New iterative reduced-rank regression procedures for seasonal cointegration analysis were proposed. The suggested methods are motivated by the idea that modelling the cointegration restrictions jointly at different frequencies may increase efficiency in finite samples. Monte Carlo simulations indicate that the new tests and estimators perform well with respect to already existing statistical procedures.
Cubadda, G., Omtzigt, P. (2005). Small-sample improvements in the statistical analysis of seasonally cointegrated systems. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 49(2), 333-348 [10.1016/j.csda.2004.05.016].
Small-sample improvements in the statistical analysis of seasonally cointegrated systems
CUBADDA, GIANLUCA;
2005-01-01
Abstract
New iterative reduced-rank regression procedures for seasonal cointegration analysis were proposed. The suggested methods are motivated by the idea that modelling the cointegration restrictions jointly at different frequencies may increase efficiency in finite samples. Monte Carlo simulations indicate that the new tests and estimators perform well with respect to already existing statistical procedures.File in questo prodotto:
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