IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-11-00791.html

Household car use in France: a demographic and economic analysis

Author

Listed:
  • Roger Collet

    (University of Paris-Est, IFSTTAR)

Abstract

This article provides an evaluation of the effects of age and generation on household car-use behavior in France, and sheds some light on household perception of fuel price volatility. Using repeated cross-section data from the French "Car Fleet" survey, a pseudo-panel averaging households in generational cohorts has been built over the 1988-2008 period. The results from the Age-Cohort-Period analysis reveal that younger households, whose heads were born at a time when cars were already very widespread in the French society, have made more intensive use of the car than their parents or grandparents at the same age, who grew up in less car-dependent times. In addition, the negative impact of fuel price volatility on car use is revealed. It can be interpreted as a sign of risk aversion, leading households to reduce their car mileage when there is an increase in uncertainty about fuel prices. Lastly, we demonstrate that failure to consider the volatility effect may result in an overestimation of household car use elasticity with respect to fuel price.

Suggested Citation

  • Roger Collet, 2012. "Household car use in France: a demographic and economic analysis," Economics Bulletin, AccessEcon, vol. 32(1), pages 475-485.
    • Handle: RePEc:ebl:ecbull:eb-11-00791
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2012/Volume32/EB-12-V32-I1-P44.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Verbeek, Marno & Nijman, Theo, 1992. "Can Cohort Data Be Treated as Genuine Panel Data?," Empirical Economics, Springer, vol. 17(1), pages 9-23.
    2. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Can cohort data be treated as genuine panel data?," Other publications TiSEM d4eada8f-b91c-4fe7-a58c-7, Tilburg University, School of Economics and Management.
    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. Rich, Jeppe & Myhrmann, Marcus Skyum & Mabit, Stefan Eriksen, 2023. "Our children cycle less - A Danish pseudo-panel analysis," Journal of Transport Geography, Elsevier, vol. 106(C).
    2. Vij, Akshay & Gorripaty, Sreeta & Walker, Joan L., 2017. "From trend spotting to trend ’splaining: Understanding modal preference shifts in the San Francisco Bay Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 238-258.
    3. Bussière, Yves D. & Madre, Jean-Loup & Tapia-Villarreal, Irving, 2019. "Will peak car observed in the North occur in the South? A demographic approach with case studies of Montreal, Lille, Juarez and Puebla," Economic Analysis and Policy, Elsevier, vol. 61(C), pages 39-54.
    4. Roger Collet & Laurent Hivert & Jean-Loup Madre, 2012. "Diffusion de l’automobile en France : vers quels plafonds pour la motorisation et l’usage ?," Économie et Statistique, Programme National Persée, vol. 457(1), pages 123-139.
    5. Collet, Roger & de Lapparent, Matthieu & Hivert, Laurent, 2015. "Are French households car-use addicts? A microeconomic perspective," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 54(C), pages 86-94.

    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. Bussolo, Maurizio & Ezebuihe, Jessy Amarachi & Munoz Boudet, Ana Maria & Poupakis, Stavros & Rahman, Tasmia & Sarma, Nayantara, 2022. "Social Norms and Gender Equality : A Descriptive Analysis for South Asia," Policy Research Working Paper Series 10142, The World Bank.
    2. Kasraian, Dena & Maat, Kees & van Wee, Bert, 2018. "Urban developments and daily travel distances: Fixed, random and hybrid effects models using a Dutch pseudo-panel over three decades," Journal of Transport Geography, Elsevier, vol. 72(C), pages 228-236.
    3. Verbeek, Marno & Vella, Francis, 2005. "Estimating dynamic models from repeated cross-sections," Journal of Econometrics, Elsevier, vol. 127(1), pages 83-102, July.
    4. Eskander Alvi & Seife Dendir, 2020. "Wage returns to education in Ethiopia," Oxford Development Studies, Taylor & Francis Journals, vol. 48(1), pages 70-84, June.
    5. Ramón López & Gustavo Anríquez, 2004. "Poverty and Agricultural Growth: Chile in the 1990s," The Electronic Journal of Agricultural and Development Economics, Food and Agriculture Organization of the United Nations, vol. 1(1), pages 6-24.
    6. Sarah Bridges & Simona Mateut, 2009. "Attitudes towards immigration in Europe," Working Papers 2009008, The University of Sheffield, Department of Economics, revised May 2009.
    7. Friedrich Breyer & Normann Lorenz & Thomas Niebel, 2015. "Health care expenditures and longevity: is there a Eubie Blake effect?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(1), pages 95-112, January.
    8. Hong Liu & Wei Tan, 2009. "The Effect of Anti-Smoking Media Campaign on Smoking Behavior: The California Experience," Annals of Economics and Finance, Society for AEF, vol. 10(1), pages 29-47, May.
    9. Koksal, Aycan & Wohlgenant, Michael, 2013. "Pseudo Panel Data Estimation Technique and Rational Addiction Model: An Analysis of Tobacco, Alcohol and Coffee Demands," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150457, Agricultural and Applied Economics Association.
    10. Blank, Steven C., 2005. "Hedging with off-farm income: implications for production and investment decisions across farm sizes," 2005 Annual Meeting, July 6-8, 2005, San Francisco, California 291741, Western Agricultural Economics Association.
    11. Lusi Liao & Sasiwimon Warunsiri Paweenawat, 2021. "The inversion of married women's labour supply and wage: Evidence from Thailand," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 35(1), pages 82-98, May.
    12. Ortiz, Rodrigo & Fernandez, Viviana, 2022. "Business perception of obstacles to innovate: Evidence from Chile with pseudo-panel data analysis," Research in International Business and Finance, Elsevier, vol. 59(C).
    13. Dang,Hai-Anh H. & Lanjouw,Peter F., 2013. "Measuring poverty dynamics with synthetic panels based on cross-sections," Policy Research Working Paper Series 6504, The World Bank.
    14. Marco Lilla, 2016. "Falling Behind or Catching Up? Cross-Country Evidence in Intra-Generational Wages Mobility through Pseudo-Panels," LIS Working papers 669, LIS Cross-National Data Center in Luxembourg.
    15. D'Amato, Alessio & Giaccherini, Matilde & Zoli, Mariangela, 2019. "The Role of Information Sources and Providers in Shaping Green Behaviors. Evidence from Europe," Ecological Economics, Elsevier, vol. 164(C), pages 1-1.
    16. W.F. Maloney & D. Lederman & J. Messina, 2011. "The Fall of Wage Flexibility," World Bank Publications - Reports 23575, The World Bank Group.
    17. Evren Ceritoglu, 2017. "Disentangling Age and Cohorts Effects on Home-Ownership and Housing Wealth in Turkey," Working Papers 1706, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    18. Daniel Bukstein & Nestor Gandelman, 2014. "Intra-Generational Social Mobility and Entrepreneurship in Uruguay," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 51(2), pages 227-245, November.
    19. Beatriz Muriel & Horacio Vera, 2015. "The Effects of Economic Growth on Earnings in Bolivia," Development Research Working Paper Series 08/2015, Institute for Advanced Development Studies.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

    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:ebl:ecbull:eb-11-00791. 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: John P. Conley (email available below). General contact details of provider: .

    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.