I've got (say) two series inflation(inf) and output gap according to different definitions (og1, og2, og3 etc...).
To judge the prediction occuracy of each measure of OG upon INF, i want to estimate
INF=c(1) + c(2)OG
with a rolling regression of this kind:
-200 initial observation
-cut the last 20, I got 180 obs left (from 1 to 180)
- use 1 to 180 to estimate the parameters;
- use parameter estimates for 1-step forecast (181° to be estimated)
- calculate between forecast and actual value and save;
-cut the last 19, I got 180 obs left (from 2 to 181)
- use 2 to 181 to estimate the parameters;
- use parameter estimates for 1-step forecast (182° to be estimated)
- calculate between forecast and actual value and save;
and so on, as long as I can still cut the sample.
Then I need a RMSE (root mean square error) computed on all the residuals saved!
CAN ANYONE PLEASE HELP ME WITH THIS? I NEED IT AS QUICK AS POSSIBLE!