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Hi,

I'm having troubles solving the following. Please bear in mind that my knowledge of econometrics and eviews 7 is fairly limited..

My panel data set, in which I regress several explanatory variables on the natural logarithm of price to net asset value (monthly basis) of 25 UK investment trusts over a 10 year period, is suffering from first order autocorrelation (DW statistic is 0.48). So I have monthly premium levels of 25 different UK investment trusts over a 10 year period, that I try to explain through several (8 different ones) explanatory variables. The tip I got from my university was to use Newey-West standard error's but I've already read in another post that this is not possible in Eviews for panel data. Hence, how can I remove this autocorrelation (and actually also heteroskedasticity) from my model?

Hope that someone here knows what to do..

ps. I'm probably forgetting relevant info to come up with a meaningful answer so let me know if any further info is required.

Thank you in advance.

edit: I've found out that in Eviews: in the 'equeation estimation' menu --> 'panel options' tab, i can choose 'Weights' and 'Coef covariance method'. Can anyone advise me what to choose here to overcome the first order autocorrelation in my dependent variable?
My dependent variable is a monthly share discount or premium to the net asset value per share of the investment trust. This discount or premium is heavily autocorrelated with the discount/premium of the month before.

I'd appreciate the help!

You can add lagged dependent regressors to whiten the residuals, but with fixed effects you'll probably have to use a GMM approach. See the literature on dynamic panel data.

Dear Glenn, thank you for your response.

Another question regarding this topic; how do i diagnose if my data suffers from heteroskedasticity? As my data is panel data I am not sure how to check if and where there is heteroskedasticity and how to adjust for it. Can someone help me out?