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Data dispersion near the boundaries: can it partially explain the problems of decision and utility theories?

Author

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  • Alexander Harin

    (MUH - Modern University for the Humanities - Modern University for the Humanities)

Abstract

An existence theorem for a bias of the mean in the presence of data dispersion is proved. The ultimate aims are to use this theorem to explain the well-known problems of utility and decision theories, such as risk aversion, the underweighting of high and the overweighting of low probabilities, the Allais paradox, etc. The results may be used to estimate preferences, choices, decisions, (ir)rational behavior at data uncertainty, noises and experimental errors in experiments interpretation, probability theory, statistics, management, finance, investment, insurance, etc.

Suggested Citation

  • Alexander Harin, 2013. "Data dispersion near the boundaries: can it partially explain the problems of decision and utility theories?," Working Papers hal-00851022, HAL.
    • Handle: RePEc:hal:wpaper:hal-00851022
    Note: View the original document on HAL open archive server: https://hal.science/hal-00851022
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    File URL: https://hal.science/hal-00851022/document
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    References listed on IDEAS

    as
    1. Alexander Harin, 2012. "Data Dispersion in Economics(II) - Inevitability and Consequences of Restrictions," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 24-36, November.
    2. Daniel Kahneman & Richard H. Thaler, 2006. "Anomalies: Utility Maximization and Experienced Utility," Journal of Economic Perspectives, American Economic Association, vol. 20(1), pages 221-234, Winter.
    3. David J. Butler & Graham C. Loomes, 2007. "Imprecision as an Account of the Preference Reversal Phenomenon," American Economic Review, American Economic Association, vol. 97(1), pages 277-297, March.
    4. Alexander Harin, 2010. "The theorem of existence of ruptures in the probability scale," Economics Bulletin, AccessEcon, vol. 30(2), pages 1-16.
    5. Alexander Harin, 2005. "A new approach to solve old problems," Game Theory and Information 0505005, University Library of Munich, Germany.
    6. Alexander Harin, 2012. "Data Dispersion in Economics (I) - Possibility of Restrictions," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 59-70, August.
    7. Schoemaker, Paul J. H. & Hershey, John C., 1992. "Utility measurement: Signal, noise, and bias," Organizational Behavior and Human Decision Processes, Elsevier, vol. 52(3), pages 397-424, August.
    8. John D. Hey & Chris Orme, 2018. "Investigating Generalizations Of Expected Utility Theory Using Experimental Data," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 3, pages 63-98, World Scientific Publishing Co. Pte. Ltd..
    9. Daniel Ellsberg, 1961. "Risk, Ambiguity, and the Savage Axioms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 75(4), pages 643-669.
    10. Tversky, Amos & Wakker, Peter, 1995. "Risk Attitudes and Decision Weights," Econometrica, Econometric Society, vol. 63(6), pages 1255-1280, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Harin, Alexander, 2018. "Forbidden zones and biases for the expectation of a random variable. Version 2," MPRA Paper 85607, University Library of Munich, Germany.
    2. Harin, Alexander, 2018. "Forbidden zones for the expectation of a random variable. New version 1," MPRA Paper 84248, University Library of Munich, Germany.
    3. Harin, Alexander, 2018. "Forbidden zones for the expectation. New mathematical results for behavioral and social sciences," MPRA Paper 86650, University Library of Munich, Germany.
    4. Harin, Alexander, 2014. "Problems of utility and prospect theories. A ”certain-uncertain” inconsistency of the random-lottery incentive system," MPRA Paper 55706, University Library of Munich, Germany.
    5. Harin, Alexander, 2014. "Is data interpretation in utility and prospect theories unquestionably correct?," MPRA Paper 53880, University Library of Munich, Germany.
    6. Harin, Alexander, 2014. "General correcting formulae for forecasts," MPRA Paper 55283, University Library of Munich, Germany.

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    Keywords

    data; behavior; rational; risk; noise; decision; utility;
    All these keywords.

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