Understanding why so many people across the world are so poor is one of the central intellectual challenges of our time. This book provides the tools and data that will enable students, researchers and professionals to address that issue.
Empirical Development Economics has been designed as a hands-on teaching tool to investigate the causes of poverty. The book begins by introducing the quantitative approach to development economics. Each section uses data to illustrate key policy issues. Part One focuses on the basics of understanding the role of education, technology and institutions in determining why incomes differ so much across individuals and countries. In Part Two, the focus is on techniques to address a number of topics in development, including how firms invest, how households decide how much to spend on their children’s education, whether microcredit helps the poor, whether food aid works, who gets private schooling and whether property rights enhance investment.
A distinctive feature of the book is its presentation of a range of approaches to studying development questions. Development economics has undergone a major change in focus over the last decade with the rise of experimental methods to address development issues; this book shows how these methods relate to more traditional ones.
Please visit the book's website at www.empiricalde.com for online supplements including Stata files and solutions to the exercises.
Table of Contents
Part One: Linking Models to Data for Development 1. An Introduction to Empirical Development Economics 2. The Simple Linear Regression Model 3 . Multiple Regression Analysis: estimation 4. Multiple Regression Analysis: inference 5. Maximum Likelihood Estimation 6. Heteroskedasticity 7 . Modeling Choice: LPM, Probit and Logit Models 8. Logit and Probit Models: Inference and Diagnostics 9. An Introduction to Time Series 10. Serial Correlation in Time Series Models 11. Cointegration 12. Panel Data: An Introduction 13. Panel Estimates: POLS, RE, FE, FD 14. Instrumental Variable Estimation 15. Program Evaluation: the Basics 16. Program Evaluation: Imperfect compliance and heterogeneity Part Two: Determinants of Income and Growth 17. Principles of Modeling: Endogeneity and Instruments 18. Structural Models 19. Econometric Analysis of Dynamic Panel Data 20. Estimating the Burnside and Dollar and the MRW Growth Models 21. Panel Data and Endogeneity 22. Sample Selection 23. The Tobit Model 24. Multinomial choice 25. Long-T Panel Data Analysis: An Introduction 26. Nonstationarity and Cointegration in Panel Time Series 27. Cross-section Dependence in Panel Time Series 28. Omitted Variable Bias, Measurement Error and IV: A Review 29. Reduced Form Evaluation Methods 30. Evaluation with Structural Models 31. Modeling: An overview 32. What does determine development?
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.