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Willingness to Pay among Swedish Households to Avoid Power Outages - A Random Parameter Tobit Model Approach

Author

Listed:
  • Carlsson, Fredrik

    () (Department of Economics, School of Economics and Commercial Law, Göteborg University)

  • Martinsson, Peter

    () (Department of Economics, School of Economics and Commercial Law, Göteborg University)

Abstract

Using a contingent valuation survey, we elicit Swedish households’ willingness to pay (WTP) to avoid power outages. In the study respondents are asked to state their WTP for avoiding nine different types of outages. We therefore apply a random parameter Tobit model since there is cross-sectional heterogeneity and a proportion of zero responses. Based on the estimations, we find that the WTP depends positively on the duration of the outages, and that WTP is significantly higher for unplanned outages. The overall variation in the WTP due to observed heterogeneity in housing and socio-economic variables is small compared to the pure effects of power outages. Policy implications of those findings are discussed.

Suggested Citation

  • Carlsson, Fredrik & Martinsson, Peter, 2004. "Willingness to Pay among Swedish Households to Avoid Power Outages - A Random Parameter Tobit Model Approach," Working Papers in Economics 154, University of Gothenburg, Department of Economics.
  • Handle: RePEc:hhs:gunwpe:0154
    Note: Published in Energy Journal, 2007, Vol 28, pp. 75-89.
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    References listed on IDEAS

    as
    1. Fredrik Carlsson & Olof Johansson-Stenman, 2000. "Willingness to pay for improved air quality in Sweden," Applied Economics, Taylor & Francis Journals, vol. 32(6), pages 661-669.
    2. Richard Carson & Nicholas Flores & Norman Meade, 2001. "Contingent Valuation: Controversies and Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 19(2), pages 173-210, June.
    3. Michael J. Doane & Raymand S. Hartman & Chi-Keung Woo, 1988. "Household Preference for Interruptible Rate Options and the Revealed Value of Service Reliability," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 121-134.
    4. Fredrik Carlsson & Olof Johansson-Stenman & Peter Martinsson, 2004. "Is Transport Safety More Valuable in the Air?," Journal of Risk and Uncertainty, Springer, vol. 28(2), pages 147-163, March.
    5. Richard Carson & Theodore Groves, 2007. "Incentive and informational properties of preference questions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 37(1), pages 181-210, May.
    6. Bengt Kriström, 1993. "Comparing continuous and discrete contingent valuation questions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 3(1), pages 63-71, February.
    7. Beenstock, Michael & Goldin, Ephraim & Haitovsky, Yoel, 1998. "Response bias in a conjoint analysis of power outages," Energy Economics, Elsevier, vol. 20(2), pages 135-156, April.
    8. Thomas C. Brown & Patricia A. Champ & Richard C. Bishop & Daniel W. McCollum, 1996. "Which Response Format Reveals the Truth about Donations to a Public Good?," Land Economics, University of Wisconsin Press, vol. 72(2), pages 152-166.
    9. John List & Craig Gallet, 2001. "What Experimental Protocol Influence Disparities Between Actual and Hypothetical Stated Values?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 20(3), pages 241-254, November.
    10. Michael J. Doane & Raymond S. Hartman & Chi-Keung Woo, 1988. "Households' Perceived Value of Service Reliability: An Analysis of Contingent Valuation Data," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 135-150.
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    More about this item

    Keywords

    Power outages; Contingent Valuation; Random parameters; Tobit model;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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