Economics Department Working Paper Series
Working Paper Number
2023-6
Publication Date
2023
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.
DOI
https://doi.org/10.7275/cjmd-yp45
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
License
UMass Amherst Open Access Policy
Recommended Citation
Basu, Deepankar, "Formal Covariate Benchmarking to Bound Omitted Variable Bias" (2023). Economics Department Working Paper Series. 349.
https://doi.org/10.7275/cjmd-yp45