Table of Contents -- List of Figures vii -- List of Tables ix -- -- Preface xi -- Acknowledgments xv -- Organization of This Book xvii -- PART I: PRELIMINARIES 1 -- Chapter 1: Questions about Questions 3 -- Chapter 2: The Experimental Ideal 11 -- 2.1 The Selection Problem 12 -- 2.2 Random Assignment Solves the Selection Problem 15 -- 2.3 Regression Analysis of Experiments 22 -- PART II: THE CORE 25 -- Chapter 3: Making Regression Make Sense 27 -- 3.1 Regression Fundamentals 28 -- 3.2 Regression and Causality 51 -- 3.3 Heterogeneity and Nonlinearity 68 -- 3.4 Regression Details 91 -- -- 3.5 Appendix: Derivation of the Average Derivative Weighting Function 110 -- Chapter 4: Instrumental Variables in Action: Sometimes You Get What You Need 113 -- 4.1 IV and Causality 115 -- 4.2 Asymptotic 2SLS Inference 138 -- 4.3 Two-Sample IV and Split-Sample IV 147 -- 4.4 IV with Heterogeneous Potential Outcomes 150 -- 4.5 Generalizing LATE 173 -- 4.6 IV Details 188 -- 4.7 Appendix 216 -- Chapter 5: Parallel Worlds: Fixed Effects, Differences-in-Differences, and Panel Data 221 -- 5.1 Individual Fixed Effects 221 -- 5.2 Differences-in-Differences 227 -- 5.3 Fixed Effects versus Lagged Dependent Variables 243 -- 5.4 Appendix: More on Fixed Effects and Lagged Dependent Variables 246 -- PART III: EXTENSIONS 249 -- Chapter 6: Getting a Little Jumpy: Regression Discontinuity Designs 251 -- -- 6.1 Sharp RD 251 -- 6.2 Fuzzy RD Is IV 259 -- Chapter 7: Quantile Regression 269 -- 7.1 The Quantile Regression Model 270 -- 7.2 IV Estimation of Quantile Treatment Effects 283 -- Chapter 8: Nonstandard Standard Error Issues 293 -- 8.1 The Bias of Robust Standard Error Estimates 294 -- 8.2 Clustering and Serial Correlation in Panels 308 -- 8.3 Appendix: Derivation of the Simple Moulton Factor 323 -- Last Words 327 -- Acronyms and Abbreviations 329 -- Empirical Studies Index 335 -- References 339 -- Index 361