期刊名称：Economics Discussion Papers / Department of Economics, College of Management and Economics, University of Guelph
出版年度：2010
卷号：2010
期号：01
出版社：University of Guelph
摘要：Previous literature has introduced causality tests with conventional limiting
distributions in I(0)/I(1) vector autoregressive (VAR) models with unknown in-
tegration orders, based on an additional surplus lag in the speci cation of the
estimated equation, which is not included in the tests. By extending this surplus
lag approach to an in nite order VARX framework, we show that it can provide
a highly persistence-robust Granger causality test that accommodates i.a. sta-
tionary, nonstationary, local-to-unity, long-memory, and certain (unmodelled)
structural break processes in the forcing variables within the context of a single
2 null limiting distribution.
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