The Effect of Omitted Variables on the Sign of Regression Coefficients

Fuente: arXiv
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Auteurs principaux: Masten, Matthew A., Poirier, Alexandre
Format: Preprint
Publié: 2022
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author Masten, Matthew A.
Poirier, Alexandre
author_facet Masten, Matthew A.
Poirier, Alexandre
contents We show that, depending on how the impact of omitted variables is measured, it can be substantially easier for omitted variables to flip coefficient signs than to drive them to zero. This behavior occurs with "Oster's delta" (Oster 2019), a widely reported robustness measure. Consequently, any time this measure is large -- suggesting that omitted variables may be unimportant -- a much smaller value reverses the sign of the parameter of interest. We propose a modified measure of robustness to address this concern. We illustrate our results in four empirical applications and two meta-analyses. We implement our methods in the companion Stata module regsensitivity.
format Preprint
id arxiv_https___arxiv_org_abs_2208_00552
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle The Effect of Omitted Variables on the Sign of Regression Coefficients
Masten, Matthew A.
Poirier, Alexandre
Econometrics
Methodology
We show that, depending on how the impact of omitted variables is measured, it can be substantially easier for omitted variables to flip coefficient signs than to drive them to zero. This behavior occurs with "Oster's delta" (Oster 2019), a widely reported robustness measure. Consequently, any time this measure is large -- suggesting that omitted variables may be unimportant -- a much smaller value reverses the sign of the parameter of interest. We propose a modified measure of robustness to address this concern. We illustrate our results in four empirical applications and two meta-analyses. We implement our methods in the companion Stata module regsensitivity.
title The Effect of Omitted Variables on the Sign of Regression Coefficients
topic Econometrics
Methodology
url https://arxiv.org/abs/2208.00552