Can't find a steady state, please help!
Posted: Wed Apr 17, 2013 12:43 pm
Please help with my code below, I keep getting the following error:
??? Error using ==> print_info at 57
Impossible to find the steady state. Either the model doesn't have a
steady state, there are an infinity of steady states, or the guess values
are too far from the solution
Error in ==> steady at 92
print_info(info,options_.noprint);
Error in ==> NKHabit1 at 252
steady;
Error in ==> dynare at 120
evalin('base',fname) ;
My model code as follows:
var y c I g a k_hat k n u nu pi pi_hush A_hat D_hat mc w R lambda mu theta m r q y_star;
varexo epsilon_a epsilon_theta epsilon_g epsilon_r epsilon_y;
parameters alpha epsilon phi beta gamma si delta sigma_o tau omega rho_a rho_g rho_r rho_theta phi_pi phi_y v theta_star pi_star rho_y;
alpha=0.3;
epsilon=6;
phi=0.5;
beta=0.99;
gamma=0.75;
si=1;
delta=1.4040;
sigma_o=0.025;
tau=0.5;
pi_star=0.005;
omega=0.2;
rho_a=0.97;
rho_g=0.85;
rho_r=0.85;
rho_theta=0.85;
phi_pi=1.5;
phi_y=0.5;
theta_star=1.9358;
v=1;
rho_y=0.95;
model;
exp(y)=exp(c)+exp(I)+exp(g);
exp(y)=(exp(a)*(exp(k_hat)^alpha)*exp(n)^(1-alpha))/exp(nu);
exp(k_hat)=exp(u)*exp(k);
exp(pi)=(((1-phi)*(exp(pi_hush)^(1-epsilon))+phi))^(1/(1-epsilon));
exp(nu)=(1-phi)*((exp(pi_hush)^(-epsilon))*(exp(pi)^epsilon))+phi*(exp(pi)^epsilon)*exp(nu(-1));
exp(pi_hush)=exp(pi)*(epsilon/(epsilon-1))*exp(A_hat)/exp(D_hat);
exp(A_hat)=exp(lambda)*exp(y)*exp(mc)+phi*beta*(exp(pi(+1))^epsilon)*exp(A_hat(+1));
exp(D_hat)=exp(lambda)*exp(y)+phi*beta*(exp(pi(+1))^(epsilon-1))*exp(D_hat(+1));
exp(w)=exp(mc)*(1-alpha)*((exp(k_hat)/(exp(n)))^alpha);
exp(R)=exp(mc)*alpha*((exp(k_hat)/(exp(n)))^(alpha-1));
exp(lambda)=(1/(exp(c)-gamma*exp(c(-1))))-((beta*gamma)/(exp(c(+1))-gamma*exp(c)));
exp(lambda)*exp(w)=theta*((1-exp(n))^(-si));
exp(lambda)*exp(R)=exp(mu)*delta*sigma_o*(exp(u)^(delta-1));
exp(lambda)=beta*exp(lambda(+1))*(1+exp(r(+1)))*(exp(pi(+1))^(-1));
exp(mu)=beta*(exp(lambda(+1)*exp(R(+1))*exp(u(+1))+exp(mu(+1))*(1-sigma_o*(exp(u(+1))^delta))));
exp(m)^(-v)=exp(lambda(+1))-beta*exp(lambda(+1))*(exp(pi(+1))^(-1));
exp(lambda)=exp(mu)*(1-((tau/2)*(((exp(I)/exp(I(-1)))-1)^2))-(tau*((exp(I)/exp(I(-1)))-1)*exp(I)/exp(I(-1))))+(beta*exp(mu(+1))*tau*((exp(I(+1))/exp(I))-1)*((exp(I(+1))/exp(I))^2));
exp(k(+1))=((1-((tau/2)*((exp(I)/exp(I(-1)))-1)^2))*exp(I))+(1-sigma_o*(exp(u)^delta))*exp(k);
exp(q)=exp(mu)/exp(lambda);
a=rho_a*(a(-1))+epsilon_a;
theta=(1-rho_theta)*theta_star+rho_theta*theta(-1)+epsilon_theta;
g=(1-rho_g)*(omega+y_star)+rho_g*g(-1)+epsilon_g;
exp(r(+1))=rho_r*exp(r)+(1-rho_r)*phi_pi*(exp(pi)-pi_star)+((1-rho_r)*phi_y*((exp(y)/exp(y(-1)))-1))+epsilon_r;
y_star=rho_y*(y_star(-1))+epsilon_y;
end;
initval;
y=0;
c=0.5;
I=0.17;
g=0.18;
a=1;
k_hat=7;
k=7;
n=0.3;
u=1;
nu=1;
pi=0.0005;
pi_hush=0.0266;
A_hat=7;
D_hat=9;
mc=0.8;
w=1.5;
R=0.035;
lambda=1.87;
mu=1.87;
theta=1.93;
m=35.6;
r=0.015;
q=1;
end;
steady;
shocks;
var epsilon_a; stderr 0.01;
var epsilon_theta; stderr 0.01;
var epsilon_g; stderr 0.01;
var epsilon_r; stderr 0.01;
var epsilon_y; stderr 0;
end;
stoch_simul(periods=1000, order=1, irf=20)y c I g a k_hat k n u nu pi pi_hush A_hat D_hat mc w R lambda mu theta m r q;
Thank you so mcuh!
??? Error using ==> print_info at 57
Impossible to find the steady state. Either the model doesn't have a
steady state, there are an infinity of steady states, or the guess values
are too far from the solution
Error in ==> steady at 92
print_info(info,options_.noprint);
Error in ==> NKHabit1 at 252
steady;
Error in ==> dynare at 120
evalin('base',fname) ;
My model code as follows:
var y c I g a k_hat k n u nu pi pi_hush A_hat D_hat mc w R lambda mu theta m r q y_star;
varexo epsilon_a epsilon_theta epsilon_g epsilon_r epsilon_y;
parameters alpha epsilon phi beta gamma si delta sigma_o tau omega rho_a rho_g rho_r rho_theta phi_pi phi_y v theta_star pi_star rho_y;
alpha=0.3;
epsilon=6;
phi=0.5;
beta=0.99;
gamma=0.75;
si=1;
delta=1.4040;
sigma_o=0.025;
tau=0.5;
pi_star=0.005;
omega=0.2;
rho_a=0.97;
rho_g=0.85;
rho_r=0.85;
rho_theta=0.85;
phi_pi=1.5;
phi_y=0.5;
theta_star=1.9358;
v=1;
rho_y=0.95;
model;
exp(y)=exp(c)+exp(I)+exp(g);
exp(y)=(exp(a)*(exp(k_hat)^alpha)*exp(n)^(1-alpha))/exp(nu);
exp(k_hat)=exp(u)*exp(k);
exp(pi)=(((1-phi)*(exp(pi_hush)^(1-epsilon))+phi))^(1/(1-epsilon));
exp(nu)=(1-phi)*((exp(pi_hush)^(-epsilon))*(exp(pi)^epsilon))+phi*(exp(pi)^epsilon)*exp(nu(-1));
exp(pi_hush)=exp(pi)*(epsilon/(epsilon-1))*exp(A_hat)/exp(D_hat);
exp(A_hat)=exp(lambda)*exp(y)*exp(mc)+phi*beta*(exp(pi(+1))^epsilon)*exp(A_hat(+1));
exp(D_hat)=exp(lambda)*exp(y)+phi*beta*(exp(pi(+1))^(epsilon-1))*exp(D_hat(+1));
exp(w)=exp(mc)*(1-alpha)*((exp(k_hat)/(exp(n)))^alpha);
exp(R)=exp(mc)*alpha*((exp(k_hat)/(exp(n)))^(alpha-1));
exp(lambda)=(1/(exp(c)-gamma*exp(c(-1))))-((beta*gamma)/(exp(c(+1))-gamma*exp(c)));
exp(lambda)*exp(w)=theta*((1-exp(n))^(-si));
exp(lambda)*exp(R)=exp(mu)*delta*sigma_o*(exp(u)^(delta-1));
exp(lambda)=beta*exp(lambda(+1))*(1+exp(r(+1)))*(exp(pi(+1))^(-1));
exp(mu)=beta*(exp(lambda(+1)*exp(R(+1))*exp(u(+1))+exp(mu(+1))*(1-sigma_o*(exp(u(+1))^delta))));
exp(m)^(-v)=exp(lambda(+1))-beta*exp(lambda(+1))*(exp(pi(+1))^(-1));
exp(lambda)=exp(mu)*(1-((tau/2)*(((exp(I)/exp(I(-1)))-1)^2))-(tau*((exp(I)/exp(I(-1)))-1)*exp(I)/exp(I(-1))))+(beta*exp(mu(+1))*tau*((exp(I(+1))/exp(I))-1)*((exp(I(+1))/exp(I))^2));
exp(k(+1))=((1-((tau/2)*((exp(I)/exp(I(-1)))-1)^2))*exp(I))+(1-sigma_o*(exp(u)^delta))*exp(k);
exp(q)=exp(mu)/exp(lambda);
a=rho_a*(a(-1))+epsilon_a;
theta=(1-rho_theta)*theta_star+rho_theta*theta(-1)+epsilon_theta;
g=(1-rho_g)*(omega+y_star)+rho_g*g(-1)+epsilon_g;
exp(r(+1))=rho_r*exp(r)+(1-rho_r)*phi_pi*(exp(pi)-pi_star)+((1-rho_r)*phi_y*((exp(y)/exp(y(-1)))-1))+epsilon_r;
y_star=rho_y*(y_star(-1))+epsilon_y;
end;
initval;
y=0;
c=0.5;
I=0.17;
g=0.18;
a=1;
k_hat=7;
k=7;
n=0.3;
u=1;
nu=1;
pi=0.0005;
pi_hush=0.0266;
A_hat=7;
D_hat=9;
mc=0.8;
w=1.5;
R=0.035;
lambda=1.87;
mu=1.87;
theta=1.93;
m=35.6;
r=0.015;
q=1;
end;
steady;
shocks;
var epsilon_a; stderr 0.01;
var epsilon_theta; stderr 0.01;
var epsilon_g; stderr 0.01;
var epsilon_r; stderr 0.01;
var epsilon_y; stderr 0;
end;
stoch_simul(periods=1000, order=1, irf=20)y c I g a k_hat k n u nu pi pi_hush A_hat D_hat mc w R lambda mu theta m r q;
Thank you so mcuh!