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Modelling Biased Judgement with Weighted Updating

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  • Zinn, Jesse

Abstract

The weighted updating model is a generalization of Bayesian updating that allows for biased beliefs by weighting the functions that constitute Bayes' rule with real exponents. I provide an axiomatic basis for this framework and show that weighting a distribution affects the information entropy of the resulting distribution. This result provides the interpretation that weighted updating models biases in which individuals mistake the information content of data. I augment the base model in two ways, allowing it to account for additional biases. The first augmentation allows for discrimination between data. The second allows the weights to vary over time. I also find a set of sufficient conditions for the uniqueness of parameter estimation through maximum likelihood, with log-concavity playing a key role. An application shows that self attribution bias can lead to optimism bias.

Suggested Citation

  • Zinn, Jesse, 2013. "Modelling Biased Judgement with Weighted Updating," MPRA Paper 50310, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:50310
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    References listed on IDEAS

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    7. Thomas R. Palfrey & Stephanie W. Wang, 2012. "Speculative Overpricing in Asset Markets With Information Flows," Econometrica, Econometric Society, vol. 80(5), pages 1937-1976, September.
    8. Mark Bagnoli & Ted Bergstrom, 2006. "Log-concave probability and its applications," Studies in Economic Theory, in: Charalambos D. Aliprantis & Rosa L. Matzkin & Daniel L. McFadden & James C. Moore & Nicholas C. Yann (ed.), Rationality and Equilibrium, pages 217-241, Springer.
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    Cited by:

    1. Zinn, Jesse, 2013. "Self-Attribution Bias and Consumption," MPRA Paper 50314, University Library of Munich, Germany.
    2. Jesse Aaron Zinn, 2015. "Expanding the Weighted Updating Model," Economics Bulletin, AccessEcon, vol. 35(1), pages 182-186.

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    More about this item

    Keywords

    Bayesian Updating; Cognative Biases; Learning; Uncertainty;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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