Characterization of the asymptotic distribution of semiparametric M-estimators |
| |
Authors: | Hidehiko Ichimura Sokbae Lee |
| |
Institution: | 1. Faculty of Economics and Graduate School of Public Policy, University of Tokyo, Japan;2. Department of Economics, University College London, London, WC1E 6BT, United Kingdom;3. Department of Economics, Seoul National University, Seoul 151-742, Republic of Korea |
| |
Abstract: | This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification. Our regularity conditions are relatively straightforward to verify and also weaker than those available in the literature. The first-stage nonparametric estimation may depend on finite dimensional parameters. We characterize: (1) conditions under which the first-stage estimation of nonparametric components do not affect the asymptotic distribution, (2) conditions under which the asymptotic distribution is affected by the derivatives of the first-stage nonparametric estimator with respect to the finite-dimensional parameters, and (3) conditions under which one can allow non-smooth objective functions. Our framework is illustrated by applying it to three examples: (1) profiled estimation of a single index quantile regression model, (2) semiparametric least squares estimation under model misspecification, and (3) a smoothed matching estimator. |
| |
Keywords: | C13 C14 |
本文献已被 ScienceDirect 等数据库收录! |
|