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January 1992 - Volume 60 Issue 1 Page 119 - 143


p.119


Canonical Cointegrating Regressions

Joon Y. Park

Abstract

This paper develops a new procedure for statistical inference in cointegrating regressions. We introduce the concept of canonical cointegrating regressions, which are the regressions formulated with the transformed data. The required transformations involve simple adjustments of the integrated processes using stationary components in cointegrating models. Canonical cointegrating regressions therefore represent the same cointegrating relationships as the original models. They are, however, constructed in such a way that the usual least squares procedure yields asymptotically efficient estimators and chi-square tests. The methodology presented here is applicable to a very wide class of cointegrating models, including models with deterministic and singular, as well as stochastic and regular, cointegrations.

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