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Consumer willingness to pay for vehicle attributes: What do we Know?

Author

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  • Greene, David
  • Hossain, Anushah
  • Hofmann, Julia
  • Helfand, Gloria
  • Beach, Robert

Abstract

As standards for vehicle greenhouse gas emissions and fuel economy have become more stringent, concerns have arisen that the incorporation of fuel-saving technologies may entail tradeoffs with other vehicle attributes important to consumers such as acceleration performance. Assessing the effects of these tradeoffs on consumer welfare requires estimates of both the degree of the tradeoffs, and consumer willingness to pay (WTP) for the foregone benefits. This paper has two objectives. The first is to review recent literature that presents, or can be used to calculate, marginal WTP (MWTP) for vehicle attributes to describe the attributes that have been studied and the estimated MWTP values. We found 52 U.S.-focused papers with sufficient data to calculate WTP values for 142 different vehicle attributes, which we organized into 15 general groups of comfort, fuel availability, fuel costs, fuel type, incentives, model availability, non-fuel operating costs, performance, pollution, prestige, range, reliability, safety, size, and vehicle type. Measures of dispersion around central MWTP values typically show large variation in MWTP values for attributes. We explore factors that may contribute to this large variation via analysis of variance (ANOVA) and find that, although most have statistically significant effects, they account for only about one third of the observed variation. Case studies of papers that provide estimates from a variety of model formulations and estimation methods suggest that decisions made by researchers can strongly influence MWTP estimates. The paper’s second objective is to seek consensus estimates for WTP for fuel cost reduction and increased acceleration performance. Meta-analysis of MWTP for reduced fuel cost indicates that estimates based on revealed vs. stated preference data differ, as do estimates from models that account for endogeneity and those that do not. We find greater consistency in estimates of MWTP for acceleration despite substantial uncertainty about the overall mean. We conclude with recommendations for improving the understanding of consumers’ MWTP for vehicle attributes.

Suggested Citation

  • Greene, David & Hossain, Anushah & Hofmann, Julia & Helfand, Gloria & Beach, Robert, 2018. "Consumer willingness to pay for vehicle attributes: What do we Know?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 258-279.
  • Handle: RePEc:eee:transa:v:118:y:2018:i:c:p:258-279
    DOI: 10.1016/j.tra.2018.09.013
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    1. Walter McManus, 2007. "The Link Between Gasoline Prices and Vehicle Sales," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 42(1), pages 53-60, January.
    2. Hidrue, Michael K. & Parsons, George R. & Kempton, Willett & Gardner, Meryl P., 2011. "Willingness to pay for electric vehicles and their attributes," Resource and Energy Economics, Elsevier, vol. 33(3), pages 686-705, September.
    3. James Murphy & P. Allen & Thomas Stevens & Darryl Weatherhead, 2005. "A Meta-analysis of Hypothetical Bias in Stated Preference Valuation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 30(3), pages 313-325, March.
    4. Dimitropoulos, Alexandros & Rietveld, Piet & van Ommeren, Jos N., 2013. "Consumer valuation of changes in driving range: A meta-analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 55(C), pages 27-45.
    5. Molly Espey & Santosh Nair, 2005. "Automobile Fuel Economy: What Is It Worth?," Contemporary Economic Policy, Western Economic Association International, vol. 23(3), pages 317-323, July.
    6. Carson, Richard T. & Czajkowski, Mikołaj, 2019. "A new baseline model for estimating willingness to pay from discrete choice models," Journal of Environmental Economics and Management, Elsevier, vol. 95(C), pages 57-61.
    7. Goldberg, Pinelopi Koujianou, 1995. "Product Differentiation and Oligopoly in International Markets: The Case of the U.S. Automobile Industry," Econometrica, Econometric Society, vol. 63(4), pages 891-951, July.
    8. Loomis, John B., 2014. "2013 WAEA Keynote Address: Strategies for Overcoming Hypothetical Bias in Stated Preference Surveys," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(1), pages 1-13, April.
    9. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    10. 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.
    11. Whitefoot, Kate S. & Skerlos, Steven J., 2012. "Design incentives to increase vehicle size created from the U.S. footprint-based fuel economy standards," Energy Policy, Elsevier, vol. 41(C), pages 402-411.
    12. Amil Petrin, 2002. "Quantifying the Benefits of New Products: The Case of the Minivan," Journal of Political Economy, University of Chicago Press, vol. 110(4), pages 705-729, August.
    13. Thomas Klier & Joshua Linn, 2012. "New‐vehicle characteristics and the cost of the Corporate Average Fuel Economy standard," RAND Journal of Economics, RAND Corporation, vol. 43(1), pages 186-213, March.
    14. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.
    15. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    16. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    17. Brownstone, David & Bunch, David S & Golob, Thomas F & Ren, Weiping, 1996. "A Transactions Choice Model for Forecasting Demand for Alternative-Fuel Vehicles," University of California Transportation Center, Working Papers qt3sm7w9zk, University of California Transportation Center.
    18. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    19. Bliemer, Michiel C.J. & Rose, John M., 2013. "Confidence intervals of willingness-to-pay for random coefficient logit models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 199-214.
    20. Daziano, Ricardo A., 2013. "Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range," Resource and Energy Economics, Elsevier, vol. 35(3), pages 429-450.
    21. Evangelos Kontopantelis & David Reeves, 2010. "metaan: Random-effects meta-analysis," Stata Journal, StataCorp LP, vol. 10(3), pages 395-407, September.
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    Cited by:

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    5. Philip, Thara & Whitehead, Jake & Prato, Carlo G., 2023. "Adoption of electric vehicles in a laggard, car-dependent nation: Investigating the potential influence of V2G and broader energy benefits on adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
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    7. Doremus, Jacqueline & Helfand, Gloria & Liu, Changzheng & Donahue, Marie & Kahan, Ari & Shelby, Michael, 2019. "Simpler is better: Predicting consumer vehicle purchases in the short run," Energy Policy, Elsevier, vol. 129(C), pages 1404-1415.
    8. Long, Zoe & Kormos, Christine & Sussman, Reuven & Axsen, Jonn, 2021. "MPG, fuel costs, or savings? Exploring the role of information framing in consumer valuation of fuel economy using a choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 109-127.
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    12. Ishengoma, Esther K. & Gabriel, Genoveva, 2021. "Factors influencing the payment of costs of converting oil-to CNG-fuelled cars in a market dominated by used-cars," Energy Policy, Elsevier, vol. 156(C).
    13. Greene, David L. & Greenwald, Judith M. & Ciez, Rebecca E., 2020. "U.S. fuel economy and greenhouse gas standards: What have they achieved and what have we learned?," Energy Policy, Elsevier, vol. 146(C).
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    15. Brown, Marilyn A. & Kale, Snehal & Cha, Min-Kyeong & Chapman, Oliver, 2023. "Exploring the willingness of consumers to electrify their homes," Applied Energy, Elsevier, vol. 338(C).

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    More about this item

    Keywords

    Vehicle choice; Fuel efficiency; Vehicle attribute; Willingness to pay;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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