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Using Elicited Choice Probabilities To Estimate Random Utility Models: Preferences For Electricity Reliability

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  • Asher A. Blass
  • Saul Lach
  • Charles F. Manski

Abstract

When choice data are not available, researchers studying preferences sometimes ask respondents to state the actions they would choose in choice scenarios. Data on stated choices are then used to estimate random utility models, as if they are data on actual choices. Stated and actual choices may differ because researchers typically provide respondents less information than they would have in actuality. Elicitation of choice probabilities overcomes this problem by permitting respondents to express uncertainty about behavior. This article shows how to use elicited choice probabilities to estimate random utility models and reports estimates of preferences for electricity reliability. Copyright (2010) by the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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Bibliographic Info

Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 51 (2010)
Issue (Month): 2 (05)
Pages: 421-440

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Handle: RePEc:ier:iecrev:v:51:y:2010:i:2:p:421-440

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  1. 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.
  2. 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.
  3. Delavande, Adeline, 2005. "Pill, Patch or Shot? Subjective Expectations and Birth Control Choice," CEPR Discussion Papers 4856, C.E.P.R. Discussion Papers.
  4. 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.
  5. 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 239-70, March.
  6. 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.
  7. 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.
  8. 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.
  9. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, 09.
  10. 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.
  11. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-31, May.
  12. 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.
  13. 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.
  14. 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.
  15. 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, May.
  16. 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.
  17. 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.
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Citations

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Cited by:
  1. Todd R. Stinebrickner & Ralph Stinebrickner, 2011. "Math or Science? Using Longitudinal Expectations Data to Examine the Process of Choosing a College Major," NBER Working Papers 16869, National Bureau of Economic Research, Inc.
  2. Christian A. Vossler & Maurice Doyon & Daniel Rondeau, 2012. "Truth in Consequentiality: Theory and Field Evidence on Discrete Choice Experiments," American Economic Journal: Microeconomics, American Economic Association, vol. 4(4), pages 145-71, November.
  3. Charles Manski, 2012. "Identification of income-leisure preferences and evaluation of income tax policy," CeMMAP working papers CWP07/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  4. Ralph Stinebrickner & Todd R. Stinebrickner, 2014. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," Review of Economic Studies, Oxford University Press, vol. 81(1), pages 426-472.
  5. Arcidiacono, Peter & Hotz, V. Joseph & Kang, Songman, 2012. "Modeling college major choices using elicited measures of expectations and counterfactuals," Journal of Econometrics, Elsevier, vol. 166(1), pages 3-16.
  6. Chad Kendall & Tommaso Nannicini & Francesco Trebbi, 2013. "How Do Voters Respond to Information? Evidence from a Randomized Campaign," Working Papers 486, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  7. Cameron, Trudy Ann & DeShazo, J.R., 2013. "Demand for health risk reductions," Journal of Environmental Economics and Management, Elsevier, vol. 65(1), pages 87-109.
  8. Charles F. Manski, 2012. "Identification of Preferences and Evaluation of Income Tax Policy," NBER Working Papers 17755, National Bureau of Economic Research, Inc.
  9. Matthew Wiswall & Basit Zafar, 2011. "Determinants of college major choice: identification using an information experiment," Staff Reports 500, Federal Reserve Bank of New York.
  10. Pamela Giustinelli, 2011. "Group Decision Making with Uncertain Outcomes: Unpacking Child-Parent Choices of High School Tracks," Working Papers 2011-030, Human Capital and Economic Opportunity Working Group.
  11. Yu Zheng & Juan Pantano, 2012. "Using Subjective Expectations Data to Allow for Unobserved Heterogeneity in Hotz-Miller Estimation Strategies," 2012 Meeting Papers 940, Society for Economic Dynamics.

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