This paper estimates consumption and GDP tail risk dynamics over the long run (1900–2020). Our predictive approach circumvents the scarcity of large macroeconomic crises by exploiting a rich information set covering 42 countries. This flexible approach does not require asset price information and can thus serve as a benchmark to evaluate the empirical validity of rare disaster models. Our estimates covary with asset prices and forecast future stock returns, in line with theory. A calibration disciplined by our estimates supports the prediction that macroeconomic tail risk drives the equity premium.

中文翻译：

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衡量宏观经济尾部风险

本文估计了长期（1900-2020）的消费和 GDP 尾部风险动态。我们的预测方法通过利用覆盖 42 个国家的丰富信息集来规避大规模宏观经济危机的稀缺性。这种灵活的方法不需要资产价格信息，因此可以作为评估罕见灾害模型经验有效性的基准。我们的估计与资产价格和预测未来股票回报率一致，与理论一致。根据我们的估计进行的校准支持了宏观经济尾部风险驱动股票溢价的预测。