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A sturdy values analysis of motor vehicle fatalities

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Listed:
  • Richard Fowles

    (University of Utah)

  • Peter D. Loeb

    (Rutgers University)

Abstract

Understanding the major determinants of crash fatalities continues to be an important topic of investigation for safety researchers. Regression models using a vast number of explanatory variables are often used which result in a huge array of specifications. Results often vary among studies based on size of estimated coefficients and significance levels. To address this, we explore both significance and model sturdiness in regression models using Leamer’s s-values. This Bayesian technique allows us to address estimation uncertainty and model ambiguity over all possible subset regressions so as to evaluate the effect of key variables which we focus on as contributors to crash fatalities. These include cell phone use, fleet modernization, suicidal behavior, alcohol use, and speed limits.

Suggested Citation

  • Richard Fowles & Peter D. Loeb, 2021. "A sturdy values analysis of motor vehicle fatalities," Empirical Economics, Springer, vol. 60(4), pages 2063-2081, April.
  • Handle: RePEc:spr:empeco:v:60:y:2021:i:4:d:10.1007_s00181-020-01826-2
    DOI: 10.1007/s00181-020-01826-2
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    References listed on IDEAS

    as
    1. Leamer, Edward E., 2016. "S-values and Bayesian weighted all-subsets regressions," European Economic Review, Elsevier, vol. 81(C), pages 15-31.
    2. Fowles, Richard & Loeb, Peter D. & Clarke, Wm. A., 2010. "The cell phone effect on motor vehicle fatality rates: A Bayesian and classical econometric evaluation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1140-1147, November.
    3. Fowles, Richard & Loeb, Peter D. & Clarke, Wm., 2013. "The cell phone effect on truck accidents: A specification error approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 18-28.
    4. Loeb, Peter D. & Clarke, William A., 2009. "The cell phone effect on pedestrian fatalities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 284-290, January.
    5. Beth A. Freeborn & Brian McManus, 2007. "Substance Abuse Treatment and Motor Vehicle Fatalities," Working Papers 66, Department of Economics, College of William and Mary.
    6. 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.
    7. Chaloupka, Frank J & Saffer, Henry & Grossman, Michael, 1993. "Alcohol-Control Policies and Motor-Vehicle Fatalities," The Journal of Legal Studies, University of Chicago Press, vol. 22(1), pages 161-186, January.
    8. 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.
    9. Peter Loeb & William Clarke & Richard Anderson, 2009. "The impact of cell phones on motor vehicle fatalities," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2905-2914.
    10. Leamer, Edward E, 1982. "Sets of Posterior Means with Bounded Variance Priors," Econometrica, Econometric Society, vol. 50(3), pages 725-736, May.
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    12. Simmons, Walter O. & Welki, Andrew M. & Zlatoper, Thomas J., 2016. "The Impact of Driving Knowledge on Motor Vehicle Fatalities," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 55(1), April.
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