This paper derives primitive, easily verifiable sufficient conditions for existence and uniqueness of  recursive utilities for a number of important classes of preferences. In order to accommodate models commonly used in practice, we allow both the statespace and per-period utilities to be unbounded. For many of the models we study, existence and uniqueness is established under a single  "thin tail" condition on the distribution of growth in per-period utilities. We illustrate our approach with applications to robust preferences, models of ambiguity aversion and learning about hidden states , dynamic discrete choice models , and Epstein-Zin preferences.
This paper derives primitive, easily verifiable sufficient conditions for existence and uniqueness of (stochastic) recursive utilities for several important classes of preferences. In order to accommodate models commonly used in practice, we allow both the state-space and per-period utilities to be unbounded. For many of the models we study, existence and uniqueness is established under a single , primitive "thin tail" condition on the distribution of growth in per-period utilities. We present several applications to robust preferences, models of ambiguity aversion and learning about hidden states , and Epstein-Zin preferences.
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(stochastic)
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a number of
several
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statespace
state-space
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, primitive
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illustrate our approach with
present several
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, dynamic discrete choice models