The Department of Economics Econometrics Seminar Series presents

"Bayesian Quantile Regression for Ordinal Models"
with Arshad Mohammad, Graduate Student, Department of Economics, UCI

Monday, May 6, 2013
3:30-5:00 p.m.
Social Science Plaza A, Room 2112

This talk introduces a Bayesian estimation method for quantile regression in univariate ordinal models. Two algorithms are presented that exploit the latent variable inferential framework of Albert-Chib-1993, capitalize on the normal-exponential representation of the asymmetric Laplace (AL) distribution, and judiciously select scale restriction to simplify the sampling procedure. Estimation utilizes Markov chain Monte Carlo (MCMC) simulation methods -- either Gibbs sampling together with the Metropolis-Hastings (MH) algorithm or only Gibbs sampling. The algorithms are demonstrated in two simulation studies and employed to analyze problems in economics (educational attainment) and political economy (public opinion on a recently proposed tax policy).

For further information, please contact Gloria Simpson, or 949-824-5788.

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