Publication Type

Journal Article

Version

Preprint

Publication Date

8-2008

Abstract

A limit theory is developed for multivariate regression in an explosive cointegrated system. The asymptotic behavior of the least squares estimator of the cointegrating coefficients is found to depend upon the precise relationship between the explosive regressors. When the eigenvalues of the autoregressive matrix Θ are distinct, the centered least squares estimator has an exponential Θn rate of convergence and a mixed normal limit distribution. No central limit theory is applicable here, and Gaussian innovations are assumed. On the other hand, when some regressors exhibit common explosive behavior, a different mixed normal limiting distribution is derived with rate of convergence reduced to . In the latter case, mixed normality applies without any distributional assumptions on the innovation errors by virtue of a Lindeberg type central limit theorem. Conventional statistical inference procedures are valid in this case, the stationary convergence rate dominating the behavior of the least squares estimator.

Keywords

Central limit theory, Exposive cointegration, Explosive process, Mixed normality

Discipline

Econometrics

Research Areas

Econometrics

Publication

Econometric Theory

Volume

24

Issue

4

First Page

865

Last Page

887

ISSN

0266-4666

Identifier

10.1017/S0266466608080353

Publisher

Cambridge University Press

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org/10.1017/S0266466608080353

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Econometrics Commons

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