Finite Sample Properties of Likelihood Ratio Tests for Cointegrating Ranks when Linear Trends are Present

1994 ◽  
Vol 76 (1) ◽  
pp. 66 ◽  
Author(s):  
Hiro Y. Toda
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Tests ◽  
Finite Sample ◽  
Finite Sample Properties ◽  
Linear Trends

Finite Sample Performance of Likelihood Ratio Tests for Cointegrating Ranks in Vector Autoregressions

1995 ◽  
Vol 11 (5) ◽  
pp. 1015-1032 ◽  
Author(s):  
Hiro Y. Toda
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Likelihood Ratio ◽  
Test Performance ◽  
Likelihood Ratio Tests ◽  
Nuisance Parameters ◽  
Test Statistics ◽  
Finite Sample ◽  
Vector Autoregressions ◽  
Finite Sample Properties

This paper investigates through Monte Carlo simulation the finite sample properties of likelihood ratio tests for cointegrating ranks that were proposed by Johansen (1991, Econometrica 59, 1551–1580). We transform the model into a canonical form so that the experiment is well controlled without loss of generality and then conduct a comprehensive simulation study. As expected, the test performance is very sensitive to the value of the stationary root(s) of the process. We also find that the test performance depends crucially on the correlation between the innovations that drive the stationary and the nonstationary components of the process. We conclude that 100 observations are not sufficient to ensure reasonably good performance uniformly over the values of the nuisance parameters that affect the distributions of the test statistics.

scholarly journals A BARTLETT CORRECTION FACTOR FOR TESTS ON THE COINTEGRATING RELATIONS

2000 ◽  
Vol 16 (5) ◽  
pp. 740-778 ◽  
Author(s):  
Søren Johansen
Keyword(s):  
Asymptotic Distribution ◽  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Correction Factor ◽  
Likelihood Ratio Tests ◽  
Ratio Test ◽  
Finite Sample ◽  
Bartlett Correction ◽  
Simulation Experiments ◽  
Sample Distribution

Likelihood ratio tests for restrictions on cointegrating vectors are asymptotically χ2 distributed. For some values of the parameters this asymptotic distribution does not give a good approximation to the finite sample distribution. In this paper we derive the Bartlett correction factor for the likelihood ratio test and show by some simulation experiments that it can be a useful tool for making inference.

A Test for Functional Form Against Nonparametric Alternatives

1992 ◽  
Vol 8 (4) ◽  
pp. 452-475 ◽  
Author(s):  
Jeffrey M. Wooldridge
Keyword(s):  
Alternative Model ◽  
Regression Models ◽  
Functional Form ◽  
Parametric Model ◽  
Finite Sample ◽  
Test Statistic ◽  
Sieve Estimation ◽  
Finite Sample Properties ◽  
Standard Normal ◽  
Nonparametric Alternatives

A test for neglected nonlinearities in regression models is proposed. The test is of the Davidson-MacKinnon type against an increasingly rich set of non-nested alternatives, and is based on sieve estimation of the alternative model. For the case of a linear parametric model, the test statistic is shown to be asymptotically standard normal under the null, while rejecting with probability going to one if the linear model is misspecified. A small simulation study suggests that the test has adequate finite sample properties, but one must guard against over fitting the nonparametric alternative.

scholarly journals Quasi-likelihood ratio tests for cointegration, cobreaking, and cotrending

2019 ◽  
Vol 38 (8) ◽  
pp. 881-898
Author(s):  
Josep Lluís Carrion-i-Silvestre ◽  
Dukpa Kim
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Tests
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