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Principal Components Analysis of Cointegrated Time Series

Published online by Cambridge University Press:  11 February 2009

Abstract

This paper considers the analysis of cointegrated time series using principal components methods. These methods have the advantage of requiring neither the normalization imposed by the triangular error correction model nor the specification of a finite-order vector autoregression. An asymptotically efficient estimator of the cointegrating vectors is given, along with tests forcointegration and tests of certain linear restrictions on the cointegrating vectors. An illustrative application is provided.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1997

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