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MLA Citation
Summary
This influential book by Angrist and Pischke provides a practical guide to modern econometric methods for causal inference. The authors bridge the gap between theoretical econometrics and applied empirical work, focusing on research designs that can credibly identify causal effects.
The book emphasizes the "design-based" approach to econometrics, where identification comes from research design rather than strong modeling assumptions. Key topics include regression with controls, instrumental variables, differences-in-differences, regression discontinuity designs, and standard errors. Each method is explained through intuitive examples and empirical applications from labor economics, education, and health economics.
A central theme is the "credibility revolution" in applied microeconomics—the shift toward research designs that provide more convincing evidence of causality. The authors argue that good research design is more important than sophisticated statistical techniques, and they provide practical advice on implementation, interpretation, and potential pitfalls.
The book has become a standard reference for graduate students and researchers in economics, political science, sociology, and public policy. Its accessible style and focus on practical application have made modern causal inference methods more widely accessible beyond the economics profession.
Key Contributions
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Provides a comprehensive, accessible introduction to modern causal inference methods for applied researchers
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Emphasizes the "design-based" approach where identification comes from research design rather than modeling assumptions
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Bridges the gap between theoretical econometrics and practical empirical work with real-world examples
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Covers essential methods including regression, instrumental variables, differences-in-differences, and regression discontinuity
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Discusses practical implementation issues like standard errors, weak instruments, and specification testing
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Advocates for the "credibility revolution" in empirical research focusing on research design quality