Recursive Preferences, Correlation Aversion, and the Temporal Resolution of Uncertainty
中文摘要
本文考察递归偏好的一种新颖行为特征：对随时间持续存在的风险的厌恶，或简称相关性厌恶。更高的持续性提供了关于未来消费的信息，但减少了对冲消费风险的机会。本文表明，对于表现出偏好不确定性早期解决的递归偏好，相关性厌恶等价于递增的相对风险厌恶。为量化相关性厌恶，本文提出持续性溢价这一概念，用以衡量个体为消除消费中的持续性愿意支付多少。本文以 Arrow–Pratt 的精神给出持续性溢价的一个近似，从而对信息与对冲之间的权衡提供定量表征。本文表明，相关性厌恶偏好具有变分表示，将相关性厌恶与对模型误设的担忧联系起来。本文提出若干应用：首先说明相关性厌恶如何塑造投资组合选择，随后展示持续性溢价如何改进宏观金融模型的校准。在一个最优税收模型中，本文表明，递归偏好——不同于标准偏好——会导致提高社会流动性的再分配税收政策。
Abstract
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.