My question is probably very elementary but I haven't been able to find an explanation of recursive forecasting that I fully understand.
I've read a journal article that seemed to recursively forecast unemployment with an AR(2) process augmented by a variable for depth of recession lagged by one period. It seems to me like that wouldn't be possible if the model doesn't produce forecasts for the other variable to include in the forecast for the subsequent period as well.
So does recursive forecasting use actual values for each subsequent forecast or forecasted ones? And does it just do that for the auto-regressed variable or both? Is it a standard practice to use forecasted values for one variable and actual ones for another?
I have quarterly data on unemployment (U) and change in total lending (DL) in an economy. I want to estimate an AR(2) for U plus DL at t-1. How can I make out of sample forecasts with this model? Is my only option to use predicted values for DL that are forecasted by a separate model?