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Identifying Free-Riding in Energy-Conservation Programs Using Revealed Preference Data

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  • Grösche, Peter
  • Schmidt, Christoph M.
  • Vance, Colin

Abstract

Identifying the incidence of free-ridership is significant to a range of issues relevant to program evaluation, including the calculation of net program benefits and more general assessments of political acceptability. Estimates of free-ridership in the area of energy policy frequently rely on ex-post surveys that ask program participants whether they would have behaved differently in the absence of program support. The present paper proposes an ex-ante approach to the calculation of the free-rider share using revealed preference data on home renovations from Germany's residential sector. We employ a discrete-choice model to simulate the effect of grants on renovation choices, the output from which is used to assess the extent of free-ridership under a contemporary subsidy program. Aside from its simplicity, a key advantage of the approach is that it bestows policymakers with an estimate of free-ridership prior to program implementation.

Suggested Citation

  • Grösche, Peter & Schmidt, Christoph M. & Vance, Colin, 2009. "Identifying Free-Riding in Energy-Conservation Programs Using Revealed Preference Data," Ruhr Economic Papers 99, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:99
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
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    Citations

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    Cited by:

    1. Nicholas Rivers and Leslie Shiell, 2016. "Free-Riding on Energy Efficiency Subsidies: the Case of Natural Gas Furnaces in Canada," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    2. Wasi, Nada & Carson, Richard T., 2013. "The influence of rebate programs on the demand for water heaters: The case of New South Wales," Energy Economics, Elsevier, vol. 40(C), pages 645-656.
    3. Marie-Laure Nauleau, 2013. "Heavy subsidization reduces free-ridership : Evidence from an econometric study of the French dwelling insulation tax credit," Working Papers hal-00866445, HAL.
    4. Löschel, Andreas & Reif, Christiane & Kesternich, Martin & Koesler, Simon & Osberghaus, Daniel & Korioth, Stefan, 2011. "Lösungsansätze zur systemeffizienten Ausgestaltung der nationalen Mittelverwendung der Einnahmen aus der Versteigerung von Zertifikaten im Rahmen des EU-ETS: Endbericht, März 2011," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 110535.
    5. Marie-Laure Nauleau, 2013. "Heavy subsidization reduces free-ridership : Evidence from an econometric study of the French dwelling insulation tax credit," CIRED Working Papers hal-00866445, HAL.

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    More about this item

    Keywords

    Energy efficiency; residential sector; random utility model; discrete choice simulation;
    All these 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

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