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数量经济与金融系列讲座第368期:Semiparametric Estimation of Censored Regression with Endogeneity

  发布日期:2017-12-05  浏览次数:

Speaker:Prof. Songnian Chen

Time: 15:30-17:00, Dec 5th (Tuesday)

Location: Room 801, SOE

Institution: Department of Economics, Hong Kong of Science and Technology

Title: Semiparametric Estimation of Censored Regression with Endogeneity

Abstract: In this paper we consider estimation a censored regression model with endogenous regressors. For the purpose of identification and estimation, we first derive a sequence of moment conditions for each quantile, and then we integrate these moment conditions over a range of quantiles to facilitate identification and improve estimation efficiency. Our proposed estimator is easy to implement by combining a convex minimization problem, inversion of a Kaplan-Meier estimator and typically low-dimensional, sometimes a merely one-dimensional, minimization search. Consistency and asymptotic normality are established under some regularity conditions, and small scale Monte Carlo experiments show good and stable performance of our estimator. ​