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So I am using STATA, I have the log likelihood, AIC and BIC as such:

AIC: -112.1838 BIC: -100.2412 log likelihood: 64.23 N= 200 observations

So how do I conclude that there is no "over fitting" using these values?

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You cannot say anything about overfitting from (log-)likelihood, AIC or BIC alone. You could say something by comparing the model's in-sample fit with its out-of-sample prediction accuracy. If the in-sample residuals are subtantially smaller than the out-of-sample forecasting errors, the model suffers from overfitting; otherwise, it does not. Time series cross validation (e.g. as presented in Hyndman & Athanasopoulos "Forecasting: Principles and Practice" Section 5.10) is your way to go.

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