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    Fossati, Sebastian 2012. Covariate unit root tests with good size and power. Computational Statistics & Data Analysis, Vol. 56, Issue. 11, p. 3070.


    Kascha, Christian and Trenkler, Carsten 2011. Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order. Computational Statistics & Data Analysis, Vol. 55, Issue. 2, p. 1008.


    Bauer, Dietmar and Wagner, Martin 2009. Using subspace algorithm cointegration analysis: Simulation performance and application to the term structure. Computational Statistics & Data Analysis, Vol. 53, Issue. 6, p. 1954.


    Qu, Zhongjun 2007. Searching for cointegration in a dynamic system. The Econometrics Journal, Vol. 10, Issue. 3, p. 580.


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A MODIFIED INFORMATION CRITERION FOR COINTEGRATION TESTS BASED ON A VAR APPROXIMATION

  • Zhongjun Qu (a1) and Pierre Perron (a2)
  • DOI: http://dx.doi.org/10.1017/S0266466607070284
  • Published online: 01 August 2007
Abstract

We consider the cointegration tests of Johansen (1988, Journal of Economic Dynamics and Control 12, 231–254; 1991, Econometrica 59, 1551–1580) when a vector autoregressive (VAR) process of order k is used to approximate a more general linear process with a possibly infinite VAR representation. Traditional methods to select the lag order, such as Akaike's information criterion (AIC) or the Bayesian information criterion, often lead to too parsimonious a model with the implication that the cointegration tests suffer from substantial size distortions in finite samples. We extend the analysis of Ng and Perron (2001, Econometrica 69, 1519–1554) to derive a modified Akaike's information criterion (MAIC) in this multivariate setting. The idea is to use the information specified by the null hypothesis as it relates to restrictions on the parameters of the model to keep an extra term in the penalty function of the AIC. This MAIC takes a very simple form for which this extra term is simply the likelihood ratio test for testing the null hypothesis of r against more than r cointegrating vectors. We provide theoretical analyses of its validity and of the fact that cointegration tests constructed from a VAR whose lag order is selected using the MAIC have the same limit distribution as when the order is finite and known. We also provide theoretical and simulation analyses to show how the MAIC leads to VAR approximations that yield tests with drastically improved size properties with little loss of power.We are grateful to two referees for especially useful and constructive comments.

Copyright
Corresponding author
Address correspondence to Zhongjun Qu, Department of Economics, University of Illinois at Urbana-Champaign, 1206 S. Sixth Street, Champaign, Illinois 61820, USA; e-mail: zqu@uiuc.edu
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Econometric Theory
  • ISSN: 0266-4666
  • EISSN: 1469-4360
  • URL: /core/journals/econometric-theory
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