Testing for Common Features
提出一类统计检验，用于判断多个变量中存在的某个特征（如序列相关、异方差性等）是否共同。通过寻找无特征的线性组合来检测共同特征，并应用于检验国际商业周期的共同性。
This article introduces a class of statistical tests for the hypothesis that some feature that is present in each of several variables is common to them. Features are data properties such as serial correlation, trends, seasonality, heteroscedasticity, autoregressive conditional hetero-scedasticity, and excess kurtosis. A feature is detected by a hypothesis test taking no feature as the null, and a common feature is detected by a test that finds linear combinations of variables with no feature. Often, an exact asymptotic critical value can be obtained that is simply a test of overidentifying restrictions in an instrumental variable regression. This article tests for a common international business cycle.