Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/283961 
Authors: 
Year of Publication: 
2023
Series/Report no.: 
Working Paper No. 2023-6
Publisher: 
University of Massachusetts, Department of Economics, Amherst, MA
Abstract: 
Covariate benchmarking is an important part of sensitivity analysis about omitted variable bias and can be used to bound the strength of the unobserved confounder using information and judgments about observed covariates. It is common to carry out formal covariate benchmarking after residualizing the unobserved confounder on the set of observed covariates. In this paper, I explain the rationale and details of this procedure. I clarify some important details of the process of formal covariate benchmarking and highlight some of the difficulties of interpretation that researchers face in reasoning about the residualized part of unobserved confounders. I explain all the points with several empirical examples.
Subjects: 
confounding
omitted variable bias
sensitivity analysis
JEL: 
C01
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Working Paper

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