Complex Reduced Rank Models for Seasonally Cointegrated Time Series
AbstractThis paper introduces a new representation for seasonally cointegrated variables, namely the complex error correction model, which allows statistical inference to be performed by reduced rank regression. The suggested estimators and tests statistics are asymptotically equivalent to their maximum likelihood counterparts. The small sample properties are evaluated by a Monte Carlo study and an empirical example is presented to illustrate the concepts and methods. Copyright 2001 by Blackwell Publishing Ltd
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Bibliographic InfoArticle provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.
Volume (Year): 63 (2001)
Issue (Month): 4 (September)
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- Gianluca Cubadda, 2000. "Complex Reduced Rank Models for Seasonally Cointegrated Time Series," Econometric Society World Congress 2000 Contributed Papers 0092, Econometric Society.
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