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Activity Number: 330 - Bayesian Analysis of Latent Variable Models in Economics
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2018 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract #328700
Title: Flexible Bayesian Quantile Regression in Ordinal Models
Author(s): Mohammad Arshad Rahman* and Shubham Karnawat
Companies: Indian Institute of Technology Kanpur and Credit Suisse
Keywords: Generalized asymmetric Laplace distribution; Gibbs Sampling; Great Recession; homeownership; Markov chain Monte Carlo; Metropolis-Hastings

The paper introduces an estimation method for flexible Bayesian quantile regression in ordinal (FBQROR) models i.e., an ordinal quantile regression where the error follows a generalized asymmetric Laplace (GAL) distribution. The GAL distribution, unlike the asymmetric Laplace (AL) distribution, allows to fix specific quantiles while simultaneously letting the mode, skewness and tails to vary. We also introduce the cumulative distribution function (necessary for constructing the likelihood) and the moment generating function of the GAL distribution. The algorithm is illustrated in multiple simulation studies and implemented to analyze public opinion on homeownership as the best long-term investment in the United States.

Authors who are presenting talks have a * after their name.

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