It depends what you are trying to do. If you work with a linear(ized) model, you can simply set the standard deviation of the shocks to the value desired. Due to certainty equivalence, that is a valid way. At higher order, you indeed need to follow the approach outlined in my mod-file.

Thanks for your reply. I’m working with a simple log-linearized RBC model.

I can’t simply set the deviation of the shock to the value desired, because it affects the expectation in intertemporal Euler equation. Specifically, I want a very large realization of the stochastic shock at the beginning followed by a series of zero deviations to investigate how the economy goes back to steady states depending on the size of the shock with the std. dev. the same. Again, std. dev. of innovation enters into play by affecting the expectation in intertemporal Euler. You could take a look of my codes here, which is really short.https://github.com/wulxGH/2010d/blob/master/PS2Q1.mod I want the shock realize 5*sigmaA rather than sigmaA.

You need to rethink your exercise. In a linear model certainty equivalence holds. In a linear model, there are no Jensen’s Inequality effects coming from the expectation operator,
The IRF to 5 standard deviation shock is simply the IRF to a 1 standard deviation shock multiplied by 5.

Again, in a linear model, there are not interaction or size effects. The IRF to a series of shocks is simply the linear combination of the IRFs to a single shock.
If you want to consider the effects of different shock sizes or interactions between shocks, you need a nonlinear model.

Yes I agree. I’m thinking about applying different shocks at different time periods and see their linear combination directly rather than doing a series of experiments and adding them myself. But maybe it’s not very meaningful. Anyway, thanks very much for your patient explanations!

I would like to set the size of a stochastic shock, with the goal of changing another variable. For example, a TFP shock to increase Y by 20%, how to set the size of the TFP shock? linearized first?

My question comes from the codes of Iacoviello (2017). They attempt to demonstrate the asymmetric responses, the sizes of a positive shock and a negative shock are different in magnitude, but they increase or decrease another variable (house price) by 20%, I’m a bit confused how to set the size of these shocks.

If I understand your question correctly, you are looking for a shock to make a given endogenous variable move by a pre-specified amount. There is no standard routine available for that. If you only have to do this once, I would simply use trial and error.

Note that linearization is not recommended. In that case, the model would become symmetric.

If you have to do this in an automated way, you could use a solver, but that is quite complicated.