Bayesian Model Selection and Prior Calibration for Structural Models in Economic Experiments: Some Guidance for the Practitioner

43 Pages Posted: 25 Jan 2023

See all articles by James R. Bland

James R. Bland

The University of Toledo, Department of Economics

Date Written: January 24, 2023

Abstract

Bayesian estimates from experimental data can be influenced by highly diffuse or "uninformative" priors. This paper discusses how practitioners can use their own expertise to critique and select a prior that (i) incorporates our knowledge as experts in the field, and (ii) achieves favorable sampling properties. I demonstrate these techniques using data from eleven experiments of decision-making under risk, and discuss some implications of the findings.

Suggested Citation

Bland, James R., Bayesian Model Selection and Prior Calibration for Structural Models in Economic Experiments: Some Guidance for the Practitioner (January 24, 2023). Available at SSRN: https://ssrn.com/abstract=4334267 or http://dx.doi.org/10.2139/ssrn.4334267

James R. Bland (Contact Author)

The University of Toledo, Department of Economics ( email )

Toledo, OH 43606
United States

HOME PAGE: http://https://sites.google.com/site/jamesbland/

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
144
Abstract Views
692
Rank
373,664
PlumX Metrics