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Hi all!

I want to do the following:

I have 3 time series of dependent variables (e1,e2,e3). I have 2 time series of explanatory variables (f1,f2). I have 6 additional time series of explanatory variables (m1,m2,m3 and r1, r2, r3). Hereby, r1 and m1 correspond to e1 and so on.

I want to estimate the following regression system:

e1 = c(1) + c(2)*f1 + c(3)*f2 + c(4)*m1 + c(5)*r1
e1 = c(6) + c(7)*f1 + c(8)*f2 + c(4)*m2 + c(5)*r2
e1 = c(9) + c(10)*f1 + c(11)*f2 + c(4)*m3 + c(5)*r3

The variables e1, e2 and e3 have common coefficients in the m and r variables and specific coefficients in the intercepts and the f1 and f2 variable.

I want to estimate this as a system of seemingly unrelated regressions with feasible generalized least squares. In addition, I want to apply the Newey-West estimator of the covariance matrix to correct for autocorrelations.

This is how I proceed: I create a systems object from object/new object/system. I type in the specification written above. Then I hit the button Estimate. Then I choose Seemingly Unrelated Regression.

Now here is my question: why can't I then choose the option generalized least squares? Why can't I choose to correct with the Newey-West method?

I thank you very much for your valuable time. An answer would be most helpful!

Kind regards

Martin

Now here is my question: why can't I then choose the option generalized least squares?

Not quite sure what you mean by this, aren't GLS and ML estimation the same for SUR, or am I misunderstanding what you want?

Why can't I choose to correct with the Newey-West method?

Simple answer is that we haven't implemented it. EViews 7 will have this feature.

Thank you very much for your answer!

So when applying SUR there is no need to set for GLS. Am I right?

How can I then correct for autocorrelation, if Newey-West is not implemented yet?

Thank you very much!

Kind regards

Martin

Thank you very much for your answer!

So when applying SUR there is no need to set for GLS. Am I right?

right.

How can I then correct for autocorrelation, if Newey-West is not implemented yet?

Unfortunately, you can't...

Ok, let me quickly review the system I posted:

e1 = c(1) + c(2)*f1 + c(3)*f2 + c(4)*m1 + c(5)*r1
e2 = c(6) + c(7)*f1 + c(8)*f2 + c(4)*m2 + c(5)*r2
e3 = c(9) + c(10)*f1 + c(11)*f2 + c(4)*m3 + c(5)*r3

Is there another option in Eviews to allow for correlation among the error terms of the three equations and to correct for autocorrelation in the error terms of a given equation (e.g. in the first equation)?

I have relatively strong autocorrelation. So this is kind of important...

Many thanks

Kind regards

M

Ok, let me quickly review the system I posted:

e1 = c(1) + c(2)*f1 + c(3)*f2 + c(4)*m1 + c(5)*r1
e2 = c(6) + c(7)*f1 + c(8)*f2 + c(4)*m2 + c(5)*r2
e3 = c(9) + c(10)*f1 + c(11)*f2 + c(4)*m3 + c(5)*r3

Is there another option in Eviews to allow for correlation among the error terms of the three equations and to correct for autocorrelation in the error terms of a given equation (e.g. in the first equation)?

I have relatively strong autocorrelation. So this is kind of important...

Many thanks

Kind regards

M

Just write out the serial correlation by hand. For example, the first equation could be written
where c(20) is the serial correlation coefficient.

I thank you very, very much!

Your advice was most helpful. Now I have the Durbin-Watsons that I want;-)

Kind regards

M

Hi,
I would like to add to this subject on the issue of the number of equations and of variables per equation supported by SUR. I have a large model of 33 equations containing each 9 variables. I need to estimate this sytem by accounting for the contemporaneous correlation of residuals but also residual autocorrelation (because all of my residuals are autocorrelated). If I express all my equations by writing out the serial correlation, my SUR system will look like:
yi = a0i (1-bi) + bi yi(-1) + a1i (x1 - bi x1(-1)) + ... + a9i (x9 - bi x9(-1)), i=1,...,33
with 33x11=363 coefficients to be estimated.

With this equation specification Eviews returns me non-singular matrix message when the system exceeds 8 equations. Is there a size limit for system models, if not do you have any idea why I can't estimate the whole model?

Kind regards

Concerning the message, I meant "near-singuler matrix", sorry for the confusion.