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RARE EVENTS AND LONG-RUN RISKS

机译:稀有事件和长期风险

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Rare events (RE) and long-run risks (LRR) are complementary elements for understanding asset-pricing patterns, including the average equity premium and the volatility of equity returns. We construct a model with RE (temporary and permanent parts) and LRR (including stochastic volatility) and estimate this model with long-term data on aggregate consumption for 42 economies. RE typically associates with major historical episodes, such as the world wars and the Great Depression and analogous country-specific events. LRR reflects gradual and evolving processes that influence long-run growth rates and volatility. A match between the model and observed average rates of return requires a coefficient of relative risk aversion, γ, around 6. Most of the explanation for the equity premium derives from RE, although LRR makes a moderate contribution. We think the required γ will decline (and, thereby, become more realistic) if we allow for incomplete information about the underlying shocks, including the breakdown of RE into temporary and permanent parts. We thought that the addition of LRR to the RE framework would help to match the observed volatility of equity returns. However, the joint model still substantially understates this volatility. We think this aspect of the model will improve if we allow for stochastic evolution of the disaster probability.
机译:稀有事件(RE)和长期风险(LRR)是理解资产定价模式的补充元素,包括平均股票溢价和股票收益率的波动性。我们用RE(临时和永久性部分)和LRR(包括随机波动率)构建模型,并使用42个经济体的总消费的长期数据估算该模型。可再生能源通常与主要历史事件相关联,例如世界大战和大萧条以及类似国家的特定事件。 LRR反映了影响长期增长率和波动性的逐渐变化的过程。模型与观察到的平均收益率之间的匹配需要相对风险厌恶系数γ约为6。尽管LRR贡献适中,但大部分关于股权溢价的解释都来自RE。我们认为,如果我们允许有关潜在冲击的不完整信息(包括将RE分解为临时部分和永久部分),所需的γ将会下降(从而变得更加现实)。我们认为将LRR添加到RE框架中将有助于匹配观察到的股本收益的波动性。但是,联合模型仍然大大低估了这种波动性。我们认为,如果我们允许灾难概率的随机演变,那么模型的这一方面将有所改善。

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  • 来源
    《Working Paper Series 》 |2016年第21871期| 1-43a1-a2| 共45页
  • 作者

    Robert J. Barro; Tao Jin;

  • 作者单位

    Department of Economics Littauer Center 218 Harvard University Cambridge, MA 02138 and NBER;

    PBC School of Finance Tsinghua University 43 Chengfu Road, Haidian District Beijing, 100083, China;

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  • 正文语种 eng
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