<p>Individuals behave differently when they know the objective probability of events and when they do not. The smooth ambiguity model accommodates both ambiguity (uncertainty) and risk. We consider an individual who trades financial assets to maximize a smooth ambiguity utility over two dates. For an incomplete, competitive asset market, we give sufficient conditions for consumption and asset demand functions generated by smooth ambiguity preferences to identify the ambiguity and risk indices as well as the ambiguity probability measure. Restrictions imposed on asset payoffs play an important role in separating risk and ambiguity preferences, and linear independence of indirect marginal utility functions over assets pins down the ambiguity beliefs. The identification procedure can determine whether the individual possesses smooth ambiguity, Kreps-Porteus-Selden or expected utility preferences. Also, our argument applies even if the conditional probability distributions in the support of the ambiguity probability measure are not observed.</p>

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Identification of smooth ambiguity

  • Herakles Polemarchakis,
  • Larry Selden,
  • Xinxi Song

摘要

Individuals behave differently when they know the objective probability of events and when they do not. The smooth ambiguity model accommodates both ambiguity (uncertainty) and risk. We consider an individual who trades financial assets to maximize a smooth ambiguity utility over two dates. For an incomplete, competitive asset market, we give sufficient conditions for consumption and asset demand functions generated by smooth ambiguity preferences to identify the ambiguity and risk indices as well as the ambiguity probability measure. Restrictions imposed on asset payoffs play an important role in separating risk and ambiguity preferences, and linear independence of indirect marginal utility functions over assets pins down the ambiguity beliefs. The identification procedure can determine whether the individual possesses smooth ambiguity, Kreps-Porteus-Selden or expected utility preferences. Also, our argument applies even if the conditional probability distributions in the support of the ambiguity probability measure are not observed.