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Conditional independence in a binary choice experiment

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  • Nathaniel T. Wilcox

    (Appalachian State University)

Abstract

Experimental and behavioral economists, as well as psychologists, commonly assume conditional independence of choices when constructing likelihood functions for structural estimation of choice functions. I test this assumption using data from a new experiment designed for this purpose. Within the limits of the experiment’s identifying restriction and designed power to detect deviations from conditional independence, conditional independence is not rejected. In naturally occurring data, concerns about violations of conditional independence are certainly proper and well-taken (for well-known reasons). However, when an experimenter employs the particular experimental mechanisms and designs used here, the findings suggest that conditional independence is an acceptable assumption for analyzing data so generated.

Suggested Citation

  • Nathaniel T. Wilcox, 2024. "Conditional independence in a binary choice experiment," Journal of Risk and Uncertainty, Springer, vol. 68(3), pages 205-225, June.
    • Handle: RePEc:kap:jrisku:v:68:y:2024:i:3:d:10.1007_s11166-024-09431-9
    DOI: 10.1007/s11166-024-09431-9
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    More about this item

    Keywords

    Alternation; Conditional independence; Choice under risk; Discrete choice; Persistence; Random problem selection;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • 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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