TESTING STRICT STATIONARITY WITH APPLICATIONS TO MACROECONOMIC TIME SERIES
提出一种无需模型假设的严格平稳性检验方法，通过比较时变特征函数与样本经验特征函数实现，并衍生出弱平稳性等检验。蒙特卡洛模拟显示检验效力优异，应用于宏观经济序列发现强烈证据反对平稳性假设，提示传统建模策略需改进。
Abstract We propose a model‐free test for strict stationarity. The idea is to estimate a nonparametric time‐varying characteristic function and compare it with the empirical characteristic function based on the whole sample. We also propose several derivative tests to check time‐invariant moments, weak stationarity, and p th order stationarity. Monte Carlo studies demonstrate excellent power of our tests. We apply our tests to various macroeconomic time series and find overwhelming evidence against strict and weak stationarity for both level and first‐differenced series. This suggests that the conventional time series econometric modeling strategies may have room to be improved by accommodating these time‐varying features.