Understanding why so many people across the world are so poor is one of the central intellectual challenges of our time. What explains a pattern of extreme destitution for billions combined with plutocratic levels of income for a tiny minority? This book offers a novel approach to addressing these areas by providing the tools and data that will enable students, researchers and professionals to investigate these issues.
Understanding why so many people across the world are so poor is one of the central intellectual challenges of our time. What explains a pattern of extreme destitution for billions combined with plutocratic levels of income for a tiny minority? This book offers a novel approach to addressing these areas by providing the tools and data that will enable students, researchers and professionals to investigate these issues.
Måns Söderbom is a Professor of Economics at the Department of Economics, School of Business, Economics and Law, University of Gothenburg, Sweden. Francis Teal is Research Associate, CSAE, University of Oxford and Managing Editor Oxford Economic Papers, UK. Markus Eberhardt is Assistant Professor in Economics, School of Economics, University of Nottingham, UK. Simon Quinn is Associate Professor in Economics and Deputy Director of the Centre for the Study of African Economies, Department of Economics, University of Oxford, UK. Andrew Zeitlin is Assistant Professor at the McCourt School of Public Policy, Georgetown University, USA.
Inhaltsangabe
I. Linking Models to Data for Development 1. An Introduction to Empirical Development Economics 2. The Linear Regression Model and the OLS Estimator 3. Using and Extending the Simple Regression Model 4. The Distribution of the OLS Estimators and Hypothesis Testing 5. The Determinants of Earnings and Productivity 6. Modelling Growth with Time Series Data 7. The Implications of Variables Having a Unit Root 8. Exogenous and Endogenous Growth 9. Panel Data: An Introduction 10. Panel Estimators: POLS, RE, FE, FD 11. Instrumental Variables and Endogeneity 12. The Progamme Evaluation Approach to Development Policy 13. Models, Experiments and Calibration in Development Policy Analysis II. Modeling Development 14. Measurement, Models and Methods for Understanding Poverty 15. Maximum Likelihood Estimation 16. Modeling Choice: The LPM, Probit and Logit Models 17. Using Logit and Probit Models for Unemployment and School Choice 18. Corner Solutions: Modeling Investing in Children and by Firms 19. An introduction to structural modelling in development economics 20. Structural methods and the return to education 21. Sample Selection: Modeling incomes where occupation is chosen 22. Programme Evaluation: Regression Discontinuity and Matching 23. Heterogeneity, Selection, and the Marginal Treatment Effect (MTE) 24. Estimation of Dynamic Effects with Panel Data 25. Modeling the Effects of Aid and the Determinants of Growth 26. Understanding Technology Using Long Panels 27. Cross-section Dependence and Nonstationary Data 28. Macro Production Functions for Manufacturing and Agriculture 29. How can the processes of development best be understood?
I. Linking Models to Data for Development 1. An Introduction to Empirical Development Economics 2. The Linear Regression Model and the OLS Estimator 3. Using and Extending the Simple Regression Model 4. The Distribution of the OLS Estimators and Hypothesis Testing 5. The Determinants of Earnings and Productivity 6. Modelling Growth with Time Series Data 7. The Implications of Variables Having a Unit Root 8. Exogenous and Endogenous Growth 9. Panel Data: An Introduction 10. Panel Estimators: POLS, RE, FE, FD 11. Instrumental Variables and Endogeneity 12. The Progamme Evaluation Approach to Development Policy 13. Models, Experiments and Calibration in Development Policy Analysis II. Modeling Development 14. Measurement, Models and Methods for Understanding Poverty 15. Maximum Likelihood Estimation 16. Modeling Choice: The LPM, Probit and Logit Models 17. Using Logit and Probit Models for Unemployment and School Choice 18. Corner Solutions: Modeling Investing in Children and by Firms 19. An introduction to structural modelling in development economics 20. Structural methods and the return to education 21. Sample Selection: Modeling incomes where occupation is chosen 22. Programme Evaluation: Regression Discontinuity and Matching 23. Heterogeneity, Selection, and the Marginal Treatment Effect (MTE) 24. Estimation of Dynamic Effects with Panel Data 25. Modeling the Effects of Aid and the Determinants of Growth 26. Understanding Technology Using Long Panels 27. Cross-section Dependence and Nonstationary Data 28. Macro Production Functions for Manufacturing and Agriculture 29. How can the processes of development best be understood?
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