_{r,e}</math>

:<math>MaxFac_{r,e}=0.1*ResorTot_{r,e}</math>

Furthermore, the capital-to-output ratio is calculated as a moving average

:<math>CompQE_{r,e}=BQE_{r,e}*(\frac{ResorTot_{r,e}}{resorrem_{r,e}})^{0.4}</math>

:<math>QE_{r,e,t+1}=(0.8*QE_{r,e,t}+0.2*CompQE_{r,e})*\mathbf{qem_{r,e}}</math>

''where''

*e is oil, gas, or coal

=== Discoveries ===

<span>Energy reserves decrease with production and increase with discoveries, the latter of which are limited by remaining resources and other factors.  This only applies to oil, gas, and coal.</span>

:<math>RESER_{r,e,t+1}=RESER_{r,e,t}+rd_{r,e}-ENP_{r,e}</math>

The rate of discovery, rd, is initially computed as a function of a number of factors related to global energy prices, remaining resources, global and domestic production, and several exogenous assumptions

:<math>rd_{r,e}=rdiaug_e*wepterm*reterm_{r,e}*\mathbf{rdm_{r,e}}</math>

'' where''

*e = oil, gas, coal
*'''''rdm'' ''' is a country and energy-specific exogenous multiplier
*rdi_aug is an energy-specific factor driven entirely by exogenous assumptions about initial rates of discovery, '''''rdi'' ''', and annual increments, '''''rdinr'' ''':

:<math>rdiaug_e=\mathbf{rdi}_e+\mathbf{rdinr}_{r,e}*(t-firstyear)</math>

*wepterm is a global factor driven by the growth in world energy prices from the first year and an exogenously defined elasticity, '''''elasdi'''''

:<math>wepterm=1+\frac{WEP_t-WEP_{t=1}}{WEP_{t=1}}*\mathbf{elasdi}</math>

*reterm is a country and energy-specific factor representing an average of a country’s remaining resources as a share of original resources and its share of current production

:<math>reterm_{r,e}=0.5*(\frac{ResorTot_{r,e}-CUMPR_{r,e}-RESER_{r,e}}{\sum_e(ResorTot_{r,e,t=1}-RESER_{r,e,t=1})}+\frac{ENP_{r,e}}{WENP_e})</math>

A further assumption is that the rate of discovery cannot exceed 4 percent of the remaining resources in a country, where remaining resources are specified as:

:<math>resorrem_{r,e}=ResorTot_{r,e}-CUMPR_{r,e}-RESER_{r,e}</math>

''where''

*e = oil, gas, coal
*For oil the amount of unconventional oil in ResorTot is also affected by the parameter '''''enresunce'' '''[2]
<div>[1] There used to be an additional impact of ICT broadband that would further reduce the BQE for other renewables, but that is currently not active in the model. <div id="ftn1">
[2] This only affects Canada, which has a value of '''''enresunce'' ''' = 0.3. Why this is not included in the QE calculations is unclear.
</div></div>
== <span style="font-size:x-large;">Energy Indicators</span> ==

Among useful energy or energy-related indicators is the ratio (ENRGDP) of energy demand (ENDEM) to gross domestic product (GDP).

:<math>ENRGDP_r=\frac{ENDEM_r}{GDP_r}</math>

Global production of energy by energy type (WENP) is the sum of regional productions (ENP).

:<math>WENP_e=\sum^RENP_{r,e}</math>

Global energy production is the basis for examining the build-up of carbon dioxide and Climate Change, as described in the documentation of the Environmental model.

The ratio of oil and gas production globally to total energy production (OILGPR) helps trace the transition to other fuels.

:<math>OILGPR=\frac{WENP_{e=1}+WENP_{e=2}}{\sum^EWENP_e}</math>

Global energy reserves (WRESER) and global resources (WRESOR) are sums by energy type across regions, the latter taking into account any resource multiplier (RESORM) that a user specifies to modify basic model resource estimates.

:<math>WRESER_e=\sum^RRESER_{r,e}</math>

:<math>WRESOR_e=\sum^R(RESOR_{r,e}*RESORM_e)</math>

= <span style="font-size:x-large;">Energy Bibliography</span> =

Kalymon, Basil A. 1975. "Economic Incentives in OPEC Oil Pricing Policy." ''Journal of Development Economics'' 2: 337-362.

Naill, Roger F. 1977.''Managing the Energy Transition.'' Vols. 1 and 2. Cambridge, Mass: Ballinger Publishing Co.

Stanford University. 1978. ''Stanford Pilot Energy/Economic Model.'' Stanford: Department of Research, Interim Report, Vol. 1.

2025-11-13T16:11:52Z

Simon.Kyeremeh: In- progress

Edits here, Add another

The Flexible Displays can be found under Display on the Main Menu.

This display feature of IFs allows users more flexibility than the [[Geographically-fixed_Displays_(Download)|Geographically-fixed Displays]] by allowing for the display of data sets by specific country or group.

[[File:Flexibledisplay.gif|frame|right|Example of the Flexible Display window in IFs]]The Flexible Displays is designed to allow users to graph information on a specific [[Country/Region,_Group_or_G-List|country/region or group]].

The display variables are located in a list on the left hand side of the screen. To the right of this list of variables is a list of general categories. Each display belongs to one of the broader categories. If you are interested in one specific category, click on it and the general list of displays will be reduced to only those that pertain to the category you have selected. [[Self-Managed_Display_(Download)|Learn how to incorporate your own categories]].

To the right of the general categories is a list of every country. If, instead of displaying countries/regions, you would like to display groups, simply click on the Using Countries/Regions option on the Flexible Displays' Main Menu. The list at the very bottom of the screen is of the different Run-Result-Files that accompanied your version of the software. If you would like to learn more about specifically what parameters and variables are affected by these Run-Result-Files, simply highlight one and click on the [[Annotation|Annotation]] button.

Certain variables and '''categories''', such as education, when selected, will cause other windows to appear that display different dimensions, or ways of disaggregating the data. For example, selecting the file Education Tertiary Student Flow brings up another dimension, in this case gender, from which the user is able to choose.

The user is also able to select more than one country or more than one Run-Result-File for graphing. Simply click on one country/region, hold in the control button (ctrl), and click on another country/region. Do the same to see a graph displaying results as the product of more than one Run-Result-File.

Flexible Display has a number of general lists on the title page, through which the user is able to explore or manipulate the graph. These are described below.

'''Display Format:''' Firstly''',''' the user can change the titles for tables and graphs, and the titles of the X and Y axes for graphs. The user can also edit the table display interval, as well as edit the year for a pie chart, scatterplot, or map. Secondly, the user is able to select a list of currencies for which one wants to display data other than US dollars (and find its equivalent with USD). Within this space, the user can adjust the horizon setting, which defines the limits of the run horizon, with a maximum of 2100 and a minimum of 2022, as well as allowing the user to run file horizon choice. ''Use estimation to complete data'' options instruct the model to use existing data to fill in missing values based on the patterns found in a complete dataset to predict future outcomes. Slightly different from the Use estimation to complete data, the ''Use estimation to complete data (only holes no extrapolation) option'' tells the model to fill in missing values within the existing data range, without predicting beyond that. Lastly, the ''"Use all available Historical Data"'' option tells the model to learn from past information and provide the most up-to-date historical data available to make predictions.

'''Other Grouping Options:''' Users can improve the accuracy of data by selecting options such as Using Intersection for "Decomposed Groups," "G-Lists," or "Grouping Aggregations," which allow for extracting data within specific geographic segments to create a representative value.

Explain

Edit List

Search Lists

Help

'''Other Graphs''': When the user has chosen the display to graph and the countries/regions or groups that you to display, click on [[General_Display_Options#Graph_Use|Line Graph or Bar Graph]]. The user is also able to display pie charts and [[General_Display_Options#Radial_Graph|radial graphs]], located under the Other Graphs heading. For an explanation on how to use the Map feature, click on [[General_Display_Options#Map_Use|Map Use]].

Additionally, choosing the Display Format option located on the Flexible Displays menu allows the user to more professionally tailor the graphs as needed. Firstly, the user can change the titles for tables and graphs, and the titles of the X and Y axes for graphs. The user can also edit the table display interval, as well as edit the year for a pie chart, scatterplot, or map. Secondly, the user is able to select the currency in which to display data that is otherwise displayed in US dollars. Thirdly, the user can set the limits of the run horizon, with a maximum horizon of 2100 and a minimum of 1960. Fourthly, check the “Use all historic data” feature, and the model will provide the most up to date historical data available. The last option, the “Use Estimation” option, tells the model to extrapolate from the historic data to fill in any possible holes in the data that exist.

The '''Explain List''' in the heading is an option that, when selected, will provide a definition, show the historic formula, and list any dimensions available for any selected variable.

Clicking on the the Search option in the heading allows the user to search for any variable in the IFs database, and add that variable to the list of available variables in the Flexible Displays.

The user is able to edit the variables listed in Flexible Displays by first selecting [[Self-Managed_Display_(Download)|Self-Managed Display]], and then selecting [[Variable_Selection_Options#Edit_Variable_List|Edit Variable Lists]].

'''The Geography Options''' is the sub-section found beneath the general list in the title of the flexible display menu. This presents the user with options to select a category (or categories) of variables vis-à-vis its specific location(s). These options enable the user to navigate among countries and regions or the classification of the aforementioned. These include ''Country/Regions, Groups, Decomposed Group, Geography-ListsCountry/Regions and Groups, Country/Regions and Decomposed Groups''. Additionally, the user could make these set options/groups appear fully or partially via the ''Hide Non-Core option''. The ''View History plus Forecast'' option enables users to view/pull previous and future datasets of variables.