EViews.com

Hi,

I have a sample of firm data for which I want to run multiple regressions. I use the same independent variables in every regression, but different dependent variables. Only complete observations (for which all variables are available) are included in the analysis. When estimating I include an AR(1) to correct for autocorrelation.

My problem is that when using different dependent variables I end up with varying number of observations, something that does not happen when I exclude the AR(1) from my model.

How can I set up my AR(1) model using exactly the same observations for all regressions?

Thank you for your help.

Lennart

AR(1) needs one lagged observation. You're probably missing that for some variables. Set the smpl to reflect complete observations for all dependent and independent including accounting for the lag. As a guess, just exclude the first observation in your current smpl.

Hi startz,

Thanks for your help.

That's what I thought as well, therefore I added the following selection criteria to my sample criteria when estimating to ensure that only complete observations are used:

sample: 1998 - 2009 if var1 <> na and var2 <> na ... etc

But it seems that this method doesn't include these selection criteria for the lagged variables needed for the AR(1) process.

Any ideas?

Thanks

I have solved the problem by generating new series for my dependent variables, setting them equal to NA if one of the other dependent variables is NA as well.