Testing Identifiability of Cointegrating Vectors
AbstractThis paper analyzes the identification and normalization of cointegrating vectors. Normalizing a cointegrating relation with respect to one of the relevant variables is with loss of generality; and restrictions which are supposed to identify a vector may fail to do so for particular parameter values. The author proposes to tackle both problems by testing whether particular rank conditions are violated. He shows that S. Johansen and K. Juselius's (1992) class of likelihood ratio statistics for structural hypotheses in a Gaussian vector autoregression may be used for this purpose. The tests are applied to a model of the demand for money in the United Kingdom.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 14 (1996)
Issue (Month): 2 (April)
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