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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 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.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14451.

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Date of creation: Oct 2008
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Publication status: published as Asher A. Blass & Saul Lach & Charles F. Manski, 2010. "Using Elicited Choice Probabilities To Estimate Random Utility Models: Preferences For Electricity Reliability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(2), pages 421-440, 05.
Handle: RePEc:nbr:nberwo:14451

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  6. Delavande, Adeline, 2005. "Pill, Patch or Shot? Subjective Expectations and Birth Control Choice," CEPR Discussion Papers 4856, C.E.P.R. Discussion Papers.
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Citations

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Cited by:
  1. Charles F. Manski, 2012. "Identification of Preferences and Evaluation of Income Tax Policy," NBER Working Papers 17755, National Bureau of Economic Research, Inc.
  2. 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.
  3. 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.
  4. Kendall, Chad & Nannicini, Tommaso & Trebbi, Francesco, 2013. "How Do Voters Respond to Information? Evidence from a Randomized Campaign," IZA Discussion Papers 7340, Institute for the Study of Labor (IZA).
  5. 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.
  6. Todd Stinebrickner & Ralph Stinebrickner, 2011. "Math or Science? Using Longitudinal Expectations Data to Examine the Process of Choosing a College Major," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20111, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  7. 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.
  8. 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.
  9. 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.
  10. Matthew Wiswall & Basit Zafar, 2011. "Determinants of college major choice: identification using an information experiment," Staff Reports 500, Federal Reserve Bank of New York.
  11. 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.

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