Brain Drain in Developing Countries

Brain Drain in Developing Countries Frederic Docquier, Olivier Lohest, and Abdeslam Marfouk An original data set on international migration by educational attainment for 1990 and 2000 is used to analyze the determinants of brain drain from developing countries. The analysis starts with a simple decomposition of the brain drain in two multiplicative components, the degree of openness of sending countries (measured by the average emigration rate) and the schooling gap (measured by the education level of emigrants compared with natives). Yet recent theoretical studies emphasize several compensatory effects, showing that a limited but positive skilled emigration rate can be beneficial for sending countries (Commander, Kangasniemi, and Winters 2004; Docquier and Rapoport 2007; Beine, Docquier, and Rapoport 2001, forthcoming; Schiff 2005 provides a critical appraisal of this literature). However, without reliable comparative data Frederic Docquier (corresponding author) is a research associate at the National Fund for Economic Research; professor of economics at the Universite Catholique de Louvain, Belgium; and research fellow at the Institute for the Study of Labor, Bonn, Germany; his email address is docquier ires.ucl.ac.be. Olivier Lohest is a research is a researcher at the Institut Wallon de l'Evaluation, de la Prospective et de la Statistique, Regional Government of Wallonia Section I presents the data set on the brain drain, as measured by the emigration rate of post-secondary-educated workers, and describes the average brain drain from developing countries by income group and country size. Section II decomposes the brain drain into two multiplicative components: the degree of openness, measured by the average emigration rate of workingage natives, and the schooling gap, measured by the relative education attainment of emigrants compared with natives. 202 THE WORLD BANK ECONOMIC REVIEW The Docquier Marfouk (2006) study, which collected census, registry, and survey data from all OECD countries, enables the size of these biases for developing countries to be evaluated. 40 million) 1990 Worlda High-income countries Developing countries Low-income countries Lower medium-income countries Upper-medium-income countries Least developed countries Landlocked developing countries Small island developing economies Large developing countries (. Cross-Section Regression Results (2000 data) OLS-1 General model Variable Country size Native population (logs) Small island developing economies Level of development Proportion of post-secondary educated natives  100 (logs) GNI per capita (logs) Least developed country Oil exporting country Sociopolitical environment Political stability Government effectiveness Religious fractionalization Geographic and cultural proximity Distance from selectiveimmigration countries (logs) Distance from EU15 countries ( The analysis starts with a simple multiplicative decomposition of the brain drain into two components: degree of openness of sending countries, as measured by average or total emigration rate, and schooling gap, as measured by the relative education level of emigrants compared with natives.

Bibliographic Details

Main Authors:	Docquier, Frédéric, Lohest, Olivier, Marfouk, Abdeslam
Format:	Journal Article biblioteca
Published:	World Bank 2007-05-30
Subjects:	Brain Drain, Developing Countries, educational attainment, human capital, immigration, international migration, migrants, political instability, skilled workers, small countries,
Online Access:	http://hdl.handle.net/10986/4454
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