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Understanding the cell phone effect on vehicle fatalities: a Bayesian view

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  • Gail Blattenberger
  • Richard Fowles
  • Peter D. Loeb
  • Wm. A. Clarke

Abstract

This article examines the potential effect of various factors on motor vehicle fatality rates using a rich set of panel data and classical regression analysis combined with Bayesian Extreme Bounds Analysis (EBA), Bayesian Model Averaging (BMA) and Stochastic Search Variable Selection (SSVS) procedures. The variables examined in the models include traditional motor vehicle and socioeconomic factors. In addition, the models address the effects of cell phone usage on such accidents. The use of both classical and Bayesian techniques diminish the model and parameter uncertainties which afflict more conventional modelling methods which rely on only one of the two methods.

Suggested Citation

  • Gail Blattenberger & Richard Fowles & Peter D. Loeb & Wm. A. Clarke, 2012. "Understanding the cell phone effect on vehicle fatalities: a Bayesian view," Applied Economics, Taylor & Francis Journals, vol. 44(14), pages 1823-1835, May.
    • Handle: RePEc:taf:applec:44:y:2012:i:14:p:1823-1835
    DOI: 10.1080/00036846.2011.554379
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    Cited by:

    1. Richard Fowles & Peter D. Loeb, 2021. "A sturdy values analysis of motor vehicle fatalities," Empirical Economics, Springer, vol. 60(4), pages 2063-2081, April.
    2. Fowles, Richard & Loeb, Peter D., 2016. "Sturdy Inference: A Bayesian Analysis of U.S. Motorcycle Helmet Laws," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 55(3), December.
    3. Blattenberger, Gail & Fowles, Richard & Loeb, Peter D., 2013. "Determinants of motor vehicle crash fatalities using Bayesian model selection methods," Research in Transportation Economics, Elsevier, vol. 43(1), pages 112-122.

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