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Using Elicited Choice Probabilities to Estimate Random Utility Models: Preferences for Electricity Reliability

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  • Blass, Asher
  • Lach, Saul
  • Manski, Charles

Abstract

When data on actual choices are not available, researchers studying preferences sometimes pose choice scenarios and ask respondents to state the actions they would choose if they were to face these scenarios. The data on stated choices are then used to estimate random utility models, as if they are data on actual choices. Stated choices may differ from actual ones because researchers typically provide respondents with less information than they would have facing actual choice problems. Elicitation of choice probabilities overcomes this problem by permitting respondents to express uncertainty about their behavior. This paper shows how to use elicited choice probabilities to estimate random utility models with random coefficients and applies the methodology to estimate preferences for electricity reliability in Israel.

Suggested Citation

  • Blass, Asher & Lach, Saul & Manski, Charles, 2008. "Using Elicited Choice Probabilities to Estimate Random Utility Models: Preferences for Electricity Reliability," CEPR Discussion Papers 7030, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:7030
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    1. Manski, Charles F, 1999. "Analysis of Choice Expectations in Incomplete Scenarios," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 49-66, December.
    2. Adeline Delavande, 2008. "Pill, Patch, Or Shot? Subjective Expectations And Birth Control Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 49(3), pages 999-1042, August.
    3. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, September.
    4. Andrew A. Goett & Kathleen Hudson & Kenneth E. Train, 2000. "Customers' Choice Among Retail Energy Suppliers: The Willingness-to-Pay for Service Attributes," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-28.
    5. Caves, Douglas W & Herriges, Joseph A & Windle, Robert J, 1990. "Customer Demand for Service Reliability in the Electric Power Industry: A Synthesis of the Outage Cost Literature," Bulletin of Economic Research, Wiley Blackwell, vol. 42(2), pages 79-119, April.
    6. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March.
    7. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    8. 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.
    9. Yongxin Cai & Iraj Deilami & Kenneth Train, 1998. "Customer Retention in a Competitive Power Market: Analysis of a 'Double-Bounded Plus Follow-Ups' Questionnaire," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 191-215.
    10. Matzkin, Rosa L, 1992. "Nonparametric and Distribution-Free Estimation of the Binary Threshold Crossing and the Binary Choice Models," Econometrica, Econometric Society, vol. 60(2), pages 239-270, March.
    11. F. Thomas Juster, 1966. "Consumer Buying Intentions and Purchase Probability: An Experiment in Survey Design," NBER Books, National Bureau of Economic Research, Inc, number just66-2, June.
    12. 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.
    13. Charles F. Manski, 2007. "Partial Identification Of Counterfactual Choice Probabilities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1393-1410, November.
    14. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-531, May.
    15. Beggs, S. & Cardell, S. & Hausman, J., 1981. "Assessing the potential demand for electric cars," Journal of Econometrics, Elsevier, vol. 17(1), pages 1-19, September.
    16. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
    17. 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.
    18. Manski, Charles F. & Molinari, Francesca, 2010. "Rounding Probabilistic Expectations in Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 219-231.
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    More about this item

    Keywords

    Choice probabilities; stated choices; WTP for electricity reliability;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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