Data and code for: A revealed preference test for Choquet and Max-Min expected utility with ambiguity aversion

Principal Investigator(s): View help for Principal Investigator(s) Thomas Demuynck, Université libre de Bruxelles; Clément Staner, Université libre de Bruxelles

Version: View help for Version V1

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Project Citation:

Demuynck, Thomas, and Staner, Clément. Data and code for: A revealed preference test for Choquet and Max-Min expected utility with ambiguity aversion. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-10-09. https://doi.org/10.3886/E193962V1

Project Description

Summary: We develop a revealed preference test for the Choquet Expected Utility model with ambiguity aversion, which does not rely on specific functional form assumptions on the utility index. It is computationally efficient if the number of states is not too large, even for a large number of observations. This is a nice feature compared to other existing revealed preference tests for decision models with ambiguity. We illustrate the usefulness of our results by implementing our test on two experimental datasets from the literature, and we compare the empirical fit of this model to the subjective expected utility model.

Funding Sources: FNRS (FC.31029); EOS (30544469)

Scope of Project

Subject Terms: Revealed Preference Theory; Choquet expected utility; Max-Min expected utility; Subjective expected utility; polymatroid; greedy algorithm

JEL Classification:
      C14 Semiparametric and Nonparametric Methods: General
      C60 Mathematical Methods; Programming Models; Mathematical and Simulation Modeling: General
      D11 Consumer Economics: Theory
      D12 Consumer Economics: Empirical Analysis
      D81 Criteria for Decision-Making under Risk and Uncertainty

Geographic Coverage: For the Ahn et al. data set the experiment was run at the Experimental Social Science Laboratory (Xlab) at the University of California, Berkely (US)., For the Hey and Pace data set 40 participants were recruited from CESARE at LUISS in Rome (Italy) and 89 participants were from EXEC at the University of York (UK).

Universe:

For the Hey and Pace data set subjects (students) were recruited using the ORSEE software.

For the Ahn et al. data set subjects were recuited from all undergraduate classes and staff at UC Berkeley.

Data Type(s): experimental data

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Published Versions

V1 [2024-10-09]

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