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Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
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Likelihood-Based Inference in Cointegrated Vector Autoregressive Models

Søren Johansen

Abstract

This monograph is concerned with the statistical analysis of multivariate systems of non‐stationary time series of type I(1). It applies the concepts of cointegration and common trends in the framework of the Gaussian vector autoregressive model. The main result on the structure of cointegrated processes as defined by the error correction model is Grangers representation theorem. The statistical results include derivation of the trace test for cointegrating rank, test on cointegrating relations, and test on adjustment coefficients and their asymptotic distributions.

Keywords: adjustment coefficients, cointegrating relations, cointegration, common trends, error correction model, Granger representation theorem, non‐stationary time series, trace test, vector autoregressive model

Bibliographic Information

Print publication date: 1995 Print ISBN-13: 9780198774501
Published to Oxford Scholarship Online: November 2003 DOI:10.1093/0198774508.001.0001

Authors

Affiliations are at time of print publication.

Søren Johansen, author
University of Copenhagen
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