Recursive Preferences, Correlation Aversion, and the Temporal Resolution of Uncertainty
Abstract
This paper investigates a novel behavioral feature of recursive preferences: aversion to risks that persist over time, or simply \textit{correlation aversion}. Greater persistence provides information about future consumption but reduces opportunities to hedge consumption risk. I show that, for recursive preferences that exhibit a preference for early resolution of uncertainty, 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 show that correlation-averse preferences have a variational representation, linking correlation aversion to concerns about model misspecification. I present several applications. I first illustrate how correlation aversion shapes portfolio choices, and then show how the persistence premium can improve the calibration of macro-finance models. In an optimal taxation model, I show that recursive preferences -- unlike standard preferences -- lead to redistributive tax policies that increase social mobility.
Cite
@article{arxiv.2304.04599,
title = {Recursive Preferences, Correlation Aversion, and the Temporal Resolution of Uncertainty},
author = {Lorenzo Maria Stanca},
journal= {arXiv preprint arXiv:2304.04599},
year = {2026}
}