Linear Transformations, Error Correction, and the Long Run in Dynamic Regression

Anindya Banerjee, Juan J. Dolado, John W. Galbraith and David F. Hendry

in Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data

Published in print May 1993 | ISBN: 9780198288107
Published online November 2003 | e-ISBN: 9780191595899 | DOI:

Series: Advanced Texts in Econometrics

 Linear Transformations, Error Correction, and the Long Run in Dynamic Regression

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The focus in this chapter is on the properties of linear autoregressive‐distributed lag (ADL) models for stationary data processes, in order to understand later transformations in non‐stationary models. Various equivalent transformations of ADL models are considered, especially the error‐correction, Bewley and Bardsen forms, and the estimation of long‐run multipliers (and their variances) from these models is discussed. The role of expectational variables in inference about long‐run multipliers is also investigated and potential problems are shown to be related to the general issue of the absence of weak exogeneity for the parameters of interest.

Keywords: Bardsen transformation; Bewley transformation; dynamic models; error‐correction models; expectations; linear transformations; long‐run multipliers; stationary processes; weak exogeneity

Chapter.  11494 words.  Illustrated.

Subjects: Econometrics and Mathematical Economics

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