I have estimated a model with many interactions of both continuous and factor explanatory variables. The model is to be used for prediction.

My model has performed reasonably in out-of-sample testing.

However, I have found that my errors are correlated.

I took my fitted values of y and ran several regressions like this:

$$y\sim \text{fitted}(y)\cdot \text{explanatory variable}$$

There were many instances where an explanatory variable already included in the model was significant.

What are some good techniques to resolve this issue?

Side note:
I have no strong a priori views on what the "true" model should look like.

  • $\begingroup$ Many people ignore the autocorrelation in logit. $\endgroup$ – Aksakal Apr 19 '14 at 19:28

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