Abstract

An inappropriate handling of cross-sectional heterogeneity renders estimates of causal effects inaccurate and uninformative. The present paper discusses how the direct modeling of cross-sectional differences via semiparametric models represents a useful bridge between a statistical approach, where the conditional distribution of the dependent variable returns any value of the outcome given any value of the explanatory variables, and an econometric analysis, where functions and parameters have direct policy implications. The explicit modeling of heterogeneity across different groups improves the quality of the estimates, mitigates their dependence upon the chosen instrumental variable, diminishes the self-selection problem, and fosters the acquisition of useful information for the entire sample.

摘要

对横截面异质性的不当处理会导致对因果效应的估计不准确且信息不足。本文讨论了通过半参数模型对横截面差异的直接建模如何代表统计方法之间的有用桥梁，其中因变量的条件分布在给定解释变量的任何值的情况下返回结果的任何值，以及计量经济学分析，其中函数和参数具有直接的政策影响。不同组间异质性的显式建模提高了估计的质量，减轻了它们对所选工具变量的依赖，减少了自我选择问题，并促进了对整个样本的有用信息的获取。