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// See fs2000.mod in the examples/ directory for details on the model
var m P c e W R k d n l gy_obs gp_obs y dA;
varexo e_a e_m;
parameters alp bet gam mst rho psi del;
alp = 0.33;
bet = 0.99;
gam = 0.003;
mst = 1.011;
rho = 0.7;
psi = 0.787;
del = 0.02;
model;
dA = exp(gam+e_a);
log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
W = l/n;
-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
P*c = m;
m-1+d = l;
e = exp(e_a);
y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
gy_obs = dA*y/y(-1);
gp_obs = (P/P(-1))*m(-1)/dA;
end;
steady_state_model;
dA = exp(gam);
gst = 1/dA;
m = mst;
khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
n = xist/(nust+xist);
P = xist + nust;
k = khst*n;
l = psi*mst*n/( (1-psi)*(1-n) );
c = mst/P;
d = l - mst + 1;
y = k^alp*n^(1-alp)*gst^alp;
R = mst/bet;
W = l/n;
ist = y-c;
q = 1 - d;
e = 1;
gp_obs = m/dA;
gy_obs = dA;
end;
shocks;
var e_a; stderr 0.014;
var e_m; stderr 0.005;
end;
steady;
check;
estimated_params;
% alp, beta_pdf, 0.356, 0.02;
bet, beta_pdf, 0.993, 0.002;
% gam, normal_pdf, 0.0085, 0.003;
% mst, normal_pdf, 1.0002, 0.007;
% rho, beta_pdf, 0.129, 0.223;
% psi, beta_pdf, 0.65, 0.05;
% del, beta_pdf, 0.01, 0.005;
% stderr e_a, inv_gamma_pdf, 0.035449, inf;
% stderr e_m, inv_gamma_pdf, 0.008862, inf;
end;
varobs gp_obs gy_obs;
options_.solve_tolf = 1e-12;
estimation(order=1,datafile=fsdat_simul,silent_optimizer,nobs=192,loglinear,mh_replic=2000,mh_nblocks=1,mh_jscale=0.8,tex);
model_comparison fs2000(0.5) fs2000_calibrated_covariance(0.5);
if isfield(oo_,'Model_Comparison')
error('Model Comparison should not work with ML')
end
model_comparison fs2000 fs2000_initialize_from_calib;
model_comparison fs2000(0.5) fs2000_initialize_from_calib(0.5);
model_comparison fs2000(0.25) fs2000_initialize_from_calib(0.25);
model_comparison (marginal_density=laplace) fs2000(0.5) fs2000_initialize_from_calib(0.5);
if oo_.Model_Comparison.fs2000.Posterior_Model_Probability < oo_.Model_Comparison.fs2000_initialize_from_calib.Posterior_Model_Probability && ...
oo_.Model_Comparison.fs2000.Log_Marginal_Density > oo_.Model_Comparison.fs2000_initialize_from_calib.Log_Marginal_Density
error('Model Comparison not correct')
end
oo_laplace=oo_;
model_comparison (marginal_density=modifiedharmonicmean) fs2000(0.5) fs2000_initialize_from_calib(0.75);
if abs(oo_laplace.Model_Comparison.fs2000.Log_Marginal_Density-oo_.Model_Comparison.fs2000.Log_Marginal_Density)>0.85
error('Laplace and Harmonic Mean do not match')
end
model_comparison (marginal_density=modifiedharmonicmean) fs2000(0) fs2000_initialize_from_calib(1);
if oo_.Model_Comparison.fs2000.Posterior_Model_Probability~=0 && oo_.Model_Comparison.fs2000_initialize_from_calib.Log_Marginal_Density~=1
error('Incorporation of prior wrong')
end
model_comparison(marginal_density=laplace) fs2000(0.333) fs2000_initialize_from_calib(0.333) fs2000_model_comparison(0.333);
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