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

In: Bayesian Model Comparison

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  • Gail Blattenberger
  • Richard Fowles
  • Peter D. Loeb

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.

Suggested Citation

  • Gail Blattenberger & Richard Fowles & Peter D. Loeb, 2014. "Variable Selection in Bayesian Models: Using Parameter Estimation and Non Parameter Estimation Methods," Advances in Econometrics, in: Bayesian Model Comparison, volume 34, pages 249-278, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-905320140000034011
    DOI: 10.1108/S0731-905320140000034011
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    More about this item

    Keywords

    Bayesian variable selection; Extreme Bounds Analysis; stochastic search model selection; Bayesian tree models; motor vehicle fatality rates; Bayesian Model Averaging; C11; C14; L9;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • L9 - Industrial Organization - - Industry Studies: Transportation and Utilities

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