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
Return to Book Description File created: 11/5/2009 | 
