I have the following time series dataset (dependent | independent) :
Sales | Income,Inflation, Interest Rates etc
All of this is dynamic data pertaining to each of 24 months (month:0 to month:24). For 25th month onward I have no data for the independent variables (Income,Inflation, Interest Rates etc), yet I want to be able to predict sales for month:25 +.
I have been trying to figure out models which I can used to implement this scenario including Dynamic Regression and ARMAX/ARIMAX models. However, it seems that to be able to predict sales for the 25th month, i need data for dependent variables (Income,Inflation, Interest Rates etc) for the month (25).
Can I create a model using lagged values of the dependent and independent variables, used together in a regression model? I'm not sure if that makes sense.
This is my first time series model and im not sure if i am on the right track. Please advise.