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Risk-Aversion and Willingness to Pay for Energy Efficient Systems in Rental Apartments

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  • Mehdi Farsi

    () (Center for Energy Policy and Economics CEPE, Department of Management, Technology and Economics, ETH Zurich, Switzerland)

Abstract

This paper uses a random utility model with a non-linear utility function to estimate the consumers’ valuation for energy efficient insulation and ventilation systems in apartment buildings. The proposed model is applied to data from a choice experiment conducted among 264 apartment tenants in Switzerland. The model relaxes the assumption of constant rate of substitution between income and energy-saving measures. These amenities are considered as non-market goods whose advantages are little known thus entailing certain risk-aversion in consumers’ preferences. The non-linear formulation can accommodate the common cases when the non-market attributes are measured by discrete variables. The analysis indicates that assuming constant rate of substitution could bring about misleading estimates of the willingness to pay, especially when the system is combined of several components. The findings provide evidence in favor of consumers’ risk-averse behavior facing choice situations regarding energy-efficient systems. The estimated risk premiums suggest that risk considerations remain a central issue in dealing with energy efficiency in residential buildings.

Suggested Citation

  • Mehdi Farsi, 2008. "Risk-Aversion and Willingness to Pay for Energy Efficient Systems in Rental Apartments," CEPE Working paper series 08-55, CEPE Center for Energy Policy and Economics, ETH Zurich.
  • Handle: RePEc:cee:wpcepe:08-55
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    File URL: http://www.cepe.ethz.ch/publications/workingPapers/CEPE_WP55.pdf
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    Cited by:

    1. Olsthoorn, Mark & Schleich, Joachim & Gassmann, Xavier & Faure, Corinne, 2017. "Free riding and rebates for residential energy efficiency upgrades: A multi-country contingent valuation experiment," Working Papers "Sustainability and Innovation" S10/2017, Fraunhofer Institute for Systems and Innovation Research (ISI).
    2. Qiu, Yueming & Colson, Gregory & Grebitus, Carola, 2014. "Risk preferences and purchase of energy-efficient technologies in the residential sector," Ecological Economics, Elsevier, vol. 107(C), pages 216-229.
    3. Richard G. Newell & Juha Siikamäki, 2014. "Nudging Energy Efficiency Behavior: The Role of Information Labels," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 1(4), pages 555-598.
    4. Ivan Tilov & Benjamin Volland & Mehdi Farsi, 2017. "Interactions in Swiss Households' Energy Demand: A Holistic Approach," IRENE Working Papers 17-11, IRENE Institute of Economic Research.
    5. Schleich, Joachim & Gassmann, Xavier & Faure, Corinne & Meissner, Thomas, 2016. "Making the implicit explicit: A look inside the implicit discount rate," Energy Policy, Elsevier, vol. 97(C), pages 321-331.
    6. repec:eee:appene:v:206:y:2017:i:c:p:1062-1075 is not listed on IDEAS
    7. 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.
    8. Volland, Benjamin, 2017. "The role of risk and trust attitudes in explaining residential energy demand: Evidence from the United Kingdom," Ecological Economics, Elsevier, vol. 132(C), pages 14-30.
    9. Oberst, Christian & Madlener, Reinhard, 2015. "Prosumer Preferences Regarding the Adoption of Micro‐Generation Technologies: Empirical Evidence for German Homeowners," FCN Working Papers 22/2014, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    10. Phillips, Yvonne, 2012. "Landlords versus tenants: Information asymmetry and mismatched preferences for home energy efficiency," Energy Policy, Elsevier, vol. 45(C), pages 112-121.
    11. Paul Thorsnes, 2017. "Heterogeneity in household preferences for energy-efficient heating systems," Working Papers 1713, University of Otago, Department of Economics, revised Dec 2017.
    12. Casaló, Luis V. & Flavián, Carlos & Guinalíu, Miguel & Ekinci, Yuksel, 2015. "Avoiding the dark side of positive online consumer reviews: Enhancing reviews' usefulness for high risk-averse travelers," Journal of Business Research, Elsevier, vol. 68(9), pages 1829-1835.
    13. repec:kap:jcopol:v:40:y:2017:i:4:d:10.1007_s10603-017-9361-0 is not listed on IDEAS
    14. Scott, Fiona L. & Jones, Christopher R. & Webb, Thomas L., 2014. "What do people living in deprived communities in the UK think about household energy efficiency interventions?," Energy Policy, Elsevier, vol. 66(C), pages 335-349.
    15. Ramos, A. & Gago, A. & Labandeira, X. & Linares, P., 2015. "The role of information for energy efficiency in the residential sector," Energy Economics, Elsevier, vol. 52(S1), pages 17-29.
    16. Collins, Matthew & Curtis, John, 2016. "Willingness-to-Pay and Free-Riding in a National Energy Efficiency Retrofit Grant Scheme: A Revealed Preference Approach," Papers WP551, Economic and Social Research Institute (ESRI).

    More about this item

    Keywords

    choice experiment; willingness to pay; risk aversion; energy efficiency; housing;

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • 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
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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