Organization of This Book
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
3. Making Regression Make Sense
3.1. Regression Fundamentals
3.2. Regression and Causality
3.3. Heterogeneity and Nonlinearity
3.5. Appendix: Derivation of the Average Derivative Weighting Function
4. Instrumental Variables in Action: Sometimes You Get What You Need
4.2. Asymptotic 2SLS Inference
4.3. Two-Sample IV and Split-Sample IV
4.4. IV with Heterogeneous Potential Outcomes
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
6. Getting a Little Jumpy: Regression Discontinuity Designs
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
Acronyms and Abbreviations
