In this chapter, we consider the nonparametric estimation of the average treatment effect (ATE) based on direct estimation of the conditional treatment effect. We establish the asymptotic distribution of the proposed ATE estimator. We also consider consistent testing for a parametric functional form for the conditional treatment effect function. A small-scale Monte Carlo simulation study is reported to examine the finite sample performance of the proposed estimator.
Gu, J., Lin, J. and Liu, D. (2011), "Estimating the Average Treatment Effect Based on Direct Estimation of the Conditional Treatment Effect", Drukker, D.M. (Ed.) Missing Data Methods: Cross-sectional Methods and Applications (Advances in Econometrics, Vol. 27 Part 1), Emerald Group Publishing Limited, Bingley, pp. 289-311. https://doi.org/10.1108/S0731-9053(2011)000027A014Download as .RIS
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