Recursive Preferences, Correlation Aversion, and the Temporal Resolution of Uncertainty,
Lorenzo Stanca
Abstract
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 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.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.