On causal and non‐causal cointegrated vector autoregressive time series
将非因果时间序列从平稳情形推广到积分过程，扩展了Johansen-Granger表示法以允许依赖未来误差，并讨论了参数估计和迹统计量的渐近分布。
Previous‐30 treatments of multivariate non‐causal time series have assumed stationarity. In this article, we consider integrated processes in a non‐causal setting. We generalize the Johansen–Granger representation for causal vector autoregressive (VAR) models to allow for dependence on future errors and discuss how the parameters can be estimated. The asymptotic distribution of the trace statistic is also considered. Some Monte Carlo simulations are presented.