Econometrica · 1992 · 1.2K citations · 19 references
BusinessEconomicsFinanceAsset PricingMicroeconomicsStochastic ProcessesAsset Pricing TheoryMarkov ProcessesPricing Under UncertaintyRisk AversionRisk-sensitive Decision MakingUtility TheoryExpected Utility MaximizationHamilton - Jacobi - Bellman EquationsHamilton-jacobi EquationsHamilton-jacobi-bellman EquationsNon-expected Utility TheoryRecursive Utility ModelsStochastic Utility FunctionsTime Consistency
The paper presents a stochastic differential formulation of recursive utility, establishing sufficient conditions for its existence, uniqueness, time consistency, monotonicity, continuity, risk aversion, concavity, and related properties. The model’s implications for asset prices are explored in a companion paper. In a Brownian information setting, recursive and intertemporal expected utility functions are observationally distinguishable, whereas non‑expected‑utility theories of one‑shot choice become indistinguishable after integration into an intertemporal framework, and in a smooth Markov setting the model generalizes the Hamilton‑Bellman‑Jacobi optimality characterization. © 1992 The Econometric Society.
A stochastic differential formulation of recursive utility is given sufficient conditions for existence, uniqueness, time consistency, monotonicity, continuity, risk aversion, concavity, and other properties. In the setting of Brownian information, recursive and intertemporal expected utility functions are observationally distinguishable. However, one cannot distinguish between a number of non-expected-utility theories of one-shot choice under uncertainty after they are suitably integrated into an intertemporal framework. In a smooth Markov setting, the stochastic differential utility model produces a generalization of the Hamilton-Bellman-Jacobi characterization of optimality. A companion paper explores the implications for asset prices. Copyright 1992 by The Econometric Society.
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