Theoretical moments do not match data
Posted: Fri Jun 22, 2012 4:09 pm
Hi,
I have estimated a DSGE model with ML using my own MATLAB code. I have then included in dynare the estimated parameters to check whether the theoretical second moments from the estimated DSGE model are close to the data. I find that the theoretical moments are far greater and cannot see why. Can anyone suggest what I am doing wrong?
Details are below.
Thanks. Vito
My mod code is
// NEW KEYNESIAN MODEL
var r y p uy up ur;
varexo ey ep er;
parameters gamma gamma1 gamma2 phi del del1 del2 kappa psip1 psiy1 psir1 psip2 psiy2 psir2;
gamma=0.3253;
gamma1=0.8491;
gamma2=-0.1906;
phi=0.0076;
del=0.4943;
del1=0.2290;
del2=0.2767;
kappa=0.0243;
psip1=0.00025;
psiy1=0.1152;
psir1=0.6095;
psip2=0.2048;
psiy2=0;
psir2=0.2537;
model(linear);
y = gamma*y(1)+gamma1*y(-1)+gamma2*y(-2)-phi*(r-p(1))+uy;
p = del*p(1)+del1*p(-1)+del2*p(-2)+kappa*y+up;
r = psip1*p(-1)+ psiy1*y(-1)+ psir1*r(-1) +psip2*p(-2) + psiy2*y(-2)+ psir2*r(-2) + ur;
up=1.12387427199994*ep;
uy=-0.0382815889959732*ep+0.759252556400376*ey;
ur=0.221657786793378*ep+0.403195872651417*ey+1.28914940964670*er;
end;
shocks;
var ey; stderr 1;
var ep; stderr 1;
var er; stderr 1;
end;
steady(solve_algo=1); // calculate steady states (solve_algo=0 use FSOLVE, solve_algo=1 us DYNARE SOLVER)
check; // check the eigenvalues of the system
stoch_simul(periods=0,irf=0,simul_seed=3) y r p;
This code returns the following theoretical moments
VARIABLE MEAN STD. DEV. VARIANCE
y 0.0000 4.7862 22.9079
r 0.0000 15.0979 227.9472
p 0.0000 10.4777 109.7812
while the sample variances for y, r and p are 5, 6 and 13 respectively .
I have estimated a DSGE model with ML using my own MATLAB code. I have then included in dynare the estimated parameters to check whether the theoretical second moments from the estimated DSGE model are close to the data. I find that the theoretical moments are far greater and cannot see why. Can anyone suggest what I am doing wrong?
Details are below.
Thanks. Vito
My mod code is
// NEW KEYNESIAN MODEL
var r y p uy up ur;
varexo ey ep er;
parameters gamma gamma1 gamma2 phi del del1 del2 kappa psip1 psiy1 psir1 psip2 psiy2 psir2;
gamma=0.3253;
gamma1=0.8491;
gamma2=-0.1906;
phi=0.0076;
del=0.4943;
del1=0.2290;
del2=0.2767;
kappa=0.0243;
psip1=0.00025;
psiy1=0.1152;
psir1=0.6095;
psip2=0.2048;
psiy2=0;
psir2=0.2537;
model(linear);
y = gamma*y(1)+gamma1*y(-1)+gamma2*y(-2)-phi*(r-p(1))+uy;
p = del*p(1)+del1*p(-1)+del2*p(-2)+kappa*y+up;
r = psip1*p(-1)+ psiy1*y(-1)+ psir1*r(-1) +psip2*p(-2) + psiy2*y(-2)+ psir2*r(-2) + ur;
up=1.12387427199994*ep;
uy=-0.0382815889959732*ep+0.759252556400376*ey;
ur=0.221657786793378*ep+0.403195872651417*ey+1.28914940964670*er;
end;
shocks;
var ey; stderr 1;
var ep; stderr 1;
var er; stderr 1;
end;
steady(solve_algo=1); // calculate steady states (solve_algo=0 use FSOLVE, solve_algo=1 us DYNARE SOLVER)
check; // check the eigenvalues of the system
stoch_simul(periods=0,irf=0,simul_seed=3) y r p;
This code returns the following theoretical moments
VARIABLE MEAN STD. DEV. VARIANCE
y 0.0000 4.7862 22.9079
r 0.0000 15.0979 227.9472
p 0.0000 10.4777 109.7812
while the sample variances for y, r and p are 5, 6 and 13 respectively .