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Quantifying Lottery Choice Complexity

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  • Benjamin Enke
  • Cassidy Shubatt

Abstract

We develop interpretable, quantitative indices of the objective and subjective complexity of lottery choice problems that can be computed for any standard dataset. These indices capture the predicted error rate in identifying the lottery with the highest expected value, where the predictions are computed as convex combinations of choice set features. The most important complexity feature in the indices is a measure of the excess dissimilarity of the cumulative distribution functions of the lotteries in the set. Using our complexity indices, we study behavioral responses to complexity out-of-sample across one million decisions in 11,000 unique experimental choice problems. Complexity makes choices substantially noisier, which can generate systematic biases in revealed preference measures such as spurious risk aversion. These effects are very large, to the degree that complexity explains a larger fraction of estimated choice errors than proximity to indifference. Accounting for complexity in structural estimations improves model fit substantially.

Suggested Citation

  • Benjamin Enke & Cassidy Shubatt, 2023. "Quantifying Lottery Choice Complexity," CESifo Working Paper Series 10644, CESifo.
    • Handle: RePEc:ces:ceswps:_10644
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    References listed on IDEAS

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    1. Michael H. Birnbaum, 2005. "Three New Tests of Independence That Differentiate Models of Risky Decision Making," Management Science, INFORMS, vol. 51(9), pages 1346-1358, September.
    2. David Buschena & David Zilberman, 2008. "Generalized expected utility, heteroscedastic error, and path dependence in risky choice," Journal of Risk and Uncertainty, Springer, vol. 36(2), pages 201-201, April.
    3. John D. Hey, 2018. "Experimental investigations of errors in decision making under risk," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 17, pages 381-388, World Scientific Publishing Co. Pte. Ltd..
    4. Huck, Steffen & Weizsacker, Georg, 1999. "Risk, complexity, and deviations from expected-value maximization: Results of a lottery choice experiment," Journal of Economic Psychology, Elsevier, vol. 20(6), pages 699-715, December.
    5. Adrian Bruhin & Helga Fehr-Duda & Thomas Epper, 2010. "Risk and Rationality: Uncovering Heterogeneity in Probability Distortion," Econometrica, Econometric Society, vol. 78(4), pages 1375-1412, July.
    6. Ryan Webb & Paul W. Glimcher & Kenway Louie, 2021. "The Normalization of Consumer Valuations: Context-Dependent Preferences from Neurobiological Constraints," Management Science, INFORMS, vol. 67(1), pages 93-125, January.
    7. Ferdinand M. Vieider, 2018. "Violence and Risk Preference: Experimental Evidence from Afghanistan: Comment," American Economic Review, American Economic Association, vol. 108(8), pages 2366-2382, August.
    8. Yoram Halevy, 2007. "Ellsberg Revisited: An Experimental Study," Econometrica, Econometric Society, vol. 75(2), pages 503-536, March.
    9. Cary Frydman & Lawrence J. Jin, 2023. "On the Source and Instability of Probability Weighting," NBER Working Papers 31573, National Bureau of Economic Research, Inc.
    10. Rubinstein, Ariel, 1988. "Similarity and decision-making under risk (is there a utility theory resolution to the Allais paradox?)," Journal of Economic Theory, Elsevier, vol. 46(1), pages 145-153, October.
    11. Leandro Carvalho & Dan Silverman, 2019. "Complexity and Sophistication," NBER Working Papers 26036, National Bureau of Economic Research, Inc.
    12. Mel Win Khaw & Ziang Li & Michael Woodford, 2021. "Cognitive Imprecision and Small-Stakes Risk Aversion [Linear Mapping of Numbers onto Space Requires Attention]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1979-2013.
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    Cited by:

    1. Benjamin Enke & Thomas Graeber & Ryan Oprea & Thomas W. Graeber, 2023. "Complexity and Hyperbolic Discounting," CESifo Working Paper Series 10861, CESifo.
    2. Jian-Qiao Zhu & Joshua C. Peterson & Benjamin Enke & Thomas L. Griffiths, 2024. "Capturing the Complexity of Human Strategic Decision-Making with Machine Learning," Papers 2408.07865, arXiv.org.
    3. Cassidy Shubatt & Jeffrey Yang, 2024. "Tradeoffs and Comparison Complexity," Papers 2401.17578, arXiv.org, revised Oct 2024.
    4. Jian-Qiao Zhu & Joshua C. Peterson & Benjamin Enke & Thomas L. Griffiths, 2024. "Capturing the Complexity of Human Strategic Decision-Making with Machine Learning," CESifo Working Paper Series 11296, CESifo.

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    Keywords

    complexity; choice under risk; cognitive uncertainty; experiments;
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