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Willingness to Pay for Energy Conservation and Free-Ridership on Subsidization: Evidence from Germany

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  • Peter Grosche
  • Colin Vance

Abstract

Understanding the determinants of home-efficiency improvements is significant to a range of energy policy issues, including the reduction of fossil fuel use and environmental protection. This paper analyzes retrofit choices by assembling a unique data set merging a nationwide household survey from Germany with regional data on wages and construction costs. To explore the influence of both heterogeneous preferences and correlation among the utility of alternatives, we estimate conditional-, random parameters-, and error components logit models that parameterize the influence of costs, energy savings, and household-level socioeconomic attributes on the likelihood of undertaking one of 16 renovation options. We use the model coefficients to derive household-specific marginal Willingness to Pay estimates, and with these assess the extent to which free-ridership may undermine the effectiveness of recently implemented programs that subsidize the costs of retrofits.

Suggested Citation

  • Peter Grosche & Colin Vance, 2009. "Willingness to Pay for Energy Conservation and Free-Ridership on Subsidization: Evidence from Germany," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 135-154.
  • Handle: RePEc:aen:journl:2009v30-02-a07
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    References listed on IDEAS

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    1. Train, Kenneth E., 1994. "Estimation of net savings from energy-conservation programs," Energy, Elsevier, vol. 19(4), pages 423-441.
    2. Gilbert E. Metcalf & Kevin A. Hassett, 1999. "Measuring The Energy Savings From Home Improvement Investments: Evidence From Monthly Billing Data," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 516-528, August.
    3. Quigley, John M & Rubinfeld, Daniel L, 1989. "Unobservables in Consumer Choice: Residential Energy and the Demand for Comfort," The Review of Economics and Statistics, MIT Press, vol. 71(3), pages 416-425, August.
    4. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    5. David A. Hensher & Stewart Jones & William H. Greene, 2007. "An Error Component Logit Analysis of Corporate Bankruptcy and Insolvency Risk in Australia," The Economic Record, The Economic Society of Australia, vol. 83(260), pages 86-103, March.
    6. Banfi, Silvia & Farsi, Mehdi & Filippini, Massimo & Jakob, Martin, 2008. "Willingness to pay for energy-saving measures in residential buildings," Energy Economics, Elsevier, vol. 30(2), pages 503-516, March.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    8. Paul L. Joskow & Donald B. Marron, 1992. "What Does a Negawatt Really Cost? Evidence from Utility Conservation Programs," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 41-74.
    9. 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.
    10. Cameron, Trudy Ann, 1985. "A Nested Logit Model of Energy Conservation Activity by Owners of Existing Single Family Dwellings," The Review of Economics and Statistics, MIT Press, vol. 67(2), pages 205-211, May.
    11. repec:cup:apsrev:v:95:y:2001:i:01:p:49-69_00 is not listed on IDEAS
    12. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
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    JEL classification:

    • F0 - International Economics - - General

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