AIRMA (2,1,3) - insignificant coefficients?

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Confusedaboutstats

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Hi there,

I estimated an AIRMA (2,1,3) model and found that AR(1), AR(2) had both significant coefficients however my MA tests were unexpected - both the MA(2) and MA(3) were significant yet the MA(1) was insignificant. Can someone please explain what that actually means? Should I remove one of the MA lags in my estimation?

Thank you very much for your help
 
Confusedaboutstats said:
Hi there,

I estimated an AIRMA (2,1,3) model and found that AR(1), AR(2) had both significant coefficients however my MA tests were unexpected - both the MA(2) and MA(3) were significant yet the MA(1) was insignificant. Can someone please explain what that actually means? Should I remove one of the MA lags in my estimation?

Thank you very much for your help
Click to expand...

I suspect that would depend on your data but using 3 error smoothing terms does seem a little excessive to me. But then I only have moderate experience with time series forecasting and that was in the somewhat distance past. Possibly
http://people.duke.edu/~rnau/411home.htm
might be of interest. It is said on one of those pages
It is generally advisable to stick to models in which at least one of p and q is no larger than 1, i.e., do not try to fit a model such as ARIMA(2,1,2), as this is likely to lead to overfitting and "common-factor" issues that are discussed in more detail in the notes on the mathematical structure of ARIMA models.
Click to expand...

BTW: It is ARIMA, not AIRMA as I understand it.
 
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