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Bayesian Inference in Regression Models with Ordinal Explanatory Variables

Sune Karlsson () and Asrat Temesgen
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Asrat Temesgen: Örebro University School of Business, Postal: Örebro University, School of Business, SE - 701 82 ÖREBRO, Sweden

No 2015:9, Working Papers from Örebro University, School of Business

Abstract: This paper considers Bayesian inference procedures for regression models with ordinally observed explanatory variables. Taking advantage of a latent variable interpretation of the ordinally observed variable we develop an efficient Bayesian inference procedure that estimates the regression model of interest jointly with an auxiliary ordered probit model for the unobserved latent variable. The properties of the inference procedure and associated MCMC algorithm are assessed using simulated data. We illustrate our approach in an investigation of gender based wage discrimination in the Swedish labor market and find evidence of wage discrimination.

Keywords: Markov Chain Monte Carlo; latent variables; ordered probit; wage discrimination (search for similar items in EconPapers)
JEL-codes: C11 C25 C35 J31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2015-09-18
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