PAIRWISE DIFFERENCE ESTIMATION WITH NONPARAMETRIC CONTROL VARIABLES*
扩展了Honoré和Powell的成对差异估计量，使其能处理非参数估计的条件期望出现在非参数部分的情况，从而适用于有样本选择或内生性的非线性模型，并推导了部分线性Logit模型估计量的渐近分布。
This article extends the pairwise difference estimators for various semilinear limited dependent variable models proposed by Honoré and Powell ( Identification and Inference in Econometric Models . Essays in Honor of Thomas Rothenberg Cambridge: Cambridge University Press, 2005) to permit the regressor appearing in the nonparametric component to itself depend upon a conditional expectation that is nonparametrically estimated. This permits the estimation approach to be applied to nonlinear models with sample selectivity and/or endogeneity, in which a “control variable” for selectivity or endogeneity is nonparametrically estimated. We develop the relevant asymptotic theory for the proposed estimators and we illustrate the theory to derive the asymptotic distribution of the estimator for the partially linear logit model.