IDEAS home Printed from https://ideas.repec.org/p/zbw/rwirep/58.html

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

Author

Listed:
  • Grösche, Peter
  • Vance, Colin

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, conditional-, random parameters-, and error components logit models are estimated 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

  • Grösche, Peter & Vance, Colin, 2008. "Willingness-to-Pay for Energy Conservation and Free-Ridership on Subsidization – Evidence from Germany," Ruhr Economic Papers 58, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  • Handle: RePEc:zbw:rwirep:58
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/26822/1/574458891.PDF
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:aen:journl:1996v17-03-a03 is not listed on IDEAS
    2. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," Department of Economics, Working Paper Series qt3tb6j874, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    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, 1999. "Forecasting new product penetration with flexible substitution patterns," University of California Transportation Center, Working Papers qt3tb6j874, University of California Transportation Center.
    5. repec:aen:journl:1992v13-04-a03 is not listed on IDEAS
    6. King, Gary & Honaker, James & Joseph, Anne & Scheve, Kenneth, 2001. "Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation," American Political Science Review, Cambridge University Press, vol. 95(1), pages 49-69, March.
    7. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    8. Train, Kenneth E., 1994. "Estimation of net savings from energy-conservation programs," Energy, Elsevier, vol. 19(4), pages 423-441.
    9. 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.
    10. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," Department of Economics, Working Paper Series qt1j6814b3, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    11. 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.
    12. Hartman, Raymond S, 1988. "Self-Selection Bias in the Evaluation of Voluntary Energy Conservation Programs," The Review of Economics and Statistics, MIT Press, vol. 70(3), pages 448-458, August.
    13. 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.
    14. 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.
    15. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," University of California Transportation Center, Working Papers qt1j6814b3, University of California Transportation Center.
    16. 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.
    17. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chlond, Bettina & Gavard, Claire & Jeuck, Lisa, 2021. "Supporting residential energy conservation under constrained public budget: Cost-effectiveness and redistribution analysis of public financial schemes in France," ZEW Discussion Papers 21-056, ZEW - Leibniz Centre for European Economic Research.
    2. Pedro Linares & Xavier Labandeira, 2010. "Energy Efficiency: Economics And Policy," Journal of Economic Surveys, Wiley Blackwell, vol. 24(3), pages 573-592, July.
    3. Bettina Chlond & Claire Gavard & Lisa Jeuck, 2023. "How to Support Residential Energy Conservation Cost-Effectively? An analysis of Public Financial Schemes in France," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 85(1), pages 29-63, May.
    4. Achtnicht, Martin & Madlener, Reinhard, 2014. "Factors influencing German house owners' preferences on energy retrofits," Energy Policy, Elsevier, vol. 68(C), pages 254-263.
    5. Robert Baumhof & Thomas Decker & Klaus Menrad, 2019. "A Comparative Analysis of House Owners in Need of Energy Efficiency Measures but with Different Intentions," Energies, MDPI, vol. 12(12), pages 1-19, June.
    6. Klingler, Anna-Lena, 2017. "Self-consumption with PV+Battery systems: A market diffusion model considering individual consumer behaviour and preferences," Applied Energy, Elsevier, vol. 205(C), pages 1560-1570.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peter Grösche & Colin Vance, 2008. "Willingness-to-Pay for Energy Conservation and Free-Ridership on Subsidization – Evidence from Germany," Ruhr Economic Papers 0058, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    2. Peter Grösche & Colin Vance, 2009. "Willingness to Pay for Energy Conservation and Free-Ridership on Subsidization: Evidence from Germany," The Energy Journal, , vol. 30(2), pages 135-154, April.
    3. Achtnicht, Martin, 2011. "Do environmental benefits matter? Evidence from a choice experiment among house owners in Germany," Ecological Economics, Elsevier, vol. 70(11), pages 2191-2200, September.
    4. Dan Marsh & Lena Mkwara & Riccardo Scarpa, 2011. "Do Respondents’ Perceptions of the Status Quo Matter in Non-Market Valuation with Choice Experiments? An Application to New Zealand Freshwater Streams," Sustainability, MDPI, vol. 3(9), pages 1-23, September.
    5. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    6. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    7. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    8. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.
    9. Achtnicht, Martin & Madlener, Reinhard, 2014. "Factors influencing German house owners' preferences on energy retrofits," Energy Policy, Elsevier, vol. 68(C), pages 254-263.
    10. Campbell, Danny & Hutchinson, W. George & Scarpa, Riccardo, 2006. "Using Discrete Choice Experiments to Derive Individual-Specific WTP Estimates for Landscape Improvements under Agri-Environmental Schemes: Evidence from the Rural Environment Protection Scheme in Ireland," Sustainability Indicators and Environmental Valuation Working Papers 12220, Fondazione Eni Enrico Mattei (FEEM).
    11. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
    12. Grösche Peter & Schmidt Christoph M. & Vance Colin, 2013. "Identifying Free-riding in Home Renovation Programs Using Revealed Preference Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(5-6), pages 600-618, October.
    13. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    14. Laura Mørch Andersen, 2013. "Obtaining reliable Likelihood Ratio tests from simulated likelihood functions," IFRO Working Paper 2013/1, University of Copenhagen, Department of Food and Resource Economics.
    15. Cordera, Rubén & Luigi dell’Olio, & Sipone, Silvia & Moura, José Luis, 2024. "Modeling airport choice for a multi-airport area using a random parameter logit model," Research in Transportation Economics, Elsevier, vol. 104(C).
    16. Campbell, Danny, 2007. "Combining mixed logit models and random effects models to identify the determinants of willingness to pay for rural landscape improvements," 81st Annual Conference, April 2-4, 2007, Reading University, UK 7975, Agricultural Economics Society.
    17. Hess, Stephane & Rose, John M., 2009. "Allowing for intra-respondent variations in coefficients estimated on repeated choice data," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 708-719, July.
    18. Bakhtiari, Fatemeh & Jacobsen, Jette Bredahl & Thorsen, Bo Jellesmark & Lundhede, Thomas Hedemark & Strange, Niels & Boman, Mattias, 2018. "Disentangling Distance and Country Effects on the Value of Conservation across National Borders," Ecological Economics, Elsevier, vol. 147(C), pages 11-20.
    19. 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.
    20. Danny Campbell & George Hutchinson & Riccardo Scarpa, 2006. "Using mixed logit models to derive individual-specific WTP estimates for landscape improvements under agri-environmental schemes: evidence from the Rural Environment Protection Scheme in Ireland," Working Papers 0607, Rural Economy and Development Programme,Teagasc.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:rwirep:58. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/rwiesde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.