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Driving for fun? Comparing the effect of fuel prices on weekday and weekend fuel consumption

  • Frondel, Manuel
  • Vance, Colin

Focusing on individual motorists in car-owning households in Germany, this paper investigates the determinants of automobile travel, with the specific aim of quantifying the effects of fuel prices and person-level attributes on travel conducted over a five-day week and weekend. Our analysis is predicated on the notion that car use is an individual decision, albeit one that is dependent on intra-household allocation processes, thereby building on a growing body of literature that has identified the importance of socioeconomic factors such as employment status, gender, and the presence of children in determining both access to and use of the car. To capture this two-stage decision process, we employ the two-part model, which consists of probit and OLS estimators, and derive elasticity estimates that incorporate both the discrete and continuous choices pertaining to car use. With fuel price elasticity estimates ranging between -Â 0.45 and -Â 0.50, our results suggest raising prices via fuel taxes to be a promising energy conservation and climate protection measure.

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Article provided by Elsevier in its journal Energy Economics.

Volume (Year): 32 (2010)
Issue (Month): 1 (January)
Pages: 102-109

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Handle: RePEc:eee:eneeco:v:32:y:2010:i:1:p:102-109
Contact details of provider: Web page: http://www.elsevier.com/locate/eneco

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  1. Jonathan E. Hughes & Christopher R. Knittel & Daniel Sperling, 2008. "Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand," The Energy Journal, International Association for Energy Economics, vol. 29(1), pages 113-134.
  2. Daniel J. Graham & Stephen Glaister, 2002. "The Demand for Automobile Fuel: A Survey of Elasticities," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 36(1), pages 1-25, January.
  3. Duan, Naihua, et al, 1984. "Choosing between the Sample-Selection Model and the Multi-part Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 283-89, July.
  4. Manuel Frondel & Jorg Peters & Colin Vance, 2008. "Identifying the Rebound: Evidence from a German Household Panel," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 145-164.
  5. Colin Vance & Ralf Hedel, 2007. "The impact of urban form on automobile travel: disentangling causation from correlation," Transportation, Springer, vol. 34(5), pages 575-588, September.
  6. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
  7. Kayser, Hilke A., 2000. "Gasoline demand and car choice: estimating gasoline demand using household information," Energy Economics, Elsevier, vol. 22(3), pages 331-348, June.
  8. Hay, Joel W & Olsen, Randall J, 1984. "Let Them Eat Cake: A Note on Comparing Alternative Models of the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 279-82, July.
  9. Edward C. Norton & Hua Wang & Chunrong Ai, 2004. "Computing interaction effects and standard errors in logit and probit models," Stata Journal, StataCorp LP, vol. 4(2), pages 154-167, June.
  10. Leung, Siu Fai & Yu, Shihti, 1996. "On the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 197-229.
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