My problem is outlined as follows:   I have a time series which I am trying to forecast (let's call this series OUTPUT), let's say through the end of 2018. The seasonal aspect of this value may be present, but if it is, is VERY slight. I also have two other time series (let's call them INPUT1 and INPUT2) that are being used to predict the OUTPUT series. I have values for these two series through the end of 2018 and would like to use their relationship with the OUTPUT in my forecast.   My attempts thus far have been using PROC ARIMA with an estimate statement that looks something like:   estimate p=1 input=( / (1) INPUT1 / (1) INPUT2)   But I'm unsure if this is correct. I've been unable to find any documentation anywhere on how to determine the proper differentiation or format of the inputs to use in a PROC ARIMA. It's also possible that PROC ESM or USM are more useful for this and I've been neglecting them. Any insight on how to choose and fit a forecasting model for a time series with inputs would be great. Thanks in advance.  ... View more