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Modifying the Rebound: It Depends!: Explaining Mobility Behaviour on the Basis of the German Socio-Economic Panel

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  • Wenzel Matiaske
  • Roland Menges
  • Martin Spieß

Abstract

We address the empirical question to which extent higher fuel efficiency of cars affects additional travel and how this behavioural aspect is modified by additional variables. The data set used to estimate a theoretical model of the rebound effect covers two panel waves, 1998 and 2003, taken from the German Socio-Economic Panel (SOEP). To take full advantage of the information in the data available, and to avoid problems due to possible selection effects, we estimated an unbalanced two-wave random effects panel model. Our results suggest that in line with the rebound hypothesis, there is a negative effect of car efficiency on the kilometers driven. That is, the lower the fuel consumption, the larger the driven distance. However, contrasting recent empirical literature about the rebound effect in the transportation sector, this seems to be true only for cars with a consumption of more than roughly eight liters per hundred kilometers. In addition, we find a positive diesel effect, which implies that owning a diesel engined car, has a positive effect on the driven distance. Both effects can be interpreted as support for the rebound hypothesis, although not in a simple linear way. Moreover, it can be shown that some "soft" variables such as certain attitudes towards the environment tend to amplify this non-linear rebound effect. Our results support the general direction of the rebound effect on households travel activities. But because of the remaining political relevance of the rebound effect, they also highlight the importance of accounting for additional behavioural variables which tend to influence individual mobility behaviour. Hence, the classical interpretation of the rebound as a linear effect of advances in fuel economy on individual travel has to be questioned.

Suggested Citation

  • Wenzel Matiaske & Roland Menges & Martin Spieß, 2009. "Modifying the Rebound: It Depends!: Explaining Mobility Behaviour on the Basis of the German Socio-Economic Panel," SOEPpapers on Multidisciplinary Panel Data Research 174, DIW Berlin, The German Socio-Economic Panel (SOEP).
  • Handle: RePEc:diw:diwsop:diw_sp174
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    References listed on IDEAS

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    Cited by:

    1. Weber, Sylvain, 2019. "Consumers' preferences on the Swiss car market: A revealed preference approach," Transport Policy, Elsevier, vol. 75(C), pages 109-118.
    2. Frondel, Manuel & Martinez Flores, Fernanda & Vance, Colin, 2016. "Heterogeneous rebound effects: Comparing estimates from discrete-continuous models," Ruhr Economic Papers 601, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Wen, Fenghua & Ye, Zhengke & Yang, Huaidong & Li, Ke, 2018. "Exploring the rebound effect from the perspective of household: An analysis of China's provincial level," Energy Economics, Elsevier, vol. 75(C), pages 345-356.
    4. Ritter, Nolan, 2012. "Beyond the Average Elasticity – Applying Quantile Panel Regression to German Household Mobility Data," Ruhr Economic Papers 392, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Johannes Buhl, 2014. "Revisiting Rebound Effects from Material Resource Use. Indications for Germany Considering Social Heterogeneity," Resources, MDPI, vol. 3(1), pages 1-17, February.
    6. Carlena Cochi Ficano & Patrick Thompson, 2014. "Estimating Rebound Effects in Personal Automotive Transport: Gas Price and the Presence of Hybrids," The American Economist, Sage Publications, vol. 59(2), pages 167-175, November.
    7. Nolan Ritter, 2012. "Beyond the Average Elasticity – Applying Quantile Panel Regression to German Household Mobility Data," Ruhr Economic Papers 0392, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    8. Schall, Dominik L. & Wolf, Menas & Mohnen, Alwine, 2016. "Do effects of theoretical training and rewards for energy-efficient behavior persist over time and interact? A natural field experiment on eco-driving in a company fleet," Energy Policy, Elsevier, vol. 97(C), pages 291-300.
    9. Dimitropoulos, Alexandros & Oueslati, Walid & Sintek, Christina, 2018. "The rebound effect in road transport: A meta-analysis of empirical studies," Energy Economics, Elsevier, vol. 75(C), pages 163-179.
    10. Siskos, Pelopidas & Capros, Pantelis & De Vita, Alessia, 2015. "CO2 and energy efficiency car standards in the EU in the context of a decarbonisation strategy: A model-based policy assessment," Energy Policy, Elsevier, vol. 84(C), pages 22-34.
    11. Murtaza Haider & Randall Shannon & George P. Moschis, 2022. "Sustainable Consumption Research and the Role of Marketing: A Review of the Literature (1976–2021)," Sustainability, MDPI, vol. 14(7), pages 1-36, March.
    12. Rosal, Ignacio del, 2022. "European dieselization: Policy insights from EU car trade," Transport Policy, Elsevier, vol. 115(C), pages 181-194.
    13. Yu, Biying & Zhang, Junyi & Fujiwara, Akimasa, 2013. "Evaluating the direct and indirect rebound effects in household energy consumption behavior: A case study of Beijing," Energy Policy, Elsevier, vol. 57(C), pages 441-453.
    14. Seebauer, Sebastian, 2017. "Individual Drivers for Direct and Indirect Rebound Effects: A Survey Study of Electric Vehicles and Building Insulation in Austria," FCN Working Papers 17/2017, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    15. Biying Yu & Junyi Zhang & Akimasa Fujiwara, 2016. "Who rebounds in the private transport sector? A comparative analysis between Beijing and Tokyo," Environment and Planning B, , vol. 43(3), pages 561-579, May.
    16. repec:zbw:rwirep:0392 is not listed on IDEAS
    17. ten Dam, Chris Djie & Kramer, Gert Jan & Ettema, Dick & Koning, Vinzenz, 2022. "Spatial and sociodemographic determinants of energy consumption for personal mobility in the Netherlands," Journal of Transport Geography, Elsevier, vol. 98(C).

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    More about this item

    Keywords

    energy demand; rebound effect; panel data analysis;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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