I try to find the shocks within a given horizon through conditional_forecast by combining the domestic data and a well-defined model. This method has been adopted and the related paper has been published in EER.
Similarily, I set preference shocks, labor supply shocks, fiscal shocks, and monetary policy shocks and obtain the values of these shocks via conditional_forecast. The impulse responses of the relevant variables in the oo_ file are consistent with the data.
However, I re-simulated these shocks using deterministic simulations and found that the impulse response functions of the variables were completely inconsistent with the data I had collected.
The last two lines of the m file correspond to the mod files for conditional prediction and cross-validation, respectively. I want to know why this difference occurs? Is it because one of them is based on VAR forecasts, while the other is based on simulations of a general equilibrium model?