REFERENCES
- Abadie, A. (2003), “Semiparametric Instrument Variable Estimation of Treatment Response Models,” Journal of Econometrics, 113, 231–263.
- Abrevaya, J. (2006), “Estimating the Effect of Smoking on Birth Outcomes Using a Matched Panel Data Approach,” Journal of Applied Econometrics, 21, 489–519.
- Abrevaya, J., and Dahl, C. (2008), “The Effects of Birth Inputs on Birthweight: Evidence From Quantile Estimation on Panel Data,” Journal of Business and Economic Statistics, 26, 379–397.
- Almond, D., Chay, K.Y., and Lee, D.S. (2005), “The Costs of Low Birth Weight,” Quarterly Journal of Economics, 120, 1031–1083.
- Cattaneo, M.D. (2010), “Efficient Semiparametric Estimation of Multi-Valued Treatment Effects Under Ignorability,” Journal of Econometrics, 155, 138–154.
- Crump, R.K., Hotz, V.J., Imbens, G.W., and Mitnik, O.A. (2009), “Dealing With Limited Overlap in Estimation of Average Treatment Effects,” Biometrika, 96, 187–199.
- da Veiga, P.V., and Wilder, R.P. (2008), “Maternal Smoking During Pregnancy and Birthweight: A Propensity Score Matching Approach,” Maternal and Child Health Journal, 12, 194–203.
- Donald, S.G., Hsu, Y.-C., and Lieli, R.P. (2014a), “Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT,” Journal of Business and Economic Statistics, 32, 395–415.
- ——— (2014b), “Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion,” Statistics and Probability Letters, 95, 132–138.
- Frölich, M. (2007), “Nonparametric IV Estimation of Local Average Treatment Effects With Covariates,” Journal of Econometrics, 139, 35–75.
- Hahn, J. (1998), “On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects,” Econometrica, 66, 315–331.
- Heckman, J., Ichimura, H., and Todd, P. (1997), “Matching as an Econometric Evaluation Estimator: Evidence From Evaluating a Job Training Program,” Review of Economic Studies, 64, 605–654.
- ——— (1998), “Matching as an Econometric Evaluations Estimator,” Review of Economic Studies, 65, 261–294.
- Heckman, J., and Vytlacil, E. (2005), “Structural Equations, Treatment Effects, and Econometric Policy Evaluation,” Econometrica, 73, 669–738.
- Hirano, K., Imbens, G.W., and Ridder, G. (2003), “Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score,” Econometrica, 71, 1161–1189.
- Hong, H., and Nekipelov, D. (2010), “Semiparametric Efficiency in Nonlinear LATE Models,” Quantitative Economics, 1, 279–304.
- Hsu, Y.-C. (2012), “Consistent Tests for Conditional Treatment Effects,” Working Paper, Institute of Economics, Academia Sinica, Taiwan.
- Ichimura, H., and Linton, O. (2005), “Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators,” in Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg, eds. D. W. K. Andrews and J. Stock, Cambridge, UK: Cambridge University Press.
- Imbens, G., and Ridder, G. (2009), “Estimation and Inference for Generalized Full and Partial Means and Derivatives,” Working Paper, Department of Economics, Harvard University.
- Imbens, G.W., and Wooldridge, J.W. (2009), “Recent Developments in the Econometrics of Program Evaluation,” Journal of Economic Literature, 47, 5–86.
- Khan, S., and Tamer, E. (2010), “Irregular Identification, Support Conditions, and Inverse Weight Estimation,” Econometrica, 6, 2021–2042.
- Lee, S., and Whang, J.-Y. (2009), “Nonparametric Tests of Conditional Treatment Effects,” Cowles Foundation Discussion Papers 1740, Cowles Foundation, Yale University.
- MaCurdy, T., Chen, X., and Hong, H. (2011), “Flexible Estimation of Treatment Effect Parameters,” American Economic Review, 101, 544–551.
- Masry, E. (1996), “Multivariate Local Polynomial Regression for Time Series: Uniform Strong Consistency and Rates,” Journal of Time Series Analysis, 17, 571–599.
- Pagan, A., and Ullah, A. (1999), Nonparametric Econometrics, Cambridge, UK: Cambridge University Press.
- Rosenbaum, P., and Rubin, D. (1983), “The Central Role of the Propensity Score in Observational Studies for Causal Effects,” Biometrika, 70, 41–55.
- ——— (1985), “Reducing Bias in Observational Studies Using Subclassfication on the Propensity Score,” Journal of American Statistical Association, 79, 516–524.
- Su, L. (2011), “A Brief Introduction to Nonparametric Econometrics,” Lecture Notes, School of Economics, Singapore Management University.
- Walker, M.B., Tekin, E., and Wallace, S. (2009), “Teen Smoking and Birth Outcomes,” Southern Economic Journal, 75, 892–907.
- Wooldridge, J.M. (2010), Econometric Analysis of Cross Section and Panel Data (2nd ed.), Cambridge, MA: MIT Press.