Pardee Wiki - User contributions [en]

File Management

2026-03-26T16:56:02Z

Ethan.Sullivan:

Use the File Management option in IFs to save and delete [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''run files (.run).''']] From the Main Menu, choose '''[[Scenario Analysis|Scenario Analysis,]]''' then '''File Management'''. Three options appear: '''OPEN run file as a working file''', '''SAVE working file as...''', and '''DELETE run file'''.
[[File:Example of File Management.png|center|thumb|950x950px|An example of the File Management dropdown options from the Main Menu.]]
To open a run file as the working file, hover over '''OPEN run file as a working file''', and click the desired run file. Setting a particular run file as the working file may be helpful when working with a large number of run files, as it will be the default scenario option and will be at the top of any scenario drop-down.

To save the most recent run of the model, click '''SAVE working file as...''' This should be the first step after [[Running the Model|running]] any [[Scenario Description|scenario]]. A page will open with a field to enter the desired name of the run file. Enter the name and click '''Save''' or cancel by clicking '''Cancel'''. Once saved run riles are located in a folder within \IFs\RUNFILES\..

To delete a run file, hover over '''DELETE run file''' and click on the file to delete. A message will appear stating the file was successfully deleted.

File Management

2026-03-26T16:54:04Z

Ethan.Sullivan:

Use the File Management option in IFs to save and delete [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''run files (.run).''']] From the Main Menu, choose '''Scenario Analysis,''' then '''File Management'''. Three options appear: '''OPEN run file as a working file''', '''SAVE working file as...''', and '''DELETE run file'''.
[[File:Example of File Management.png|center|thumb|950x950px|An example of the File Management dropdown options from the Main Menu.]]
To open a run file as the working file, hover over '''OPEN run file as a working file''', and click the desired run file. Setting a particular run file as the working file may be helpful when working with a large number of run files, as it will be the default scenario option and will be at the top of any scenario drop-down.

To save the most recent run of the model, click '''SAVE working file as...''' This should be the first step after [[Running the Model|running]] any [[Scenario Description|scenario]]. A page will open with a field to enter the desired name of the run file. Enter the name and click '''Save''' or cancel by clicking '''Cancel'''. Once saved run riles are located in a folder within \IFs\RUNFILES\..

To delete a run file, hover over '''DELETE run file''' and click on the file to delete. A message will appear stating the file was successfully deleted.

File Management

2026-03-26T16:53:38Z

Ethan.Sullivan:

Use the File Management option in IFs to save and delete [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''run files (.run).''']] From the Main Menu, choose '''Scenario Analysis,''' then''' File Management'''. Three options appear: '''OPEN run file as a working file''', '''SAVE working file as...''', and '''DELETE run file'''.
[[File:Example of File Management.png|center|thumb|950x950px|An example of the File Management dropdown options from the Main Menu.]]
To open a run file as the working file, hover over '''OPEN run file as a working file''', and click the desired run file. Setting a particular run file as the working file may be helpful when working with a large number of run files, as it will be the default scenario option and will be at the top of any scenario drop-down.

To save the most recent run of the model, click '''SAVE working file as...''' This should be the first step after [[Running the Model|running]] any [[Scenario Description|scenario]]. A page will open with a field to enter the desired name of the run file. Enter the name and click '''Save''' or cancel by clicking '''Cancel'''. Once saved run riles are located in a folder within \IFs\RUNFILES\..

To delete a run file, hover over '''DELETE run file''' and click on the file to delete. A message will appear stating the file was successfully deleted.

File Management

2026-03-26T16:53:10Z

Ethan.Sullivan:

Use the File Management option in IFs to save and delete [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''run files (.run).''']] From the Main Menu, choose '''Scenario Analysis,''' the'''n File Management'''. Three options appear: '''OPEN run file as a working file''', '''SAVE working file as...''', and '''DELETE run file'''.
[[File:Example of File Management.png|center|thumb|950x950px|An example of the File Management dropdown options from the Main Menu.]]
To open a run file as the working file, hover over '''OPEN run file as a working file''', and click the desired run file. Setting a particular run file as the working file may be helpful when working with a large number of run files, as it will be the default scenario option and will be at the top of any scenario drop-down.

To save the most recent run of the model, click '''SAVE working file as...''' This should be the first step after [[Running the Model|running]] any [[Scenario Description|scenario]]. A page will open with a field to enter the desired name of the run file. Enter the name and click '''Save''' or cancel by clicking '''Cancel'''. Once saved run riles are located in a folder within \IFs\RUNFILES\..

To delete a run file, hover over '''DELETE run file''' and click on the file to delete. A message will appear stating the file was successfully deleted.

Understand Scenarios in IFs

2026-03-26T16:50:44Z

Ethan.Sullivan:

= Introduction to Scenarios =
A scenario is a story or story outline. Thinking about the future normally involves creating alternative scenarios, or stories, about the possible evolution of drivers. Some such scenarios are exploratory and consider the possible unfolding of different futures around key uncertainties, such as the rate of some aspect of technological advance or the fragility of some element in the global environment. Other scenarios are normative and develop stories about preferred futures, such as a global transformation to sustainability.

Scenarios in a large integrated model typically are built from multiple interventions that collectively help build a coherent story about the future. Often, but somewhat imprecisely, the word ''scenario'' is used more loosely to refer to any intervention (such as the change of a fertility rate for a country or an alternative assumption about oil resources).

Scenarios or interventions with respect to what? When IFs or other computer simulations are "run", without making any changes to parameters or initial conditions specified as the default values, they generate a forecast that is typically called the base case (sometimes reference run). The IFs base case, always available when a model session is initiated, is itself a scenario. Sometimes the base case is incorrectly referred to as a trend extrapolation or a "business as usual" scenario. More accurately, however, the base case of IFs is a computation that involves the full dynamics of the model and therefore has very nonlinear behavior, often quite different from trends. It is a good starting point for scenario analysis for two reasons. First, it is built from initial conditions of all variables that have been given reasonable values from data or other analysis. These initial conditions and parameters make up the package of interventions that constitute the base case scenario. Second, the base case is periodically analyzed relative to the forecasts of many other projects across the range of issue areas covered by IFs and sometimes "tuned" to reproduce the behavior of respected forecasters.

= Creating Scenarios in IFs =
Change initial conditions and parameters using the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create scenarios beyond the base case. Adjust parameters to make specific intended interventions, for example use the Government Spending by Destination and Sector multiplier parameter gdsm to increase government spending in education. A detailed guide of the different parameters and their potential uses can be found in the [[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis]].

==== Scenario Files and Run Files ====
Use the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create and save two different kinds of files: ''S''cenario Files (.sce) and Run Files (.run). The Scenario Files represent changes that were made to parameters in IFs but that have not yet run through IFs. Scenario Files will be saved with .sce as the file extension. Once saved scenario files are located in a folder within \IFs\Scenario\..The Run Files are files that hold forecast results after the IFs software has run. Run Files will be saved with .run as the file extension. The running of a Scenario Files through the IFs software, will include those parameter changes in the scenario file while the model runs and will produce a Run File. Once saved run files are located in a folder within \IFs\RUNFILES\. The most recent Run File produced by running the model is called the ''Working-File''. By default the Working-File is the base case until the model is run.

In addition to the base case, some versions of IFs will include a number of other previously-run scenarios, perhaps the set of scenarios for the National Intelligence Council’s (NIC) 2020 Project or those for the five Shared Socioeconomic Pathways. In the '''Scenarios''' drop down in Flex Displays, a list of previously-run scenarios is shown before any new scenarios are run. Because those have already been run, based on a set of interventions constituting their foundations, their results can already be displayed.

= Parameter Types =
Parameters are numbers that determine relationships among variables in the equations of IFs. Parameters are often set to a single value across time and they therefore do not always "vary" as do "real" variables. Many parameters are "policy handles," the value of which are set in order to determine the behavior of the model. In IFs parameters are written in lower case form such as endemm and variables are written in upper case such as ENDEM. There are several types of parameters that include:

'''Multiplier''': An equation result parameter that multiplies results (of variable calculations) by the value of the parameter. These parameters are 1 by default, thereby leaving what is multiplied unchanged. Examples of multipliers include: enpm (energy production multiplier), or tfrm (total fertility rate multiplier). Note that multipliers typically end with the letter "m".

'''Additive Factor''': Also, an equation result parameter. Changes results by adding the value of the parameter to the results. These parameters are 0 by default, thereby leaving what is added unchanged. Some examples are: mfpadd (an additive factor on multi-factor productivity growth rate), or migrateinadd (migration rate inward additive factor). Additive Factors typically end with “add”.

'''Switch''': Turn off or on model elements, therefore they alter the structure of the model. They generally take on values of 1 (on) or 0 (off). Switches are most often on or off for the entire run, but it sometimes makes sense to "throw a switch" in the middle of a run. Switch examples include: agon (agriculture economy linkage) and squeez (economic impact of energy shortage). Switch parameters may end in "sw" but have no specific naming structure.

'''Initial Condition''': These are not strictly parameters, but rather first-year values for variables that are subsequently computed by the model, or values for rates of change. These cannot be changed in years beyond the base. These include parameters like: carinit (carbon dioxide in atmosphere in base year, initial condition) or igdpr (initial gdp growth rate). There is no specific naming structure to these parameters.

'''Limit''': These parameters set a limit for a variable such as the maximum or minimum. Some examples include: watwastetreatcostupper (wastewater treatment unit maximum cost, limit) or ylmax (maximum possible agricultural yield, limit). There is no specific naming structure to these parameters but many end in “max” “min” "upper" and "lower".

'''Rate''': Change rates directly or to alter rates of growth or decline. Some examples of rate parameters are: femshrgr (annual growth of female share of the labor force, rate) or ginidomr (domestic gini index growth rate). There is no specific naming structure to these parameters.

'''Relationships''': Set or alter the relationship between two variables, by setting or altering the response level of one variable based on changes in another. Examples include: fpricr1 (food prices response to stock level, relationship) or elasde (energy demand to change in price, relationship)

'''Target''': These are parameters that set a target value and the number of years to achieve certain targets or convergence between countries or variables. Target parameters typically come in pairs with the first parameter setting the target for a variable and the second setting the number of years to achieve that target. For example: sanithhbasictrgtval (percent of people with at least basic sanitation service, Target) and sanithhbasictrgtyr (percent of people with at least basic sanitation service, year to achieve, target). Many times, these parameters end in “val” and “yr” corresponding with setting the target value and year respectively. Another common ending for target parameters is “conv” for conversion targets.

'''Level''': Parameters that override the value of a variable, like: enprix (energy price, level). There is no specific naming structure to these parameters.

'''Function Coefficient''': Alter terms in internal calculations. These parameters will change the underlying structure of equations in the model and as a result will alter the values of variables. Examples of function coefficients include: labinformcoeffintercept (Intercept in the Calculation of Informal Labor Share, Function Coefficient) or govriskweight (Weights in the Calculation of the Government Risk Index, Function Coefficient).

The focus here is on exogenous parameters only - on those elements of the model that can be manually changed. Many computed variables are used in the computation of other variables in the same way that parameters are, as multipliers, additive factors, coefficients, and so on. These can be displayed too, but unlike true parameters, they cannot be changed.

Quick Scenario Analysis with Tree

2026-03-26T16:36:06Z

Ethan.Sullivan:

The ''Quick Scenario Analysis with Tree'' page can be accessed from the Main Menu by selecting '''[[Scenario Analysis]]''' and then '''''Quick Scenario Analysis with Tree'''.'' Use this feature to develop, review, and edit scenarios in IFs. This feature allows for building and editing a Scenario File (.sce) which loads interventions to be run in the IFs model to produce a Run File (.run), which displays scenario results.
[[File:Example of the Quick Scenario Guide.png|center|thumb|950x950px|An example of the Quick Scenario Guide page in IFs when first opened.]]
This page has a number of features and options to create, load, adjust, and run scenarios. These options and features include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''Scenario Files''']]:
** '''Clear Tree''': Clear any interventions currently loaded to the scenario tree.
** '''Open''': Load any set of saved or preloaded Scenario Files (.sce). Hover over folder names to find and select the desired scenario. The '''Open''' drop-down folders reflect those in \IFs\Scenario file path on the current device. The scenare tree will update with the interventions in the chosen scenario file.
** '''Name and Save''': Open a pop-up to save the scenario currently reflected in the scenario tree. The pop-up includes two fields to enter text into; type the desired scenario file name and folder name in the fields, then click '''Save''' or '''Cancel'''. The two fields are:
*** '''File Name''': Enter a file name for the created scenario, which will create a scenario file named ''FileName.sce.''
*** '''Folder Name''': Enter a new or already existing folder name to save the scenario file to that location. This folder will show up in \IFs\Scenario\User Defined Scenarios\ on the current device.
** '''Export to IFs Standard CSV Format''': Save a CSV version of the scenario to the same folder that the currently displayed scenario is stored in. For newly created scenarios, click '''Name and Save''' first before clicking this option. CSV versions of scenarios can be easier to manage and understand, as all years and dimensions are aligned in titled columns, unlike Scenario Files (.sce) that are written in comma-separated text format.
** '''Export Working File''': Download a Scenario File (.sce) of the current scenario tree.
** '''Import IFs Standard CSV Format files''': Load a scenario that has been saved using the '''Export to IFs Standard CSV Format''' in the scenario tree. This requires that a scenario has previously been saved using the IFs standard CSV format and located in a folder within \IFs\Scenario\. Follow the appropriate file path and click on the desired scenario CSV to import.
* '''Add Scenario Component''': Similar to '''Open''' from the [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''Scenario Files''']] options. Layer multiple scenario files or interventions by adding components from another scenario once one has loaded.
* '''[[Running the Model|Run Scenario]]''': Open the '''[[Running the Model|Run]]''' page for the current scenario in the scenario tree. Adjust the horizon to the desired end year and click '''Start Run'''.
* '''Delete Selection''': When an intervention is displayed on the screen next to the scenario tree from either clicking on a parameter directly in the tree or from the '''Parameter Search''' option, click '''Delete''' to remove that intervention from the current scenario.
* '''[[Country/Region, Group or G-List|Set Group or Country]]''': Click '''Groups''' to make interventions for particular groups, or '''Countries''' for a particular country or countries. The current selection will have a checkmark next to it.
* '''Annotate Scenario''': Click Annotate to open a description of the scenario interventions based on the current Scenario Tree. An annotation is generated by default, which can be edited or supplemented with explanatory or narrative information describing the scenario. To edit the annotation, click in the text box and change or add text as desired. Below the text box click '''Save''' to save edits, '''Clear''' to remove all text in the annotation, '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Exit''' to return to the ''Quick Scenario Analysis with Tree.''
* '''Parameter Search''': Click '''Search''' to open the ''Parameter Search'' page to search to find and select specific parameters. The Parameter Search feature is described below.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]].

= <span style="font-size:xx-large;">Parameter Search</span> =

Use the ''Parameter Search'' feature to search, explore, and choose parameters to adjust for scenario analysis. Use this feature with the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' to find the parameters most useful for the intended intervention or scenario goal. Type the desired parameter name in the search bar, then click '''Search'''. Click on the parameter, which will bring up a few options described below. Click '''Load''' to select this parameter in the scenario tree. Click '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Continue''' to go back to the previous menu or to the Main Menu of IFs.
[[File:Example of Parameter Search Option.png|center|thumb|950x950px|An example of the Parameter Search option for the total fertility rate multiplier tfrm.]]
The options, once a parameter is clicked, include:
* '''Define''': See a brief definition of the parameter and how it works, where available.
* '''Block Diagram (Pop-Up)''': Open a new tab with a wiki page displaying a diagram and text explanation that broadly explains how drivers interact for the area of inquiry (agriculture, economics, etc.), where available.
* '''Equations (Pop-Up)''': Open a new tab with a wiki page of the mathematical equations that are used to determine this parameter, where available.

= <span style="font-size:xx-large;">Using the Scenario Tree</span> =
The easiest way to create scenario interventions is to use the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' along with the Parameter Search option, described above. The Scenario Tree can also be used to find and select a parameter. Click on any of the categories in the Scenario Tree (ex., Technological change. to open sub -categories and eventually to open up a parameter choices box. Once this box appears to the right of the scenario tree with parameter names and descriptions, click on any parameter to reveal a few options shown below.
[[File:Example of Scenario Tree usage.png|center|thumb|950x950px|An example of the scenario tree being used for Technological Change, Energy, and with the QEM parameter selected; shows the options that selecting a parameter will reveal.]]
The options include:

* '''Select''': Choose the parameter in order to load and edit it.
* '''Drivers''': Click to see what variables are affecting the chosen parameter, where available.
* '''Explain (Pop-Up)''': Open a new tab with a wiki page displaying a diagram and text explanation that broadly explains how drivers interact for the area of inquiry (agriculture, economics, etc.), where available.
* '''View Equations (Pop-Up)''': Open a new tab with a wiki page of the mathematical equations that are used to determine this parameter, where available.
* '''Define''': See a brief definition of the parameter and how it works, where available.

= Adjusting Parameters =
Once a parameter is chosen by clicking '''Select''', as described above, a drop-down will appear to choose either a particular [[Country/Region, Group or G-List|country or group]]. Choose the desired country or group by clicking on it. Another drop-down will appear if the parameter has dimensions (e.g., Male, Female, Total), click on the desired dimension choice, and repeat if the parameter has multiple dimension choices. After this, the selected parameter will appear to the right of the tree with its base value or scenario value (if opened within an already made scenario) shown. An example of this screen is shown below.
[[File:Example of Parameter Adjustment on Scenario Tree.png|center|thumb|950x950px|An example of a parameter selected to adjust on the Quick Scenario Analysis Tree page. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
This screen offers a few basic options for adjusting parameters. Adjust the initial parameter value to make interventions using default changes by clicking the bubble for '''High''' or '''Low''', or to return to the base, click '''Base'''. Alternately, use the slider or enter the desired number into the field above the slider and click '''Apply'''. Using this slider or field option will apply that value to the whole time horizon to the year 2150, with an initial shift period based upon the choice from the '''Shift Years''' dropdown. In the example, the value is 5.177, and the shift years are 10, so the parameter interpolates from 1 to 5.177 from 2020 to 2030 and then stays at that value for the whole horizon.

For developing high-quality scenarios, full parameter customization is recommended. Click '''Fully Customize''' for more options and to load the '''Change Values''' screen'''.'''
[[File:Example of the Fully Customize Parameter option.png|center|thumb|950x950px|An example of the Fully Customize option for parameter changes. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
The '''Fully Customize''' option allows more control over parameter behavior. The '''Information''' table displays information on parameter value for a given year, and the minimum and maximum values that IFs recommends for intervention. If above or below these, a warning message will appear. Use the '''Year''' field in this table to jump to a particular year to view the value or to start an intervention from.

The '''Change Numerically''' table is where the changes to a parameter are made. Use the '''Next Year''' or '''Previous Year''' buttons to change the '''Year''' field by one. Once at the desired year to start an intervention shown in the '''Year''' field, enter in the '''Desired Value''' field the value to change the parameter to, use the '''Years to Repeat or Interpolate''' field to set the number of years for the intervention to take place (this includes the current year so to increase the value for the next 10 years, enter 11). Click '''Change/Repeat''' to apply the desired value for the number of years entered (for example, an increase to 8 for 61 years from 2090 to 2150, shown above) or click '''Interpolate''' to smoothly shift the value over the number of years entered from the current value to the desired value. Continue to use the '''Change Numerically''' table until the parameter is adjusted as desired.

To ensure that the parameter is adjusted as desired, hover over the graph on the right side of the page to see the parameter value in any given year. Click '''Register Change''' to apply this intervention to the current scenario, '''Cancel All Changes''' to clear the current parameter adjustments, '''Exit to Scenario Tree''' to return to the scenario tree, or '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]].

File Management

2026-03-26T16:27:37Z

Ethan.Sullivan:

Use the File Management option in IFs to save and delete [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''run files (.run).''']] From the Main Menu, choose '''Scenario Analysis,''' the'''n File Management'''. Three options appear: '''OPEN run file as a working file''', '''SAVE working file as...''', and '''DELETE run file'''.
[[File:Example of File Management.png|center|thumb|950x950px|An example of the File Management dropdown options from the Main Menu.]]
To open a run file as the working file, hover over '''OPEN run file as a working file''', and click the desired run file. Setting a particular run file as the working file may be helpful when working with a large number of run files, as it will be the default scenario option and will be at the top of any scenario drop-down.

To save the most recent run of the model, click '''SAVE working file as...''' This should be the first step after [[Running the Model|running]] any [[Scenario Description|scenario]]. A page will open with a field to enter the desired name of the run file. Enter the name and click '''Save''' or cancel by clicking '''Cancel'''.

To delete a run file, hover over '''DELETE run file''' and click on the file to delete. A message will appear stating the file was successfully deleted.

Reload Base

2026-03-26T16:23:25Z

Ethan.Sullivan:

Use the ''Reload Base'' feature in IFs to reload the [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''base case run to the working file.''']] This may be helpful when working with a large number of run files, as it will reset the base case as the default scenario option and can be accessed from the scenario drop-down at the top of the list. From the ''Main Menu,'' choose '''[[Scenario Analysis]]''' and click '''''Reload Base'''''. A message will appear stating that the base has successfully been reloaded.

Change Selected Functions

2026-03-25T23:06:27Z

Ethan.Sullivan:

To open the ''Bivariate Functions'' or the ''Multivariate Functions'' page from the Main Menu of IFs: choose '''Scenario Analysis''', '''Change Selected Functions''', and click '''''Bivariate Function.'''''

Variables are forecast based on mathematical relationships that are represented by functions within IFs. These functions can be changed based on different understandings of relationships between variables. Changing functions gives you a powerful tool for using IFs to investigate possible futures and, to an extent, to change the model itself. Change the relationships between two variables or multiple variables using the ''Bivariate'' and ''Multivariate function'' pages.

= <span style="font-size:xx-large;">Bivariate Functions</span> =

Open the ''Bivariate Functions'' page from the Main Menu of IFs: choose '''Scenario Analysis''', '''Change Selected Functions''', and click '''''Bivariate Function.''''' Once on the ''Bivariate Function'' page, search for a particular function in the '''Filter Functions (press enter)''' field or scroll through the '''Function (click to see/edit)''' dropdown to view a relationship that is already in IFs. Use the filter options ('''Used in Run''', '''Used in Historical Run,''' etc.) to the right of the dropdown to filter for functions that are used for particular model tasks, or not used at all.
[[File:Example of Bivariate Function page.png|center|thumb|950x950px|An example of the Bivariate Function page used to change functions in IFs.]]
When a function is clicked, the relationship of the function will be shown in graph form at the bottom of the screen. Depending on the type of function, an R-squared and standard error of the relationship may also be shown below the graph. Export the graph by clicking on the three lines in the upper right corner of the graph, then select the desired format to export.

To change a chosen function, use the '''Table Functions Points''' frame option or the '''Analytic Function''' button option to specify a new relationship.

'''Table Functions Points''': A table function relationship is based upon lines that connect given points. In the '''Table''' '''Function Points''' frame, there are boxes for specifying the X-axis and Y-axis values. Specify a desired point by entering the X and Y axis values, then click '''Add'''. Add as many points as desired, and click '''Previous''' and '''Next''' to move between already created points. Click '''Delete''' to remove a point from the graph. When the points desired to create a function with are all added, click '''Alter''' to alter the function to now be based on this new relationship.

'''Analytic Function''': Click to open the ''Specify Analytic Function'' page. Use this page to change the mathematical formula of a function by adjusting its function terms. A function based on a linear regression will only have a and b1 terms, and altering other bs will change the whole function type. More complex functions will use different b terms, for example, an exponential will use b2 and a logarithmic b4.
[[File:Example of the Specify Analytic Function page.png|center|thumb|950x950px|An example of the Specify Analytic Function page, for GDP and car sales.]]
Change the '''Display Figure from X Value''' and '''To X Value''' fields to change the graph in the ''Bivariate Functions'' screen. Once the function is changed as desired, click '''Save and Continue''' to save and return to the ''Bivariate Functions'' page or '''Exit - Abandon Changes''' to return without saving the change.

Click '''Reverse Changes''' to return to the default for the selected function, '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Exit''' to return to the ''Main Menu''. After clicking '''Exit,''' IFs gives a very important informational warning on how any function changes will be active only in the current session of IFs. Starting IFs again resets all functions to standard values. Moreover, although runs of the model that you make with altered functions will reflect the changes in functions, no information about the changed functions is saved with the model Run Files. Keep track of these changes somewhere for replicability.

Now [[Running the Model|run the model]] using the [[Quick Scenario Analysis with Tree]] option from the Main Menu. Once the model has run, a [[Understand Scenarios in IFs#Scenario Files and Run Files|new working file]] is loaded that reflects the changed functions and their impact on all computations. Compare this working file (or a saved run file version of it) with the base case or with other scenarios.

= <span style="font-size:xx-large;">Multivariate Functions</span> =

Open the ''Multivariate Functions'' page from the Main Menu of IFs: choose '''Scenario Analysis''', '''Change Selected Functions''', and click '''''Multivariate Functions'''.'' This page displays a table with multivariate function names, their intercept, R-squared, and standard errors. Search for a particular function using the search bar or scroll through the table to find the desired function. Use the filter options ('''Used in Run''', '''Used in Historical Run,''' etc.) to the right of the table to filter for functions that are used for particular model tasks, or not used at all.
[[File:Example of Multivariate Functions page.png|center|thumb|950x950px|An example of the Multivariate Functions page.]]
Click on any intercept to change the intercept term or on any function name to alter the other terms used in the function. A new page will open, where changes to function terms can be made.
[[File:Example of Change Multivariate Function Sreen.png|center|thumb|950x950px|An example of the Change Multivariate Function screen for Bilateral Aid Exports.]]
Click on the desired b coefficient to change the value for that coefficient. The b coefficients are based upon the standard function shown above the table; for example, b4 is for logarithmic functions. Once clicked, enter the desired value, then click '''Continue''' to save that term and repeat for each coefficient term desired to change. Then click '''Continue''' to save and update the function. Remember, starting IFs again resets all functions to standard values, and although runs of the model that you make with altered functions will reflect the changes in functions, no information about the changed functions is saved with the model Run Files. Keep track of these changes somewhere for replicability.

Again, [[Running the Model|run the model]] using the [[Quick Scenario Analysis with Tree]] option from the Main Menu to see the results of the altered functions. Once the model has run, a [[Understand Scenarios in IFs#Scenario Files and Run Files|new working file]] is loaded that reflects the changed functions and their impact on all computations. Compare this working file (or a saved run file version of it) with the base case or with other scenarios.

Reload Base

2026-03-25T21:40:37Z

Ethan.Sullivan:

Use the ''Reload Base'' feature in IFs to reload the base case run to the working file. This may be helpful when working with a large number of run files, as it will reset the base case as the default scenario option and can be accessed from the scenario drop-down at the top of the list. From the ''Main Menu,'' choose '''[[Scenario Analysis]]''' and click '''''Reload Base'''''. A message will appear stating that the base has successfully been reloaded.

Quick Scenario Analysis with Tree

2026-03-25T21:37:49Z

Ethan.Sullivan:

The ''Quick Scenario Analysis with Tree'' page can be accessed from the Main Menu by selecting '''[[Scenario Analysis]]''' and then '''''Quick Scenario Analysis with Tree'''.'' Use this feature to develop, review, and edit scenarios in IFs. This feature allows for building and editing a Scenario File (.sce) which loads interventions to be run in the IFs model to produce a Run File (.run), which displays scenario results.
[[File:Example of the Quick Scenario Guide.png|center|thumb|950x950px|An example of the Quick Scenario Guide page in IFs when first opened.]]
This page has a number of features and options to create, load, adjust, and run scenarios. These options and features include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* [[Understand_Scenarios_in_IFs#Scenario_Files_and_Run_Files|'''Scenario Files''']]:
** '''Clear Tree''': Clear any interventions currently loaded to the scenario tree.
** '''Open''': Load any set of saved or preloaded Scenario Files (.sce). Hover over folder names to find and select the desired scenario. The '''Open''' drop-down folders reflect those in \IFs\Scenario file path on the current device. The scenare tree will update with the interventions in the chosen scenario file.
** '''Name and Save''': Open a pop-up to save the scenario currently reflected in the scenario tree. The pop-up includes two fields to enter text into; type the desired scenario file name and folder name in the fields, then click '''Save''' or '''Cancel'''. The two fields are:
*** '''File Name''': Enter a file name for the created scenario, which will create a scenario file named ''FileName.sce.''
*** '''Folder Name''': Enter a new or already existing folder name to save the scenario file to that location. This folder will show up in \IFs\Scenario\User Defined Scenarios\ on the current device.
** '''Export to IFs Standard CSV Format''': Save a CSV version of the scenario to the same folder that the currently displayed scenario is stored in. For newly created scenarios, click '''Name and Save''' first before clicking this option. CSV versions of scenarios can be easier to manage and understand, as all years and dimensions are aligned in titled columns, unlike Scenario Files (.sce) that are written in comma-separated text format.
** '''Export Working File''': Download a Scenario File (.sce) of the current scenario tree.
** '''Import IFs Standard CSV Format files''': Load a scenario that has been saved using the '''Export to IFs Standard CSV Format''' in the scenario tree. This requires that a scenario has previously been saved using the IFs standard CSV format and located in a folder within \IFs\Scenario\. Follow the appropriate file path and click on the desired scenario CSV to import.
* '''Add Scenario Component''': Similar to '''Open''' from the '''Scenario Files''' options. Layer multiple scenario files or interventions by adding components from another scenario once one has loaded.
* '''[[Running the Model|Run Scenario]]''': Open the '''[[Running the Model|Run]]''' page for the current scenario in the scenario tree. Adjust the horizon to the desired end year and click '''Start Run'''.
* '''Delete Selection''': When an intervention is displayed on the screen next to the scenario tree from either clicking on a parameter directly in the tree or from the '''Parameter Search''' option, click '''Delete''' to remove that intervention from the current scenario.
* '''[[Country/Region, Group or G-List|Set Group or Country]]''': Click '''Groups''' to make interventions for particular groups, or '''Countries''' for a particular country or countries. The current selection will have a checkmark next to it.
* '''Annotate Scenario''': Click Annotate to open a description of the scenario interventions based on the current Scenario Tree. An annotation is generated by default, which can be edited or supplemented with explanatory or narrative information describing the scenario. To edit the annotation, click in the text box and change or add text as desired. Below the text box click '''Save''' to save edits, '''Clear''' to remove all text in the annotation, '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Exit''' to return to the ''Quick Scenario Analysis with Tree.''
* '''Parameter Search''': Click '''Search''' to open the ''Parameter Search'' page to search to find and select specific parameters. The Parameter Search feature is described below.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]].

= <span style="font-size:xx-large;">Parameter Search</span> =

Use the ''Parameter Search'' feature to search, explore, and choose parameters to adjust for scenario analysis. Use this feature with the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' to find the parameters most useful for the intended intervention or scenario goal. Type the desired parameter name in the search bar, then click '''Search'''. Click on the parameter, which will bring up a few options described below. Click '''Load''' to select this parameter in the scenario tree. Click '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Continue''' to go back to the previous menu or to the Main Menu of IFs.
[[File:Example of Parameter Search Option.png|center|thumb|950x950px|An example of the Parameter Search option for the total fertility rate multiplier tfrm.]]
The options, once a parameter is clicked, include:
* '''Define''': See a brief definition of the parameter and how it works, where available.
* '''Block Diagram (Pop-Up)''': Open a new tab with a wiki page displaying a diagram and text explanation that broadly explains how drivers interact for the area of inquiry (agriculture, economics, etc.), where available.
* '''Equations (Pop-Up)''': Open a new tab with a wiki page of the mathematical equations that are used to determine this parameter, where available.

= <span style="font-size:xx-large;">Using the Scenario Tree</span> =
The easiest way to create scenario interventions is to use the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' along with the Parameter Search option, described above. The Scenario Tree can also be used to find and select a parameter. Click on any of the categories in the Scenario Tree (ex., Technological change. to open sub -categories and eventually to open up a parameter choices box. Once this box appears to the right of the scenario tree with parameter names and descriptions, click on any parameter to reveal a few options shown below.
[[File:Example of Scenario Tree usage.png|center|thumb|950x950px|An example of the scenario tree being used for Technological Change, Energy, and with the QEM parameter selected; shows the options that selecting a parameter will reveal.]]
The options include:

* '''Select''': Choose the parameter in order to load and edit it.
* '''Drivers''': Click to see what variables are affecting the chosen parameter, where available.
* '''Explain (Pop-Up)''': Open a new tab with a wiki page displaying a diagram and text explanation that broadly explains how drivers interact for the area of inquiry (agriculture, economics, etc.), where available.
* '''View Equations (Pop-Up)''': Open a new tab with a wiki page of the mathematical equations that are used to determine this parameter, where available.
* '''Define''': See a brief definition of the parameter and how it works, where available.

= Adjusting Parameters =
Once a parameter is chosen by clicking '''Select''', as described above, a drop-down will appear to choose either a particular [[Country/Region, Group or G-List|country or group]]. Choose the desired country or group by clicking on it. Another drop-down will appear if the parameter has dimensions (e.g., Male, Female, Total), click on the desired dimension choice, and repeat if the parameter has multiple dimension choices. After this, the selected parameter will appear to the right of the tree with its base value or scenario value (if opened within an already made scenario) shown. An example of this screen is shown below.
[[File:Example of Parameter Adjustment on Scenario Tree.png|center|thumb|950x950px|An example of a parameter selected to adjust on the Quick Scenario Analysis Tree page. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
This screen offers a few basic options for adjusting parameters. Adjust the initial parameter value to make interventions using default changes by clicking the bubble for '''High''' or '''Low''', or to return to the base, click '''Base'''. Alternately, use the slider or enter the desired number into the field above the slider and click '''Apply'''. Using this slider or field option will apply that value to the whole time horizon to the year 2150, with an initial shift period based upon the choice from the '''Shift Years''' dropdown. In the example, the value is 5.177, and the shift years are 10, so the parameter interpolates from 1 to 5.177 from 2020 to 2030 and then stays at that value for the whole horizon.

For developing high-quality scenarios, full parameter customization is recommended. Click '''Fully Customize''' for more options and to load the '''Change Values''' screen'''.'''
[[File:Example of the Fully Customize Parameter option.png|center|thumb|950x950px|An example of the Fully Customize option for parameter changes. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
The '''Fully Customize''' option allows more control over parameter behavior. The '''Information''' table displays information on parameter value for a given year, and the minimum and maximum values that IFs recommends for intervention. If above or below these, a warning message will appear. Use the '''Year''' field in this table to jump to a particular year to view the value or to start an intervention from.

The '''Change Numerically''' table is where the changes to a parameter are made. Use the '''Next Year''' or '''Previous Year''' buttons to change the '''Year''' field by one. Once at the desired year to start an intervention shown in the '''Year''' field, enter in the '''Desired Value''' field the value to change the parameter to, use the '''Years to Repeat or Interpolate''' field to set the number of years for the intervention to take place (this includes the current year so to increase the value for the next 10 years, enter 11). Click '''Change/Repeat''' to apply the desired value for the number of years entered (for example, an increase to 8 for 61 years from 2090 to 2150, shown above) or click '''Interpolate''' to smoothly shift the value over the number of years entered from the current value to the desired value. Continue to use the '''Change Numerically''' table until the parameter is adjusted as desired.

To ensure that the parameter is adjusted as desired, hover over the graph on the right side of the page to see the parameter value in any given year. Click '''Register Change''' to apply this intervention to the current scenario, '''Cancel All Changes''' to clear the current parameter adjustments, '''Exit to Scenario Tree''' to return to the scenario tree, or '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]].

IFs Network Diagram

2026-03-25T20:57:05Z

Ethan.Sullivan:

== What is the IFs Network Diagram? ==

The IFs Network Diagram is an interactive visualization of the internal structure of the International Futures (IFs) model. It shows the variable and parameter relationships 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.[[File:Screenshot 2026-03-24 091534.png|center|thumb|990x990px]]

== Views ==
The diagram has three levels:

* Macro view: Shows the 11 major categories in IFs
[[File:Picture 2.png|thumb|center|457x457px]]
* Use this view to see the big picture of how sectors connect

* Meso view: Shows the subcategories within each meso category and their connections
[[File:Picture 3.png|center|thumb]]
* Use this view to gain more detail without seeing every variable

* Variable view: Shows all individual variables and parameters (nodes) and their links
[[File:Picture 4.png|center|thumb]]
* 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
[[File:Picture 5.png|center|thumb]]
* Zoom In / Zoom Out / Fit to Screen (Bottom Left Corner):
[[File:Picture 6.png|center|thumb]]

* Download:
* Download a .png image of the current view
[[File:Picture 7.png|center|thumb]]

* Help Panel:

* Opens pop-up with link to full instructions
[[File:Picture 8.png|center|thumb]]

Variable View

Some features are only available in Variable View:

[[File:Picture 9.png|center|thumb]]

* 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
[[File:Picture 10.png|center|thumb]]
* Nearest Neighbor: shows all nodes that are connected to the selected root node, up to three degrees away
[[File:Picture 11.png|center|thumb]]
* 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:
[[File:Picture 12.png|center|thumb]]

* 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.
[[File:Picture 13.png|center|thumb]]

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.
[[File:Picture 14.png|center|thumb]]

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

2026-03-25T20:30:37Z

Ethan.Sullivan:

== What is the IFs Network Diagram? ==

The IFs Network Diagram is an interactive visualization of the internal structure of the International Futures (IFs) model. It shows the variable and parameter relationships 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.[[File:Screenshot 2026-03-24 091534.png|center|thumb|990x990px]]

== Views ==
The diagram has three levels:

* Macro view: Shows the 11 major categories in IFs
[[File:Picture 2.png|thumb|center|457x457px]]
* Use this view to see the big picture of how sectors connect

* Meso view: Shows the subcategories within each meso category and their connections
[[File:Picture 3.png|center|thumb]]
* Use this view to gain more detail without seeing every variable

* Variable view: Shows all individual variables and parameters (nodes) and their links
[[File:Picture 4.png|center|thumb]]
* 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
[[File:Picture 5.png|center|thumb]]
* Zoom In / Zoom Out / Fit to Screen (Bottom Left Corner):
[[File:Picture 6.png|center|thumb]]

* Download:
* Download a .png image of the current view
[[File:Picture 7.png|center|thumb]]

* Help Panel:

* Opens pop-up with link to full instructions
[[File:Picture 8.png|center|thumb]]

Variable View

Some features are only available in Variable View:

[[File:Picture 9.png|center|thumb]]

* 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
[[File:Picture 10.png|center|thumb]]
* Nearest Neighbor: shows all nodes that are connected to the selected root node, up to three degrees away
[[File:Picture 11.png|center|thumb]]
* 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:
[[File:Picture 12.png|center|thumb]]

* 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.
[[File:Picture 13.png|center|thumb]]

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.
[[File:Picture 14.png|center|thumb]]

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

2026-03-25T20:22:13Z

Ethan.Sullivan:

= What is the IFs Network Diagram? =
The IFs Network Diagram is an interactive visualization of the internal structure of the International Futures (IFs) model. It shows the variable and parameter relationships 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.[[File:Screenshot 2026-03-24 091534.png|center|thumb|990x990px]]

= Views =
The diagram has three levels:

* Macro view: Shows the 11 major categories in IFs
[[File:Picture 2.png|thumb|center|457x457px]]
* Use this view to see the big picture of how sectors connect

* Meso view: Shows the subcategories within each meso category and their connections
[[File:Picture 3.png|center|thumb]]
* Use this view to gain more detail without seeing every variable

* Variable view: Shows all individual variables and parameters (nodes) and their links
[[File:Picture 4.png|center|thumb]]
* 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
[[File:Picture 5.png|center|thumb]]
* Zoom In / Zoom Out / Fit to Screen (Bottom Left Corner):
[[File:Picture 6.png|center|thumb]]

* Download:
* Download a .png image of the current view
[[File:Picture 7.png|center|thumb]]

* Help Panel:

* Opens pop-up with link to full instructions
[[File:Picture 8.png|center|thumb]]

Variable View

Some features are only available in Variable View:

[[File:Picture 9.png|center|thumb]]

* 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
[[File:Picture 10.png|center|thumb]]
* Nearest Neighbor: shows all nodes that are connected to the selected root node, up to three degrees away
[[File:Picture 11.png|center|thumb]]
* 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:
[[File:Picture 12.png|center|thumb]]

* 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.
[[File:Picture 13.png|center|thumb]]

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.
[[File:Picture 14.png|center|thumb]]

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'''

International Futures (IFs)

2026-03-25T20:13:11Z

Ethan.Sullivan:

'''Welcome to the International Futures (IFs) wiki. '''

'''[[Introduction_to_IFs|Introduction to IFs]]''' - Click here for an overview of the IFs system, including a description of the tool's purpose and major assumptions in its Base Case forecasts.

'''[[Use_IFs_(Download_Version)|Use IFs (Download Version)]] '''- Click here for instructions on using the standalone desktop version of IFs.

'''[[Use_IFs_(Online_Version)|Use IFs (Online Version)]] '''- Click here for instructions on using the web (cloud) version of IFs.

'''[[Understand_the_Model|Understand IFs]]''' - Click here to access documentation on each of the major system models in IFs. 

'''[[IFs_Network_Diagram|IFs Network Diagram]]''' - Click here for instructions on using the IFs Network Diagram.

'''[[Guide_to_Scenario_Analysis_in_International_Futures_(IFs)|Guide to Scenario Analysis in IFs]] '''- Click here for instructions on creating and comparing alternative scenarios in IFs. This guide also includes an updated list of IFs parameters.

'''[[Project_Documentation|Project Documentation]] '''- Click here for documentation regarding ongoing projects at the Frederick S. Pardee Center.

'''[[Data]] '''- Click here for data updates

'''[[Additional_resources|Additional Resources]]'''

'''[[Index Page For All Other Version Notes|Version Notes]]''' - Click here to download the latest version of IFs and view an index of previous version notes.

[https://forms.office.com/Pages/ResponsePage.aspx?id=N3A8b8KF5kCd7BiwLSiSiAabQPS0TfVGq22zkCelI51UMko4UFpVRk5BQTVRSTU5NExSV0JBV1BYUSQlQCN0PWcu '''Newsletter Subscription Link''']

== Feedback ==

Feedback on how to improve IFs is always appreciated, especially if you find something that is not working. Compliments are also accepted. To send feedback or if you have any questions about using IFs, please email us at pardee.center [at] du.edu. You can also find additional contact information on our center's website. 

IFs Network Diagram

2026-03-24T15:17:29Z

Ethan.Sullivan: Test image

IFs Network Diagram User Documentation

What is the IFs Network Diagram?
[[File:Screenshot 2026-03-24 091534.png|center|thumb|990x990px]]

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|thumb|center|457x457px]]
* Use this view to see the big picture of how sectors connect

* Meso view: Shows the subcategories within each meso category and their connections
[[File:Picture 3.png|center|thumb]]
* Use this view to gain more detail without seeing every variable

* Variable view: Shows all individual variables and parameters (nodes) and their links
[[File:Picture 4.png|center|thumb]]
* 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
[[File:Picture 5.png|center|thumb]]
* Zoom In / Zoom Out / Fit to Screen (Bottom Left Corner):
[[File:Picture 6.png|center|thumb]]

* Download:
* Download a .png image of the current view
[[File:Picture 7.png|center|thumb]]

* Help Panel:

* Opens pop-up with link to full instructions
[[File:Picture 8.png|center|thumb]]

Variable View

Some features are only available in Variable View:

[[File:Picture 9.png|center|thumb]]

* 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
[[File:Picture 10.png|center|thumb]]
* Nearest Neighbor: shows all nodes that are connected to the selected root node, up to three degrees away
[[File:Picture 11.png|center|thumb]]
* 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:
[[File:Picture 12.png|center|thumb]]

* 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.
[[File:Picture 13.png|center|thumb]]

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.
[[File:Picture 14.png|center|thumb]]

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'''

File:Screenshot 2026-03-24 091534.png

2026-03-24T15:16:36Z

Ethan.Sullivan:

Screenshot of network diagram Macro

Change Selected Functions

2026-02-14T01:13:39Z

Ethan.Sullivan:

Variables are forecast based on mathematical relationships that are represented by functions within IFs. These functions can be changed based on different understandings of relationships between variables. Changing functions gives you a powerful tool for using IFs to investigate possible futures and, to an extent, to change the model itself. Change the relationships between two variables or multiple variables using the ''Bivariate'' and ''Multivariate function'' pages.

= <span style="font-size:xx-large;">Bivariate Functions</span> =

To open the ''Bivariate Functions'' page from the Main Menu of IFs: choose '''Scenario Analysis''', '''Change Selected Functions''', and click '''''Bivariate Function.''''' Once on the ''Bivariate Function'' page, search for a particular function in the '''Filter Functions (press enter)''' field or scroll through the '''Function (click to see/edit)''' dropdown to view a relationship that is already in IFs. Use the filter options ('''Used in Run''', '''Used in Historical Run,''' etc.) to the right of the dropdown to filter for functions that are used for particular model tasks, or not used at all.
[[File:Example of Bivariate Function page.png|center|thumb|950x950px|An example of the Bivariate Function page used to change functions in IFs.]]
When a function is clicked, the relationship of the function will be shown in graph form at the bottom of the screen. Depending on the type of function, an R-squared and standard error of the relationship may also be shown below the graph. Export the graph by clicking on the three lines in the upper right corner of the graph, then select the desired format to export.

To change a chosen function, use the '''Table Functions Points''' frame option or the '''Analytic Function''' button option to specify a new relationship.

'''Table Functions Points''': A table function relationship is based upon lines that connect given points. In the '''Table''' '''Function Points''' frame, there are boxes for specifying the X-axis and Y-axis values. Specify a desired point by entering the X and Y axis values, then click '''Add'''. Add as many points as desired, and click '''Previous''' and '''Next''' to move between already created points. Click '''Delete''' to remove a point from the graph. When the points desired to create a function with are all added, click '''Alter''' to alter the function to now be based on this new relationship.

'''Analytic Function''': Click to open the ''Specify Analytic Function'' page. Use this page to change the mathematical formula of a function by adjusting its function terms. A function based on a linear regression will only have a and b1 terms, and altering other bs will change the whole function type. More complex functions will use different b terms, for example, an exponential will use b2 and a logarithmic b4.
[[File:Example of the Specify Analytic Function page.png|center|thumb|950x950px|An example of the Specify Analytic Function page, for GDP and car sales.]]
Change the '''Display Figure from X Value''' and '''To X Value''' fields to change the graph in the ''Bivariate Functions'' screen. Once the function is changed as desired, click '''Save and Continue''' to save and return to the ''Bivariate Functions'' page or '''Exit - Abandon Changes''' to return without saving the change.

Click '''Reverse Changes''' to return to the default for the selected function, '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Exit''' to return to the ''Main Menu''. After clicking '''Exit,''' IFs gives a very important informational warning on how any function changes will be active only in the current session of IFs. Starting IFs again resets all functions to standard values. Moreover, although runs of the model that you make with altered functions will reflect the changes in functions, no information about the changed functions is saved with the model Run Files. Keep track of these changes somewhere for replicability.

Now [[Running the Model|run the model]] using the [[Quick Scenario Analysis with Tree]] option from the Main Menu. Once the model has run a [[Understand Scenarios in IFs#Scenario Files and Run Files|new working file]] that reflects the changed functions and their impact on all computations is loaded. Compare this working file (or a saved run file version of it) with the base case or with other scenarios.

= <span style="font-size:xx-large;">Multivariate Functions</span> =

To open the ''Multivariate Functions'' page from the Main Menu of IFs: choose '''Scenario Analysis''', '''Change Selected Functions''', and click '''''Multivariate Functions'''.'' This page displays a table with multivariate function names, their intercept, R-squared, and standard errors. Search for a particular function using the search bar or scroll through the table to find the desired function. Use the filter options ('''Used in Run''', '''Used in Historical Run,''' etc.) to the right of the table to filter for functions that are used for particular model tasks, or not used at all.
[[File:Example of Multivariate Functions page.png|center|thumb|950x950px|An example of the Multivariate Functions page.]]
Click on any intercept to change the intercept term or on any function name to alter the other terms used in the function. A new page will open, where changes to function terms can be made.
[[File:Example of Change Multivariate Function Sreen.png|center|thumb|950x950px|An example of the Change Multivariate Function screen for Bilateral Aid Exports.]]
Click on the desired b coefficient to change the value for that coefficient. The b coefficients are based upon the standard function shown above the table; for example, b4 is for logarithmic functions. Once clicked, enter the desired value, then click '''Continue''' to save that term and repeat for each coefficient term desired to change. Then click '''Continue''' to save and update the function. Remember, starting IFs again resets all functions to standard values, and although runs of the model that you make with altered functions will reflect the changes in functions, no information about the changed functions is saved with the model Run Files. Keep track of these changes somewhere for replicability.

Again, [[Running the Model|run the model]] using the [[Quick Scenario Analysis with Tree]] option from the Main Menu to see the results of the altered functions. Once the model has run a [[Understand Scenarios in IFs#Scenario Files and Run Files|new working file]] that reflects the changed functions and their impact on all computations is loaded. Compare this working file (or a saved run file version of it) with the base case or with other scenarios.

Understand Scenarios in IFs

2026-02-14T01:07:23Z

Ethan.Sullivan:

= Introduction to Scenarios =
A scenario is a story or story outline. Thinking about the future normally involves creating alternative scenarios, or stories, about the possible evolution of drivers. Some such scenarios are exploratory and consider the possible unfolding of different futures around key uncertainties, such as the rate of some aspect of technological advance or the fragility of some element in the global environment. Other scenarios are normative and develop stories about preferred futures, such as a global transformation to sustainability.

Scenarios in a large integrated model typically are built from multiple interventions that collectively help build a coherent story about the future. Often, but somewhat imprecisely, the word ''scenario'' is used more loosely to refer to any intervention (such as the change of a fertility rate for a country or an alternative assumption about oil resources).

Scenarios or interventions with respect to what? When IFs or other computer simulations are "run", without making any changes to parameters or initial conditions specified as the default values, they generate a forecast that is typically called the base case (sometimes reference run). The IFs base case, always available when a model session is initiated, is itself a scenario. Sometimes the base case is incorrectly referred to as a trend extrapolation or a "business as usual" scenario. More accurately, however, the base case of IFs is a computation that involves the full dynamics of the model and therefore has very nonlinear behavior, often quite different from trends. It is a good starting point for scenario analysis for two reasons. First, it is built from initial conditions of all variables that have been given reasonable values from data or other analysis. These initial conditions and parameters make up the package of interventions that constitute the base case scenario. Second, the base case is periodically analyzed relative to the forecasts of many other projects across the range of issue areas covered by IFs and sometimes "tuned" to reproduce the behavior of respected forecasters.

= Creating Scenarios in IFs =
Change initial conditions and parameters using the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create scenarios beyond the base case. Adjust parameters to make specific intended interventions, for example use the Government Spending by Destination and Sector multiplier parameter gdsm to increase government spending in education. A detailed guide of the different parameters and their potential uses can be found in the [[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis]].

==== Scenario Files and Run Files ====
Use the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create and save two different kinds of files: ''S''cenario Files (.sce) and Run Files (.run). The Scenario Files represent changes that were made to parameters in IFs but that have not yet run through IFs. Scenario Files will be saved with .sce as the file extension. The Run Files are files that hold forecast results after the IFs software has run. Run Files will be saved with .run as the file extension. The running of a Scenario Files through the IFs software, will include those parameter changes in the scenario file while the model runs and will produce a Run File. The most recent Run File produced by running the model is called the ''Working-File''. By default the Working-File is the base case until the model is run.

In addition to the base case, some versions of IFs will include a number of other previously-run scenarios, perhaps the set of scenarios for the National Intelligence Council’s (NIC) 2020 Project or those for the five Shared Socioeconomic Pathways. In the '''Scenarios''' drop down in Flex Displays, a list of previously-run scenarios is shown before any new scenarios are run. Because those have already been run, based on a set of interventions constituting their foundations, their results can already be displayed.

= Parameter Types =
Parameters are numbers that determine relationships among variables in the equations of IFs. Parameters are often set to a single value across time and they therefore do not always "vary" as do "real" variables. Many parameters are "policy handles," the value of which are set in order to determine the behavior of the model. In IFs parameters are written in lower case form such as endemm and variables are written in upper case such as ENDEM. There are several types of parameters that include:

'''Multiplier''': An equation result parameter that multiplies results (of variable calculations) by the value of the parameter. These parameters are 1 by default, thereby leaving what is multiplied unchanged. Examples of multipliers include: enpm (energy production multiplier), or tfrm (total fertility rate multiplier). Note that multipliers typically end with the letter "m".

'''Additive Factor''': Also, an equation result parameter. Changes results by adding the value of the parameter to the results. These parameters are 0 by default, thereby leaving what is added unchanged. Some examples are: mfpadd (an additive factor on multi-factor productivity growth rate), or migrateinadd (migration rate inward additive factor). Additive Factors typically end with “add”.

'''Switch''': Turn off or on model elements, therefore they alter the structure of the model. They generally take on values of 1 (on) or 0 (off). Switches are most often on or off for the entire run, but it sometimes makes sense to "throw a switch" in the middle of a run. Switch examples include: agon (agriculture economy linkage) and squeez (economic impact of energy shortage). Switch parameters may end in "sw" but have no specific naming structure.

'''Initial Condition''': These are not strictly parameters, but rather first-year values for variables that are subsequently computed by the model, or values for rates of change. These cannot be changed in years beyond the base. These include parameters like: carinit (carbon dioxide in atmosphere in base year, initial condition) or igdpr (initial gdp growth rate). There is no specific naming structure to these parameters.

'''Limit''': These parameters set a limit for a variable such as the maximum or minimum. Some examples include: watwastetreatcostupper (wastewater treatment unit maximum cost, limit) or ylmax (maximum possible agricultural yield, limit). There is no specific naming structure to these parameters but many end in “max” “min” "upper" and "lower".

'''Rate''': Change rates directly or to alter rates of growth or decline. Some examples of rate parameters are: femshrgr (annual growth of female share of the labor force, rate) or ginidomr (domestic gini index growth rate). There is no specific naming structure to these parameters.

'''Relationships''': Set or alter the relationship between two variables, by setting or altering the response level of one variable based on changes in another. Examples include: fpricr1 (food prices response to stock level, relationship) or elasde (energy demand to change in price, relationship)

'''Target''': These are parameters that set a target value and the number of years to achieve certain targets or convergence between countries or variables. Target parameters typically come in pairs with the first parameter setting the target for a variable and the second setting the number of years to achieve that target. For example: sanithhbasictrgtval (percent of people with at least basic sanitation service, Target) and sanithhbasictrgtyr (percent of people with at least basic sanitation service, year to achieve, target). Many times, these parameters end in “val” and “yr” corresponding with setting the target value and year respectively. Another common ending for target parameters is “conv” for conversion targets.

'''Level''': Parameters that override the value of a variable, like: enprix (energy price, level). There is no specific naming structure to these parameters.

'''Function Coefficient''': Alter terms in internal calculations. These parameters will change the underlying structure of equations in the model and as a result will alter the values of variables. Examples of function coefficients include: labinformcoeffintercept (Intercept in the Calculation of Informal Labor Share, Function Coefficient) or govriskweight (Weights in the Calculation of the Government Risk Index, Function Coefficient).

The focus here is on exogenous parameters only - on those elements of the model that can be manually changed. Many computed variables are used in the computation of other variables in the same way that parameters are, as multipliers, additive factors, coefficients, and so on. These can be displayed too, but unlike true parameters, they cannot be changed.

Understand Scenarios in IFs

2026-02-14T01:06:41Z

Ethan.Sullivan:

= Introduction to Scenarios =
A scenario is a story or story outline. Thinking about the future normally involves creating alternative scenarios, or stories, about the possible evolution of drivers. Some such scenarios are exploratory and consider the possible unfolding of different futures around key uncertainties, such as the rate of some aspect of technological advance or the fragility of some element in the global environment. Other scenarios are normative and develop stories about preferred futures, such as a global transformation to sustainability.

Scenarios in a large integrated model typically are built from multiple interventions that collectively help build a coherent story about the future. Often, but somewhat imprecisely, the word ''scenario'' is used more loosely to refer to any intervention (such as the change of a fertility rate for a country or an alternative assumption about oil resources).

Scenarios or interventions with respect to what? When IFs or other computer simulations are "run", without making any changes to parameters or initial conditions specified as the default values, they generate a forecast that is typically called the base case (sometimes reference run). The IFs base case, always available when a model session is initiated, is itself a scenario. Sometimes the base case is incorrectly referred to as a trend extrapolation or a "business as usual" scenario. More accurately, however, the base case of IFs is a computation that involves the full dynamics of the model and therefore has very nonlinear behavior, often quite different from trends. It is a good starting point for scenario analysis for two reasons. First, it is built from initial conditions of all variables that have been given reasonable values from data or other analysis. These initial conditions and parameters make up the package of interventions that constitute the base case scenario. Second, the base case is periodically analyzed relative to the forecasts of many other projects across the range of issue areas covered by IFs and sometimes "tuned" to reproduce the behavior of respected forecasters.

= Creating Scenarios in IFs =
Change initial conditions and parameters using the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create scenarios beyond the base case. Adjust parameters to make specific intended interventions, for example use the Government Spending by Destination and Sector multiplier parameter gdsm to increase government spending in education. A detailed guide of the different parameters and their potential uses can be found in the [[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis]].

==== Files and Run Files ====
Use the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create and save two different kinds of files: ''S''cenario Files (.sce) and Run Files (.run). The Scenario Files represent changes that were made to parameters in IFs but that have not yet run through IFs. Scenario Files will be saved with .sce as the file extension. The Run Files are files that hold forecast results after the IFs software has run. Run Files will be saved with .run as the file extension. The running of a Scenario Files through the IFs software, will include those parameter changes in the scenario file while the model runs and will produce a Run File. The most recent Run File produced by running the model is called the ''Working-File''. By default the Working-File is the base case until the model is run.

In addition to the base case, some versions of IFs will include a number of other previously-run scenarios, perhaps the set of scenarios for the National Intelligence Council’s (NIC) 2020 Project or those for the five Shared Socioeconomic Pathways. In the '''Scenarios''' drop down in Flex Displays, a list of previously-run scenarios is shown before any new scenarios are run. Because those have already been run, based on a set of interventions constituting their foundations, their results can already be displayed.

= Parameter Types =
Parameters are numbers that determine relationships among variables in the equations of IFs. Parameters are often set to a single value across time and they therefore do not always "vary" as do "real" variables. Many parameters are "policy handles," the value of which are set in order to determine the behavior of the model. In IFs parameters are written in lower case form such as endemm and variables are written in upper case such as ENDEM. There are several types of parameters that include:

'''Multiplier''': An equation result parameter that multiplies results (of variable calculations) by the value of the parameter. These parameters are 1 by default, thereby leaving what is multiplied unchanged. Examples of multipliers include: enpm (energy production multiplier), or tfrm (total fertility rate multiplier). Note that multipliers typically end with the letter "m".

'''Additive Factor''': Also, an equation result parameter. Changes results by adding the value of the parameter to the results. These parameters are 0 by default, thereby leaving what is added unchanged. Some examples are: mfpadd (an additive factor on multi-factor productivity growth rate), or migrateinadd (migration rate inward additive factor). Additive Factors typically end with “add”.

'''Switch''': Turn off or on model elements, therefore they alter the structure of the model. They generally take on values of 1 (on) or 0 (off). Switches are most often on or off for the entire run, but it sometimes makes sense to "throw a switch" in the middle of a run. Switch examples include: agon (agriculture economy linkage) and squeez (economic impact of energy shortage). Switch parameters may end in "sw" but have no specific naming structure.

'''Initial Condition''': These are not strictly parameters, but rather first-year values for variables that are subsequently computed by the model, or values for rates of change. These cannot be changed in years beyond the base. These include parameters like: carinit (carbon dioxide in atmosphere in base year, initial condition) or igdpr (initial gdp growth rate). There is no specific naming structure to these parameters.

'''Limit''': These parameters set a limit for a variable such as the maximum or minimum. Some examples include: watwastetreatcostupper (wastewater treatment unit maximum cost, limit) or ylmax (maximum possible agricultural yield, limit). There is no specific naming structure to these parameters but many end in “max” “min” "upper" and "lower".

'''Rate''': Change rates directly or to alter rates of growth or decline. Some examples of rate parameters are: femshrgr (annual growth of female share of the labor force, rate) or ginidomr (domestic gini index growth rate). There is no specific naming structure to these parameters.

'''Relationships''': Set or alter the relationship between two variables, by setting or altering the response level of one variable based on changes in another. Examples include: fpricr1 (food prices response to stock level, relationship) or elasde (energy demand to change in price, relationship)

'''Target''': These are parameters that set a target value and the number of years to achieve certain targets or convergence between countries or variables. Target parameters typically come in pairs with the first parameter setting the target for a variable and the second setting the number of years to achieve that target. For example: sanithhbasictrgtval (percent of people with at least basic sanitation service, Target) and sanithhbasictrgtyr (percent of people with at least basic sanitation service, year to achieve, target). Many times, these parameters end in “val” and “yr” corresponding with setting the target value and year respectively. Another common ending for target parameters is “conv” for conversion targets.

'''Level''': Parameters that override the value of a variable, like: enprix (energy price, level). There is no specific naming structure to these parameters.

'''Function Coefficient''': Alter terms in internal calculations. These parameters will change the underlying structure of equations in the model and as a result will alter the values of variables. Examples of function coefficients include: labinformcoeffintercept (Intercept in the Calculation of Informal Labor Share, Function Coefficient) or govriskweight (Weights in the Calculation of the Government Risk Index, Function Coefficient).

The focus here is on exogenous parameters only - on those elements of the model that can be manually changed. Many computed variables are used in the computation of other variables in the same way that parameters are, as multipliers, additive factors, coefficients, and so on. These can be displayed too, but unlike true parameters, they cannot be changed.

Quick Scenario Analysis with Tree

2026-02-14T01:04:35Z

Ethan.Sullivan:

The ''Quick Scenario Analysis with Tree'' page can be accessed from the Main Menu by selecting '''Scenario Analysis''' and then '''''Quick Scenario Analysis with Tree'''.'' Use this feature to develop, review, and edit scenarios in IFs. This feature allows for building and editing a Scenario File (.sce) which loads interventions to be run in the IFs model to produce a Run File (.run), which displays scenario results.
[[File:Example of the Quick Scenario Guide.png|center|thumb|950x950px|An example of the Quick Scenario Guide page in IFs when first opened.]]
This page has a number of features and options to create, load, adjust, and run scenarios. These options and features include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Scenario Files''':
** '''Clear Tree''': Clear any interventions currently loaded to the scenario tree.
** '''Open''': Load any set of saved or preloaded Scenario Files (.sce). Hover over folder names to find and select the desired scenario. The '''Open''' drop-down folders reflect those in \IFs\Scenario file path on the current device. The scenare tree will update with the interventions in the chosen scenario file.
** '''Name and Save''': Open a pop-up to save the scenario currently reflected in the scenario tree. The pop-up includes two fields to enter text into; type the desired scenario file name and folder name in the fields, then click '''Save''' or '''Cancel'''. The two fields are:
*** '''File Name''': Enter a file name for the created scenario, which will create a scenario file named ''FileName.sce.''
*** '''Folder Name''': Enter a new or already existing folder name to save the scenario file to that location. This folder will show up in \IFs\Scenario\User Defined Scenarios\ on the current device.
** '''Export to IFs Standard CSV Format''': Save a CSV version of the scenario to the same folder that the currently displayed scenario is stored in. For newly created scenarios, click '''Name and Save''' first before clicking this option. CSV versions of scenarios can be easier to manage and understand, as all years and dimensions are aligned in titled columns, unlike Scenario Files (.sce) that are written in comma-separated text format.
** '''Export Working File''': Download a Scenario File (.sce) of the current scenario tree.
** '''Import IFs Standard CSV Format files''': Load a scenario that has been saved using the '''Export to IFs Standard CSV Format''' in the scenario tree. This requires that a scenario has previously been saved using the IFs standard CSV format and located in a folder within \IFs\Scenario\. Follow the appropriate file path and click on the desired scenario CSV to import.
* '''Add Scenario Component''': Similar to '''Open''' from the '''Scenario Files''' options. Layer multiple scenario files or interventions by adding components from another scenario once one has loaded.
* '''[[Running the Model|Run Scenario]]''': Open the '''[[Running the Model|Run]]''' page for the current scenario in the scenario tree. Adjust the horizon to the desired end year and click '''Start Run'''.
* '''Delete Selection''': When an intervention is displayed on the screen next to the scenario tree from either clicking on a parameter directly in the tree or from the '''Parameter Search''' option, click '''Delete''' to remove that intervention from the current scenario.
* '''[[Country/Region, Group or G-List|Set Group or Country]]''': Click '''Groups''' to make interventions for particular groups, or '''Countries''' for a particular country or countries. The current selection will have a checkmark next to it.
* '''Annotate Scenario''': Click Annotate to open a description of the scenario interventions based on the current Scenario Tree. An annotation is generated by default, which can be edited or supplemented with explanatory or narrative information describing the scenario. To edit the annotation, click in the text box and change or add text as desired. Below the text box click '''Save''' to save edits, '''Clear''' to remove all text in the annotation, '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Exit''' to return to the ''Quick Scenario Analysis with Tree.''
* '''Parameter Search''': Click '''Search''' to open the ''Parameter Search'' page to search to find and select specific parameters. The Parameter Search feature is described below.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]].

= <span style="font-size:xx-large;">Parameter Search</span> =

Use the ''Parameter Search'' feature to search, explore, and choose parameters to adjust for scenario analysis. Use this feature with the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' to find the parameters most useful for the intended intervention or scenario goal. Type the desired parameter name in the search bar, then click '''Search'''. Click on the parameter, which will bring up a few options described below. Click '''Load''' to select this parameter in the scenario tree. Click '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Continue''' to go back to the previous menu or to the Main Menu of IFs.
[[File:Example of Parameter Search Option.png|center|thumb|950x950px|An example of the Parameter Search option for the total fertility rate multiplier tfrm.]]
The options, once a parameter is clicked, include: <span style="color:red">These options are not available for all parameters.
* '''Define''': See a brief definition of the parameter and how it works.
* '''Block Diagram (Pop-Up)''': Open a new tab with a wiki page displaying a diagram and text explanation that broadly explains how drivers interact for the area of inquiry (agriculture, economics, etc.).
* '''Equations (Pop-Up)''': Open a new tab with a wiki page of the mathematical equations that are used to determine this parameter.

= <span style="font-size:xx-large;">Using the Scenario Tree</span> =
The easiest way to create scenario interventions is to use the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' along with the Parameter Search option, described above. The Scenario Tree can also be used to find and select a parameter. Click on any of the categories in the Scenario Tree (ex., Technological change. to open sub -categories and eventually to open up a parameter choices box. Once this box appears to the right of the scenario tree with parameter names and descriptions, click on any parameter to reveal a few options shown below.
[[File:Example of Scenario Tree usage.png|center|thumb|950x950px|An example of the scenario tree being used for Technological Change, Energy, and with the QEM parameter selected; shows the options that selecting a parameter will reveal.]]
The options include: <span style="color:red">These options are not available for all parameters.

* '''Select''': Choose the parameter in order to load and edit it.
* '''Drivers''': Click to see what variables are affecting the chosen parameter.
* '''Explain (Pop-Up)''': Open a new tab with a wiki page displaying a diagram and text explanation that broadly explains how drivers interact for the area of inquiry (agriculture, economics, etc.).
* '''View Equations (Pop-Up)''': Open a new tab with a wiki page of the mathematical equations that are used to determine this parameter.
* '''Define''': See a brief definition of the parameter and how it works.

= Adjusting Parameters =
Once a parameter is chosen by clicking '''Select''', as described above, a drop-down will appear to choose either a particular [[Country/Region, Group or G-List|country or group]]. Choose the desired country or group by clicking on it. Another drop-down will appear if the parameter has dimensions (e.g., Male, Female, Total), click on the desired dimension choice, and repeat if the parameter has multiple dimension choices. After this, the selected parameter will appear to the right of the tree with its base value or scenario value (if opened within an already made scenario) shown. An example of this screen is shown below.
[[File:Example of Parameter Adjustment on Scenario Tree.png|center|thumb|950x950px|An example of a parameter selected to adjust on the Quick Scenario Analysis Tree page. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
This screen offers a few basic options for adjusting parameters. Adjust the initial parameter value to make interventions using default changes by clicking the bubble for '''High''' or '''Low''', or to return to the base, click '''Base'''. Alternately, use the slider or enter the desired number into the field above the slider and click '''Apply'''. Using this slider or field option will apply that value to the whole time horizon to the year 2150, with an initial shift period based upon the choice from the '''Shift Years''' dropdown. In the example, the value is 5.177, and the shift years are 10, so the parameter interpolates from 1 to 5.177 from 2020 to 2030 and then stays at that value for the whole horizon.

For developing high-quality scenarios, full parameter customization is recommended. Click '''Fully Customize''' for more options and to load the '''Change Values''' screen'''.'''
[[File:Example of the Fully Customize Parameter option.png|center|thumb|950x950px|An example of the Fully Customize option for parameter changes. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
The '''Fully Customize''' option allows more control over parameter behavior. The '''Information''' table displays information on parameter value for a given year, and the minimum and maximum values that IFs recommends for intervention. If above or below these, a warning message will appear. Use the '''Year''' field in this table to jump to a particular year to view the value or to start an intervention from.

The '''Change Numerically''' table is where the changes to a parameter are made. Use the '''Next Year''' or '''Previous Year''' buttons to change the '''Year''' field by one. Once at the desired year to start an intervention shown in the '''Year''' field, enter in the '''Desired Value''' field the value to change the parameter to, use the '''Years to Repeat or Interpolate''' field to set the number of years for the intervention to take place (this includes the current year so to increase the value for the next 10 years, enter 11). Click '''Change/Repeat''' to apply the desired value for the number of years entered (for example, an increase to 8 for 61 years from 2090 to 2150, shown above) or click '''Interpolate''' to smoothly shift the value over the number of years entered from the current value to the desired value. Continue to use the '''Change Numerically''' table until the parameter is adjusted as desired.

To ensure that the parameter is adjusted as desired, hover over the graph on the right side of the page to see the parameter value in any given year. Click '''Register Change''' to apply this intervention to the current scenario, '''Cancel All Changes''' to clear the current parameter adjustments, '''Exit to Scenario Tree''' to return to the scenario tree, or '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]].

Understand Scenarios in IFs

2026-02-06T18:22:17Z

Ethan.Sullivan:

= Introduction to Scenarios =
A scenario is a story or story outline. Thinking about the future normally involves creating alternative scenarios, or stories, about the possible evolution of drivers. Some such scenarios are exploratory and consider the possible unfolding of different futures around key uncertainties, such as the rate of some aspect of technological advance or the fragility of some element in the global environment. Other scenarios are normative and develop stories about preferred futures, such as a global transformation to sustainability.

Scenarios in a large integrated model typically are built from multiple interventions that collectively help build a coherent story about the future. Often, but somewhat imprecisely, the word ''scenario'' is used more loosely to refer to any intervention (such as the change of a fertility rate for a country or an alternative assumption about oil resources).

Scenarios or interventions with respect to what? When IFs or other computer simulations are "run", without making any changes to parameters or initial conditions specified as the default values, they generate a forecast that is typically called the base case (sometimes reference run). The IFs base case, always available when a model session is initiated, is itself a scenario. Sometimes the base case is incorrectly referred to as a trend extrapolation or a "business as usual" scenario. More accurately, however, the base case of IFs is a computation that involves the full dynamics of the model and therefore has very nonlinear behavior, often quite different from trends. It is a good starting point for scenario analysis for two reasons. First, it is built from initial conditions of all variables that have been given reasonable values from data or other analysis. These initial conditions and parameters make up the package of interventions that constitute the base case scenario. Second, the base case is periodically analyzed relative to the forecasts of many other projects across the range of issue areas covered by IFs and sometimes "tuned" to reproduce the behavior of respected forecasters.

= Creating Scenarios in IFs =
Change initial conditions and parameters using the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create scenarios beyond the base case. Adjust parameters to make specific intended interventions, for example use the Government Spending by Destination and Sector multiplier parameter gdsm to increase government spending in education. A detailed guide of the different parameters and their potential uses can be found in the [[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis]].

==== Scenario-Files and Run-Files ====
Use the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create and save two different kinds of files: ''Scenario-Files (.sce)'' and ''Run-Files (.run)''. The Scenario-Files represent changes that were made to parameters in IFs but that have not yet run through IFs. Scenario-Files will be saved with .sce as the file extension. The Run-Files are files that hold forecast results after the IFs software has run. Run-Files will be saved with .run as the file extension. The running of a Scenario-Files through the IFs software, will include those parameter changes in the scenario file while the model runs and will produce a Run-File. The most recent Run-File produced by running the model is called the ''Working-File''. By default the Working-File is the base case until the model is run.

In addition to the base case, some versions of IFs will include a number of other previously-run scenarios, perhaps the set of scenarios for the National Intelligence Council’s (NIC) 2020 Project or those for the five Shared Socioeconomic Pathways. In the '''Scenarios''' drop down in Flex Displays, a list of previously-run scenarios is shown before any new scenarios are run. Because those have already been run, based on a set of interventions constituting their foundations, their results can already be displayed.

= Parameter Types =
Parameters are numbers that determine relationships among variables in the equations of IFs. Parameters are often set to a single value across time and they therefore do not always "vary" as do "real" variables. Many parameters are "policy handles," the value of which are set in order to determine the behavior of the model. In IFs parameters are written in lower case form such as endemm and variables are written in upper case such as ENDEM. There are several types of parameters that include:

'''Multiplier''': An equation result parameter that multiplies results (of variable calculations) by the value of the parameter. These parameters are 1 by default, thereby leaving what is multiplied unchanged. Examples of multipliers include: enpm (energy production multiplier), or tfrm (total fertility rate multiplier). Note that multipliers typically end with the letter "m".

'''Additive Factor''': Also, an equation result parameter. Changes results by adding the value of the parameter to the results. These parameters are 0 by default, thereby leaving what is added unchanged. Some examples are: mfpadd (an additive factor on multi-factor productivity growth rate), or migrateinadd (migration rate inward additive factor). Additive Factors typically end with “add”.

'''Switch''': Turn off or on model elements, therefore they alter the structure of the model. They generally take on values of 1 (on) or 0 (off). Switches are most often on or off for the entire run, but it sometimes makes sense to "throw a switch" in the middle of a run. Switch examples include: agon (agriculture economy linkage) and squeez (economic impact of energy shortage). Switch parameters may end in "sw" but have no specific naming structure.

'''Initial Condition''': These are not strictly parameters, but rather first-year values for variables that are subsequently computed by the model, or values for rates of change. These cannot be changed in years beyond the base. These include parameters like: carinit (carbon dioxide in atmosphere in base year, initial condition) or igdpr (initial gdp growth rate). There is no specific naming structure to these parameters.

'''Limit''': These parameters set a limit for a variable such as the maximum or minimum. Some examples include: watwastetreatcostupper (wastewater treatment unit maximum cost, limit) or ylmax (maximum possible agricultural yield, limit). There is no specific naming structure to these parameters but many end in “max” “min” "upper" and "lower".

'''Rate''': Change rates directly or to alter rates of growth or decline. Some examples of rate parameters are: femshrgr (annual growth of female share of the labor force, rate) or ginidomr (domestic gini index growth rate). There is no specific naming structure to these parameters.

'''Relationships''': Set or alter the relationship between two variables, by setting or altering the response level of one variable based on changes in another. Examples include: fpricr1 (food prices response to stock level, relationship) or elasde (energy demand to change in price, relationship)

'''Target''': These are parameters that set a target value and the number of years to achieve certain targets or convergence between countries or variables. Target parameters typically come in pairs with the first parameter setting the target for a variable and the second setting the number of years to achieve that target. For example: sanithhbasictrgtval (percent of people with at least basic sanitation service, Target) and sanithhbasictrgtyr (percent of people with at least basic sanitation service, year to achieve, target). Many times, these parameters end in “val” and “yr” corresponding with setting the target value and year respectively. Another common ending for target parameters is “conv” for conversion targets.

'''Level''': Parameters that override the value of a variable, like: enprix (energy price, level). There is no specific naming structure to these parameters.

'''Function Coefficient''': Alter terms in internal calculations. These parameters will change the underlying structure of equations in the model and as a result will alter the values of variables. Examples of function coefficients include: labinformcoeffintercept (Intercept in the Calculation of Informal Labor Share, Function Coefficient) or govriskweight (Weights in the Calculation of the Government Risk Index, Function Coefficient).

The focus here is on exogenous parameters only - on those elements of the model that can be manually changed. Many computed variables are used in the computation of other variables in the same way that parameters are, as multipliers, additive factors, coefficients, and so on. These can be displayed too, but unlike true parameters, they cannot be changed.

Use IFs (Download) Scenario Analysis

2026-02-06T01:48:30Z

Ethan.Sullivan:

[[Understand_Scenarios_in_IFs|Understand Scenario Analysis in IFs]]

[[Quick_Scenario_Analysis_with_Tree|Quick Scenario Analysis with Tree]]

[[Change_Selected_Functions|Change Selected Functions]]

[[Running the Model]]

[[File_Management|File Management]]

[[Reload Base]]

Understand Scenarios in IFs

2026-02-06T01:25:37Z

Ethan.Sullivan: Updated parameter types and wording in many places

= Introduction to Scenarios =
A scenario is a story or story outline. Thinking about the future normally involves creating alternative scenarios, or stories, about the possible evolution of drivers. Some such scenarios are exploratory and consider the possible unfolding of different futures around key uncertainties, such as the rate of some aspect of technological advance or the fragility of some element in the global environment. Other scenarios are normative and develop stories about preferred futures, such as a global transformation to sustainability.

Scenarios in a large integrated model typically are built from multiple interventions that collectively help build a coherent story about the future. Often, but somewhat imprecisely, the word scenario is used more loosely to refer to any intervention (such as the change of a fertility rate for a country or an alternative assumption about oil resources).

Scenarios or interventions with respect to what? When IFs or other computer simulations are "run", without making any changes to parameters or initial conditions specified as the default values, they generate a forecast that is typically called the base case (sometimes reference run). The IFs base case, always available when a model session is initiated, is itself a scenario. Sometimes the base case is incorrectly referred to as a trend extrapolation or a "business as usual" scenario. More accurately, however, the base case of IFs is a computation that involves the full dynamics of the model and therefore has very nonlinear behavior, often quite different from trends. It is a good starting point for scenario analysis for two reasons. First, it is built from initial conditions of all variables that have been given reasonable values from data or other analysis. These initial conditions and parameters make up the package of interventions that constitute the base case scenario. Second, the base case is periodically analyzed relative to the forecasts of many other projects across the range of issue areas covered by IFs and sometimes "tuned" to reproduce the behavior of respected forecasters.

= Creating Scenarios in IFs =
Change initial conditions and parameters using the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create scenarios beyond the base case. Adjust parameters to make specific intended interventions, for example use the Government Spending by Destination and Sector multiplier parameter gdsm to increase government spending in education. A detailed guide of the different parameters and their potential uses can be found in the [[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis]].

==== Scenario-Files and Run-Files ====
Use the [[Quick Scenario Analysis with Tree|Quick Scenario Tree]] to create and save two different kinds of files: ''Scenario-Files (.sce)'' and ''Run-Files (.run)''. The Scenario-Files represent changes that were made to parameters in IFs but that have not yet run through IFs software. Scenario-Files will be saved with .sce as the file extension. The Run-Files are files that hold forecast results after the IFs software has run. Run-Files will be saved with .run as the file extension. The running of a Scenario-Files through the IFs software, will include those parameter changes in the scenario file while the model runs and will produce a Run-File. The most recent Run-File produced by running the model is called the Working-File. By default the Working-File is the base case until the model is run.

In addition to the base case, some versions of IFs will include a number of other previously-run scenarios, perhaps the set of scenarios for the National Intelligence Council’s (NIC) 2020 Project or those for the five Shared Socioeconomic Pathways. In the '''Scenarios''' drop down in Flex Displays, a list of previously-run scenarios is shown before any new scenarios are run. Because those have already been run, based on a set of interventions constituting their foundations, their results can already be displayed.

= Parameter Types =
Parameters are numbers that determine relationships among variables in the equations of IFs. Parameters are often set to a single value across time and they therefore do not always "vary" as do "real" variables. Many parameters are "policy handles," the value of which is set in order to determine the behavior of the model. In IFs parameters are written in lower case form such as endemm and variables are written in upper case such as ENDEM. There are several types of parameters that include:

'''Multiplier''': An equation result parameter that multiplies results (of variable calculations) by the value of the parameter. These parameters are 1 by default, thereby leaving what is multiplied unchanged. Examples of multipliers include: enpm (energy production multiplier), or tfrm (total fertility rate multiplier). Note that multipliers typically end with the letter "m".

'''Additive Factor''': Also, an equation result parameter. Changes results by adding the value of the parameter to the results. These parameters are 0 by default, thereby leaving what is added unchanged. Some examples are: mfpadd (an additive factor on multi-factor productivity growth rate), or migrateinadd (migration rate inward additive factor). Additive Factors typically end with “add”.

'''Switch''': Turn off or on model elements, so alter the structure of the model. They generally take on values of 1 (on) or 0 (off). Switches are most often on or off for the entire run, but it sometimes makes sense to "throw a switch" in the middle of a run. Switch examples include: agon (agriculture economy linkage) and squeez (economic impact of energy shortage). Switch parameters typically end with “sw”.

'''Initial Condition''': These are not strictly parameters, but rather first-year values for variables that are subsequently computed by the model, or values for rates of change that cannot be altered in other years. These cannot be changed in years beyond the base. These will include parameters like: carinit (carbon dioxide in atmosphere in base year, initial condition) or igdpr (initial gdp growth rate). There is no apparent naming structure to these parameters.

'''Limit''': These parameters set a limit for a variable such as the maximum or minimum. Some examples include: watwastetreatcostupper (wastewater treatment unit maximum cost, limit) or ylmax (maximum possible agricultural yield, limit). There is no apparent naming structure to these parameters but many end in “max” or “min”.

'''Rate''': Change rates directly or to alter rates of growth or decline. Some examples of rate parameters are: femshrgr (annual growth of female share of the labor force, rate) or ginidomr (domestic gini index growth rate). There is no apparent naming structure to these parameters.

'''Relationships''': Set or alter the relationship between two variables, by setting or altering the response level of one variable based on changes in another. Examples include: fpricr1 (food prices response to stock level, relationship) or elasde (energy demand to change in price, relationship)

'''Target''': These are parameters that set a target values and the number of years to achieve certain targets or convergence between countries or variables. Target parameters typically come in pairs with the first parameter setting the target for a variable and the second setting the number of years to achieve that target. For example: sanithhbasictrgtval (percent of people with at least basic sanitation service, Target) and sanithhbasictrgtyr (percent of people with at least basic sanitation service, year to achieve, target). Many times, these parameters end in “val” and “yr” corresponding with setting the target value and year respectively. Another common ending for target parameters is “conv” for conversion targets.

'''Level''': Parameters that override the value of a variable result from an internal calculation like: enprix (energy price, level). There is no apparent naming structure to these parameters.

'''Function Coefficient''': Alter terms in internal calculations. These parameters will change the underlying structure of equations in the model and as a result will alter the values of variables. Examples of function coefficients include: labinformcoeffintercept (Intercept in the Calculation of Informal Labor Share, Function Coefficient) or govriskweight (Weights in the Calculation of the Government Risk Index, Function Coefficient)

The focus here is on exogenous parameters only - on those elements of the model that can be manually changed. Many computed variables are used in the computation of other variables in the same way that parameters are, as multipliers, additive factors, coefficients, and so on. These can be displayed too, but unlike true parameters, they cannot be changed.

Energy

2026-01-27T22:07:46Z

Ethan.Sullivan: test save

Test save

Please cite as: Hughes, Barry B., José R. Solórzano, and Dale S. Rothman. 2014. "IFs Energy Model Documentation." Working paper 2014.10.17. Pardee Center for International Futures, Josef Korbel School of International Studies, University of Denver, Denver, CO. Accessed DD Month YYYY <https://pardee.du.edu/wiki/Energy>

The energy model combines a growth process in production with a partial equilibrium process.  The energy model automatically replaces the energy sector in the full economic model unless the user disconnects that linkage. 

For energy, the partial equilibrium structures have distinct demand and supply sides, using price to seek a balance.  As in the economic model, however, no effort is made to obtain a precise equilibrium in any time step.  Instead stocks serve as a temporary buffer and the model again chases equilibrium over time.

Gross domestic product (GDP) from the economic model provides the basis for energy demand calculations.  Energy demand elasticities tend, however, to be quite high.  Thus the physical constraints on the supply side are terribly important in determining the dynamics of the energy model.

IFs distinguishes six energy production categories: oil, natural gas, coal, hydroelectric, nuclear, and other renewables.  For each category both conventional and unconventional sources are considered, but these have only been fully implemented for oil.  IFs computes only aggregated regional or national energy demands and prices, however, 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 not a full connection between the energy model and access to electricity and electricity production (see the IFs Infrastructure Model Documentation for a description of the electricity aspects of IFs).

= <span style="font-size:xx-large;">Introductions</span> =
{| class="tableGrid" style="width:100%;" cellspacing="0" cellpadding="5" border="1"
|-
| style="width: 50%" | <div>'''System/Subsystem'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Energy</div>
|-
| style="text-align: left" | <div>'''Organizing Structure'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Partial market</div>
|-
| style="text-align: left" | <div>'''Stocks'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Capital, resources, reserves</div>
|-
| style="text-align: left" valign="center" | <div>'''Flows'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Production, consumption, trade, discoveries, investment</div>
|-
| style="text-align: left" | <div>'''Key Aggregate ''' '''Relationships '''</div><div>(illustrative, not comprehensive)</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Production function with exogenous technology change;</div><div> </div><div>Energy demand relative to GDP;</div><div> </div><div>Price determination</div>
|-
| style="text-align: left" valign="center" | <div style="text-align: left">'''Key Agent-Class Behavior ''' '''Relationships'''</div><div style="text-align: left">(illustrative, not comprehensive)</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Government taxes, subsidies<br/></div>
|}

= <span style="font-size:xx-large;">Dominant Relations: Energy</span> =

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'' ''') 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 fossils fuels and hydro, there are upper bounds on production.  For fossil fuels, these are based on reserve 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 demand multiplier ('''''enpm'' ''') to directly modify energy production by energy type.

CAPITAL/OUTPUT RATIO The capital/output (capital/production) ratios for all fuel types decline over time due to technological improvements at rates determined by two user controllable parameters ('''''etechadv'' ''' and '''''etechadvuncon'' ''').  For fossil fuels, this is counteracted by a factor that increases the capital/output ratio as the amount of remaining resources decreases.  Something similar happens for hydro and other renewables, but here the capital/output ratios increase as production approaches a maximum possible level.  The user can further modify the capital/output ratios with the multipliers ('''''qem'' ''' and '''''qeunconm'' ''').

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 it 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 influence this in the aggregate (via '''''eninvm'' ''') and can also 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 in the aggregate (via '''''eninvtm'' ''').  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 control over energy trade.  The levels of imports and exports 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'' ''').

= <span style="font-size:xx-large;">Energy Flow Charts</span> =

=== 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.

[[File:Eng1.png|frame|center|Visual representation of the energy production growth process]]

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

Energy production is a function of the capital stock in energy and the capital-output ratios, modified by a capacity utilization factor and exogenous multipliers and production limits.  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.

[[File:Eng2.png|frame|center|Visual representation of energy production]]

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

The capital stock by energy type decreases with depreciation and grows with investment.  Investment or growth in the capital stock, while affected by numerous factors, is driven heavily by energy profits and stocks (unless the user intervenes with a scenario multiplier), and constrained by the reserves available of each specific energy type and production constraints.  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.

[[File:Eng3.png|frame|center|Visual representation of energy capital and investment]]

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

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.

[[File:Eng4.png|frame|center|Visual representation of energy demand]]

== <span style="font-size:x-large;">Energy Resources and Reserves Detail</span> ==

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 ('''''enresorunce'' ''').  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'' ''').[[File:Eng5.png|frame|center|551x255px|Visual representation of energy resources and reserves]]

= <span style="font-size:xx-large;">Energy Equations</span> =

=== Overview ===

This section of the Help system 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 pre-processor as necessary.

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

<span>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.</span>

<span>In the first year, total primary energy demand is calculated as an apparent demand, with attention paid to stocks and expected growth in production.</span>

:<math>ENDEM_{r,t=1}=\sum_eENP_{r,e,t=1}+ENM_{r,t=1}-ENX_{r,t=1}-ENST_{r,t=1}*AVEPR_{r,t=1}</math>

''where''

*ENP, ENM, ENX, ENST, and AVEPR are energy production, energy imports, energy exports, energy stocks, and an average of the expected growth in production across all energy types.  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).[1] This function is show in the figure below[2]:[[File:Eng6.png|frame|right|Total primary energy demand]]

A small amount, 0.0005, 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.  Over a time period 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).[3]

:<math>endemba_r=GDPP_r*endemperunit_r</math>

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 (ENPRI, base year =100).[4]  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.[5]  The historical weight is controlled by the parameter '''''ehw'' ''', so that:

:<math>renpri_{r,t}=\mathbf{ehw}*renpri_{r,t-1}+(1-\mathbf{ehw})*(WEP_{t-1}+CarTaxEnPriAdd_{r,t-1}*\frac{WEP_{t=1}}{WEPBYEAR_{t=1}})</math>

''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, '''''carfuel1-3'' ''':

:<math>CarTaxEnPri_r=\frac{\sum_e(ENP_{r,e}*\mathbf{carfuel_e})}{\sum_eENP_{r,e}}*\mathbf{carbtax_r}</math>

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.

:<math>elasadjusted_r=\mathbf{elasde_r}*\frac{ENPRII_r}{renpri_r}</math>

This, in effect, decreases the price elasticity of energy demand as prices increase.

This adjusted elasticity is then used to calculate the impact on energy demand, elasterm, as

:<math>elasterm_r=1+\frac{renpri_r+ENPRII_r}{ENPRII_r}*elasadjusted_{r^6}</math>

The user can also introduce a further adjustment to total primary energy demand with a multiplier, '''''endemm'' ''', yielding:

:<math>ENDEM_r=endemba_r*elasterm_r*\mathbf{endemm_r}</math>

IFs makes a final adjustment to total primary energy demand related to changes in energy efficiency of the economy unrelated to prices.[6] All countries receive an annual boost in energy efficiency related to technology given by the parameter '''''enrgdpr'' '''.  In addition, if a country is not a major energy exporter and its economy is less energy efficient than the global average, measured as ENDEM divided by GDP (in PPP terms)[7], it gets an additional boost to its energy efficiency.  This effect is cumulative, so ENDEM is adjusted as follows:

:<math>ENDEM_r=ENDEM_r*(1+\frac{EnRGDPGRCalc_r}{100})^{iy}</math>

''where''

*EnRGDPGRCalc is the annual average boost in energy efficiency
*iy is the number of years since the base year plus 1

Finally, IFs makes an initial estimate of energy use per unit GDP in MER terms, ENRGDP.  An estimate of GDP based on the previous year’s GDP in MER terms and a growth rate is used due to the order of calculations, but this is corrected later in the model sequence.

----
<div id="ftn1">
[1] 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.
</div><div id="ftn2">
[2] The exact equation is compendemperunit = 0.0023428 -0.0003878*ln(GDPPCP).

[3] Again, IFs uses GDP from the previous time cycle here, because the recursive structure of IFs computes current GDP later.
<div id="ftn1">
[4] The model also has a variable representing the price index in each economic sector, one of which is energy. This value is stored in the variable PRI, which uses an index value of 1 in the base year.  ENPRI and PRI (energy) track each other, with former having a value 100 times that of the latter due to the different initial index values.
</div><div id="ftn2">
[5] Because energy prices and carbon taxes are computed later in the model sequence, the previous year’s values are used here.
<div id="ftn1">
[6] This is generally referred to as autonomous energy efficiency improvement, or aeei.
</div><div id="ftn2">
[7] An estimate of this year’s GDPP based on the previous year’s GDPP and a growth rate is used here due to the order of calculations.
</div></div></div>
== <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.

Understand IFs

2026-01-08T20:24:33Z

Ethan.Sullivan:

= Help During Use of IFs =

The full Help System is always available to users of IFs from the Help option on the Main Menu. In addition, however, there are several types of Help that are available at key points of model use and that are generally more specific to the specific points of model use. The goals of the IFs system are '''user-friendliness''' with respect to the interface and '''transparency and openness''' with respect to the structure of the model.

'''Context Sensitive Help.''' The use of the F1 key will normally provide screens that provide information about the specific form or window being used at the time. These explain the interactive interface of the model.

'''Pop-up Menus with Help Options.''' Users also want Help, however, when dealing with variables and parameters in the model. They want to know longer names for the short ones sometimes used in the model and want to understand the causal linkages of variables to each other. The use of pop-up menus at many places when variables/parameters are being chosen or used for inputs and for display opens up a variety of options for understanding the names and linkages. For instance, when a table is displayed, a double-click on the body of the table with the right or left mouse button produces a pop-up menu with several options. Similarly, at the bottom of the Display Menu or the Variable Selection form are status boxes with short variable names selected by the user. A right or left mouse click brings up [[Define,_Drivers,_Explain,_Code_and_Delete|similar pop-up menu]].

The pop-up menu system was developed by Mohammod T. Irfan. 

= Understanding the Modeling Approach =

There are many "routes to understanding" of a model: the general philosophy of the modeling approach, the key or dominant relationships and dynamics in the model, the primary causal linkages in the model (using flow charts or causal diagrams), the equations, the full model computer code, and the data used. In order to facilitate the search for understanding, this documentation provides each of these paths, more or less in the sequence of this listing.

The documentation groups most of the "routes to understanding" under issue modules (such as the energy module). The exception is model code, which is collected across modules because of its specialized character.

The IFs model is constantly evolving. In addition to the documentation here, there is stand-alone documentation on the [https://korbel.du.edu/pardee/international-futures-platform/ Reports]page of the IFs project web site. The model user would be advised, in particular, to look at the paper on "[http://www.ifs.du.edu/assets/documents/StructureofIFsV1_0.pdf The Structure of International Futures (IFs)]." 

== IFs Structure: Elements and Philosophy ==

A basic mental model helps frame the approach to modeling in International Futures:

Global human systems consist of classes of agents and larger structures within which those agents interact. Over time agents and the larger structures evolve in processes of mutual influence and determination.

That conceptualization shapes the methodological approach:

At one time global models were categorized as using either econometric or systems dynamics methodologies. IFs draws upon techniques found in both traditions, but reaches beyond them, especially in its structural representations.

Structural representations include cohort-component systems for population; markets for production, exchange, and consumption of goods and service; and social accounting matrices for financial flows.

This emergent IFs methodology is Structure-Based and Agent-Class Driven Modeling.

More detail is available on the manifestation of this modeling approach for the following structural systems of IFs:

::Structure and Agent System: [[Agriculture#Structure_and_Agent_System:_Agriculture|Agriculture]]
::Structure and Agent System: [[Population#Structure_and_Agent_System:_Demographic|Demographic]]
::Structure and Agent System: [[Economics#Structure_and_Agent_System|Economics]]
::Structure and Agent System: [[Education#Structure_and_Agent_System:_Education|Education]]
::Structure and Agent System: [[Energy#Structure_and_Agent_System:_Energy|Energy]]
::Structure and Agent System: [[Environment#Structure_and_Agent_System:_Environment|Environment]]
::Structure and Agent System: [[Governance#Structure_and_Agent_System:_Governance|Governance]]
::Structure and Agent System: [[Health#Structure_and_Agent_System:_Health|Health]]
::Structure and Agent System: [[Infrastructure#Structure_and_Agent_System:_Infrastructure|Infrastructure]]
::Structure and Agent System: [[Interstate_Politics_(IP)#Structure_and_Agent_System:_Interstate_Interaction|Interstate Interaction]]
::Structure and Agent System: [[Socio-Political#Structure_and_Agent_System:_Socio-Political|Socio-Political]]

== Structure-Based and Agent-Class Driven Modeling ==

'''The''' '''Structure-Based, Agent-Class Driven''' approach has five key elements methodologically: organizing structures, stocks, flows, key aggregate relationships, and key agent-class behavioral relationships.

Organizing structures are well-recognized and theoretical and conceptual frameworks with an organizing character for important human systems: cohort-component structures for demographic systems, markets for economic systems, financial flows for socio-political-economic systems, and so on.

'''Stocks and flows remind us of systems dynamics.''' In demographic systems, the stocks are numbers of people in age- and sex-specific cohorts, while the flows are births, deaths, and migration. Systems dynamics would deal with the key relationships as auxiliaries, but econometrics would recognize them as equations that require empirical estimation.<ref>[[Understand IFs#Dominant Relations|1]]</ref>

'''Key Aggregate Relationships.''' Life expectancy or mortality is a key aggregate relationship, clearly a function of income, perhaps education, and certainly of technological change. Aggregate Relationships are often actually Agent-Class behaviors that have not yet been decomposed enough to represent in terms of a single agent class. For instance, life expectancy is a function of government and firm spending on R&D as well as household life-style choices; it could eventually be decomposed to the agent-class level.

'''Key Agent-Class Behavioral Relationships.''' For example, in the case of fertility, there is one primary agent-class, namely households, whose behavior, as a function again of income, education, and technology, will change over time.

'''Agent-classes versus micro agents.''' IFs is not agent-based in the sense of models that represent individual micro-agents following rules and generating structures through their behavior. Instead, IFs represents both existing macro-agent classes and existing structures (with complex historic path dependencies), attempting to represent some elements of how behavior of those agents can change and how the structures can evolve. Although building aggregate model behavior and structure upward from micro agent behavior is laudable in more narrowly-focused models, global systems and structures are far too numerous and well-developed for such efforts to succeed across the breadth of concerns in IFs.

In representing the behavior of agent classes and the structures of systems, IFs draws upon large bodies of insight in many theoretical and modeling literatures. Although IFs sometimes breaks new ground with respect to specific sub-systems, its strengths lie primarily in the integration and synthesis of much earlier work.

== Dominant Relations ==

Any computer simulation or other model will have some relationships and dynamics that dominate the behavior of the model and that therefore most heavily influence the analyses done with the model. Understanding these dominant relations will facilitate model use, particularly in the definition of key or framing scenarios.

The value added by more detailed specification of relationships in the model will lie partly in more probing analysis, often around specific policy options. Much of the value added by a more complete model specification will, however, lie in the dynamics of the full model.

For an introductory summary of dominant relations and dynamics by submodule:

*Dominant Relations: [[Agriculture#Dominant_Relations:_Agriculture|Agriculture]]
*Dominant Relations: [[Population#Dominant_Relations:_Population|Demography/Population]]
*Dominant Relations:[[Economics#Dominant_Relations:_Economics|Economics]]
*Dominant Relations: [[Education#Dominant_Relations:_Education|Education]]
*Dominant Relations: [[Energy#Dominant_Relations:_Energy|Energy]]
*Dominant Relations: [[Environment#Dominant_Relations:_Environment|Environment]]
*Dominant Relations: [[Governance#Dominant_Relations:_Governance|Governance]]
*Dominant Relations: [[Health#Dominant_Relations:_Health|Health]]
*Dominant Relations: [[Infrastructure#Dominant_Relations:_Infrastructure|Infrastructure]]
*Dominant Relations: [[Interstate_Politics_(IP)#Dominant_Relations:_Interstate_Politics|Interstate Politics]]
*Dominant Relations: [[Socio-Political#Dominant_Relations:_Socio-Political|Socio-Political]]

= Understanding the Equations =

As a general rule, the equations closely follow the computer code. Insofar as possible without confusion, variable and parameter names here are the same as those in the computer program, but in a few cases equation names differ to enhance readability. Computer code shows a single computed variable on the left and one or more input variables and parameters on the right. In fact, computer code frequently shows the computed variable on both the left and the right hand side, which is NOT standard mathematical equation form and a few traditional purists have difficulty understanding this (as well as preferring non-mnemonic single letter variable names and Greek symbols to much more intelligible computer-based variable names). As an appropriate accommodation, this documentation sometimes uses asterisks to distinguish different values of the same variable name on left and right-hand sides of equations.

IFs has multiple modules: population, economic, agriculture, energy, and socio-political. An environmental "module" is scattered across other modules, especially agriculture and energy. Equations are presented by module and cross references in the documentation of each module indicate linkages.

IFs is a recursive dynamic system and equation sequence is therefore important. This text presents equations in largely the same sequence as in the computer program. Program flow exits from and returns to each module up to three times each time step (year), however, and it would break up discussions of module too much if we were to follow computational flow slavishly. Moreover, to facilitate understanding this documentation sometimes presents the key equations of a module or a section of one first, with subsequent explanation of the compu"tational procedures for variables used therein (thereby deviating further from actual computation sequence). Equation form here is the same as in the computer program, including the presentation of a single "computed" variable on the left side of the equal sign.

== Equation Notation ==

Variable names are shown in all capitals, as in the display functions of the model. Parameters are shown in lower case and boldface. Empirically-based initial conditions of variables are in capitals with boldface. Internal computed variables, which are not available for display, are shown in mixed upper and lower case.

At one time the project used a superscript of "t" to indicate time/year. Although it has mostly moved that to subscripts, it may sometimes still be found in project documentation. Superscripts other than "t" indicate exponentiation. Subscripts or superscripts with "t" indicate time, but will be omitted when a reference is contemporary to model year "t."

Subscripts show dimensionality and there are a number of standard ones in the model:

*'''r''' for region/country r = 1,2,... (e.g., United States, European Union, Japan, Brazil...)
*'''b''' (sometimes the project uses j) for age cohort c/j = 1,2,...,22 (infant, 0-4 years,...95-99 years, 100+ years; abbreviated set for World Value Survey variables)
*'''s''' for economic sector s = 1,2,3,4,5,6 (agriculture, energy, materials, manufactures, services, ICT)
*'''f''' for food types f = 1,2 (crops, meat/fish)
*'''l''' for land types l = 1,2,3,4,5 (crop, grazing, forest, unused, urban/industrial)
*'''e''' for energy types e = 1,2,3,4,5,6,7 (oil, gas, coal, hydroelectric, nuclear, other renewable, unconventional oil)
*'''g''' for govt spending g = 1,2,3,4,5,6 (military, health, education, R&D, other, foreign aid)
*'''p''' for population sex p=1,2 (male, female)
*'''ss''' for safe water and sanitation ladder categories
*'''d''' for cause of death (15 in total)
*'''dg''' for cause of death group dg=1,2,3 (communicable, non-communicable, injuries/accidents)
*'''h''' for household types h=1,2 (unskilled, skilled)

Individual equations specify a range of dimensionality only if it differs from that above.

== Specialized Functions ==

=== AnalFunc and TablFunc ===

Throughout the IFs documentation there will also be references to analytic functions that have been added to the library of IFs functions. Because the user interface allows display and change of such functions, the form and parameters are not always elaborated in the written documentation. Some references to TablFunc persist in error from earlier versions of documentation when analytic functions were still represented as systems-dynamic like table functions, but an effort is being made to reserve TablFunc for the handful of functions that are still truly represented in such a manner. Occasionally an "F" creeps in, also referring to analytic functions in the library.

=== AMAX and AMIN ===

IFs often bounds a variables computation with upper or lower limits. This serves a number of functions, all related to assuring reasonable behavior of the model under extreme conditions. For instance, denominators that might approach 0 are bound with the AMAX function so that they take on at least some specified number – the AMAX function returns the larger of the computed value and the number specified. Other computations are subject to the AMIN function so as to avoid becoming unreasonably large (such as probabilities that exceed 1) – the AMIN function returns the smaller of the computed value and the number specified.

=== Converge Over Time Mechanism ===

In the development of IFs it has been found that there are many instances in which initial empirical conditions for values in specific countries vary considerably from what one might expect in the longer-term. In some instances, data may be faulty. In others, there may be disequilibria that appear unlikely to be maintained over time or cultural distinctiveness that appears likely to erode. Because immediate readjustment of such values would both violate the integrity of the data and, in many cases, create other discrepancies, such adjustment is rare in IFs. Instead, the modeling system uses a mechanism to facilitate convergence over time of the values to a target computation that appears a reasonable longer-term expectation. The mechanism is used with sufficient frequency that it is built into a function with the name ConvergeOverTime, and that name returns a value to the program when it is called with three parameters: a base value that comes from the empirical side (Base), a target value that comes from forecasting relationships (Target), and a number of years over which the model should interpolate between the base and the target, converging with the target over that period (Years to Converge).

:<math>ConvergeOverTime=\frac{Base*(YearsToConverge-TimeFac)+Target*TimeFac}{YearsToConverge}</math>

where

:<math>TimeFac=Amin(t,YearsToCoverge)</math>

=== Adjustment Mechanism ===

In many modules, especially the economic module and the two elaborated sectoral modules, IFs relies upon an adjustment function to alter key variables (e.g., demand, prices, trade, and investment) in the pursuit of equilibrium. The adjustment function compares the level of some stock type variable (most often either inventory levels or prices, but including other variables such as international indebtedness) with a desired level, and adjusts the dependent variable.

IFs computes a difference (DIFF1) between the actual and desired levels and scales that difference with a scaling base (SCALINGBASE) value (for instance, total production in an economic sector might be a reasonable scaling base value against which to gauge the importance of a deviation of inventories from desired levels). In addition, the adjustment mechanism uses a second-order difference (DIFF2) to compare the level of the stock-type driving variable with its value in the previous time cycle, relying upon the same scaling base.

Non-zero differences result in a multiplier value (MUL) that deviates from "1" depending on the magnitude of two elasticities (EL1 and EL2). Specifically, the formulation is

:<math>MUL=(1+\frac{DIFF1}{SCALINGBASE})^{EL1}*(1+\frac{DIFF2}{SCALINGBASE})^{EL2}</math>

This mechanism is represented in a function called the adjuster (ADJSTR) that the model calls at numerous locations. The magnitude of the two parameters will, of course, differ depending on the model variable in which equilibrium is being pursued. Experience has shown, however, that EL1 normally takes absolute values between 0.2 and 0.4, while EL2 is most often two times the value of EL1 and thus varies most often between 0.4 and 0.8. The values of EL1 and EL2 have been determined experimentally, in order to be large enough to maintain approximate equilibrium and small enough to avoid unreasonably rapid or extreme oscillation. There will inevitably be some oscillation in equilibrium-seeking processes, and in some cases (such as inventory levels), the values could be set so as to provide an oscillation consistent with known cycles (such as business cycles). Because IFs is a long-term rather than a short-term model, however, we have generally devoted little attention in scaling to the oscillation cycle, focusing instead on long-term stability in the face of shocks introduced by scenarios of model users.

This kind of adjustment mechanism is sometimes called a PID controller, that is, an adjustment process that responds proportionately (the adjustment parameters) to the integral of the error (the stock discrepancy) and to the derivative of the error (the change in stock term). We shall see many PID controllers in IFs. For more information see the books by Chang (1961) and by Mishkin and Braun (1961) in the bibliography. An early version of this adjustment mechanism was developed by Thomas Shook for the Mesarovic-Pestel modeling project.

=== Standard Error Targeting ===

Especially for the purposes of policy analysis, we often want to force the result of an equation towards a particular value over time (e.g. to achieve the elimination of indoor use of solid fuels). Target variables are generally paired, one for the target level and one for the number of years to reach the target (from the initial year of the model forecast). Targets have different types:

==== Absolute Targets ====

In this case, the target value and year define to what absolute value the variable should move and in how many years after the first model year. Together they determine a path in which the value for the variable moves linearly from the value in first year to the target value in the target year. (In some cases, the model uses non-linear convergence, e.g. to accelerate movement in early years and then to slow it as the target is approached.) Trgtval and trgtyr are the parameter suffixes used for this parameter type. The first of these changes the target itself and the second of these alters the number of years to the target.

==== Relative (Standard Error) Targets ====

In this case, the target value and year def ine to what relative value the variable should move and in how many years after the first. The relative value is defined as the number of standard errors above or below the “expected” value of the variable of interest. (An expectation is usually based on the country's GDP per capita and a cross-sectional analysis of country values.) As with the absolute targets the value calculated using the targeting is compared to the value forecast in the model without targeting and the final forecast value gradually moves from that pre-targeting forecast value to the target value. Two different parameter suffixes are used in standard-error targeting: setar and seyrtar. The first of these changes the target itself and the second of these alters the number of years to the target.

<references />

Energy

2025-12-16T17:26:01Z

Ethan.Sullivan:

Please cite as: Hughes, Barry B., José R. Solórzano, and Dale S. Rothman. 2014. "IFs Energy Model Documentation." Working paper 2014.10.17. Pardee Center for International Futures, Josef Korbel School of International Studies, University of Denver, Denver, CO. Accessed DD Month YYYY <https://pardee.du.edu/wiki/Energy>

The energy model combines a growth process in production with a partial equilibrium process.  The energy model automatically replaces the energy sector in the full economic model unless the user disconnects that linkage. 

For energy, the partial equilibrium structures have distinct demand and supply sides, using price to seek a balance.  As in the economic model, however, no effort is made to obtain a precise equilibrium in any time step.  Instead stocks serve as a temporary buffer and the model again chases equilibrium over time.

Gross domestic product (GDP) from the economic model provides the basis for energy demand calculations.  Energy demand elasticities tend, however, to be quite high.  Thus the physical constraints on the supply side are terribly important in determining the dynamics of the energy model.

IFs distinguishes six energy production categories: oil, natural gas, coal, hydroelectric, nuclear, and other renewables.  For each category both conventional and unconventional sources are considered, but these have only been fully implemented for oil.  IFs computes only aggregated regional or national energy demands and prices, however, 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 not a full connection between the energy model and access to electricity and electricity production (see the IFs Infrastructure Model Documentation for a description of the electricity aspects of IFs).

= <span style="font-size:xx-large;">Introductions</span> =
{| class="tableGrid" style="width:100%;" cellspacing="0" cellpadding="5" border="1"
|-
| style="width: 50%" | <div>'''System/Subsystem'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Energy</div>
|-
| style="text-align: left" | <div>'''Organizing Structure'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Partial market</div>
|-
| style="text-align: left" | <div>'''Stocks'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Capital, resources, reserves</div>
|-
| style="text-align: left" valign="center" | <div>'''Flows'''</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Production, consumption, trade, discoveries, investment</div>
|-
| style="text-align: left" | <div>'''Key Aggregate ''' '''Relationships '''</div><div>(illustrative, not comprehensive)</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Production function with exogenous technology change;</div><div> </div><div>Energy demand relative to GDP;</div><div> </div><div>Price determination</div>
|-
| style="text-align: left" valign="center" | <div style="text-align: left">'''Key Agent-Class Behavior ''' '''Relationships'''</div><div style="text-align: left">(illustrative, not comprehensive)</div>
| style="text-align: left; padding-left: 10px" align="center" | <div>Government taxes, subsidies<br/></div>
|}

= <span style="font-size:xx-large;">Dominant Relations: Energy</span> =

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'' ''') 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 fossils fuels and hydro, there are upper bounds on production.  For fossil fuels, these are based on reserve 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 demand multiplier ('''''enpm'' ''') to directly modify energy production by energy type.

CAPITAL/OUTPUT RATIO The capital/output (capital/production) ratios for all fuel types decline over time due to technological improvements at rates determined by two user controllable parameters ('''''etechadv'' ''' and '''''etechadvuncon'' ''').  For fossil fuels, this is counteracted by a factor that increases the capital/output ratio as the amount of remaining resources decreases.  Something similar happens for hydro and other renewables, but here the capital/output ratios increase as production approaches a maximum possible level.  The user can further modify the capital/output ratios with the multipliers ('''''qem'' ''' and '''''qeunconm'' ''').

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 it 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 influence this in the aggregate (via '''''eninvm'' ''') and can also 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 in the aggregate (via '''''eninvtm'' ''').  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 control over energy trade.  The levels of imports and exports 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'' ''').

= <span style="font-size:xx-large;">Energy Flow Charts</span> =

=== 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.

[[File:Eng1.png|frame|center|Visual representation of the energy production growth process]]

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

Energy production is a function of the capital stock in energy and the capital-output ratios, modified by a capacity utilization factor and exogenous multipliers and production limits.  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.

[[File:Eng2.png|frame|center|Visual representation of energy production]]

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

The capital stock by energy type decreases with depreciation and grows with investment.  Investment or growth in the capital stock, while affected by numerous factors, is driven heavily by energy profits and stocks (unless the user intervenes with a scenario multiplier), and constrained by the reserves available of each specific energy type and production constraints.  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.

[[File:Eng3.png|frame|center|Visual representation of energy capital and investment]]

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

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.

[[File:Eng4.png|frame|center|Visual representation of energy demand]]

== <span style="font-size:x-large;">Energy Resources and Reserves Detail</span> ==

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 ('''''enresorunce'' ''').  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'' ''').[[File:Eng5.png|frame|center|551x255px|Visual representation of energy resources and reserves]]

= <span style="font-size:xx-large;">Energy Equations</span> =

=== Overview ===

This section of the Help system 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 pre-processor as necessary.

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

<span>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.</span>

<span>In the first year, total primary energy demand is calculated as an apparent demand, with attention paid to stocks and expected growth in production.</span>

:<math>ENDEM_{r,t=1}=\sum_eENP_{r,e,t=1}+ENM_{r,t=1}-ENX_{r,t=1}-ENST_{r,t=1}*AVEPR_{r,t=1}</math>

''where''

*ENP, ENM, ENX, ENST, and AVEPR are energy production, energy imports, energy exports, energy stocks, and an average of the expected growth in production across all energy types.  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).[1] This function is show in the figure below[2]:[[File:Eng6.png|frame|right|Total primary energy demand]]

A small amount, 0.0005, 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.  Over a time period 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).[3]

:<math>endemba_r=GDPP_r*endemperunit_r</math>

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 (ENPRI, base year =100).[4]  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.[5]  The historical weight is controlled by the parameter '''''ehw'' ''', so that:

:<math>renpri_{r,t}=\mathbf{ehw}*renpri_{r,t-1}+(1-\mathbf{ehw})*(WEP_{t-1}+CarTaxEnPriAdd_{r,t-1}*\frac{WEP_{t=1}}{WEPBYEAR_{t=1}})</math>

''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, '''''carfuel1-3'' ''':

:<math>CarTaxEnPri_r=\frac{\sum_e(ENP_{r,e}*\mathbf{carfuel_e})}{\sum_eENP_{r,e}}*\mathbf{carbtax_r}</math>

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.

:<math>elasadjusted_r=\mathbf{elasde_r}*\frac{ENPRII_r}{renpri_r}</math>

This, in effect, decreases the price elasticity of energy demand as prices increase.

This adjusted elasticity is then used to calculate the impact on energy demand, elasterm, as

:<math>elasterm_r=1+\frac{renpri_r+ENPRII_r}{ENPRII_r}*elasadjusted_{r^6}</math>

The user can also introduce a further adjustment to total primary energy demand with a multiplier, '''''endemm'' ''', yielding:

:<math>ENDEM_r=endemba_r*elasterm_r*\mathbf{endemm_r}</math>

IFs makes a final adjustment to total primary energy demand related to changes in energy efficiency of the economy unrelated to prices.[6] All countries receive an annual boost in energy efficiency related to technology given by the parameter '''''enrgdpr'' '''.  In addition, if a country is not a major energy exporter and its economy is less energy efficient than the global average, measured as ENDEM divided by GDP (in PPP terms)[7], it gets an additional boost to its energy efficiency.  This effect is cumulative, so ENDEM is adjusted as follows:

:<math>ENDEM_r=ENDEM_r*(1+\frac{EnRGDPGRCalc_r}{100})^{iy}</math>

''where''

*EnRGDPGRCalc is the annual average boost in energy efficiency
*iy is the number of years since the base year plus 1

Finally, IFs makes an initial estimate of energy use per unit GDP in MER terms, ENRGDP.  An estimate of GDP based on the previous year’s GDP in MER terms and a growth rate is used due to the order of calculations, but this is corrected later in the model sequence.

----
<div id="ftn1">
[1] 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.
</div><div id="ftn2">
[2] The exact equation is compendemperunit = 0.0023428 -0.0003878*ln(GDPPCP).

[3] Again, IFs uses GDP from the previous time cycle here, because the recursive structure of IFs computes current GDP later.
<div id="ftn1">
[4] The model also has a variable representing the price index in each economic sector, one of which is energy. This value is stored in the variable PRI, which uses an index value of 1 in the base year.  ENPRI and PRI (energy) track each other, with former having a value 100 times that of the latter due to the different initial index values.
</div><div id="ftn2">
[5] Because energy prices and carbon taxes are computed later in the model sequence, the previous year’s values are used here.
<div id="ftn1">
[6] This is generally referred to as autonomous energy efficiency improvement, or aeei.
</div><div id="ftn2">
[7] An estimate of this year’s GDPP based on the previous year’s GDPP and a growth rate is used here due to the order of calculations.
</div></div></div>
== <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.

Flexible Displays (Download)

2025-11-04T20:53:02Z

Ethan.Sullivan:

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.

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]].

Flexible Displays (Download)

2025-10-23T19:40:06Z

Ethan.Sullivan: changes

Edits here

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.

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]].

Country Groupings in IFs

2025-10-13T21:00:51Z

Ethan.Sullivan:

= Overview =
Countries are often grouped for various purposes, including research, forecasting, strategic planning, comparability, representation, advocacy, cultural identity, and policymaking. Regional, continental, strategic, and economic classifications of countries provide a valuable framework for understanding and analyzing global dynamics and play a critical role in economic and human development modeling used to forecast future outcomes. However, there is no universal agreement on how certain groups and their memberships should be defined. This lack of consensus has far-reaching implications, affecting development efforts, international cooperation, and policy decisions designed to address shared challenges and opportunities effectively.

To address this lack of standardization and the absence of published comprehensive justifications, the Pardee Institute for International Futures at the University of Denver has created its own set of country groupings for 188 countries in the International Futures (IFs) modeling tool. The Institute’s classifications are based on the United Nations Statistical Division’s (UNSD) M49 system but include additional research and justifications for specific country placements considered to be boundary cases. For countries where classifications have discrepancies or are controversial across multinational organizations, universities, or governments, we determine their grouping in IFs based on a thorough analysis of the country’s geographical, historical, political, strategic, cultural, ethnic, and linguistic characteristics to justify their classification.

Summary of Core Issues

· No international consensus on how countries should be regionally classified.

· Classification differences affect data analysis, policy design, and forecasts (e.g., HDI or economic outlooks).

· Some countries, called boundary cases, are highly disputed, requiring explicit justification.

= Methodology =
The primary framework for groupings is founded on the UN’s M49 standard, developed by the UNSD. The Pardee Institute then conducted a qualitative analysis of various published country, regional, and continental classifications to understand the underlying rationale for these classifications. A range of sources were also reviewed, including classifications from international organizations (e.g., World Bank, International Monetary Fund (IMF), and Organization of Economic Cooperation and Development (OECD)), and academic and institutional groupings to develop a consistent and transparent framework for the IFs modeling tool. Particular attention was paid to identifying "boundary cases," where there is significant disagreement or ambiguity regarding a country’s placement. For each boundary case, the Institute undertook a comprehensive, multi-faceted assessment, incorporating:

· ''Geographical factors'': The physical location of a country, natural boundaries such as rivers and mountains, and its proximity to other regions.

· ''Historical context and political dynamics'': The country’s historical alliances, colonial past, and territorial boundaries established through treaties or conflicts. It also includes current and historical political affiliations, including membership in regional or global alliances like the African Union (AU), the Association of Southeast Asian Nations. (ASEAN), or the North Atlantic Treaty Organization (NATO).

· ''Ethnic, cultural, language, and racial considerations'': The demographic composition of the country and its alignment with neighboring states or regions, the shared linguistic ties, and cultural practices that align a country with specific regions

Classification balances these factors transparently. Each factor has therefore been assessed according to its relevance in deciding a country’s grouping, ensuring that those decisions are well-reasoned and contextually appropriate. For instance, Cyprus’s cultural and political history with Europe outweighs its geographic position in Asia.

= Regional Groupings in IFs =
· ''Africa'': North, South, East, Central, West (55 countries).

· ''Asia'': Central, East, South, Southeast, West (49 countries).

· ''Europe'': North, South, East, West (41 countries).

· ''Oceania'': Australia and New Zealand, Melanesia, Micronesia, and Polynesia (10 countries).

· ''Americas'': North, Central, South, and the Caribbean (33 countries).

= Boundary Cases =
Africa

· ''Sudan'': Sometimes classified in Africa East, Africa North Africa, and MENA. In IFs, it is grouped in Africa North.

· ''Mauritania'': Sometimes classified in Africa West or Africa North. In IFs, it is grouped in Africa West.

Asia

· ''Afghanistan'': Sometimes classified in Asia Central, Asia East or Asia South. In IFs, it is grouped in Asia South.

· ''Cyprus'': Sometimes classified in Asia West or Europe South. In IFs, it is grouped in Europe South.

· ''Türkiye'': Sometimes considered Europe West Europe or Asia West. In IFs, it is grouped in Asia West.

· ''Iraq'': Sometimes classified as Asia South or Asia West. In IFs, it is grouped in Asia West.

· ''Iran'': Sometimes classified as Asia South or Asia West. In IFs, it is grouped in Asia West.

· ''Georgia'': Sometimes classified as Europe East or Asia West. In IFs, it is grouped in Europe East.

· ''Russian Federation'': Sometimes classified as Europe East or North Asia. In IFs, it is grouped in Europe East.

Europe

· ''Iceland'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe North

· ''United Kingdom'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe West

· ''Ireland'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe West

· ''Spain'': Sometimes classified as Europe South or Europe West. In IFs, it is grouped in Europe South

· ''Portugal'': Sometimes classified as Europe South or Europe West. In IFs, it is grouped in Europe South.

· ''Austria'': Sometimes classified as Europe East or Europe West. In IFs, it is grouped in Europe West.

· ''Kosovo'': Sometimes classified as Europe South or Europe East. In IFs, it is grouped in Europe South.

· ''Albania'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe South.

· ''Latvia'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

· ''Lithuania'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

· ''Estonia'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

Americas

''Americas North''

· ''Mexico'': Sometimes classified as Americas North, Americas Central, and Americas Caribbean. In IFs, it is grouped in Americas North.

· ''Puerto Rico'': Sometimes classified as Americas North, Americas Central, Americas South, and Americas Caribbean. In IFs, it is grouped in Americas North.

''Americas Central and the Caribbean''.

· ''Belize'': Sometimes classified as Americas Central or the Caribbean. In IFs, it is grouped in Americas Central.

Economic and Development Groupings

Countries in IFs are also classified by:

· ''Human Development Index (HDI)'': Low, Medium, High, Very High.

· ''World Bank Income Levels'': Low, Lower-Middle, Upper-Middle, High income.

= Conclusion =
The IFs groupings aim for transparency and consistency while addressing disputes over boundary cases. By explicitly justifying controversial classifications, the framework strengthens forecasting accuracy and helps researchers and policymakers interpret global trends with clarity.

To find more detailed information on decisions behind country groupings please refer to the [https://korbel.du.edu/pardee-resources/international-futures-ifs-country-groupings/ International Futures (IFs) Country Groupings] working paper on the Pardee Institute website.

Country Groupings in IFs

2025-10-13T20:20:45Z

Ethan.Sullivan: Added link to full working paper

= Overview =
Countries are often grouped for various purposes, including research, forecasting, strategic planning, comparability, representation, advocacy, cultural identity, and policymaking. Regional, continental, strategic, and economic classifications of countries provide a valuable framework for understanding and analyzing global dynamics and play a critical role in economic and human development modeling used to forecast future outcomes. However, there is no universal agreement on how certain groups and their memberships should be defined. This lack of consensus has far-reaching implications, affecting development efforts, international cooperation, and policy decisions designed to address shared challenges and opportunities effectively.

To address this lack of standardization and the absence of published comprehensive justifications, the Pardee Institute for International Futures at the University of Denver has created its own set of country groupings for 188 countries in the International Futures (IFs) modeling tool. The Institute’s classifications are based on the United Nations Statistical Division’s (UNSD) M49 system but include additional research and justifications for specific country placements considered to be boundary cases. For countries where classifications have discrepancies or are controversial across multinational organizations, universities, or governments, we determine their grouping in IFs based on a thorough analysis of the country’s geographical, historical, political, strategic, cultural, ethnic, and linguistic characteristics to justify their classification.

Summary of Core Issues

· No international consensus on how countries should be regionally classified.

· Classification differences affect data analysis, policy design, and forecasts (e.g., HDI or economic outlooks).

· Some countries, called boundary cases, are highly disputed, requiring explicit justification.

= Methodology =
The primary framework for groupings is founded on the UN’s M49 standard, developed by the UNSD. The Pardee Institute then conducted a qualitative analysis of various published country, regional, and continental classifications to understand the underlying rationale for these classifications. A range of sources were also reviewed, including classifications from international organizations (e.g., World Bank, International Monetary Fund (IMF), and Organization of Economic Cooperation and Development (OECD)), and academic and institutional groupings to develop a consistent and transparent framework for the IFs modeling tool. Particular attention was paid to identifying "boundary cases," where there is significant disagreement or ambiguity regarding a country’s placement. For each boundary case, the Institute undertook a comprehensive, multi-faceted assessment, incorporating:

· ''Geographical factors'': The physical location of a country, natural boundaries such as rivers and mountains, and its proximity to other regions.

· ''Historical context and political dynamics'': The country’s historical alliances, colonial past, and territorial boundaries established through treaties or conflicts. It also includes current and historical political affiliations, including membership in regional or global alliances like the African Union (AU), the Association of Southeast Asian Nations. (ASEAN), or the North Atlantic Treaty Organization (NATO).

· ''Ethnic, cultural, language, and racial considerations'': The demographic composition of the country and its alignment with neighboring states or regions, the shared linguistic ties, and cultural practices that align a country with specific regions

Classification balances these factors transparently. Each factor has therefore been assessed according to its relevance in deciding a country’s grouping, ensuring that those decisions are well-reasoned and contextually appropriate. For instance, Cyprus’s cultural and political history with Europe outweighs its geographic position in Asia.

= Regional Groupings in IFs =
· ''Africa'': North, South, East, Central, West (55 countries).

· ''Asia'': Central, East, South, Southeast, West (49 countries).

· ''Europe'': North, South, East, West (41 countries).

· ''Oceania'': Australia and New Zealand, Melanesia, Micronesia, and Polynesia (10 countries).

· ''Americas'': North, Central, South, and the Caribbean (33 countries).

= Boundary Cases =
Africa

· ''Sudan'': Sometimes classified in Africa East, Africa North Africa, and MENA. In IFs, it is grouped in Africa North.

· ''Mauritania'': Sometimes classified in Africa West or Africa North. In IFs, it is grouped in Africa West.

Asia

· ''Afghanistan'': Sometimes classified in Asia Central, Asia East or Asia South. In IFs, it is grouped in Asia South.

· ''Cyprus'': Sometimes classified in Asia West or Europe South. In IFs, it is grouped in Europe South.

· ''Türkiye'': Sometimes considered Europe West Europe or Asia West. In IFs, it is grouped in Asia West.

· ''Iraq'': Sometimes classified as Asia South or Asia West. In IFs, it is grouped in Asia West.

· ''Iran'': Sometimes classified as Asia South or Asia West. In IFs, it is grouped in Asia West.

· ''Georgia'': Sometimes classified as Europe East or Asia West. In IFs, it is grouped in Europe East.

· ''Russian Federation'': Sometimes classified as Europe East or North Asia. In IFs, it is grouped in Europe East.

Europe

· ''Iceland'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe North

· ''United Kingdom'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe West

· ''Ireland'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe West

· ''Spain'': Sometimes classified as Europe South or Europe West. In IFs, it is grouped in Europe South

· ''Portugal'': Sometimes classified as Europe South or Europe West. In IFs, it is grouped in Europe South.

· ''Austria'': Sometimes classified as Europe East or Europe West. In IFs, it is grouped in Europe West.

· ''Kosovo'': Sometimes classified as Europe South or Europe East. In IFs, it is grouped in Europe South.

· ''Albania'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe South.

· ''Latvia'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

· ''Lithuania'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

· ''Estonia'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

Americas

''Americas North''

· ''Mexico'': Sometimes classified as Americas North, Americas Central, and Americas Caribbean. In IFs, it is grouped in Americas North.

· ''Puerto Rico'': Sometimes classified as Americas North, Americas Central, Americas South, and Americas Caribbean. In IFs, it is grouped in Americas North.

''Americas Central and the Caribbean''.

· ''Mexico''

· ''Puerto Rico''

· ''Belize'': Sometimes classified as Americas Central or the Caribbean. In IFs, it is grouped in Americas Central.

Economic and Development Groupings

Countries in IFs are also classified by:

· ''Human Development Index (HDI)'': Low, Medium, High, Very High.

· ''World Bank Income Levels'': Low, Lower-Middle, Upper-Middle, High income.

= Conclusion =
The IFs groupings aim for transparency and consistency while addressing disputes over boundary cases. By explicitly justifying controversial classifications, the framework strengthens forecasting accuracy and helps researchers and policymakers interpret global trends with clarity.

To find more detailed information on decisions behind country groupings please refer to the [https://korbel.du.edu/pardee-resources/international-futures-ifs-country-groupings/ International Futures (IFs) Country Groupings] working paper on the Pardee Institute website.

Country Groupings in IFs

2025-10-13T18:51:15Z

Ethan.Sullivan: New Country Groupings; need to review still

= Overview =
Countries are often grouped for various purposes, including research, forecasting, strategic planning, comparability, representation, advocacy, cultural identity, and policymaking. Regional, continental, strategic, and economic classifications of countries provide a valuable framework for understanding and analyzing global dynamics and play a critical role in economic and human development modeling used to forecast future outcomes. However, there is no universal agreement on how certain groups and their memberships should be defined. This lack of consensus has far-reaching implications, affecting development efforts, international cooperation, and policy decisions designed to address shared challenges and opportunities effectively.

To address this lack of standardization and the absence of published comprehensive justifications, the Pardee Institute for International Futures at the University of Denver has created its own set of country groupings for 188 countries in the International Futures (IFs) modeling tool. The Institute’s classifications are based on the United Nations Statistical Division’s (UNSD) M49 system but include additional research and justifications for specific country placements considered to be boundary cases. For countries where classifications have discrepancies or are controversial across multinational organizations, universities, or governments, we determine their grouping in IFs based on a thorough analysis of the country’s geographical, historical, political, strategic, cultural, ethnic, and linguistic characteristics to justify their classification.

Summary of Core Issues

· No international consensus on how countries should be regionally classified.

· Classification differences affect data analysis, policy design, and forecasts (e.g., HDI or economic outlooks).

· Some countries, called boundary cases, are highly disputed, requiring explicit justification.

= Methodology =
The primary framework for groupings is founded on the UN’s M49 standard, developed by the UNSD. The Pardee Institute then conducted a qualitative analysis of various published country, regional, and continental classifications to understand the underlying rationale for these classifications. A range of sources were also reviewed, including classifications from international organizations (e.g., World Bank, International Monetary Fund (IMF), and Organization of Economic Cooperation and Development (OECD)), and academic and institutional groupings to develop a consistent and transparent framework for the IFs modeling tool. Particular attention was paid to identifying "boundary cases," where there is significant disagreement or ambiguity regarding a country’s placement. For each boundary case, the Institute undertook a comprehensive, multi-faceted assessment, incorporating:

· ''Geographical factors'': The physical location of a country, natural boundaries such as rivers and mountains, and its proximity to other regions.

· ''Historical context and political dynamics'': The country’s historical alliances, colonial past, and territorial boundaries established through treaties or conflicts. It also includes current and historical political affiliations, including membership in regional or global alliances like the African Union (AU), the Association of Southeast Asian Nations. (ASEAN), or the North Atlantic Treaty Organization (NATO).

· ''Ethnic, cultural, language, and racial considerations'': The demographic composition of the country and its alignment with neighboring states or regions, the shared linguistic ties, and cultural practices that align a country with specific regions

Classification balances these factors transparently. Each factor has therefore been assessed according to its relevance in deciding a country’s grouping, ensuring that those decisions are well-reasoned and contextually appropriate. For instance, Cyprus’s cultural and political history with Europe outweighs its geographic position in Asia.

= Regional Groupings in IFs =
· ''Africa'': North, South, East, Central, West (55 countries).

· ''Asia'': Central, East, South, Southeast, West (49 countries).

· ''Europe'': North, South, East, West (41 countries).

· ''Oceania'': Australia and New Zealand, Melanesia, Micronesia, and Polynesia (10 countries).

· ''Americas'': North, Central, South, and the Caribbean (33 countries).

= Boundary Cases =
Africa

· ''Sudan'': Sometimes classified in Africa East, Africa North Africa, and MENA. In IFs, it is grouped in Africa North.

· ''Mauritania'': Sometimes classified in Africa West or Africa North. In IFs, it is grouped in Africa West.

Asia

· ''Afghanistan'': Sometimes classified in Asia Central, Asia East or Asia South. In IFs, it is grouped in Asia South.

· ''Cyprus'': Sometimes classified in Asia West or Europe South. In IFs, it is grouped in Europe South.

· ''Türkiye'': Sometimes considered Europe West Europe or Asia West. In IFs, it is grouped in Asia West.

· ''Iraq'': Sometimes classified as Asia South or Asia West. In IFs, it is grouped in Asia West.

· ''Iran'': Sometimes classified as Asia South or Asia West. In IFs, it is grouped in Asia West.

· ''Georgia'': Sometimes classified as Europe East or Asia West. In IFs, it is grouped in Europe East.

· ''Russian Federation'': Sometimes classified as Europe East or North Asia. In IFs, it is grouped in Europe East.

Europe

· ''Iceland'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe North

· ''United Kingdom'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe West

· ''Ireland'': Sometimes classified as Europe North or Europe West. In IFs, it is grouped in Europe West

· ''Spain'': Sometimes classified as Europe South or Europe West. In IFs, it is grouped in Europe South

· ''Portugal'': Sometimes classified as Europe South or Europe West. In IFs, it is grouped in Europe South.

· ''Austria'': Sometimes classified as Europe East or Europe West. In IFs, it is grouped in Europe West.

· ''Kosovo'': Sometimes classified as Europe South or Europe East. In IFs, it is grouped in Europe South.

· ''Albania'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe South.

· ''Latvia'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

· ''Lithuania'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

· ''Estonia'': Sometimes classified as Europe South, Europe East, or Europe North. In IFs, it is grouped in Europe North.

Americas

''Americas North''

· ''Mexico'': Sometimes classified as Americas North, Americas Central, and Americas Caribbean. In IFs, it is grouped in Americas North.

· ''Puerto Rico'': Sometimes classified as Americas North, Americas Central, Americas South, and Americas Caribbean. In IFs, it is grouped in Americas North.

''Americas Central and the Caribbean''.

· ''Mexico''

· ''Puerto Rico''

· ''Belize'': Sometimes classified as Americas Central or the Caribbean. In IFs, it is grouped in Americas Central.

Economic and Development Groupings

Countries in IFs are also classified by:

· ''Human Development Index (HDI)'': Low, Medium, High, Very High.

· ''World Bank Income Levels'': Low, Lower-Middle, Upper-Middle, High income.

= Conclusion =
The IFs groupings aim for transparency and consistency while addressing disputes over boundary cases. By explicitly justifying controversial classifications, the framework strengthens forecasting accuracy and helps researchers and policymakers interpret global trends with clarity.

<nowiki>https://korbel.du.edu/pardee-resources/international-futures-ifs-country-groupings/</nowiki>

Understand the Model

2025-10-13T18:49:29Z

Ethan.Sullivan:

'''"Opening the Black Box"'''

This section of the Help system contains detailed explanations of the issue sub-modules. You can find flow charts, equations, and other information on each by exploring the sections below:

*[[Understand_IFs#Help_During_Use_of_IFs|Help During Use of IFs]]
*[[Guide_to_Scenario_Analysis_in_International_Futures_(IFs)|Guide to Scenario Analysis in International Futures (IFs)]]
*[[Understand_IFs#Understanding_the_Modeling_Approach|Understanding the Modeling Approach]]
*[[Understand_IFs#Understanding_the_Equations|Understanding the Equations]]
*[[Agriculture|Agriculture]]
*[[Population|Demography/Population]]
*[[Economics|Economics]]
*[[Education|Education]]
*[[Energy|Energy]]
*[[Environment|Environment]]
*[[Governance|Governance]]
*[[Health|Health]]
*[[Infrastructure|Infrastructure]]
*[[Interstate_Politics_(IP)|Interstate Politics]]
*[[Socio-Political|Socio-Political]]
*[[Transport|Transportation]]
*[[Water_model_documentation|Water]]
*[[Country Groupings in IFs|Country Groupings in IFs]]

Understand the Model

2025-10-13T18:48:25Z

Ethan.Sullivan:

Talk:Self-Managed Display (Download)

2025-10-08T19:09:30Z

Ethan.Sullivan: Created page with "Add the Select Exports Button"

Add the Select Exports Button

Quick Scenario Analysis with Tree

2025-09-24T17:22:18Z

Ethan.Sullivan: Incorporating Bido's feedback

The ''Quick Scenario Analysis with Tree'' page can be accessed from the Main Menu: choose '''Scenario Analysis''' then click '''''Quick Scenario Analysis with Tree'''.'' Use this feature to call up or to mix and match an extensive number of scenario interventions and/or a set of stored scenario intervention files, or to change any parameter or initial condition used in the software for any country/region, thus effecting the relationships used to forecast trends. Use the ''Quick Scenario Analysis with Tree'' to create Scenario-Load-Files (.sce), run these files through IFs in order to create Run-Result-Files (.run) that you can use throughout IFs.
[[File:Example of the Quick Scenario Guide.png|center|thumb|950x950px|An example of the Quick Scenario Guide page in IFs when first opened.]]
This page has a number of features and options to create, load, adjust, and run scenarios. These options and features include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Scenario Files''':
** '''Clear Tree''': Clear any interventions currently loaded to the scenario tree.
** '''Open''': Load any set of saved or preloaded Scenario-Load-Files (.sce). Hover over folder names to get to the desired scenario to load then click on that scenario. The '''Open''' drop down is based upon the "Scenarios" folder in the IFs file on the current device. Follow the same file path from the "Scenarios" folder to get to the desired scenario. The parameter tree will change corresponding to the conditions of the chosen scenario file.
** '''Name and Save''': Open a pop up to save a newly created scenario. The popup includes two fields to enter text into; type in the fields then click '''Save''' or '''Cancel'''. The two fields are:
*** '''File Name''': Enter a name for the created scenario.
*** '''Folder Name''': Enter a new or already used folder name within the "User Defined Scenarios" folder under the "Scenarios" folder of the IFs file on the current device, to save the newly created scenario to that location.
** '''Export to IFs Standard CSV Format''': Save a CSV version of the scenario to the same folder that the currently displayed scenario is stored in. For newly created scenarios click '''Name and Save''' first before clicking this option. CSV versions of scenarios can be easier to manage and understand, as all years and dimensions are aligned in titled columns, unlike Scenario-Load-Files (.sce) that are written in comma separated text format.
** '''Export Working File''': Download a Scenario-Load-File (.sce) of the current scenario tree.
** '''Import IFs Standard CSV Format files''': If a scenario is saved using the IFs standard csv format (use '''Export to IFs Standard CSV Format''' for an example of the format) in a folder under the "Scenario" folder in IFs file on the current device, it will appear as an option to import. Follow the same file path from the "Scenario" folder and click on the desired scenario csv to import.
* '''Add Scenario Component''': Similar to '''Open''' from the '''Scenario Files''' options. Layer multiple scenario files or interventions by clicking a different scenario once one has loaded.
* '''Run Scenario''': Open the '''[[Running the Model|Run]]''' page for the current scenario in the scenario tree. Adjust the horizon and click '''Start Run'''.
* '''Delete Selection''': When an intervention is displayed on the screen next to the scenario tree from either clicking on a parameter directly in the tree or from the '''Parameter Search''' option, click '''Delete''' to remove that intervention from the current scenario.
* '''Set Group or Country''': Click '''Groups''' to make interventions for particular groups, or '''Countries''' for a particular country or countries. The current selection will have a checkmark next to it.
* '''Annotate Scenario''': Click Annotate to open a description of the scenario interventions based on the current Scenario Tree. This is auto generated, but to edit the annotation click in the text box and change or add text as desired. Below the text box click '''Save''' to save edits, '''Clear''' to remove all text in the annotation, '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Exit''' to return to the ''Quick Scenario Analysis Tree.''
* '''Parameter Search''': Click '''Search''' to open the ''Parameter Search'' page to search and select specific parameters. The Parameter Search feature is described below.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]].

= <span style="font-size:xx-large;">Parameter Search</span> =

Use the ''Parameter Search'' feature to search, explore, and choose parameters to adjust for scenario analysis. Use this feature with the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' to find the parameters most useful for the intended intervention or scenario goal. Type the desired parameter name in the search bar then click '''Search'''. Click on the parameter which will bring a few options described below. Click '''Load''' to select this parameter in the scenario tree, to adjust it for a scenario. Click '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]], or '''Continue''' to go back to the previous menu or to the Main Menu of IFs.
[[File:Example of Parameter Search Option.png|center|thumb|950x950px|An example of the Parameter Search option for the total fertility rate multiplier tfrm.]]
The options once a parameter is clicked include: <span style="color:red">These options are not available for all parameters.
* '''Define''': See a brief definition of what the parameter is.
* '''Block Diagram (Pop-Up)''': Bring up a help-file that shows a diagram that broadly explains how drivers interact for the area of inquiry (agriculture, economics, etc.). There normally is also textual explanation.
* '''Equations (Pop-Up)''': See the mathematical equations that are used to determine this parameter.

= <span style="font-size:xx-large;">Using the Scenario Tree</span> =
The easiest way to create scenario interventions is to use the ''[[Guide to Scenario Analysis in International Futures (IFs)|Guide to Scenario Analysis in IFs]]'' along with the Parameter Search option, but if desired use the Scenario Tree. Click on any of the categories in the Scenario Tree (ex. Technological change.) to open sub categories and eventually to open up a parameter choices box. Once this box appears to the right of the scenario tree with parameter names and descriptions, click on any parameter to reveal a few options shown below.
[[File:Example of Scenario Tree usage.png|center|thumb|950x950px|An example of the scenario tree being used for Technological Change, Energy, and with the QEM parameter selected; shows the options that selecting a parameter will reveal.]]
The options include: <span style="color:red">These options are not available for all parameters.

* '''Select''': Choose the parameter in order to change it.
* '''Drivers''': Click to see what variables are affecting the chosen parameter.
* '''Explain (Pop-Up)''': See a causal diagram and an explanation of what affects this parameter.
* '''View Equations (Pop-Up)''': See the mathematical equations that are used to determine this number.
* '''Define''': See a brief definition of what the parameter is.
Once a parameter is chosen by clicking '''Select''' a drop down will appear to choose either a particular country or group. Choose the desired country or group by clicking on it. Another drop down will appear if the parameter has dimensions (ex. Male, Female, Total), click on the desired dimension choice and repeat if the parameter has multiple dimension choices. After this the selected parameter will appear to the right of the tree with its base value or scenario value (if opened within an already made scenario) shown. An example of this screen is shown below.
[[File:Example of Parameter Adjustment on Scenario Tree.png|center|thumb|950x950px|An example of a parameter selected to adjust on the Quick Scenario Analysis Tree page. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
Adjust the initial parameter value to make interventions using default changes by clicking the bubble for '''High''' or '''Low''', or to return to the base click '''Base'''. Instead of using the default options use the slider or enter the desired number into the field above the slider and click '''Apply'''. Using this slider or field option will apply that value to the whole time horizon to the year 2150, with an initial shift period based upon the choice from the '''Shift Years''' dropdown. In the example the value is 5.177 and the shift years are 10, so the parameter interpolates from 1 to 5.177 from 2020 to 2030 and then stays at that value for the whole horizon. To have even more control of the parameter click '''Fully Customize'''.
[[File:Example of the Fully Customize Parameter option.png|center|thumb|950x950px|An example of the Fully Customize option for parameter changes. Example of the Government expenditures by destination multiplier (Health) parameter for Argentina.]]
The '''Fully Customize''' option allows more control over parameter behavior. The '''Information''' table displays information of parameter value for a given year, and the minimum and maximum values that IFs allows users to intervene on. If above or below these a warning message will appear. Use the '''Year''' field in this table to jump to a particular year to view the value or to start an intervention from.

The '''Change Numerically''' table is where the changes to a parameter are made from. Use the '''Next Year''' or '''Previous Year''' buttons to change the '''Year''' field by one. Once at the desired year to start an intervention shown in the '''Year''' field, enter in the '''Desired Value''' field the value to change the parameter to, use the '''Years to Repeat or Interpolate''' field to set the number of years for the intervention to take place (this includes the current year so to increase the value for the next 10 years enter 11). Click '''Change/Repeat''' to apply the desired value for the number of years entered (for example an increase to 8 for 61 years from 2090 to 2150, shown above) or click '''Interpolate''' to smoothly shift the value over the number of years entered from the current value to the desired value. Continue to use the '''Change Numerically''' table until the parameter is adjusted as desired.

To ensure that the parameter is adjusted as desired hover over the graph in the right side of the page to see the parameter value in any given year. Click '''Register Change''' to apply this intervention to the current scenario, '''Cancel All Changes''' to clear the current parameter adjustments, '''Exit to Scenario Tree''' to return to the scenario tree, or '''Help''' to open the corresponding page in the [[Main Page|Pardee Wiki]].

Show Computed Functions

2025-09-08T21:39:13Z

Ethan.Sullivan: Created page with "Variables are forecast based on mathematic relationships that are represented by functions within IFs. The ''Show Computed Functions'' option is helpful in exploring these relationships between variables. From the Main Menu choose '''Display''' then click '''''Show Computed Functions'''''. Select a function to visualize from the drop down above the graph; Use the '''Filter Functions (press enter)''' bar to search for specific functions. Check '''Extend List''' to choose..."

Variables are forecast based on mathematic relationships that are represented by functions within IFs. The ''Show Computed Functions'' option is helpful in exploring these relationships between variables. From the Main Menu choose '''Display''' then click '''''Show Computed Functions'''''. Select a function to visualize from the drop down above the graph; Use the '''Filter Functions (press enter)''' bar to search for specific functions. Check '''Extend List''' to choose form all functions not just a core set, and '''Order by Last Change''' to list functions in their order of change. Check the other filters to the right of the dropdown and above the graph to help sort functions; these filter options include: '''Used in Run''', '''Used in Historical Run''', '''Used in Preprocessor''', '''Used in Historical Preprocessor''', '''Not Used''', and '''All'''.
[[File:Example of Show Computed Functions.png|center|thumb|950x950px|An example of the Show Computed Functions page.]]
Once a function is selected from the drop down choose the '''Graph''' option then click '''Draw''' to visualize the function. Below the graph the function will be displayed with its R-square, standard error, and the function equation. The other options and features on this page are:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Graph''': Click '''Draw''' to visualize function once one is selected from the dropdown.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

File:Example of Show Computed Functions.png

2025-09-08T21:26:43Z

Ethan.Sullivan:

An example of the Show Computed Functions page.

Analyze Across Time (Longitudinal)

2025-09-08T21:09:13Z

Ethan.Sullivan:

Use the ''Analyze Across Time'' feature to analyze a variable or a few variables across time for one or a few countries. From the ''Main Menu'': choose '''Data Analysis''' then click '''''Analyze Across Time (Longitudinal)'''''.

There are a number of options and features that alter how the Analyze Across Time feature is used. Always select at least one variable and one country or there will be not data to plot. Choose a variable (or two if you are using '''As Points''' or '''As Time''') from the variable drop down then click '''Select''', then select at least one country using the '''Select Countries''' button, and lastly click '''Plot''' to analyze. When selecting a variable prior to clicking '''Select''' another option '''Data Information''' will be available; click to open information on the data source and availability of the data in different years.
[[File:Example of Analyze Across Time.png|center|thumb|950x950px|An example of the Analyze Across Time page.]]
Use these features and options to assist in analysis:

* '''Treatment of Time''': Choose how to treat time and whether to display more than one variable
** '''As Independent Variable''': Plot one variable across time.
** '''As Points''': Plot two variables, with x and y axis representing one variable, and each point representing a year. Points will be numbered with the first year as 1 and each year after increasing by one.
** '''As Time''': Plot two variables across time. This feature is most useful when variables share similar units.
* '''Independent Variable''' and '''Dependent Variable''': Click on desired choice before choosing a variable; only one option will be shown when using '''As Independent Variable'''.
* '''Show Variable Name Subset''': Choose the variable category like '''Health''' or '''International Politics''' to refine the search.
* '''Other Filters''': Choose '''Used for Initialization''' to only select variables that are used in the model preprocessor, choose variables with '''At least 10 Data Points''', choose variables with data '''At least through 2020''', or choose '''All''' to display all variables.
* '''Use Nulls as Zeros''' or I'''gnore Nulls''': Choose to display years with no available data as zero or to ignore those years.
* '''Select Countries''' or '''Select Groups''': Choose groups or countries to display data for. This option is explained further below.
* '''Plot''': Create a plot of the chosen variables. The plot option is explained further below.
* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Use Groups''' or '''Use Countries''': Switch between using groups or countries; the option to switch to will be displayed.
* '''Computations''': Create a computation for a new variable list to use for data analysis. Follow the steps from the [[Self-Managed Display (Download)#Computations|Computations section of Self Managed Display]] except choose a year when prompted.
* '''Table''': Open a Table Display of the currently selected variable for the selected countries or all countries if non are selected. This feature is only available when using the '''As Independent Variable''' option of '''Treatment of Time'''.
* '''Search''': Open a search page to search and choose variables. The search option is explained further in the [[Analyze Across Countries (Cross Sectional)#Search|Analyze Across Countries]] page.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Select Countries or Groups ==
Use this option to choose the country(s) and or group(s) to display. Choose the desired country or group to display then use the arrow pointing toward the selections box to add it as a selection. Click on a country or group in the selections box and use the arrow pointing away to remove a selection. Add both countries and groups to the selection box by clicking on an option below the selection box: '''Country/Regions''', '''Groups''', or '''Decomp. Groups'''; this will change the selection choices box.
[[File:Example of Select Countries Analyze Across Time.png|center|thumb|950x950px|An example of the Select Countries option from the Analyze Across Time page.]]

== Plot ==
Use the ''Plot'' option to visualize how variables change overtime and their relations with each other. Depending on the choice of '''Treatment of Time''' the plot option will look different. Some plots may have variables on both the X and Y axis, others may have time on the X axis and variables on the other. All plots have options and features that can alter the way data is displayed.
[[File:Example of Plot option Analyze Across Time.png|center|thumb|950x950px|An example of the Plot option from the Analyze Across Time page, for Belize and GDP.]]
These options and features vary between plot but may include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* [[Main Menu Map|'''Main Menu''']]: Go back to the Main Menu of IFs.
* '''Scaling''': When plotting two variables use this option to set the scaling between variable units.
** '''Common''': Scales to a common measure, with 1 representing the largest observation of both variables.
** '''Scale''': Scales to the most recent variable chosen.
* '''View Table''': Open the data displayed on the plot in table display.
* '''Trend''': Add a trend line to fit the data being plotted.
** Choose between '''Linear''', '''Polynomial''', '''Logarithmic''', '''Exponential''', '''S-Curve''', or '''Extrapolation''' '''Setup''' to customize the function relationship.
* Display Format:
** '''Set Title, Display Interval, or Year''': Edit specific display features for the plot such as axis titles and ranges.
** '''Format Legend Labels''': Change the legend format or labels.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

Analyze Across Time (Longitudinal)

2025-09-08T20:56:34Z

Ethan.Sullivan:

Use the ''Analyze Across Time'' feature to analyze a variable or a few variables across time for one or a few countries. From the ''Main Menu'': choose '''Data Analysis''' then click '''''Analyze Across Time (Longitudinal)'''''.

There are a number of options and features that alter how the Analyze Across Time feature is used. Always select at least one variable and one country or there will be not data to plot. Choose a variable (or two if you are using '''As Points''' or '''As Time''') from the variable drop down then click '''Select''', then select at least one country using the '''Select Countries''' button, and lastly click '''Plot''' to analyze. When selecting a variable prior to clicking '''Select''' another option '''Data Information''' will be available; click to open information on the data source and availability of the data in different years.
[[File:Example of Analyze Across Time.png|center|thumb|950x950px|An example of the Analyze Across Time page.]]
Use these features and options to assist in analysis:

* '''Treatment of Time''': Choose how to treat time and whether to display more than one variable
** '''As Independent Variable''': Plot one variable across time.
** '''As Points''': Plot two variables, with x and y axis representing one variable, and each point representing a year. Points will be numbered with the first year as 1 and each year after increasing by one.
** '''As Time''': Plot two variables across time. This feature is most useful when variables share similar units.
* '''Independent Variable''' and '''Dependent Variable''': Click on desired choice before choosing a variable; only one option will be shown when using '''As Independent Variable'''.
* '''Show Variable Name Subset''': Choose the variable category like '''Health''' or '''International Politics''' to refine the search.
* '''Other Filters''': Choose '''Used for Initialization''' to only select variables that are used in the model preprocessor, choose variables with '''At least 10 Data Points''', choose variables with data '''At least through 2020''', or choose '''All''' to display all variables.
* '''Use Nulls as Zeros''' or I'''gnore Nulls''': Choose to display years with no available data as zero or to ignore those years.
* '''Select Countries''' or '''Select Groups''': Choose groups or countries to display data for. This option is explained further below.
* '''Plot''': Create a plot of the chosen variables. The plot option is explained further below.
* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Use Groups''' or '''Use Countries''': Switch between using groups or countries; the option to switch to will be displayed.
* '''Computations''': Create a computation for a new variable list to use for data analysis. Follow the steps from the [[Self-Managed Display (Download)#Computations|Computations section of Self Managed Display]] except choose a year when prompted.
* '''Table''': Open a Table Display of the currently selected variable for the selected countries or all countries if non are selected. This feature is only available when using the '''As Independent Variable''' option of '''Treatment of Time'''.
* '''Search''': Open a search page to search and choose variables. The search option is explained further in the ANALYZE ACROSS COUNTRIES PAGE.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Select Countries or Groups ==
Use this option to choose the country(s) and or group(s) to display. Choose the desired country or group to display then use the arrow pointing toward the selections box to add it as a selection. Click on a country or group in the selections box and use the arrow pointing away to remove a selection. Add both countries and groups to the selection box by clicking on an option below the selection box: '''Country/Regions''', '''Groups''', or '''Decomp. Groups'''; this will change the selection choices box.
[[File:Example of Select Countries Analyze Across Time.png|center|thumb|950x950px|An example of the Select Countries option from the Analyze Across Time page.]]

== Plot ==
Use the ''Plot'' option to visualize how variables change overtime and their relations with each other. Depending on the choice of '''Treatment of Time''' the plot option will look different. Some plots may have variables on both the X and Y axis, others may have time on the X axis and variables on the other. All plots have options and features that can alter the way data is displayed.
[[File:Example of Plot option Analyze Across Time.png|center|thumb|950x950px|An example of the Plot option from the Analyze Across Time page, for Belize and GDP.]]
These options and features vary between plot but may include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* [[Main Menu Map|'''Main Menu''']]: Go back to the Main Menu of IFs.
* '''Scaling''': When plotting two variables use this option to set the scaling between variable units.
** '''Common''': Scales to a common measure, with 1 representing the largest observation of both variables.
** '''Scale''': Scales to the most recent variable chosen.
* '''View Table''': Open the data displayed on the plot in table display.
* '''Trend''': Add a trend line to fit the data being plotted.
** Choose between '''Linear''', '''Polynomial''', '''Logarithmic''', '''Exponential''', '''S-Curve''', or '''Extrapolation''' '''Setup''' to customize the function relationship.
* Display Format:
** '''Set Title, Display Interval, or Year''': Edit specific display features for the plot such as axis titles and ranges.
** '''Format Legend Labels''': Change the legend format or labels.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

File:Example of Plot option Analyze Across Time.png

2025-09-08T20:20:42Z

Ethan.Sullivan:

An example of the Plot option from the Analyze Across Time page, for Belize and GDP.

Analyze Across Time (Longitudinal)

2025-09-04T16:57:19Z

Ethan.Sullivan: work in progress

File:Example of Select Countries Analyze Across Time.png

2025-09-04T16:54:22Z

Ethan.Sullivan:

An example of the Select Countries option from the Analyze Across Time page.

File:Example of the Select Countries from Analyze Across Time.png

2025-09-04T16:52:14Z

Ethan.Sullivan:

An example of the Select Countries or Select Groups option from the Analyze Across Time Page.

File:Example of Analyze Across Time.png

2025-09-04T15:52:38Z

Ethan.Sullivan:

An example of the Analyze Across Time page.

Analyze Across Time (Longitudinal)

2025-09-03T22:55:18Z

Ethan.Sullivan: in progress

Use the ''Analyze Across Time'' feature to analyze a variable or a few variables across time for some or a few countries. From the ''Main Menu'': choose '''Data Analysis''' then click '''''Analyze Across Time (Longitudinal)'''''.

There are a number of options and features that alter how the Analyze Across Time feature is used, but always select a variable (

Analyze Across Countries (Cross Sectional)

2025-09-03T21:24:04Z

Ethan.Sullivan: Added links to other pages

This option can be accessed from the Main Menu: choose '''Data Analysis''' then click '''Analyze Across Countries (Cross-Sectional Analysis)'''.

Use this option to analyze variables across countries at a given point in time. Explore the relationships between two or more variables by selecting the variables of interest from the drop down. First click the bubble below the drop down to select for either the '''Dependent Variable''' or an '''Independent variable''' for the analysis, then choose the desired variable from the drop down. Type into the search bar above the variable dropdown to quickly find a variable. Then use the options and features described below to plot and further explore relationships between variables.
[[File:Example of Analyze Across .png|center|thumb|950x950px|An example of the Analyze Across Countries page.]]
These options and features include:

* '''Show Variable Name Subset''': Choose the variable category like '''Health''' or '''International Politics''' to refine the search.
* '''Other Filters''': Choose '''Used for Initialization''' to only select variables that are used in the model preprocessor, choose variables with '''At least 10 Data Points''', choose variables with data '''At least through 2020''', or choose '''All''' to display all variables.
* '''Analysis''': Choose to '''Use All Years (In Statistics)''', '''Use All Years and Time (In Statistics)''', or '''None''' to only choose one year.
* '''Plot''': Create a plot of the chosen variables. IFs will only plot the relationship between up to three variables. The plot option is explained further below.
* '''Statistics''': Generate statistics for the chosen variables relationships. This explained further below.
* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Computations''': Create a computation for a new variable list to use for data analysis. Follow the steps from the [[Self-Managed Display (Download)#Computations|Computations section of Self Managed Display]] except choose a year when prompted.
* '''Search''': Open a search page to search and choose variables. The search option is explained further below.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Plot ==
Use the '''Plot''' option to visualize relationships between up to three variables. When plotting three variables one of the variables will be represented by dot size.
[[File:Example of Plot for Across Countries.png|center|thumb|950x950px|An example of the Plot option from the Analyze Across Countries page. This example is for Education Years of 25 plus and GDP per capita, with a linear relationship chosen.]]
Option and Features on the Plot page include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* [[Main Menu Map|'''Main Menu''']]: Go back to the Main Menu of IFs.
* '''Display Labels''': Choose '''Country Names''' or '''Country Codes''' to display them on the plot. Choose '''No Labels''' to display none, or choose one of the other two options:
** '''Axis Labels''': Edit the text of the Axis Labels, add a title, or add a subtitle to the plot.
** '''Axis Points and Labels''': Choose which countries to display points or labels for; all countries' points are displayed by default.
* '''Specify Geography''': Change which set of countries or year is displayed; selected option will have a checkmark next to it.
** '''Countries''': Display all countries; selected by default.
** '''Select Geographic List''': Choose a geographic list to display only the countries in that list. Click '''Select''' once the desired list is clicked or '''Continue''' to go back.
** '''Select Group''': Choose a group to display only the countries in that group. Click '''Select''' once the desired group is selected or '''Continue''' to go back.
** '''Add Geographic List''' or '''Add Group''': Select a second or multiple geographic lists or groups to plot, in order to display multiple lists or groups in the same plot.
** '''Add Year''': Choose an additional year to display on the plot.
* '''Relationships''': Choose from a statistical relationship (function) to estimate the relationship between the chosen variables. Once chosen a line of the relationship and the relationship equation will be displayed on the graph like above.
** Relationship options include: '''Linear''', '''Logarithmic''', '''Exponential''', '''Power''', '''Polynomial Second Degree''', '''Polynomial Third Degree''', '''Logistic''', and '''No Regression'''.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Statistics ==
Use the '''Statistics''' option to explore the relationship between chosen variables. Click on any of the Transformation options to transform a variable in the relationship function.
[[File:Example of Statistics Page from Analyze Across Country.png|center|thumb|950x950px|An example of the Statistics option from the Analyze Across Countries page, for GDP per capita and Education Years 25+.]]
Some Options and features within the Statistics option include:

* '''Return to Variable Selection''': Go back to the previous page.
* '''Compute and Show Statistics''': Show statistics and function equation based upon the selected variables and transformations.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Search ==
Similar to the [[Quick Scenario Analysis with Tree#Parameter Search|Parmeter Search]] option, use the variable '''Search''' option to search, explore, and choose variables for data analysis. Type the known name for the variable then click enter or '''Search''', a list of variables that feature what was searched will show in the drop down. From the drop select the desired variable then use the options to right to load or find out more about it.
[[File:Example of Search Variable from Analyze Across Countries.png|center|thumb|950x950px|An example of the Search variable option showing GDP per capita, from the Analyze Across Countries page. ]]
The options on the Search Variables page include:

* '''Search''': Click to search for variables.
* '''Load''': Load this variable as an independent or dependent variable on the ''Analyze Across Countries'' page.
* '''Data Analysis''': Open information on the data source and availability of the data in different years.
* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

Analyze Across Countries (Cross Sectional)

2025-09-03T21:18:41Z

Ethan.Sullivan: Still in progress

This option can be accessed from the Main Menu: choose '''Data Analysis''' then click '''Analyze Across Countries (Cross-Sectional Analysis)'''.

Use this option to analyze variables across countries at a given point in time. Explore the relationships between two or more variables by selecting the variables of interest from the drop down. First click the bubble below the drop down to select for either the '''Dependent Variable''' or an '''Independent variable''' for the analysis, then choose the desired variable from the drop down. Type into the search bar above the variable dropdown to quickly find a variable. Then use the options and features described below to plot and further explore relationships between variables.
[[File:Example of Analyze Across .png|center|thumb|950x950px|An example of the Analyze Across Countries page.]]
These options and features include:

* '''Show Variable Name Subset''': Choose the variable category like '''Health''' or '''International Politics''' to refine the search.
* '''Other Filters''': Choose '''Used for Initialization''' to only select variables that are used in the model preprocessor, choose variables with '''At least 10 Data Points''', choose variables with data '''At least through 2020''', or choose '''All''' to display all variables.
* '''Analysis''': Choose to '''Use All Years (In Statistics)''', '''Use All Years and Time (In Statistics)''', or '''None''' to only choose one year.
* '''Plot''': Create a plot of the chosen variables. IFs will only plot the relationship between up to three variables. The plot option is explained further below.
* '''Statistics''': Generate statistics for the chosen variables relationships. This explained further below.
* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Computations''': Create a computation for a new variable list to use for data analysis. Follow the steps from the COMPUTATIOLNS PAGe except choose a year when prompted.
* '''Search''': Open a search page to search and choose variables. The search option is explained further below.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Plot ==
Use the '''Plot''' option to visualize relationships between up to three variables. When plotting three variables one of the variables will be represented by dot size.
[[File:Example of Plot for Across Countries.png|center|thumb|950x950px|An example of the Plot option from the Analyze Across Countries page. This example is for Education Years of 25 plus and GDP per capita, with a linear relationship chosen.]]
Option and Features on the Plot page include:

* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* [[Main Menu Map|'''Main Menu''']]: Go back to the Main Menu of IFs.
* '''Display Labels''': Choose '''Country Names''' or '''Country Codes''' to display them on the plot. Choose '''No Labels''' to display none, or choose one of the other two options:
** '''Axis Labels''': Edit the text of the Axis Labels, add a title, or add a subtitle to the plot.
** '''Axis Points and Labels''': Choose which countries to display points or labels for; all countries' points are displayed by default.
* '''Specify Geography''': Change which set of countries or year is displayed; selected option will have a checkmark next to it.
** '''Countries''': Display all countries; selected by default.
** '''Select Geographic List''': Choose a geographic list to display only the countries in that list. Click '''Select''' once the desired list is clicked or '''Continue''' to go back.
** '''Select Group''': Choose a group to display only the countries in that group. Click '''Select''' once the desired group is selected or '''Continue''' to go back.
** '''Add Geographic List''' or '''Add Group''': Select a second or multiple geographic lists or groups to plot, in order to display multiple lists or groups in the same plot.
** '''Add Year''': Choose an additional year to display on the plot.
* '''Relationships''': Choose from a statistical relationship (function) to estimate the relationship between the chosen variables. Once chosen a line of the relationship and the relationship equation will be displayed on the graph like above.
** Relationship options include: '''Linear''', '''Logarithmic''', '''Exponential''', '''Power''', '''Polynomial Second Degree''', '''Polynomial Third Degree''', '''Logistic''', and '''No Regression'''.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Statistics ==
Use the '''Statistics''' option to explore the relationship between chosen variables. Click on any of the Transformation options to transform a variable in the relationship function.
[[File:Example of Statistics Page from Analyze Across Country.png|center|thumb|950x950px|An example of the Statistics option from the Analyze Across Countries page, for GDP per capita and Education Years 25+.]]
Some Options and features within the Statistics option include:

* '''Return to Variable Selection''': Go back to the previous page.
* '''Compute and Show Statistics''': Show statistics and function equation based upon the selected variables and transformations.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

== Search ==
Similar to the SEARCH PARAMErTs option, use the variable '''Search''' option to search, explore, and choose variables for data analysis. Type the known name for the variable then click enter or '''Search''', a list of variables that feature what was searched will show in the drop down. From the drop select the desired variable then use the options to right to load or find out more about it.
[[File:Example of Search Variable from Analyze Across Countries.png|center|thumb|950x950px|An example of the Search variable option showing GDP per capita, from the Analyze Across Countries page. ]]
The options on the Search Variables page include:

* '''Search''': Click to search for variables.
* '''Load''': Load this variable as an independent or dependent variable on the ''Analyze Across Countries'' page.
* '''Data Analysis''': Open information on the data source and availability of the data in different years.
* [[Repeated Features#General%20Display%20Options|'''Continue''']]: Go back to the previous menu or to the Main Menu of IFs.
* '''Help''': Open the corresponding page in the [[Main Page|Pardee Wiki]] with the current feature or display they are using.

File:Example of Search Variable from Analyze Across Countries.png

2025-09-03T20:47:36Z

Ethan.Sullivan:

An example of the Search variable option showing GDP per capita, from the Analyze Across Countries page.

File:Example of Statistics Page from Analyze Across Country.png

2025-09-03T19:51:02Z

Ethan.Sullivan:

An example of the Statistics option from the Analyze Across Countries page, for GDP per capita and Education Years 25+.