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Title: Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects
Resulting in 1 citation.
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Ishimaru, Shoya |
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Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects Review of Economics and Statistics published online (25 January 2022): DOI: 10.1162/rest_a_01169. Also: https://direct.mit.edu/rest/article/doi/10.1162/rest_a_01169/109261/ Cohort(s): NLSY79 Publisher: MIT Press Keyword(s): Educational Attainment; Educational Returns; Modeling, Instrumental Variables; Modeling, OLS; Statistical Analysis; Wages This study proposes an econometric framework to interpret and empirically decompose the difference between IV and OLS estimates given by a linear regression model when the true causal effects of the treatment are nonlinear in treatment levels and heterogeneous across covariates. I show that the IV-OLS coefficient gap consists of three estimable components: the difference in weights on the covariates, the difference in weights on the treatment levels, and the difference in identified marginal effects that arises from endogeneity bias. Applications of this framework to return-to-schooling estimates demonstrate the empirical relevance of this distinction in properly interpreting the IV-OLS gap. |
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Bibliography Citation
Ishimaru, Shoya. "Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects." Review of Economics and Statistics published online (25 January 2022): DOI: 10.1162/rest_a_01169.
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