Permanent shock for welfare

Conditional welfare is just the output of simult_ in a stochastic context.

But how can you have a permanent shock in a stochastic context?

I guess this is the point of our talk. Doing permanent shock in a stochastic context is not a good idea (i.e using a unit root process). But is there any way to have both at the same time, permanent shock and any kind of welfare measurement that can be used for optimal simple rules at the same time?

Many thanks for your kind help.

Try using a setup like the attached one. It features a unit root process with zero variance. Should should allow to analyze an unexpected unit root shock.
example1_unit.mod (1.7 KB)

Many thanks

Might be a stupid question. For me, it looks like the mod file gives back the IRFs for the model. But to my best knowledge, the “theoretical moments” or “approximated moments” is calculated differently right?

If you define welfare in your model, then the first simulation period value will provide conditional welfare.

1 Like