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Contribution Details

Type Working Paper
Scope Discipline-based scholarship
Title Poorly measured confounders are more useful on the left than on the right
Organization Unit
  • Zhuan Pei
  • Jörn-Steffen Pischke
  • Hannes Schwandt
  • English
Institution National Bureau of Economic Research
Series Name NBER Working Papers
Number 23232
Number of Pages 67
Date 2017
Abstract Text 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.
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