Vector autoregression and causality
Vector autoregression and causality
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发表时间：
1991-05
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通讯作者：
Hiro Y. Toda;P. Phillips
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作者：
Hiro Y. Toda;P. Phillips
本文发展了一个完整的极限理论的Wald测试的格兰杰因果关系的水平向量自回归（VAR）和Johansen型误差校正模型（ECM）允许存在的随机趋势和协整。西姆斯，股票和沃森（1990）的三变量VAR系统的早期工作扩展到一般情况下，从而正式特征的情况下，这些Wald测试是渐近有效的卡方准则。我们的结果推断无限制的水平VAR是不令人鼓舞的。
This paper develops a complete limit theory for Wald tests of Granger causality in levels vector autoregression (VAR's) and Johansen-type error correction models (ECM's) allowing for the presence of stochastic trends and cointegration. Earlier work by Sims, Stock and Watson (1990) on trivariate VAR systems is extended to the general case, thereby formally characterizing the circumstances when these Wald tests are asymptotically valid as chi-square criteria. Our results for inference from unrestricted levels VAR are not encouraging.