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Variable Selection in Bayesian Models: Using Parameter Estimation and Non Parameter Estimation Methods

Bayesian Model Comparison

ISBN: 978-1-78441-185-5

ISSN: 0731-9053

Publication date: 19 November 2014

Abstract

This paper examines variable selection among various factors related to motor vehicle fatality rates using a rich set of panel data. Four Bayesian methods are used. These include Extreme Bounds Analysis (EBA), Stochastic Search Variable Selection (SSVS), Bayesian Model Averaging (BMA), and Bayesian Additive Regression Trees (BART). The first three of these employ parameter estimation, the last, BART, involves no parameter estimation. Nonetheless, it also has implications for variable selection. The variables examined in the models include traditional motor vehicle and socioeconomic factors along with important policy-related variables. Policy recommendations are suggested with respect to cell phone use, modernization of the fleet, alcohol use, and diminishing suicidal behavior.

Keywords

Citation

Blattenberger, G., Fowles, R. and Loeb, P.D. (2014), "Variable Selection in Bayesian Models: Using Parameter Estimation and Non Parameter Estimation Methods", Bayesian Model Comparison (Advances in Econometrics, Vol. 34), Emerald Group Publishing Limited, Bingley, pp. 249-278. https://doi.org/10.1108/S0731-905320140000034011

Publisher

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Emerald Group Publishing Limited

Copyright © 2014 Emerald Group Publishing Limited