OK, I got it, now. I think we call these pseudo out of sample, because we do have observations for them.
We now have them with recursive estimation, but we should add it for fixed calibrated/estimated-once parameters and comute RMSEs
Johannes Pfeifer writes:
Isn't it what the forecast option of estimation() does?
No. If the model is estimated at the first 100 observations (nobs=100), the forecast option does the last forecast at observation 100, i.e. E_100(y_100+k). But I want to have E_101(y_101+k), E_102(y_102+k), E_103(y_103+k),...m E_200(y_200+k)
RMSE would imply several forecasts at k horizon.
Exactly. But this is what I would get in the case outlined above. 100 k-step ahead forecasts made conditional on information available at t=101,...,t=200.
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