Given I want to forecast e.g. monthly sales (dependent variable, likely non-stationary) with regression and ARIMA errors (ARIMA in R with xreg) I have e.g. two independent variables/covariates:
- Holidays per month (stationary)
- GDP or similar (non-stationary)
In R an ARIMA(p,1,q) will automatically difference the covariates automatically as well - could that be an issue, given one variable is already stationary? If yes, how could it be avoided?
Edit: I would like to avoid to check for stationarity and do differencing manually - as it gets ugly/tedious especially with seasonality. So far I'm using mostly the auto.arima from the forecast package with some restrictions.