Hi Flora, To my knowledge, PROC PANEL does not have a stepwise option. I'm not a fan of automatic selection, but there are a number of things you can do to go down that path. Given that the panel membership is reasonably highly correlated, you could pick a test subject and perform a stepwise OLS regression. Or similarly, perform a stepwise regression on the panel average. You could also produce ranked pairwise correlations to provide guidance while manually model building. On the complex side, you could write a macro for a panel stepwise selection using AIC/BIC instead of Rsq. Hope this helps!
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Realizing that this is old thread, but it is still unanswered... Manuel, what you are observing as an 'offset' in the plot is the error correction mechanism in action. The best way to observe the effects of the ECM would be to revise your plot and show actuals, structural (unconditional) forecasts, and error corrected (conditional) forecasts. On your output statement, use PREDICTEDM= and PREDICTED= for the structural and conditional forecasts, respectively. You will find that there is a substantial difference in fit visually. This is because, in an AR(1) model, the ECM 'corrects' the structural forecast for the current period by applying a percentage of the last period's residual (something a little different happens in the out-of-sample period). Your ECM forecasts will always be expected to 'follow' your actual values in the in-sample period. Be very cautious of relying on the goodness of the in-sample fit, as for this type of model, that may or may not be indicative of accurate forecasts. Hope this helps any stragglers coming across this post!
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