The higher dimensional autoregressive models would describe some of the econometric processes relatively generically if they incorporate the heterogeneity in dependence on times. This paper analyzes the stationarity of an autoregressive process of dimension $k>1$ having a sequence of coefficients $\beta$ multiplied by successively increasing powers of $0<\delta<1$. The theorem gives the conditions of stationarity in simple relations between the coefficients and $k$ in terms of $\delta$. Computationally, the evidence of stationarity depends on the parameters. The choice of $\delta$ sets the bounds on $\beta$ and the number of time lags for prediction of the model.

翻译：更高维度的自动递减模型将比较笼统地描述一些计量经济学过程,如果它们包含依赖时间的异质性。本文分析一个自动递减过程的固定性,该过程的维度为$>1美元,其系数序列乘以连续递增的0. ⁇ delta<1美元。该理论在系数与美元之间的简单关系中提供了固定性条件,其值为$\delta美元。计算结果是,固定性的证据取决于参数。 选择$\delta$的界限是$\beta$,预测模型的时滞数是多少。