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Individual Characteristics and Stated Preferences for Alternative Energy Sources and Propulsion Technologies in Vehicles: A Discrete Choice Analysis

This paper empirically examines the determinants of the demand for alternative energy sources and propulsion technologies in vehicles. The data stem from a stated preference discrete choice experiment with 598 potential car buyers. In order to simulate a realistic automobile purchase situation, seven alternatives were incorporated in each of the six choice sets, i.e. hybrid, gas, biofuel, hydrogen, and electric as well as the common fuels gasoline and diesel. The vehicle types were additionally characterized by a set of attributes, such as purchase price or motor power. Besides these vehicle attributes, our study particularly considers a multitude of individual characteristics, such as socio-demographic and vehicle purchase variables. The econometric analysis with multinomial probit models identifies some population groups with a higher propensity for alternative energy sources or propulsion technologies in vehicles, which can be focused by policy and automobile firms. For example, younger people and people who usually purchase environment-friendly products have a higher stated preference to purchase biofuel, hydrogen, and electric automobiles than other population groups. Methodologically, our study highlights the importance of the inclusion of taste persistence across the choice sets. Furthermore, it suggests a high number of random draws in the Geweke-Hajivassiliou-Keane simulator, which is incorporated in the simulated maximum likelihood estimation and the simulated testing of statistical hypotheses.

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File URL: http://www.cer.ethz.ch/research/WP-10-125.pdf
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Paper provided by CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich in its series CER-ETH Economics working paper series with number 10/125.

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Length: 34 pages
Date of creation: Mar 2010
Date of revision:
Handle: RePEc:eth:wpswif:10-125
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  1. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
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  4. Benno Torgler & María A. García Valiñas & Alison Macintyre, 2008. "Differences in Preferences Towards the Environment: The Impact of a Gender, Age and Parental Effect," Working Papers 2008.18, Fondazione Eni Enrico Mattei.
  5. Brownstone, David & Bunch, David S & Train, Kenneth, 1999. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," University of California Transportation Center, Working Papers qt45f996hh, University of California Transportation Center.
  6. Dagsvik, John K. & Wennemo, Tom & Wetterwald, Dag G. & Aaberge, Rolf, 2002. "Potential demand for alternative fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 36(4), pages 361-384, May.
  7. Geweke, John & Keane, Michael P & Runkle, David, 1994. "Alternative Computational Approaches to Inference in the Multinomial Probit Model," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 609-32, November.
  8. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  9. Vassilis A. Hajivassiliou & Axel Borsch-Supan, 1990. "Smooth Unbiased Multivariate Probability Simulators for Maximum Likelihood Estimation of Limited Dependent Variable Models," Cowles Foundation Discussion Papers 960, Cowles Foundation for Research in Economics, Yale University.
  10. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Institute of Transportation Studies, Working Paper Series qt02n9j6cv, Institute of Transportation Studies, UC Davis.
  11. Benno Torgler & Maria A. Garcia-Valiñas, 2005. "The Determinants of Individuals’ Attitudes Towards Preventing Environmental Damage," Working Papers 2005.110, Fondazione Eni Enrico Mattei.
  12. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
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  14. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September.
  15. Ahn, Jiwoon & Jeong, Gicheol & Kim, Yeonbae, 2008. "A forecast of household ownership and use of alternative fuel vehicles: A multiple discrete-continuous choice approach," Energy Economics, Elsevier, vol. 30(5), pages 2091-2104, September.
  16. Vijverberg, Wim P. M., 1997. "Monte Carlo evaluation of multivariate normal probabilities," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 281-307.
  17. Horne, Matt & Jaccard, Mark & Tiedemann, Ken, 2005. "Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions," Energy Economics, Elsevier, vol. 27(1), pages 59-77, January.
  18. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Resource and Energy Economics, Elsevier, vol. 31(3), pages 221-238, August.
  19. Dansie, B. R., 1985. "Parameter estimability in the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 19(6), pages 526-528, December.
  20. Bunch, David S. & Bradley, Mark & Golob, Thomas F. & Kitamura, Ryuichi & Occhiuzzo, Gareth P., 1993. "Demand for clean-fuel vehicles in California: A discrete-choice stated preference pilot project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(3), pages 237-253, May.
  21. Andreas Ziegler, 2007. "Simulated classical tests in multinomial probit models," Statistical Papers, Springer, vol. 48(4), pages 655-681, October.
  22. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
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