外源处理与内源因素:在相互作用项上忽略变量偏差的消失

Q3 Mathematics
O. Nizalova, Irina Murtazashvili
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引用次数: 175

摘要

无论是对某一特定因素在不同制度环境下的差异影响感兴趣,还是对政策或随机实验的异质效应感兴趣,实证研究者都面临着一个问题,即如果感兴趣的因素与遗漏的变量相关。本文提出了可能对上述效应得出一致估计的情况。我们发现,如果异质性的来源和被忽略的变量共同独立于政策或治疗,那么治疗和内生因素之间的相互作用项的OLS估计是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exogenous Treatment and Endogenous Factors: Vanishing of Omitted Variable Bias on the Interaction Term
Abstract Whether interested in the differential impact of a particular factor in various institutional settings or in the heterogeneous effect of policy or random experiment, the empirical researcher confronts a problem if the factor of interest is correlated with an omitted variable. This paper presents the circumstances under which it is possible to arrive at a consistent estimate of the mentioned effect. We find that if the source of heterogeneity and omitted variable are jointly independent of policy or treatment, then the OLS estimate on the interaction term between the treatment and endogenous factor turns out to be consistent.
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来源期刊
Journal of Econometric Methods
Journal of Econometric Methods Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
2.20
自引率
0.00%
发文量
7
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