Recursive Preferences, Correlation Aversion, and the Temporal Resolution of Uncertainty

This paper investigates a novel behavioral feature of recursive preferences: aversion to risks that persist over time, or simply correlation aversion. Greater persistence provides information about future consumption but reduces opportunities to hedge consumption risk. I show that, for recursive preferences, correlation aversion is equivalent to increasing relative risk aversion. To quantify correlation aversion, I develop the concept of the persistence premium, which measures how much an individual is willing to pay to eliminate persistence in consumption. I provide an approximation of the persistence premium in the spirit of Arrow-Pratt, which provides a quantitative representation of the trade-off between information and hedging. I present several applications. The persistence premium helps create more realistic calibrations for macro-finance models. In an optimal taxation model, I show that recursive preferences unlike standard preferences-lead to more progressive taxation when human capital persistence is greater. Finally, I show that correlation-averse preferences have a variational representation, linking correlation aversion to concerns about model misspecification.