Testing for Causation Using Infinite Order Vector Autoregressive Processes
研究了当真实数据生成过程为无限阶时，拟合有限阶VAR模型进行格兰杰因果检验的渐近性质，并通过模拟获得小样本结果。
Tests for Granger-causality have been performed in numerous empirical studies. These tests are usually based on finite order vector autoregressive (VAR) processes, and the assumption is made that the model fitted to the available data corresponds to the true data generating mechanism. In the present study, the more general assumption is made that a finite order VAR model is fitted to a potentially infinite order process. The order is assumed to increase with the sample size. Asymptotic properties of tests for Granger-causality as well as other types of causality concepts are derived. Some limited small sample results are obtained using simulation methods.