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This paper reviews the small but growing literature on intergenerational educational mobility in the developing world. Education is a critical determinant of economic well-being, and it predicts a range of non-pecuniary outcomes such as marriage, fertility, health, crime, and political attitudes. We show that developing nations feature stronger intergenerational educational persistence than high-income countries, in spite of substantial educational expansion in the last decades. We consider variations in mobility across gender and region, and discuss the macro-level correlates of educational mobility in developing countries. The paper also discusses the literatures on (i) concepts and measures of educational mobility, (ii) theoretical perspectives to understand educational persistence across generations, (iii) the role that education plays in the economic mobility process, and (iv) differences in the type and quality of education as vehicles for intergenerational persistence, and it applies these literatures to understand educational mobility in the developing world.

"In Change Leadership for Developing Countries, Franca Ovadje offers readers a comprehensive and integrative model for the design, implementation and evaluation of organizational change. This unique book embodies an African perspective, discussing the specific needs and issues associated with leading change within the institutional, economic, social, and cultural context of developing economies. Based on extensive research, as well as the first-hand experiences of managers who have led change initiatives in Africa, this book envisions a change leadership model based on conscious decision-making, rather than taking a prescriptive approach. With examples and case studies drawn from African organizations, this book is a vital tool for students and managers who are based in (or interact with) emerging economies"--

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.

Globalization means that today, more than ever before, growth in developing countries and the reduction of poverty depend on world trade and a well functioning trading system. This volume reviews developing countries' trade policies and institutions, and the challenges they face in the World Trade Organization where the rules that govern the international trading system are set

Relying on an original data set on international migration by educational attainment for 1990 and 2000, we analyze the determinants of the brain drain from developing countries. We start from a simple decomposition of the brain drain in two multiplicative components, the degree of openness of sending countries (as measured by their average emigration rate) and the schooling gap (as measured by the relative education level of emigrants compared to natives). Using various regression models, we put forward the determinants of these components and explain cross-country differences in skilled migration. Unsurprisingly, the brain drain is strong in small countries which are not too distant from the major OECD regions, which share colonial links with OECD countries and which send most of their migrants to host countries where quality-selective immigration programs exist. More interestingly, the brain drain increases with political instability and the degree of fractionalization at origin; it globally decreases with natives' human capital.

Relying on an original data set on international migration by educational attainment for 1990 and 2000, we analyze the determinants of the brain drain from developing countries. We start from a simple decomposition of the brain drain in two multiplicative components, the degree of openness of sending countries (as measured by their average emigration rate) and the schooling gap (as measured by the relative education level of emigrants compared to natives). Using various regression models, we put forward the determinants of these components and explain cross-country differences in skilled migration. Unsurprisingly, the brain drain is strong in small countries which are not too distant from the major OECD regions, which share colonial links with OECD countries and which send most of their migrants to host countries where quality-selective immigration programs exist. More interestingly, the brain drain increases with political instability and the degree of fractionalization at origin; it globally decreases with natives' human capital.

Intro -- Foreword -- Foreword -- Acknowledgments -- Introduction -- Contents -- Part I: Africa Today -- 1: Health in Sub-Saharan Africa: HIV, TB and Malaria Epidemiology -- 1.1 Global HIV, TB and Malaria Incidence and Mortality Rates -- 1.2 HIV/AIDS: Epidemiological Perspective -- 1.3 TB: Epidemiological Perspective -- 1.4 Malaria: Epidemiological Perspective -- Bibliography -- 2: Chronic-Degenerative Diseases in Sub-Saharan Africa -- 2.1 The Incidence of Chronic Diseases in the World -- 2.2 Chronic-Degenerative Diseases in Medium-Low-Income Countries -- 2.3 Cardiovascular Diseases: A Model of Chronic-Degenerative Disease on the Increase in Countries in Sub-Saharan Africa -- 2.4 Metabolic Diseases: Diabetes in Sub-Saharan Africa -- References -- References with no reference to the text -- Part II: DREAM 2.0 -- 3: From DREAM to DREAM 2.0: An African Model -- 3.1 The Origin of the DREAM Programme -- 3.2 DREAM 2.0: The Growth of the Programme -- References -- 4: The DREAM Management Software -- 4.1 DREAM Software -- 4.2 Social Data Management -- 4.3 Managing and Monitoring the Appointments -- 4.4 Dispensing Drugs -- 4.5 Clinical Dashboard -- 4.6 Monitoring Children´s Psychophysical Development -- 4.7 Clinical Evidence and Management Tools -- 4.8 The Technological Help Desk -- References -- 5: DREAM Centre Remote Telemonitoring -- References -- 6: DREAM Data Activity -- References -- 7: DREAM 2.0 A Replicable Model -- 7.1 DREAM Replicable -- 7.1.1 Excellence -- 7.1.2 The Centrality of the Patient -- 7.1.3 A Caring Community -- 7.1.4 Health Is Not Only Healthcare -- 7.1.5 The Patients as Central Figures -- 7.1.6 The Fight Against Malnutrition -- 7.1.7 Light Healthcare -- 7.1.8 Free of Charge -- References -- 8: The Challenge of Sustainability: The Impact of DREAM Programme on the Social, Economic and Working Conditions of Patients w...