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On attitude polarization under Bayesian learning with non-additive beliefs

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  • Alexander Zimper

    ()

  • Alexander Ludwig

    ()

Abstract

Ample psychological evidence suggests that people’s learning behavior is often prone to a "myside bias" or "irrational belief persistence" in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such a bias may result in diverging posterior beliefs and attitude polarization even if agents receive identical information. Such patterns cannot be explained by the standard model of rational Bayesian learning that implies convergent beliefs. As our key contribution, we therefore develop formal models of Bayesian learning with psychological bias as alternatives to rational Bayesian learning. We derive conditions under which beliefs may diverge in the learning process despite the fact that all agents observe the same - arbitrarily large - sample, which is drawn from an "objective" i.i.d. process. Furthermore, one of our learning scenarios results in attitude polarization even in the case of common priors. Key to our approach is the assumption of ambiguous beliefs that are formalized as non-additive probability measures arising in Choquet expected utility theory. As a specific feature of our approach, our models of Bayesian learning with psychological bias reduce to rational Bayesian learning in the absence of ambiguity.

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File URL: http://hdl.handle.net/10.1007/s11166-009-9074-0
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Bibliographic Info

Article provided by Springer in its journal Journal of Risk and Uncertainty.

Volume (Year): 39 (2009)
Issue (Month): 2 (October)
Pages: 181-212

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Handle: RePEc:kap:jrisku:v:39:y:2009:i:2:p:181-212

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Web page: http://www.springerlink.com/link.asp?id=100299

Related research

Keywords: Non-additive probability measures; Choquet expected utility theory; Bayesian learning; Bounded rationality; C79; D83;

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References

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Citations

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Cited by:
  1. Sandeep Baliga & Eran Hanany & Peter Klibanoff, 2013. "Polarization and Ambiguity," Discussion Papers 1558, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  2. Aurélien Baillon & Laure Cabantous & Peter Wakker, 2012. "Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 115-147, April.
  3. A. Ludwig & A. Zimper, 2013. "A parsimonious model of subjective life expectancy," Theory and Decision, Springer, vol. 75(4), pages 519-541, October.
  4. Zimper, Alexander, 2012. "Asset pricing in a Lucas fruit-tree economy with the best and worst in mind," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 610-628.
  5. Alexander Ludwig & Alexander Zimper, 2013. "A decision-theoretic model of asset-price underreaction and overreaction to dividend news," Annals of Finance, Springer, vol. 9(4), pages 625-665, November.
  6. Alexander Ludwig and Alexander Zimper, 2013. "Biased Bayesian Learning with an Application to the Risk-Free Rate Puzzle," Working Papers 390, Economic Research Southern Africa.
  7. Max Groneck & Alexander Ludwig & Alexander Zimper, 2013. "A Life-Cycle Model with Ambiguous Survival Beliefs," Working Paper Series in Economics 63, University of Cologne, Department of Economics, revised 22 Nov 2013.

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