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New Vehicle Choice, Fuel Economy and Vehicle Incentives: An Analysis of Hybrid Tax Credits and the Gasoline Tax

  • Martin, Elliott William
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    Automobiles impose considerable public costs in the form of emissions and foreign oil dependence. Public policy has thus taken a considerable interest in influencing the technology and fuel economy associated with new vehicles brought to market. In spite of this interest, there is very limited information on the effectiveness of these policies in reducing greenhouse gas emissions or shifting vehicle demands. This is in part due to the fact that modeling the demand for automobiles is wrought with many challenges. These include large choice sets that change frequently over time and significant data collection obstacles. This work proposes a methodology for data development that simplifies many of the challenges associated with data collection in automotive modeling. The methodology explores a technique to merge data on aggregate sales with disaggregate vehicle holdings data to synthesize a complete dataset that preserves the strengths of both. The merged dataset is used to estimate a logit choice model of automotive choice 2 that is applied in evaluating the effectiveness of hybrid tax credits and the gasoline tax in reducing greenhouse gas emissions. Policy simulations suggest that hybrid tax credits have saved an average 1.5 million metric tons of greenhouse gas emissions based on sales between 2006 and 2007. When considered in conjunction with the cost of the policies, the credits appear to have a cost effectiveness ranging between $1000 to $3000 per metric ton of greenhouse gas emissions reduced. Hybrid tax credits are also found to be more effective than a doubling of the gasoline tax in shifting the new vehicle stock towards more fuel efficient vehicles. Finally, the model evaluates the market willingness to pay for fuel cost reduction. The results suggest an average willingness to pay of $522 in purchase price per 1¢ reduction in fuel cost per mile. This means that reasonable circumstances exist in which some buyers will pay more for fuel economy than they save in fuel cost expenses over the life span of their automobiles.

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    Paper provided by University of California Transportation Center in its series University of California Transportation Center, Working Papers with number qt5gd206wv.

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    Date of creation: 01 Oct 2009
    Date of revision:
    Handle: RePEc:cdl:uctcwp:qt5gd206wv
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    1. Nair, Santosh & Espey, Molly, 2004. "Automobile Fuel Economy: What is it Worth?," 2004 Annual meeting, August 1-4, Denver, CO 20102, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
    4. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    5. Jonathan E. Hughes & Christopher R. Knittel & Daniel Sperling, 2006. "Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand," NBER Working Papers 12530, National Bureau of Economic Research, Inc.
    6. Heffner, Reid R., 2007. "Semiotics and Advanced Vehicles: What Hybrid Electric Vehicles (HEVs) Mean and Why it Matters to Consumers," Institute of Transportation Studies, Working Paper Series qt9mw1t4w3, Institute of Transportation Studies, UC Davis.
    7. Kenneth E. Train & Clifford Winston, 2007. "Vehicle Choice Behavior And The Declining Market Share Of U.S. Automakers," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1469-1496, November.
    8. Steven Berry & James Levinsohn & Ariel Pakes, 1998. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," NBER Working Papers 6481, National Bureau of Economic Research, Inc.
    9. Turrentine, Thomas S. & Kurani, Kenneth S., 2007. "Car buyers and fuel economy?," Energy Policy, Elsevier, vol. 35(2), pages 1213-1223, February.
    10. Choo, Sangho & Mokhtarian, Patricia L., 2004. "What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(3), pages 201-222, March.
    11. Herriges, Joseph A. & Kling, Catherine L., 1996. "Testing the consistency of nested logit models with utility maximization," Economics Letters, Elsevier, vol. 50(1), pages 33-39, January.
    12. Berkovec, James, 1985. "Forecasting automobile demand using disaggregate choice models," Transportation Research Part B: Methodological, Elsevier, vol. 19(4), pages 315-329, August.
    13. Kenneth A. Small & Kurt Van Dender, 2006. "Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound Effect," Working Papers 050603, University of California-Irvine, Department of Economics.
    14. McManus, Walter, 2007. "The link between gasoline prices and vehicle sales:economic theory trumps conventional Detroit wisdom," MPRA Paper 3463, University Library of Munich, Germany.
    15. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-90, July.
    16. Train, Kenneth E. & Davis, William B. & Levine, Mark D., 1997. "Fees and rebates on new vehicles: Impacts on fuel efficiency, carbon dioxide emissions, and consumer surplus," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 33(1), pages 1-13, March.
    17. Turrentine, Tom & Kurani, Kenneth S, 2007. "Car buyers and fuel economy?," Institute of Transportation Studies, Working Paper Series qt56x845v4, Institute of Transportation Studies, UC Davis.
    18. Small, Kenneth A, 1987. "A Discrete Choice Model for Ordered Alternatives," Econometrica, Econometric Society, vol. 55(2), pages 409-24, March.
    19. Mannering, Fred L. & Train, Kenneth, 1985. "Recent directions in automobile demand modeling," Transportation Research Part B: Methodological, Elsevier, vol. 19(4), pages 265-274, August.
    20. McCarthy, Patrick S, 1996. "Market Price and Income Elasticities of New Vehicles Demand," The Review of Economics and Statistics, MIT Press, vol. 78(3), pages 543-47, August.
    21. Mannering, Fred & Winston, Clifford & Starkey, William, 2002. "An exploratory analysis of automobile leasing by US households," Journal of Urban Economics, Elsevier, vol. 52(1), pages 154-176, July.
    22. Greene, David L. & Patterson, Philip D. & Singh, Margaret & Li, Jia, 2005. "Feebates, rebates and gas-guzzler taxes: a study of incentives for increased fuel economy," Energy Policy, Elsevier, vol. 33(6), pages 757-775, April.
    23. Cowling, Keith & Cubbin, John, 1972. "Hedonic Price Indexes for United Kingdom Cars," Economic Journal, Royal Economic Society, vol. 82(327), pages 963-78, September.
    24. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    25. Kling, Catherine L. & Herriges, Joseph A., 1995. "Empirical Investigation of the Consistency of Nested Logit Models with Utility Maximization (An)," Staff General Research Papers 1499, Iowa State University, Department of Economics.
    26. Small, Kenneth A., 1994. "Approximate generalized extreme value models of discrete choice," Journal of Econometrics, Elsevier, vol. 62(2), pages 351-382, June.
    27. Berkovec, James & Rust, John, 1985. "A nested logit model of automobile holdings for one vehicle households," Transportation Research Part B: Methodological, Elsevier, vol. 19(4), pages 275-285, August.
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