Poorly Measured Confounders are More Useful on the Left than on the Right

69 Pages Posted: 19 Mar 2017 Last revised: 25 Jun 2023

See all articles by Zhuan Pei

Zhuan Pei

W.E. Upjohn Institute for Employment Research

Jörn-Steffen Pischke

London School of Economics; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR); IZA Institute of Labor Economics

Hannes Schwandt

Princeton University - Center for Health and Wellbeing

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Date Written: March 2017

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 various strategies which have been suggested to identify the returns to schooling.

Suggested Citation

Pei, Zhuan and Pischke, Jörn-Steffen (Steve) and Schwandt, Hannes, Poorly Measured Confounders are More Useful on the Left than on the Right (March 2017). NBER Working Paper No. w23232, Available at SSRN: https://ssrn.com/abstract=2935437

Zhuan Pei (Contact Author)

W.E. Upjohn Institute for Employment Research ( email )

300 South Westnedge Avenue
Kalamazoo, MI 49007-4686
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Jörn-Steffen (Steve) Pischke

London School of Economics ( email )

Houghton Street
London WC2A 2AE
+44 207 955 6509 (Phone)
+44 207 955 7595 (Fax)

National Bureau of Economic Research (NBER)

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Centre for Economic Policy Research (CEPR)

London
United Kingdom

IZA Institute of Labor Economics

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Bonn, D-53072
Germany

Hannes Schwandt

Princeton University - Center for Health and Wellbeing ( email )

22 Chambers Street
Princeton, NJ 08544-0708
United States

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