Inference for Unstable Long-Memory Processes with Applications to Fractional Unit Root Autoregressions
不稳定长记忆过程的推断及其在分数单位根自回归中的应用
An autoregressive time series is said to be unstable if all of its characteristic roots lie on or outside the unit circle, with at least one on the unit circle. This paper aims at developing asymptotic inferential schemes for an unstable autoregressive model generated by long-memory innovations. This setting allows both nonstationarity and long-memory behavior in the modeling of low-frequency phenomena. In developing these procedures, a novel weak convergence result for a…