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


'''International Futures (IFs) is a tool for thinking about long-term global trends and planning more strategically for the&nbsp;future.&nbsp;'''
'''The International Futures (IFs) model helps us explore, understand, and shape global questions about future human well-being. The model empowers users to examine past trends to understand the current trajectory we are on, how human, social, and environmental systems interact over time, and how we think about and address the “grand challenges” awaiting the global community.'''


IFs can help you:
'''IFs can help you:'''


*Understand&nbsp;the state of major&nbsp;global systems
*Understand&nbsp;the state of major&nbsp;global systems
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*Develop alternative scenarios (if-then statements) about the future
*Develop alternative scenarios (if-then statements) about the future
*Investigate how different groups (households, firms or governments) can shape the future
*Investigate how different groups (households, firms or governments) can shape the future
*Evaluate the potential impacts of policies


'''IFs development and analysis depend&nbsp;on core, underlying assumptions, including the following.'''
'''The IFs platform relies&nbsp;on core, underlying assumptions, including the following.'''


*Global issues are becoming&nbsp;more significant as the scope of human interaction and human impact on the broader environment grow.
*Global issues are becoming&nbsp;more significant as the scope of human interaction and human impact on the broader environment grow
*Goals and priorities for human systems are becoming clearer and are more frequently and consistently communicated.
*Goals and priorities for human systems are becoming clearer and are more frequently and consistently communicated
*Understanding of the dynamics of human systems is improving&nbsp;rapidly.
*Understanding of the dynamics of human systems is improving&nbsp;rapidly
*The domain of human choice and action is broadening.
*The domain of human choice and action is broadening


'''What issues can you&nbsp;investigate with IFs?'''
'''Which issues can you&nbsp;investigate with IFs? Some examples include:'''


*[[Environment]]: Atmospheric carbon dioxide levels, world forest area, fossil fuel usage
*[[Environment]]: Atmospheric carbon dioxide levels, world forest area, temperature change
*[[Socio-Political|Socio-Political Change]]: Life expectancy, literacy rate, democracy level, status of women, value change
*[[Infrastructure]]: Electricity access, number of fixed broadband subscriptions
*[[Health]]: Life expectancy, HIV prevalence, death rates by category of cause
*[[Education]]: Average years of education, literacy rate
*[[Governance]]: Democracy level, expenditure and spending levels, debt level
*Human Development: Poverty level, status of women
*[[Interstate Politics (IP)|International Relations]]: Country and regional power levels, interstate conflict likelihood
*[[Population|Demographics]]: Population levels and growth, fertility, mortality, migration
*[[Population|Demographics]]: Population levels and growth, fertility, mortality, migration
*[[Agriculture|Food and Agriculture]]: Land use and production levels, calorie availability, malnutrition rates
*[[Agriculture]]: Land use and production levels, calorie availability, malnutrition rates
*[[Energy]]: Resource and production levels, demand patterns, renewable energy share
*[[Energy]]: Resource and production levels, demand patterns, fossil fuel usage, renewable energy share
*[[Economics]]: Sectoral production, consumption, and trade patterns and structural change
*[[Economics]]: Sectoral production, consumption, trade patterns and structural change
*[[Interstate_Politics_(IP)|Geopolitics]]: Country and regional power levels


= <span style="font-size:xx-large;">IFs Issues and Modules: Visual Representation</span> =
= <span style="font-size:xx-large;">IFs Issues and Modules: Visual Representation</span> =
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Among the philosophical premises of the International Futures (IFs) project is that the model cannot be a "black box" to users and be truly useful. Model users must be able to examine the structures of IFs in order (1) to have confidence in them, and (2) learn from them.
Among the philosophical premises of the International Futures (IFs) project is that the model cannot be a "black box" to users and be truly useful. Model users must be able to examine the structures of IFs in order (1) to have confidence in them, and (2) learn from them.


There is available (see topics under Understanding the Mode in the contents of this help system):
The following topics are useful starting points for better understanding the model.


*[[Understand_IFs#Dominant_Relations|Dominant Relations]] of the model structure
*[[Understand_IFs#Dominant_Relations|Dominant Relations]] of the model structure
*[[Understand_IFs#2.2|Structure-Based and Agent-Class Driven Modeling]]
*[[Understand_IFs#2.2|Structure-Based and Agent-Class Driven Modeling]]
*[[Understand_IFs#Equation_Notation|Equation Notation]]
*[[Understand_IFs#Equation_Notation|Equation Notation]]
*[[Introduction_to_IFs#IFs_Bibliography|IFs Bibliography]] of data and data sources
*[[IFs_Bibliography|IFs Bibliography]] of data and data sources


= <span style="font-size:xx-large;">IFs Issues and Modules: Quick Survey</span> =
= <span style="font-size:xx-large;">IFs Issues and Models: Quick Survey</span> =


The '''population''' module:
International Futures is a collection of interconnected models (sometimes referred to as modules). Below is a quick survey of the major models in IFs. For more information on each one, please click on the model headings.
 
The '''[[Population|demographics]]''' model:


*represents 22 age-sex cohorts to age 100+
*represents 22 age-sex cohorts to age 100+
*calculates change in fertility and mortality rates in response to income, income distribution, and analysis multipliers
*calculates change in fertility and mortality rates in response to income, income distribution, and analysis multipliers
*computes average life expectancy at birth, literacy rate, and overall measures of human development (HDI) and physical quality of life
*computes average life expectancy at birth and represents migration
*represents migration and HIV/AIDS
*includes a newly developing submodel of formal education across primary, secondary, and tertiary levels


The '''economic''' module:
The '''[[Economics|economic]]''' model:


*represents the economy in six sectors: agriculture, materials, energy, industry, services, and ICT (other sectors could be configured, using raw data from the GTAP project)
*represents the economy in six sectors: agriculture, raw materials, energy, manufactures, services, and ICT (other sectors could be configured, using raw data from the GTAP project)
*computes and uses input-output matrices that change dynamically with development level
*is a general equilibrium-seeking model that does not assume exact equilibrium will exist in any given year; rather it uses inventories as buffer stocks and to provide price signals so that the model chases equilibrium over time
*is a general equilibrium-seeking model that does not assume exact equilibrium will exist in any given year; rather it uses inventories as buffer stocks and to provide price signals so that the model chases equilibrium over time
*contains an endogenous production function that represents contributions to growth in multifactor productivity from R&D, education, worker health, economic policies ("freedom"), and energy prices (the "quality" of capital)
*contains an endogenous production function that represents contributions to growth in multifactor productivity from R&D, education, worker health, economic policies ("freedom"), and energy prices (the "quality" of capital)
*uses a Linear Expenditure System to represent changing consumption patterns
*multifactor productivity from the production function along with labor and capital stock are the main drivers of the magnitude of production
*utilizes a "pooled" rather than the bilateral trade approach for international trade
*utilizes a "pooled" rather than the bilateral trade approach for international trade
*is being imbedded during 2002 in a social accounting matrix (SAM) envelope that will tie economic production and consumption to intra-actor financial flows
*computes and uses a social accounting matrix (SAM) that ties economic production and consumption to intra-actor financial flows both domestically and internationally for households, governments, and industry
*the SAM calculates changes in income distributions based on its projection of household consumption and on the education model's projections of skill level


The '''agricultural''' module:
The '''[[Agriculture|agricultural]]''' model:


*represents production, consumption and trade of crops and meat; it also carries ocean fish catch and aquaculture in less detail
*represents production, consumption and trade of crops, meat, and fish
*maintains land use in crop, grazing, forest, urban, and "other" categories
*maintains land use in crop, grazing, forest, urban, and "other" categories; and water use
*represents demand for food, for livestock feed, and for industrial use of agricultural products
*represents demand for food, for livestock feed, and for industrial use of agricultural products
*is a partial equilibrium model in which food stocks buffer imbalances between production and consumption and determine price changes
*is a partial equilibrium model in which food stocks buffer imbalances between production and consumption and determine price changes
*overrides the agricultural sector in the economic module unless the user chooses otherwise
*overrides the agricultural sector in the economic module unless the user chooses otherwise


The '''energy''' module:
The '''[[energy]]''' model:


*portrays production of six energy types: oil, gas, coal, nuclear, hydroelectric, and other renewable
*portrays production of six energy types: oil, natural gas, coal, nuclear, hydroelectric, and other renewable
*represents consumption and trade of energy in the aggregate
*represents consumption and trade of energy in the aggregate
*represents known reserves and ultimate resources of the fossil fuels
*represents known reserves and ultimate resources of the fossil fuels
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*overrides the energy sector in the economic module unless the user chooses otherwise
*overrides the energy sector in the economic module unless the user chooses otherwise


The two '''socio-political''' sub-modules:
The [[Interstate Politics (IP)|international relations]] model:


Within countries or geographic groupings
Within countries or geographic groupings


*represents fiscal policy through taxing and spending decisions
*shows six categories of government spending: military, health, education, R&D, foreign aid, and a residual category
*represents changes in social conditions of individuals (like fertility rates or literacy levels), attitudes of individuals (such as the level of materialism/postmaterialism of a society from the World Value Survey), and the social organization of people (such as the status of women)
*represents the evolution of democracy
*represents the prospects for state instability or failure
*represents the prospects for state instability or failure


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*allows exploration of changes in the level of interstate threat
*allows exploration of changes in the level of interstate threat
*represents possible action-reaction processes and arms races with associated potential for conflict among countries
*represents possible action-reaction processes and arms races with associated potential for conflict among countries
The [[governance]] model:
*is a two way interaction between governments and the socio-cultural system
*has three dimensions of governance: capacity, security, and inclusion that closely interact bi-directionally
*represents the evolution of democracy
*represents fiscal policy through taxing and spending decisions
*shows six categories of government spending: military, health, education, R&D, foreign aid, and a residual category
The [[infrastructure]] model:
* forecasts the demand of infrastructure and the funding available to meet the demand
* forecasts levels of infrastructure based on this demand and funding constraint
* measures access to key infrastructures like water, electricity, or broadband
* maintains and calculates changes in physical stocks like percentage of roads paved, and area equipped with irrigation


The implicit '''environmental''' module:
The [[health]] model:


* forecasts age, sex, and health indicators related to 15 causes of death modeled in IFs
* splits causes of death into three cause groups: communicable, maternal, perinatal, and nutritional conditions; noncommunicable diseases; and injuries
* is driven by education, technology, and income
The [[education]] model:
* projects educational participation and attainment across primary, secondary, and tertiary levels for each country in IFs
* determines attainment and participation through the demand for education and the investment in education by governments
* has educational demand based on income while educational investment is a result of government spending
* models the rates of dropout, completion, and transition to the next level of schooling
The '''[[Environment|environmental]]''' model:
*is distributed throughout the overall model
*is distributed throughout the overall model
*allows tracking of remaining resources of fossil fuels, of the area of forested land, of water usage, and of atmospheric carbon dioxide emissions
*allows tracking of remaining resources of fossil fuels, of the area of forested land, of water usage, and of atmospheric carbon dioxide emissions


The implicit '''technology''' module:
The implicit '''technology''' model:


*is distributed throughout the overall model
*is distributed throughout the overall model
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*explicitly represents the extent of electronic networking of individuals in societies
*explicitly represents the extent of electronic networking of individuals in societies
*is tied to the governmental spending model with respect to R&D spending&nbsp;
*is tied to the governmental spending model with respect to R&D spending&nbsp;
*represents changes in social conditions of individuals (like fertility rates or literacy levels), attitudes of individuals (such as the level of materialism/postmaterialism of a society from the World Value Survey), and the social organization of people (such as the status of women)


= <span style="font-size:xx-large;">IFs Background</span> =
= <span style="font-size:xx-large;">IFs Background</span> =


International Futures (IFs) has evolved since 1980 through three "generations," with a fourth generation now taking form.
International Futures (IFs) has evolved since 1980 through eight "generations," with the eighth generation now taking form.
 
'''The first generation''' had deep roots in the world models of the 1970s, including those of the Club of Rome. In particular, IFs drew on the Mesarovic-Pestel or World Integrated Model (Mesarovic and Pestel 1974). The author of IFs had contributed to that project, including the construction of the energy submodel. IFs consciously also drew on the Leontief World Model (Leontief et al. 1977), the Bariloche Foundation’s world model (Herrera et al. 1976), and Systems Analysis Research Unit Model (SARU 1977), following comparative analysis of those models by Hughes (1980). That generation was written in FORTRAN and available for use on main-frame computers through CONDUIT, an educational software distribution center at the University of Iowa. Although the primary use of that and subsequent generations was by students, IFs has always had some policy analysis capability that has appealed to specialists. For example, the U.S. Foreign Service Institute used the first generation of IFs in a mid-career training program.
 
'''The second generation''' of International Futures moved to early microcomputers in 1985, using the DOS platform. It was a very simplified version of the original IFs without regional or country differentiation.
 
'''The third generation''', first available in 1993, became a full-scale microcomputer model. The third generation improved earlier representations of demographic, energy, and food systems, but added new environmental and socio-political content. It built upon the collaboration of the author with the GLOBUS project, and it adopted the economic submodel of GLOBUS (developed by the author). GLOBUS had been created with the inspiration of Karl Deutsch and under the leadership of Stuart Bremer (1987) at the Wissenschaftszentrum in Berlin.
 
The third generation produced three editions/major releases of IFs, each accompanied by a book also called International Futures (Hughes 1993, 1996, 1999). The second edition moved to a Visual Basic platform that allowed a much improved menu-driven interface, running under Windows. The third edition incorporated an early global mapping capability and an initial ability to do cross-sectional and longitudinal data analysis.
 
'''The fourth generation''' took shape since early 2000. It was heavily influenced by the usage of the model by several important organizations for policy-analysis. First, General Motors commissioned a specialized version of IFs named CoVaTrA (Consumer Values Trends Analysis) with a need for updated and extended demographic modeling and representation of value change. An alliance was established with the World Values Survey, directed by Ronald Inglehart, to create that version. Second, the Strategic Assessments Group of the Central Intelligence Agency commissioned a specialized version named IFs for SAG. The work involved in preparing that greatly extended and enhanced the socio-political representations of the model, both domestic and international. Third, the European Commission sponsored a project named TERRA which has led to a specialized version named IFs for TERRA. The IFs for TERRA work led to enhancements across the model, including improved representation of economic sectors, updated IO matrices and a basic Social Accounting Matrix, GINI and Lorenz curves, and preparing for extended environmental impact representation (drawing upon the Advanced Sustainability Analysis framework of the Finland Futures Research Center).


The first generation had deep roots in the world models of the 1970s, including those of the Club of Rome. In particular, IFs drew on the Mesarovic-Pestel or World Integrated Model (Mesarovic and Pestel 1974). The author of IFs had contributed to that project, including the construction of the energy submodel. IFs consciously also drew on the Leontief World Model (Leontief et al. 1977), the Bariloche Foundation’s world model (Herrera et al. 1976), and Systems Analysis Research Unit Model (SARU 1977), following comparative analysis of those models by Hughes (1980). That generation was written in FORTRAN and available for use on main-frame computers through CONDUIT, an educational software distribution center at the University of Iowa. Although the primary use of that and subsequent generations was by students, IFs has always had some policy analysis capability that has appealed to specialists. For example, the U.S. Foreign Service Institute used the first generation of IFs in a mid-career training program.
The fourth generation of IFs also had a heavy emphasis on enhancing usability. Ideas from Robert Pestel in the TERRA project led to the creation of a new tree-structure for scenario creation and management. Ideas from Ronald Inglehart led to the development of the Guided Use structure and a somewhat more game-like character within that structure. Inglehart also helped to arrange funding to support the programming of Guided Use through the European Union Center of the University of Michigan.


The second generation of International Futures moved to early microcomputers in 1985, using the DOS platform. It was a very simplified version of the original IFs without regional or country differentiation.
'''The fifth generation''' of IFs (from 2004-2009) focused on improving the model, its usability, and transparency. Model improvements included clearer and more extensive representations of the agent classes and their points of leverage, stemming from the desire to make the modeling system a more valuable scenario-testing and policy analysis tool. The further elaboration of the social accounting matrix, structure, the development of education and health sub-models, and the substantial redesign of an economic production function with endogenous multifactor productivity were all outcomes of this version.


The third generation, first available in 1993, became a full-scale microcomputer model. The third generation improved earlier representations of demographic, energy, and food systems, but added new environmental and socio-political content. It built upon the collaboration of the author with the GLOBUS project, and it adopted the economic submodel of GLOBUS (developed by the author). GLOBUS had been created with the inspiration of Karl Deutsch and under the leadership of Stuart Bremer (1987) at the Wissenschaftszentrum in Berlin.
Efforts to enhance the models usability included the addition of a number of specialized displays, such as those for seeing the social accounting matrices, to display progress towards the Millennium Development Goals, to explore poverty at different income levels, and to represent the educational attainment of population cohorts. Mapping and data analysis tools were also strengthened. The ability to drill down into select countries to explore futures at the state or province-level was also added. Packaged Displays and Flex Packaged Displays were introduced that allowed for the creation of very specific lists of countries/regions, groups or G-lists. Greater transparency came from adding the ability for users to access the flow charts, equations, and code underlying the model.


The third generation has produced three editions/major releases of IFs, each accompanied by a book also called International Futures (Hughes 1993, 1996, 1999). The second edition moved to a Visual Basic platform that allowed a much improved menu-driven interface, running under Windows. The third edition incorporated an early global mapping capability and an initial ability to do cross-sectional and longitudinal data analysis.
The fifth version was the first version of this software to be placed online due to the help of the National Intelligence Council (http://www.ifs.du.edu). New scenarios were created for UNEP (focusing on environmental change) and Pardee (focusing on poverty). Finally, one of the largest changes made was incorporating 182 countries into the Base-Case scenario used by IFs. Previous versions of IFs used broader regions to forecast global trends. This change also did away with the Student and Professional versions.


The fourth generation has been taking shape since early 2000. It has been heavily influenced by the usage of the model in an increasingly policy-analysis mode by several important organizations. First, General Motors commissioned a specialized version of IFs named CoVaTrA (Consumer Values Trends Analysis) with a need for updated and extended demographic modeling and representation of value change. An alliance was established with the World Values Survey, directed by Ronald Inglehart, to create that version. Second, the Strategic Assessments Group of the Central Intelligence Agency commissioned a specialized version named IFs for SAG. The work involved in preparing that greatly extended and enhanced the socio-political representations of the model, both domestic and international. Third, the European Commission sponsored a project named TERRA which has led to a specialized version named IFs for TERRA. IFs for TERRA work led to enhancements across the model, including improved representation of economic sectors, updated IO matrices and a basic Social Accounting Matrix, GINI and Lorenz curves, and preparing for extended environmental impact representation (drawing upon the Advanced Sustainability Analysis framework of the Finland Futures Research Center).
'''The sixth generation''' of IFs began in 2010 and revolved around the development of the Patterns of Potential Human Progress (PPHP) series. The [https://korbel.du.edu/pardee/content/patterns-potential-human-progress PPHP] volumes, with their focus on major human development systems, spurred the further enhancement of the model’s major subsystems, especially population, economic (especially poverty representation), education, health, infrastructure, and governance. The supporting documentation required for the PPHP series also gave rise to efforts to create the most detailed documentation of the model to date.


Throughout this emergence of a fourth generation IFs (incorporating all of the above elements for additional users) there has been also a heavy emphasis on enhanced usability. Ideas from Robert Pestel in the TERRA project led to the creation of a new tree-structure for scenario creation and management. Ideas from Ronald Inglehart led to the development of the Guided Use structure and a somewhat more game-like character within that structure. Inglehart also help arrange funding to support the programming of Guided Use through the European Union Center of the University of Michigan.
'''The seventh generation''' officially began in 2014. This generation emerged after the PPHP volumes and with the advent of a variety of new projects, including wider support for provincial and state breakdowns, new means of forecasting diplomatic and power interactions, and enhanced representations in many of the IFs modules. Central to the institute's efforts this version also had continuous improvements in the existing elements of the model and usability. The sixth generation greatly strengthened the web-based version and it will increasingly become central to our work in the current generation.


The fifth version of IFs is currently in use and represents broad strides to improving the model and its usability. It is the first version of this software to be placed online due to the help of the National Intelligence Council ([http://www.ifs.du.edu http://www.ifs.du.edu]). Also, usability has been increased as Packaged Displays and Flex Packaged Displays were introduced that allowed for the creation of very specific lists of countries/regions, groups or Glists. A new education model has also been incorporated into the broader IFs model. New scenarios were created for UNEP (focusing on environmental change) and Pardee (focusing on poverty). Finally, one of the largest changes made was incorporating 182 countries into the Base-Case scenario used by IFs. Previous versions of IFs used broader regions to forecast global trends. This change also did away with the Student and Professional versions.
'''The current (eighth) generation''' is primarily distinguished by a transition in the underlying coding language, shifting from Visual Basic 6 to Visual Basic .NET. This shift has facilitated the integration of both online and standalone user interfaces, streamlining the process of implementing interface modifications. Moreover, the adoption of this new underlying language and user interface has empowered developers to leverage a broader range of third-party applications and dynamic visualization tools, while aligning with Microsoft-supported languages.  


= <span style="font-size:xx-large;">Geographic Representation of the World</span> =
= <span style="font-size:xx-large;">Geographic Representation of the World</span> =


186 countries underpin the functioning of IFs and these countries can be displayed separately or as parts of larger groups that users can determine.
188 countries underpin the functioning of IFs and these countries can be displayed separately or as parts of larger groups that users can determine.


''Below is a visual representation of how different entities are organized into Countries/Regions, Groups or Glists:''
''Below is a visual representation of how different entities are organized into Countries/Regions, Groups or Glists:''
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When using IFs, there are many occasions where the user is asked whether or not they would like to display their results as a product of single countries, or larger groups. This is typically a toggle switch that moves between Country/Region and Groups, however, it might be a three-way-toggle that includes Country/Region, Group and Glist.
When using IFs, there are many occasions where the user is asked whether or not they would like to display their results as a product of single countries, or larger groups. This is typically a toggle switch that moves between Country/Region and Groups, however, it might be a three-way-toggle that includes Country/Region, Group and Glist.


Countries/Regions are currently the smallest geographical unit that users can represent. The ability to split countries down into smaller regions, or states, is under development. There are 186 different countries/regions that users can display.
Countries/Regions are currently the smallest geographical unit that users can represent. The ability to split countries down into smaller regions, or states, is under development. There are 188 different countries/regions that users can display.


Groups are variably organized geographically or by memberships in international institutions/regimes. You can find out who is represented in each group and add or delete members by exploring the [[Extended_Features#Manage_Groups/Regions|Managing Regionalization]] function.
Groups are variably organized geographically or by memberships in international institutions/regimes. You can find out who is represented in each group and add or delete members by exploring the [[Extended_Features#Manage_Groups/Regions|Managing Regionalization]] function.
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= <span style="font-size:xx-large;">IFs Time Horizon</span> =
= <span style="font-size:xx-large;">IFs Time Horizon</span> =


'''Future Forecasts.''' IFs begins computation with data from 2000 and can dynamically calculate values for all variables annually through 2100.
'''Future Forecasts.''' IFs begins computation with data from 2020 and can dynamically calculate values for all variables annually through 2100.
 
'''Historical Analysis and "Forecasts."''' IFs also includes an extensive and growing historical data base starting in 1960. The data basis allows analysis of relationships among variables across countries and across time.&nbsp;
 
== <span style="font-size:x-large;">Instructional Use</span> ==
 
The standard modes for using IFs in a classroom are:
 
1. Assigning class members to an issue area or topic. Consider identifying specific questions for them to address.
 
2. Assigning class members to a country/geographic region. Again, specificity helps.
 
Most often, students will work independently or in groups on projects and share information after completing them. It is possible, however, to have students work interactively, by assigning them topics or regions, letting them begin work, and then have the interacting groups (or individuals) create a collective model run with the changes that each group proposes by topic or region. That process, although more difficult to organize, allows the class as whole to investigate the interaction of their topics or regions (and to share learning about model use).
 
There is a&nbsp;[http://portfolio.du.edu/bhughes web site]&nbsp;available in support of the educational use of IFs. You will find syllabi at that site. There are several [[Introduction_to_IFs#Publications_on_IFs|publications]] on IFs, including a book structured specifically for educational use.
 
Donald Borock has described his classroom use of IFs in print. Borock, Donald. 1996. "Using Computer Assisted Instruction to Enhance the Understanding of Policymaking," Advances in Social Science and Computers 4, 103-127.
 
= <span style="font-size:xx-large;">Acknowledgements</span> =
 
The author gratefully recognizes critical contributions in the forms of:
 
:1. Testing and suggestions for development of IFs in one or more of multiple generations. By Donald Borock, Richard Chadwick, William Dixon, Dale Rothman, Phil Schrodt, Douglas Stuart, Donald Sylvan, Jonathan Wilkenfeld, and Ronald Inglehart.
 
:2. Computer assistance across many releases. By Michael Niemann, Terrance Peet-Lukes, Douglas McClure, Mohammod Irfan, and Jose Solorzano.
 
:3. Data gathering and general assistance. By James Chung, Padma Padula, Shannon Brady, David Horan, Michael Ferrier, Kay Drucker, Warren Christopher, and Anwar Hossain.
 
:4. Long-term encouragement and support. By Harold Guetzkow, Karl Deutsch, Richard Chadwick, Gerald Barney, and Ronald Inglehart.
 
:5. Association in related world modeling projects and projects building upon IFs. By Mihajlo Mesarovic, Aldo Barsotti, Juan Huerta, John Richardson, Thomas Shook, Patricia Strauch, and other members of the World Integrated Model (WIM) team. By Stuart Bremer, Peter Brecke, Thomas Cusack, Wolf Dieter-Eberwein, Brian Pollins, and Dale Smith of the GLOBUS modeling project. By Evan Hillebrand, Paul Herman, and others of the IFs for SAG project. By Rob Lempert and Steve Bankes at RAND, Santa Monica. By Robert Pestel, Jonathan Cave, Ronald Inglehart, Sergei Parinov, Pentti Malaska, and many others in the IFs for TERRA project.
 
:6. Financial assistance (without responsibility for the form of the evolving product). By the National Science Foundation, the Cleveland Foundation, the Exxon Education Foundation, the Kettering Family Foundation, the Pacific Cultural Foundation, the United States Institute of Peace, General Motors, the Strategic Assessments Group of the Central Intelligence Agency, the European Commission (Information Society Technology) Programme, the European Union Center of the University of Michigan, the National Intelligence Council (for web conversion), and Frederick S. Pardee. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;
 
= <span style="font-size:xx-large;">Feedback</span> =
 
Feedback on how to improve IFs is always appreciated, especially if you find something that is not working. Compliments are also accepted. Please contact. To send the IFs team an e-mail, click on&nbsp;[mailto:pardee.center@du.edu Pardee Center]&nbsp;in stand-alone versions or on the web.
 
= <span style="font-size:xx-large;">Support for IFs Use</span> =
 
== <span style="font-size:x-large;">Publications on IFs</span> ==
 
To obtain additional information about IFs and its use, consult:
 
Barry B. Hughes and Evan E. Hillebrand, '''Exploring and Shaping International Futures.''' Boulder, CO: Paradigm Publishers, 2006. Specifically, see chapter 4.
 
Barry B. Hughes, '''International Futures: Choices in the Face of Uncertainty,''' 3rd ed. Boulder, CO: Westview Press, 1999. This volume is built around IFs and contains detailed suggestions for its use. Version 3.17 of IFs, which runs under Windows 95, is distributed with the third edition of the book. The second edition contained a version for Windows 3.1, and the first edition ran under DOS. Chapter 4 of the 2nd edition of IFs included Flow Charts of Worldviews , reproduced now in this Help system.
 
Barry B. Hughes, '''Continuity and Change in World Politics,''' 4th ed. Englewood Cliffs, N.J.: Prentice Hall, 2000. IFs can also usefully supplement this textbook on global politics.
 
Barry B. Hughes, "The International Futures (IFs) Modeling Project. 1999. '''Simulation and Gaming''' 30, No. 3 (September): 304-326.
 
== <span style="font-size:x-large;">IFs Bibliography</span> ==
 
Alcamo, Joseph, Rik Leemans and Eric Kreileman, eds. 1998.&nbsp;''Global Change Scenarios of the 21st Century: Results from the IMAGE 2.1 Model''. The Netherlands: Pergamon.
 
Alcamo, Joseph. 1994.&nbsp;''IMAGE 2.0: Integrated Modeling of Global Climate Change''. Dordrecht, The Netherlands: Kluwer Academic Publishers.
 
Alexandratos, Nikos, ed. 1995.&nbsp;''World Agriculture: Towards 2010''&nbsp;(An FAO Study). New York: FAO and John Wiley and Sons.
 
Allen, R. G. D. 1968.&nbsp;''Macro-Economic Theory: A Mathematical Treatment''. New York: St. Martin's Press.
 
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United Nations Development Program (UNDP). 1995.&nbsp;''Human Development Report''. New York: Oxford University Press.
 
United Nations Food and Agricultural Organization (FAO). 1992.&nbsp;''Production Yearbook.''&nbsp;Rome: FAO.
 
United Nations Food and Agricultural Organization (FAO). 1995.''&nbsp;World Agriculture: Towards 2010.''&nbsp;Rome: FAO.
 
United Nations Population Division. 1999. The World at Six Billion New York: UN.
 
United Nations Population Division. 2000. Replacement Migration: Is it a Solution to Declining and Ageing Populations? New York: UN.
 
United States Arms Control and Disarmament Agency (ACDA). 1995.&nbsp;''World Military Expenditures and Arms Transfers 1995''. Washington, D.C.: Arms Control and Disarmament Agency.
 
United States Bureau of the Census. 1991.&nbsp;''World Population Profile: 1991''. Report WP/91 Washington, D.C.: Government Printing Office.
 
Walters, Robert S. and David H. Blake. 1992.&nbsp;''The Politics of Global Economic Relations'', 4th edition. Englewood Cliffs, N.J.: Prentice-Hall.
 
Waltz, Kenneth N. 1959. Man, the State, and War: A Theoretical Analysis. New York: Columbia University Press.
 
Watkins, John Elfreth, Jr. 1990. "What May Happen in the Next Hundred Years," in Edward Cornish, ed.,&nbsp;''The 1990s and Beyond.''&nbsp;Bethesda, Maryland: World Future Society, pp. 150-155.
 
Wildavsky, Aaron, and Ellen Tenenbaum. 1981.&nbsp;''The Politics of Mistrust''. Beverly Hills: Sage Publications.
 
World Bank. 1991b.&nbsp;''World Tables 1991''. New York: Johns Hopkins University Press.
 
World Bank. 1995&nbsp;''World Development Report 1995''. New York: Oxford University Press.
 
World Energy Council (WEC) Commission. 1993.&nbsp;''Energy for Tomorrow’s World.''&nbsp;New York: St. Martin’s Press.
 
World Resources Institute (WRI). 1994.&nbsp;''World Resources 1994-95.''&nbsp;New York: Oxford University Press.
 
Wortman, Sterling and Ralph W. Cummings, Jr. 1978.''&nbsp;To Feed This World''. Baltimore: Johns Hopkins University Press.
 
Zinnes, Dina A. and John W. Gillespie, eds. 1976.&nbsp;''Mathematical Models in International Relations''&nbsp;(New York: Preaeger).
 
== <span style="font-size:x-large;">Health Bibliography</span> ==
 
Adams 1987.&nbsp;[http://www.geog.ucl.ac.uk/~jadams/PDFs/smeed's%20law.pdf "Smeed's Law: some further thoughts."]&nbsp;''Traffic Engineering and Control''&nbsp;(Feb) 70-73.
 
Alsan, Marcella, David E. Bloom, and David Canning. 2006. “The Effects of Population Health on Foreign Direct Investment Inflows to Low- and Middle-Income Countries,”&nbsp;''World Development''&nbsp;34(4): 613-630.
 
Anand, Sudhir and Martin Ravallion. 1993. “Human development in poor countries: on the role of private incomes and public services,”&nbsp;''Journal of Economic Perspectives''&nbsp;7(1): 133–150.
 
Ashraf, Quamrul H., Ashley Lester, and David N. Weil. 2008. “When Does Improving Health Raise GDP?”&nbsp; NBER Working Paper No. 14449. National Bureau of Economic Research, Cambridge, MA.
 
Bidani, Benu and Martin Ravallion. 1997. “Decomposing social indicators using distributional data.”&nbsp;''Journal of Econometrics''&nbsp;77: 125–139.
 
Bloom, David E., and David Canning. 2004. “Global Demographic Change: Dimensions and Economic Significance.” NBER Working Paper No. 10817.&nbsp; National Bureau of Economic Research, Cambridge, MA.
 
Blössner, Monika, and Mercedes de Onis. 2005.&nbsp;''Malnutrition: quantifying the health impact at national and local levels.''&nbsp;Geneva, World Health Organization. (WHO Environmental Burden of Disease Series, No. 12).
 
Dargay, Gately, and Sommer 2007. “Vehicle Ownership and Income Growth, Worldwide: 1960-2030”. Joyce Dargay, Dermot Gately and Martin Sommer, January 2007.
 
Deaton, Angus, and Christina Paxson. 2000 (May). “Growth and Savings Among Individuals and Households.”&nbsp;''The Review of Economics and Statistics''&nbsp;82(2): 212-225.
 
Desai, Manish A., Sumi Mehta, and Kirk R. Smith. 2004. “Indoor smoke from solid fuels: Assessing the environmental burden of disease.”WHOEnvironmental Burden of Disease Series No. 4''.&nbsp;''Annette Pruss-Üstun, Diamid Campbell-Lendrum, Carlos Corvalán, and Alistair Woodward, series eds. World Health Organization, Geneva.
 
Ezzati, Majid and Alan D. Lopez. 2004. “Smoking and oral tobacco use.” In Majid Ezzati, Alan D. Lopez, Anthony Rodgers, and Cristopher J.L. Murray, eds.,&nbsp;''Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors''. Geneva: World Health Organization, 883-957.&nbsp; Retrieved 4 Feb 2009, from&nbsp;[http://www.who.int/publications/cra/chapters/volume1/part4/en/index.html http://www.who.int/publications/cra/chapters/volume1/part4/en/index.html].
 
Ezzati, Majid, Alan D. Lopez, Anthony Rodgers, Christopher J.L. Murray, eds. 2004.&nbsp;''Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors''. Geneva: World Health Organization.
 
Fernández-Villaverde, Jesús, and Dirk Kruegger. 2004 (September 14). “Consumption over the Life Cycle: Facts from Consumer Expenditure Survey Data,” unpublished manuscript, University of Pennsylvania and University of Frankfort.&nbsp;&nbsp;[http://www.dklevine.com/archive/refs4506439000000000304.pdf http://www.dklevine.com/archive/refs4506439000000000304.pdf]
 
Fernández-Villaverde, Jesús, and Dirk Kruegger. 2005 (December 19). “Consumption over the Life Cycle: How Important are Consumer Durables?,” unpublished manuscript, University of Pennsylvania and Goethe University.&nbsp;&nbsp;[http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8466457 http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=8466457]
 
Gakidou, Emmanuela, Shefali Oza, Cecilia Vidal Fuertes, Amy Y. Li, Diana K. Lee, Angelica Sousa, Margaret C. Hogan, Stephen Vander Hoorn, and Majid Ezzati. 2007.” Improving Child Survival Through Environmental and Nutritional Interventions: The Importance of Targeting Interventions Toward the Poor.”&nbsp;''Journal of the American Medical Association''&nbsp;298(16): 1876-1887.
 
Hughes, Barry B. and Hillebrand, Evan E. 2006. “Exploring and shaping International Futures”. Boulder, CO: Paradigm Publishers.
 
Hughes, Barry B., Randall Kuhn, Cecilia Peterson, Dale Rothman, and Jose Solorzano. 2011.&nbsp;&nbsp;''Improving Global Health: Patterns of Potential Human Progress, Volume 3''.&nbsp; Paradigm Publishing and Oxford India.
 
Hughes, Barry B. 2005.&nbsp; “Productivity in IFs.” Pardee Center for International Futures Working Paper, University of Denver, Denver, CO.&nbsp;&nbsp;[http://www.ifs.du.edu/documents/reports.aspx http://www.ifs.du.edu/documents/reports.aspx].
 
James, W. Philip T., Rachel Jackson-Leach , Cliona Ni Mhurchu, Eleni Kalamara, Maryam Shayeghi, Neville J. Rigby, Chizuru Nishida, and Anthony Rodgers. 2004.&nbsp; “Overweight and obesity (high body mass index).” In Majid Ezzati, Alan D. Lopez, Anthony Rodgers and Christopher J.L. Murray, eds.,&nbsp;''Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors.''&nbsp;Geneva: World Health Organization, 959-1108.
 
Jamison, Dean T., Jia Wang, Kenneth Hill, and Juan-Luis Londono. 1996. “Income, Mortality and Fertility in Latin America: Country-Level Performance, 1960 - 90.”&nbsp;''Analisis Economico''11(2): 219-261.
 
Kelly, Christopher, Nora Pashayan, Sreetharan Munisamy, and Joshn W. Powles. 2009.&nbsp; “Mortality attributable to excess adiposity in England and Wales in 2003 and 2015: explorations with a spreadsheet implementation of the Comparative Risk Assessment mentodology.”&nbsp;''Population Health Metrics''&nbsp;7(11): 1-7.
 
Lopez, Alan D., Neil E. Collishaw, and Tapani Piha. 1994. “A descriptive model of the cigarette epidemic in developed countries.”&nbsp;''Tobacco Control''&nbsp;3(3): 242-247. &nbsp;
 
Mathers, Colin D., and Dejan Loncar. 2005. "Updated Projections of Global Mortality and Burden of Disease, 2002-2030: Data Sources, Methods and Results." Evidence and Information for Policy Working Paper. World Health Organization, Geneva.
 
Mathers, Colin D., and Dejan Loncar. 2006. "Projections of Global Mortality and Burden of Disease from 2002 to 2030."&nbsp;''PLoS Medicine''&nbsp;3(11): e442, 2011-2030.&nbsp; Retrieved 13 March 2009. doi:10.1371/journal.pmed.0030442.
 
Mathers, Colin D., and Dejan Loncar. 2006b. “New projections of global mortality and burden of disease from 2002 to 2030.” Protocol S1. Technical Appendix to Mathers and Loncar 2006.&nbsp;
 
Mathers, Colin D., and Dejan Loncar. 2006c. “Results of Regressions of Age–Sex-Specific Mortality for Detailed Causes on the Respective Cause Cluster Based on the Full Country Panel Dataset, 1950–2002.” Technical Appendix to Mathers and Loncar 2006.&nbsp;
 
Nixon, John, and Philippe Ulmann. 2006. “The Relationship Between Health Care Expenditure and Health Outcomes: Evidence and caveats for a Causal Link.”&nbsp;''European Journal of Health Economics''&nbsp;7: 7-18.
 
Peto, Richard, Jillian Boreham, Alan D. Lopez, Michael Thun, and Clark Heath, Jr. 1992. “Mortality from Tobacco in Developed Countries: Indirect Estimation from National Vital Statistics.”&nbsp;''Lancet&nbsp;''339(8804): 1268–1278. doi:10.1016/0140- 6736(92)91600-D.
 
Ploeg, Martine, Katja K. H. Aben, and Lambertus A. Kiemeney. 2009. “The Present and Future Burden of Urinary Bladder Cancer in the World.”&nbsp;''World Journal of Urology''&nbsp;27(3): 289-293. doi:[http://dx.doi.org/10.1007/s00345-009-0383-3 &nbsp;10.1007/s00345-009-0383-3&nbsp;]. &nbsp;
 
Shibuya, Kenji, Mie Inoue, and Alan D. Lopez. 2005. “Statistical Modeling and Projections of Lung Cancer Mortality in 4 Industrialized Countries.”&nbsp;''International Journal of Cancer''&nbsp;117(3): 476-485. doi:[http://dx.doi.org/10.1002/ijc.21078 &nbsp;10.1002/ijc.21078&nbsp;]. &nbsp;
 
Smeed, RJ 1949. "Some statistical aspects of road safety research".&nbsp;[http://en.wikipedia.org/wiki/Royal_Statistical_Society ''Royal Statistical Society''], Journal (A) CXII (Part I, series 4). 1-24.
 
Smith, Lisa C. and Lawrence Haddad. 2000. “Explaining Child Malnutrition in Developing Countries: A Cross-Sectional Analysis.” Washington, D.C.: International Food Policy Research Institute.
 
Soares, Rodrigo R. 2007. “On the Determinants of Mortality Reductions in the Developing World.”&nbsp;''Population and Development Review&nbsp;''33(2): 247-287.
 
United Nations Population Division. 2003.&nbsp;''&nbsp;''&nbsp;''World Population Prospects: The 2002 Revision, Highlight.''&nbsp; New York:&nbsp; United Nations. Department of Economics and Social Affairs.
 
United Nations Population Division. 2009.&nbsp;''&nbsp;''&nbsp;''World Population Prospects: The 2008 Revision, Highlights.''&nbsp; New York:&nbsp; United Nations. Department of Economics and Social Affairs.
 
Wagstaff, Adam. 2002. “Inequalities in Health in Developing Countries: Swimming Against the Tide?” Unpublished Manuscript
 
== <span style="font-size:x-large;">Infrastructure Bibliography</span> ==
 
Agénor, Pierre-Richard, Mustapha Kamel Nabli, and Tarik M. Yousef. 2007. “Public Infrastructure and Private Investment in the Middle East and North Africa.” In Mustapha Kamel Nabli, ed.,. Breaking the Barriers to Higher Economic Growth: Better Governance and Deeper Reforms in the Middle East and North Africa. Washington, DC: World Bank Publications, 399–422.
 
Asian Development Bank, Japan Bank for International Cooperation, and World Bank. 2005.&nbsp;''Connecting East Asia: A New Framework for Infrastructure''. Tokyo: Asian Development Bank, Japan Bank for International Cooperation, and World Bank.&nbsp;[http://siteresources.worldbank.org/INTEASTASIAPACIFIC/Resources/Connecting-East-Asia.pdf http://siteresources.worldbank.org/INTEASTASIAPACIFIC/Resources/Connecting-East-Asia.pdf].
 
Bhattacharyay, Biswa Nath. 2010. “Estimating Demand for Infrastructure in Energy, Transport, Telecommunications, Water and Sanitation in Asia and the Pacific: 2010-2020”. Working Paper no. 248. Asian Development Bank Institute, Tokyo.&nbsp;[http://www.adbi.org/working-paper/2010/09/09/4062.infrastructure.demand.asia.pacific/ http://www.adbi.org/working-paper/2010/09/09/4062.infrastructure.demand.asia.pacific/].
 
Bruinsma, Jelle. 2011. “The Resources Outlook: By How Much Do Land, Water and Crop Yields Need to Increase by 2050?” In Piero Conforti, ed.,.&nbsp;''Looking Ahead in World Food and Agriculture: Perspectives to 2050''. Rome: Food and Agriculture Organization of the United Nations (FAO), 233–275.&nbsp;[http://www.fao.org/docrep/014/i2280e/i2280e.pdf http://www.fao.org/docrep/014/i2280e/i2280e.pdf].
 
Calderón, César, and Luis Servén. 2010a. “Infrastructure and Economic Development in Sub-Saharan Africa.”&nbsp;''Journal of African Economies''&nbsp;19(Supplement 1): i13–i87. doi:10.1093/jae/ejp022.&nbsp;[http://jae.oxfordjournals.org/cgi/content/abstract/19/suppl_1/i13 http://jae.oxfordjournals.org/cgi/content/abstract/19/suppl_1/i13].
 
Calderón, César, and Luis Servén. 2010b. “Infrastructure in Latin America”. World Bank Policy Research Working Paper. Report Number 5317. World Bank, Washington, DC.
 
Canning, David. 1998. “A Database of World Stocks of Infrastructure, 1950-1995.”&nbsp;''The World Bank Economic Review''&nbsp;12(3): 529–548.
 
Canning, David, and Mansour Farahani. 2007. “A Database of World Stocks of Infrastructure: Update 1950-2005”. Harvard School of Public Health, Boston, MA.&nbsp;[http://www.hsph.harvard.edu/faculty/david-canning/data-sets/ http://www.hsph.harvard.edu/faculty/david-canning/data-sets/].
 
Cavallo, Eduardo Alfredo, and Christian Daude. 2008. “Public Investment in Developing Countries: A Blessing or a Curse?” RES Working Paper #4597. Inter-American Development Bank (IADB) - Research Department, OECD, Washington, DC.
 
Chatterton, Isabe, and Olga S. Puerto. 2006.&nbsp;''Estimation of Infrastructure Investment Needs in the South Asia Region: Executive Summary''. Washington, DC: World Bank.&nbsp;[http://siteresources.worldbank.org/INTSARREGTOPTRANSPORT/Resources/Inf_Investment_Needs_IC_version4.pdf http://siteresources.worldbank.org/INTSARREGTOPTRANSPORT/Resources/Inf_Investment_Needs_IC_version4.pdf].
 
Congressional Budget Office. 2010.&nbsp;''Public Spending on Transportation and Water Infrastructure''. Washington, DC: Congressional Budget Office.&nbsp;[http://www.cbo.gov/publication/21902 http://www.cbo.gov/publication/21902].
 
Estache, Antonio, and Ana Goicoechea. 2005. “A Research Database on Infrastructure Economic Performance”. Policy Research Working Paper no. 3643. World Bank, Washington, DC.&nbsp;[http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2005/06/16/000016406_20050616100502/Rendered/PDF/wps3643.pdf http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2005/06/16/000016406_20050616100502/Rendered/PDF/wps3643.pdf].
 
Ezzati, Majid, Alan D. Lopez, Anthony Rodgers, and Christopher J. L. Murray, eds. 2004.&nbsp;''Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors''. Geneva, Switzerland: World Health Organization (WHO).
 
Fay, Marianne. 2001. “Financing the Future: Infrastructure Needs in Latin America, 2000-05”. Policy Research Working Paper no. 2545. World Bank, Washington, DC.&nbsp;[http://elibrary.worldbank.org/docserver/download/2545.pdf?expires=1375200693&id=id&accname=guest&checksum=DB7E5FB146EE28C93511B5ADAB2FD3CB http://elibrary.worldbank.org/docserver/download/2545.pdf?expires=1375200693&id=id&accname=guest&checksum=DB7E5FB146EE28C93511B5ADAB2FD3CB].
 
Fay, Marianne, and Tito Yepes. 2003. “Investing in Infrastructure: What Is Needed from 2000 to 2010?” Policy Research Working Paper no. 3102. World Bank, Washington, DC. RePEc.&nbsp;[http://ideas.repec.org/p/wbk/wbrwps/3102.html http://ideas.repec.org/p/wbk/wbrwps/3102.html].
 
Hughes, Barry B. 2007. “Forecasting Global Economic Growth with Endogenous Multifactor Productivity: The International Futures (IFs) Approach”. Pardee Center for International Futures Working Paper, University of Denver. Denver, CO.&nbsp;[http://www.ifs.du.edu/documents/reports.aspx www.ifs.du.edu/documents/reports.aspx].
 
Hughes, Barry B., Devin Joshi, Jonathan Moyer, Timothy Sisk and José Roberto Solórzano. 2014. Strengthening Governance Globally. vol. 5, Patterns of Potential Human Progress series. Boulder, CO, and New Delhi, India: Paradigm Publishers and Oxford University Press.
 
Hughes, Gordon, Paul Chinowsky, and Ken Strzepek. 2009. “The Costs of Adapting to Climate Change for Infrastructure”. Economics of Adaptation to Climate Change Discussion Paper no. 2. World Bank, Washington, DC.
 
International Transport Forum, and Organisation for Economic Cooperation and Development (OECD). 2011. “Trends in Transport Infrastructure Investment 1995-2009”. Paris.
 
Kohli, Harpaul Alberto, and Phillip Basil. 2011. “Requirements for Infrastructure Investment in Latin America Under Alternate Growth Scenarios.”&nbsp;''Global Journal of Emerging Market Economies''&nbsp;3(1): 59 –110. doi:10.1177/097491011000300103.&nbsp;[http://eme.sagepub.com/content/3/1/59.abstract http://eme.sagepub.com/content/3/1/59.abstract].
 
Kim, M. Julie, and Rita Nangia. 2010. “Infrastructure Development in India and China—A Comparative Analysis.” In William Ascher and Corinne Krupp, eds.,.&nbsp;''Physical Infrastructure Development: Balancing The Growth, Equity, and Environmental Imperatives''. New York, NY: Palgrave Macmillan, 97–140.
 
Lora, Eduardo A. 2007.&nbsp;''Public Investment in Infrastructure in Latin America: Is Debt the Culprit?''&nbsp;Inter-American Development Bank Working Paper. Washington, DC: Inter-American Development Bank (IADB) - Research Department.
 
Nelson, Gerald C., Mark W. Rosegrant, Amanda Palazzo, Ian Gray, Christina Ingersoll, Richard Robertson, Simla Tokgoz, Tingju Zhu, Timothy B. Sulser, Claudia Ringler, Siwa Msangi, and Liangzhi You. 2010.&nbsp;''Food Security, Farming, and Climate Change to 2050: Scenarios, Results, Policy Options''. Washington, DC: International Food Policy Research Institute.&nbsp;[http://www.ifpri.org/publication/food-security-farming-and-climate-change-2050 http://www.ifpri.org/publication/food-security-farming-and-climate-change-2050].
 
Organisation for Economic Co-operation and Development. 2006.&nbsp;''Infrastructure to 2030 Volume 1: Telecom, Land Transport, Water and Electricity''. Infrastructure to 2030. Paris: Organisation for Economic Cooperation and Development.
 
Organisation for Economic Co-operation and Development. 2009.&nbsp;''Going for Growth: Economic Policy Reforms''. Paris: Organisation for Economic Cooperation and Development (OECD).
 
Qiang, Christine Zhen-Wei, Carlo M. Rossotto, and Kaoru Kimura. 2009. “Economic Impacts of Broadband.” In World Bank, ed.,.&nbsp;''2009 Information and Communications for Development: Extending Reach and Increasing Impact''. Washington, DC: World Bank, 35–50.
 
Rothman, Dale S. Mohammod T. Irfan, Eli Margolese-Malin, Barry B. Hughes, Jonathan Moyer, and Janet Dickson. 2013.&nbsp;''Building Global Infrastructure.&nbsp;''vol. 4, Patterns of Potential Human Progress series. Boulder, CO, and New Delhi, India: Paradigm Publishers and Oxford University Press. Stambrook, David. 2006. “Key Factors Driving the Future Demand for Surface Transport Infrastructure and Services.” In Organisation for Economic Cooperation and Development (OECD), ed.,.&nbsp;''Infrastructure to 2030 Volume 1: Telecom, Land Transport, Water and Electricity''. Infrastructure to 2030. Paris: Organisation for Economic Cooperation and Development (OECD), 185–239.
 
World Health Organization, and UNICEF. 2013.&nbsp;''Progress on Sanitation and Drinking-Water - 2013 Update''. Geneva: World Health Organization.
 
Yepes, Tito. 2008. “Investment Needs for Infrastructure in Developing Countries 2008-15”. Draft. World Bank, Washington, DC.
 
Yepes, Tito. 2005.&nbsp;''Expenditure on Infrastructure in East Asia Region, 2006–2010''. East Asia Pacific Infrastructure Flagship Study. Manila: Asian Development Bank (ADB), Japan Bank for International Cooperation (JBIC), World Bank.
 
You, Liangzhi, Claudia Ringler, Ulrike Wood-Sichra, Richard Robertson, Stanley Wood, Tingju Zhu, Gerald Nelson, Zhe Guo, and Yan Sun. 2011. “What Is the Irrigation Potential for Africa? A Combined Biophysical and Socioeconomic Approach.”&nbsp;''Food Policy''&nbsp;36(6): 770–782. doi:10.1016/j.foodpol.2011.09.001.&nbsp;[http://www.sciencedirect.com/science/article/pii/S030691921100114X http://www.sciencedirect.com/science/article/pii/S030691921100114X].


== [[Development_Mode_Features|Development Mode Features]] ==
'''Historical Analysis and "Forecasts."''' IFs also includes an extensive and growing historical data base starting in 1960. The data basis allows analysis of relationships among variables across countries and across time.

Latest revision as of 21:36, 2 December 2024

Purposes

The International Futures (IFs) model helps us explore, understand, and shape global questions about future human well-being. The model empowers users to examine past trends to understand the current trajectory we are on, how human, social, and environmental systems interact over time, and how we think about and address the “grand challenges” awaiting the global community.

IFs can help you:

  • Understand the state of major global systems
  • Explore long-term trends and consider where they might take us
  • Learn about the dynamic interactions between global systems
  • Clarify long-term organizational goals/priorities
  • Develop alternative scenarios (if-then statements) about the future
  • Investigate how different groups (households, firms or governments) can shape the future
  • Evaluate the potential impacts of policies

The IFs platform relies on core, underlying assumptions, including the following.

  • Global issues are becoming more significant as the scope of human interaction and human impact on the broader environment grow
  • Goals and priorities for human systems are becoming clearer and are more frequently and consistently communicated
  • Understanding of the dynamics of human systems is improving rapidly
  • The domain of human choice and action is broadening

Which issues can you investigate with IFs? Some examples include:

  • Environment: Atmospheric carbon dioxide levels, world forest area, temperature change
  • Infrastructure: Electricity access, number of fixed broadband subscriptions
  • Health: Life expectancy, HIV prevalence, death rates by category of cause
  • Education: Average years of education, literacy rate
  • Governance: Democracy level, expenditure and spending levels, debt level
  • Human Development: Poverty level, status of women
  • International Relations: Country and regional power levels, interstate conflict likelihood
  • Demographics: Population levels and growth, fertility, mortality, migration
  • Agriculture: Land use and production levels, calorie availability, malnutrition rates
  • Energy: Resource and production levels, demand patterns, fossil fuel usage, renewable energy share
  • Economics: Sectoral production, consumption, trade patterns and structural change

IFs Issues and Modules: Visual Representation

Visual representation of IFs structure

Among the philosophical premises of the International Futures (IFs) project is that the model cannot be a "black box" to users and be truly useful. Model users must be able to examine the structures of IFs in order (1) to have confidence in them, and (2) learn from them.

The following topics are useful starting points for better understanding the model.

IFs Issues and Models: Quick Survey

International Futures is a collection of interconnected models (sometimes referred to as modules). Below is a quick survey of the major models in IFs. For more information on each one, please click on the model headings.

The demographics model:

  • represents 22 age-sex cohorts to age 100+
  • calculates change in fertility and mortality rates in response to income, income distribution, and analysis multipliers
  • computes average life expectancy at birth and represents migration

The economic model:

  • represents the economy in six sectors: agriculture, raw materials, energy, manufactures, services, and ICT (other sectors could be configured, using raw data from the GTAP project)
  • is a general equilibrium-seeking model that does not assume exact equilibrium will exist in any given year; rather it uses inventories as buffer stocks and to provide price signals so that the model chases equilibrium over time
  • contains an endogenous production function that represents contributions to growth in multifactor productivity from R&D, education, worker health, economic policies ("freedom"), and energy prices (the "quality" of capital)
  • multifactor productivity from the production function along with labor and capital stock are the main drivers of the magnitude of production
  • utilizes a "pooled" rather than the bilateral trade approach for international trade
  • computes and uses a social accounting matrix (SAM) that ties economic production and consumption to intra-actor financial flows both domestically and internationally for households, governments, and industry
  • the SAM calculates changes in income distributions based on its projection of household consumption and on the education model's projections of skill level

The agricultural model:

  • represents production, consumption and trade of crops, meat, and fish
  • maintains land use in crop, grazing, forest, urban, and "other" categories; and water use
  • represents demand for food, for livestock feed, and for industrial use of agricultural products
  • is a partial equilibrium model in which food stocks buffer imbalances between production and consumption and determine price changes
  • overrides the agricultural sector in the economic module unless the user chooses otherwise

The energy model:

  • portrays production of six energy types: oil, natural gas, coal, nuclear, hydroelectric, and other renewable
  • represents consumption and trade of energy in the aggregate
  • represents known reserves and ultimate resources of the fossil fuels
  • portrays changing capital costs of each energy type with technological change as well as with draw-downs of resources
  • is a partial equilibrium model in which energy stocks buffer imbalances between production and consumption and determine price changes
  • overrides the energy sector in the economic module unless the user chooses otherwise

The international relations model:

Within countries or geographic groupings

  • represents the prospects for state instability or failure

Between countries or groupings of countries

  • traces changes in power balances across states and regions
  • allows exploration of changes in the level of interstate threat
  • represents possible action-reaction processes and arms races with associated potential for conflict among countries

The governance model:

  • is a two way interaction between governments and the socio-cultural system
  • has three dimensions of governance: capacity, security, and inclusion that closely interact bi-directionally
  • represents the evolution of democracy
  • represents fiscal policy through taxing and spending decisions
  • shows six categories of government spending: military, health, education, R&D, foreign aid, and a residual category

The infrastructure model:

  • forecasts the demand of infrastructure and the funding available to meet the demand
  • forecasts levels of infrastructure based on this demand and funding constraint
  • measures access to key infrastructures like water, electricity, or broadband
  • maintains and calculates changes in physical stocks like percentage of roads paved, and area equipped with irrigation

The health model:

  • forecasts age, sex, and health indicators related to 15 causes of death modeled in IFs
  • splits causes of death into three cause groups: communicable, maternal, perinatal, and nutritional conditions; noncommunicable diseases; and injuries
  • is driven by education, technology, and income

The education model:

  • projects educational participation and attainment across primary, secondary, and tertiary levels for each country in IFs
  • determines attainment and participation through the demand for education and the investment in education by governments
  • has educational demand based on income while educational investment is a result of government spending
  • models the rates of dropout, completion, and transition to the next level of schooling

The environmental model:

  • is distributed throughout the overall model
  • allows tracking of remaining resources of fossil fuels, of the area of forested land, of water usage, and of atmospheric carbon dioxide emissions

The implicit technology model:

  • is distributed throughout the overall model
  • allows changes in assumptions about rates of technological advance in agriculture, energy, and the broader economy
  • explicitly represents the extent of electronic networking of individuals in societies
  • is tied to the governmental spending model with respect to R&D spending 
  • represents changes in social conditions of individuals (like fertility rates or literacy levels), attitudes of individuals (such as the level of materialism/postmaterialism of a society from the World Value Survey), and the social organization of people (such as the status of women)

IFs Background

International Futures (IFs) has evolved since 1980 through eight "generations," with the eighth generation now taking form.

The first generation had deep roots in the world models of the 1970s, including those of the Club of Rome. In particular, IFs drew on the Mesarovic-Pestel or World Integrated Model (Mesarovic and Pestel 1974). The author of IFs had contributed to that project, including the construction of the energy submodel. IFs consciously also drew on the Leontief World Model (Leontief et al. 1977), the Bariloche Foundation’s world model (Herrera et al. 1976), and Systems Analysis Research Unit Model (SARU 1977), following comparative analysis of those models by Hughes (1980). That generation was written in FORTRAN and available for use on main-frame computers through CONDUIT, an educational software distribution center at the University of Iowa. Although the primary use of that and subsequent generations was by students, IFs has always had some policy analysis capability that has appealed to specialists. For example, the U.S. Foreign Service Institute used the first generation of IFs in a mid-career training program.

The second generation of International Futures moved to early microcomputers in 1985, using the DOS platform. It was a very simplified version of the original IFs without regional or country differentiation.

The third generation, first available in 1993, became a full-scale microcomputer model. The third generation improved earlier representations of demographic, energy, and food systems, but added new environmental and socio-political content. It built upon the collaboration of the author with the GLOBUS project, and it adopted the economic submodel of GLOBUS (developed by the author). GLOBUS had been created with the inspiration of Karl Deutsch and under the leadership of Stuart Bremer (1987) at the Wissenschaftszentrum in Berlin.

The third generation produced three editions/major releases of IFs, each accompanied by a book also called International Futures (Hughes 1993, 1996, 1999). The second edition moved to a Visual Basic platform that allowed a much improved menu-driven interface, running under Windows. The third edition incorporated an early global mapping capability and an initial ability to do cross-sectional and longitudinal data analysis.

The fourth generation took shape since early 2000. It was heavily influenced by the usage of the model by several important organizations for policy-analysis. First, General Motors commissioned a specialized version of IFs named CoVaTrA (Consumer Values Trends Analysis) with a need for updated and extended demographic modeling and representation of value change. An alliance was established with the World Values Survey, directed by Ronald Inglehart, to create that version. Second, the Strategic Assessments Group of the Central Intelligence Agency commissioned a specialized version named IFs for SAG. The work involved in preparing that greatly extended and enhanced the socio-political representations of the model, both domestic and international. Third, the European Commission sponsored a project named TERRA which has led to a specialized version named IFs for TERRA. The IFs for TERRA work led to enhancements across the model, including improved representation of economic sectors, updated IO matrices and a basic Social Accounting Matrix, GINI and Lorenz curves, and preparing for extended environmental impact representation (drawing upon the Advanced Sustainability Analysis framework of the Finland Futures Research Center).

The fourth generation of IFs also had a heavy emphasis on enhancing usability. Ideas from Robert Pestel in the TERRA project led to the creation of a new tree-structure for scenario creation and management. Ideas from Ronald Inglehart led to the development of the Guided Use structure and a somewhat more game-like character within that structure. Inglehart also helped to arrange funding to support the programming of Guided Use through the European Union Center of the University of Michigan.

The fifth generation of IFs (from 2004-2009) focused on improving the model, its usability, and transparency. Model improvements included clearer and more extensive representations of the agent classes and their points of leverage, stemming from the desire to make the modeling system a more valuable scenario-testing and policy analysis tool. The further elaboration of the social accounting matrix, structure, the development of education and health sub-models, and the substantial redesign of an economic production function with endogenous multifactor productivity were all outcomes of this version.

Efforts to enhance the models usability included the addition of a number of specialized displays, such as those for seeing the social accounting matrices, to display progress towards the Millennium Development Goals, to explore poverty at different income levels, and to represent the educational attainment of population cohorts. Mapping and data analysis tools were also strengthened. The ability to drill down into select countries to explore futures at the state or province-level was also added. Packaged Displays and Flex Packaged Displays were introduced that allowed for the creation of very specific lists of countries/regions, groups or G-lists. Greater transparency came from adding the ability for users to access the flow charts, equations, and code underlying the model.

The fifth version was the first version of this software to be placed online due to the help of the National Intelligence Council (http://www.ifs.du.edu). New scenarios were created for UNEP (focusing on environmental change) and Pardee (focusing on poverty). Finally, one of the largest changes made was incorporating 182 countries into the Base-Case scenario used by IFs. Previous versions of IFs used broader regions to forecast global trends. This change also did away with the Student and Professional versions.

The sixth generation of IFs began in 2010 and revolved around the development of the Patterns of Potential Human Progress (PPHP) series. The PPHP volumes, with their focus on major human development systems, spurred the further enhancement of the model’s major subsystems, especially population, economic (especially poverty representation), education, health, infrastructure, and governance. The supporting documentation required for the PPHP series also gave rise to efforts to create the most detailed documentation of the model to date.

The seventh generation officially began in 2014. This generation emerged after the PPHP volumes and with the advent of a variety of new projects, including wider support for provincial and state breakdowns, new means of forecasting diplomatic and power interactions, and enhanced representations in many of the IFs modules. Central to the institute's efforts this version also had continuous improvements in the existing elements of the model and usability. The sixth generation greatly strengthened the web-based version and it will increasingly become central to our work in the current generation.

The current (eighth) generation is primarily distinguished by a transition in the underlying coding language, shifting from Visual Basic 6 to Visual Basic .NET. This shift has facilitated the integration of both online and standalone user interfaces, streamlining the process of implementing interface modifications. Moreover, the adoption of this new underlying language and user interface has empowered developers to leverage a broader range of third-party applications and dynamic visualization tools, while aligning with Microsoft-supported languages.

Geographic Representation of the World

188 countries underpin the functioning of IFs and these countries can be displayed separately or as parts of larger groups that users can determine.

Below is a visual representation of how different entities are organized into Countries/Regions, Groups or Glists:

Visual representation of IF's definition of regions/countries/groups/glists

*Note: In older versions of IFs, Regions were used as intermediaries between Countries and Groups. In the future, they, or some similarly named unit, will be a sub-unit of Countries. Regions, acting as a sub-unit of Countries, are currently not a feature of IFs. See the image located at the bottom of this Help topic.

When using IFs, there are many occasions where the user is asked whether or not they would like to display their results as a product of single countries, or larger groups. This is typically a toggle switch that moves between Country/Region and Groups, however, it might be a three-way-toggle that includes Country/Region, Group and Glist.

Countries/Regions are currently the smallest geographical unit that users can represent. The ability to split countries down into smaller regions, or states, is under development. There are 188 different countries/regions that users can display.

Groups are variably organized geographically or by memberships in international institutions/regimes. You can find out who is represented in each group and add or delete members by exploring the Managing Regionalization function.

Glists merge both Groups and Countries/Regions. These lists are mostly geographically bound. In the future, the Glist distinction will become more important as some users may want to place, for example, both the Indian state of Kerala in a Glist with Sri Lanka and Nepal.

Users may also want to create their own groups or explore what countries are members of what groups.

IFs Time Horizon

Future Forecasts. IFs begins computation with data from 2020 and can dynamically calculate values for all variables annually through 2100.

Historical Analysis and "Forecasts." IFs also includes an extensive and growing historical data base starting in 1960. The data basis allows analysis of relationships among variables across countries and across time.

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