Assessing Macroeconomic Tail Risk
研究发现美国实际GDP和工业生产的尾部风险不对称，且多种结构性冲击（如货币政策、金融、不确定性、油价冲击）对预测分布第十百分位数的影响是中位数的三到六倍，表明存在共同的传导机制。
Abstract Real gross domestic product and industrial production in the United States display substantial asymmetry and tail risk. Is this asymmetry driven by a specific structural shock? Our empirical approach, based on quantile regressions and local projections, suggests otherwise. We find that the tenth percentile of predictive growth distributions responds between three and six times more than the median to monetary policy shocks, financial shocks, uncertainty shocks, and oil price shocks, indicating a common transmission mechanism. We present two data-generating processes that are capable of matching this finding: a threshold vector autoregression model and a non-linear equilibrium model.