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Model Uncertainty

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  • Massimo Marinacci

Abstract

We study decision problems in which consequences of the various alternative actions depend on states determined by a generative mechanism representing some natural or social phenomenon. Model uncertainty arises because decision makers may not know this mechanism. Two types of uncertainty result, a state uncertainty within models and a model uncertainty across them. We discuss some two-stage static decision criteria proposed in the literature that address state uncertainty in the first stage and model uncertainty in the second (by considering subjective probabilities over models). We consider two approaches to the Ellsberg-type phenomena characteristic of such decision problems: a Bayesian approach based on the distinction between subjective attitudes toward the two kinds of uncertainty; and a non-Bayesian approach that permits multiple subjective probabilities. Several applications are used to illustrate concepts as they are introduced.

Suggested Citation

  • Massimo Marinacci, 2015. "Model Uncertainty," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1022-1100, December.
  • Handle: RePEc:bla:jeurec:v:13:y:2015:i:6:p:1022-1100
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    5. Simone Cerreia Vioglio & Fabio Maccheroni & Massimo Marinacci, 2016. "Absolute and Relative Ambiguity Aversion: A Preferential Approach," Working Papers 578, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    6. Simon Quemin, 2016. "Intertemporal abatement decisions under ambiguity aversion in a cap and trade," Working Papers 1604, Chaire Economie du climat.
    7. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    8. Astrid Gamba & Tobias Regner, 2015. "Preferences-dependent learning in the Centipede game," Jena Economics Research Papers 2015-012, Friedrich-Schiller-University Jena.
    9. Battigalli, P. & Francetich, A. & Lanzani, G. & Marinacci, M., 2019. "Learning and self-confirming long-run biases," Journal of Economic Theory, Elsevier, vol. 183(C), pages 740-785.
    10. Pierpaolo Battigalli & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Thomas Sargent, 2016. "A Framework for the Analysis of Self-Confirming Policies," Working Papers 573, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    11. Loic Berger & Valentina Bosetti, 2016. "Ellsberg Re-revisited: An Experiment Disentangling Model Uncertainty and Risk Aversion," Working Papers 2016.37, Fondazione Eni Enrico Mattei.
    12. Battigalli, P. & Catonini, E. & Lanzani, G. & Marinacci, M., 2019. "Ambiguity attitudes and self-confirming equilibrium in sequential games," Games and Economic Behavior, Elsevier, vol. 115(C), pages 1-29.
    13. Battigalli, P. & Cerreia-Vioglio, S. & Maccheroni, F. & Marinacci, M., 2016. "Analysis of information feedback and selfconfirming equilibrium," Journal of Mathematical Economics, Elsevier, vol. 66(C), pages 40-51.
    14. Loic Berger & Valentina Bosetti, 2016. "Ellsberg Re-revisited: An Experiment Disentangling Model Uncertainty and Risk Aversion," Working Papers 2016.37, Fondazione Eni Enrico Mattei.
    15. Loic Berger & Massimo Marinacci, 2017. "Model Uncertainty in Climate Change Economics," Working Papers 616, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
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    17. Aurélien Baillon & Zhenxing Huang & Asli Selim & Peter P. Wakker, 2018. "Measuring Ambiguity Attitudes for All (Natural) Events," Econometrica, Econometric Society, vol. 86(5), pages 1839-1858, September.

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