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Capturing Preferences Under Incomplete Scenarios Using Elicited Choice Probabilities

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  • Herriges, Joseph A.
  • Bhattacharjee, Subhra
  • Kling, Catherine L.

Abstract

Manski (1999) proposed an approach for dealing with a particular form respondent uncertainty in discrete choice settings, particularly relevant in survey based research when the uncertainty stems from the incomplete description of the choice scenarios. Specifically, he suggests eliciting choice probabilities from respondents rather than their single choice of an alternative. A recent paper in IER by Blass et al. (2010) further develops the approach and presents the first empirical application. This paper extends the literature in a number of directions, examining the linkage between elicited choice probabilities and the more common discrete choice elicitation format. We also provide the first convergent validity test of the elicited choice probability format vis-\`a-vis the standard discrete choice format in a split sample experiment. Finally, we discuss the differences between welfare measures that can be derived from elicited choice probabilities versus those that can obtained from discrete choice responses.

Suggested Citation

  • Herriges, Joseph A. & Bhattacharjee, Subhra & Kling, Catherine L., 2011. "Capturing Preferences Under Incomplete Scenarios Using Elicited Choice Probabilities," Staff General Research Papers Archive 32626, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:32626
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    References listed on IDEAS

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    1. de Palma, Andre & Myers, Gordon M & Papageorgiou, Yorgos Y, 1994. "Rational Choice under an Imperfect Ability to Choose," American Economic Review, American Economic Association, vol. 84(3), pages 419-440, June.
    2. Andre Palma & Moshe Ben-Akiva & David Brownstone & Charles Holt & Thierry Magnac & Daniel McFadden & Peter Moffatt & Nathalie Picard & Kenneth Train & Peter Wakker & Joan Walker, 2008. "Risk, uncertainty and discrete choice models," Marketing Letters, Springer, vol. 19(3), pages 269-285, December.
      • André de Palma & Moshe Ben-Akiva & David Brownstone & Charles Holt & Thierry Magnac & Daniel McFadden & Peter Moffatt & Nathalie Picard & Kenneth Train & Peter Wakker & Joan Walker, 2008. "Risk, Uncertainty and Discrete Choice Models," THEMA Working Papers 2008-02, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
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    Cited by:

    1. Kettlewell, Nathan & Walker, Matthew J. & Yoo, Hong Il, 2024. "Alternative Models of Preference Heterogeneity for Elicited Choice Probabilities," IZA Discussion Papers 16821, Institute of Labor Economics (IZA).
    2. Pedersen, Line Bjørnskov & Mørkbak, Morten Raun & Scarpa, Riccardo, 2020. "Handling resolvable uncertainty from incomplete scenarios in future doctors' job choice – Probabilities vs discrete choices," Journal of choice modelling, Elsevier, vol. 34(C).
    3. Riccardo Scarpa & Claudia Bazzani & Diego Begalli & Roberta Capitello, 2021. "Resolvable and Near‐epistemic Uncertainty in Stated Preference for Olive Oil: An Empirical Exploration," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(2), pages 335-369, June.
    4. Kim, Hyeon-Woong & Sung, Jae-hoon, 2024. "An Analysis of Preference for the Rural Residential environment and Landscape Improvements," 2024 Annual Meeting, July 28-30, New Orleans, LA 343815, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    discrete choice; Elicited Choice Probabilities;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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