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Startz,

Thank you very much for your time! Helped me a lot.

Wouter

That's not possible when running a GARCH(1,1) model. I use Eviews 7. The only test available is the ARCH LM test under this window...

Durbin Watson, or is that not a valid test if a lagged independent variable in included on teh right hand side? If so, is Durbin Watson a valid test for ar(1) included?

I mean lagged dependent variable so y(-1). So what youre saying with your last sentence is both are valid to do but lagged dependet variable is better? Can it be determined which is best to ( lagged depenedent or ar(1)) do since the results vary quite substantially?

Would it be wrong to use a ldv instead of ar(1)? The results (coefficients etc) vary dramatically, but both seem to remove autocorrelation

ok thank you very much!

So which one is better to include in the mean equation in order to control for autocorrelation?

startz,

What is the difference between including an ar(1) or a lagged dependent variable in the equation?

sincerely

Wouter

Hi all,

I'm wondering the same thing as Michal83. Does anyone know this?

Thanks in advance!

Wouter

ok thanks!

Oke thank you! I recently read another post of yours about serial correlation and GARCH(1,1) models. If my residuals contain serial correlation and an ARCH test shows I should use a GARCH(1,1) model, how can i correct for serial correlation in the GARCH model? I do not find such an option in the opt...

If the explanatory variables are strongly correlated this can lead to inflated standard errors leading to unstable results. So I guess just for the regular multicollinearity problems.

Dear, By generating a correlation matrix between the independent variables of my panel of data I checked for possible multicollinearity problems. I have 4 different sections. My question now is whether I should look at the correlations between the variables only within an section or also across sect...

So is it then a sound move to use 'white cross section' in the coefficient covariance method menu for my panel data because I found heteroskedasticity in the unstructured data set (same data as panel)? Or should I just select ordinary ?

Dear, I have two questions: 1): I'm currently running a regression with panel data. In order to put less weight on outliers I would like to run a robust least squares regression. This function is however not incorporated in the version (7) I use. Is there a way to do something similar? For now I hav...