Dear All,

I would like to mix deterministic and stochastic shock (i.e., the model is stochastic, but agents know from the start of the simulation about future exogenous changes).

This is how I try to do it:

var k, c, y, z;

varexo_det e;

varexo u;

parameters rho psi alpha;

parameters alpha, beta, delta, rho;

alpha = 0.36;

beta = 0.98;

delta = 0.2;

rho = 1;

model;

1/c = beta * 1/c(+1) * (exp(z(+1)) * alpha * k^(alpha-1) + 1 - delta);

y = exp(e)*exp(z) * k(-1)^alpha;

k = y - c + (1 - delta) * k(-1);

z = rho * z(-1) + u;

end;

initval;

k = 0.1;

c = 1;

y = 1;

z = 0;

u = 0;

end;

steady;

shocks;

var u; stderr 0.05;

var e;

periods 1:1 2:2 3:3;

values 0.01 0.02 0.03;

end;

stoch_simul(irf=20,drop=0);

forecast(periods=200);

Is that correct (I was also thinking about including e=0 in initval, but I am not sure this would be correct)?

If yes, why IRFs for this model are exactly the same as IRFs for the model without a deterministic shock? I would think that steady-states for the two models should differ given that with stoch_simul and deterministic shock I should get IRFs that are conditional on this deterministic shock?

Am I missing something?

Many thanks for all your potential responses.