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var i, w, c, h, y, k, d, n, inv, l, q;
predetermined_variables k d;
varexo a p e;

parameters theta, beta, eta, delta, alpha, gamma, phi, rho;
beta = 0.985;
theta = 0.75;
delta = 0.025;
alpha = 0.33;
gamma = 0.27;
eta = 0.5;
phi = 0.5;
rho = 0.9;

model;
1 = beta*c/c(+1)*(1+i)*p/p(+1);
w/p = ((1-theta)/theta)*(c/(1-h));
alpha*y/k = ((delta+i*exp(q))/p)+(n<0)*((exp(q)-exp(q(+1))*(1-delta))/(p*(1-eta)));
gamma*y/h = w/p;
exp(q)*k = d + n;
k(+1) = (1-delta)*k+inv;
d(+1) = d+l-phi*(1-eta)*(p*y-w*h-delta*k-i*d);
exp(q(+1))*inv = l+(1-phi)*(1-eta)*(p*y-w*h-delta*k-i*d);
y = a*(k^alpha)*(h^gamma);
y = c+inv;
q(+1) = rho*q - e;
end;

initval;
i = 0.0152;
w = 1.1451;
c = 1.7015;
h = 0.5047;
y = 2.1404;
k = 17.5581;
d = 16.1304;
n = 1.4277;
inv = 0.4390;
l = 0.2195;
q = 0;
e = 0;
a = 1;
p = 1;
end;
steady;
check;

shocks;
var e = 1;
end;

stoch_simul (irf=100,pruning,periods=1000);


Code: Select all

alpha*y/k = ((delta+i*exp(q))/p)


WARNING: you are using a function (max, min, abs, sign) or an operator (<, >, <=, >=, ==, !=) which is unsuitable for a stochastic context; see the reference manual, section about "Expressions", for more details.

The use of the following functions and operators is strongly discouraged in a stochastic context:
max, min, abs, sign, <, >, <=, >=, ==, !=.
The reason is that the local approximation used by stoch_simul or estimation will by nature
ignore the non-linearities introduced by these functions if the steady state is away from the kink.
And, if the steady state is exactly at the kink, then the approximation will be bogus because the
derivative of these functions at the kink is bogus (as explained in the respective documentations of
these functions and operators).