Matching, Regression Discontinuity, Difference in Differences, and BeyondMyoung-jae Lee reviews the three most popular methods (and their extensions) in applied economics and other social sciences: matching, regression discontinuity, and difference in differences. This book introduces the underlying econometric and statistical ideas, shows what is identified and how the identified parameters are estimated, and illustrates how they are applied with real empirical examples. Lee emphasizes how to implement the three methods with data: data and programs are provided in a useful online appendix. All readers-theoretical econometricians/statisticians, applied economists/social-scientists and researchers/students-will find something useful in the book from different perspectives. |
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Contents
Matching | |
Index | |
1 | |
Regression Discontinuity | |
Complete Pairing with PS for Union on Wage CpUnionOnWage | |
Difference in Differences | |
Repeated CrossSection DD DdReCroVary4WavesSim | |
Triple Difference and Beyond | |
A Appendix | |
and GDD for Differenced Model DdGddPanel5WavesSim | |
Other editions - View all
Matching, Regression Discontinuity, Difference in Differences, and Beyond Myoung-jae Lee Limited preview - 2016 |
Matching, Regression Discontinuity, Difference in Differences, and Beyond Myoung-jae Lee Limited preview - 2016 |
Matching, Regression Discontinuity, Difference in Differences, and Beyond Myoung-Jae Lee No preview available - 2016 |
Common terms and phrases
analogously Angrist assumption asymptotic variance average becomes image binary bootstrap break causal cluster variance estimator continuity of image control group control image correlation counterfactual covariates covariates image define image dummies effect image effect of image estimate image estimator for image gives image group image ID image identification condition identified image and image image denote image equation image gives image i.e. image image image indexes image where image image with image image’s individual instance kernel Let image linear model logit LSE of image Mahalanobis distance marginal effect matching estimator mean effect nonparametric Observe image obtain panel data panel linear model parameters posttreatment pretreatment probit propensity score quantile random regression imputation regressors repeated crosssections replace image response variable righthand side selection sulfa drugs Suppose image timeconstant timevarying treated image treatment effect analysis treatment group tvalue unobserved confounders wage zero