IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v43y2013i1p112-122.html
   My bibliography  Save this article

Determinants of motor vehicle crash fatalities using Bayesian model selection methods

Author

Listed:
  • Blattenberger, Gail
  • Fowles, Richard
  • Loeb, Peter D.

Abstract

Motor vehicle crashes continue to result in large numbers of fatalities each year and represent the leading cause of death for young persons. In 2006, for example, there were over 42,700 fatalities associated with these crashes. Understanding the causes of these crashes and methods to reduce them continues to be of great interest to economists, public health officials, and policy makers. We present in this paper statistical models using a rich set of panel data covering the period 1980 to 2007 by state and the District of Columbia. Our choice of variables is based on an extensive literature highlighting the importance of policy, safety, demographic, and economic determinants of fatality rates.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:retrec:v:43:y:2013:i:1:p:112-122
    DOI: 10.1016/j.retrec.2012.12.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739885912002089
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.retrec.2012.12.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Keeler, Theodore E, 1994. "Highway Safety, Economic Behavior, and Driving Environment," American Economic Review, American Economic Association, vol. 84(3), pages 684-693, June.
    3. Leamer, Edward E, 1997. "Revisiting Tobin's 1950 Study of Food Expenditure: Reply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 559-561, Sept.-Oct.
    4. Clarke, William A. & Loeb, Peter D., 2005. "The determinants of train fatalities: keeping the model on track," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(2), pages 145-158, March.
    5. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    6. Levy, David T & Asch, Peter, 1989. "Speeding, Coordination, and the 55-MPH Limit: Comment," American Economic Review, American Economic Association, vol. 79(4), pages 913-915, September.
    7. Beth A. Freeborn & Brian McManus, 2007. "Substance Abuse Treatment and Motor Vehicle Fatalities," Working Papers 66, Department of Economics, College of William and Mary.
    8. 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.
    9. 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.
    10. Gail Blattenberger & Richard Fowles & Peter D Loeb & Wm. A. Clarke, 2008. "Understanding the Cell Phone Effect on Motor Vehicle Fatalities Using Classical and Bayesian Methods," Working Paper Series, Department of Economics, University of Utah 2008_24, University of Utah, Department of Economics.
    11. Henry Saffer & Michael Grossman, 1986. "Beer Taxes, the Legal Drinking Age, and Youth Motor Vehicle Fatalities," NBER Working Papers 1914, National Bureau of Economic Research, Inc.
    12. Saffer, Henry & Grossman, Michael, 1987. "Drinking Age Laws and Highway Mortality Rates: Cause and Effect," Economic Inquiry, Western Economic Association International, vol. 25(3), pages 403-417, July.
    13. Leamer, Edward E, 1997. "Revisiting Tobin's 1950 Study of Food Expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 533-553, Sept.-Oct.
    14. Lave, Charles A, 1985. "Speeding, Coordination, and the 55 MPH Limit," American Economic Review, American Economic Association, vol. 75(5), pages 1159-1164, December.
    15. Savage, Ian, 2007. "Trespassing on the Railroad," Research in Transportation Economics, Elsevier, vol. 20(1), pages 199-224, January.
    16. 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.
    17. Leamer, Edward E, 1982. "Sets of Posterior Means with Bounded Variance Priors," Econometrica, Econometric Society, vol. 50(3), pages 725-736, May.
    18. Peltzman, Sam, 1975. "The Effects of Automobile Safety Regulation," Journal of Political Economy, University of Chicago Press, vol. 83(4), pages 677-725, August.
    19. Alma Cohen & Liran Einav, 2003. "The Effects of Mandatory Seat Belt Laws on Driving Behavior and Traffic Fatalities," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 828-843, November.
    20. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    21. Fowles, Richard & Loeb, Peter D, 1989. "Speeding, Coordination, and the 55-MPH Limit: Comment," American Economic Review, American Economic Association, vol. 79(4), pages 916-921, September.
    22. Loeb, Peter D. & Clarke, William A., 2007. "The determinants of truck accidents," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 442-452, July.
    23. Peter Asch & David T. Levy, 1987. "Does the minimum drinking age affect traffic fatalities?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 6(2), pages 180-192.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tyndall, Justin, 2021. "Pedestrian deaths and large vehicles," Economics of Transportation, Elsevier, vol. 26.
    2. Mary J. Becker & Thomas J. Zlatoper, 2022. "Relationship Between Smoking and Motor Vehicle Death Rates in the U.S," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 50(1), pages 53-65, June.
    3. 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.
    4. 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.
    5. Richard Fowles & Peter D. Loeb, 2021. "A sturdy values analysis of motor vehicle fatalities," Empirical Economics, Springer, vol. 60(4), pages 2063-2081, April.
    6. Savage, Ian, 2013. "Comparing the fatality risks in United States transportation across modes and over time," Research in Transportation Economics, Elsevier, vol. 43(1), pages 9-22.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Richard Fowles & Peter Loeb & William A. Clarke, 2009. "A Bayesian and Classical Econometric Evaluation of the Effect of Cell Phones on Motor Vehicle Fatality Rates," Working Papers Rutgers University, Newark 2009-001, Department of Economics, Rutgers University, Newark.
    2. Richard Fowles & Peter D. Loeb, 2021. "A sturdy values analysis of motor vehicle fatalities," Empirical Economics, Springer, vol. 60(4), pages 2063-2081, April.
    3. Keeler, Theodore E., 1993. "Highway Safety, Economic Behavior, and Driving Environment," University of California Transportation Center, Working Papers qt9c27z2z1, University of California Transportation Center.
    4. Peter D. Loeb & William A. Clarke, 2005. "The Determinants of Truck Accidents in the United States," Working Papers Rutgers University, Newark 2005-002, Department of Economics, Rutgers University, Newark.
    5. 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.
    6. McCarthy, Patrick S., 1999. "Public policy and highway safety: a city-wide perspective," Regional Science and Urban Economics, Elsevier, vol. 29(2), pages 231-244, March.
    7. 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.
    8. Elizabeth Kopits & Maureen Cropper, 2008. "Why Have Traffic Fatalities Declined in Industrialised Countries?: Implications for Pedestrians and Vehicle Occupants," Journal of Transport Economics and Policy, University of Bath, vol. 42(1), pages 129-154, January.
    9. Patrick S. McCarthy, 1991. "HIGHWAY SAFETY AND THE 65‐mph SPEED LIMIT," Contemporary Economic Policy, Western Economic Association International, vol. 9(4), pages 82-92, October.
    10. Neil R. Ericsson, 2008. "The Fragility of Sensitivity Analysis: An Encompassing Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 895-914, December.
    11. David J. Houston & Lilliard E. Richardson, Jr., 2006. "Reducing traffic fatalities in the American States by upgrading seat belt use laws to primary enforcement," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 25(3), pages 645-659.
    12. Orley Ashenfelter & Michael Greenstone, 2004. "Using Mandated Speed Limits to Measure the Value of a Statistical Life," Journal of Political Economy, University of Chicago Press, vol. 112(S1), pages 226-267, February.
    13. Henry Saffer & Frank Chaloupka, 1987. "Breath Testing and the Demand for Drunk Driving," NBER Working Papers 2301, National Bureau of Economic Research, Inc.
    14. Daniel Albalate, 2013. "The Road against Fatalities: Infrastructure Spending vs. Regulation?," ERSA conference papers ersa13p221, European Regional Science Association.
    15. repec:ags:aaea22:335618 is not listed on IDEAS
    16. Ruhm, Christopher J., 1996. "Alcohol policies and highway vehicle fatalities," Journal of Health Economics, Elsevier, vol. 15(4), pages 435-454, August.
    17. Cook, Philip J. & Moore, Michael J., 2000. "Alcohol," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 30, pages 1629-1673, Elsevier.
    18. Daniel Shefer & Piet Rietveld, 1997. "Congestion and Safety on Highways: Towards an Analytical Model," Urban Studies, Urban Studies Journal Limited, vol. 34(4), pages 679-692, April.
    19. Clifford Winston & Vikram Maheshri & Fred Mannering, 2006. "An exploration of the offset hypothesis using disaggregate data: The case of airbags and antilock brakes," Journal of Risk and Uncertainty, Springer, vol. 32(2), pages 83-99, March.
    20. Thomas S. Dee & William N. Evans, 2001. "Teens and Traffic Safety," NBER Chapters, in: Risky Behavior among Youths: An Economic Analysis, pages 121-166, National Bureau of Economic Research, Inc.
    21. Berlemann, Michael & Matthes, Andreas, 2014. "Positive externalities from active car safety systems," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 313-329.

    More about this item

    Keywords

    Motor vehicle crashes; Bayesian econometrics; Cell phones; Vehicle safety;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:retrec:v:43:y:2013:i:1:p:112-122. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/620614/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.