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Testing for independence while allowing for probabilistic choice

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  • Graham Loomes
  • Ganna Pogrebna

Abstract

We propose a broad framework for individual choice under risk which can accommodate many stochastic formulations of various deterministic theories. Using this framework to guide an experimental design, we show that most individuals’ departures from the independence axiom cannot be explained by adding a ‘random noise’ term to a deterministic ‘core’ theory which incorporates this axiom. We also find behaviour that cannot be explained in terms of the standard assumptions of Cumulative Prospect Theory, often invoked to account for violations of independence. Our results suggest that ‘similarity’ effects may explain the data better. Copyright The Author(s) 2014

Suggested Citation

  • Graham Loomes & Ganna Pogrebna, 2014. "Testing for independence while allowing for probabilistic choice," Journal of Risk and Uncertainty, Springer, vol. 49(3), pages 189-211, December.
    • Handle: RePEc:kap:jrisku:v:49:y:2014:i:3:p:189-211
    DOI: 10.1007/s11166-014-9205-0
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    References listed on IDEAS

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    Cited by:

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    3. Matthew Ryan, 2015. "A Strict Stochastic Utility Theorem," Economics Bulletin, AccessEcon, vol. 35(4), pages 2664-2672.
    4. Simone Ferrari-Toniolo & Leo Chi U. Seak & Wolfram Schultz, 2022. "Risky choice: Probability weighting explains independence axiom violations in monkeys," Journal of Risk and Uncertainty, Springer, vol. 65(3), pages 319-351, December.

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    More about this item

    Keywords

    Independence axiom; Stochastic choice; Expected utility theory; Prospect theory; C81; C91; D81;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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