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Principal Components Analysis ofCointegrated Time Series

Published online by Cambridge University Press:  11 February 2009

Abstract

This paper considers the analysis of cointegrated timeseries using principal components methods. Thesemethods have the advantage of requiring neither thenormalization imposed by the triangular errorcorrection model nor the specification of afinite-order vector autoregression. Anasymptotically efficient estimator of thecointegrating vectors is given, along with testsforcointegration and tests of certain linearrestrictions on the cointegrating vectors. Anillustrative application is provided.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 1997

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