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Some estimations of the minimal magnitudes of forbidden zones in experimental data

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  • Harin, Alexander

Abstract

Suppose a random variable takes on values in an interval. The minimal distance between the expectation of the variable and the nearest boundary of the interval is considered in the present article. A question whether this distance can be neglected with respect to the standard deviation is analyzed as the main item. This minimal distance can determine the minimal magnitudes of non-zero forbidden zones and biases caused by noise for results of experiments. These non-zero forbidden zones and biases cause fundamental problems, especially in interpretations of experiments in behavioral economics and decision sciences.

Suggested Citation

  • Harin, Alexander, 2017. "Some estimations of the minimal magnitudes of forbidden zones in experimental data," MPRA Paper 80319, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:80319
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    File URL: https://mpra.ub.uni-muenchen.de/80319/1/MPRA_paper_80319.pdf
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    References listed on IDEAS

    as
    1. Harin, Alexander, 2017. "Can forbidden zones for the expectation explain noise influence in behavioral economics and decision sciences?," MPRA Paper 76240, University Library of Munich, Germany.
    2. 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.
    3. 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.
    4. 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.
    5. Steftcho P. Dokov & David P. Morton, 2005. "Second-Order Lower Bounds on the Expectation of a Convex Function," Mathematics of Operations Research, INFORMS, vol. 30(3), pages 662-677, August.
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    Cited by:

    1. Harin, Alexander, 2019. "Behavioral sciences and auto-transformations. Introduction," MPRA Paper 97344, University Library of Munich, Germany.

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    More about this item

    Keywords

    utility theory; prospect theory; behavioral economics; decision sciences; probability; experiments; data; variance; expectation; noise;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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