This book provides scholars and students with the first comprehensive guide to the use and evaluation of natural experiments â an increasingly popular methodology in the social sciences. It introduces the key issues in causal inference, including model specification, and emphasizes the importance of strong research design over complex statistical analysis.
This book provides scholars and students with the first comprehensive guide to the use and evaluation of natural experiments â an increasingly popular methodology in the social sciences. It introduces the key issues in causal inference, including model specification, and emphasizes the importance of strong research design over complex statistical analysis.
Thad Dunning is Associate Professor of Political Science at Yale University and a research fellow at Yale's Institution for Social and Policy Studies and the Whitney and Betty MacMillan Center for International and Area Studies. He has written on a range of methodological topics, including impact evaluation, econometric corrections for selection effects and multi-method research in the social sciences, and his first book, Crude Democracy: Natural Resource Wealth and Political Regimes (Cambridge University Press, 2008), won the Best Book Award from the Comparative Democratization Section of the American Political Science Association.
Inhaltsangabe
1. Introduction: why natural experiments?; Part I. Discovering Natural Experiments: 2. Standard natural experiments; 3. Regression-discontinuity designs; 4. Instrumental-variables designs; Part II. Analyzing Natural Experiments: 5. Simplicity and transparency: keys to quantitative analysis; 6. Sampling processes and standard errors; 7. The central role of qualitative evidence; Part III. Evaluating Natural Experiments: 8. How plausible is as-if random?; 9. How credible is the model?; 10. How relevant is the intervention?; Part IV. Conclusion: 11. Building strong research designs through multi-method research.
1. Introduction: why natural experiments?; Part I. Discovering Natural Experiments: 2. Standard natural experiments; 3. Regression-discontinuity designs; 4. Instrumental-variables designs; Part II. Analyzing Natural Experiments: 5. Simplicity and transparency: keys to quantitative analysis; 6. Sampling processes and standard errors; 7. The central role of qualitative evidence; Part III. Evaluating Natural Experiments: 8. How plausible is as-if random?; 9. How credible is the model?; 10. How relevant is the intervention?; Part IV. Conclusion: 11. Building strong research designs through multi-method research.
Rezensionen
'Dunning has produced a useful and remarkably accessible guide for social scientists of all sorts. I especially like his guide to discovering natural experiments.' J. D. Angrist, Massachusetts Institute of Technology
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