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Index
Title Page Copyright Page Contents List of Figures List of Tables Preface Acknowledgments Organization of This Book I Preliminaries
1 Questions about Questions 2 The Experimental Ideal
2.1 The Selection Problem 2.2 Random Assignment Solves the Selection Problem 2.3 Regression Analysis of Experiments
II The Core
3 Making Regression Make Sense
3.1 Regression Fundamentals 3.2 Regression and Causality 3.3 Heterogeneity and Nonlinearity 3.4 Regression Details 3.5 Appendix: Derivation of the Average Derivative Weighting Function
4 Instrumental Variables in Action: Sometimes You Get What You Need
4.1 IV and Causality 4.2 Asymptotic 2SLS Inference 4.3 Two-Sample IV and Split-Sample IV 4.4 IV with Heterogeneous Potential Outcomes 4.5 Generalizing LATE 4.6 IV Details 4.7 Appendix
5 Parallel Worlds: Fixed Effects, Differences-in-Differences, and Panel Data
5.1 Individual Fixed Effects 5.2 Differences-in-Differences 5.3 Fixed Effects versus Lagged Dependent Variables 5.4 Appendix: More on Fixed Effects and Lagged Dependent Variables
III Extensions
6 Getting a Little Jumpy: Regression Discontinuity Designs
6.1 Sharp RD 6.2 Fuzzy RD Is IV
7 Quantile Regression
7.1 The Quantile Regression Model 7.2 IV Estimation of Quantile Treatment Effects
8 Nonstandard Standard Error Issues
8.1 The Bias of Robust Standard Error Estimates 8.2 Clustering and Serial Correlation in Panels 8.3 Appendix: Derivation of the Simple Moulton Factor
Last Words Acronyms and Abbreviations Empirical Studies Index References Index
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