Modeling and Forecasting Macroeconomic Downside Risk
研究了美国GDP增长预测分布的永久性和暂时性变化，发现过去30年下行风险显著增加，条件偏度随经济周期顺周期变化，模型在尾部事件预测上优于标准基准。
We model permanent and transitory changes of the predictive density of US GDP growth. A substantial increase in downside risk to US economic growth emerges over the last 30 years, associated with the long-run growth slowdown started in the early 2000s. Conditional skewness moves procyclically, implying negatively skewed predictive densities ahead and during recessions, often anticipated by deteriorating financial conditions. Conversely, positively skewed distributions characterize expansions. The modelling framework ensures robustness to tail events, allows for both dense or sparse predictor designs, and delivers competitive out-of-sample (point, density and tail) forecasts, improving upon standard benchmarks.