NEAR-INTEGRATED RANDOM COEFFICIENT AUTOREGRESSIVE TIME SERIES
研究了近积分一阶随机系数自回归RCA(1)时间序列的极限行为，发现有限维分布的渐近性质取决于临界值1的逼近方式，这决定了过程是近平稳、有单位根还是轻度爆炸。
We determine the limiting behavior of near-integrated first-order random coefficient autoregressive RCA(1) time series. It is shown that the asymptotics of the finite-dimensional distributions crucially depends on how the critical value 1 is approached, which determines whether the process is near-stationary, has a unit root, or is mildly explosive. %In a second part, we derive the limit distribution of the serial correlation coefficient in the near stationary and the mildly explosive settings under very general conditions on the parameters. The results obtained are in accordance with those available for first-order autoregressive time series and can hence serve as an addition to existing literature in the area.