What is Pedroni cointegration test?

What is Pedroni cointegration test?

Pedroni (Engle-Granger based) Cointegration Tests. The Engle-Granger (1987) cointegration test is based on an examination of the residuals of a spurious regression performed using I(1) variables. If the variables are cointegrated then the residuals should be I(0).

What is Engle Granger test?

The Engle Granger test is a test for cointegration. It constructs residuals (errors) based on the static regression. The test uses the residuals to see if unit roots are present, using Augmented Dickey-Fuller test or another, similar test. The residuals will be practically stationary if the time series is cointegrated.

How do you read Engle Granger cointegration test?

Interpreting Our Cointegration Results The Engle-Granger test statistic for cointegration reduces to an ADF unit root test of the residuals of the cointegration regression: If the residuals contain a unit root, then there is no cointegration. The null hypothesis of the ADF test is that the residuals have a unit root.

How do you read Johansen cointegration results?

Interpreting Johansen Cointegration Test Results

1. The EViews output releases two statistics, Trace Statistic and Max-Eigen Statistic.
2. Rejection criteria is at 0.05 level.
3. Rejection of the null hypothesis is indicated by an asterisk sign (*)
4. Reject the null hypothesis if the probability value is less than or equal to 0.05.

Is there a panel cointegration test for unit root?

This paper presents a review of the most recent cointegration tests in a panel framework. This kind of test has been developed to extend the unit root approach to a multivariate context.

How is cointegration used to test static regression?

This method is based on testing the residuals created based on static regression for the presence of unit roots, i.e., if two non-stationary time series are cointegrated, the result will confirm the stationary characteristic of residuals.

How does the Westerlund test of cointegration work?

These related tests of cointegration work differently but allow us to come to the same conclusion: the panels are cointegrated. The Westerlund test uses yet another approach, one that imposes fewer restrictions.

How are panel cointegration tests used in multivariate contexts?

This kind of test has been developed to extend the unit root approach to a multivariate context. Panel cointegration tests in literature are twofold, on the one hand there are those which verify the null hypothesis of no cointegration, on the other hand there are those which verify the null hypothesis of cointegration.