Bayesian Heteroskedasticity-Robust Standard Errors

Richard Startz

University of California at Santa Barbara, Economics Working Paper Series from Department of Economics, UC Santa Barbara

Abstract: Use of heteroskedasticity-robust standard errors has become common in frequentist regressions. I offer here a Bayesian analog. The Bayesian version is derived by first focusing on the likelihood function for the sample values of the identifying moment conditions of least squares and then formulating a convenient prior for the variances of the error terms. The first step introduces a sandwich estimator into the posterior calculations, while the second step allows the investigator to set the sandwich for either heteroskedastic or homoskedastic error variances. If desired, the Bayesian estimator can be made to look very similar to the usual heteroskedasticity-robust frequentist estimator. Bayesian estimation is easily accomplished by a standard MCMC procedure.

Keywords: Social and Behavioral Sciences; robust standard errors; bayesian (search for similar items in EconPapers)
Date: 2012-08-15
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.escholarship.org/uc/item/69c4x8m9.pdf;origin=repeccitec (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cdl:ucsbec:qt69c4x8m9

Access Statistics for this paper

More papers in University of California at Santa Barbara, Economics Working Paper Series from Department of Economics, UC Santa Barbara Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().