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Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles

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  • Axsen, Jonn
  • Mountain, Dean C.
  • Jaccard, Mark
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    Abstract

    According to intuition and theories of diffusion, consumer preferences develop along with technological change. However, most economic models designed for policy simulation unrealistically assume static preferences. To improve the behavioral realism of an energy-economy policy model, this study investigates the "neighbor effect," where a new technology becomes more desirable as its adoption becomes more widespread in the market. We measure this effect as a change in aggregated willingness to pay under different levels of technology penetration. Focusing on hybrid-electric vehicles, an online survey experiment collected stated preference (SP) data from 535 Canadian and 408 Californian vehicle owners under different hypothetical market conditions. Revealed preference (RP) data was collected from the same respondents by eliciting the year, make and model of recent vehicle purchases from regions with different degrees of HEV popularity: Canada with 0.17% new market share, and California with 3.0% new market share. We compare choice models estimated from RP data only with three joint SP-RP estimation techniques, each assigning a different weight to the influence of SP and RP data in coefficient estimates. Statistically, models allowing more RP influence outperform SP influenced models. However, results suggest that because the RP data in this study is afflicted by multicollinearity, techniques that allow more SP influence in the beta estimates while maintaining RP data for calibrating vehicle class constraints produce more realistic estimates of willingness to pay. Furthermore, SP influenced coefficient estimates also translate to more realistic behavioral parameters for CIMS, allowing more sensitivity to policy simulations.

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    Bibliographic Info

    Paper provided by Institute of Transportation Studies, UC Davis in its series Institute of Transportation Studies, Working Paper Series with number qt02n9j6cv.

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    Date of creation: 03 Mar 2009
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    Handle: RePEc:cdl:itsdav:qt02n9j6cv

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    Keywords: UCD-ITS-RP-09-19; Engineering;

    References

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    1. Chris Bataille, Mark Jaccard, John Nyboer and Nic Rivers, 2006. "Towards General Equilibrium in a Technology-Rich Model with Empirically Estimated Behavioral Parameters," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 93-112.
    2. Nic Rivers & Mark Jaccard, 2005. "Combining Top-Down and Bottom-Up Approaches to Energy-Economy Modeling Using Discrete Choice Methods," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 83-106.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, April.
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    6. Brownston, 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 qt7rf7s3nx, University of California Transportation Center.
    7. Mau, Paulus & Eyzaguirre, Jimena & Jaccard, Mark & Collins-Dodd, Colleen & Tiedemann, Kenneth, 2008. "The 'neighbor effect': Simulating dynamics in consumer preferences for new vehicle technologies," Ecological Economics, Elsevier, vol. 68(1-2), pages 504-516, December.
    8. Adam B. Jaffe & Robert N. Stavins, 1994. "Energy-Efficiency Investments and Public Policy," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 43-66.
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    11. Eckel, Catherine C. & Grossman, Philip J., 2003. "Rebate versus matching: does how we subsidize charitable contributions matter?," Journal of Public Economics, Elsevier, vol. 87(3-4), pages 681-701, March.
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    Cited by:
    1. Ladenburg, Jacob & Lutzeyer, Sanja, 2012. "The economics of visual disamenity reductions of offshore wind farms—Review and suggestions from an emerging field," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(9), pages 6793-6802.
    2. Jérôme Massiani, 2013. "SP surveys for electric and alternative fuel vehicles: are we doing the right thing?," Working Papers 2013_01, Department of Economics, University of Venice "Ca' Foscari".
    3. Driscoll, Áine & Lyons, Seán & Mariuzzo, Franco & Tol, Richard S. J., 2012. "Simulating Demand for Electrical Vehicles using Revealed Preference Data," Papers WP437, Economic and Social Research Institute (ESRI).
    4. Alexandros Dimitropoulos & Piet Rietveld & Jos N. van Ommeren, 2011. "Consumer Valuation of Driving Range: A Meta-Analysis," Tinbergen Institute Discussion Papers 11-133/3, Tinbergen Institute.
    5. Giraudet, Louis-Gaëtan & Guivarch, Céline & Quirion, Philippe, 2012. "Exploring the potential for energy conservation in French households through hybrid modeling," Energy Economics, Elsevier, vol. 34(2), pages 426-445.
    6. Yao, Richard T. & Scarpa, Riccardo & Turner, James A. & Barnard, Tim D. & Rose, John M. & Palma, João H.N. & Harrison, Duncan R., 2014. "Valuing biodiversity enhancement in New Zealand's planted forests: Socioeconomic and spatial determinants of willingness-to-pay," Ecological Economics, Elsevier, vol. 98(C), pages 90-101.
    7. Axsen, Jonn & Orlebar, Caroline & Skippon, Stephen, 2013. "Social influence and consumer preference formation for pro-environmental technology: The case of a U.K. workplace electric-vehicle study," Ecological Economics, Elsevier, vol. 95(C), pages 96-107.
    8. McCoy, Daire & Lyons, Sean, 2014. "The diffusion of electric vehicles: An agent-based microsimulation," MPRA Paper 54560, University Library of Munich, Germany.
    9. Takanori Ida & Kayo Murakami & Makoto Tanaka, 2012. "Keys to Smart Home Diffusion: A Stated Preference Analysis of Smart Meters, Photovoltaic Generation, and Electric/Hybrid Vehicles," Discussion papers e-11-011, Graduate School of Economics Project Center, Kyoto University.
    10. Ziegler, Andreas, 2012. "Individual characteristics and stated preferences for alternative energy sources and propulsion technologies in vehicles: A discrete choice analysis for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1372-1385.
    11. Alexandros Dimitropoulos & Piet Rietveld & Jos N. van Ommeren, 2011. "Consumer Valuation of Driving Range: A Meta-Analysis," Tinbergen Institute Discussion Papers 11-133/3, Tinbergen Institute.
    12. Kloess, Maximilian & Müller, Andreas, 2011. "Simulating the impact of policy, energy prices and technological progress on the passenger car fleet in Austria--A model based analysis 2010-2050," Energy Policy, Elsevier, vol. 39(9), pages 5045-5062, September.
    13. Parsons, George R. & Hidrue, Michael K. & Kempton, Willett & Gardner, Meryl P., 2014. "Willingness to pay for vehicle-to-grid (V2G) electric vehicles and their contract terms," Energy Economics, Elsevier, vol. 42(C), pages 313-324.
    14. Axsen, Jonn & Kurani, Kenneth S., 2013. "Hybrid, plug-in hybrid, or electric—What do car buyers want?," Energy Policy, Elsevier, vol. 61(C), pages 532-543.
    15. Noll, Daniel & Dawes, Colleen & Rai, Varun, 2014. "Solar Community Organizations and active peer effects in the adoption of residential PV," Energy Policy, Elsevier, vol. 67(C), pages 330-343.
    16. Axsen, Jonn & Kurani, Kenneth S., 2009. "Interpersonal Influence within Car Buyers’ Social Networks: Five Perspectives on Plug-in Hybrid Electric Vehicle Demonstration Participants," Institute of Transportation Studies, Working Paper Series qt35w7s3jp, Institute of Transportation Studies, UC Davis.
    17. Hackbarth, André & Madlener, Reinhard, 2011. "Consumer Preferences for Alternative Fuel Vehicles: A Discrete Choice Analysis," FCN Working Papers 20/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    18. Andreas Ziegler, 2010. "Individual Characteristics and Stated Preferences for Alternative Energy Sources and Propulsion Technologies in Vehicles: A Discrete Choice Analysis," CER-ETH Economics working paper series 10/125, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    19. Jérôme Massiani, 2013. "The use of Stated Preferences to forecast alternative fuel vehicles market diffusion: Comparisons with other methods and proposal for a Synthetic Utility Function," Working Papers 2013:12, Department of Economics, University of Venice "Ca' Foscari".
    20. 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.
    21. Hackbarth, André & Madlener, Reinhard, 2013. "Willingness-to-Pay for Alternative Fuel Vehicle Characteristics: A Stated Choice Study for Germany," FCN Working Papers 20/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).

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