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Are Risk Averse Agents More Optimistic? A Bayesian Estimation Approach

  • Elyès Jouini

    ()

    (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - CNRS - Université Paris IX - Paris Dauphine)

  • Selima Ben Mansour

    (DRM - Dauphine Recherches en Management - CNRS - Université Paris IX - Paris Dauphine)

  • Clotilde Napp

    (DRM - Dauphine Recherches en Management - CNRS - Université Paris IX - Paris Dauphine)

  • Jean-Michel Marin

    ()

    (SELECT - Model selection in statistical learning - LMO - Laboratoire de Mathématiques d'Orsay - Université Paris Saclay - INRIA Saclay - Ile de France - INRIA - CNRS)

  • Christian Robert

    (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - CNRS - Université Paris IX - Paris Dauphine)

Our aim is to analyze the link between optimism and risk aversion in a subjective expected utility setting and to estimate the average level of optimism when weighted by risk tolerance. This quantity is of particular importance since it characterizes the consensus belief in risk-taking situations with heterogeneous beliefs. Its estimation leads to a nontrivial statistical problem. We start from a large lottery survey (1,536 individuals). We assume that individuals have true unobservable characteristics and that their answers in the survey are noisy realizations of these characteristics. We adopt a Bayesian approach for the statistical analysis of this problem and use an hybrid MCMC approximation method to numerically estimate the distributions of the unobservable characteristics. We obtain that individuals are on average pessimistic and that pessimism and risk tolerance are positively correlated. As a consequence, we conclude that the consensus belief is biased towards pessimism.

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Paper provided by HAL in its series Post-Print with number halshs-00176629.

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Date of creation: 2008
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Publication status: Published in Journal of Applied Econometrics, Wiley, 2008, pp.843-860
Handle: RePEc:hal:journl:halshs-00176629
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00176629v2
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