Compare unrestricted and restricted VARX-DCC model
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mengqi
- Posts: 18
- Joined: Tue Jun 21, 2016 1:35 pm
Compare unrestricted and restricted VARX-DCC model
Hi Tom,
I have bivariate VAR-DCC model with some exogenous variables in the conditional mean equations. How do I run a F-test, to see whether a restricted version of the model is preferable?
kind regards
I have bivariate VAR-DCC model with some exogenous variables in the conditional mean equations. How do I run a F-test, to see whether a restricted version of the model is preferable?
kind regards
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TomDoan
- Posts: 7825
- Joined: Wed Nov 01, 2006 4:36 pm
Re: Compare unrestricted and restricted VARX-DCC model
Probably the simplest thing would be to do a likelihood ratio test. To do a Wald test, use the Statistics--Regression Tests, pick Exclusion Restrictions and select the exogenous variables in the scrolling list.
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Esteban
- Posts: 10
- Joined: Tue May 14, 2019 12:13 pm
Re: Compare unrestricted and restricted VARX-DCC model
Hi Tom,
One doubt about what you answered. The thing is that the GARCH instruction doesn't define the variable %logdet (Log determinant), so what should we do in order to calculate the loglikelihood ratio?. By first calculating the determinant of the H matrices?. Or we just simply use the %logdet of the VAR as a good estimation of the average variance matrix Σ.
Thanks for your help.
One doubt about what you answered. The thing is that the GARCH instruction doesn't define the variable %logdet (Log determinant), so what should we do in order to calculate the loglikelihood ratio?. By first calculating the determinant of the H matrices?. Or we just simply use the %logdet of the VAR as a good estimation of the average variance matrix Σ.
Thanks for your help.
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TomDoan
- Posts: 7825
- Joined: Wed Nov 01, 2006 4:36 pm
Re: Compare unrestricted and restricted VARX-DCC model
Use %LOGL. %LOGDET only has a 1-1 mapping with the log likelihood for VAR's and similar models (with a covariance matrix fixed over time)---it's not defined by GARCH because it has no meaning with a GARCH model.