Poorly measured confounders are more useful on the left than on the right

Pei, Zhuan, Pischke, Jorn-Steffen ORCID: 0000-0002-6466-1874 and Schwandt, Hannes (2018) Poorly measured confounders are more useful on the left than on the right. Journal of Business and Economic Statistics. ISSN 0735-0015

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Abstract

Researchers frequently test identifying assumptions in regression based research designs (which include instrumental variables or difference-in-differences models) by adding additional control variables on the right hand side of the regression. If such additions do not affect the coefficient of interest (much) a study is presumed to be reliable. We caution that such invariance may result from the fact that the observed variables used in such robustness checks are often poor measures of the potential underlying confounders. In this case, a more powerful test of the identifying assumption is to put the variable on the left hand side of the candidate regression. We provide derivations for the estimators and test statistics involved, as well as power calculations, which can help applied researchers interpret their findings. We illustrate these results in the context of estimating the returns to schooling.

Item Type:	Article
Official URL:	https://amstat.tandfonline.com/toc/ubes20/current
Additional Information:	© 2018 Informa Group plc
Divisions:	Economics
Subjects:	H Social Sciences > HB Economic Theory
JEL classification:	C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C31 - Cross-Sectional Models; Spatial Models; Treatment Effect Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection
Date Deposited:	15 Jun 2018 09:30
Last Modified:	30 Nov 2024 18:24
Projects:	ES/H02123X/1
Funders:	Economic and Social Research Council
URI:	http://eprints.lse.ac.uk/id/eprint/88352

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