评估和检验长期风险模型:国际证据

Andras Fulop, Junye Li, Hening Liu, Cheng Yan
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引用次数: 0

摘要

我们使用国际宏观经济和金融数据来估计和测试长期风险模型。基准模型的特征是具有递归偏好的代表性代理,具有时间偏好冲击,预期消费增长的持久成分,以及以自回归Gamma过程为特征的基本面的随机波动。我们构建了战后10个发达国家季度频率的综合数据集,并采用有效的基于似然的贝叶斯方法,该方法利用最新的顺序蒙特卡罗方法进行全面的计量经济学推断。我们的估计为支持长期风险、时变偏好冲击和随机贴现因子的逆周期性提供了国际证据。
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Estimating and Testing Long-Run Risk Models: International Evidence
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 in the post-war period 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 estimation provides international evidence in support of long-run risks, time-varying preference shocks, and countercyclicality of the stochastic discount factor.
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