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Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration
TLDR
The authors employed response surface regressions based on simulation experments to calculate asymptotic distribution functions for the likelihood ratio tests for cointegration proposed by Johansen and provided tables of critical values that are very much more accurate than those available previously.Abstract:
This paper employs response surface regressions based on simulation experments to calculate asymptotic distribution functions for the likelihood ratio tests for cointegration proposed by Johansen The paper provides tables of critical values that are very much more accurate than those available previously However the principal contributions of the paper are a set of data les that contain estimated asymptotic quantiles obtained from response surface estimation and a computer program for utilizing them This program which is freely available via the Internet can easily be used to calculate asymptotic critical values and P values Graphs of some of the tabulated distribution functions are also provided An empirical example motivated by the European Economic and Monetary Union proposed in the Maastricht Treaty suggests that not all the countries of the European Union may qualify initially for participation in the EMU.read more
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References
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Journal ArticleDOI
Statistical analysis of cointegration vectors
TL;DR: In this paper, the authors consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors, and derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimensions.
Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models / Søren Johansen
TL;DR: In this paper, the authors present the likelihood methods for the analysis of cointegration in VAR models with Gaussian errors, seasonal dummies, and constant terms, and show that the asymptotic distribution of the maximum likelihood estimator is mixed Gausssian.
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Critical values for cointegration tests
TL;DR: In this article, the results of the simulation experiments are summarized by means of response surface regressions in which critical values depend on the sample size and can be read off directly, and critical values for any finite sample size can easily be computed with a hand calculator.
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Numerical distribution functions for unit root and cointegration tests
TL;DR: In this article, the authors used response surface regressions based on simulation experiments to calculate distribution functions for some well-known unit root and cointegration test statistics, which can be used to calculate both asymptotic and finite sample critical values and P-values for any of the tests.
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A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics1
TL;DR: In this paper, the authors present an examination of such models for variables integrated at most of order one, when tests for cointegration involve statistics with non-standard asymptotic distributions.