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What would households pay for a reduction of automobile traffic? Evidence from nine German cities

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  • Wellmann, Nicolas
  • Czarnowske, Daniel

Abstract

This paper quantifies the marginal willingness to pay for a reduction of automobile traffic. By using a new structural approach in a hedonic framework by Bishop and Timmins 2019 we are able to avoid common issues in hedonic studies using instrumental variables. Our analysis is based on data from nine large cities in Germany between 2016 and 2019 and includes 533,402 detailed observations at the apartment level as well as for various points of interest. To the best of our knowledge this is the first paper to conduct this analysis for Germany. We estimate that the average willingness to pay for a reduction of traffic by city and per year ranges between €30.3-59.2 for a 10% reduction, €93.8-158.3 for a 20% reduction and €190.6-252 for a 30% reduction. The highest willingness to pay for a reduction of traffic is observed in Frankfurt am Main, the lowest in Leipzig. Further, we compute the expected gains for a reduction of traffic at the city level. In addition to the willingness to pay for a reduction of traffic, this considers the composition of the road network as well as for the number of households. Accordingly, these expected gains amount to €163,970-1,019,454€ for a 10% reduction, €484,023-3,261,837 for a 20% reduction, and €1,018,240-6,727,148 for a 30% reduction. The highest expected gains for a reduction of traffic is observed in Munich, the lowest in Leipzig

Suggested Citation

  • Wellmann, Nicolas & Czarnowske, Daniel, 2021. "What would households pay for a reduction of automobile traffic? Evidence from nine German cities," DICE Discussion Papers 361, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
  • Handle: RePEc:zbw:dicedp:361
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    References listed on IDEAS

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    1. Kahn, Shulamit & Lang, Kevin, 1988. "Efficient Estimation of Structural Hedonic Systems," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(1), pages 157-166, February.
    2. Epple, Dennis, 1987. "Hedonic Prices and Implicit Markets: Estimating Demand and Supply Functions for Differentiated Products," Journal of Political Economy, University of Chicago Press, vol. 95(1), pages 59-80, February.
    3. Beland, Louis-Philippe & Brent, Daniel A., 2018. "Traffic and crime," Journal of Public Economics, Elsevier, vol. 160(C), pages 96-116.
    4. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
    5. Konstantin A. Kholodilin & Andreas Mense & Claus Michelsen, 2016. "Market Break or Simply Fake? Empirics on the Causal Effects of Rent Controls in Germany," Discussion Papers of DIW Berlin 1584, DIW Berlin, German Institute for Economic Research.
    6. Bishop, Kelly C. & Timmins, Christopher, 2019. "Estimating the marginal willingness to pay function without instrumental variables," Journal of Urban Economics, Elsevier, vol. 109(C), pages 66-83.
    7. Gee, Gilbert C. & Takeuchi, D.T.David T., 2004. "Traffic stress, vehicular burden and well-being: A multilevel analysis," Social Science & Medicine, Elsevier, vol. 59(2), pages 405-414, July.
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    More about this item

    Keywords

    willingness to pay; traffic; air pollution; hedonic price models; rent prices; environmental policy;
    All these keywords.

    JEL classification:

    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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