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Conditional Independence in a Binary Choice Experiment

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  • Nathaniel T. Wilcox

    (Economics Science Institute, Chapman University)

Abstract

Experimental and behavioral economists, as well as psychologists, commonly assume conditional independence of choices when constructing likelihood functions for structural estimation. 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 contemporary state-of-the-art experimental mechanisms and designs, the current evidence suggests that conditional independence is an acceptable assumption for analyzing data so generated.

Suggested Citation

  • Nathaniel T. Wilcox, 2018. "Conditional Independence in a Binary Choice Experiment," Working Papers 18-08, Chapman University, Economic Science Institute.
  • Handle: RePEc:chu:wpaper:18-08
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    File URL: https://digitalcommons.chapman.edu/esi_working_papers/246/
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Alternation; Conditional Independence; Choice Under Risk; Discrete Choice; Persistence; Random Lottery Incentive; Random Lottery Selection; Random Problem Selection; Random Round Payoff;
    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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