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Global Income Distribution Dynamics (GIDD)

  • About the tool
  • Methodology
  • Dataset
  • Applications
  • Core Team
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Economists have long been interested in measuring the effects of economic policies on poverty and on the distribution of welfare among individuals and households.

Devising satisfactory methods for accurate evaluations has proven to be a difficult task.

Progress in economic analysis and the growing availability of microeconomic household data have improved the situation. At the same time, however, calls for rigorous assessment have intensified. Partly because of the fierce debate on the social effects of globalization, economic policy objectives and social demands have increasingly focused on poverty reduction and distribution outcomes.

Policy makers have become aware that the selection and implementation of economic policies require a careful assessment of their effects both on aggregate economy wide variables—such as employment, inflation, or real GDP growth— and on income distribution and poverty. Modern macro-micro simulation techniques, which, with different degrees of integration, combine macro and micro modeling frameworks, are the most promising tool for providing that careful assessment.

In this context, the World Bank Development Economics Department (DEC) has developed 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. Academics and development practitioners can use the GIDD 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). The GIDD also allows analyzing 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.

We strongly recommend visitors to take a look into the Applications section to see our current research agenda. Feel free to contact us for questions and suggestions about the GIDD at globaltrends@worldbank.org.

The macro-micro modeling framework described here explicitly considers long term time horizons during which changes in the demographic structure may become a crucial component of both growth and distribution dynamics. The GIDD’s empirical framework is schematically represented in this figure.

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The expected changes in population structure by age (upper left part of the figure) are exogenous, meaning that 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 (linking arrow from top left box to top right box in the figure).

Next, 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 (larger box in the middle of the figure). The impact of changes in the demographic structure on labor supply (by skill level) is incorporated into the CGE model, which then provides a set of link variables for the micro-simulation:

  • (a) change in the allocation of workers across sectors in the economy,
  • (b) change in returns to labor by skill and occupation,
  • (c) change in the relative price of food and non-food consumption baskets, and
  • (d) 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 (bottom link in the figure).

The GIDD’s methodology is explained in full detailed in the following working paper:

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.

While the literature has made important strides in addressing what constitutes an appropriate measure of inequality, analyses of global income distribution are still plagued with serious data problems, including the limitations of traditional databases and the poor comparability of data despite some obvious improvements in the availability of income inequality data mainly spawned by the pioneering work of Deininger and Squire (1996).

Given the recent considerable interest and concern about the distributional effects of increasing globalization, there is even a more present need for reliable datasets that permits meaningful comparison of inequality not only within countries but across regions and nations. Even in the presence of a reliable global income distribution dataset, in the absence of global determinants of household income (such as educational attainment, age, household size and composition, occupation of the household head, etc.) there is little scope for understanding the causes behind the global inequality we observed.

The GIDD database is not a mere compilation of secondary cross-country inequality indices. Instead, it is an actual presentation of a truly global income distribution based entirely on household survey data. Additionally, the GIDD global income distribution data includes information on the conditional distribution of important household income determinants like education, age, household size, among others.

The dataset version 1.0 is available as an EXCEL file (583 KB) or as a STATA zip file (86 KB).

Our ultimate goal is to assemble existing representative household data for all countries on the globe, standardize them so that they are internationally comparable, and make the minimal distribution data available to researchers in a ready-to-use format for the analysis of global income distribution. This goal is motivated by the publicly non-availability of data on global income distribution (and its determinants) limiting the ability of researchers to identify the positions of each country in the global income distribution.

A full description of how the GIDD dataset was constructed is available from:

Ackah, Charles, Maurizio Bussolo, Rafael De Hoyos, and Denis Medvedev (2009), “A New Dataset on Global Income Distribution,” Unpublished. The World Bank.

The GIDD framework has been used to answer questions in various topics. Here are some examples of the kind of findings can be generated from a GIDD-based analysis.

Prospects for Global Inequality and Global Middle Class 

1. 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.

Presentation prepared for the World Bank’s 2008 Economist Forum, April 17, Washington, D.C.

2. 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.

Presentation prepared for the WIDER project meeting on “Southern Engines of Growth”, 12-13 January 2007, Beijing, China.

Agricultural Distortions

3. 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.

Presentation prepared for the 11th annual GTAP conference 12-14 June 2008, Helsinki, Finland.

Climate Change 

4. 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.

Presentation prepared for the 11th annual GTAP conference 12-14 June 2008, Helsinki, Finland.

Food Prices and Poverty 

5. 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.

Presentation of this and other findings on the poverty effects of higher food prices prepared for a conference on "Food and Fuel Price Increase: Implications for Trade and Food Security Policies," held on October 2, 2008 at the World Bank in Washington, D.C.

The GIDD has also been used in the Global Economic Prospects 2007 and 2009:
• Global Economic Prospects 2007: Managing the Next Wave of Globalization.
• Global Economic Prospects 2009: Commodity Markets at the Crossroads.

For questions not covered in this site, please contact us at: globaltrends@worldbank.org.

The team responsible for development of this tool 

Maurizio Bussolo has been working at the World Bank since 2003, working on quantitative analyses of economic policy and development including: poverty, income distribution, labor markets, remittances, international trade, Millennium Development Goals, agriculture, environment. Among his other activities, he monitors and forecasts macroeconomic trends in Latin America and the Caribbean and has worked on several Economic and Sector Work projects with some very poor countries in Sub-Saharan Africa (Chad, Ghana, Ethiopia) and lower to middle income countries in Latin America (Brazil, Colombia, Nicaragua, Honduras, Panama). Before joining the World Bank, he worked at the OECD Development Centre, was previously research fellow at the Overseas Development Institute in London, and before economist at Fedesarrollo and professor at the University Los Andes in Bogotá Colombia. He has published in international journals and his recent publications include: “The Impact of Macroeconomic Policies on Poverty and Income Distribution – Macro-Micro Evaluation Techniques and Tools” jointly edited with Francois Bourguignon and Luiz Pereira da Silva. He holds a PhD in economics from the University of Warwick, UK.

Rafael E. De Hoyos participated in the GIDD project from 2006 to 2008 as a researcher for the Development Economics Prospects Group at the World Bank. In 2008, he became the chief of advisers to the under-minister of education in Mexico. Previously, Mr. De Hoyos was a research fellow at the Judge Business School in the University of Cambridge. He has worked as a consultant to the UN Economic Commission for Latin America and the Caribbean in Mexico and at the UN World Institute for Development Economics Research in Finland. Mr. De Hoyos holds a PhD in economics from the University of Cambridge. His main research has focused on the economics of income inequality and how this is linked with the process of globalization.

Denis Medvedev participated in this project as a Young Professional with the Development Prospects Group of the World Bank. His responsibilities included working on international trade issues and the Millennium Development Goals. He worked on several of the World Bank's Global Economic Prospects reports, and was previously a consultant at the IFC. He holds a Ph.D. from American University.

Israel Osorio Rodarte is currently a consultant with the World Bank's Development Prospects Group. As part of the Infrastructure and Modeling Team, his main duty consists of estimating the distributional impacts of macroeconomic shocks at the micro-level. He also contributes to the unit's macroeconomic forecast and has vast experience on the economics of innovation and structural change. Prior to joing the World Bank, he was a graduate student at the Georgetown Public Policy Institute and at Mexico’s Tecnológico de Monterrey.




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