VECTOR AUTOREGRESSIONS WITH UNKNOWN MIXTURES OF I(0), I(1), AND I(2) COMPONENTSYoosoon Chang Econometric Theory, 2000, vol. 16, issue 06, pages 905-926 Abstract: This paper develops a new estimation method for nonstationary vector autoregressions (VAR s) with unknown mixtures of I(0), I(1), and I(2) components. The method does not require prior knowledge on the exact number and location of unit roots in the system. It is, therefore, applicable for VAR s with any mixture of I(0), I(1), and I(2) variables, which may be cointegrated in any form. The limit theory for the stationary component of our estimator is still normal, thereby preserving the usual VAR limit theory. Yet, the leading term of the nonstationary component of the estimator has mixed normal limit distribution and does not involve unit root distribution. Our method is an extension of the FM-VAR procedure by Phillips (1995, Econometrica 63, 1023 1078) and yields an estimator that is optimal in the sense of Phillips (1991, Econometrica 59, 283 306). Moreover, we show for a certain class of linear restrictions that the Wald tests based on the estimator are asymptotically distributed as a weighted sum of independent chi-square variates with weights between zero and one. For such restrictions, the limit distribution of the standard Wald test is nonstandard and nuisance parameter dependent. This has a direct application for Granger-causality testing in nonstationary VAR s. Date: 2000 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:16:y:2000:i:06:p:905-926_16 Access Statistics for this article More articles in Econometric Theory from Cambridge University Press |
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