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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.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7030.

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Date of creation: Nov 2008
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Handle: RePEc:cpr:ceprdp:7030

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Keywords: Choice probabilities; stated choices; WTP for electricity reliability;

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  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.
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Citations

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Cited by:
  1. 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.
  2. 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.
  3. Arcidiacono, Peter & Hotz, V. Joseph & Kang, Songman, 2010. "Modeling College Major Choices Using Elicited Measures of Expectations and Counterfactuals," IZA Discussion Papers 4738, Institute for the Study of Labor (IZA).
  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. Matthew Wiswall & Basit Zafar, 2011. "Determinants of college major choice: identification using an information experiment," Staff Reports 500, Federal Reserve Bank of New York.
  6. Ralph Stinebrickner & Todd Stinebrickner, 2013. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20134, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  7. 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.
  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. 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.
  10. Charles F. Manski, 2012. "Identification of Preferences and Evaluation of Income Tax Policy," NBER Working Papers 17755, National Bureau of Economic Research, Inc.
  11. 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.

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