Estimating and Testing Long-Run Risk Models: International Evidence

Hening Liu, Andras Fulop, Junye Li, Cheng Yan

Research output: Contribution to journalArticlepeer-review

73 Downloads (Pure)

Abstract

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 dataset with quarterly frequency for ten 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.
Original languageEnglish
JournalMANAGEMENT SCIENCE
Volumeforthcoming
Publication statusPublished - 2024

Fingerprint

Dive into the research topics of 'Estimating and Testing Long-Run Risk Models: International Evidence'. Together they form a unique fingerprint.

Cite this