The Development Prospects Group of the World Bank has developed a broad set of tools for forecasting and policy analysis in the areas of macro-economics, trade, finance, income distribution, and country strategies.

• The Global Income Distribution Dynamic (GIDD) model, is a global CGE-microsimulation framework that takes into account the macro nature of growth and integrates a microeconomic (that is, individual and household) dimension. By including 121 countries and covering 90 percent of the world population, the GIDD is the first macro-micro global simulation model.

• The Global Linkage model is a global dynamic computable general equilibrium model which supports global trade policy analysis.

• iSimulate is a platform for performing collaborative economic simulations across the internet. It currently hosts a number of experimental World Bank economic models, including a 150+ country global macroeconomic forecasting model, a model simulating terms-of-trade shocks, and a potential output model.
• MAMS (Maquette for MDG Simulations) tool is a dynamic Computable General Equilibrium (CGE) model designed for country-level analysis of medium- and long-run development policies, including strategies for reducing poverty and achieving the Millennium Development Goals (MDGs).
• The ENVISAGE model is designed to analyze a variety of issues related to the economics of climate change

Global Income Distribution Dynamic (GIDD) model

The Global Income Distribution Dynamics (GIDD), the first global CGE-microsimulation model. The GIDD takes into account the macro nature of growth and of economic policies and adds a microeconomic—that is, household and individual—dimension to it. The GIDD includes distributional data for 121 countries and covers 90 percent of the world population.

Functions

• To assess growth and distribution effects of global policies such as multilateral trade liberalization, policies dealing with international migration and climate change, among others (see the applications section of this webpage).
• To analyze the impacts on global income distribution from different global growth scenarios and to distinguish changes due to shifts in average income between countries from changes attributable to widening disparities within countries.

Applications

• Prospects for Global Inequality and Global Middle Class
• Bussolo, M., De Hoyos, R., and Medvedev, D. (2008). “Is the Developing World Catching Up? Global Convergence and National Rising Dispersion” Policy Research Working Paper Series 4733, The World Bank.
• Bussolo, M, De Hoyos, R., Medvedev, D. and van der Mensbrugghe, D. (2007). “Global growth and distribution: are China and India reshaping the world?,” Policy Research Working Paper Series 4392, The World Bank.
• Agricultural distortions
• Bussolo, M., De Hoyos, R., and Medvedev, D. (forthcoming) “Global Income Distribution and Poverty in the Absence of Agricultural Distortions” in K. Anderson, J. Cockburn, and W. A. Martin, ed. “Agricultural Price Distortions, Inequality and Poverty” Palgrave and The World Bank.
• Climate change
• Bussolo, M, De Hoyos, R., Medvedev, D. and van der Mensbrugghe, D. (2008). “Global climate change and its distributional impacts” paper presented at the 11th annual GTAP conference 12-14 June 2008, Helsinki, Finland.
• Food prices and poverty
• Dessus, S., S. Herrera, and R. de Hoyos. (forthcoming) “The Impact of Food Inflation on Urban Poverty and Its Monetary Cost: Some Back-of-the-Envelope Calculations.” Agricultural Economics. 

Methodology

• Step 1: Socio-demographic changes and educational changes
• The expected changes in population structure by age are exogenous (i.e. fertility decisions and mortality rates are determined outside the model)
• The change in shares of the population by education groups incorporates the expected demographic changes
• New sets of population shares by age and education subgroups are computed and household sampling weights are re-scaled according to the demographic and educational changes above
• Step 2:  Macroeconomic changes
• The impact of changes in the demographic structure on labor supply (by skill level) is incorporated into the CGE model because these changes are likely to have important consequences for economic growth and the distribution of  income  within a given country.
• Hence, LINKAGE (a "relatively" standard CGE model) model is used such that a series of end-of-period equilibriums are linked with a set of equations that update the main macro variables.
• This provides a set of link variables for the microsimulation
• Step 3: Labor reallocation
• The above CGE model microsimulation predicts:
  
• Change in the allocation of workers across sectors in the economy (ex: agriculture v manufacturing)
• Change in returns to labor by skill and occupation

• Step 4: Income Assignment
• The  final step in the GIDD microsimulation is to adjust factor returns by skill and sector, as well as the average income/consumption per capita, in accordance with the results of the CGE model. The model predicts:
• Change in the relative price of food and non-food consumption baskets
• Differentiation in per capita income/consumption growth rates across countries. The final distribution is obtained by applying the changes in these link variables to the re-weighted household survey

• Full explanation:

Bussolo, M., R. de Hoyos, and D. Medvedev (2010). "Economic Growth and Income Distribution: Linking Macro Economic Models with Household Survey Data at the Global Level," International Journal of Microsimulation, 3 (1), 92-102.

MAMS (Maquette for MDG Simulations)

MAMS (Maquette for MDG Simulations) is a dynamic Computable General Equilibrium (CGE) model that has been extended to cover the generation of outcomes in terms of growth, MDGs, and the educational make-up of the labor force, as well as the interaction of these outcomes with other aspects of economic performance. The tool allows for economy-wide, country-level analysis of medium- and long-run development policies, including strategies for reducing poverty and achieving the Millennium Development Goals (MDGs). 

Methodology

The government policies that are considered include:

• spending: its level and allocation across different areas (including education, health, and infrastructure);
• financing: policies for taxation, domestic and foreign borrowing, and foreign aid.

Economic performance is measured by the evolution of:

• poverty and other MDG targets;
• macro indicators:
• GDP (split into private and government consumption and investment; exports; imports);
• the composition of the government budget, the balance of payments, and the savings-investment balance;
• total factor productivity;
• domestic and foreign debt stocks.
• sectoral structure of production, employment, incomes, and trade;
• the labor market: unemployment; educational composition of the labor force.

MAMS is a flexible tool that can be run in different versions that differ in data needs. For example, for analysis of macro issues, it is sufficient to use a version with minimal data needs; analysis of MDG strategies requires a version with additional sectoral disaggregation and a more detailed database.

Applications

• Lofgren, Hans, and Praveen Kumar. 2007. The Challenges of Achieving Kenya’s Vision 2030: A Macro Perspective (137 KB). Draft. August.
• Kiringai, Jane, and Jörgen Levin. 2008. Achieving The MDGs in Kenya with Some Aid and Reallocation of Public Expenditures (177 KB). Working Paper No. 10, Swedish Business School at Örebro University.
• World Bank. 2008. Kenya: Accelerating and Sustaining Inclusive Growth (8.95 MB). Policy Note. Report no. 42844-KE. Poverty Reduction and Economic Management Unit 2. Country Department for Kenya. Africa Region. (For MAMS-related materials, prepared by Hans Lofgren and Praveen Kumar, see pp. 24 and 101-104.). World Bank. Washington, D.C.

Resources

This page provides other resources relevant to country-level -development strategy analysis with a focus on MDGs as well as links to other websites with more materials.

Selected Background Resources

• Burfisher, Mary E.. 2011. Introduction to Computable General Equilibrium Models. New York: Cambridge University Press.
• Dervis, Kemal, Jaime de Melo, and Sherman Robinson. 1982. General Equilibrium Models for Development Policy World Bank Research Publication, Report no. 10173. Washington, D.C.: World Bank.
• Francois, Joseph F., and Kenneth A. Reinert. 1998. Editors. Applied Methods for Trade Policy Analysis: A Handbook. New York: Cambridge University Press.
• Hosoe, Nobuhiro, Kenji Gasawa, and Hideo Hashimoto (2010). Textbook of Computable General Equilibrium Modeling: Programming and Simulations. New York: Palgrave MacMillan.
• Lofgren, Hans, Rebecca Lee Harris, and Sherman Robinson, with assistance from Moataz El-Said and Marcelle Thomas. 2002. A Standard Computable General Equilibrium (CGE) Model in GAMS. Microcomputers in Policy Research, Vol. 5. Washington, D.C.: IFPRI.
• Robinson, Sherman and Hans Lofgren. 2008. Economy-Wide Models and Poverty Analysis. Presentation delivered by Sherman Robinson at the WIDER Conference “Frontiers of Poverty Analysis,” held in Helsinki, Finland, September 26-27.
• TIPS (Trade and Industrial Policy Strategies), Pretoria, South Africa. Downloadable materials used for the 2007 "Introductory Course on Computable General Equilibrium Modeling", offered by Dirk Ernst van Seventer and Rob Davies.
• van der Mensbrugghe, Dominique. 2005. Prototype Model for a Single Country Real Computable General Equilibrium Model. Development Prospects Group, World Bank.

Additional World Bank Materials

• Data and Research. Entry point to main World Bank unit for development economics, divided into Data, Research, and Prospects.
• Poverty Reduction and Economic Management Network. Entry point to the Bankwide network, divided into Poverty Reduction, Economic Policy and Debt, Public Sector Governance, Trade, Gender and Development, and Global Development Architecture
• Millennium Development Goals (MDGs). Data and links to resources on the MDGs.
• Global Monitoring Report. Annual report on the MDGs produced by the World Bank and the International Monetary Fund (IMF).
• Information by countries and regions. Search engine providing access to World Bank documents classified by country and region.
• The site Tools and Methods for PSIA (Poverty and Social Impact Analysis) provides information about selected tools for the analysis of the impacts of reforms.
• The Human Development (HD) Network provides resources on health, education and other HD areas, including materials relevant to Public Expenditure Reviews.

Additional Resources

• EcoMod Network. The Network, which is global, promotes model-based policy analysis. Among other things, website provides information about its activities, including courses and conferences.
• General Algebraic Modeling System (GAMS). MAMS and many other CGE models are written in GAMS, a system for mathematical programming and simultaneous equation modeling. The website of the GAMS Development Corporation provides access to documentation, manuals and the software (a license is required to be able to solve anything but small models).
• Global Trade Analysis Project (GTAP). GTAP is a global collaborative network that promotes model-based policy analysis and database development, both global and at the country level. Its website is an excellent source of data, documents and research outputs.
• International Food Policy Research Institute (IFPRI). The IFPRI website provides access research in the food policy area. Of particular interesty for economywide modeling are the Discussion Papers of the Trade and Macroeconomics Division and IFPRI's repository of Social Accounting Matrices (SAMs).
• Poverty and Economic Policy (PEP) Research Network. PEP promotes research by developing country researchers working to reduce poverty. Its Modeling and Policy Impact Analysis (MPIA) network provides access to working papers, training materials, and software related to country-level macro-micro analysis.