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Welfare Effects of Adverse Weather through Speed Changes in Car Commuting Trips

Author

Listed:
  • Muhammad Sabir

    (VU University Amsterdam)

  • Jos van Ommeren

    (VU University Amsterdam)

  • Mark Koetse

    (VU University Amsterdam)

  • Piet Rietveld

    (VU University Amsterdam)

Abstract

This discussion paper led to a publication in 'Networks and Spatial Economics' , 2011, 11(4), 197-199. This paper investigates the welfare effect of adverse weather through changes in the speed of individuals’ car commuting trips in the entire Netherlands. Weather measurements are local and time specific (hourly basis). As most commuters travel twice a day between home and work, we are able to estimate the effect of adverse weather employing panel data techniques, which is novel in this context. We find that for most commuters the welfare effects of adverse weather conditions are negative but small. However, the commuters’ welfare costs due to rain are rather substantial during rush hours in congested areas (and up to 15 percent of the overall commuting costs).

Suggested Citation

  • Muhammad Sabir & Jos van Ommeren & Mark Koetse & Piet Rietveld, 2008. "Welfare Effects of Adverse Weather through Speed Changes in Car Commuting Trips," Tinbergen Institute Discussion Papers 08-087/3, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20080087
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    References listed on IDEAS

    as
    1. Mogens Fosgerau, 2005. "Speed and Income," Journal of Transport Economics and Policy, University of Bath, vol. 39(2), pages 225-240, May.
    2. Bert Zwart & Piet Rietveld & Toon van den Hoorn & Bert van Wee, 1999. "On the relationship between travel time and travel distance of commuters Reported versus network travel data in the Netherlands," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 33(3), pages 269-287.
    3. Jos Van Ommeren & Joyce Dargay, 2006. "The Optimal Choice of Commuting Speed: Consequences for Commuting Time, Distance and Costs," Journal of Transport Economics and Policy, University of Bath, vol. 40(2), pages 279-296, May.
    4. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1999. "Information and time-of-usage decisions in the bottleneck model with stochastic capacity and demand," European Economic Review, Elsevier, vol. 43(3), pages 525-548, March.
    5. Robin Lindsey & Andre de Palma, 1998. "Information and Usage of Congestible Facilities Under Different Pricing Regimes," Canadian Journal of Economics, Canadian Economics Association, vol. 31(3), pages 666-692, August.
    6. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
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    Citations

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    Cited by:

    1. Tsapakis, Ioannis & Cheng, Tao & Bolbol, Adel, 2013. "Impact of weather conditions on macroscopic urban travel times," Journal of Transport Geography, Elsevier, vol. 28(C), pages 204-211.
    2. Nordin, Lina & Arvidsson, Anna K., 2014. "Are winter road maintenance practices energy efficient? A geographical analysis in terms of traffic energy use," Journal of Transport Geography, Elsevier, vol. 41(C), pages 163-174.
    3. Yoon-Ha Lee & Young-Chan Kim & Hyuncheol Seo, 2022. "Selecting Disaster Waste Transportation Routes to Reduce Overlapping of Transportation Routes after Floods," Sustainability, MDPI, vol. 14(5), pages 1-20, March.
    4. Sharaf AlKheder & Abdullah AlOmair, 2022. "Urban traffic prediction using metrological data with fuzzy logic, long short-term memory (LSTM), and decision trees (DTs)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1685-1719, March.
    5. Muhammad Sabir & Mark Koetse & Jos Van Ommeren & Piet Rietveld, 2010. "Weather and Travel Time of Public Transport Trips," Tinbergen Institute Discussion Papers 10-029/3, Tinbergen Institute.

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    More about this item

    Keywords

    adverse weather speed;

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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