Difference between revisions of "Guide to Scenario Analysis in International Futures (IFs)"

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= <span style="font-size:xx-large;">Introduction</span> =
 
 
 
The purpose of this document is to facilitate the development of scenarios with the International Futures (IFs) system. This document supplements the IFs Training Manual. That manual provides a general introduction to IFs and assistance with the use of the interface (e.g., how do I create a graphic?). In turn, the broader Help system of IFs supplements this manual. It provides detailed information on the structure of IFs, including the underlying equations in the model (e.g., what does the economic production function look like?). This document should help users understand the leverage points that are available to change parameters (and in a few cases even equations) and create alternative scenarios relative to the Base Case scenario of IFs (e.g., how do I decrease fertility rates or increase agricultural production?). It proceeds across the modules of IFs, such as demographic, economic, energy, health, and infrastructure, to (1) identify some of the key variables that you might want to influence to build scenarios and (2) the parameters that you will want to manipulate to affect your variables of interest. The Training Manual will help you actually make the parameter changes in the computer program and the Help system will facilitate your understanding of the structures, equations and algorithms that constitute the model. We begin by introducing the types of parameters within IFs and then proceed to a discussion of variables and parameters within each of the IFs modules.
 
The purpose of this document is to facilitate the development of scenarios with the International Futures (IFs) system. This document supplements the IFs Training Manual. That manual provides a general introduction to IFs and assistance with the use of the interface (e.g., how do I create a graphic?). In turn, the broader Help system of IFs supplements this manual. It provides detailed information on the structure of IFs, including the underlying equations in the model (e.g., what does the economic production function look like?). This document should help users understand the leverage points that are available to change parameters (and in a few cases even equations) and create alternative scenarios relative to the Base Case scenario of IFs (e.g., how do I decrease fertility rates or increase agricultural production?). It proceeds across the modules of IFs, such as demographic, economic, energy, health, and infrastructure, to (1) identify some of the key variables that you might want to influence to build scenarios and (2) the parameters that you will want to manipulate to affect your variables of interest. The Training Manual will help you actually make the parameter changes in the computer program and the Help system will facilitate your understanding of the structures, equations and algorithms that constitute the model. We begin by introducing the types of parameters within IFs and then proceed to a discussion of variables and parameters within each of the IFs modules.
  
== <span style="font-size:x-large;">A Note on Parameter Names</span><span style="font-size:x-large;"></span> ==
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== <span style="font-size:x-large;">A Note on Parameter Names</span> ==
  
 
In this manual we will provide the internal computer program names of variables and parameters, as well as their descriptions. Those names are especially important for use of the Self-Managed Display form, which provides model users with complete access to all variables and parameters in the system. Most model use, however, employs the Scenario Tree form to build scenarios and the Flexible Display form to show scenario-specific forecasts, and both of those forms rely primarily on natural language descriptions of variables and parameters. To match the names provided here with the options in those forms, you can use the Search feature from the menu. The Training Manual describes how to use features such as the Flexible Display form to see computed forecast variables in natural language. And it also describes how to use the Scenario Tree form to access parameters in something close to natural language. Nonetheless, it helps very much in the use of those features and the model generally to know the actual variable and parameter names.
 
In this manual we will provide the internal computer program names of variables and parameters, as well as their descriptions. Those names are especially important for use of the Self-Managed Display form, which provides model users with complete access to all variables and parameters in the system. Most model use, however, employs the Scenario Tree form to build scenarios and the Flexible Display form to show scenario-specific forecasts, and both of those forms rely primarily on natural language descriptions of variables and parameters. To match the names provided here with the options in those forms, you can use the Search feature from the menu. The Training Manual describes how to use features such as the Flexible Display form to see computed forecast variables in natural language. And it also describes how to use the Scenario Tree form to access parameters in something close to natural language. Nonetheless, it helps very much in the use of those features and the model generally to know the actual variable and parameter names.
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You will typically manipulate parameters to create scenarios or internally coherent stories about the future. You may create scenarios because you wish to represent and explore the possible impact of policy interventions. Or your stories may represent views of the dynamics of global systems alternative to that in the IFs Base Case scenario. Most of the time, you will be interested in tracking the possible futures of selected variables having particular interest to you. The following sections, each covering a module of the IFs system, begin by identifying some of the variables of potentially greatest interest to you. They then provide suggestions on which parameters are likely to be of most useful in building alternative scenarios for those variables. Each section includes tables listing the most effective parameters with which to target certain outcomes. While these suggestions are intended to help you start to think about which parameters you might use to build your scenarios, it is essential that you consider seriously what the policy-based, empirical-knowledge-rooted, or theoretically informed foundations are for your changes.
 
You will typically manipulate parameters to create scenarios or internally coherent stories about the future. You may create scenarios because you wish to represent and explore the possible impact of policy interventions. Or your stories may represent views of the dynamics of global systems alternative to that in the IFs Base Case scenario. Most of the time, you will be interested in tracking the possible futures of selected variables having particular interest to you. The following sections, each covering a module of the IFs system, begin by identifying some of the variables of potentially greatest interest to you. They then provide suggestions on which parameters are likely to be of most useful in building alternative scenarios for those variables. Each section includes tables listing the most effective parameters with which to target certain outcomes. While these suggestions are intended to help you start to think about which parameters you might use to build your scenarios, it is essential that you consider seriously what the policy-based, empirical-knowledge-rooted, or theoretically informed foundations are for your changes.
  
== <span style="font-size:x-large;">Keys to Successfully Modifying Parameters in IFs<span style="font-size:x-large;"></span></span> ==
+
== <span style="font-size:x-large;">Keys to Successfully Modifying Parameters in IFs</span> ==
  
*<span style="font-size:x-large;"></span><span style="font-size:x-large;"></span><span style="font-size:x-large;"></span><span style="font-size:x-large;"></span> Test all parameter changes individually before building combinations, in order to be able to identify which parameters are having specific impacts
+
*Test all parameter changes individually before building combinations, in order to be able to identify which parameters are having specific impacts
*After changing a parameter value and running a scenario, check the impact on the most proximate or closely related variables (identified in the tables of each module section), before checking the secondary impacts of your selected parameter on more distally related variables  
+
*After changing a parameter value and running a scenario, check the impact on the most proximate or closely related variables (identified in the tables of each module section), before checking the secondary impacts of your selected parameter on more distally related variables
*Tie parameter changes to policy options, empirical knowledge, or theoretical insight identified in literature  
+
*Tie parameter changes to policy options, empirical knowledge, or theoretical insight identified in literature
*Bear in mind the relevant geographical level at which a parameter operates; some parameters function directly at a global level (e.g., global migration rates), while others will be most relevant at the regional, or national level  
+
*Bear in mind the relevant geographical level at which a parameter operates; some parameters function directly at a global level (e.g., global migration rates), while others will be most relevant at the regional, or national level
*Some parameters are only effective when used in combination with one another (such as target values and years to reach a target)  
+
*Some parameters are only effective when used in combination with one another (such as target values and years to reach a target)
*Some parameters cancel one another out; for example, trgtval and setar parameters cannot be used together except under very limited circumstances that we attempt to note in the subsequent text  
+
*Some parameters cancel one another out; for example, trgtval and setar parameters cannot be used together except under very limited circumstances that we attempt to note in the subsequent text
*In many cases, variables affected by certain parameters have natural maximums (e.g. 100 percent) or minimums (e.g. fertility rate), so that changes to the parameters affecting them, where countries may already be approaching such a limit, will not have a significant impact  
+
*In many cases, variables affected by certain parameters have natural maximums (e.g. 100 percent) or minimums (e.g. fertility rate), so that changes to the parameters affecting them, where countries may already be approaching such a limit, will not have a significant impact
 
*The IFs systems contains many equilibrating processes, such as those around prices; interventions meant to affect one side of such an equilibration (such as efforts to reduce energy demand) may have offsetting effects (such as lower prices for energy and resultant demand increase) that make it harder than you expect to push the system in the desired direction; real-world policy makers often face such difficulties and may need to push harder than anticipated
 
*The IFs systems contains many equilibrating processes, such as those around prices; interventions meant to affect one side of such an equilibration (such as efforts to reduce energy demand) may have offsetting effects (such as lower prices for energy and resultant demand increase) that make it harder than you expect to push the system in the desired direction; real-world policy makers often face such difficulties and may need to push harder than anticipated
  
<span style="font-size:x-large;"></span>
 
  
<span style="font-size:x-large;"></span>
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== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
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== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
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 +
{| border="1" cellspacing="1" cellpadding="1" style="width: 343px;"
 +
|-
 +
| style="width: 57px;" | '''Variable'''
 +
| style="width: 235px;" | '''Description'''
 +
|-
 +
| style="width: 57px;" | POP
 +
| style="width: 235px;" | Total population
 +
|-
 +
| style="width: 57px;" | POPLE15
 +
| style="width: 235px;" | Population, age 15 or less<br/>
 +
|-
 +
| style="width: 57px;" | POP15TO65
 +
| style="width: 235px;" | Population, age 15 to 65<br/>
 +
|-
 +
| style="width: 57px;" | POPGT65<br/>
 +
| style="width: 235px;" | Population, greater than 65<br/>
 +
|-
 +
| style="width: 57px;" | POPPREWORK<br/>
 +
| style="width: 235px;" | Population, pre-working years<br/>
 +
|-
 +
| style="width: 57px;" | POPWORKING<br/>
 +
| style="width: 235px;" | Population, working years<br/>
 +
|-
 +
| style="width: 57px;" | POPRETIRED<br/>
 +
| style="width: 235px;" | Population, retired<br/>
 +
|-
 +
| style="width: 57px;" | YTHBULGE<br/>
 +
| style="width: 235px;" | &nbsp;% of the population between 15 and 29<br/>
 +
|-
 +
| style="width: 57px;" | POPMEDAGE<br/>
 +
| style="width: 235px;" | Population, median age<br/>
 +
|-
 +
| style="width: 57px;" | LAB<br/>
 +
| style="width: 235px;" | Labor force size<br/>
 +
|-
 +
| style="width: 57px;" | BIRTHS<br/>
 +
| style="width: 235px;" | Births<br/>
 +
|-
 +
| style="width: 57px;" | DEATHS<br/>
 +
| style="width: 235px;" | Deaths<br/>
 +
|-
 +
| style="width: 57px;" | MIGRANTS<br/>
 +
| style="width: 235px;" | Net migration (inward)<br/>
 +
|-
 +
| style="width: 57px;" | CBR<br/>
 +
| style="width: 235px;" | Crude birth rate<br/>
 +
|-
 +
| style="width: 57px;" | CDR
 +
| style="width: 235px;" | Crude death rate<br/>
 +
|-
 +
| style="width: 57px;" | TFR
 +
| style="width: 235px;" | Total fertility rate<br/>
 +
|-
 +
| style="width: 57px;" | CONTRUSE
 +
| style="width: 235px;" | Contraceptive usage<br/>
 +
|-
 +
| style="width: 57px;" | LIFEXP
 +
| style="width: 235px;" | Life expectancy<br/>
 +
|-
 +
| style="width: 57px;" | MIGRATE
 +
| style="width: 235px;" | Net migration rate (inward)<br/>
 +
|}
  
 
The IFs demographic module breaks country populations down into 21 fiveyear age groups, each one subdivided by gender. This allows the model to create an age-sex cohort structure that responds to changes in the three fundamental drivers of population: fertility, mortality, and migration. Births are calculated as a function of each country’s fertility distribution and age distribution. As children are born, they enter the lowest band of the agesex structure, the layer representing people aged 0 through 5. Each country’s population growth is reduced by deaths at each age level; like births, deaths are calculated as a function of the mortality distribution and the age distribution. Finally, migration patterns either add to, or subtract from, each country’s population, depending on the balance of immigration and emigration<sup>3</sup> . Each of the three proximate drivers of population is influenced by deeper social processes: births are a product of fertility patterns; deaths are linked to life expectancy; and net migrants are determined by an overall global migration rate.
 
The IFs demographic module breaks country populations down into 21 fiveyear age groups, each one subdivided by gender. This allows the model to create an age-sex cohort structure that responds to changes in the three fundamental drivers of population: fertility, mortality, and migration. Births are calculated as a function of each country’s fertility distribution and age distribution. As children are born, they enter the lowest band of the agesex structure, the layer representing people aged 0 through 5. Each country’s population growth is reduced by deaths at each age level; like births, deaths are calculated as a function of the mortality distribution and the age distribution. Finally, migration patterns either add to, or subtract from, each country’s population, depending on the balance of immigration and emigration<sup>3</sup> . Each of the three proximate drivers of population is influenced by deeper social processes: births are a product of fertility patterns; deaths are linked to life expectancy; and net migrants are determined by an overall global migration rate.
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== <span style="font-size:x-large;">Parameters to Affect Fertility</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Fertility</span> ==
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{| border="1" cellspacing="1" cellpadding="1" style="width: 443px;"
 +
|-
 +
| style="width: 68px;" | Parameter
 +
| style="width: 115px;" | Variable of Interest
 +
| style="width: 151px;" | Description
 +
| style="width: 93px;" | Type
 +
|-
 +
| style="width: 68px;" | tfrm
 +
| style="width: 115px;" | TFR, CBR
 +
| style="width: 151px;" | Total fertility multiplier<br/>
 +
| style="width: 93px;" | Multiplier<br/>
 +
|-
 +
| style="width: 68px;" | contrusm
 +
| style="width: 115px;" | CONTRUSE
 +
| style="width: 151px;" | Contraceptive use multiplier<br/>
 +
| style="width: 93px;" | Multiplier<br/>
 +
|-
 +
| style="width: 68px;" | eltfrcon
 +
| style="width: 115px;" | TFR
 +
| style="width: 151px;" | Elasticity of total fertility rate to contraception use<br/>
 +
| style="width: 93px;" | Elasticity
 +
|-
 +
| style="width: 68px;" | tfrmin
 +
| style="width: 115px;" | TFR
 +
| style="width: 151px;" | Long term TFR convergence value<br/>
 +
| style="width: 93px;" | Limit
 +
|}
 +
 +
The single most powerful way for users to modify fertility rates is to manipulate '''tfrm''', a parameter that directly alters the total fertility rate within a country or region. This parameter serves as a multiplier on the fertility rate calculated by the model—a 20% increase or decrease in the value of the parameter will result in a similar magnitude of change in the value of the associated variable, '''TFR'''. Because it is a brute force multiplier, users should justify their modifications to the parameter. When used thoughtfully, '''tfrm''' can be a powerful tool for scenario analysis. It can be used to model the impact of fertility control initiatives that extend beyond simple contraceptive use. An example would be the implementation of a program to offer public seminars on the benefits of having fewer children, which could lower the fertility rate even when overall contraceptive usage rates are low. Health care programs for women are a major contributor to fertility decline.
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Users can also directly change the percentage of the population that uses contraceptives via '''contrusm''', a parameter that indirectly affects the total fertility rate via '''CONTRUSE'''. As this is a multiplier, it works the same way as tfrm. It can be used to model the impact of an increase in the availability of family planning education, a campaign to promote the use of condoms, or any other intervention that would likely increase (or decrease) the percentage of a population using contraceptives. Additionally, the parameter '''eltfrcon''' allows users to control the elasticity of total fertility to contraceptive use. For example, a weaker relationship between the two variables might be justified if the contraceptive methods in use in a country or region are widely known to have high failure rates.
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When creating alternative scenarios that span long time horizons, users may wish to modify fertility assumptions built into the demographic module. As countries grow richer and reach higher levels of educational attainment, total fertility rates tend to decrease. However, in forecast years, a minimum value prevents countries from dipping too far below replacement rate. As a default setting, the minimum parameter, '''tfrmin''', is set to 1.9. Thus, in the Base Case, '''TFR''' in highly developed countries will converge to just below 2 children per woman. By increasing or decreasing the parameter, users can experiment with different long-term fertility patterns.
  
 
== <span style="font-size:x-large;">Parameters to Affect Mortality</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Mortality</span> ==
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{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| Parameter
 +
| Variable of Interest
 +
| Description
 +
| Type
 +
|-
 +
| mortm
 +
| DEATHS
 +
| Mortality multiplier (not cause specific)<br/>
 +
| Multiplier<br/>
 +
|-
 +
| hlmortm
 +
| DEATHS
 +
| Mortality multiplier by cause<br/>
 +
| Multiplier<br/>
 +
|}
 +
 +
The [[Health_module_write-up|<span style="background-color:#FFFF00;">health module write-up</span>]] includes a full description of the drivers of mortality in the IFs system, and explains how to manipulate each one. However, one parameter affecting mortality, '''mortm''', is worth discussing separately. 14 This parameter functions similarly to the '''hlmortm''' parameter available in the health module, but does not disaggregate by cause of death. Similar to '''tfrm''', '''mortm''' can be used to model the impact of events that have broad impacts across the population, such as the end of an armed conflict or the implications of a plague. Usually however, if a user is building a scenario analyzing health trends, using the '''hlmortm''' multiplier will be more useful because it disaggregates mortality on the basis of cause. Because morbidity rates in IFs are linked normally to mortality rates, these parameters will affect them also.
  
 
== <span style="font-size:x-large;">Parameters to Affect Migration</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Migration</span> ==
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{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Parameter'''
 +
| '''Variable of Interest'''
 +
| '''Description'''
 +
| '''Type'''
 +
|-
 +
| wmigrm
 +
| MIGRATE, MIGRANTS
 +
| World migration rate multiplier<br/>
 +
| Multiplier
 +
|-
 +
| migrater
 +
| MIGRATE, MIGRANTS
 +
| Net migration rate (inward)<br/>
 +
| Rate of change
 +
|}
 +
 +
Users interested in modifying migration patterns should bear in mind that migrant flows are subject to an accounting system that keeps the global number of net migrants equal to zero. In other words, a person leaving one country will be accounted for when they enter another country. Changing the world migration rate, '''wmigrm''', is the easiest way to affect migration patterns in IFs. Altering this parameter will allow users to increase the overall rate at which migration occurs at a global level, enabling users to simulate large scale increases (or decreases) in migration generated by, say, reductions in visa fees, or the opening of borders as is the case in the EU’s Schengen area. The parameter '''migrater''', on the other hand, allows users to affect the rate of migration into individual countries or regions (values can range from positive, indicating net inward migration, to negative, indicating net outward migration).
  
 
== <span style="font-size:x-large;">Parameters to Affect Working Age</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Working Age</span> ==
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 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Parameter'''
 +
| '''Variable of Interest'''
 +
| '''Description'''
 +
| '''Type'''
 +
|-
 +
| workageentry
 +
| POPPREWORK, POPWORKING<br/>
 +
| Working age determinant<br/>
 +
| Exogenous specification<br/>
 +
|-
 +
| workageretire
 +
| POPWORKING, POPRETIRED<br/>
 +
| Retirement age determinant<br/>
 +
| Exogenous specification<br/>
 +
|}
 +
 +
In addition to manipulating the rate at which populations grow, users can experiment with the effects of changing a country’s working age, something that will be fiscally important in many countries as populations age. The variables '''POPPREWORK''', '''POPWORKING''' and '''POPRETIRE''' map the typical age structure of a country or region’s work force. Two parameters, '''workageentry''' and '''workageretire''', control the age at which a person is considered eligible for work and the age at which a person is eligible for retirement. Changes in the workforce’s age configuration link forward to economic production via the size of the labor force ('''LAB'''). Raising or lowering the retirement age will additionally affect government finances via the size of population of retirement age and the level of pension support provided to households ('''GOVHHPENT''').
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
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 +
An installation of IFs includes high and low population-framing scenarios. Originally created for the poverty volume of the Pardee Center’s Potential Patterns of Human Progress (PPHP) series, the two files are located in the Framing Scenarios folder under Population. Both scenarios feature the direct total fertility rate multiplier. '''Tfrm''' in the high fertility scenario is set to 1.5 globally. In the low fertility scenario, '''tfrm''' is set to .6 in non-OECD nations, and the limit parameter '''tfrmin''' is set to 1.6 globally. Although the two scenarios only feature a few interventions, the effects of such a large change in human reproductive behavior would have significant forward linkages throughout each of the model’s systems.
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Four of the prepackaged scenarios located in the folder Interventions and Agent Behavior contain additional examples of the demographic module’s parameters: Non OECD Contraception Use Slowed, Non OECD Contraception Use Accelerated, World Migration High, and World Migration Low. The pair of scenarios focusing on contraceptive usage rates both utilize '''contrusm'''. In the accelerated scenario, the multiplier takes the value 1.2 in non-OECD nations; and the value 0.8 in the slowed scenario for all non-OECD nations. The two alternate migration scenarios similarly feature interventions on a single parameter: the global migration multiplier '''wmigrm'''. In the high scenario the parameter takes on a value of 2, doubling global migration flows; and in the low scenarios flows are halved, with '''wmigrm''' declining to a value of 0.5.
  
 
= <span style="font-size:xx-large;">Health Module</span> =
 
= <span style="font-size:xx-large;">Health Module</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
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{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| LIFEXP/LIFEXPHLM<br/>
 +
| Life Expectancy<br/>
 +
|-
 +
| CDR
 +
| Crude Death Rate<br/>
 +
|-
 +
| DEATHCAT
 +
| Deaths by Mortality Type<br/>
 +
|-
 +
| HLYLL
 +
| Years of Life Lost<br/>
 +
|-
 +
| HLYLLWORK
 +
| Years of Working Life Lost<br/>
 +
|-
 +
| HLYLD
 +
| Years Lived with Disability<br/>
 +
|-
 +
| HLDALY
 +
| Disability Adjusted Life Years Lost<br/>
 +
|-
 +
| INFMOR
 +
| Infant mortality rate<br/>
 +
|-
 +
| HLSTUNT
 +
| Percentage of population stunted<br/>
 +
|-
 +
| MALNCHP
 +
| Percentage of children malnourished<br/>
 +
|-
 +
| MALNPOPP
 +
| Percentage of population malnourished<br/>
 +
|-
 +
| HLBMI
 +
| Body Mass Index<br/>
 +
|-
 +
| HLOBESITY
 +
| Percentage of population obese<br/>
 +
|-
 +
| HLSMOKING
 +
| Percentage of population that smokes<br/>
 +
|}
 +
 +
The primary variables of interest in the IFs health module are those that pertain to mortality and morbidity due to a variety of causes. '''LIFEXP''' and '''CDR''', discussed in the population module, provide basic measures of population health. '''DEATHCAT''' provides a measure of the number of deaths (in thousands) due to different categories of mortality. IFs can display health variables in the following categories of disease: Other Communicable Disease, Malignant Neoplasm, Cardiovascular, Digestive, Respiratory, Other NonCommunicable Diseases, Unintentional Injuries, Intentional Injuries, Diabetes, AIDs, Diarrhea, Malaria, Respiratory Infections, and Mental Health. Using the Flexible Display form, it is also possible to see many of these variables in the rolled-up categories of Communicable Disease, Non-Communicable Disease, and Injuries or Accidents. Because different health conditions affect age cohorts differentially, the above measure is insufficient in understanding the full impact of ill health. For this reason, it is also possible to break down the actual number of deaths accruing to each cohort, sex, and cause via the Specialized Display menu under the health heading. For example, both the Mortality by Age, Sex, and Cause and the J-Curve displays provide useful information about the health status of a country.
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Three other measures help to enrich the picture: '''HLYLL''', '''HLYLD''' and '''HLDALY'''. Like '''DEATHCAT''', these aggregate (across age-cohort) measures are available by cause and country. '''HLYLL''' is a measure of the number of life years lost due to premature death. It differs from the '''DEATHCAT''' variable because it represents the burden of premature mortality In terms of life years lost, which allows us to account for the fact that some diseases, like HIV/AIDS, primarily affect younger people, while others, like cardiovascular disease, are primarily fatal in older adults. Although the total number of deaths may be the same between two countries for each cause, there may be significant differences between two countries’ health profiles in terms of YLLs.
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'''HLYLD''' is another measure that represents the burden of ill health in terms of life years of impact. It indicates the burden of years lived with disability or disease. In calculating YLD, IFs uses the disability weights that WHO created to rank the relative severity of different conditions and their impact on productivity.
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Finally, Disability Adjusted Life Years (DALYs) are a measure of morbidity (disability or infirmity due to ill health). '''HLDALY''' sums YLLs and YLDs to create a measure of the number of years of life lost to both premature mortality and morbidity due to ill health. Like the other measures discussed above, DALYs can be broken down by different disease categories within IFs. The DALY is probably the most expansive measure of ill-health within a population because it includes mortality burden by age of death and the lost quality of life for those who did not die from health events, but who are disabled by them in some way.
 +
 +
Other measures provide indicators of health in regard to certain specific risk factors for disease or among certain segments of the population. Infant mortality, '''INFMOR''', can be used to assess the burden of ill health among children under one year of age. '''HLSTUNT''', displays the percentage of the population who are stunted (have low height for age),while '''MALNCHP''' and '''MALNPOPP''', provide information on the percentage of the child and adult population who are malnourished respectively. The variables '''INFMOR''', '''HLSTUNT''' and '''MALNCHP''' are especially useful for assessing the burden of ill health due to communicable diseases and other conditions that primarily affect children. By contrast, the variables '''HLBMI''', '''HLOBESITY''', and '''HLSMOKING''' provide risk factor information on diseases that affect primarily adults. HLBMI represents the body mass index in a country while '''HLOBESITY''' and '''HLSMOKING''' provide information on the percentage of the population that is obese or smokes.
 +
 +
Other variables that will be useful to users interested in specific conditions or subpopulations include indicators on stunting and BMI, as well as smoking and obesity. Variables for HIV/AIDS are also available and discussed separately below in the subsection on the [[HIV/AIDS|<span style="background-color:#FFFF00;">HIV/AIDS</span>]] sub-module.
  
 
== <span style="font-size:x-large;">Parameters to Affect Overall Health and Burden of Disease</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Overall Health and Burden of Disease</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Parameter'''
 +
| '''Variable of Interest'''
 +
| '''Description'''
 +
| '''Type'''
 +
|-
 +
| hlmortm
 +
| DEATHCAT/HLYLL/HLDALY
 +
| Multiplier on Mortality (by cause)<br/>
 +
| Multiplier<br/>
 +
|-
 +
| hlmorbm
 +
| YLD
 +
| Multiplier on morbidity<br/>
 +
| Multiplier<br/>
 +
|-
 +
| hlstddthsw
 +
| DEATHCAT
 +
| Switches DEATHCAT from absolute numbers to deaths/1000<br/>
 +
| Switch
 +
|}
 +
 +
The above parameters provide simple ways to directly affect the burden of disease within a country. The most important parameter for modifying mortality rates is '''hlmortm''', a parameter that allows users to increase or decrease the prevalence of deaths in any particular category of illness. IFs modifies mortality in the following categories: Other Communicable Disease, Malignant Neoplasm, Cardiovascular, Digestive, Respiratory, Other NonCommunicable Diseases, Unintentional Injuries, Intentional Injuries, diabetes, AIDs, Diarrhea, Malaria, Respiratory Infections, and Mental Health. Altering the mortality burden will affect the variables '''DEATHCAT''', '''HLYLL''', and '''HLDALYs'''. The parameter will indirectly affect morbidity because of its direct link to mortality. In the case of Mental Health Diseases, the parameter will not have much impact on '''DEATHCAT''', but may have a significant impact on the number of DALY’s experienced by a population. Because '''hlmortm''' is a multiplier, increasing its value from 1 to 1.2 represents a 20% increase in the burden of mortality from a particular cause. A similar parameter, '''hlmorbm''', allows users to affect morbidity directly through a brute force multiplicative parameter. This allows users to affect the years lost to disability in a working life and by extension multifactor productivity due to human capital ('''MFPHC'''). The '''hlstddthsw''' allows users to switch between displaying DEATHCAT in absolute numbers to deaths per thousand people.
  
 
== <span style="font-size:x-large;">Parameters that Affect Communicable Diseases</span> ==
 
== <span style="font-size:x-large;">Parameters that Affect Communicable Diseases</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| Parameter
 +
| Variable of Interest
 +
| Description
 +
| Type
 +
|-
 +
| watsafem
 +
| WATSAFE, INFMOR<br/>
 +
| Percentage of population with access to safe water<br/>
 +
| Multiplier<br/>
 +
|-
 +
| sanitationm
 +
| SANITATION, INFMOR<br/>
 +
| Percentage of population with access to improved sanitation<br/>
 +
| Multiplier<br/>
 +
|-
 +
| malnm
 +
| MALNCHPSH<br/>
 +
| Prevalence of child malnutrition<br/>
 +
| Multiplier<br/>
 +
|-
 +
| ylm
 +
| YL
 +
| Yield multiplier on agriculture<br/>
 +
| Multiplier<br/>
 +
|-
 +
| hivm
 +
| HIVCASES<br/>
 +
| Rate of HIV infection<br/>
 +
| Multiplier<br/>
 +
|}
 +
 +
Above are a number of the parameters that users may wish to use to manipulate communicable diseases (which predominantly affect children). '''Ylm''' is a multiplicative parameter in the [[Agriculture_module|<span style="background-color:#FFFF00;">agriculture module</span>]] that can be used to change the yield of agricultural lands within a country, affecting the number of calories available for consumption, and thereby altering the rates of malnutrition and obesity. '''Watsafem''' and '''sanitationm''', in the [[Infrastructure#Infrastructure|infrastructure module]], influence the percentage of the population that has access to safe water and sanitation respectively, thus decreasing childhood exposure to diarrheal disease, malnutrition and premature death. Other parameters to control safe water and sanitation access are discussed in the [[Infrastructure|<span style="background-color:#FFFF00;">infrastructure</span>]] section of the model. Finally, although HIV is more thoroughly discussed in the [[HIV/AIDs_submodule|<span style="background-color:#FFFF00;">HIV/AIDs submodule</span>]], one brute force parameter is worth noting here. '''Hivm''' allows users to directly affect the rate of infection with the HIV virus.
  
 
== <span style="font-size:x-large;">Parameters that Affect Non-Communicable Disease</span> ==
 
== <span style="font-size:x-large;">Parameters that Affect Non-Communicable Disease</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Parameter'''
 +
| '''Variable of Interest'''
 +
| '''Description'''
 +
| '''Type'''
 +
|-
 +
| envpm2pt5m<br/>
 +
| ENVPM2PT5<br/>
 +
| Increases levels of environmental pollution<br/>
 +
| Multiplier<br/>
 +
|-
 +
| hlsmokingm<br/>
 +
| HLSMOKING<br/>
 +
| Increases rate of smoking<br/>
 +
| Multiplier<br/>
 +
|-
 +
| hlobesitym<br/>
 +
| HLOBESITY<br/>
 +
| Prevalence of obesity<br/>
 +
| Multiplier<br/>
 +
|-
 +
| hlbmim<br/>
 +
| HLBMI<br/>
 +
| Multiplier on body mass index<br/>
 +
| Multiplier<br/>
 +
|}
 +
 +
'''Hlsmokingm''' is a multiplicative parameter that will change the rate of smoking, which will affect the prevalence of respiratory diseases. '''Envpm2pt5m''' is a multiplicative parameter that will change the level of ambient environmental pollution in terms of parts per million; higher levels of environmental pollution are a risk factor for both communicable and non-communicable respiratory diseases.
 +
 +
'''Hlobesitym''' works similarly to affect the prevalence of obesity within a society in the absence of overall caloric intake changes. This parameter can be used to model the impact of changing levels of physical activity within a society. Both of the above parameters work similarly to other multiplicative parameters: increasing the value of the parameter to 1.2 from 1, represents a 20% increase in the value of the parameter over the base case. By the same token, users can use '''hlbmim''' to affect the body mass index in a country, a major risk factor for cardiovascular diseases, diabetes, and overall morbidity. Please note: '''hlobesitym''' affects only obesity rates and has no affect on health; in contrast, '''hlbmim''' will affect body mass index, obesity, and deaths from heart disease and diabetes.
  
 
== <span style="font-size:x-large;">Parameters that Affect Injuries and Accidents</span> ==
 
== <span style="font-size:x-large;">Parameters that Affect Injuries and Accidents</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Parameter'''
 +
| '''Variable of Interest'''
 +
| '''Description'''
 +
| '''Type'''
 +
|-
 +
| deathtrpvm<br/>
 +
| DEATHTRPV<br/>
 +
| Multiplier on traffic deaths per vehicle<br/>
 +
| Multiplier<br/>
 +
|-
 +
| deathtrpvsetar, deathtrpseyrtar<br/>
 +
| DEATHTRPV<br/>
 +
| Standard error target for traffic deaths per vehicle<br/>
 +
| Relative target Value/Year<br/>
 +
|}
 +
 +
Only a small set of parameters allow users to affect injuries and accidents, and these primarily revolve around reducing traffic deaths. Users may reduce traffic deaths as a ratio of the number of vehicles in a country using either a multiplier, '''deathtrpvm''', or a pair of standard error targeting parameters, '''deathtrpvsetar''' and '''deathtrpseyrtar'''. Standard error targeting is discussed in detail in the [[Infrastructure#Infrastructure|infrastructure module]]. These parameters allow users to model the impact of road safety on mortality and, by extension, on economic productivity.
  
 
== <span style="font-size:x-large;">Parameters to Affect Technology</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Technology</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| Parameter
 +
| Variable of Interest
 +
| Description
 +
| Type
 +
|-
 +
| hlmortmodsw<br/>
 +
| CDR<br/>
 +
| Reduces crude death rate in Africa, Europe, Southeast Asia, West Pacific<br/>
 +
| Switch
 +
|-
 +
| hltechshift<br/>
 +
| CDR<br/>
 +
| Rate of change in health technology<br/>
 +
| Additive factor<br/>
 +
|-
 +
| hltechlinc<br/>
 +
| CDR<br/>
 +
| Rate of change in health technology in low income countries<br/>
 +
| Additive factor<br/>
 +
|-
 +
| hltechssa<br/>
 +
| CDR<br/>
 +
| Rate of change in health technology in Sub-Saharan Africa<br/>
 +
| Additive factor<br/>
 +
|-
 +
| hltechbase<br/>
 +
| CDR<br/>
 +
| Rate of change in health technology at base<br/>
 +
| Exogenous specification<br/>
 +
|}
 +
 +
Aside from the direct and indirect parameters affecting health, the distal drivers of health include per capita GDP, years of education, and technology. Per capita GDP is an element of the [[Economics#Economics|economic module]] and can be changed in a number of ways, but especially by changing the elements that make up multifactor productivity. Years of education is an element of the [[Education#Education|education module]] and can be changed by altering the duration of schooling, and the completion rate.
 +
 +
Moving to the third distal driver of health, there are a number of parameters built into the health module that can be used to alter the rate of technological change. '''Hlmortmodsw''' is a master switch that, when set to 1 as in the Base Case default, reduces technological progress for low-income countries of Africa, Europe, Southeast Asia, and West Pacific based on geographic and income categories. There are parameters available to alter these assumptions about differentials in mortality declines in these regions, but they only have an effect in the base case; when '''hlmortmodsw''' is set to 0 these parameters have no impact.
 +
 +
Once '''hlmortmodsw''' is set to 1, users can manipulate mortality patterns through several parameters. Hltechshift, alters the rate of change for health technology impacts relative to GDP. The '''hltechshift''' parameter allows users to change the mortality rate using a shift parameter that alters the technology factor affecting mortality decline relative to initial GDP. '''Hltechlinc''' and '''hltechssa''' can be used to change the rate of technological advance resulting in mortality decline in low-income countries ('''hltechlinc''') and sub-Saharan Africa (hltechssa) specifically. Meanwhile, the '''hltechbase''' parameter allows users to change the base level of technological change across the 20 world, rather than country by country as you can do using the '''hltechshift''' parameter. All of these parameters pertain to all causes of mortality except cardiovascular mortality, which uses a different regression equation.
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
Three major integrated scenarios on health were developed by the Pardee Center for the health volume of the Patterns of Potential Human Progress series (Hughes et al., 2011). The World Integrated Scenario Sets folder contains the scenarios that were built for this volume, of which three are worth an extended discussion. The first is the Proximate Drivers Excluding Environment folder, which contains parameters to individually alter four of the major risk factors for several causes of mortality. These are Body Mass Index which is a risk factor for cardiovascular disease; under nutrition, which is a risk factor for communicable diseases; smoking which is a risk factor for respiratory disease; and large increases in the number of cars per person coupled with poor pedestrian safety, which is a major risk factor for accidental death. This scenario also includes increased to improved water sources and piped sanitation taken from the infrastructure module, and parameters to reduce environmental exposure to poor air quality. This scenario reduces these risk factors to their theoretical minima, to simulate aggressive efforts to reduce, high BMI, the obesity rate, childhood malnutrition, smoking, and traffic mortality. Malnutrition is set to 0.01, smoking and obesity multipliers are set to 0, BMI multiplier to 0.8, vehicle fleets to 0.5, and traffic mortality to 0.
 +
 +
Another important pair of prepackaged scenarios contains the optimistic Luck and Enlightenment scenario, and a scenario that considers what happens when Things Go Wrong. The Luck and Enlightenment scenario includes improvements to HIV/AIDS, sanitation access, improved air quality, and reduced smoking rates which help lower the burden of NCDs. It also features changes to the burden of communicable disease designed to increase the levels of these. A variation to Luck and Enlightenment has add-ins that also increase foreign aid donations and agricultural yields, effectively modeling a situation in which increased global cooperation supports these efforts. Things Go Wrong models a world in which air quality worsens, smoking and obesity rates increase and there is little international cooperation on addressing these challenges.
  
 
= <span style="font-size:xx-large;">HIV/AIDS Submodule</span> =
 
= <span style="font-size:xx-large;">HIV/AIDS Submodule</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| HIVCASES
 +
| Number of HIV cases<br/>
 +
|-
 +
| HIVRATE
 +
| HIV infection rate<br/>
 +
|-
 +
| HIVTECCNTL
 +
| Rate of technical control of infection, cumulative reduction in infection rate<br/>
 +
|-
 +
| AIDSDTHS
 +
| Number of AIDS deaths<br/>
 +
|-
 +
| AIDSDRATE
 +
| Death rate from AIDS<br/>
 +
|-
 +
| AIDSDTHSCM
 +
| Cumulative Number of AIDS deaths since first year of model<br/>
 +
|}
 +
 +
HIV and AIDS have attracted significant interest among policy makers because of the tremendous toll that these diseases have on populations in both human and economic terms. Because of this interest, it is worth discussing the HIV/AIDS submodule separately from the rest of the health module. That submodule represents both the extent of HIV prevalence in a population (a stock variable) and the annual deaths from AIDS (a flow variable driven in substantial part by the prevalence rate, but also responsive to technological advance in the fight against AIDS). A number of key variables are available to represent the burden of HIV and AIDS within a country.
 +
 +
Three variables are key to understanding the progression of infection within a country. '''HIVCASES''' provides the total number of HIV cases, '''HIVRATE''' represents a flow variable showing the rate at which people are being infected with HIV, and '''HIVTECCNTL''' indicates the progress being made in reducing the rate of infection within a country.
 +
 +
Three other variables assess mortality due to HIV and AIDs within a country. Similar to HIV, the variables '''AIDSDTHS''' and '''AIDSDRATE''' indicate the number of AIDs deaths and the rate of mortality from AIDs respectively, while '''AIDSDTHSCM''' represents the cumulative number of deaths due to the disease.
  
 
== <span style="font-size:x-large;">Parameters to Affect Prevalence</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Prevalence</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Parameter'''
 +
| '''Variable of Interest'''
 +
| '''Description'''
 +
| '''Type'''
 +
|-
 +
| hivm
 +
| HIVRATE<br/>
 +
| HIV infection rate, multiplier of percent of population infected<br/>
 +
| Multiplier
 +
|-
 +
| hivtadvr<br/>
 +
| HIV CASES/ HIVRATE<br/>
 +
| Technical advance rate in of control of infection<br/>
 +
| Rate of change<br/>
 +
|-
 +
| hivmdcm<br/>
 +
| HIVRATE<br/>
 +
| HIV infection rate maximum for MDCs, multiplier<br/>
 +
| Rate of change<br/>
 +
|-
 +
| hivpeakr<br/>
 +
| HIVCASES/ HIVRATE<br/>
 +
| HIV infection rate at year of peak<br/>
 +
| Target value
 +
|-
 +
| hivpeakyr<br/>
 +
| HIVRATE<br/>
 +
| Sets year of epidemic peak<br/>
 +
| Target year
 +
|-
 +
| hivincr<br/>
 +
| HIVCASES<br/>
 +
| HIV increase rate, only used prior to 2000<br/>
 +
| Rate of change<br/>
 +
|}
 +
 +
Modifying the infection rate with '''hivm''' is probably the easiest way to adjust the burden of HIV infection within a country. Like '''hlmortm''', '''hivm''' is a multiplicative parameter. In other words, increasing the value of the parameter in scenario analysis from 1 to 1.2 represents a 20% increase in the rate of infection relative to the base case. '''Hivtadvr''' allows users to change the prevalence of HIV, once the epidemic has peaked, by a certain percent annually to model different assumptions about the rate at which control technologies will improve, reducing the prevalence of the disease over time. Unlike the mortality multiplier, which takes effect once the model has calculated the base Variable Name Description HIVCASES Number of HIV cases HIVRATE HIV infection rate HIVTECCNTL Rate of technical control of infection, cumulative reduction in infection rate AIDSDTHS Number of AIDS deaths AIDSDRATE Death rate from AIDS AIDSDTHSCM Cumulative Number of AIDS deaths since first year of model 22 case, this parameter will affect the actual calculations the model makes while running. This parameter functions as additive factor to a growth rate within IFs. In other words, a 0.01 increase in the parameter represents a 0.01 increase in the growth rate for the technical advance rate in HIV infection control ('''hivtadvr''').
 +
 +
The HIV submodule is designed to allow users to affect the course of the epidemic across countries and across time. The multiplier '''hivmdcm''' is a multiplicative parameter that affects the maximum infection rate in middleincome developing countries. Another way to alter the course of the epidemic is by manipulating the coefficient on '''hivpeakr''', which is an additive parameter that will increase the peak rate of infection over the course of the epidemic. Thus a 0.01 increase in the value of the coefficient represents a 0.01 increase in the peak infection rate. An associated parameter, '''hivpeakyr''' sets the date at which the epidemic will peak before the infection rate begins to decline. Changing this parameter in the Scenario Analysis page will allow users to set any year between 2010 and 2100 as the year of peak infection rate depending on their assumptions regarding the technical rate of advance in controlling the disease. Finally, the parameter hivincr controls the increased rate in infection prior to 2000, when our knowledge of the epidemic was much less complete and control efforts were far less effective.
  
 
== <span style="font-size:x-large;">Parameters to Affect Mortality</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Mortality</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Parameter'''
 +
| '''Variable of Interest'''
 +
| '''Description'''
 +
| '''Type'''
 +
|-
 +
| aidsdrtadvr<br/>
 +
| AIDSDTHS/AIDSRATE<br/>
 +
| AIDs death rate, technical annual advance rate in control<br/>
 +
| Rate of change<br/>
 +
|-
 +
| aidsdratem<br/>
 +
| AIDSRATE<br/>
 +
| AIDs death rate as&nbsp;% of HIV infection rate, multiplier<br/>
 +
| Multiplier
 +
|}
 +
 +
Just as there are a variety of parameters available to control the prevalence of HIV within a population, there are also a number of parameters that allow users to control the lethality of the epidemic. The first of these parameters allow user to change the death rate as a percentage of the infection rate via the parameter '''aidsdratem'''. This parameter directly alters the lethality of the disease; it serves as a proxy for the presence or absence of control measures within a country since the availability of anti-retroviral medications will affect the rate at which people who are HIV positive die from AIDs. Of course, new research strongly suggests that ART therapies may also significantly reduce the HIV infection rate as well, but because these are not yet linked in the model, users should be aware that a more realistic use of this parameter would alter not only the AIDs mortality rate, but the infection rate as well. The other parameter available to users to control mortality from AIDs is '''aidsdrtadvr''', a parameter which changes the technical annual advance rate in control. This parameter simulates the annual advance in technologies to control AIDs mortality, altering the lethality of the disease.
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
There are several prepackaged scenarios that deal with the HIV/AIDS epidemic. The first, under the heading Hivaids in the Technological Advance section of the Framing Scenarios folder, models two scenarios around technological advance to control the epidemic. One models rapid technical advances to control HIV infection, while the other presents a scenario in which technological progress slows, slowing the resulting decline in infections.
 +
 +
A second set of prepackaged scenarios are available to affect HIV/AIDS are focused on altering the course of the epidemic in key countries, rather than at a global level. They are called: Intermediate HIV/AIDS, Intermediate for New School Paper, Severe HIV Aids and Total Failure to Control HIV AIDs and are located in the Surprises and Wildcards folder, under the heading AIDs. These scenarios modify the course of the AIDS epidemic in Russia, China, India, and the world at large. Each one affects parameters controlling the infection rate at the peak year of the epidemic, the peak infection rate, the initial rate of infection, the rate of advance in the infection, and the elasticity of multifactor productivity to life expectancy. They give a good example of how to modify combinations of parameters in specific countries to create different trajectories for the epidemic.
 +
 +
  
 
= <span style="font-size:xx-large;">Education Module</span> =
 
= <span style="font-size:xx-large;">Education Module</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
|
 +
'''EDYRSAG15'''
 +
 +
'''EDYRSAG25'''
 +
 +
'''EDYRSAG15TO24'''
 +
 +
| Educational attainment, adults by age group
 +
|-
 +
|
 +
'''EDPRIPER'''
 +
 +
'''EDSECPER'''
 +
 +
'''EDTERPER'''
 +
 +
| Percent of the population completing primary, secondary and tertiary
 +
|-
 +
|
 +
'''EDPRIENRG'''
 +
 +
'''EDSECENRG'''
 +
 +
'''EDSECLOWRENRG'''
 +
 +
'''EDSECUPPRENRG'''
 +
 +
'''EDTERENRG'''
 +
 +
| Gross enrollment rate in primary, secondary, lower secondary, upper secondary and tertary
 +
|-
 +
|
 +
'''EDPRIENRN'''
 +
 +
'''EDSECENRN'''
 +
 +
| Net enrollment rate in primary, secondary
 +
|-
 +
|
 +
'''EDPRIINT'''
 +
 +
'''EDPRIINTN'''
 +
 +
'''EDTERINT'''
 +
 +
| Primary intake rates, gross and net, and tertiary intake rates, gross
 +
|-
 +
|
 +
'''EDSECLOWRTRAN'''
 +
 +
'''EDSECUPPRTRAN'''
 +
 +
| Transition rates from primary to lower secondary and from lowers secondary to upper secondary
 +
|-
 +
|
 +
'''EDPRISUR'''
 +
 +
'''EDSECLOWRSUR'''
 +
 +
'''EDSECUPPRSUR'''
 +
 +
| Survival rates for primary, lower secondary, upper secondary
 +
|-
 +
|
 +
'''EDPRICR'''
 +
 +
'''EDSECLOWRGRATE'''
 +
 +
'''EDSECUPPRGRATE'''
 +
 +
'''EDTERGRATE'''
 +
 +
| Graduation rates in primary, lower, secondary, upper secondary and tertiary
 +
|-
 +
|
 +
'''EDSECLOWRVOC'''
 +
 +
'''EDSECUPPRVOC'''
 +
 +
| Vocational enrollment rates, lower and upper secondary
 +
|-
 +
|
 +
'''EDEXPERPRI'''
 +
 +
'''EDEXPERSEC'''
 +
 +
'''EDEXPERTER'''
 +
 +
| Government spending per student as a percentage of GDP for primary, secondary and tertiary
 +
|-
 +
| '''GDSED'''
 +
| Spending shares by level of education
 +
|}
 +
 +
 +
 +
Like all of IFs, the education module is amenable to systems thinking, or conceptualizing elements as stocks and flows. Students flow through primary, lower-secondary, upper-secondary and tertiary education levels. Each time an age cohort completes a grade level, a year is added to that group’s stock of educational attainment; as adults (aged either 15 and older or 25 and older) they will have attained some number of years of formal education based on grades completed. For any given grade, the number of students enrolled is determined by the intake rate—or, at the secondary level, the transition rate from the previous level of education—and by the percentage of students passing through the last grade. Government spending influences the system by restraining the number of students that can be sustained at a given level of education.
 +
 +
Most analysis of the international education system focuses on educational attainment. IFs operationalizes this stock as the average years of education successfully completed by adults in all countries, following a typology designed by Harvard economists Robert Barro and Jong-Wha Lee (2000, 2001). '''EDYRSAG15''' captures the mean years of education attained for all adults older than 15; this important variable links forward to several other sectors of the model, including economics through multifactor productivity, health through fertility rate, and even governance through state fragility indicators. Users may wish to view mean years of education by other age breakdowns, available through '''EDYRSAG25 '''and&nbsp;'''EDYRSAG15TO24''' though these variables do not have the forward linkages in the model that '''EDYRSAG15''' does. As an alternative to average years of education, '''EDPRIPER, EDSECPER and EDTERPER '''track attainment as a percentage of the population to successfully complete each level of education.
 +
 +
In addition to attainment measures, most users will focus their attention on enrolment rates, the most common measure of student flows. Enrolment rates answer the simple question: at a given time, how many children are in school?
 +
 +
Enrollment is captured in the variables '''EDPRIENRG '''and&nbsp;'''EDPRIENRN '''for primary,'''EDSECENRG''','''EDSECENRN''','''EDSECLOWERENRG '''and '''EDSECUPPRENRG '''for secondary and&nbsp;'''EDTERENRG '''for the tertiary level'''.''' Many of the indicators used to measure education systems are either gross rates or net rates. This important distinction has to do with student age. Gross Enrollment Rates (GER), for example, are calculated by dividing the total student body by the official school-age population; Angola’s primary GER would be the number of primary students enrolled in school divided by the primary age population of the country and has often exceeded 100 percent because of primary enrollment by over-aged students who enter or return to school for various reasons. Net Enrollment Rates (NER), on the other hand, measure only the students of official school age. A country’s NER is the enrolled age-appropriate students divided by only the school-age population and should not exceed 100 percent. Net enrolment data are often more difficult to find than gross, simply because it requires the age of enrollees to calculate. Intake rates are also presented in both net and gross formulations. For a more detailed description of commonly used education indicators see UNESCO’s technical guidelines: [http://www.uis.unesco.org/Library/Documents/eiguide09-en.pdf http://www.uis.unesco.org/Library/Documents/eiguide09-en.pdf].
 +
 +
For each of the countries in IFs, two factors ultimately control enrolment rates: intake rates and survival rates. Drawing on drivers such as GDP per capita and educational spending, the model forecasts intake rates for primary and tertiary levels ('''EDPRIINT, EDPRIINTN, and EDTERINT''') and transition rates from the previous level of schooling for secondary education ('''EDECLOWRTRAN EDSECUPPRTRAN'''). The model also forecasts a student persistence rate for all levels (except tertiary), often referred to as survival rate, captured in the variables '''EDPRISUR''', '''EDSECLOWRSUR''', and '''EDSECUPPRSUR'''. Enrolment rates at each level are calculated as the combined result of these student flows. Or thought of more simply, enrolment rates track the number of students who enter school and stay in school. Graduation rates at all levels are also forecast and the corresponding variables are: EDPRICR, '''EDSECLOWRGRATE''', '''EDSECUPPRGRATE''' and '''EDTERGRATE'''. The model also forecasts vocational shares in lower secondary and upper secondary and the variables are '''EDSEECLOWRVOC''' and '''EDSECUPPRVOC'''.
 +
 +
All indicators in the model that measure the stock of educational attainment or student flows can be disaggregated by gender. Thus, the user is able to evaluate each country’s progress toward eliminating gender-based disparity in the classroom. In order to disaggregate performance by gender, a second dimension of almost all education variables allows the selection of display by male, female or total. In addition to setting normative goals, separate treatment of female education allows the model to establish powerful forward linkages. For example, female educational attainment and fertility rates are negatively related, because schooling increases the opportunity cost of having and raising a child.
 +
 +
In addition to student flows, the model captures financial flows tied to each country’s education system. Educational finance is the result of interplay between supply-side and demand-side forces. Demand for education can be conceptualized as the product of spending per student and enrollment rates at each level of schooling—'''EDEXPERPRI, EDEXPERSEC '''and&nbsp;'''EDEXPERTER''' track spending per student as a percent of GDP per capita for primary, secondary and tertiary education. However, such a formulation of demand is crude, as the number of children already in the system is constrained by the preexisting structure of government spending. Financial supply, captured as a percent of GDP by the variable '''GDSED''', is generated by the government finance submodule. Due to a lack of reliable data, IFs does not capture private educational funding, though it is important in some countries.
  
 
== <span style="font-size:x-large;">Parameters to Affect Intake Rates and Survival Rates: Annual Growth</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Intake Rates and Survival Rates: Annual Growth</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edpriintngr'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDPRIINTN
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Primary net intake rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Annual growth
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edterintgr'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDTERINT
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Tertiary intake rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Annual growth
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edseclowrtrangr'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDSECLOWRTRAN
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Lower secondary transition rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Annual growth
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edsecupprtrangr'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDSECUPPRTRAN
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Upper secondary transition rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Annual growth
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edprisurgr'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDPRISUR
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Primary survival rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Annual growth
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edtergradgr'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDTERGRAD
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Tertiary graduation rates
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Annual growth
 +
 +
|}
 +
 +
In the IFs model, improved education outcomes can be achieved most directly through changes to intake and survival rates. The number of students entering the first grade of each schooling level can be pushed up or down using annual (percentage point) growth parameters: '''edpriintngr '''for primary school''', edseclowrtrangr '''for transfer rates between primary and secondary''', edsecupprtrangr '''for transition between lower and upper secondary and'''edterintgr '''for intake into the tertiary level'''. '''However, any improvements to enrolment stemming from intake rate boosts are restrained when coupled with high dropout or repetition rates. Like intake rates, survival rates can be directly manipulated through annual growth parameters. '''Edprisurgr '''controls survival growth (in percentage points) at the primary level.&nbsp;And finally, '''edtergradgr '''controls tertiary survival rates (also referred to as graduation rates).
 +
 +
&nbsp;Though intake rates and survival rates can be manipulated separately, users will often wish to manipulate them in conjunction due to the presence of interaction effects between the two sets of variables. For example, a rapid increase in intake/transition rates can result in a decline in country’s survival rate. The educational system may simply not have the resources to cope with an influx of students. Furthermore, the incoming cohort, which has spent years outside the system, may represent individuals from disadvantaged backgrounds—a group prone to dropping out. On the other hand, rising intake rates may have a positive threshold effect on survival rates. In many countries, once intake rates reach a certain level, dropout and repetition have declined. At this time such relationships are not captured in IFs. Thus, the user may want to build interaction and threshold effects into education policy interventions.
  
 
== <span style="font-size:x-large;">Parameters to Affect Intake Rates and Survival Rates: Target Year for Universal Education</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Intake Rates and Survival Rates: Target Year for Universal Education</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="638" style="width:638px;"
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:192px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:193px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''edpriintntrgtyr'''
 +
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
EDPRIINTN
 +
 +
| nowrap="nowrap" style="width:192px;height:22px;" |
 +
Primary net intake rate
 +
 +
| nowrap="nowrap" style="width:193px;height:22px;" |
 +
No. of years to reach 100% &nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''edseclowrtrantrgtyr'''
 +
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
EDSECLOWRTRAN
 +
 +
| nowrap="nowrap" style="width:192px;height:22px;" |
 +
Lower secondary transition rate
 +
 +
| nowrap="nowrap" style="width:193px;height:22px;" |
 +
No. of years to reach 100% &nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''edsecupprtrantrgtyr'''
 +
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
EDSECUPPRTRAN
 +
 +
| nowrap="nowrap" style="width:192px;height:22px;" |
 +
Upper secondary transition rate
 +
 +
| nowrap="nowrap" style="width:193px;height:22px;" |
 +
No. of years to reach 100% &nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''edterinttrgtyr'''
 +
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
EDTERINT
 +
 +
| nowrap="nowrap" style="width:192px;height:22px;" |
 +
Tertiary Intake Rate
 +
 +
| nowrap="nowrap" style="width:193px;height:22px;" |
 +
No. of years to reach 100% &nbsp;&nbsp;&nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''edprisurtrgtyr'''
 +
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
EDPRISUR
 +
 +
| nowrap="nowrap" style="width:192px;height:22px;" |
 +
Primary survival rate
 +
 +
| nowrap="nowrap" style="width:193px;height:22px;" |
 +
No. of years to reach 100% &nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''edtergradtrgtyr'''
 +
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
EDTERGRAD
 +
 +
| nowrap="nowrap" style="width:192px;height:22px;" |
 +
Tertiary graduation rates
 +
 +
| nowrap="nowrap" style="width:193px;height:22px;" |
 +
No. of years to reach 100% &nbsp;
 +
 +
|}
 +
 +
Development goals like universal access to education with a specific target date can be explored through target year parameters on intake (transition) or survival (graduation) rates. These parameters ramp up the base year value of the variable of interest to one hundred percent within the number of years marked by the parameter. For countries with limited availability of government resources, these target parameters might need an education budget set aside through the edbudgon parameter described later in the budget sub-section .
  
 
== <span style="font-size:x-large;">Parameters to Affect Intake Rates and Survival Rates: Multiplier</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Intake Rates and Survival Rates: Multiplier</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edpriintnm'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDPRIINTN
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Primary net intake rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Multiplier on base case
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edterintm'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDTERINT
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Tertiary intake rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Multiplier on base case
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edseclowrtranm'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDSECLOWRTRAN
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Lower secondary transition rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Multiplier on base case
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edsecupprtranm'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDSECUPPRTRAN
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Upper secondary transition rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Multiplier on base case
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edprisurm'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDPRISUR
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Primary survival rate
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Multiplier on base case
 +
 +
|-
 +
| nowrap="nowrap" style="width:118px;height:22px;" |
 +
'''edtergradm'''
 +
 +
| nowrap="nowrap" style="width:135px;height:22px;" |
 +
EDTERGRAD
 +
 +
| nowrap="nowrap" style="width:234px;height:22px;" |
 +
Tertiary survival rates
 +
 +
| nowrap="nowrap" style="width:145px;height:22px;" |
 +
Multiplier on base case
 +
 +
|}
 +
 +
In addition to the growth and target parameters described above, intake (or transition) and survival (or graduation) rates can also be modified using a set of multipliers listed in the table above. Like other multipliers in the model these work by ramping up (or down) the base case forecast over a horizon chosen in the scenario design.
  
 
== <span style="font-size:x-large;">Parameters to Affect Education Spending</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Education Spending</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''gdsm (education)'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Government spending on education
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''edbudgon'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Education funding impact and priority
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''gdsedm'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Education spending distribution
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''edexppconv'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
EDEXPERPRI
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Education spending per student, primary
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''edexpslconv'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
EDEXPERSEC
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Education spending per student, secondary
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''edexpsuconv'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
EDEXPERSEC
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Education spending per student, secondary
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''edexptconv'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
EDEXPERTER
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Education spending per student, tertiary
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:126px;height:22px;" |
 +
'''edqtqltrm'''
 +
 +
| nowrap="nowrap" style="width:190px;height:22px;" |
 +
EDEXPERPRI, EDEXPERSEC , EDEXPERTER and GDS
 +
 +
| nowrap="nowrap" style="width:195px;height:22px;" |
 +
Education quantity-quality balance
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplier
 +
 +
|}
 +
 +
Attainment levels also respond indirectly to changes in the educational spending structure. The number of students enrolled at all grade levels is constrained by total public spending on education. In IFs, public finance allocations are distributed between transfer payments, the military, education, health and infrastructure in the [[#_The_Social_Accounting|government budget submodule]]. Bottom-up factors like demographic changes and policies targeting intake or survival will pressure the government to increase education spending. But the model features somewhat rigid top-down control of the budget—spending on education competes with other government spending and IFs maintains accounting of both total government revenues and expenditures. Most countries spend something close to the global average of 5 percent of GDP on education each year. Thus demand-side shifts may secure an increase in resources, but it is difficult to increase total education spending much in excess of historically observed values. Users can intervene in this accounting process by manipulating '''gdsm (education)''', a multiplier that directly increases the share of government expenditure accounted for by education, at the expense of spending in other arenas such as military or health. Alternatively, users can prioritize education spending over other government expenditure targets. The priority parameter '''edbudgon''', takes on values from zero to one, with lower values representing lower priority to education funding demands and one representing maximum priority. Any non-zero value pushes education allocations away from those determined by historical spending patterns and level of economic development—as calculated in the economic module—and toward the bottom-up demand for expenditures calculated in the education model. The parameter '''edbudgon''' can also be used to completely turn off the budget impacts on student flow rates through a zero value of the parameter. The turning off of budget impacts is helpful in projecting the demand for funds for certain types of education intervention, e.g., universal primary education. However, fund demand in such a scenario is calculated in the EDTOTCOST and not in the GDS(Education) variable, which is determined, in this case, completely through the government budget allocation algorithm without using any input from the education model. &nbsp;&nbsp;&nbsp;
 +
 +
&nbsp;The government-budget submodule automatically allocates resources to the educational level most in need (although that interacts with historical patterns of educational preference), starting with primary education. As enrolment rates in a country’s primary education system reach a very high level, the model reallocates funding up the chain to secondary. Users may wish to change this pattern and create normative scenarios that prioritize higher levels of education, or balance spending between primary, secondary and tertiary. The '''gdsedm '''parameter allows for such experimentation via a second dimension that allots the spending increase to a specific level of schooling.
 +
 +
When developing education budgets, planners must account for trade-offs between equity and efficiency. What is more important, increasing total spending on the system in an effort to support more students, or increasing spending per student in an effort to improve the experience of being in school? In a crude way this can be thought of as the difference between increasing intake and increasing survival rates. IFs includes parameters that shift the spending focus in the direction of system efficiency. '''Edexppconv '''can be used to decrease the time it takes a country’s initial spending per primary student to converge with the model’s expected function. '''Edexppslconv '''and&nbsp;'''edexppuconv '''control the student expenditure function for lower and upper secondary, and&nbsp;'''edexpptconv '''does the same for the tertiary level'''.''' Increasing the target value used in a convergence parameter will increase per student spending for countries below the expected value, but the opposite is true in countries exhibiting higher than expected values. If a user wishes to boost per student expenditure in a high performing country, he or she should make use of the '''edqtqltrm''' parameter, a multiplier that shifts emphasis away from education quantity and towards education quality—with values less than one indicating a shift towards quality.
  
 
== <span style="font-size:x-large;">Parameters to Affect Gender Parity</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Gender Parity</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:155px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:239px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:116px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:155px;height:22px;" |
 +
'''edprigndreqintn'''
 +
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
EDPRIINTN
 +
 +
| nowrap="nowrap" style="width:239px;height:22px;" |
 +
Gender parity for primary intake
 +
 +
| nowrap="nowrap" style="width:116px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:155px;height:22px;" |
 +
'''edprigndreqsur'''
 +
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
EDPRISUR
 +
 +
| nowrap="nowrap" style="width:239px;height:22px;" |
 +
Gender parity for primary survival
 +
 +
| nowrap="nowrap" style="width:116px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:155px;height:22px;" |
 +
'''edseclowrgndreqtran'''
 +
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
EDSECLWRTRAN
 +
 +
| nowrap="nowrap" style="width:239px;height:22px;" |
 +
Gender parity for lower secondary transition
 +
 +
| nowrap="nowrap" style="width:116px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:155px;height:22px;" |
 +
'''edsecupprgndreqtran'''
 +
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
EDSECUPPRTRAN
 +
 +
| nowrap="nowrap" style="width:239px;height:22px;" |
 +
Gender parity for upper secondary transition
 +
 +
| nowrap="nowrap" style="width:116px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:155px;height:22px;" |
 +
'''edtergndreqint'''
 +
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
EDTERINT
 +
 +
| nowrap="nowrap" style="width:239px;height:22px;" |
 +
Gender parity for tertiary intake
 +
 +
| nowrap="nowrap" style="width:116px;height:22px;" |
 +
Convergence speed
 +
 +
|-
 +
| nowrap="nowrap" style="width:155px;height:22px;" |
 +
'''edtergndreqgrad'''
 +
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
EDTERSUR
 +
 +
| nowrap="nowrap" style="width:239px;height:22px;" |
 +
Gender parity for tertiary survival
 +
 +
| nowrap="nowrap" style="width:116px;height:22px;" |
 +
Convergence speed
 +
 +
|}
 +
 +
Some development projects focus on gender disparity in education, rather than aggregate enrolment. In recent decades male and female enrolment rates have converged rapidly across all regions of the world. In fact, primary, secondary and tertiary enrolment taken as a global aggregate has already surpassed a female-male ratio of 0.97—commonly considered an indicator of parity. However this abstracted view obscures struggles facing women in low-performing areas, especially sub-Saharan Africa. Users may explore effects linked to improvements in female-specific enrolment rates via the intake and survival parameters described above; each parameter has a dimension that applies the annual increase to males, females, or the total student population. Alternatively, users can experiment with closing the gender attainment gap existing in some countries by setting time sensitive goals. Goals around intake can be set through '''edprigndreqintn '''for primary,'''&nbsp;''''''edsecupprgndreqtran '''for secondary and&nbsp;'''edtergndreqint '''for the tertiary level. Gender conversion goals may also be set for the other direct driver of enrolment, survival rates: '''edprigndreqsur '''controls female survival rates at the primary level''', '''&nbsp;and&nbsp;'''edtergndreqgrad '''controls tertiary rates. Each of the gender-focused parameters are convergence speed goals, meaning the user sets the number of years that will elapse before the country’s gender parity in the corresponding measure converges to the expected function.
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
&nbsp;An installation of IFs includes scenarios used in each entry in the Pardee Center’s Potential Patterns of Human Progress (PPHP) series. Scenarios created for the education volume include: a best and worst case framing scenario; case study interventions in several countries and regions; high spending and low spending scenarios; and over twenty normative scenarios (Dickson et al., 2010). This section will briefly describe the parameters used to construct a single normative scenario titled, Norm Mar 1 2009.
 +
 +
Norm Mar 1 2009 simulates a worldwide improvement in educational performance through interventions to: intake rates, student persistence, gender parity and educational spending, including boosts to foreign aid. From 2010 to 2100, the parameter '''edpriintngr''' is set to 2.2, and '''edprisurgr''' is set to 1.2, setting up annual increases to primary school intake and survival rates. The scenario includes similar annual growth increases for intake and student persistence across lower secondary and upper secondary schooling. '''Edseclowrtrangr '''is set to one percent, &nbsp;'''edsecupprtrangr''' to 0.5 percent. The corresponding parameters for tertiary education are not assigned a value other than the default of zero. Additional interventions speed up the narrowing of persisting gender gaps in intake, survival and transition rates. The parameters '''edprigndreqintn and edprigndreqsur''' set a ten year time goal for gender parity at the primary level; '''edseclowrgndreqtran and edseclowrgndreqsurv '''set a thirteen year goal for parity at the lower secondary level; and,'''edsecupprgndreqtran '''set a 20 year time goal for parity at the upper secondary level. In order to simulate improved education quality, across levels, '''edexppconv, edexpslconv, edexpsuconv and edexptconv '''all take the value of 20, signifying a convergence to the expected function after 20 forecast years. Because this scenario was created as a tool to explore the potential impacts of a world in which educational goals are achieved by all nations, the budget switch, '''edbudgon''', is set to 0, the highest prioritization of education funding.
  
 
= <span style="font-size:xx-large;">Economic Module</span> =
 
= <span style="font-size:xx-large;">Economic Module</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 +
 +
The treatment of economics in IFs draws on both the classical tradition’s focus on economic growth (with great attention in IFs to the newer work on endogenous growth theory) and the neoclassical perspective's general equilibrium approach.
 +
 +
The economic module is a core component of the IFs system for multiple reasons, in particular for its close interactions with all other modules. On the input side, variables from almost all other modules affect production levels. On the output side, the magnitude of GDP and the level of GDP per capita are critical, in turn, for essentially all other modules. Mostly closely linked to the economic module are the energy and agriculture modules, both of which use a partial equilibrium structure that echoes the one in the economic module, and both of which provide physical values that fully determine the currency value-based representations of their respective sectors in the economic model.
 +
 +
Basic economic variables include: GDP at market exchange rates ('''GDP'''), GDP at purchasing power parity ('''GDPP'''), GDP per capita at market exchange rates ('''GDPPC'''), and GDP per capita at purchasing power parity ('''GDPPCP'''). The model represents all of these in constant 2011 dollars (the interface allows the user to convert to other currencies). &nbsp;&nbsp;The model also includes a representation of the portion of the economy that is informal.
 +
 +
==== Multifactor Productivity ====
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| '''GDP'''
 +
| Gross domestic product
 +
|-
 +
| '''GDPP'''
 +
| GDP at purchasing power parity
 +
|-
 +
| '''GDPPCP'''
 +
| Per capita GDP at purchasing power parity
 +
|-
 +
| '''GDPPC'''<br/>
 +
| Per capita GDP
 +
|-
 +
| '''LAB'''<br/>
 +
| Labor<br/>
 +
|-
 +
| '''KS'''<br/>
 +
| Capital stock<br/>
 +
|-
 +
| '''I'''<br/>
 +
| Investment<br/>
 +
|-
 +
| '''POPRETIRED'''<br/>
 +
| Retired Population<br/>
 +
|-
 +
| '''MFP (HC,SC,PC,KN)'''<br/>
 +
| Multifactor productivity<br/>
 +
|}
 +
 +
The supply side of the economic module is based on the Cobb-Douglas Production Function and uses labor ('''LAB'''), capital ('''KS'''), and multifactor productivity ('''MFP''') as the primary drivers of economic growth. Capital stock ('''KS''') is a function of investment ('''I''') and depreciation rates. Labor supply ('''LAB''') is determined from population and endogenously derived labor force participation rates.
 +
 +
While the treatment of capital and labor in the IFs system will be familiar to users with an understanding of neoclassical economics, the treatment of productivity within IFs deserves greater explanation. Unlike most neoclassical models, which primarily focus on technology as the determining factor of productivity in their equations, the IFs system uses a broader definition of productivity called multifactor productivity (MFP). This multi-factor productivity term in IFs has four basic components: human ('''MFPHC'''), social ('''MFPSC'''), physical ('''MFPPC'''), and knowledge capital productivity ('''MFPKN'''). Each of these components can take on a positive or negative value depending on whether the calculated value of the component is providing a positive or negative impact to economic growth rates relative to what would be expected based on the country’s level of development. (See the Development Profile form in IFs to display the magnitude and direction of the four productivity elements.)
 +
 +
Drivers of multifactor productivity vary by component. '''MFPHC''' is driven by years of education, education expenditures, life expectancy and health expenditure. '''MFPSC''' is driven by Freedom House’s measure of political freedom (a variable describing democracy), governance effectiveness, corruption perceptions, and economic freedom. '''MFPPC''' is driven by two separate indices of infrastructure: traditional (roads, electricity, and water and sanitation), and information and communications technology (ICT). Finally, '''MFPKN''' is driven by R&D expenditures and economic integration (in the model, trade serves as a proxy for trade). This final component of MFP represents a measure of connectedness to the global economy. Altering any of these using the appropriate parameters will result in changes to the relevant component of multifactor productivity and therefore to economic growth.
 +
 +
==== The Social Accounting Matrix and Domestic Finance ====
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| '''C'''
 +
| Private consumption
 +
|-
 +
| '''SAVINGS'''
 +
| Net national savings
 +
|-
 +
| '''HHINC'''
 +
| Household income
 +
|-
 +
| '''HHSAV'''
 +
| Household savings
 +
|-
 +
| '''FIRMINC'''
 +
| Firm income
 +
|-
 +
| '''FIRMSAV'''
 +
| Firm savings
 +
|-
 +
| '''IDS'''
 +
| Investment by destination sector
 +
|-
 +
| '''GOVREV'''
 +
| Government revenue
 +
|-
 +
| '''GOVEXP'''
 +
| Government expenditures
 +
|-
 +
| '''GOVHHTRN'''
 +
| Government household transfers
 +
|-
 +
| '''GOVCON'''
 +
| Government consumption
 +
|-
 +
| '''GDS'''
 +
| Government spending by destination
 +
|-
 +
| '''GOVBAL'''
 +
| Government balance
 +
|-
 +
| '''GOVDEBT'''
 +
| Government debt
 +
|}
 +
 +
The production function is embedded in a six sector model of the economy featuring agriculture, raw materials, energy, manufactures, services, and ICT that balances domestic demand and trade in a general equilibrium seeking structure. Production and consumption of goods and services are in turn incorporated into a larger social accounting matrix (SAM) which represents the behavior and financial interaction of households, firms and government. A social accounting matrix traditionally represents ''flows'' among different economic sectors and agent categories (i.e., households, firms, and government). For instance, it represents private consumption ('''C''') and net national savings ('''SAVINGS'''), as well as household income ('''HHINC''') and savings ('''HHSAV'''); firm income ('''FIRMINC'''), investment by sector ('''IDS'''), and savings ('''FIRMSAV'''); government revenues ('''GOVREV'''), total expenditures with transfers ('''GOVEXP'''), transfers to households ('''GOVHHTRN'''), directed consumption in total ('''GOVCON'''), and by sector ('''GDS'''), and balance ('''GOVBAL'''). IFs builds a full and balanced social accounting matrix of these and many other inter-agent flows. It also creates a second matrix which represents financial ''stocks'' (assets and liabilities) of different agent categories for all countries in the system, including for instance, government debt ('''GOVDEBT'''). The representation of stocks in this fashion provides the foundation upon which the system adjusts flows of finance among different agents and among countries over time (see, for instance, the net foreign debt or '''XDEBT''' of countries), maintaining consistency with the liability-asset approach used in standard accounting systems. The behavior of agents within this system is not fixed, like it is in many computable general equilibrium models (which use SAMs commonly). Instead, agent behavior is partially endogenized using algorithms that allow the behavior of agents to shift depending on the levels of stocks of relevant variables within the SAM. So, for example, different levels of government debt trigger different patterns of government spending in IFs.
 +
 +
Because of its centrality to the IFs system, users should understand the basic character of the social accounting matrix. Both the stock and flow matrices are available in the specialized displays menu in the display section of the main menu. The social accounting matrix loads the flow matrix by default, but the stock matrix can be accessed via the Show Stocks button on the bar at the top. Full breakouts of the SAM into its component parts is also available on this screen by clicking the button Expand SAM on the same top bar.
 +
 +
==== International Trade and Finance ====
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| '''CURACT'''<br/>
 +
| Current account balance
 +
|-
 +
| '''CAPACT'''
 +
| Capital account
 +
|-
 +
| '''TRADEBAL'''
 +
| Trade balance
 +
|-
 +
| '''XWORKREMIT'''
 +
| Worker remittances from abroad<br/>
 +
|-
 +
| '''AID'''<br/>
 +
| Net foreign aid receipts<br/>
 +
|-
 +
| '''X or XS'''<br/>
 +
| Exports and exports by sector<br/>
 +
|-
 +
| '''M or MS'''<br/>
 +
| Imports and Imports by sector<br/>
 +
|-
 +
| '''ENX/ENM'''<br/>
 +
| Energy exports/imports<br/>
 +
|-
 +
| '''AGX/AGM'''<br/>
 +
| Agricultural exports/imports<br/>
 +
|-
 +
| '''XFDIFIN'''<br/>
 +
| Inward flow of FDI<br/>
 +
|-
 +
| '''XFDIFOUT'''<br/>
 +
| Outward flow of FDI<br/>
 +
|-
 +
| '''XFDISTOCK'''<br/>
 +
| Inward stocks of FDI<br/>
 +
|-
 +
| '''XFDISTOUT'''<br/>
 +
| Outward stocks of FDI<br/>
 +
|-
 +
| '''XPORTFIN'''<br/>
 +
| Inward flows of portfolio investment<br/>
 +
|-
 +
| '''XPORTFOUT'''<br/>
 +
| Outward flows of portfolio investment<br/>
 +
|-
 +
| '''XPORTFOLIO'''<br/>
 +
| Inward stocks of portfolio investment<br/>
 +
|-
 +
| '''XPORTSTOUT'''<br/>
 +
| Outward stocks of portfolio investment<br/>
 +
|-
 +
| '''XDEBTRPA'''<br/>
 +
| External debt, relative price adjusted<br/>
 +
|-
 +
| '''EXRATE'''<br/>
 +
| Exchange rate<br/>
 +
|}
 +
 +
The international financial position of a country is typically represented by the balance of payments, which is equal to zero if all flows of goods and finance into and out of a country are included. The balance of payments is determined by the status of three indicators, the current account ('''CURACT'''), the capital account ('''CAPACT'''), and the foreign reserve account (not explicitly modeled in IFs). Imbalances can exist in any of these if imports of goods and services outweigh exports for example, or if governments spend down foreign reserves.
 +
 +
In IFs, the status of the current account balance ('''CURACT'''), which reflects the many flows into and out of a country, is a function of the trade balance ('''TRADEBAL'''), net foreign worker remittances ('''XWORKREMIT'''), net foreign aid ('''AID'''), and net interest on foreign debt. Worker remittances are calculated on the basis of the size of the population of a country that is living and working abroad.
 +
 +
Of these the trade balance and treatment of trade within IFs more generally is worth further discussion. Trade in the IFs system is part of the social accounting matrix structure and is modeled using a pooled rather than bilateral approach. This means that IFs tracks information on gross exports and imports of countries by sector and in total. An algorithm sums price-adjusted import demand and export capacity across all countries that trade in a given sector and defines world trade as the average of those two values. Demand and capacity are then normalized to the total of world trade to determine total and sectoral exports ('''X''' or XS '''by''' sector) and imports ('''M''' or '''MS''' by sector) by country. As already noted, the agricultural and energy modules each represent production, consumption and trade that supersede the results of the economic module’s production function and SAM. For instance, exports and imports in these modules are represented separately within the IFs system via '''ENX'''/'''ENM''' and '''AGX'''/'''AGM'''. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;
 +
 +
Interacting with the current account is the capital account ('''CAPACT'''). It captures the flows of foreign direct and portfolio investment into ('''XFDIFIN''' and '''XPORTFIN''') and out of countries ('''XFDIFOUT''' and '''XPORTFOUT'''). The system also represents the stocks of inward and outward FDI and portfolio investment ('''XFDISTOCK'''/ '''XPORTFOLIO''' and '''XFDISTOUT'''/'''XPORTOUT'''). Together the current and capital account flows shape the stock of relative-price-adjusted net foreign indebtedness ('''XDEBTRPA'''), which in turn via an equilibration process changes the exchange rate ('''EXRATE'''). The exchange rate, in interaction with local relative prices, affects trade and financial flows over time as a key part of that equilibration process.
 +
 +
==== Informal Economy ====
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| '''LABINFORMSHR'''
 +
| Informal share of the labor force<br/>
 +
|-
 +
| '''LABINFORMPCNTINF'''<br/>
 +
| Portion of informal labor employed inside informal sector<br/>
 +
|-
 +
| '''LABINFORMPCNTNONINF'''<br/>
 +
| Portion of informal labor employed outside the informal sector (in formal enterprises or households)<br/>
 +
|-
 +
| '''GDPINFORMSHR'''<br/>
 +
| Informal share of GDP<br/>
 +
|-
 +
| '''GDPSHADOWSHR'''<br/>
 +
| Shadow economy share of GDP<br/>
 +
|-
 +
| '''EDYRSAG15'''<br/>
 +
| Educational attainment of adults 15 and older<br/>
 +
|-
 +
| '''GOVBUSREGIND'''<br/>
 +
| Government business regulation index (higher is better)<br/>
 +
|-
 +
| '''GOVCORRUPT'''<br/>
 +
| Government corruption (higher is less corrupt)<br/>
 +
|-
 +
| '''GOVHHTRN'''<br/>
 +
| Government transfers to households for welfare and pensions<br/>
 +
|-
 +
| '''GDS, R&D'''<br/>
 +
| Government spending on research and development<br/>
 +
|-
 +
| '''FIRMTAXR'''<br/>
 +
| Tax rate (direct) on firms<br/>
 +
|-
 +
| '''HHTAXR'''<br/>
 +
| Tax rate (direct) on households<br/>
 +
|-
 +
| '''SSWELTAXR '''<br/>
 +
| Tax rate (direct) on households and firms for social welfare<br/>
 +
|-
 +
| '''RANDDEXP'''<br/>
 +
| Total (public and private) spending on research and development<br/>
 +
|-
 +
| '''TEFF '''<br/>
 +
| Stock of total (multifactor)productivity<br/>
 +
|}
 +
 +
The economic module represents the informal economy as the share of the total labor force employed informally ('''LABINFORMSHR'''), the share of total GDP generated by informal activities ('''GDPINFORMSHR'''), and the share of total GDP generated by the shadow economy ('''GDPSHADOWSHR'''). The informal labor share is driven by four main variables: the educational attainment of adults 15 years of age and older ('''EDYSAG15''', see the education model for parameters to affect this variable), the government business index ('''GOVBUSREGIND'''), the ratio of government transfers to households as a portion of GDP ('''GOVHHTRN'''), and the tax rate on firms ('''FIRMTAXR''').
 +
 +
The informal labor share is divided into two sectors, the portion of informal labor employed inside the informal sector ('''LABINFORMPCNTINF''', informal) and the portion of informal labor employed in the formal sector (represented by a simple residual '''LABINFORMPCNTNONINF'''). Each sector is further divided by sex.
 +
 +
The share of informal labor in total labor and the portion of informal labor employed inside the informal sector both help drive informal and shadow GDP shares. Other drivers include the level of corruption ('''GOVCORRUPT'''), public expenditure on research and development as a percentage of its GDP ('''GDS, R&D'''), and total (public and private) spending on research and development ('''RANDDEXP).''' &nbsp;
 +
 +
While informal ''and'' shadow GDP shares are initialized in the Base Case, ''only'' informal ('''GDPINFORMSHR''') has active forward linkages. To drive the forward linkages with the shadow economy share instead, you must change the switch, '''gdpshadowon''', from its default, Base Case setting of 0 to 1 (see Parameters for Affecting the Informal Economy section below).&nbsp;
 +
 +
The informal GDP shares, in turn, have forward linkages to total or multifactor productivity ('''TEFF'''), effective household ('''HHTAXR) '''and firm tax rates, as well as to the effective rate for social welfare ('''SSWELTAXR''').
  
 
== <span style="font-size:x-large;">Parameters to Affect Production and Growth</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Production and Growth</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" colspan="4" |
 +
''<u>Labor</u>''
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''lapoprm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
LAB
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Labor participation rate multiplier
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''labfemshrm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
LAB
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Female labor force participation rate multiplier&nbsp;
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''labretagem'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
LAB
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Retirement age, labor force participation multiplier
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''workageentry'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
POPRETIRED
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Age at which individuals enter the labor force
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''workageretire'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
POPRETIRED
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Age at which individuals leave the labor force
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
&nbsp;
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
&nbsp;
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
&nbsp;
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
&nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" colspan="4" |
 +
''<u>Capital</u>''
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''invm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
IDS
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Investment by destination sector
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
&nbsp;
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
&nbsp;
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
&nbsp;
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
&nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" colspan="4" |
 +
''<u>Productivity</u>''
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''mfpadd'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
MFP components
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Multifactor productivity, additive
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Additive factor
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''mfpleadr'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
MFP
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
MFP growth rate of the technological lead country
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Growth Rate
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''mfpedspn'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
GDS-educ
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Increase portion of spending going to education
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''malnm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
HLSTUNT
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
&nbsp;Malnutrition multiplier
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''ylm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
YL
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
&nbsp;Land yield
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''aginvm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
AGINV
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Investment in agriculture
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''econfreem'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
ECONFREE
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Economic freedom
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''goveffectm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
GOVEFFECT
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Government effectiveness
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''govcorruptm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
GOVCORRUPT
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Government corruption
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''freedomm'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
FREEDOM
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Freedom/democracy
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''mfpinfrindtrad'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
INFRAINDTRAD
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Traditional infrastructure
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''mfpinfrindict'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
INFRAINDICT
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
ICT infrastructure
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''mfpenpri'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
WEP
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
World energy price
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''gdsm, R&D'''
 +
 +
| nowrap="nowrap" style="width:112px;height:22px;" |
 +
GDS, R&D
 +
 +
| nowrap="nowrap" style="width:282px;height:22px;" |
 +
Connectivity
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|}
 +
 +
Based upon the discussion of key variables, the areas of likely interest to users are clear: parameters that affect production and growth most directly, parameters that affect domestic finance (including government) and the flows of the social accounting system, and parameters that affect trade and finance. We start with production and growth and the key parameters affect labor, capital and multifactor productivity. Parameters exist in the IFs system that allows users to modify any of the component parts of the Cobb Douglas Production function. Parameters affecting labor supply include '''lapoprm,''' '''labfemshrm, '''and '''labretagem'''. The first of these, '''lapoprm''', modifies the '''laborforce''' participation rate, while the second changes the female share of the existing labor force, and the last, '''labretagem,''' changes the number of retired persons who participate in the labor market. Other parameters, discussed in the [[#_Demographic_Module|demographic section]], also impact the size of the labor force. The parameters '''workageentry''' and '''workageretire''', will change when people enter and leave the labor force, thus altering the length of time they are employed and the size of the labor pool.
 +
 +
Users can affect capital accumulation by changing the parameter '''invm''', which alters investment in the economy using a multiplicative approach. Unlike spending multipliers discussed later under Domestic Finance, this multiplier cannot be broken out by destination. It will also affect savings because domestic savings rates are directly tied to investment rates. In addition to altering savings, investment rate changes affect the rate of capital accumulation.
 +
 +
Two brute force multipliers on productivity are available to users. First, '''mfpadd '''allows users to increase productivity growth in an additive manner on a country-by-country basis. Second, the parameter '''mfpleadr''' allows users to set the growth rate of the world’s technological leader, the United States. Since all other country’s productivity is tied to the leader, changes to this parameter model assumptions about global economic growth rates, which will tend to change productivity growth rates across a number of countries. Although both these parameters represent powerful ways to affect GDP and growth, users should note that they do not carry a cost. Like other brute force multipliers, there is no cost accounting system that might limit the impact of changes introduced, so users must be extremely careful to justify any changes made with these parameters.
 +
 +
Users can change any one of the components of multifactor productivity by affecting the drivers of the component. Any of the parameters that impact life expectancy, education levels, or health and education spending, as discussed in the [[#_The_Health_Module|health]] or [[#_Education|education]] modules, will impact MFPHC. Examples include but are not limited to: '''mfpedspn''', '''malnm''', '''ylm''', and '''aginvm.'''
 +
 +
Similarly, anything that affects drivers of social capital will affect MFPSC. These include many of the [[#_Governance_Module|governance]] parameters, such as: '''econfreem''','''goveffectm''','''govcorruptm''', and '''freedomm.'''
 +
 +
Physical capital is primarily impacted by two indices of physical [[#_Infrastructure_2|infrastructure]] development, one for traditional infrastructure, which includes electricity, transportation, and water and sanitation, and a separate index for ICT. Users can affect the elasticity of MFP to these indices using '''mfpinfrindtrad''', and '''mfpinfrindict'''. By changing these parameters users can make the value of MFPPC more or less responsive to the speed of growth in the two areas of infrastructure discussed above. They can also alter the elasticity of MFP to the world energy prices using '''mfpenpri''', which performs a similar function for changing the relationship of MFPPC to energy prices globally. See the discussion of the infrastructure module to see the large number of parameters that affect the specific elements of the two general infrastructure indices.
 +
 +
Knowledge capital will respond to changes in the parameter '''gdsm, '''targeted at changing the amount of government spending directed towards research and development. It will also respond to the level of trade interconnectedness, which the level of protectionism ('''protecm''') can affect—to be discussed again below.
  
 
== <span style="font-size:x-large;">Parameters to Affect Domestic Financial Flows and the Social Accounting System</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Domestic Financial Flows and the Social Accounting System</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''govrevm'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
GOVREV
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
Government revenue multiplier
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''gdsm'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
Government spending by destination sector
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''gdsedm'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
Education spending distribution multiplier
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''govhhtrnpenm'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
GOVHHTRN
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
Government pension spending multiplier
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''firmtaxrm,'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
SAVINGS
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
National tax rates on firms, households, and indirect taxation
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''hhtaxrm (skilled, unskilled)'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
SAVINGS
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
National tax rates on households, broken down by skilled and unskilled
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''indirecttaxrm­­­'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
SAVINGS
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
National tax rates on firms, households, and indirect taxation
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''ginidomr'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
GINIDOM
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
Domestic Gini Index growth rate
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Growth Rate
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''ginidomm'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
GINIDOM
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
Domestic Gini Index multiplier
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:127px;height:22px;" |
 +
'''gdprext'''
 +
 +
| nowrap="nowrap" style="width:81px;height:22px;" |
 +
GDP
 +
 +
| nowrap="nowrap" style="width:316px;height:22px;" |
 +
GDP growth rate
 +
 +
| nowrap="nowrap" style="width:109px;height:22px;" |
 +
Growth Rate
 +
 +
|}
 +
 +
The leverage points within the area of domestic financial flows and the social accounting matrix of greatest interest for most analyses and government revenues and expenditures. The brute force multiplier on government revenues ('''govrevm''') will increase or decrease those and have wide secondary effects as processes play out to adjust revenue raising and expenditure patterns to the new level. On the outflow side, the government spending by destination multiplier ('''gdsm''') will change patterns of government consumption using a multiplier that acts on military, health, education, R&D, infrastructure, other infrastructure, and other (the residual). Education spending can also be modified using '''gdsedm,''' which directly modifies spending on education by level (as discussed in the [[#_Education|education module]]). Unless total government consumption ('''GOVON''') is altered, however, changes in spending patterns by target will create shifts from one category to another rather than changes in the total, because the model will normalize the sum of spending by sector to that total. Similarly, the user can use multipliers on government pension ('''govhhtrnpenm''') &nbsp;spending to change levels in either of those categories, but subject along with direct consumption expenditure to the constraint of total government expenditures ('''GOVEXP'''). Hence, parameters that affect government revenues are very important.
 +
 +
Changes in the tax rates can have profound implications for government capacity, and for this reason IFs contains a number of parameters to alter taxation rates for different actors, in addition to the direct multiplier on government revenues, which will cause the model to endogenously adjust such tax rates. Of these, three stand out. '''Hhtaxrm '''affects household savings rates, '''firmtaxrm''' modifies firm taxation rates, and '''indirecttaxrm '''changes the indirect taxation rate on goods and services. The household taxation rate multiplier is subdivided according to whether households are skilled or unskilled. Users who are interested in scenarios that change domestic income inequality may want to change '''ginidomr''', which alters the ratio of the domestic Gini ('''GINIDOM''') to the initial condition. Domestic Gini ('''GINIDOM''') can also be altered using the parameter '''ginidomm''', which acts as a multiplier on the calculated value of '''GINIDOM''' in the model. Finally, '''gdprext''' offers users a power way to speed up, or slow down, total GDP growth.
  
 
== <span style="font-size:x-large;">Parameters to Affect Trade and International Finance</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Trade and International Finance</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''xshift'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
X, XS
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Export shift as a result of trade promotion
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Additive factor
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''protecm'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
M, MS
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Protectionism in trade, multiplier on import prices
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''termtrm'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
TERMTR
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Terms of trade balance, higher favors global south
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''xfdistockm'''&nbsp;
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
XFDISTOCK
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Inward stocks of FDI multiplier
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''xfdistoutm'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
XFDISTOUT
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Outward stocks FDI multiplier
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''xfdiwgrm'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
XFDI&nbsp;STOCK, XFDIOUT
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
World FDI growth rate multiplier
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''xportfoliom'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
XPORTFOLIO
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Inward portfolio investment multiplier
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''xportstoutm'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
XPORTFOLIO
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Outward portfolio investment stock multiplier
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''aiddon'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
AID
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Aid foreign loan donations as&nbsp;% GDP
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Additive factor
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''aidrecm'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
AID
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Aid receipts as&nbsp;% GDP
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier&nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''aidlpm&nbsp;'''
 +
 +
| nowrap="nowrap" style="width:94px;height:22px;" |
 +
AID
 +
 +
| nowrap="nowrap" style="width:304px;height:22px;" |
 +
Aid foreign loan percentage multiplier
 +
 +
| nowrap="nowrap" style="width:137px;height:22px;" |
 +
Multiplier
 +
 +
|}
 +
 +
Users can alter imports and exports via two major channels. First, they can force a shift towards export promotion using the additive '''xshift''' parameter. Increasing the parameter value to .05 would result in an additional 5% being added to the value of exports for that year and all subsequent years until the dynamics of the model dampen the effect. Protectionism in imports can be modeled by changing the value of '''protecm''', which is a multiplicative parameter that increases the cost of imports and thereby proxies an increase in tariff rates or of non-tariff barriers to trade.
 +
 +
Finally the distribution of the global terms of trade can be impacted by '''termtrm'''. Raising this multiplicative parameter will alter the balance of global trade patterns to favor southern developing countries (colloquially known as the Global South). This means that an increase in this parameter will increase the financial value of the exports from these developing nations, while reducing the relative financial value of exports from developed nations.
 +
 +
Affecting global financial flows is a relatively complex process in the IFs economic system. Multiple channels exist to modify the different major sources of international financial flows. Users can alter foreign direct investment flows using the '''xfdistockm''' parameter, which increases the stocks of FDI within a country and adjusts flows accordingly. Conversely, '''xfdistoutm''' will increase the size of the stock of FDI slated to exit a country. Users may also wish to alter the growth rate for FDI at a global level via the parameter '''xfdiwgrm'''.
 +
 +
Portfolio investment can be modified using a similar set of parameters. '''Xportfoliom '''allows users to increase the stocks of portfolio investment within a country, while '''xportstout''' controls the amount of portfolio investment that a country’s citizens hold abroad.
 +
 +
Aid parameters differ somewhat from those available for FDI and portfolio investment. Users can change the amount of foreign loan donations as a percent of GDP via '''aiddon''', which specifies the portion of donor country GDP given in the form of aid. They may change the amount of aid a country receives using the '''aidrecm''' parameter, which determine the portion of the global aid pool created by donors that any individual country will receive (the total claims on that pool determined by '''aidrecm''' will be normalized to the total size of the pool). Finally, users may alter the portion of aid that comes in the form of loans that accrue interest and must be repaid within a certain time frame using the multiplicative parameter '''aidlpm'''.
  
 
== <span style="font-size:x-large;">Parameters to Affect the Informal Economy</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect the Informal Economy</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="638"
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''labinformshrm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
LABINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal labor force share multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpinformshrm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal GDP share multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpshadowshrm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPSHADOWSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Shadow economy GDP share multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpshadowon'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPSHADOWSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Switch to turn on GDPSHADOWSHR instead of GDPINFORMSHR. Default is 0 (GDPINFORMSHR). 1 turns on GDPSHADOWSHR instead.
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Switch
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''edyrsagm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
EDYRSAG15
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Years of education ages 15 and up multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''firmtaxrm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
FIRMTAX
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Tax rate on firms multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdsm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Government R&D (and education) spending distribution multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''govbusregindm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GOVBUSREGIND
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Government business regulation index multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''govcorruptm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GOVCORRUPT
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Government corruption multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''govhhtrnpenm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GOVHHTRN
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Government pension spending multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''govhhtrnwelm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GOVHHTRN
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Government welfare spending multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''randdexpm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
RANDEXP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Total (public and private) expenditure on research and development multiplier
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''taxinfadjm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
HHTAXR, FIRMTAXR,&nbsp; SSWELTAXR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Multiplier of impact of informal GDP share on tax rates
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''tefinfadjm'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
SAVINGS
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Multiplier of impact of informal GDP share on productivity
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''labinformcoeffbus'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
LABINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal labor share, coefficient of business index
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''labinformcoeffed'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
LABINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal labor share, coefficient of education years
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''labinformcoeffhhtrn'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
LABINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal labor share, coefficient of household transfers
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''labinformcoeffintercept'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
LABINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal labor share, intercept of model
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''labinformcoefftax'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
LABINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal labor share, coefficient of tax rate
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpinformcoeffcorrupt'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal GDP share, coefficient of government corruption
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpinformcoeffintercept'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal GDP share, intercept of model
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpinformcoefflabinf'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal GDP share, coefficient of informal labor share
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpinformcoeffRanD'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPINFORMSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Informal GDP share, coefficient of R&D spending
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpshadowcoeffintercept'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPSHADOWSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Shadow economy GDP share, intercept of model
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpshadowcoefflabinf'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPSHADOWSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Shadow economy GDP share, coefficient of informal labor share
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpshadowcoeffcorrupt'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPSHADOWSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Shadow economy GDP share, coefficient of government corruption
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:139px;height:22px;" |
 +
'''gdpshadowcoeffRanD'''
 +
 +
| nowrap="nowrap" style="width:114px;height:22px;" |
 +
GDPSHADOWSHR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Shadow economy GDP share, coefficient of R&D spending
 +
 +
| nowrap="nowrap" style="width:102px;height:22px;" |
 +
Coefficient
 +
 +
|}
 +
 +
Users can affect the labor informal share of the total labor force directly ('''labinformshrm''').&nbsp; In most cases they will do so indirectly by affecting the driving variables of that share.&nbsp; One of the driving variables is educational attainment of adults, so any parameter affecting that attainment will have a potential impact (see the parameters for education including the prepackaged scenarios).&nbsp; Another is the government business index ('''govbusregindm''').&nbsp; A third is government to household transfers for either pensions or welfare ('''govhhtrnpenm''' and '''govhhtrnwelm''').&nbsp; A fourth is the tax rate on firms ('''firmtaxm''').
 +
 +
The forward linkage from informal labor share to informal GDP share is affected by a multiplier ('''gdpinformshrm''') that can totally turn off that linkage if set to 0.&nbsp; The informal GDP share can be directly affected via '''gdpinformshrm''', or indirectly by affecting its drivers, including informal labor share. Other drivers include: the level of government corruption ('''govcorruptm'''), government spending on research and development (gdsm, R&D) and total (public and private) spending on research and development ('''randdexpm'''). Manipulating '''randdexpm '''itself will increase private sector spending while changing '''gdsm''' will also impact the public portion of '''RANDDEXP'''.
 +
 +
The linkage from informal GDP share to multifactor productivity is controlled by '''tefinfadjm''' and the linkage to tax rates is controlled by '''taxinfadjm.&nbsp; '''Again, a zero value would turn off the linkage.
 +
 +
A set of parameters ('''labinformcoeffintercept , labinformcoeffbus, labinformcoeffed, labinformcoeffhhtrn, labinformcoefftax''') control the calculation of informal labor share from its assorted drivers.
 +
 +
A similar set of parameters ('''gdpinformcoeffintercept''', '''gdpinformcoeffcorrupt''', '''gdpinformcoefflabinf''', '''gdpinformcoeffRandD''') control the calculation of informal GDP from its assorted drivers.
 +
 +
The model includes the shadow economy share of GDP ('''GDPSHADOWSHR''') as an additional measure of informality in the economy. Under the Base Case, '''GDPSHADOWSHR '''is initialized but does not have active forward linkages (the Base Case drives all informality-related forward linkages with GDPINFORMSHR instead). The shadow economy GDP share can be affected directly by changing '''gdpshardowshrm '''or indirectly by changing its drivers, which as with the informal economy share, are: informal labor, government corruption, and spending on R&D. The shadow economy uses a similar set of parameters to the informal economy ('''gdpshadowcoeffintercept''','''gdpshadowcoeffcorrupt''','''gdpshadowcoefflabinf''','''gdpshadowcoeffRandD''') to control the calculation of the shadow economy from its drivers.
 +
 +
Users wanting to drive the forward linkages from informality with the shadow economy instead of the informal economy can do so by changing the switch '''gdpshadowon''' from its default, Base Case setting of 0 (which tells the model to drive the forward linkages with '''GDPINFORMSHR''') to 1 (which tells the model to drive them with '''GDPSHADOWSHR''' instead).
 +
 +
The informal and shadow GDP shares (whichever is activated—see above) use the same multipliers for their linkages to multifactor productivity ('''tefinfadjm''') and tax rate ('''taxinfadjm''')'''.&nbsp;'''
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
A large number of prepackaged scenarios that revolve around economic development and poverty alleviation are available for user access, located under the PPHP Poverty heading in the World Integrated Scenario Sets. The best and worst case Framing Scenarios include changes to the growth in MFP for the world leader, the additive growth rate factor for MFP, TFR, and the Gini index.
 +
 +
More integrated scenario sets are available as well to model the effects of combinations of interventions. These are labeled Combined Dom Intl Interventions (Rev, Rev2). This scenario is built from two different series of interventions: Leverage Testing Intl, and Leverage Testing Domestic, which user can explore if they wish to look more closely at individual interventions from the combined scenario. Users should also use these scenarios and the Combined Dom Intl Interventions (Rev, Rev2) to get a sense of how to scale interventions to different regions of the world or even globally, rather than altering a single country at a time.
 +
 +
Revision 2 models a number of parameter changes including: growth in multifactor productivity ('''mfpadd'''), [[#_The_Health_Module|declines in TFR ('''tfrm'''),]] increases in the female share of the labor force('''labfemshrm''') and [[#_The_Health|world migration]]('''wmigrm'''), increases in investment ('''invm)''', foreign aid, FDI and portfolio investment ('''xfdistockm''' and '''xportfoliom'''), declines in protectionism and resulting increase in exports ('''protecm''' and '''xshift'''), increased government expenditures on education, health, and R&D ('''gdsm'''), greater welfare transfers to unskilled labor('''govhhtrnwelm'''),[[#_Governance_Module|improvements to governance]] (declines in corruption-'''govcorruptm''', increases in effectiveness- '''goveffectm''', and economic freedom- '''econfreem'''), [[#_Infrastructure_2|improved infrastructure]] in roads, ICT, and telephone network density ('''infranetm''', '''infraroadm''','''infratelem'''), and [[#_Energy_Module|increased energy production]] from renewable resources ('''enpm''').
 +
 +
Of these, the economic changes deserve special attention. This scenario includes an improvement in multifactor productivity in the World Bank developing economies to 0.002 over a ten year time horizon, growth in the female share of the labor force to 1.5 time the base case over a 50 year time frame and increases in world migration multiplier to 1.5 over a 15 year time frame. It also increases investment multiplier to between 1.3 and 2 over a 15 to 25 year time frame depending on the region triggering increased capital accumulation and savings.
 +
 +
Government expenditure is also affected. Expenditure to education increases to between 1.2 and 1.8 times the base case implemented over ten years. Expenditure to health and research and development also increase by similar amounts over approximately the same time frame. Government to household transfers increase in different regions by 50 to 100% (multiplier values of 1.5 to 2) over a 20-year time frame. Trade and export promotion increase as well. Levels of protectionism decline by 20% over 20 years (a multiplier value of .8) and the ratio of exports to imports grows by .04.
 +
 +
And finally, FDI and portfolio investment are affected. FDI doubles over 25 years in the World Bank developing economies while portfolio investment increases by 50% over the same time frame. Foreign aid by donor nations increases to .5% of GDP over ten years. There are also increases in the availability of IMF funding that go beyond the scope of this guide, but which may be of interest to specialists in international finance.
 +
 +
With respect to the informal economy, eight scenarios have been developed for Peru. Six of them each manipulate one of the drivers of either informal labor or informal GDP share.&nbsp; In each case an "aggressive but reasonable" value of the driver works to reduce informality.&nbsp; The other two involve more general impacts on information.&nbsp; The first (Comb Lab GDP 1.5 drivers.sce) combines all of the six individual drivers into a single scenario to reduce informality. The second or counterfactual scenario (Informal GDP Share Total Decline Peru 15 years.sce) use a brute force multiplier on the informal GDP share to reduce it to the minimum value allowed (1 percent) between 2016 and 2030.
  
 
= <span style="font-size:xx-large;">Infrastructure Module</span> =
 
= <span style="font-size:xx-large;">Infrastructure Module</span> =
Line 179: Line 2,563:
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
  
 +
The Infrastructure module in the IFs system forecasts infrastructure development and its consequences via a five stage process that is driven primarily by the expected/demanded levels of infrastructure and the funding available to meet these expectations or demands.
 +
 +
The model first estimates the expected/demanded level of infrastructure within a country in relation to key drivers like GDP per capita and population.<sup>4&nbsp;</sup>Second, it translates these expectations into financial requirements, accounting for both new construction and maintenance. Third, the system balances these desired funding levels with the actual resources available for infrastructure construction and maintenance. Fourth, it forecasts the actual attained levels of infrastructure (both in raw physical terms and in terms of population access rates). Fifth, these levels of infrastructure have specific and direct social, economic and environmental impacts related to these attained levels (processes discussed in connection with other modules).
 +
 +
The distinction between expected and demanded levels of infrastructure is a function of the scenario being modeled. In general scenarios, e.g., the Base Case, we use the term expected because the underlying equations are based on historical data reflecting both underlying demands and supply constraints. In scenarios with targets, however, these equations are overridden by equations reflecting the target path, when the expected values lag behind the values defined by the target path. In such instances, therefore, we are more clearly identifying demands for infrastructure, rather than expectations.
 +
 +
Infrastructure variables can be divided into three major types: physical infrastructure, access, and funding.<sup>5&nbsp;</sup>Road density, percentage of road paved, electricity generation capacity, and the amount of land equipped for irrigation all represent key physical infrastructure variables that indicate actual infrastructure stocks within a country. Key access variables, which indicate the degree to which people are able to benefit from existing infrastructure, include: rural population living within 2 kilometers of an all-season road (the road access index); population with access to electricity; reliance on solid fuels for energy; population with access to improved safe water, sanitation, and wastewater treatment; and subscriptions per 100 people to fixed line telephones, mobile phones, and fixed or mobile broadband.
 +
<div><br/>
 +
----
 +
<div id="ftn1">
 +
<sup>4</sup>This calculation treats physical stocks differently from access indicators depending on the type of infrastructure being considered. For roads, expected access is calculated as a function of the physical stocks, while for electricity, water and sanitation, and ICT, physical stocks are calculated on the basis of the expected levels of access. This has implications for the functioning of the parameters discussed below.
 +
</div><div id="ftn2">
 +
<sup>5</sup>IFs also distinguishes between ‘core’ and ‘other’ infrastructure. Core infrastructure refers to those types of infrastructure that we represent explicitly in IFs—roads, electricity generation, improved water and sanitation, and ICT. Other infrastructure refers to those types that we do not represent explicitly—e.g., railroads, ports, airports, and future types of infrastructure yet to be envisioned. Please note that although we do not represent these other forms of infrastructure explicitly, we do estimate spending on them in order to avoid under-representing the total demand for infrastructure. The choice of what to include as core infrastructure reflects the availability of historical data and our determination of what can be modelled within IFs at this time.
 +
</div></div>
 +
=== <span style="font-size:small;">Physical Infrastructure</span> ===
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| style="width: 246px;" | '''Variable Name'''
 +
| style="width: 241px;" | '''Description'''
 +
|-
 +
| style="width: 246px;" colspan="2" | ''Transportation''<br/>
 +
|-
 +
| style="width: 246px;" | '''INFRAROAD*'''<br/>
 +
| style="width: 241px;" | Total road density<br/>
 +
|-
 +
| style="width: 246px;" | '''INFRAROADPAVEDPCNT*'''<br/>
 +
| style="width: 241px;" | Percentage of roads paved<br/>
 +
|-
 +
| style="width: 246px;" colspan="2" | ''Electricity''<br/>
 +
|-
 +
| style="width: 246px;" | '''INFRAELECGENCAP*'''<br/>
 +
| style="width: 241px;" | Electricity generation capacity per capita<br/>
 +
|-
 +
| style="width: 246px;" | '''INFRAELECTRANSLOSS'''<br/>
 +
| style="width: 241px;" | Electricity transmission loss<br/>
 +
|-
 +
| style="width: 246px;" | '''INFRAELECADJFACT'''<br/>
 +
| style="width: 241px;" | Electricity adjustment factor<br/>
 +
|-
 +
| style="width: 246px;" | '''ENELECSHRENDEM'''<br/>
 +
| style="width: 241px;" | Ratio of electricity use to total primary energy use<br/>
 +
|-
 +
| style="width: 246px;" colspan="2" | ''Water and Sanitation''<br/>
 +
|-
 +
| style="width: 246px;" | '''LANDIRAREAEQUIP'''<br/>
 +
| style="width: 241px;" | Area equipped with irrigation<br/>
 +
|-
 +
| style="width: 246px;" colspan="2" | * each variable marked with an asterisk has a companion variable with the suffix DEM, which indicates the expected/demanded level of the variable in the absence of funding constraints<br/>
 +
|}
 +
 +
Key physical Infrastructure variables for transportation are '''INFRAROAD''', and '''INFRAROADPAVEDPCNT'''. The variable '''INFRAROAD''' represents a measure of total road density (paved and unpaved), while the variable '''INFRAROADPAVEDPCNT''' offers a measure of the quality of the transportation infrastructure within a country using paved percentage as a proxy.
 +
 +
Key variables for electricity are the amount of electricity generation capacity within a country, denoted by '''INFRAELECGENCAP''' and expressed in kilowatts per person. Other variables, which represent quality indicators, are '''INFRAELECTRANSLOSS'''—the transmission and distribution loss in percent—and '''INFRAELECADJFACT'''—the capacity factor for electricity production, expressed as a fraction, and '''ENELECSHRENDEM''', the ratio of electricity use to total primary energy use. It is also possible to calculate electricity connections using the results on access to electricity, discussed below, and population.
 +
 +
The only physical infrastructure variable for water and sanitation is the area equipped for irrigation, '''LANDIRAREAEQUIP''', which represents the amount of land in thousands of hectares that is equipped with irrigation. There are no key physical infrastructure variables associated with ICT, only access rates. Users wishing to affect ICT infrastructure should modify access, which, along with population, can be used to calculate actual physical infrastructure levels.
 +
 +
=== <span style="font-size:small;">Access to Infrastructure</span> ===
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="589"
 +
|-
 +
| style="width:151px;" |
 +
'''Variable Name'''
 +
 +
| style="width:192px;" |
 +
'''Sub Categories'''
 +
 +
| style="width:246px;" |
 +
'''Description'''
 +
 +
|-
 +
| style="width:151px;" colspan="3" |
 +
''Transportation''
 +
 +
|-
 +
| style="width:151px;" |
 +
'''INFRAROADRAI*'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Access to rural roads
 +
 +
|-
 +
| style="width:151px;" colspan="3" |
 +
''Electricity''
 +
 +
|-
 +
| style="width:151px;" |
 +
'''INFRAELECACC*'''
 +
 +
| style="width:192px;" |
 +
Rural, urban, total
 +
 +
| style="width:246px;" |
 +
Access to electricity
 +
 +
|-
 +
| style="width:151px;" |
 +
'''ENSOLFUEL'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Solid fuel use
 +
 +
|-
 +
| style="width:151px;" colspan="3" |
 +
''Water and Sanitation''
 +
 +
|-
 +
| style="width:151px;" |
 +
'''WATSAFE*'''
 +
 +
| style="width:192px;" |
 +
None, other improved, piped
 +
 +
| style="width:246px;" |
 +
Access to improved water
 +
 +
|-
 +
| style="width:151px;" |
 +
'''SANITATION*'''
 +
 +
| style="width:192px;" |
 +
Other unimproved, shared, improved
 +
 +
| style="width:246px;" |
 +
Access to improved sanitation
 +
 +
|-
 +
| style="width:151px;" |
 +
'''WATWASTE'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Access to wastewater collection
 +
 +
|-
 +
| style="width:151px;" |
 +
'''WATWASTETREAT*'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Access to wastewater treatment
 +
 +
|-
 +
| style="width:151px;" colspan="3" |
 +
''ICT''
 +
 +
|-
 +
| style="width:151px;" |
 +
'''INFRATELE*'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Fixed telephone lines
 +
 +
|-
 +
| style="width:151px;" |
 +
'''ICTBROAD*'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Fixed broadband subscriptions
 +
 +
|-
 +
| style="width:151px;" |
 +
'''ICTMOBIL*'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Mobile telephone subscriptions
 +
 +
&nbsp;
 +
 +
|-
 +
| style="width:151px;" |
 +
'''ICTBROADMOBIL*'''
 +
 +
| style="width:192px;" |
 +
&nbsp;
 +
 +
| style="width:246px;" |
 +
Mobile broadband subscriptions
 +
 +
|-
 +
| colspan="3" style="width:589px;" |
 +
*each variable marked with an asterisk has a companion variable with the suffix DEM, which indicates the expected/demanded level of the variable in the absence of funding constraints. Please see the note below for a more comprehensive description of the difference<sup>6</sup>
 +
 +
|}
 +
 +
Physical infrastructure may be essential, but unless people have access to it, they cannot benefit. Because of this, access variables are included wherever possible in the IFs system. Transportation contains only one key access variable. This variable, '''INFRAROADRAI''', provides a measure of degree of access people have to the existing road infrastructure. It is defined as the percent of the rural population living within 2km of an all season road.
 +
 +
'''INFRAELECACC''' provides a measure of access to electricity, disaggregated by rural and urban users. Another measure of access to electricity that users may be interested in from a health perspective is '''ENSOLFUEL''' which represents the percentage of the population relying on solid fuels for energy, and a significant factor in both environmental change and certain health conditions.
 +
 +
The two fundamental access variables of interest for water and sanitation are '''WATSAFE''' and '''SANITATION''', which measure the percentage of the population with access to improved water sources and sanitation, respectively, by type of access. Water access is subdivided into unimproved, other improved, and piped. Sanitation access is subdivided into other unimproved, shared, and improved (note that shared access is not considered improved). '''WATWASTE''' and '''WATWASTETREAT''' represent the percentage of the population whose wastewater is collected and treated, respectively.
 +
 +
Four ICT variables represent access to the major components of information and communication technologies. '''INFRATELE''' represents the number of fixed line telephones per 100 people while the other three indicators, '''ICTBROAD''', '''ICTMOBIL''', and '''ICTBROADMOBIL''', provide the number of subscriptions per 100 people for fixed broadband, mobile telephones, and mobile broadband, respectively. The dynamics of the model are structured in such a way that the long term trend is for fixed line telephones to decline, while use of mobile and mobile broadband increases.
 +
 +
----
 +
<div id="ftn1">
 +
<sup>6</sup>The vast majority of Infrastructure variables have both a standard variable, representing the actual achieved level of infrastructure stock or access, and a demand/expectations related variable suffixed by *DEM. The interpretation of the *DEM variables should change subtly depending on the analytical context. When discussing the Base Case or when applying any of the multiplicative parameters, it is more useful to think of the *DEM variables as expected levels; when building scenarios that manipulate the '''*setar/*seyrtar''' parameters, it is more accurate to think of them as demand variables.
 +
</div>
 +
=== <span style="font-size:small;">Infrastructure Funding</span> ===
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="637" style="width:637px;"
 +
|-
 +
| style="width:211px;" |
 +
'''Variable Name'''
 +
 +
| style="width:426px;" |
 +
'''Description'''
 +
 +
|-
 +
| style="width:211px;" |
 +
'''GDS (infrastructure, infraother)'''
 +
 +
| style="width:426px;" |
 +
Government consumption, by category
 +
 +
|-
 +
| style="width:211px;" |
 +
'''INFRAINVESTMAINT'''
 +
 +
| style="width:426px;" |
 +
Total (public plus private) investment for core infrastructure maintenance, by type of infrastructure
 +
 +
|-
 +
| style="width:211px;" |
 +
'''INFRAINVESTMAINTPUB*'''
 +
 +
| style="width:426px;" |
 +
Public investment for core infrastructure maintenance, by type of infrastructure
 +
 +
|-
 +
| style="width:211px;" |
 +
'''INFRAINVESTNEW'''
 +
 +
| style="width:426px;" |
 +
Total (public plus private) investment for construction of new core infrastructure, by type of infrastructure
 +
 +
|-
 +
| style="width:211px;" |
 +
'''INFRAINVESTNEWPUB*'''
 +
 +
| style="width:426px;" |
 +
Public investment for construction of new core infrastructure, by type of infrastructure
 +
 +
|-
 +
| colspan="2" style="width:637px;" |
 +
*the companion variables, '''INFRABUDDEMMNT''' and '''INFRABUDDEMNEW''', are the amounts of public spending originally requested prior to the government budget allocation process
 +
 +
|}
 +
 +
The infrastructure module in IFs incorporates a cost accounting system that ensures that all infrastructure improvements are funded prior to construction, which allows for a gap between the amount of infrastructure that is expected/demanded and the amount that is actually achieved.
 +
 +
As in other modules, GDS provides a good overview of total public spending on infrastructure, but this cannot be broken down by type of infrastructure any more specifically than core infrastructure and other infrastructure. '''INFRAINVESTMAINT''' provides the measure of the total investment for infrastructure maintenance, while '''INFRAINVESTMAINTPUB''' provides infrastructure investment for maintenance provided by public sector funds. '''INFRAINVESTNEW''' provides an indicator of the total spending on construction of new infrastructure, while '''INFRAINVESTNEWPUB''' provides the spending that came from public sources for the purposes of new investment. For the purposes of parameter manipulation, we will discuss the types of infrastructure separately because their dynamics vary widely with regards to how the model calculates physical infrastructure versus access. Absolute and relative target parameters to affect infrastructure access are discussed together because all share similarities in terms of structure and function within the model. Finally, there is some discussion of how to combine the two different types of parameter. These variables are subdivided based on whether the spending is for maintenance purposes or for the building of new infrastructure, and whether funding comes from public or private sources. Private funding is related to public funding in some ratio in all cases but ICT, where private funding has historically been the driver of infrastructure investment.
 +
 +
The two public spending variables, '''INFRAINVESTMAINTPUB''' and '''INFRAINVESTNEWPUB''', have companion variables like many of the physical infrastructure and access variables discussed above. Specifically, the variables '''INFRABUDDEMMNT''' and '''INFRABUDDEMNEW''' represent the amounts of public spending originally requested prior to the government budget allocation process. When there are shortages, '''INFRAINVESTMAINTPUB''' and '''INFRAINVESTNEWPUB''' will be less than '''INFRABUDDEMMNT''' and '''INFRABUDDEMNEW'''.<sup>7</sup>&nbsp;In addition to producing a shortfall of public investment, this will also reduce private spending, except for the case of ICT infrastructure. The treatment of ICT differs because private funding has historically been the driver of investment in ICT infrastructure, whereas the public sector has been the driver of investment in other infrastructure.
 +
<div>
 +
----
 +
<div id="ftn1">
 +
<sup>7</sup>It is also possible for '''INFRAINVESTMAINTPUB''' and '''INFRAINVESTNEWPUB''' to be less than '''INFRABUDDEMMNT''' and '''INFRABUDDEMNEW''' for another reason. This occurs when countries try to increase infrastructure spending more rapidly than is considered feasible. In this case, some of the funds allocated are held back and released over several years. Please refer to the technical documentation on the infrastructure model for more details on this process.
 +
</div></div>
 
== <span style="font-size:x-large;">Parameters to Affect Infrastructure</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Infrastructure</span> ==
 +
 +
Four basic types of parameter are used in this module. They are, multiplicative parameters, technological shift factors, absolute, and relative targets. In general, multiplicative and technological shift factors operate in the same way; likewise, absolute and relative targets have similar functionalities.
 +
 +
There are some general rules that govern the interaction among the different types of parameters. <sup>8</sup>The first rule states that, if multiplicative or tech shift factor parameters are used in conjunction with absolute or relative targets, the multiplicative/technological shift parameters are applied first and then the relative or absolute targets are calculated. The second rule states that absolute and relative targets cannot be applied together. If they are, the model interprets this as an inconsistent application of parameters and will not implement either. The exception to both these rules are ICT fixed and mobile broadband, where the multipliers '''ictbroadm '''(for fixed broadband) and'''ictbroadmobilm '''(for mobile broadband), are applied after the absolute or relative target parameters are applied. Fixed broadband is also the exception to the rule that absolute and relative targets cannot be applied together. Instead they are both calculated within the model and then the larger of the two values is taken.
 +
 +
&nbsp;In analyzing scenarios involving changes to the majority of the parameters described below, users should first check variables with the suffix DEM, where available, because many of the parameters modify expected/demanded levels of access. Assuming that the model has modified the expected/demanded level as desired, the user should next check the actual achieved levels of infrastructure. The reason is that if a parameter change increased the level of demand, but the impact did not raise demand above achieved levels otherwise computed in the model, there would likely be no apparent impact on the achieved level. For instance, users wishing to affect access to sanitation via '''sanitationm '''should first check '''SANITATIONDEM''' to examine the impact on expected/demanded levels, before checking '''SANITATION''' to determine the impact on the actual level fuels of access to sanitation within the population.
 +
<div>
 +
----
 +
<div id="ftn1">
 +
<sup>8</sup>There are some exceptions to the rules laid out below, primarily as pertains to the treatment of fixed broadband within ICT.
 +
</div></div>
 +
=== <span style="font-size:small;">Roads</span> ===
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:154px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:228px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
'''infraroadm'''
 +
 +
| nowrap="nowrap" style="width:154px;height:22px;" |
 +
INFRAROAD
 +
 +
| nowrap="nowrap" style="width:228px;height:22px;" |
 +
Multiplier on road density expected/demanded
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
'''infraroadpavedpcntm'''
 +
 +
| nowrap="nowrap" style="width:154px;height:22px;" |
 +
INFRAROADPAVED
 +
 +
PCNT
 +
 +
| nowrap="nowrap" style="width:228px;height:22px;" |
 +
Multiplier on percentage of roads paved
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
'''Infraroadraitrgtval, Infraroadraitrgtyr'''
 +
 +
| nowrap="nowrap" style="width:154px;height:22px;" |
 +
INFRAROADRAI
 +
 +
| nowrap="nowrap" style="width:228px;height:22px;" |
 +
Target value/years after 2010 for achievement for population percentage living w/in 2km of an all-weather road
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Absolute target
 +
 +
|-
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
'''infraroadraisetar, infraroadraiseyrtar'''
 +
 +
| nowrap="nowrap" style="width:154px;height:22px;" |
 +
INFRAROADRAI
 +
 +
| nowrap="nowrap" style="width:228px;height:22px;" |
 +
Standard error target and years after 2010 for achievement for rural road access index
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" colspan="4" style="width:632px;height:22px;" |
 +
Note: Using both *'''trgtval/trgtyr''' and the *'''setar/*seyrtar''' parameters to affect the same outcome variable will block the impact of both, so users should be careful to only use one or the other of these types at a time, except in the case of fixed broadband, where the larger of the two effects will have an impact.
 +
 +
|}
 +
 +
All the multiplicative parameters that users can use to affect roads affect physical infrastructure variables. This means that changes to '''infraroadm''' directly impact the variable '''INFRAROAD''', which are in turn used to calculate the variable INFRAROADRAI, which is the infrastructure access variable for road infrastructure. Changes to '''infraroadpavedpcntm''' actually alter the percentage of roads in a country which are paved. There are no multiplicative parameters which directly affect road access.
 +
 +
To directly alter '''INFRAROADRAI''' users can use one or the other of the parameter combinations '''infraroadraitrgtval'''/'''infraroadraitrgtyr''' or '''infraroadraisetar'''/'''infraroadraiseyrtar'''. Either set will affect desired levels of access to road infrastructure. In the event that initially computed achieved road access levels do not meet the target value, the model will determine the levels of physical infrastructure stocks required to meet the desired levels of road access and will, subject to financial resource constraints, adjust they physical stocks so as to move the achieved access level to the target.
 +
 +
=== Electricity ===
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''infraelecgencapm'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
INFRAELECGENCAP
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Multiplier on electricity generation capacity
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''Infraelecaccm'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
INFRAELECACC
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Multiplier on electricity access
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''enelecshrendemm'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
INFRAELECDEM
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Multiplier on ratio of electricity use to total primary energy use
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''infraelectranlossm'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
INFRAELECTRANLOSS
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Multiplier on the loss of electricity in transmission and distribution
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''ensolfuelm'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
ENSOLFUEL
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Multiplier on the reliance on solid fuel as a source of energy
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''infraelecacctrgtval/ infraelecacctrgtyr'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
INFRAELECACC
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Target value and years after 2010 for target achievement for population percentage w/ access to electricity
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Absolute target
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''infraelecaccsetar/ infraelecaccseyrtar'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
INFRAELECACC
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Standard error target and years after 2010 for population percentage w/ access to electricity
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''ensolfueltrgtval/ ensolfueltrgtyr'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
ENSOLFUEL
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Target value and years after 2010 for target achievement for percentage of households reliant on solid fuels
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Absolute target
 +
 +
|-
 +
| nowrap="nowrap" style="width:148px;height:22px;" |
 +
'''ensolfuelsetar/ ensolfuelseyrtar'''
 +
 +
| nowrap="nowrap" style="width:147px;height:22px;" |
 +
ENSOLFUEL
 +
 +
| nowrap="nowrap" style="width:235px;height:22px;" |
 +
Standard error target and years after 2010 for target achievement for percentage of households reliant on solid fuels
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" colspan="4" style="width:632px;height:22px;" |
 +
Note: Using both *'''trgtval/trgtyr''' and the *'''setar/*seyrtar''' parameters to affect the same outcome variable will block the impact of both, so users should be careful to only use one or the other of these types at a time, except in the case of fixed broadband, where the larger of the two effects will have an impact.
 +
 +
|}
 +
 +
Electricity in the infrastructure model contains parameters that alter both physical infrastructure and access levels using multiplicative parameters. The parameter '''infraelecgencapm''' directly affects '''INFRAELECGEN''', which represents the physical capacity to generate electricity and is a physical infrastructure variable.
 +
 +
Access to electricity, which is represented by '''INFRAELECACC''', can be directly affected by '''infraelecaccm''', a parameter that directly impacts access to electricity. This parameter is subdivided to allow users to affect urban and rural access separately.
 +
 +
Three other multiplicative parameters are relevant to discussion of electricity access in the infrastructure module. These are '''ensolfuelm''', '''enelecshrendemm,''' and '''infraelectranlossm'''. '''Ensolfuelm''' changes solid fuel reliance as a primary energy source for domestic cooking and heating (ENSOLFUEL), which is also driven by '''INFRAELECACC'''. '''Enelecshrendemm''', changes the ratio of electricity use to total primary energy use (this is a variable of relevance to the [[#_Energy_Module|energy]] module, but is not yet linked to it). It allows users to change how reliant a country is on electricity relative to other sources of final energy use. It indirectly affects the expected/demanded amount of electricity generation capacity as represented by the variable '''INFRAELECACCDEM'''. '''Infraelectranlossm''' affects the loss of electricity during transmission and distribution. It is a parameter that allows users to affect the efficiency and quality of the electricity infrastructure. Like '''enelecshrendemm''', this parameter indirectly affects '''INFRAELECACCDEM'''.
 +
 +
There are also target access parameters to allow users to set targets for desired levels of infrastructure access. These include '''infraelecacctrgtval/infraelecacctrgtyr''', '''infraelecaccsetar/infraelecaccseyrtar''', '''ensolfueltrgtval/ensolfueltrgtyr''', and '''ensolfuelsetar/ensolfuelseyrtar'''. These set absolute and relative targets and target years for desired levels of electricity access and solid fuel use respectively.
 +
 +
=== Water and Sanitation ===
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''landirareaequipm'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
LANDIRAREAEQUIP
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Multiplier on land area equipped for irrigation
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''sanitationm'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
SANITATION
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Multiplier on percentage of people with access to sanitation
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''watsafem'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
WATSAFE
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Multiplier on percentage of people with access to safe water
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''watwastem'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
WATWASTE
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Multiplier on percentage of people connected to wastewater collection system,
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Absolute target
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''watwastetreatm'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
WATWASTETREAT
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Multiplier on percentage of people connected to wastewater treatment
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Absolute target
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''sanitationtrgtval/ sanitationtrgtyr'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
SANITATION
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Target value and years after 2010 for target achievement for population percentage with improved access to improved sanitation, by category of
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''watsafetrgtval/ watsafetrgtyr'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
WATSAFE
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Target value and years after 2010 for target achievement for population percentage without access to improved sources of water
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" style="width:152px;height:22px;" |
 +
'''sanitnoconsetar/ sanitimpconsetar/ sanithhconsetar/ sanitnoconseyrtar'''
 +
 +
| nowrap="nowrap" style="width:133px;height:22px;" |
 +
SANITATION
 +
 +
| nowrap="nowrap" style="width:243px;height:22px;" |
 +
Standard error targets and years after 2010 for target achievement for population percentage with varying access to sanitation
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" colspan="4" style="width:632px;height:22px;" |
 +
Note: Using both *'''trgtval/trgtyr''' and the *'''setar/*seyrtar''' parameters to affect the same outcome variable will block the impact of both, so users should be careful to only use one or the other of these types at a time, except in the case of fixed broadband, where the larger of the two effects will have an impact.
 +
 +
|}
 +
 +
Water and sanitation only contains one parameter which directly affects physical infrastructure levels. This parameter is '''landirareaequipm''', a parameter that affects the land area equipped for irrigation. All other parameters affect access to water, wastewater collection and treatment, and sanitation; the access rate then determines the expected/demanded level of the physical stock. There are no direct multipliers on physical stocks for these types of infrastructure. '''Sanitationm''', '''watsafem''', '''watwastem''', and '''watwastetreatm''' are access parameters that affect access to sanitation, safe water, waste water collection, and waste water treatment, respectively.
 +
 +
Targeting parameters for water and sanitation are:'''sanitationtrgtval/sanitationtrgtyr''', '''watsafetrgtval/watsafetrgtyr''', '''sanitnoconsetar/sanitimpconsetar/sanihhconsetar/sanitnoconseyrtar''', '''watsafenoconsetar/watsafimpconsetart/watsafhhconsetar/watsafenoconseyrtar''', and '''watwastetreatsetar/watwastetreatseyrtar'''. The first two pairs provide absolute target values for sanitation and safe water access. The second two pairs define relative target values and years for reducing the number of people with no access to improved sanitation, safe water, or wastewater treatment.
 +
 +
=== ICT ===
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''infratelem'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
INFRATELE
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Multiplier on fixed-line telephone lines per 100 persons
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''ictbroadm'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
ICTBROAD
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Multiplier on fixed-line broadband subscriptions per 100 persons
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''ictbroadmobilm'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
ICTBROADMOBIL
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Multiplier on mobile broadband subscriptions per 100 persons
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''ictbroadtrgtval, ictbroadtrgtyr'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
ICTBROAD
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Target value and years after 2010 for target achievement for number of subscriptions per 100 persons
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Absolute target
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''ictbroadmobiltrgtval, ictbroadmobiltrgtyr'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
ICTBROADMOBIL
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Target value and years after 2010 for target achievement for number of subscriptions per 100 persons; varies between 0 and 150
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Absolute target
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''ictbroadmobilsetar, ictbroadmobilseyrtar'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
ICTBROADMOBIL
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Standard error target and years after 2010 for target achievement for ICT mobile broadband access
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''ictbroadsetar, ictbroadseyrtar'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
ICTBROAD
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Standard error target and years after 2010 for target achievement for fixed broadband access
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" style="width:149px;height:22px;" |
 +
'''ictmobilsetar, ictmobilseyrtar'''
 +
 +
| nowrap="nowrap" style="width:134px;height:22px;" |
 +
ICTMOBIL
 +
 +
| nowrap="nowrap" style="width:245px;height:22px;" |
 +
Standard error target and years after 2010 for target achievement for mobile phone access
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Relative target
 +
 +
|-
 +
| nowrap="nowrap" colspan="4" style="width:632px;height:22px;" |
 +
Note: Using both *'''trgtval/trgtyr''' and the *'''setar/*seyrtar''' parameters to affect the same outcome variable will block the impact of both, so users should be careful to only use one or the other of these types at a time, except in the case of fixed broadband, where the larger of the two effects will have an impact.
 +
 +
|}
 +
 +
'''Infratelem''', '''ictbroadm''' and '''ictbroadmobilm''' are the only three multiplicative parameters that apply to ICT, and they serve to modify expected or demanded levels of access to telephones, fixed broadband, and mobile broadband respectively. IFs calculates broadband ICT slightly differently than other infrastructure types. Rather than being mutually exclusive, both absolute target values and relative targets (discussed in the paragraph below) apply to the calculation of ICTBROAD. Rather than calculating the value of the parameter adding the multiplier effect and then applying the relevant absolute and relative targets, which is what occurs in the rest of the infrastructure module, the calculation process differs markedly in regards to broadband. In this case, the value of ICTBROAD is calculated twice, once with and once without the application of the target access levels, and the larger of these two values is used by the model for calculations going forward. Then the multiplier '''ictbroadm''' is applied.
 +
 +
'''Ictbroadtrgtval/ictbroadtrgtyr '''and '''ictbroadmobiltrgtval/ictbroadmobiltrgtvr '''set absolute target values and years for fixed and mobile broadband access. '''Ictbroadsetar/ictbroadseyrtar''', '''ictbroadmobilsetar/ictbroadmobilseyrtar''', and '''ictmobilsetar/ictmobilseyrtar '''establish relative target access values for desired broadband access, mobile broadband, and mobile access respectively. Absolute and relative target parameters behave differently when used in combination with one another in regards to fixed broadband than in other infrastructure areas. Instead of canceling one another out, combining'''ictbroadtrgtval '''and '''ictbroadsetar/ictbroadseyrtar''', causes the model to calculate both and then take the larger of the two values and use that.
  
 
== <span style="font-size:x-large;">Parameters to Affect Funding</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Funding</span> ==
  
 +
{| border="1" cellspacing="1" cellpadding="1" width="618" style="width:618px;"
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:150px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''gdsm (infrastructure)'''
 +
 +
| style="width:150px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Gross domestic spending multiplier (infrastructure)
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''infrainvnewpubshrm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Portion of maintenance funding coming from public sources
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''Infrainvmaintpubshrm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Portion of new infrastructure funding coming from public sources
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''hhsizem'''
 +
 +
| style="width:150px;height:22px;" |
 +
GDS
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Household size multiplier
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''infraroadpavedcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of paved roads
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''infraroadunpavedcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of unpaved roads
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''infraelecgencostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of electricity generation
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''infraelecaccruralcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of rural electricity access
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''infraelecaccurbancostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of urban electricity access
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''watsafecostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of safe water
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''watsafeimpcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of improved safe water sources
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''sanitationcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of basic sanitation
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''sanitationimpcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of improved sanitation
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''watwastetreatcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of waste water treatment
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''landircostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of equipping land for irrigation
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''infratelecostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of telephone
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''ictmobilcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of mobile
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''ictbroadcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on unit cost of broadband
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:157px;height:22px;" |
 +
'''ictbroadmobilcostm'''
 +
 +
| style="width:150px;height:22px;" |
 +
INFRAINVESTNEWPUB,
 +
 +
INFRAINVESTMAINTPUB
 +
 +
| nowrap="nowrap" style="width:222px;height:22px;" |
 +
Multiplier on mobile broadband
 +
 +
| nowrap="nowrap" style="width:89px;height:22px;" |
 +
Multiplier
 +
 +
|}
 +
 +
A number of major parameters for affecting the funding process in the infrastructure module exist. The first, more completely discussed in the [[#_The_Economic_Module|economic module]] (in association with the social accounting matrix and government expenditures), is the government spending by destination multiplier '''gdsm'''. By manipulating the infrastructure component of '''gdsm''' users can change the proportion of government spending that goes towards infrastructure thus altering the amount of funding available to achieved the expected or demanded levels of core and other infrastructure; it can also be used to increase or decrease the spending on other infrastructure.&nbsp;
 +
 +
Public spending on infrastructure, both for new infrastructure and maintenance purposes, can be increased using the parameters '''infrainvnewpubshrm''' and '''infrainvmaintpubshrm''' respectively. Each of these parameters can be manipulated separately for different types of infrastructure, and changes to the public share will also affect private sector in a positive relationship (as public funding goes up so does private). Users can change the average household size using the parameter '''hhsizem''', which has an indirect effect on budget by altering the total number of infrastructural connections required for a population. <sup>9</sup>Since budget availability affects attainment of infrastructure, as explained above, this parameter can ultimately change access rates.
 +
 +
Finally, users can also directly alter the unit cost of certain kinds of infrastructure, using one of a series of cost multipliers. The parameters '''infraroadpavedcostm''', and '''infraroadunpavedcostm '''alter the unit cost of paved and unpaved roads respectively. '''Infraelecgencostm''' alters the cost of electricity generation, while '''infraelecaccruralcostm''' and '''infraeleaccurbancostm''' alter the cost of electricity access in rural and urban areas. The parameters '''watsafecostm''' and '''sanitationcostm''', alter the cost of basic water and sanitation access while '''watsafeimpcostm''' and '''sanitationimpcostm''' change the cost of providing improved access to each. '''Landircostm''' changes the unit cost of equipping land for irrigation. '''Infratelecostm''', '''ictmobilcostm''', '''ictbroadcostm''', and '''ictbroadmobilcostm''' all change the cost of different types of ICT.
 +
<div><br/>
 +
----
 +
<div id="ftn1">
 +
<sup>9</sup>Household size parameters are applicable only for those types of infrastructure that are delivered at a household level, e.g., water, sanitation and electricity connections.
 +
</div></div>
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
Because of the complexity of the infrastructure module, and the sheer number of parameters it contains, users may wish to rely more heavily on prepackaged scenarios in order to find effective combinations of multipliers than they do in other IFs modules. One package of scenarios that was developed to model extensions of ICT broadband connectivity and resulting potential gains in efficiency of energy use was developed for the EU and includes modifications to a number of parameters. '''Ictbroadm''' is used to increase broadband penetration rates while '''lke''' (lifetime of capital in energy) increases the efficiency of energy capital investments, making energy production more efficient. This prepackaged scenario set can be accessed from the Scenario Development form of IFs, using the Add Scenario Component menu option. The set can be found within the World Integrated Scenario Sets grouping where it is labeled ICT Scenarios for the EU. See Acknowledging Limits, Betting on Silver Bullets, Broadband Stupidity, and Networked Solutions (Moyer and Hughes, 2012).
 +
 +
Other Prepackaged Scenarios were developed for Chapter 6 of the Infrastructure volume of the ''Patterns of Potential Human Progress ''series (Rothman et al., 2013). This set of scenarios can be located in the PPHP InfrastructureChapter6 grouping of the World Integrated Scenario Sets. It contains a large number of scenarios using infrastructure targets. The scenario TarAllNNoBudgPriority, referred to as Universal Targets Pursuit in the volume, represents a future in which efforts are made to achieve universal access to water and sanitation, electricity, rural roads, and mobile broadband, as well as the elimination of solid fuel use, by 2030; no budget priority is given to infrastructure in this scenario. The scenario TarSENoBudgPriority has the same target date of 2030, but instead of universal access, countries only aim to achieve levels of access that exceed the expected value for their level of development by one standard deviation; again no budget priority is given to infrastructure. The other scenarios, TarAll2050NoBudgPriority, TarElecNoBudgPriority, TarICTNoBudgPriority, TarSE0NoBudgPriority, TarSENoP2050, TarTranNoBudgPriority, and TarWatNoBudgPriority, build on these two scenarios, adjusting the target level, the target date, or the categories of infrastructure with targets.
  
 
= <span style="font-size:xx-large;">Agriculture Module</span> =
 
= <span style="font-size:xx-large;">Agriculture Module</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| '''AGDEM'''<br/>
 +
| Agricultural demand<br/>
 +
|-
 +
| '''FDEM'''<br/>
 +
| Food demand for consumption<br/>
 +
|-
 +
| '''FEDDEM'''<br/>
 +
| Feed demand for livestock<br/>
 +
|-
 +
| '''INDEM'''<br/>
 +
| Industrial demand for food<br/>
 +
|-
 +
| '''AGP'''<br/>
 +
| Agricultural production<br/>
 +
|-
 +
| '''YL'''<br/>
 +
| Yield per hectare of land<br/>
 +
|-
 +
| '''LD'''<br/>
 +
| Land area<br/>
 +
|-
 +
| '''FISH'''<br/>
 +
| Fish production from ocean and mariculture<br/>
 +
|-
 +
| '''AGM'''<br/>
 +
| Agriculture Imports<br/>
 +
|-
 +
| '''AQUACUL'''<br/>
 +
| Million metric tons of fish produced via aquaculture<br/>
 +
|-
 +
| '''AGX'''<br/>
 +
| Agriculture Exports<br/>
 +
|-
 +
| '''LOSS'''<br/>
 +
| Portion of food produced that never reaches markets<br/>
 +
|-
 +
| '''CLPC'''<br/>
 +
| Calories per capita<br/>
 +
|-
 +
| '''MALNCHP'''<br/>
 +
| Percent of children malnourished<br/>
 +
|-
 +
| '''MALNPOPP'''<br/>
 +
| Percent of population malnourished<br/>
 +
|}
 +
 +
The IFs system models agriculture in terms of supply and demand. Consumption, from the demand side, links forward into food availability and nutrition. Both supply and demand dynamics in the agricultural module are closely linked to dynamics in the population and economic modules. For simplicity of representation, IFs models three primary foodstuffs: meat, crops and fish. Stocks (inventories) of food are driven by interaction between production and demand. Stocks affect prices and prices generate movement to supply and demand equilibration, a process that also involves trade.
 +
 +
The agriculture model represents demand for food ('''AGDEM''') as a function of population size, population income, the share of income spent on food, and agricultural prices. A number of other variables also help to illustrate different aspects of the demand side of the equation. The first is food demand '''FDEM''', which represents the amount of food demanded for human consumption. The second is '''FEDDEM''', which represents the amount of food demanded for use as feed by livestock and the third is INDEM which represents the amount of food demanded for use in industrial processes. As a country develops, the balance between these types of demand change; in general, nations with more industry will have a higher level of industrial demand for food, and major meat producing nations will have a higher demand for crops to use as feed.
 +
 +
At a basic level, the supply of food produced within a country ('''AGP''') is a product of the amount of land available for cultivation ('''LD''') and the productivity or yield of that land represented by YL in the IFs model. A number of factors affect yield ('''YL''') including: the level of technology, the amount of labor available for agriculture, the investment of capital into agriculture, and the propensity for yields to saturate at some point even in the face of progressively increased input levels. Investment in agriculture is driven by product prices relative to the additional capital investment required and therefore profit levels. Given the common cycles in agriculture and long lead times in response to investment, however, farmers cannot always make decisions based on current conditions. Investment is also directly responsive to global inventory or stock levels and has an inertial component.
 +
 +
IFs also represents losses to the agricultural production system, and they can have a powerful impact on the availability of food in a country. Not all of the food produced within a country makes it to a market, because of poor infrastructure, such as a lack of refrigeration or other inefficiencies in the production system. In IFs this process is represented via the '''LOSS''' variable. For higher income countries, a larger portion of the loss is actually on the demand or consumption side. Because agricultural products are globally traded commodities, imports and exports of food, discussed in the [[#_The_Economic_Module|economic module]] as well, play an important role in moderating the availability of food within a country. In IFs these are represented by the variables'''AGX''', agricultural exports, and '''AGM''', agricultural imports.
 +
 +
The dynamics of the above processes ultimately affect the ability of people in a country to avoid malnutrition in the form of either obesity or starvation. In many developing nations, meeting daily caloric needs is a struggle and large portions of the population in these countries may be malnourished, leaving them vulnerable to death by preventable diseases. This is especially true of children, for whom the consequences of both short and long term under nutrition are especially severe. To help users keep track of this essential developmental indicator, IFs includes a number of variables that represent the nutritional challenges faced within a country. First, calories per capita ('''CLPC''') provides a rough measure of the total number of calories available to individuals. It provides a rough guide to the kinds of nutritional challenges a nation may face. Populations getting less than approximately 2100 calories a day may experience higher levels of malnutrition, while those that are getting significantly above 3000 calories a day may experience increasing levels of overweight and obesity. However, more important than a crude measure of calorie availability is the impact that chronic malnourishment poses from a development standpoint. To illustrate this burden, IFs includes variables that provide the percentage of the population that is malnourished ('''MALNPOPP'''). Data tend to be better for child undernutrition and we typically have more confidence in and pay more attention to the variable that indicates the percentage of a country’s children (under five) who are malnourished ('''MALNCHP''').
  
 
== <span style="font-size:x-large;">Parameters to Affect Demand</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Demand</span> ==
 +
 +
{| border="2" cellspacing="0" cellpadding="0" width="0" style="width:577px;"
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''clpcm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
AGDEM
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Caloric demand for agricultural production
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''elascd'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
AGDEM
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Elasticity of crop demand to changes in food price
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''elasmd'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
AGDEM
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Elasticity of meat demand to changes in food price
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''elasfd'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
AGDEM
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Elasticity of fish demand to changes in food price
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''indemm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
INDEM
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Industrial demand for crops
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Multiplier
 +
 +
|}
 +
 +
 +
 +
A brute force multiplier on agricultural demand ('''clpcm''') allows direct manipulation of demand and can be used to represent a wide range of scenarios relative to the Base Case, including changing tastes among consumers, changing responses to prices, and changes in incomes or the movement of individuals into the middle class. Changes in consumer desires for certain foods could also be modeled using the parameter '''clpcm '''which also adjusts the portion of calories obtained from meat. It is a multiplicative parameter, so a 0.2 increase in the value of the parameter from its base value of 1.0 would generate a 20% increase in the value of the variable relative to the base case. However, this is a relatively difficult parameter for which to identify reasonable values for such changes. Similarly, changes to '''elascd''' (elasticity of crop demand to changes in price) ,'''elasmd''' (elasticity of meat demand to changes in price) and '''elasfd''' (elasticity of fish demand to changes in price) should be made with caution because they involve changing the responsiveness of demand to changes in price. Such parametric interventions might be appropriate in cases where you want to model the impact of a mass movement to change diet patterns, such as in response to a national campaign for healthy eating or decreased meat consumption due to preference changes. In all three cases the relevant outcome variable is '''AGDEM'''. Also, the parameter '''indemm '''can be used to manipulate levels of industrial demand for crops.
  
 
== <span style="font-size:x-large;">Parameters to Affect Supply (Production)</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Supply (Production)</span> ==
 +
 +
{| border="2" cellspacing="0" cellpadding="0" width="0" style="width:638px;"
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''tgrld'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
AGP
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Target growth rate in cultivated land
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Initial
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''ylm'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
YL
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Crop yield (agricultural production)
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''ylmax'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
YL
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Maximum crop yield
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''envylchgadd'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
ENVYLDCHNG
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Agricultural yield change
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Additive factor&nbsp;
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''slr'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
AGP
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Livestock slaughter rate
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''livhdpro'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
AGP
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Livestock herd productivity gain with grain feeding
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''aquaculm'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
FISH
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Fish production through aquaculture, multiplier
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''aquaculgr'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
AQUACUL
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Growth in the use of aquaculture
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Growth Rate
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''aquaculconv'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
AQUACUL
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
The number years in which aquaculture growth rate&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;converges to 0
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Convergence rate
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''&nbsp;fishcatchm &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
FISH&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Fish production through wild catch
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''aglosstransm'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
LOSS
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Agricultural wastage
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''aglossprodperc'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
LOSS
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Agricultural production loss
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''aglossconsperc'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
LOSS
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Food consumption loss
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''Aginvm'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
YL, IDS (agriculture)
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Investment in agriculture
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''Elagind'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
AGP
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Elasticity of industrial use of crops with price
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''elinag1'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
IDS (agriculture)
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Elasticity of investment in agriculture to profit levels
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''elinag2'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
IDS (agriculture)
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Elasticity of investment in agriculture to changes in profit level
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''&nbsp;ldcropm &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;'''
 +
 +
| nowrap="nowrap" style="width:97px;height:22px;" |
 +
LD(crop land)
 +
 +
| nowrap="nowrap" style="width:343px;height:22px;" |
 +
Share of crop land in total land
 +
 +
| nowrap="nowrap" style="width:100px;height:22px;" |
 +
Multiplier
 +
 +
|}
 +
 +
 +
 +
There are two primary channels to think about changing the supply of agricultural production. The first is via increases in the amount of resources devoted to agricultural production such as by increasing the amount of land under cultivation. This can be done via the '''tgrld '''parameter. The earth’s arable land is relatively finite, however, and land under cultivation has not been a major driver of increased production for decades in most countries.
 +
 +
A more appropriate channel to think about is technological change that increases the efficiency of food production systems thereby increasing yield. The yield multiplier ('''ylm'''), which affects the yield of land being used for crop production, could be used, for example, to model the effect of a second green revolution. This parameter does not carry an intrinsic cost to use, making it both a powerful way of affecting the agricultural model, but also making it essential to justify the reason for any yield change. For example, this multiplier could be effective in representing the impact of improvements to climate or technology that increase the output of a particular unit of land in the absence of increased labor or investment. Users can also alter the maximum yield that can be harvested from a plot of land using '''ylmax''', an exogenous parameter which sets a maximum level for yield. Changes to this parameter can model extreme changes to land yield, such as a second green revolution. Moreover, the parameter '''ldcropm '''can be used to change the share of crop land in the total land.
 +
 +
Another parameter that can be used to affect yield is '''envylchgadd''', also discussed in the [[#_Environment_Module|environmental module]]. It can be used to model the effect global warming is having on agricultural yields. Modifying this parameter allows users to test different assumptions about the effect that increased CO<sub>2 </sub>and increased temperatures will have on crop yield.
 +
 +
Changes in the patterns of production of meat and fish can be modeled in the IFs system through a number of parameters. Meat production can be affected by changing the rate at which livestock are slaughtered via '''slr'''. This parameter could be altered to model the transition from subsistence to factory farming, and the increasing use of modern slaughterhouses in developing countries. The parameter '''livhdpro''' is also useful for modeling the impact of increased meat production from livestock as a result of the transition to grain feeding, which allows producers to extract more meat from each animal they own.
 +
 +
Similarly the parameters '''aquaculm '''and '''aquaculgr''' can be altered to model the impact of increasing reliance on aquaculture for fish production because of technological improvements to this method of food production. The variable of interest will be FISH. The parameter '''aquaculm''' works like other multiplicative parameters, while the parameter '''aquaculgr''' alters the rate at which the use of aquaculture increases. The first parameter targets the actual amount of aquaculture a country uses, and is easiest to manipulate for the average user. The second, '''aquaculgr''', is set within the model and alters the rate at which countries begin to develop aquaculture resources. Finally the parameter '''aquaculconv''' can be used to determine the number years in which aquaculture growth rate converges to 0.
 +
 +
&nbsp;Other parameters that affect the level of fish production include '''fishcatchm''' and '''aquaculm. '''The first, modifies the amount of fish catch while the second''', '''changes the rate of catch from aquaculture.
 +
 +
Changing the loss rate of agricultural output to waste (rotting in fields, lost/spoiled during transportation, or not used in the home) via the '''Aglosstransm''' parameter is a powerful way to model the impact of changing agricultural distribution loss of food. It is a multiplicative parameter. Moreover production losses and consumption losses can be manipulated through the parameters, '''aglossprodperc''' and '''aglossconsperc''' which allow the user to specify the rates of production losses and consumption losses respectively. &nbsp;
 +
 +
Technological improvement is not the only pathway through which yield (YL) may be affected within IFs. Financial pathways can change the amount of capital being invested in agriculture, resulting in higher yields. For example, parameter '''aginvm''', directly changes the investment in agriculture. This parameter can be used to model the effects of investment in improved agricultural technologies like genetically modified crops or new methods of aquaculture. Because of the financial accounting systems within IFs, changes in agricultural investment will affect investment in other sectors. '''Elagind''' is a parameter that may be useful those who wish to adjust the percentage of crop production that is diverted for industrial uses such as ethanol, or beer.
  
 
== <span style="font-size:x-large;">Parameters to Affect Nutrition</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Nutrition</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="0" style="width:623px;"
 +
|-
 +
| nowrap="nowrap" style="width:111px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:111px;height:22px;" |
 +
'''malnelimstartyr'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
MALNPOP
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Undernourishment elimination start year
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Standard error target
 +
 +
|-
 +
| nowrap="nowrap" style="width:111px;height:22px;" |
 +
'''malnelimtargetyr'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
MALNPOP
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Undernourishment elimination target year
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Standard error target
 +
 +
|-
 +
| nowrap="nowrap" style="width:111px;height:22px;" |
 +
'''malelimprecisesw'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
MALNPOP&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Undernourishment elimination
 +
 +
| nowrap="nowrap" style="width:104px;height:22px;" |
 +
Switch
 +
 +
|}
 +
 +
 +
 +
Finally, model users may wish to use parameters to explore the health and economic impacts of different levels of nutritional deficiencies. In the health model, nutritional deficiency manifests itself in terms of mortality and morbidity related to communicable diseases. It can have especially large effects on children, who if undernourished for a significant period of their childhood, suffer developmental and cognitive delays that can impact their future productivity. The most important of these parameters are '''malnelimstartyr '''and '''malnelimtargetyr, '''which are standard error target parameters that affects the number of undernourished people in a country as a percent of the population. These parameters could also be used to represent the impact of school based nutrition programs or other targeted feeding programs. The parameter '''malelimprecisesw''' is a switch that when activated calculates the required number of calories to eliminate hunger for the most undernourished part of the population.
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
One prepackaged scenario that makes significant improvements to agricultural yield in the developing world was developed as a policy brief, and models the impact of a green revolution in Africa. The scenario combines multipliers and other parameters, including '''ylm, ylmax, aginvm, '''and'''tgrld'''. It was designed to model the impact of a green revolution type of event occurring in the developing world and involving improved yield of crops through improvements in cultivation techniques and new technologies. Users will find it saved under the African Policy Briefs section of the World Integrated Scenario Sets, under the heading Green Revolution, which is also the title of the scenario. It increases agricultural yields by 76 percent over a 32-year period (increasing the parameter '''ylm''' to 1.76). It also increases the maximum yield in all African countries, as well as modeling 20 percent growth in agricultural investment and an initial target for growth in cultivated land of 8 percent.
 +
 +
Another prepackaged scenario that makes significant changes to agriculture is the Politics of Belly scenario developed for the African Futures 2050 project. This scenario is located in the Afp 2050 folder in the World Integrated Scenario Sets heading. This posits a much less positive outlook for African agriculture, simulating a 20 percent decline in yields that could represent the negative impact of climate change, much more than offsetting the mitigating effect that plant responsiveness to C02 increases might have on yields.
  
 
= <span style="font-size:xx-large;">Energy Module</span> =
 
= <span style="font-size:xx-large;">Energy Module</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="366" style="width:366px;"
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:24px;" |
 +
'''Variable Name'''
 +
 +
| nowrap="nowrap" style="width:231px;height:24px;" |
 +
'''Description'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENDEM'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Energy demand
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''WEP'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
World energy prices
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''WEPBYEAR'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Translates global energy prices into dollars per barrel of oil equivalent
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENPRI'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Energy prices
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENST'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Energy stock
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENRGDP'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Ratio of energy demand to GDP
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENP'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Energy production
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''WENP'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Global energy production
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''KS'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Capital stock
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''IDS'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Investment in energy
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''QE'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Capital output ratio
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''RESER'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Accessible energy reserves
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''RESOR'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Ultimate conventional energy resources
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''RESORUNCON'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Ultimate unconventional energy resources
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENM'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Energy imports
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENX'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Energy exports
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''ENSHO'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Energy shortage
 +
 +
|-
 +
| nowrap="nowrap" style="width:135px;height:23px;" |
 +
'''VADD'''
 +
 +
| nowrap="nowrap" style="width:231px;height:23px;" |
 +
Value added, energy
 +
 +
|}
 +
 +
Rapid development of unconventional oil and gas production—particularly from shale sources—and high rates of growth in energy from renewable sources make the future of energy highly uncertain. Several research organizations have forecasting projects that provide long-term analysis. In the United States, the Department of Energy's Energy information Agency produces a yearly report titled, ''International Energy Outlook; ''the International Energy Agency produces similar forecasts for the world as a whole, as well as for many individual countries, in its annual ''World Energy Outlook.'' The IFs energy module contributes to this existing body of research on international energy futures. A selection of variables and parameters allows users to explore alternative patterns of energy demand, production, resource discovery and technological developments.
 +
 +
The structure of the IFs energy model is similar to that of the agriculture module, [[#_Agriculture_Module|discussed in the preceding section]]. Both systems are driven by demand and supply dynamics within an equilibrium-seeking system that involves prices, trade, and investment. In both cases, the model translates forecasts of the physical system into value terms for the economic module and interaction with other sectors. The size of the economy and population shape demand, which IFs represents in the aggregate (not within sub-categories such as transportation, residential/commercial and industrial). The supply side differentiates production dynamics for oil, gas, coal, hydroelectric, nuclear, and other renewable energy and separately represents conventional and unconventional energy resources, such as shale deposits.
 +
 +
Beginning our elaboration with the demand side first, IFs derives each country’s energy demand from the overall size of the economy, the level of development as measured by GDP per capita, and world energy prices. The variable '''ENDEM,''' displayed as a default in billion barrels of oil equivalent (BBOE), captures demand from all sectors, and for all types of energy. The energy intensity of an economy—the usage of energy per unit of GDP ('''ENRGDP''')—is a very important measure, influenced by the development level, the advance of technology, and energy prices. Reductions in that, or improvements of efficiency over time, have been occurring in most countries. Users may explore several different formulations of energy price, which is a key factor used to derive demand and affect the energy intensity. '''WEP''' is a single composite measure of the global price of energy, expressed as an index with a base of 100 in the first model year ('''WEPBYEAR''' translates global energy prices into dollars per barrel of oil equivalent). Like '''WEP''', '''ENPRI''' displays country-level energy price as an index, base 100. Each country’s price is a function of global capital costs of energy production and a regional markup factor that reflects the level of country-specific energy stocks ('''ENST''').
 +
 +
Key indicators for the other side of the energy system, the supply side, include production, capital/output ratio and available natural resources. Production is measured in the variable '''ENP'''; production can be displayed as a total, or disaggregated through the energy type dimension to produce individual displays of oil, natural gas, coal, hydroelectric power, nuclear, and other renewables. '''WENP '''is energy production for the world as a whole, disaggregated by production type. For each country, energy production is partially determined by relationships around capital. The portion of the initial capital stock dedicated to the energy sector, '''KS''', limits the scale of possible production. And the capital-output ratio, '''QE''', translates capital stock ('''KS''') into production level. Capital stock itself is augmented over time by investment,'''IDS''', dependent on the profitability of investment in energy.
 +
 +
The concept of capital-output ratio ('''QE''') warrants clarification because it is important to the energy module's equilibrating dynamics. When production requires relatively little invested capital to produce a unit of output, the capital-output ratio is low. Conversely, a high ratio would mean a large amount of capital is required to produce a unit of output. All things equal, the lower the capital-output ratio, the greater the opportunity for profits. Thus, in the model, a low '''QE '''will generally trigger an increase in production.
 +
 +
Available natural resources are the final factor constraining supply. Levels of proven reserves, '''RESER''', drive the price structure component of production—by affecting '''QE'''. Proven reserves are in turn bounded by the availability of ultimately recoverable resources, displayed in the variable '''RESOR '''for conventional resources, and the variable'''RESORUNCON '''for unconventional resources, both of which must be discovered ('''RD''') to become reserves. As we shall see in the discussion of parameters, '''QE''' is affected not just by resource constraints, but also by the advance of technology.
 +
 +
A set of trade variables measures countries’ external reliance on energy. While high levels of energy exports can enrich public finances through taxation, an overreliance on either energy imports or exports increases vulnerability to external price shocks. Energy imports and exports are measured in billion barrels of oil equivalent by '''ENM '''and '''ENX''' and represent aggregate trade in energy without distinguishing energy types. A more direct indication of vulnerability to shock is located in Flexible Display, under the heading Energy Imports as a Percent of Total Demand.
 +
 +
Disruptive price swings are inherent to any commodity market. In energy markets they can result from either political disruption in energy producers such as Iraq or from collusion among producers—evidenced by the cartel behavior of The Organization of Petroleum Exporting Countries (OPEC). As economists point out, prices can theoretically always rise or fall to balance demand and supply—to clear the market. But as history has shown, severe energy shocks, sometimes in environments where leaderships do not allow prices to fully adjust, can result in actual physical shortages ('''ENSHO'''). In normal years the level of energy stocks in a country is visible through the variable '''ENST'''.
 +
 +
A final set of indicators, measured not in physical but in monetary value terms, represents the overlap between the energy and economic modules in IFs. The variable '''VADD '''displays the total value added that is contributed to a country's GDP by various sectors, including energy; this gives a quick look at how much a country relies on energy production as a source of wealth. Investment ('''IDS''') and capital stock ('''KS''') present additional measures of the size of the energy sector in absolute terms and relative to other sectors.
  
 
== <span style="font-size:x-large;">Parameters to Affect Demand</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Demand</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="578" style="width:578px;"
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''endemm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENDEM
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Energy demand
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''elasde'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENP, WEP
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Price elasticity of energy demand
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:22px;" |
 +
'''carbtax'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENP
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Carbon tax
 +
 +
| nowrap="nowrap" style="width:91px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:79px;height:24px;" |
 +
'''enrgdpgr'''
 +
 +
| nowrap="nowrap" style="width:103px;height:24px;" |
 +
ENP, QE
 +
 +
| nowrap="nowrap" style="width:305px;height:24px;" |
 +
Growth in energy efficiency
 +
 +
| nowrap="nowrap" style="width:91px;height:24px;" |
 +
Rate of change
 +
 +
|}
 +
 +
The demand side of the energy system features several leverage points that can be used to create alternative scenarios. The multiplier '''endemm''' directly manipulates aggregate energy demand in a country or region relative to its underlying calculation from economic size and other driving variables. A second key demand-side parameter, '''enrgdpgr''', allows the user to change the default rate of change in energy intensity (the inverse of energy efficiency). Turning from the more brute-force parametric intervention approaches to a more policy specific one, country-level energy prices and therefore energy demand can also be manipulated directly through the additive parameter '''carbtax'''. As the name implies, this parameter simulates the effects of a tax on carbon emissions—even employed at a reasonable level, a carbon tax can have substantial impacts on energy demand.
 +
 +
In the energy analysis community there is always some uncertainty and debate concerning the strength of the relationship between energy price and demand. The parameter '''elasde''' allows users to change the long-term price elasticity of demand. This elasticity is negative in the model, corresponding to traditional formulations of supply and demand—as prices rise demand for energy falls. Users building scenarios may wish to experiment with different values of '''elasde''', while bearing in mind the possibility that long-term and short-term elasticities may differ.
 +
 +
&nbsp;These demand-side leverage points offer a rich area for experimentation. Work by groups such as the International Energy Agency (IEA) and the International Panel on Climate Change (IPCC), have simulated several alternative future forecasts for energy efficiency development.
  
 
== <span style="font-size:x-large;">Parameters to Affect Supply</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Supply</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="602" style="width:602px;"
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''enpm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENP
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Production multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''eprodr'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENP
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Production growth rate
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Growth rate
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''resorm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
RESOR&nbsp;
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Conventional resource multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''resorunconm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
RESORUNCON
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Unconventional resource multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''rdm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
RESER
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Discovery multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''etechadv'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
QE
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Rate of technical advance in energy
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''etechadvuncon'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
QE
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Rate of technical advance in unconventional energy
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''qem'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
QE
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Capital output multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''eninvm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENIV
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Energy investment
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''enprix'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENPRI
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Regional energy price
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:98px;height:22px;" |
 +
'''enml, enxl'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENM, ENX
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Limits on energy imports and exports
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Exogenous specification
 +
 +
|}
 +
 +
Turning to the supply side of the IFs energy module, two parameters in the model directly alter the relative production of oil, gas, coal, hydroelectric, nuclear, and other renewable energy. '''Enpm''', a multiplier, scales up or down existing production of a specified energy type; '''eprodr''', a growth rate parameter, forces a specified yearly percentage increase in production on the desired energy type. Both types of direct production modification can be used to trace the effects that a shift in energy production profile may have on life in a country, region, or the entire global community. For some observers, renewables represent the most important source of uncertainty surrounding the character global energy production. The IFs Base Case forecast assumes that renewable energy will grow rapidly in importance in the decades to come – see '''WENP''' across all energy types for a clear depiction. What if the model’s baseline assumptions are too optimistic, or too pessimistic? Scenarios created with '''enpm '''and'''eprodr''' can explore variations on the Base Case renewable energy story.
 +
 +
Moving below the direct interventions on production to parameters that affect the drivers of that production, both conventional and unconventional deposits of oil, gas and coal resources offer possible points of leverage for supply-side energy scenarios. As mentioned above, IFs divides raw materials used in energy production into resources and reserves. Scenario interventions are most effective when they include simultaneous changes to the reserves that are very closely tied to production, and to the more distil element of total resources (resources only become reserves when they are discovered and deemed to be economically exploitable with current technology and prices). An increase to the '''resorm '''or'''resorunconm '''parameters will expand the amount of materials that can potentially transition to reserves and become economically viable. As a second step, users can speed up this transition by manipulating '''rdm''', a parameter that represents the rate of geologic discovery (or improved economic exploitability) in a country. An increase in the stock of fossil fuel reserves creates the possibility that they will be produced and that they will have forward impacts on energy price ('''ENPRI''') and '''GDP''' of energy producing countries.
 +
 +
A key source of uncertainty around the future of energy supply concerns production costs. Technological progress could dramatically increase the amount of energy output possible at current levels of investment. The parameters '''etechadv''' and '''etechadvuncon''' directly control the rate of technological advance and cost reduction by energy type, whether based on fossil fuels or renewable energy. For fossil-based energy in particular, several other parameters enable users to explore the consequences of various energy production cost structures. '''Qem''', a capital-output multiplier, directly scales up—or down—the capital cost per output unit of each energy type at the country level.
 +
 +
Government policies could additionally affect the future of energy production. Actions such as tax increases or direct subsidies can be simulated using '''eninvm''', an investment multiplier. The parameter either increases or decreases overall investment in energy—the model still controls which energy-type is affected, based on price signals. Remember that the equilibrating mechanisms of the model will respond to any change in investment patterns. For example, an increase in investment flowing to oil, would increase production, eventually reducing oil prices, and leading to a subsequent decrease in investment. Remember also that the accounting mechanisms of the model will assure that any additional investment in energy will come from somewhere, such as investment in other sectors, other government expenditures, or household consumption.
 +
 +
Government decisions can also affect energy prices quickly, through intentional price shocks similar to those initiated by OPEC in the 1970s. The '''enprix''' parameter can simulate a concerted effort on the part of energy exporters to fix prices; '''enprix '''exogenously sets the type-specific energy price—'''ENPRI'''— for a region. As in real life, any price fixing scenario will have wide-ranging, and potentially perverse economic consequences. Two additional parameters exist that can simulate short-term supply disruptions via trade restrictions: '''enml '''exogenously imposes a limit to energy imports and '''enxl''' imposes a limit to energy exports.
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
Currently, none of the prepackaged scenario files demonstrate the use of parameters linked to the energy module.
  
 
= <span style="font-size:xx-large;">Environment Module</span> =
 
= <span style="font-size:xx-large;">Environment Module</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| '''CO2PPM'''<br/>
 +
| CO2 parts per million<br/>
 +
|-
 +
| '''CO2PER'''<br/>
 +
| Percentage increase in atmospheric CO2<br/>
 +
|-
 +
| '''CARANN'''<br/>
 +
| Annual carbon emissions from fossil fuels<br/>
 +
|-
 +
| '''CARFOROTH'''<br/>
 +
| Annual net carbon release from forests<br/>
 +
|-
 +
| '''WTEMP'''<br/>
 +
| Average annual world temperature<br/>
 +
|-
 +
| '''ENVTPCHG'''<br/>
 +
| Annual average temperature change from 1990<br/>
 +
|-
 +
| '''ENVPRCHG'''<br/>
 +
| Annual average precipitation change from 1990<br/>
 +
|-
 +
| '''WFORST'''<br/>
 +
| World forest area<br/>
 +
|-
 +
| '''LD'''<br/>
 +
| Land area by type<br/>
 +
|-
 +
| '''WATUSE'''
 +
| Annual water usage<br/>
 +
|-
 +
| '''WATUSEPC'''<br/>
 +
| Annual water usage per capita<br/>
 +
|-
 +
| '''ENVPM2PT5'''<br/>
 +
| PM2.5 levels in residential areas<br/>
 +
|-
 +
| '''ENSOLFUEL'''<br/>
 +
| Solid fuel use<br/>
 +
|}
 +
 +
As the global population has grown, and more and more countries have industrialized, sustainable development has come to occupy a permanent place on national, regional and global agendas. Growing concern for the environment was brought to the fore at the 1992 UN Conference on the Environment in Rio de Janiero. More than 2 decades have passed since the Rio conference, and the global community’s dedication to environmental concerns (if not always to action) has remained strong. In 2012 a follow up conference was held in Rio—the United Nation’s Conference on Sustainable Development, or Rio + 20—at which leaders discussed strategies to end poverty, address environmental destruction and build a bridge to the future. Other forward-looking environmental initiatives include the United Nations Environment Program’s (UNEP) Global Environmental Outlook Series. Since the first entry in the series, published in 1997, the UNEP has followed up with four additional reports (the International Futures model contributed to the most recent report). Despite the creation of dozens of internationally agreed upon goals, 2012’s ''Global Environmental Outlook 5'' warned that the world remains on an unsustainable path. Around the world, forestland is decreasing, centuries-old glaciers are retreating, aquifers are being depleted and the amount of atmospheric carbon dioxide is on the rise. Not all environmental trends are negative, however. Developed countries have made progress on urban air pollution. Developing countries have experienced improved drinking water quality and safe sanitation access. And globally, the volume of CFCs damaging the ozone layer has dropped dramatically over the course of recent decades.
 +
 +
Environmental issues have potential or actual connections to all of the modules in IFs. For instance, processes associated with energy, agriculture, infrastructure, and the broader economy directly impact the earth’s forests, water supply, and atmosphere, as does governance more indirectly. The environmental module elaborates a subset of these potential connections in four specific areas: the global carbon cycle, land use (notably forest area), water use (agricultural), and air quality (urban and indoor).
 +
 +
The numerous ways in which human actions influence the environment are evident throughout the carbon cycle. Carbon is continuously moving within and across the boundaries of the Earth’s atmosphere, hydrosphere and biosphere. In systems dynamics terminology, the elements in the cycle are known as stocks and flows. Put simply, stocks are long-term repositories of carbon such as the world's fossil fuels, biomass and oceans, and flows are movements from one stock to another. This stock-flow dichotomy serves as a useful heuristic for users who are interested in creating scenarios in the IFs environment model more generally, but especially with respect to carbon. Interventions can target carbon stocks through processes that affect flows, such as energy production and reforestation. Key carbon stock indicators are '''CO2PPM''', the level of atmospheric carbon dioxide measured in parts per million, and '''CO2PER''', atmospheric carbon dioxide, measured as a percent relative to pre-industrial levels. On the flow side, key indicators available in the model include '''CARANN''', the annual flow of carbon emissions from fossil fuel use, and '''CARFOROTH''', global net carbon released annually from forests and other sources (discussed below). As we shall see, the model also allows parametric control of the flow of carbon from the atmospheric stock to that dissolved in the oceans, another stock.
 +
 +
The atmospheric carbon stocks have important forward linkages. One of the most important, temperature change, can be tracked via '''WTEMP''', the global average annual temperature in degrees centigrade. A derivative temperature variable but at the country level, '''ENVTPCHG''', captures the average annual temperature change from the year 1990, and '''ENVPRCHG''' similarly tracks the change in precipitation. These have further forward linkages to agriculture.
 +
 +
Several variables in the model measure the configuration of the world’s land area. Two variables capture trends in forest coverage: '''WFORST '''is an aggregate measure of the world’s land area covered by forest, reported in millions of hectares; and the land variable '''LD '''is disaggregated by land type, enabling country- or region-level displays of the following categories: crop, grazing, forest, urban and other. (See the [[#_Agriculture_Module|agricultural module]] for a complete discussion of land use variables and parameters). Land use links back to the carbon representation because trees and other plants making up the world’s forests absorb carbon dioxide through photosynthesis and their carbon content is still another important global stock. As indicated above, change in forest area, such as clearing of land for agricultural use, generates one of the carbon flow terms of the model.
 +
 +
The environment submodule includes water indicators. The annual use of freshwater resources is reported in cubic centimeters via '''WATUSE, '''tied in IFs to the major source of water use, agricultural production. Users can additionally choose to explore water use per capita, expressed in thousands of cubic meters, via the variable '''WATUSEPC'''. Currently, the model’s treatment of water does not feature the stock and flow elements seen in the carbon cycle. Although '''WATUSE '''is a flow of water used each year, no corresponding variable captures the total stock of water—say in nonrenewable (or at least very slowly recharging) fossil water aquifers. This is a shortcoming that we hope to address in the near future. However, a parameter, '''watres '''(see the discussion below), does provide an estimate of the level of annually renewable water resources in countries and regions. The ratio of use to renewable resources serves as a measure of relative water stress. With respect to forward linkages, water stress is one of the drivers of state fragility (see the [[#_Governance_Module|government module]]).
 +
 +
A final set of environmental indicators pertains to air pollution. The amount of solid matter suspended in the Earth’s atmosphere serves as a measure of relative air quality; high levels of atmospheric particulate matter (PM) can have adverse effects on human health. Depending on the data source, PM concentration readings may include particles that are either 10 or 2.5 micrometers in diameter. In the model, the variable'''ENVPM2PT5''' captures levels of fine particulate matter, PM2.5, found in residential areas (although our current data source is actually for 10 micrometer particulates). The prevalence of solid fuel use is a second indicator of air pollution. The variable '''ENSOLFUEL''' captures the percent of a population relying on solid fuel as the primary source of domestic energy. Burning solid fuel, such as wood, peat, coal, dung, and certain grains, produces a toxic environment indoors (see the [[#_The_Social_Accounting|infrastructure module]]).
 +
 +
Alternative scenarios, built in any IFs module, are likely to have bearing on environmental indicators. Users exploring the consequences of scenario interventions in economics, energy or agriculture are likely to see the greatest environmental effects. Interventions in other modules will still affect the environment, though through weaker, more distal, drivers. The environmental sub-module, however, allows users to directly explore the effects of environmental change. Environmental parameters can be categorized as those that affect carbon stocks and flows, land use, water resources, and air quality.
  
 
== <span style="font-size:x-large;">Parameters&nbsp;Affecting Carbon</span> ==
 
== <span style="font-size:x-large;">Parameters&nbsp;Affecting Carbon</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''enpm'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
ENP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Energy production by type
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''endemm'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
ENDEM, WEP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Energy demand multiplier
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''carbtax'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
ENP, CARANN
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Carbon tax
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Exogenous Specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''qem'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
ENP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Capital-output ratio multiplier
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''resorm'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
RESOR
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Resource multiplier
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''enrgdpgr'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
ENP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Energy efficiency
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Growth rate
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''carfuel1'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
CARANN
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Carbon generated by gas
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''carfuel2'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
CARANN
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Carbon generated by natural gas
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''carfuel3'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
CARANN
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Carbon generated by coal
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''envclimsens'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
CO2PPM, WTEMP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Time sensitivity of global temperature to carbon dioxide
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Limit
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''carabr'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
CO2PPM, WTEMP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Carbon absorbed by oceans
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''carabrchng'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
CO2PPM, WTEMP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
annual change in this absorption rate of carbon by oceans
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Coefficient
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''envco2fert'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
AGP
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Crop sensitivity to environmental change
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Elasticity
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''envylchgadd'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
ENVYLDCHNG
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Agricultural yield change
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Additive factor
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''envylchgm'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
ENVYLDCHNG
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Agricultural yield change
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplicative
 +
 +
|}
 +
 +
There is no way to directly target atmospheric carbon stocks in the model. Instead, points of intervention involve flows, the most important of which is the burning of fossil fuels and therefore the rate of flow of carbon from its stock in those fuels to the stock in the atmosphere With respect to fossil fuel use, there are leverage points on both the production and consumption side—see the [[#_Energy_1|energy model]] discussion. '''Enpm''', the energy production multiplier, will alter the flow of carbon into the atmosphere and can serve as a powerful leverage point in energy-driven environmental scenarios. Users can alter the mix of energy types produced within a country, thereby reducing or increasing the use of fossil fuels, and trace the environmental effects.
 +
 +
On the demand side, a reduction in '''endemm''', the energy demand multiplier, can likewise simulate conservation/efficiency enhancement programs that alter the flow of carbon into the atmosphere. It is important to note that reductions in energy use triggered by '''endemm''' are free; that is to say, they are not accompanied in the model by economic costs. In reality, conservation or efficiency efforts occasionally do reduce energy use without a large cost—as evidenced by voluntary behavioral shifts on the part of citizens, or regulations enforced by the government. However, because it may be unrealistic to assume costless energy demand changes, users may wish to include financial considerations in their scenarios. The parameter '''carbtax '''simulates a reduction in demand triggered by tax; users would pay an additional fee on fossil fuels proportional to carbon content. This would encourage conservation or a transition to less expensive forms of energy. Users experimenting with carbon taxes should observe the effects on the energy production system '''(ENP)''', the level of annual carbon emissions '''(CARANN'''), world temperature ('''WTEMP''') and the level of economic output ('''GDP)'''.
 +
 +
Users can also simulate government interventions designed to encourage research and development focused on renewable energy or energy efficiency. Each energy type’s cost profile is linked to a capital-output ratio multiplier, '''qem'''. Users can simulate a decrease in the cost of renewables by reducing the multiplier’s initial value from 1.0 to 0.8—this would reduce all production costs by 20 percent (on top of whatever cost changes the model endogenously computes). Energy prices can also be indirectly controlled by changes to natural resources needed to produce fossil fuels. As oil and gas resources are exploited, the remainder becomes more expensive to extract. Users can use '''resorm''' to enforce alternative assumptions about the scale of ultimate resources available for discovery, and eventually, production. Mechanisms involving resources, reserves, and energy price operate over a long time horizon. Any scenario using '''resorm''' should be run out to at least the year 2050 in order to display significant forward linkages.
 +
 +
Changes in the efficiency of energy use from oil and gas sources would have bearing on carbon emissions as well. Changes in energy efficiency are controlled by the growth rate parameter '''enrgdpgr '''in addition or instead of the use of '''endemm. '''Changes to this parameter simulate the impact of successful research and development programs in the public or private sphere. Three parameters offer an additional way to simulate improvements to energy efficiency: '''carfuel1, carfuel2 '''and '''carfuel3 '''set, respectively, the amount of carbon emitted by burning oil, natural gas and coal. Normally these should be considered physical constants and not changed, but the model does not contain a representation of carbon sequestration and '''carfuel3''' could be used to represent its impact, although not its cost. For a complete discussion on parameters pertaining to energy production see the [[#_Energy_Module|energy section]].
 +
 +
Returning to the issue of stock-to-stock flows of carbon, so far we have focused only on the movement of carbon from fossil fuels to the atmosphere. Not all carbon emitted into the atmosphere remains there, and the model contains parameters to control the absorption of atmospheric carbon by the oceans. Two parameters control this process in the model. The first is '''carabr''', an exogenous specification of the billion tons of carbon that annually moves to or is absorbed by the oceans. The second is '''carabrchng''', which sets the annual change in the absorption rate (a measure of flow). At this point the parameter is not functional, and the user should be aware that change in it will have no effect. The final stock-to-stock flow represented in the model is between the atmosphere and forests (to be discussed below). Because the model does not explicitly represent the flow between the atmosphere and other non-forest vegetation (or organic matter in the soil), users with interest in this area could turn to the parameter '''carabr''' to implicitly capture, not just absorption into oceans, but into other matter as well.
 +
 +
Turning to forward linkages, future trends in the carbon system will affect the world’s agricultural sector. The stock of atmospheric carbon dioxide ('''CO2PPM''') and the related level of global temperature ('''WTEMP''') are the variables that transmit the carbon system's effects. The model represents two major paths of impact, one related to each variable. The first path is the so-called carbon-fertilization effect. Because plants need carbon, an increase in '''CO2PPM''' can actually increase agricultural yields, and the parameter that controls that is '''envco2fert''', crop sensitivity to atmospheric carbon dioxide. A value of zero would turn off this linkage.
 +
 +
The second path is from global temperature ('''WTEMP''') to country-specific temperature and precipitation changes ('''ENVTPCHG '''and'''ENVPRCHG) '''and then to agricultural yield. The translation in the model of changes in global temperature to changes in country-specific temperature and precipitation uses information from climate-specific models and is not subject to parametric control by users (in modeling terminology, they are “hard-coded” within the model). The user can, however, affect the further impact of country-specific values to yield. While the model's formulation for that impact ('''ENVYLCHNG''') on yield is quite complex, two parameters exist for influencing it, the multiplicative parameter '''envylchgadd '''and the additive parameter '''envylchgm. '''Their effects are sequential, so it is best that the user rely on one or the other, not both.
 +
 +
One additional parameter is important in this consideration of forward linkages, namely that which controls the translation of atmospheric carbon levels ('''CO2PPM)''' into global temperature ('''WTEMP'''). That parameter is '''envclimsens''', the time sensitivity of global temperature to carbon dioxide. The very large-scale global circulation models of climate change struggle to make the connection between these two variables and IFs uses this simple parametric linkage to summarize some of what we have learned from them. But the relationship is uncertain, so a scenario that would raise or lower the parameter and the impact on global temperature might be of interest. Moreover, the impact of carbon on temperature is likely to be one that involves lags (increasing temperature slowly even at a given fixed level of raised carbon dioxide), so one could consider a dynamic value of the parameter over time in order to capture that.
 +
 +
==== Land Use ====
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="632" style="width:632px;"
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''forestm'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
WFOREST
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
World forest multiplier
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Multiplicative
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''tgrld'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
WFOREST, LD
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Land growth by type
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Initial condition
 +
 +
|-
 +
| nowrap="nowrap" style="width:99px;height:22px;" |
 +
'''carforst'''
 +
 +
| nowrap="nowrap" style="width:129px;height:22px;" |
 +
CO2PPM
 +
 +
| nowrap="nowrap" style="width:283px;height:22px;" |
 +
Level of carbon sequestered by forests
 +
 +
| nowrap="nowrap" style="width:121px;height:22px;" |
 +
Coefficient
 +
 +
|}
 +
 +
The importance of land extends beyond its role in carbon cycle. We are interested in forest area, for instance, due to its involvement in species preservation, in water cycle control, and for its own intrinsic value. A direct multiplier, '''forestm''', imposes an increase or a decrease on a country’s forest area. Any change in land area is constrained by a country’s geographic size because an increase in forest area requires a corresponding decrease in the land available for other types of use, such as crop production. As another way to affect land use, the parameter '''tgrld''' sets an initial target for annual growth in cropland. This second parameter achieves a change in land devoted to crops primarily as a trade off with forest area. For a complete discussion of parameters concerning patterns of land use, see the [[#_Agriculture_Module|agricultural section]]. Changes in land use will, of course, have secondary consequences visible in '''GDP''', '''AGP''', '''AGX''', and '''AGM''', among other variables
 +
 +
Returning to the role of forests in the carbon cycle, the key parameter is the amount of carbon sequestered by each million hectares of the earth’s forests, '''carforst'''. By default, this coefficient is set to 0.12—meaning that every million hectares of forest sequesters 0.12 billion tons of carbon. By increasing or decreasing the value, users can explore futures in which forests are more or less effective at removing carbon from the atmosphere.
  
 
== <span style="font-size:x-large;">Parameters Affecting Water Resources</span> ==
 
== <span style="font-size:x-large;">Parameters Affecting Water Resources</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="626" style="width:626px;"
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''watres'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
Unknown
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Renewable water resources
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Exogenous specification
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''tgrld'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
AGP
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Land growth by type
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Initial condition
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''ylm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
YL
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Agricultural yield multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|}
 +
 +
Currently, only one parameter in the model is directly linked to water variables. '''Watres '''allows users to set the renewable resources located in each of the countries in IFs. Changes to this parameter or exogenous variable (we would like it at some point to be a variable) can either be instantaneous or gradual, as specified by the user. Though each country’s renewable water resources, and associated water stress, has bearing on state fragility, it is important to note that the '''watres '''parameter does not constrain water use. As mentioned in the discussion above, modeling work is currently envisioned to create a dynamic water system.
 +
 +
Users can, however, affect water use via deeper drivers. Any increase (or decrease) in crop land, and subsequent increases (or decreases) in production, will require a corresponding change in water usage ('''WATUSE'''). Water usage per capita is linked to crop production per capita by a function in the model (Crop Production/Capita Versus Water Use/Capita). Thus, changing that function or manipulating the land growth by type parameter, '''tgrld''', can trigger patterns of water uses differing from those featured in the Base Case. The yield multiplier '''ylm''' provides a very direct method of indirect water use modification; increases in production will require more water, often (implicitly in the model) through irrigation.
  
 
== <span style="font-size:x-large;">Parameters Affecting Air Pollution</span> ==
 
== <span style="font-size:x-large;">Parameters Affecting Air Pollution</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="626" style="width:626px;"
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''Parameter'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
'''Variable of Interest'''
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
'''Description'''
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
'''Type'''
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''envpm2pt5m'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENVPM2PT5
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
PM2.5 levels multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''ensolfuelm'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENSOLFUEL
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Solid fuel use multiplier
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Multiplier
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''ensolfuelsetar'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENSOLFUEL
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Solid fuel use SE target
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Standard error target
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''ensolfuelseyrtar'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENSOLFUEL
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Solid fuel use SE target
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Standard error target
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''ensolfueltrgtval'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENSOL FUEL
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Solid fuel elimination target
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Target
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''ensolfueltrgtyr'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
ENSOLFUEL
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Solid fuel elimination target
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Target
 +
 +
|-
 +
| nowrap="nowrap" style="width:122px;height:22px;" |
 +
'''hlsolfuelsw'''
 +
 +
| nowrap="nowrap" style="width:103px;height:22px;" |
 +
DEATHCAT
 +
 +
| nowrap="nowrap" style="width:305px;height:22px;" |
 +
Relationship between solid fuel and respiratory diseases
 +
 +
| nowrap="nowrap" style="width:96px;height:22px;" |
 +
Switch
 +
 +
|}
 +
 +
Several environmental parameters allow users to directly manipulate levels of air pollution. Fine grain aerial particulate matter levels in residential areas ('''ENVPM2PT5''') are controlled by a multiplicative parameter, '''envpm2pt5m'''. Like any multiplier, assigning higher or lower values will result in a proportional change in the associated variable—in this case '''ENVPM2PT5'''. As an alternative, users can explore variations of solid fuel use in a specific country, region, or the world as a whole. The percentage of a population using solid fuel as their primary source of electricity ('''ENSOLFUEL)''' is connected to a multiplier, '''ensolfuelm'''. The model also features a pair of standard error target parameters: one that establishes the target, '''ensolfuelsetar''', and one that establishes the year by which the target will be reached, '''ensolfuelseyrtar'''. Users can alternatively (not simultaneously) utilize a second pair of parameters to set a year by which solid fuel use will be either reduced, or eliminated completely. '''Ensolfueltrgtval''' sets the desired reduction, and '''ensolfueltrgtyr''' sets the target year. Finally, and related to forward linkages, users can control whether there is a relationship between the burning of solid fuel and health. When the switch parameter '''hlsolfuelsw''' is set to 1 (the default), a positive relationship between solid fuel use and respiratory disease is active; when the switch is set to 0, the relationship is deactivated.
  
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 
== <span style="font-size:x-large;">Prepackaged Scenarios</span> ==
 +
 +
Exploring an alternative scenario conceptualized by the Netherlands Environmental Assessment Agency (PBL) can give users a quick overview of some of the powerful leverage points in the environment module. Using their integrated assessment model, called IMAGE, PBL constructed a set of forecasts representing a future in which carbon emissions drop dramatically. A replication of this scenario comes pre-packaged with the IFs installation, in the World Integrated Scenario Sets folder and the NCAR IPCC subfolder, under the title IMAGE_hirenew_lowcarbon. The folder contains, in total, five scenarios, all of which were developed during the course of a joint project between the Pardee Center and the National Center for Atmospheric Research (NCAR), which is located in Boulder, Colorado. Each alternative scenario uses IFs parameters to approximate work done by another integrated assessment model: BPL’s Integrated Model to Assess the Global Environment (IMAGE), Asia-Pacific Environment Innovation Strategy’s AIM, the International Atomic Energy Agency’s MESSAGE, and Pacific Northwest National Laboratory’s Mini-Climate Assessment Model, or MiniCAM,
 +
 +
In order to simulate a significant reduction in global carbon emissions, the IMAGE_hirenew_lowcarbon scenario includes interventions in capital-output ratio, fossil fuel burning behavior, and carbon tax policy. For oil, gas, coal and nuclear production in every country, the parameter '''qem '''is set to rise steadily, reaching a value of four by mid-century and remaining there until 2100. Conversely, the capital cost of each unit of renewable energy produced in the world is set to decline, with '''qem''' approaching 0.3, and remaining at that value until 2100. As fossil fuel production becomes expensive and green energy becomes relatively cheaper, price signals will push global energy producers to reduce carbon emissions. The use of the '''carbtax''' parameter augments the economic incentives attached to renewables in the scenario. By 2100 a carbon tax of 400 billion U.S. dollars is in place in every country in the world. Finally, the scenario adds an element of environmentally friendly technological change, through a reduction in the parameters '''carfuel1''', '''carfuel2''', and '''carfuel3'''. This would simulate worldwide discoveries allowing for the cleaner burning of oil, natural gas, and coal.
  
 
= <span style="font-size:xx-large;">Governance Module</span> =
 
= <span style="font-size:xx-large;">Governance Module</span> =
  
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 
== <span style="font-size:x-large;">Variables of Interest</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" style="width:500px;"
 +
|-
 +
| '''Variable Name'''
 +
| '''Description'''
 +
|-
 +
| '''GOVINDSECUR'''<br/>
 +
| Governance security index<br/>
 +
|-
 +
| '''GOVINDCAPAC'''<br/>
 +
| Governance capacity index<br/>
 +
|-
 +
| '''GOVINDINCLUS'''<br/>
 +
| Government inclusiveness index<br/>
 +
|-
 +
| '''GOVINDTOTAL'''<br/>
 +
| Total governance index<br/>
 +
|-
 +
| '''SFINTLWARALL'''<br/>
 +
| Internal war, event occurrence<br/>
 +
|-
 +
| '''SFINTLWARMAG'''<br/>
 +
| Internal war, magnitude<br/>
 +
|-
 +
| '''GOVRISK'''<br/>
 +
| Government risk index<br/>
 +
|-
 +
| '''GOVREV'''<br/>
 +
| Government revenues<br/>
 +
|-
 +
| '''AID'''<br/>
 +
| Foreign Aid<br/>
 +
|-
 +
| '''GOVCORRUPT'''<br/>
 +
| Government Corruption<br/>
 +
|-
 +
| '''REGQUALITY'''<br/>
 +
| Regulatory quality<br/>
 +
|-
 +
| '''ECONFREE'''<br/>
 +
| Economic freedom measure<br/>
 +
|-
 +
| '''GOVEFFECT'''<br/>
 +
| Government effectiveness<br/>
 +
|-
 +
| '''DEMOCPOLITY'''<br/>
 +
| Level of democracy<br/>
 +
|-
 +
| '''FREEDOM'''<br/>
 +
| Freedom measure<br/>
 +
|-
 +
| '''GEM'''<br/>
 +
| Gender empowerment measure<br/>
 +
|}
 +
 +
The IFs governance module contributes to a growing body of work dedicated to quantifying the performance of governments around the world. The IFs model adds to that literature especially by facilitating forecasting and scenario analysis. The module represents governance as a composite system, made up of three interconnected dimensions: security, capacity and inclusiveness. The modelling process builds on a large number of data series and governance indices constructed by various research groups, mostly in academia, non-profit organizations, and international organizations. Variables capturing regulatory quality and government effectiveness, for example, come from the World Bank’s World Governance Indicator project; Freedom House and Transparency International provide measures of economic freedom and corruption; and the Center for Systemic Peace provides state fragility and democracy indicators. Based on such data and series, the IFs system builds up to aggregate indices for its three dimensions of governance: '''GOVINDSECUR '''for security, '''GOVINDCAPAC '''for capacity, and '''GOVINDINCLUS '''for inclusivity. These three indices are then combined into an overall governance index,'''GOVINDTOTAL.'''
 +
 +
The building blocks of the three indices, however, are sub dimensions and component variables. Security’s sub-dimensions are the probability of intrastate conflict ('''SFINTLWARALL''') and a general level of government performance with associated risk of instability ('''GOVRISK'''). Although not used in the security index, '''SFINTLWARMAG''' supplements '''SFINTLWARALL''' by forecasting the average magnitude of internal conflict.
 +
 +
Forecasts of intrastate war probability ('''SFINTLWARALL''') are heavily path dependent, driven by a moving average of countries’ past experiences with violence. Over time, however, other factors—infant mortality, level of democracy, economic growth rate, and trade openness, among others—affect the probability of conflict as well. IFs uses an index, '''GOVRISK''', to measure the second sub-dimension of security, government performance and associated risk. For the 186 countries included in the model, the overall index value ranges roughly from 15 to 60, with a higher number signifying increased levels of risk. Low risk countries such as Sweden will generally fall at the bottom of the range, while high risk ones such as Somalia will be at the top. Like the probability of war, each country’s performance risk profile is driven by an array of factors across demographic, environmental, economic, health and education subsystems. A comprehensive look at each country’s performance and risk profile is available through Specialized Display under the option Performance Risk Evaluation. The display includes raw values and a global ranking, for each of the index’s nine components. Weighting and relative risk levels associated with each component are also listed.
 +
 +
The sub-dimensions of the second dimension of governance, capacity, are government revenue and government quality. Each country’s ability to raise revenue is captured by a simple ratio of '''GOVREV '''to'''GDP'''—net of foreign aid ('''AID''') received by governments, which the index does not include. The more revenue a government is able to raise relative to GDP, the higher the capacity score will be—for a discussion of the equilibrating processes used to calculate government revenue, expenditure and transfer payments see the [[#_The_Economic_Module|economic module]]. Governance quality, capacity’s second sub-dimension, is represented by corruption. In the model, '''GOVCORRUPT''' measures relative levels of political corruption, with 0 representing extremely corrupt practices, and 10 representing extreme transparency, or lack of corruption. Indices tracking regulatory quality ('''REGQUALITY)''', economic freedom ('''ECONFREE)''', and government effectiveness ('''GOVEFFECT)''' offer alternative formulations of governance quality. Although the '''GOVCORRUPT''' score is the only element used to generate the composite index '''GOVINDCAP''', the other indicators link forward to economic and infrastructure development processes.
 +
 +
The third dimension of governance, inclusiveness, is made up of the level of formal democratization and an element that measures gender empowerment in society. The '''DEMOCPOLITY '''index represents the strength of democratic institutions; in IFs, values range from 0 to 20, higher numbers signifying greater levels of democracy. In forecast years, several factors—the age structure of society, dependence on raw materials, energy exports and energy price—determine the strength of democracy. The model uses the gender empowerment measure ('''GEM''') as another index of inclusiveness. The measure takes its historical values—and its name—from the United Nations Development Program’s Gender Empowerment Measure. Forecasts of gender empowerment are driven by a country’s youth population size, GDP per capita at purchasing power parity, and years of formal education attained by female adults. The index '''FREEDOM''', created by Freedom House, offers a final formulation of civil participation in society. This measure is not used to generate the aggregate inclusiveness index, but it links forward to the social capital component of multifactor productivity.
 +
 +
While the three dimensions represent distinct facets of governance, they are tightly interrelated. Indeed, the drivers of security, capacity and inclusion often overlap. For example, gender empowerment, a sub-dimension of inclusion, drives security’s vulnerability to conflict index and capacity’s corruption index. And the three composite indices—'''GOVINDSECUR, GOVINDCAPAC '''and'''GOVINDINCLUS'''—interact bi-directionally with each other. Beyond the sub-module, strong relationships link the key governance indices and other measures of human well-being, represented by GDP per capita and the Human Development Index (HDI). For instance, economic freedom ('''ECONFREE''') links forward to multifactor productivity ('''MFP''') and thus on to broader economic growth. And conversely, other systems affect governance forecasts, as evidenced by the relationship between levels of per capita income and '''HDI''' and '''DEMOCPOLITY'''—higher levels of well-being lead to increased pressure for democracy.
 +
 +
The tri-part conceptualization of governance originated in the Pardee Center’s analysis of historical trends, as discussed in ''Potential Patterns of Human Progress'': ''Strengthening Governance Globally (''Hughes et al. (2014)). Over time, the story of governance has unfolded differently in countries across the world—some countries have developed security, capacity and inclusiveness sequentially, and some countries have developed all three dimensions simultaneously. A suite of parameters attached to the sub-dimensions of each dimension allows users to explore a range of potential patterns of global governance.
  
 
== <span style="font-size:x-large;">Parameters to Affect Security</span> ==
 
== <span style="font-size:x-large;">Parameters to Affect Security</span> ==
 +
 +
{| border="1" cellspacing="1" cellpadding="1" width="601" style="width:601px;"
 +
|-
 +
| nowrap="nowrap" style="width:85px;height:22px;" |
 +
'''Parameter'''
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'''Variable of Interest'''
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'''Description'''
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'''Type'''
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|-
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'''sfintlwaradd'''
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 +
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SFINTLWAR
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 +
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State failure/internal war addition
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 +
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Additive
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|-
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| nowrap="nowrap" style="width:85px;height:22px;" |
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'''sfconv'''
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| nowrap="nowrap" style="width:103px;height:22px;" |
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SFINTLWAR
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| nowrap="nowrap" style="width:305px;height:22px;" |
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State failure convergence
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| nowrap="nowrap" style="width:108px;height:22px;" |
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Convergence speed (years)
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|-
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| nowrap="nowrap" style="width:85px;height:22px;" |
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'''sfmassrep'''
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| nowrap="nowrap" style="width:103px;height:22px;" |
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SFINTLWAR
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| nowrap="nowrap" style="width:305px;height:22px;" |
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Mass repression factor
 +
 +
| nowrap="nowrap" style="width:108px;height:22px;" |
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Additive
 +
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|-
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| nowrap="nowrap" style="width:85px;height:22px;" |
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'''wpextinterv'''
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| nowrap="nowrap" style="width:103px;height:22px;" |
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SFINTLWAR
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| nowrap="nowrap" style="width:305px;height:22px;" |
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External intervention factor
 +
 +
| nowrap="nowrap" style="width:108px;height:22px;" |
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Additive
 +
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|-
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| nowrap="nowrap" style="width:85px;height:22px;" |
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'''govriskm'''
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| nowrap="nowrap" style="width:103px;height:22px;" |
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GOVRISK
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| nowrap="nowrap" style="width:305px;height:22px;" |
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Government risk multiplier
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 +
| nowrap="nowrap" style="width:108px;height:22px;" |
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Multiplicative
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|-
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| nowrap="nowrap" style="width:85px;height:22px;" |
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'''govriskweight'''
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| nowrap="nowrap" style="width:103px;height:22px;" |
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GOVRISK
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| nowrap="nowrap" style="width:305px;height:22px;" |
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Government risk weight
 +
 +
| nowrap="nowrap" style="width:108px;height:22px;" |
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Weight
 +
 +
|}
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The most direct way in which to change the probability of internal war, and thus its broader consequences, is to manipulate the additive parameter affecting the variable, '''sfintlwaradd'''. Other parameters connected to internal war and the country performance risk evaluation allow users to explore alternate scenarios around security. Over time, a country’s probability of internal war will converge to the model’s expected function, a function driven by demographic and economic factors. However, users can control the speed of convergence through the parameter '''sfconv'''—accelerating this convergence would be an effective way to improve the fortunes of countries with especially bad histories of intrastate violence, because path dependency is a driver of internal war probability. Though set to 0.0 in the Base Case, two additional parameters exist that can directly affect the likelihood of internal war. '''Wpextinterv '''is a parameter that, when activated, simulates a conflict-creating external intervention; when the parameter is set to 1.0 the probability of intrastate conflict rises to 1.0 also. Another parameter, '''sfmassrep''', works in a similar way but with a reverse valence. Assigning it a value other than 0.0 simulates a campaign of mass repression by the central government that lowers the probability of overt intra-state violence.
 +
 +
Turning to government