具有内生变量的分位数样本选择模型的估计方法及应用  

Estimator and Application of Quantile Sample Selection Models with Endogenous Variables

作　　者：谭黎明 金泽群 张征宇[1] 周亚虹[1] TAN Liming;JIN Zequn;ZHANG Zhengyu;ZHOU Yahong(School of Economics,Shanghai University of Finance and Economics)

机构地区：[1]上海财经大学经济学院

出　　处：《数量经济技术经济研究》2024年第12期199-218,共20页Journal of Quantitative & Technological Economics

基　　金：国家自然科学基金专项项目(72342034);国家自然科学基金重点项目(72333002);国家自然科学基金面上项目(72173083,72273076);国家自然科学基金青年项目(72103126);中央高校基本科研业务费专项资金(2023110077)的资助。

摘　　要：处理非线性模型中的样本选择问题和内生变量问题是计量经济学关注的重点与难点。本文提出采用控制函数法对具有内生变量的分位数样本选择模型进行识别与估计。参考Arellano和Bonhomme(2017),我们将结果方程和选择方程中不可观测扰动项的联合分布建模为Copula函数,修正了分位数样本选择问题所产生的选择偏误。在此基础上,我们提出在结果方程中加入用基函数逼近的控制函数作为额外的解释变量来处理内生变量问题。在处理内生变量问题上,控制函数方法与逆分位数回归相比易于实现,避免了求解非凸目标函数的优化问题。进一步地,我们证明了估计量的一致性与渐近正态性,通过蒙特卡洛模拟给出了该估计量的有限样本结果,并与逆分位数回归进行了比较。最后,我们将该模型应用于分析已婚女性的教育回报率,体现了本模型的实用价值。The problem of nonrandom sample selection in empirical research is of wide interest.Typically,various unobserved factors affect both individual choice decisions and outcomes,e.g.,an individual's choice of whether to participate in the labor market and the wage received after participating in the labor market,leading to selection bias in estimating models with sample selection problems.For example,in the study of wages and employment,we can only observe the wages of employed individuals,and the decision to enter the labor market is a self-selecting behavior.Thus,traditional measures of returns to education or wage inequality may be biased.In addition to sample selection problems,the presence of endogeneity in explanatory variables caused by simultaneous equations,measurement errors,or omitted variables is also common.Having both problems of sample selection and endogenous variables is common in empirical research in economics.Consider again the classic example of wages and employment,where an individual's decision whether to enter the labor market creates a sample selection problem,while the explanatory variable in the outcome equation,education,is often considered an endogenous variable,and unobservable ability in the outcome equation usually affects education as well.In this study,we propose an estimation method for a quantile sample selection model with continuous endogenous explanatory variables.We use a control function approach to deal with endogenous variables in quantile regression models by including an additional unknown control function in the outcome equation to control for the effects of correlation between the endogenous explanatory variables and the error term in the outcome equation.Thus,we use the control function method to transform a linear quantile regression model with endogenous variables into a partial linear model in the exogenous case.We then approximate the nonlinear part with a series of basis functions,and the partial linear quantile regression model can be easily estimated by minimizin

关 键 词：分位数回归 样本选择 控制函数 COPULA函数 级数估计 

分 类 号：F064.1[经济管理—政治经济学]