Empirical tests of stochastic binary choice models.
This paper provides an experimental test of stochastic choice models of decisions. Models that admit Fechnerian structure are tested through the repeated pairwise choice problems. Results refute the Fechner hypothesis that characterizing the probability of selecting a given prospect increases in how strongly it is preferred to alternative choices. However, the experimental data lend support to characterizing an individual’s binary choice probability as some scalable functions of the von Neumann–Morgenstern utilities in the risky context.
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The original experimental data are available upon request.
Notes.
Here, for expository purposes, I assume that A is convex, where A is a mixture set in the official model setups.
See Remark 1 in Ryan (2018) for a detailed discussion on this matter.
I conducted a parametric random effects regression analysis to detect whether subjects behave differently in the later experimental repetitions, as opposed to the earlier repetitions, for the binary choice problems in MMT 4. No significant impact from either the ranking of the repetitions or the different subjects was found on the choice pattern for the \(\ \) pairs.
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Acknowledgements.
The author thanks Pavlo Blavatskyy, Denis Bouyssou, David Butler, Simona Fabrizi, John Hey, Steffen Lippert, Alan Rogers, Matthew Ryan, and Ronald Peeters for their valuable comments. The author also thanks the audiences at the 20th Annual Society for check out the post right here Advancement of Economic Theory Meeting hosted by Seoul National University, at the International Summer School on ‘Preferences, Decisions and Games’ hosted by LIP6, Sorbonne University, at the 8th Microeconomic Theory Workshop hosted by Victoria University of Wellington; and at the 2018 Australia New Zealand Workshop in Experimental Economics, as well as the participants in research seminars at the University of Auckland and at Xi’an Jiaotong-Liverpool University for their helpful suggestions. The author also thanks the two anonymous referees and the editor for very useful comments on this paper.
Funding.
This research was funded by the University of Auckland Faculty Research Development Fund #3717595.
Author information.
Affiliations.
International Business School Suzhou, Xi’an Jiaotong-Liverpool University, Business Building, South Campus, 8 Chongwen Road, Suzhou Dushu Lake Science and Education Innovation District, Suzhou Industrial Park, Suzhou, 215123, People’s Republic of China.
Centre for Mathematical Social Science at the University of Auckland, Auckland, New Zealand.
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