Estimating and Testing Long-Run Risk Models: International Evidence

• 成果类型: Article
• 署名作者: Fulop, Andras; Li, Junye; Liu, Hening; Yan, Cheng
• 署名单位: ESSEC Business School; Fudan University; University of Manchester; Alliance Manchester Business School; University of Essex
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.04054
• 发表日期: 2025
• 关键词: consumption; equity premium; Long-run risk; stochastic discount factor; projection methods; sequential Monte Carlo sampler

摘要

We estimate and test long-run risk models using international macroeconomic and financial data. The benchmark model features a representative agent who has recursive preferences with a time preference shock, a persistent component in expected consumption growth, and stochastic volatility in fundamentals characterized by an autoregressive gamma process. We construct a comprehensive data set with quarterly frequency for 10 developed countries and employ an efficient likelihood-based Bayesian method that exploits up-to-date sequential Monte Carlo methods to make full econometric inference. Our empirical findings provide international evidence in support of long-run risks, time-varying preference shocks, and countercyclicality of the stochastic discount factor. We show the existence of a global long-run consumption factor driving equity returns across individual countries.