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Estimating and Testing Long-Run Risk Models: International Evidence

Author

Listed:
  • Andras Fulop

    (ESSEC Business School, Paris-Singapore, 95021 Cergy-Pontoise, France)

  • Junye Li

    (School of Management, Fudan University, Shanghai 200433, China)

  • Hening Liu

    (Alliance Manchester Business School, The University of Manchester, Manchester M15 6PB, United Kingdom)

  • Cheng Yan

    (Essex Business School, University of Essex, Colchester CO4 3SQ, United Kingdom)

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 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.

Suggested Citation

  • Andras Fulop & Junye Li & Hening Liu & Cheng Yan, 2025. "Estimating and Testing Long-Run Risk Models: International Evidence," Management Science, INFORMS, vol. 71(4), pages 3517-3536, April.
    • Handle: RePEc:inm:ormnsc:v:71:y:2025:i:4:p:3517-3536
    DOI: 10.1287/mnsc.2022.04054
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