Testing for Noninvertible Models with Applications
针对平稳但非可逆的自回归移动平均模型，构造一个非平稳但可逆的派生过程，利用现有单位根检验统计量提出检验非可逆性的方法，并应用于美国经济时间序列的趋势平稳性检测。
This article is concerned with testing for noninvertible time series models. For a stationary but noninvertible autoregressive moving average model, I construct a derived process that is nonstationary but invertible with a nonstationary factor identical to the noninvertible factor of the original time series. I then propose a test procedure for testing noninvertibility using various unit-root test statistics available in the literature. The limiting distributions of the test statistics employed depend on the mean as well as the initial innovations of the original series. I also compare the performance of the proposed test procedure with that of other noninvertible tests available in the literature. For illustration, I apply the proposed test procedure to detect trend stationarity of two U.S. economic time series.