Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects

Shoya Ishimaru

Papers from arXiv.org

Abstract: 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.

Date: 2021-01, Revised 2022-06
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (5)

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Journal Article: Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2101.04346

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