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Monotone additive statistics

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  • Xiaosheng Mu
  • Luciano Pomatto
  • Philipp Strack
  • Omer Tamuz

Abstract

The expectation is an example of a descriptive statistic that is monotone with respect to stochastic dominance, and additive for sums of independent random variables. We provide a complete characterization of such statistics, and explore a number of applications to models of individual and group decision-making. These include a representation of stationary monotone time preferences, extending the work of Fishburn and Rubinstein (1982) to time lotteries. This extension offers a new perspective on risk attitudes toward time, as well as on the aggregation of multiple discount factors. We also offer a novel class of nonexpected utility preferences over gambles which satisfy invariance to background risk as well as betweenness, but are versatile enough to capture mixed risk attitudes.

Suggested Citation

  • Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2021. "Monotone additive statistics," Papers 2102.00618, arXiv.org, revised Apr 2024.
  • Handle: RePEc:arx:papers:2102.00618
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    References listed on IDEAS

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    1. Patrick DeJarnette & David Dillenberger & Daniel Gottlieb & Pietro Ortoleva, 2020. "Time Lotteries and Stochastic Impatience," Econometrica, Econometric Society, vol. 88(2), pages 619-656, March.
    2. Simone Cerreia‐Vioglio & David Dillenberger & Pietro Ortoleva, 2015. "Cautious Expected Utility and the Certainty Effect," Econometrica, Econometric Society, vol. 83, pages 693-728, March.
    3. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2021. "From Blackwell Dominance in Large Samples to Rényi Divergences and Back Again," Econometrica, Econometric Society, vol. 89(1), pages 475-506, January.
    4. Yoram Halevy, 2015. "Time Consistency: Stationarity and Time Invariance," Econometrica, Econometric Society, vol. 83, pages 335-352, January.
    5. Goovaerts, Marc J. & Kaas, Rob & Laeven, Roger J.A. & Tang, Qihe, 2004. "A comonotonic image of independence for additive risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 581-594, December.
    6. Harrell Chesson & W. Viscusi, 2003. "Commonalities in Time and Ambiguity Aversion for Long-Term Risks ," Theory and Decision, Springer, vol. 54(1), pages 57-71, February.
    7. Matthew Rabin & Georg Weizsacker, 2009. "Narrow Bracketing and Dominated Choices," American Economic Review, American Economic Association, vol. 99(4), pages 1508-1543, September.
    8. Luciano Pomatto & Philipp Strack & Omer Tamuz, 2020. "Stochastic Dominance under Independent Noise," Journal of Political Economy, University of Chicago Press, vol. 128(5), pages 1877-1900.
    9. Dekel, Eddie, 1986. "An axiomatic characterization of preferences under uncertainty: Weakening the independence axiom," Journal of Economic Theory, Elsevier, vol. 40(2), pages 304-318, December.
    10. Charalambos D. Aliprantis & Kim C. Border, 2006. "Infinite Dimensional Analysis," Springer Books, Springer, edition 0, number 978-3-540-29587-7, January.
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    Cited by:

    1. Balbus, Łukasz & Reffett, Kevin & Woźny, Łukasz, 2022. "Time-consistent equilibria in dynamic models with recursive payoffs and behavioral discounting," Journal of Economic Theory, Elsevier, vol. 204(C).
    2. Minghao Pan, 2022. "Risk and Intertemporal Preferences over Time Lotteries," Papers 2209.01790, arXiv.org.
    3. Christopher P. Chambers & Alan D. Miller, 2023. "Multiple Adjusted Quantiles," Papers 2305.06354, arXiv.org.
    4. Jianming Xia, 2021. "Optimal Investment with Risk Controlled by Weighted Entropic Risk Measures," Papers 2112.02284, arXiv.org.
    5. Sebastian Ebert, 2021. "Prudent Discounting: Experimental Evidence On Higher Order Time Risk Preferences," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(4), pages 1489-1511, November.

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