var y k l z c i g ex ms r f;
varexo eps_g eps_z eps_f eps_ms eps_ex;
parameters beta alpha delta gam_l gam_c gam_i gam_g gam_ex
gam_ms j eta_ms eta_g eta_f k2 h2
rho_g rho_z rho_f rho_ex rho_fe rho_ef;
predetermined_variables k;
beta=0.99;
alpha=0.9;
delta=0.05;
gam_l=1;
gam_c=0.3778;
gam_i=0.9;
gam_g=0.2;
gam_ex=0.5328;
gam_ms=0.01;
j=0.1;
eta_ms=0.6;
eta_g=0.7;
eta_f=2.2281;
k2=0.3;
h2=0.1;
rho_g=0.67;
rho_z=0.5;
rho_ex=0.2828;
rho_f=2;
rho_fe=-1.5;
rho_ef=1.1;
model(linear);
y=alpha*k+(1-alpha)*l+(log((1-beta+delta*beta)/(alpha*beta))+(1-alpha)*log(alpha/(1-alpha)))*z;
c=alpha*k-(alpha-gam_l)*l+(log((1-beta+delta*beta)/(alpha*beta))+(1-alpha)*log(alpha/(1-alpha)))*z;
c-c(+1)+(1-beta+delta*beta)*(1-alpha)*(1/(1-alpha)*log((1-beta+delta*beta)/(alpha*beta))+log(alpha/(1-alpha)))*z=0;
k(+1)=delta*i+(1-delta)*k;
i=-j*r;
y=gam_c*c+gam_i*i+gam_g*g+gam_ex*ex-gam_ms*(ms-ms(-1));
eta_ms*ms(-1)+eta_g*eps_g+eta_f*eps_f=k2/gam_ms*y-h2*r;
g=rho_g*g(-1)+eps_g;
z=rho_z*z(-1)+eps_z;
f=rho_f*f(-1)+rho_fe*ex(-1)+eps_f;
ex=rho_ex*ex(-1)+rho_ef(-1)*f+eps_ex;
end;
initval;
y=0;
k=0;
l=0;
z=0;
c=0;
i=0;
g=0;
ex=0;
ms=0;
r=0;
f=0;
end;
steady;
check;
shocks;
var eps_g=0.09^2;
var eps_z=0.09^2;
var eps_f=0.09^2;
var eps_ex=0.09^2;
var eps_ms=0.09^2;
end;
stoch_simul(order=1,nograph);
varobs ms f;
estimated_params;
beta, beta_pdf, 0.99, 0.002;
alpha, beta_pdf, 0.9, 0.002;
delta, beta_pdf, 0.05, 0.002;
gam_c, beta_pdf, 0.3778, 0.002;
gam_i, beta_pdf, 0.9, 0.002;
gam_g, beta_pdf, 0.2, 0.002;
gam_ex, beta_pdf, 0.5328, 0.002;
gam_ms, beta_pdf, 0.01, 0.002;
j, beta_pdf, 0.1, 0.002;
eta_ms, normal_pdf, 0.6, 0.002;
eta_g, normal_pdf, 0.7, 0.002;
eta_f, normal_pdf, 2.2281, 0.002;
k2, normal_pdf, 0.3, 0.002;
h2, gamma_pdf, 0.1,0.05;
rho_g, normal_pdf, 0.67, 0.002;
rho_z, normal_pdf, 0.5, 0.002;
rho_f, normal_pdf, 2, 0.002;
rho_ex, normal_pdf, 0.2828, 0.002;
rho_fe, normal_pdf, -1.5, 0.002;
rho_ef, normal_pdf, 1.1, 0.002;
end;
estimation(datafile=fms) f ms;
fms (2).xls
(38.76 KB)


雷达卡


期待您的指导啊,您一直以来的帮助对我学习DSGE也是一种莫大的鼓励,再次向您致敬!我也一定要向您学习,成为一名优秀的经济科学家
那我再试着重新编辑下模型,看看问题在哪里。。这个Et=Et+1我也是从欧拉公式线性化得到的。也许我哪里方法用的不对吧。我解了好几遍,最后得到的结果好像都和这个类似。我一会再重新推演下模型。谢谢老师指点。还有这个ms,那个万老师原文里是指y+ms-ms(-1)=c+i+g+ex作为行为人的效用最大化约束方程,我将它线性化后,不是ms-ms(-1)这项是不能避免的啊,老师说的ms是指这里么?老师看过那篇论文,那应该怎么解决?我的数据还需要HP去除趋势项么?
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