报告题目：Distributional Effects in Censored Quantile Regressions with Endogeneity and Heteroskedasticity（存在内生性与异方差性的删截数据分位数回归中的分布效应）
报告人：王曦（暨南大学）
报告时间：2026年5月6日（星期三）10:30-11:45
报告地点：suncitygroup太阳新城318会议室
邀请部门：经济学系
 
报告人简介：
王曦，暨南大学副教授，博士毕业于香港科技大学，主要研究计量经济学理论及应用，论文发表于Journal of Econometrics，Econometric Theory，Oxford Bulletin of Economic and Statistics，Econometric Journal，Marketing Letters等期刊。

 

报告摘要：
Distributional effects, captured by quantile frameworks, are well-received for characterizing heterogeneous impacts of economic factors across the unobserved relative ranks.  Censored outcome, endogenous regressor and heteroskedastic error are prevalent in empirical work, yet challenge the consistency of existing quantile estimation methods.

This paper proposes a two-nested-step(TNS) estimation method for distributional effects in censored quantile models with endogeneity and heteroskedasticity.  It combines the sequential analysis with the control function approach, adapting for heterogeneous distributional effects. 

The estimation algorithm is a two-step procedure nested with a sequence of series quantile regressions, thereby providing applied researchers with a computationally tractable and practically feasible tool.  Monte Carlo simulation results demonstrate the good performance of our estimator in a finite sample. We apply the proposed method to estimate heterogeneous income elasticities of households across relative ranks of commodity expenditure using data from the UK Family Expenditure Survey.