Large shocks, small shocks, and economic fluctuations: Outliers in macroeconomic time series
用改进的异常值识别方法分析二战后美国15个宏观经济时间序列，发现所有序列都存在“大冲击”，且异常值呈现三种模式：与商业周期相关、时间与序列间聚集、实际与名义序列行为二分；控制异常值后，许多序列的非线性证据消失。
Abstract We analyse fifteen post‐World War II US macroeconomic time series using a modified outlier identification procedure based on Tsay (1988a). ‘Large shocks’ appear to be present in all the series we examined. Furthermore, there are three basic outlier patterns: (1) outliers seem to be associated with business cycles, (2) outliers are clustered together—both over time and across series, (3) there appears to be a dichotomy between outlier behaviour of real versus nominal series. Also, after controlling for outliers, much of the evidence of non‐linearity in many of the time series is eliminated.