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Comparative analysis of long-term road fatality targets for individual states in the US—An application of experience curve models

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  • Chang, Yu Sang

Abstract

Both the Federal government and individual state governments in the US establish long-term road fatality targets to plan and evaluate the effectiveness of their respective safety programs. The purpose of this paper is to develop a simple fatality projection model to project future fatality rates and number of fatalities through 2020 and 2030 for individual states. And then, long-term fatality target value established by ten selected states will be compared to our projected values to assess realism of these targets.

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  • Chang, Yu Sang, 2014. "Comparative analysis of long-term road fatality targets for individual states in the US—An application of experience curve models," Transport Policy, Elsevier, vol. 36(C), pages 53-69.
  • Handle: RePEc:eee:trapol:v:36:y:2014:i:c:p:53-69
    DOI: 10.1016/j.tranpol.2014.07.005
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    1. David J. Houston & Lilliard E. Richardson, 2007. "Risk Compensation or Risk Reduction? Seatbelts, State Laws, and Traffic Fatalities," Social Science Quarterly, Southwestern Social Science Association, vol. 88(4), pages 913-936, December.
    2. Commandeur, Jacques J.F. & Koopman, Siem Jan, 2007. "An Introduction to State Space Time Series Analysis," OUP Catalogue, Oxford University Press, number 9780199228874, Decembrie.
    3. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    4. Rout, Ullash K. & Blesl, Markus & Fahl, Ulrich & Remme, Uwe & Voß, Alfred, 2009. "Uncertainty in the learning rates of energy technologies: An experiment in a global multi-regional energy system model," Energy Policy, Elsevier, vol. 37(11), pages 4927-4942, November.
    5. Hull, Angela, 2008. "Policy integration: What will it take to achieve more sustainable transport solutions in cities," Transport Policy, Elsevier, vol. 15(2), pages 94-103, March.
    6. Kweon, Young-Jun, 2010. "Data-driven reduction targets for a highway safety plan," Transport Policy, Elsevier, vol. 17(4), pages 230-239, August.
    7. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, Decembrie.
    8. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    9. A. Tolón-Becerra & X. Lastra-Bravo & I. Flores-Parra, 2014. "National road mortality reduction targets under European Union road safety policy: 2011-2020," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(3), pages 264-286, April.
    10. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    11. Kopits, Elizabeth & Cropper, Maureen, 2003. "Traffic fatalities and economic growth," Policy Research Working Paper Series 3035, The World Bank.
    12. Sahal, Devendra, 1985. "Technological guideposts and innovation avenues," Research Policy, Elsevier, vol. 14(2), pages 61-82, April.
    13. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    14. Canoquena, Joao Manuel da Costa, 2013. "Reconceptualising policy integration in road safety management," Transport Policy, Elsevier, vol. 25(C), pages 61-80.
    15. Weijermars, Wendy & Wesemann, Paul, 2013. "Road safety forecasting and ex-ante evaluation of policy in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 64-72.
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    Cited by:

    1. Yu Sang Chang & Dosoung Choi & Hann Earl Kim, 2017. "Dynamic Trends of Carbon Intensities among 127 Countries," Sustainability, MDPI, vol. 9(12), pages 1-21, December.

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