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copying tests from version 3 to version 4 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@10 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
michel 2005-02-19 19:13:45 +00:00
parent 95d2f1d0a4
commit f570680c6f
45 changed files with 2103 additions and 0 deletions
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23
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var dx dy x y;
varexo e_x e_y;
parameters rho_x rho_y;
rho_x = 0.5;
rho_y = -0.3;
model;
dx = rho_x*dx(-1)+e_x;
dy = rho_y*dy(-1)+e_y;
x = x(-1)+dx;
y = y(-1)+dy;
end;
shocks;
var e_x; stderr 0.01;
var e_y; stderr 0.01;
end;
stoch_simul(order=1,periods=1000,irf=0,nomoments);
save data1 dx dy x y;

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var dx dy;
varexo e_x e_y;
parameters rho_x rho_y;
rho_x = 0.5;
rho_y = -0.3;
model;
dx = rho_x*dx(-1)+e_x;
dy = rho_y*dy(-1)+e_y;
end;
estimated_params;
rho_x,NORMAL_PDF,0.5,0.1;
rho_y,NORMAL_PDF,-0.3,0.1;
stderr e_x,INV_GAMMA_PDF,0.01,inf;
stderr e_y,INV_GAMMA_PDF,0.01,inf;
end;
varobs dx dy;
check;
estimation(datafile=data1,nobs=1000,mh_replic=2000);

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var dx dy x y;
varexo e_x e_y;
parameters rho_x rho_y;
rho_x = 0.5;
rho_y = -0.3;
model;
dx = rho_x*dx(-1)+e_x;
dy = rho_y*dy(-1)+e_y;
x = x(-1)+dx;
y = y(-1)+dy;
end;
estimated_params;
rho_x,NORMAL_PDF,0.5,0.1;
rho_y,NORMAL_PDF,-0.3,0.1;
stderr e_x,INV_GAMMA_PDF,0.01,inf;
stderr e_y,INV_GAMMA_PDF,0.01,inf;
end;
varobs x y;
options_.unit_root_vars = {'x'; 'y'};
estimation(datafile=data1,nobs=1000,mh_replic=0,load_mh_file,mode_compute=0,mode_file=mod1b_mode,lik_init=2);

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var dx dy x y;
varexo e_x e_y;
parameters rho_x rho_y;
rho_x = 0.5;
rho_y = -0.3;
model;
dx = rho_x*dx(-1)+e_x;
dy = rho_y*dy(-1)+e_y;
x = x(-1)+dx;
y = y(-1)+dy;
end;
estimated_params;
rho_x,NORMAL_PDF,0.5,0.1;
rho_y,NORMAL_PDF,-0.3,0.1;
stderr e_x,INV_GAMMA_PDF,0.01,inf;
stderr e_y,INV_GAMMA_PDF,0.01,inf;
stderr x,INV_GAMMA_PDF,0.01,inf;
stderr y,INV_GAMMA_PDF,0.01,inf;
end;
varobs x y;
options_.unit_root_vars = {'x'; 'y'};
estimation(datafile=data1,nobs=1000,mh_replic=2000,lik_init=2);

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var dx dy x y;
varexo e_x e_y;
parameters rho_x rho_y b a1 a2;
rho_x = 0.5;
rho_y = -0.3;
b = 1;
a1 = -0.1;
a2 = 0.2;
model;
dx = rho_x*dx(-1)+a1*(x(-1)-b*y(-1))+e_x;
dy = rho_y*dy(-1)+a2*(x(-1)-b*y(-1))+e_y;
x = x(-1)+dx;
y = y(-1)+dy;
end;
shocks;
var e_x; stderr 0.01;
var e_y; stderr 0.01;
end;
stoch_simul(order=1,periods=1000,irf=0,nomoments);
save data2 dx dy x y;

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var dx dy x y;
varexo e_x e_y;
parameters rho_x rho_y b a1 a2;
rho_x = 0.5;
rho_y = -0.3;
b = 1;
a1 = -0.1;
a2 = 0.2;
model;
dx = rho_x*dx(-1)+a1*(x(-1)-b*y(-1))+e_x;
dy = rho_y*dy(-1)+a2*(x(-1)-b*y(-1))+e_y;
x = x(-1)+dx;
y = y(-1)+dy;
end;
estimated_params;
rho_x,NORMAL_PDF,0.5,0.1;
rho_y,NORMAL_PDF,-0.3,0.1;
b,NORMAL_PDF,1,0.1;
a1,NORMAL_PDF,-0.1,0.1;
a2,NORMAL_PDF,0.2,0.1;
stderr e_x,INV_GAMMA_PDF,0.01,inf;
stderr e_y,INV_GAMMA_PDF,0.01,inf;
end;
varobs dx dy;
options_.unit_root_vars = {'x'; 'y'};
estimation(datafile=data2,nobs=100,mh_replic=0,lik_init=2);

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var dx dy x y;
varexo e_x e_y;
parameters rho_x rho_y b a1 a2;
rho_x = 0.5;
rho_y = -0.3;
b = 1;
a1 = -0.1;
a2 = 0.2;
model;
dx = rho_x*dx(-1)+a1*(x(-1)-b*y(-1))+e_x;
dy = rho_y*dy(-1)+a2*(x(-1)-b*y(-1))+e_y;
x = x(-1)+dx;
y = y(-1)+dy;
end;
estimated_params;
rho_x,NORMAL_PDF,0.5,0.1;
rho_y,NORMAL_PDF,-0.3,0.1;
b,NORMAL_PDF,1,0.1;
a1,NORMAL_PDF,-0.1,0.1;
a2,NORMAL_PDF,0.2,0.1;
stderr e_x,INV_GAMMA_PDF,0.01,inf;
stderr e_y,INV_GAMMA_PDF,0.01,inf;
end;
varobs x y;
options_.unit_root_vars = {'x'; 'y'};
estimation(datafile=data2,nobs=100,mh_replic=0,lik_init=2);

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var dx dy coint_err;
varexo e_x e_y;
parameters rho_x rho_y b a1 a2;
rho_x = 0.5;
rho_y = -0.3;
b = 1;
a1 = -0.1;
a2 = 0.2;
model;
dx = rho_x*dx(-1)+a1*coint_err(-1)+e_x;
dy = rho_y*dy(-1)+a2*coint_err(-1)+e_y;
coint_err = dx-b*dy+coint_err(-1);
end;
estimated_params;
rho_x,NORMAL_PDF,0.5,0.1;
rho_y,NORMAL_PDF,-0.3,0.1;
b,NORMAL_PDF,1,0.1;
a1,NORMAL_PDF,-0.1,0.1;
a2,NORMAL_PDF,0.2,0.1;
stderr e_x,INV_GAMMA_PDF,0.01,inf;
stderr e_y,INV_GAMMA_PDF,0.01,inf;
end;
varobs dx dy;
estimation(datafile=data2,nobs=100,mh_replic=0);

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// example 1 from Collard's guide to Dynare
var y, c, k, a, h, b;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b(-1) + e;
b = tau*a(-1)+rho*b(-1) + u;
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
a = 0;
b = 0;
e = 0;
u = 0;
end;
shocks;
var e; stderr 0.009;
var u; stderr 0.009;
var e, u = phi*0.009*0.009;
end;
stoch_simul(periods=2100);

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// example 2 from Collard's guide to Dynare
var y, c, k, a, h, b;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau ;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
model;
exp(c)*theta*exp(h)^(1+psi)=(1-alpha)*exp(y);
exp(k) = beta*(((exp(b)*exp(c))/(exp(b(+1))*exp(c(+1))))
*(exp(b(+1))*alpha*exp(y(+1))+(1-delta)*exp(k)));
exp(y) = exp(a)*(exp(k(-1))^alpha)*(exp(h)^(1-alpha));
exp(k) = exp(b)*(exp(y)-exp(c))+(1-delta)*exp(k(-1));
a = rho*a(-1)+tau*b(-1) + e;
b = tau*a(-1)+rho*b(-1) + u;
end;
initval;
y = 0.1;
c = -0.2;
h = -1.2;
k = 2.4;
a = 0;
b = 0;
e = 0;
u = 0;
end;
steady;
shocks;
var e = 0.009^2;
var u = 0.009^2;
end;
stoch_simul(dr_algo=1,drop=200);

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// This file replicates the estimation of the CIA model from
// Frank Schorfheide (2000) "Loss function-based evaluation of DSGE models"
// Journal of Applied Econometrics, 15, 645-670.
// the data are the ones provided on Schorfheide's web site with the programs.
// http://www.econ.upenn.edu/~schorf/programs/dsgesel.ZIP
// You need to have fsdat.m in the same directory as this file.
// This file replicates:
// -the posterior mode as computed by Frank's Gauss programs
// -the parameter mean posterior estimates reported in the paper
// -the model probability (harmonic mean) reported in the paper
// This file was tested with dyn_mat_test_0218.zip
// the smooth shocks are probably stil buggy
//
// The equations are taken from J. Nason and T. Cogley (1994)
// "Testing the implications of long-run neutrality for monetary business
// cycle models" Journal of Applied Econometrics, 9, S37-S70.
// Note that there is an initial minus sign missing in equation (A1), p. S63.
//
// Michel Juillard, February 2004
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;
initval;
k = 6;
m = mst;
P = 2.25;
c = 0.45;
e = 1;
W = 4;
R = 1.02;
d = 0.85;
n = 0.19;
l = 0.86;
y = 0.6;
gy_obs = exp(gam);
gp_obs = exp(-gam);
dA = exp(gam);
end;
shocks;
var e_a; stderr 0.014;
var e_m; stderr 0.005;
end;
steady;
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;
estimation(datafile=fsdat,nobs=192,loglinear,mh_replic=2000,mh_nblocks=5,mh_jscale=0.8);

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// This file replicates the estimation of the CIA model from
// Frank Schorfheide (2000) "Loss function-based evaluation of DSGE models"
// Journal of Applied Econometrics, 15, 645-670.
// the data are the ones provided on Schorfheide's web site with the programs.
// http://www.econ.upenn.edu/~schorf/programs/dsgesel.ZIP
// You need to have fsdat.m in the same directory as this file.
// This file replicates:
// -the posterior mode as computed by Frank's Gauss programs
// -the parameter mean posterior estimates reported in the paper
// -the model probability (harmonic mean) reported in the paper
// This file was tested with dyn_mat_test_0218.zip
// the smooth shocks are probably stil buggy
//
// The equations are taken from J. Nason and T. Cogley (1994)
// "Testing the implications of long-run neutrality for monetary business
// cycle models" Journal of Applied Econometrics, 9, S37-S70.
// Note that there is an initial minus sign missing in equation (A1), p. S63.
//
// Michel Juillard, February 2004
var m P c e W R k d n l gy_obs gp_obs Y_obs P_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;
Y_obs/Y_obs(-1) = gy_obs;
P_obs/P_obs(-1) = gp_obs;
end;
initval;
k = 6;
m = mst;
P = 2.25;
c = 0.45;
e = 1;
W = 4;
R = 1.02;
d = 0.85;
n = 0.19;
l = 0.86;
y = 0.6;
gy_obs = exp(gam);
gp_obs = exp(-gam);
dA = exp(gam);
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 P_obs Y_obs;
observation_trends;
P_obs (log(exp(gam)/mst));
Y_obs (gam);
end;
options_.unit_root_vars = {'P_obs'; 'Y_obs'};
//stoch_simul(order=1,nomoments,irf=0);
estimation(datafile=fsdat,nobs=192,loglinear,mh_replic=5000,mh_nblocks=10,mh_drop=0.45,lik_init=2);

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% computes the steady state of fs2000 analyticaly
% largely inspired by the program of F. Schorfheide
function [ys,check] = fs2000a_steadystate(junk,ys)
global alp bet gam mst rho psi del;
check = 0;
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;
P_obs = 1;
Y_obs = 1;
ys =[
c
d
dA
e
gp_obs
gy_obs
k
l
m
n
p
P_obs
r
w
y
Y_obs
];

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@ -0,0 +1,210 @@
data_q = [
18.02 1474.5 150.2
17.94 1538.2 150.9
18.01 1584.5 151.4
18.42 1644.1 152
18.73 1678.6 152.7
19.46 1693.1 153.3
19.55 1724 153.9
19.56 1758.2 154.7
19.79 1760.6 155.4
19.77 1779.2 156
19.82 1778.8 156.6
20.03 1790.9 157.3
20.12 1846 158
20.1 1882.6 158.6
20.14 1897.3 159.2
20.22 1887.4 160
20.27 1858.2 160.7
20.34 1849.9 161.4
20.39 1848.5 162
20.42 1868.9 162.8
20.47 1905.6 163.6
20.56 1959.6 164.3
20.62 1994.4 164.9
20.78 2020.1 165.7
21 2030.5 166.5
21.2 2023.6 167.2
21.33 2037.7 167.9
21.62 2033.4 168.7
21.71 2066.2 169.5
22.01 2077.5 170.2
22.15 2071.9 170.9
22.27 2094 171.7
22.29 2070.8 172.5
22.56 2012.6 173.1
22.64 2024.7 173.8
22.77 2072.3 174.5
22.88 2120.6 175.3
22.92 2165 176.045
22.91 2223.3 176.727
22.94 2221.4 177.481
23.03 2230.95 178.268
23.13 2279.22 179.694
23.22 2265.48 180.335
23.32 2268.29 181.094
23.4 2238.57 181.915
23.45 2251.68 182.634
23.51 2292.02 183.337
23.56 2332.61 184.103
23.63 2381.01 184.894
23.75 2422.59 185.553
23.81 2448.01 186.203
23.87 2471.86 186.926
23.94 2476.67 187.68
24 2508.7 188.299
24.07 2538.05 188.906
24.12 2586.26 189.631
24.29 2604.62 190.362
24.35 2666.69 190.954
24.41 2697.54 191.56
24.52 2729.63 192.256
24.64 2739.75 192.938
24.77 2808.88 193.467
24.88 2846.34 193.994
25.01 2898.79 194.647
25.17 2970.48 195.279
25.32 3042.35 195.763
25.53 3055.53 196.277
25.79 3076.51 196.877
26.02 3102.36 197.481
26.14 3127.15 197.967
26.31 3129.53 198.455
26.6 3154.19 199.012
26.9 3177.98 199.572
27.21 3236.18 199.995
27.49 3292.07 200.452
27.75 3316.11 200.997
28.12 3331.22 201.538
28.39 3381.86 201.955
28.73 3390.23 202.419
29.14 3409.65 202.986
29.51 3392.6 203.584
29.94 3386.49 204.086
30.36 3391.61 204.721
30.61 3422.95 205.419
31.02 3389.36 206.13
31.5 3481.4 206.763
31.93 3500.95 207.362
32.27 3523.8 208
32.54 3533.79 208.642
33.02 3604.73 209.142
33.2 3687.9 209.637
33.49 3726.18 210.181
33.95 3790.44 210.737
34.36 3892.22 211.192
34.94 3919.01 211.663
35.61 3907.08 212.191
36.29 3947.11 212.708
37.01 3908.15 213.144
37.79 3922.57 213.602
38.96 3879.98 214.147
40.13 3854.13 214.7
41.05 3800.93 215.135
41.66 3835.21 215.652
42.41 3907.02 216.289
43.19 3952.48 216.848
43.69 4044.59 217.314
44.15 4072.19 217.776
44.77 4088.49 218.338
45.57 4126.39 218.917
46.32 4176.28 219.427
47.07 4260.08 219.956
47.66 4329.46 220.573
48.63 4328.33 221.201
49.42 4345.51 221.719
50.41 4510.73 222.281
51.27 4552.14 222.933
52.35 4603.65 223.583
53.51 4605.65 224.152
54.65 4615.64 224.737
55.82 4644.93 225.418
56.92 4656.23 226.117
58.18 4678.96 226.754
59.55 4566.62 227.389
61.01 4562.25 228.07
62.59 4651.86 228.689
64.15 4739.16 229.155
65.37 4696.82 229.674
66.65 4753.02 230.301
67.87 4693.76 230.903
68.86 4615.89 231.395
69.72 4634.88 231.906
70.66 4612.08 232.498
71.44 4618.26 233.074
72.08 4662.97 233.546
72.83 4763.57 234.028
73.48 4849 234.603
74.19 4939.23 235.153
75.02 5053.56 235.605
75.58 5132.87 236.082
76.25 5170.34 236.657
76.81 5203.68 237.232
77.63 5257.26 237.673
78.25 5283.73 238.176
78.76 5359.6 238.789
79.45 5393.57 239.387
79.81 5460.83 239.861
80.22 5466.95 240.368
80.84 5496.29 240.962
81.45 5526.77 241.539
82.09 5561.8 242.009
82.68 5618 242.52
83.33 5667.39 243.12
84.09 5750.57 243.721
84.67 5785.29 244.208
85.56 5844.05 244.716
86.66 5878.7 245.354
87.44 5952.83 245.966
88.45 6010.96 246.46
89.39 6055.61 247.017
90.13 6087.96 247.698
90.88 6093.51 248.374
92 6152.59 248.928
93.18 6171.57 249.564
94.14 6142.1 250.299
95.11 6078.96 251.031
96.27 6047.49 251.65
97 6074.66 252.295
97.7 6090.14 253.033
98.31 6105.25 253.743
99.13 6175.69 254.338
99.79 6214.22 255.032
100.17 6260.74 255.815
100.88 6327.12 256.543
101.84 6327.93 257.151
102.35 6359.9 257.785
102.83 6393.5 258.516
103.51 6476.86 259.191
104.13 6524.5 259.738
104.71 6600.31 260.351
105.39 6629.47 261.04
106.09 6688.61 261.692
106.75 6717.46 262.236
107.24 6724.2 262.847
107.75 6779.53 263.527
108.29 6825.8 264.169
108.91 6882 264.681
109.24 6983.91 265.258
109.74 7020 265.887
110.23 7093.12 266.491
111 7166.68 266.987
111.43 7236.5 267.545
111.76 7311.24 268.171
112.08 7364.63 268.815
];
%GDPD GDPQ GPOP
series = zeros(193,2);
series(:,2) = data_q(:,1);
series(:,1) = 1000*data_q(:,2)./data_q(:,3);
Y_obs = series(:,1);
P_obs = series(:,2);
series = series(2:193,:)./series(1:192,:);
gy_obs = series(:,1);
gp_obs = series(:,2);
ti = [1950:0.25:1997.75];

4
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@ -0,0 +1,4 @@
function test(a,b,n)
if max(max(abs(a)-abs(b))) > 1e-5
error(['Test error in test ' int2str(n)])
end

100
tests/ls2003/data_ca1.m Normal file
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@ -0,0 +1,100 @@
data = [0.928467646476 11.8716889412 20 0.418037507392 0.227382377518 ...
-0.705994063083 11.7522582094 21.25 1.09254424511 -1.29488274994 ...
-0.511895351926 9.68144025625 17.25 -1.66150408407 0.331508393098 ...
-0.990955971267 10.0890781236 17 1.43016275252 -2.43589670141 ...
-0.981233061806 12.1094840679 18.25 2.91293288733 -0.790246576864 ...
-0.882182844512 8.54559460406 15 0.419579139481 0.358729719566 ...
-0.930893002836 6.19238374422 12.5 -1.48847457959 0.739779938797 ...
1.53158206947 2.76544271886 11.5 -0.336216769682 0.455559918769 ...
2.2659052834 5.47418162513 11 0.306436789767 -0.0707985731221 ...
1.05419803797 6.35698426189 11 0.140700250477 0.620401487202 ...
1.20161076793 3.4253301593 11 0.461296492351 0.14354323987 ...
1.73934077971 4.70926070322 11.5 1.35798282982 0.38564694435 ...
1.71735262584 3.54232079749 12.5 2.9097529155 -0.804308583301 ...
0.426343657844 3.32719108897 13 1.64214862652 -1.18214664701 ...
1.67751812324 2.93444727338 11.25 0.344434910651 -1.6529373719 ...
1.37013301099 4.72303361923 11.75 2.61511526582 0.327684243041 ...
0.281231073781 4.4893853071 10.5 1.17043449257 1.12855106649 ...
1.53638992834 3.7325309699 10.25 -0.683947046728 0.11943538737 ...
1.68081431462 3.34729969129 10 1.41159342106 -1.59065680853 ...
-0.343321601133 5.05563513564 12 1.75117366498 -2.40127764642 ...
0.873415608666 3.2779996255 10.25 -1.39895866711 0.0971444398216 ...
0.26399696544 4.78229419828 9.75 0.0914692438124 0.299310457612 ...
-0.562233624818 3.88598638237 9.75 -0.0505384765105 0.332826708151 ...
2.15161914936 3.84859710132 8.75 -3.44811080489 0.789138678784 ...
1.2345093726 5.62225030942 9.5 -0.366945407434 2.32974981198 ...
1.62554967459 4.24667132831 10 -0.800958371402 0.0293183770935 ...
1.33035402527 2.75248979249 9.75 -0.855723113225 0.852493939813 ...
1.52078814077 3.53415985826 9.75 -3.37963469203 -1.05133958119 ...
1.16704983697 4.92754079464 10.75 -3.0142303324 0.459907431978 ...
0.277213572101 4.55532133037 11.75 -0.851995599415 2.03242034852 ...
0.842215068977 3.11164509647 12.25 -1.08290421696 0.014323281961 ...
1.05325028606 4.92882647578 13.5 -1.1953883867 0.706764750654 ...
0.453051253568 6.82998950103 13.5 0.111803656462 0.088462593153 ...
0.199885995525 5.82643354662 13.5 -0.920501518421 -0.26504958666 ...
0.137907999624 2.66076369132 13.5 -1.17122929812 -0.995642430514 ...
0.721949686709 5.70497876823 14.25 1.19378169018 -1.10644839651 ...
-0.418465249225 3.75861110232 14.75 -1.03131674824 0.188507675831 ...
-0.644028342116 4.15104788154 13.75 -1.48911756546 0.204560913792 ...
-0.848213852668 5.65580324027 12.75 0.677011703877 -0.849628054542 ...
-1.51954076928 11.4866911266 11.25 -0.446024680774 -0.456342350765 ...
0.265275055215 2.85472749592 9.75 -0.598778202436 -0.907311640831 ...
0.356162529063 2.29614015658 9.5 -0.46820788432 -1.22130883441 ...
0.368308864363 -0.539083504685 8 -0.781333991956 0.374007246518 ...
-0.145751412732 1.61507621789 8.25 3.68291932628 1.32438399845 ...
0.285457283664 2.14334055993 7 1.42819405379 -0.00818660844123 ...
0.372390129412 1.60000213334 6.25 0.626106424052 -0.10136772765 ...
0.382720203063 1.72614243263 7.25 4.89631941021 -1.10060711916 ...
0.737957515573 2.90430582851 6 -0.0422721010314 0.4178952497 ...
0.649532581668 0.657135682543 6 0.692066153971 0.422299120276 ...
0.627159201987 1.70352689913 5.75 2.62066711305 -1.29237304034 ...
0.905441299817 1.95663197267 5.5 1.5949697565 -0.27115830703 ...
1.49322577898 -2.08741765309 6.25 1.23027694802 0.418336889527 ...
1.48750731567 -1.57274121871 8 3.01660550994 -0.893958254365 ...
1.39783858087 2.22623066426 7 -0.80842319214 1.47625453886 ...
0.89274836317 1.30378081742 8 -0.249485058661 0.159871204185 ...
0.920652246088 4.1437741965 9.75 2.8204453623 0.178149239655 ...
-0.00264276644799 3.07989972052 8.75 -2.56342461535 2.105998353 ...
0.0198190461681 0.766283759256 8 -1.15838865989 1.56888883418 ...
0.440050515311 0.127570085801 7.5 0.0400753569995 0.028914333532 ...
0.129536637901 1.78174141526 6.75 0.959943962785 0.307781224401 ...
0.398549827172 3.03606770667 6.5 -0.340209794742 0.100979469478 ...
1.17174775425 0.629625188037 5.75 0.403003686814 0.902394579377 ...
0.991163981251 2.50862910684 4.75 -1.44963996982 1.16150986945 ...
0.967603566096 2.12003739013 4.75 0.610846030775 -0.889994896068 ...
1.14689383604 1.24185011459 4.75 2.01098091308 -1.73846431001 ...
1.32593824054 0.990713820685 4.75 -0.0955142989332 -0.0369257308362 ...
0.861135002644 -0.24744943605 6 1.72793107135 -0.691506789639 ...
1.26870850151 2.09844764887 6.5 1.50720217572 -1.31399187077 ...
0.260364987715 1.10650139716 6.5 1.13659047496 0.0720441664643 ...
1.09731242214 0.490796381346 7.25 4.59123894147 -2.14073070763 ...
1.63792841781 0.612652594286 6.75 1.79604605035 -0.644363995357 ...
1.48465576034 0.978295808687 6.75 -2.00753620902 1.39437534964 ...
1.0987608663 4.25212569087 6.25 -2.58901196498 2.56054320803 ...
1.42592178132 2.76984518311 6.25 0.888195752358 1.03114549274 ...
1.52958239462 1.31795955491 6.5 -0.902907564082 -0.0952198893776 ...
1.0170168994 2.14733589918 7 -1.3054866978 2.68803738466 ...
0.723253652257 3.43552889347 7.5 1.8213700853 0.592593586195 ...
1.24720806008 3.87383806577 7.5 0.0522300654168 0.988871238698 ...
0.482531471239 2.67793287032 7.5 2.9693944293 -0.108591166081 ...
0.154056100439 0.927269031704 6.75 0.119222057561 3.30489209451 ...
0.0694865769274 6.65916526788 6.25 0.889014476084 -2.83976849035 ...
-0.121267434867 0.341442615696 5.25 0.323053239216 -3.49289229012 ...
0.726473690375 -3.5423730964 4 2.19149290449 -3.20855054004 ...
1.39271709108 2.63121085718 3.75 0.88406577736 0.75622580197 ...
1.07502077727 5.88578836799 4.25 -2.55088273352 2.89018116374 ...
0.759049251607 4.24703604223 4.5 0.575687665685 -0.388292506167 ...
];
data = reshape(data,5,86)';
y_obs = data(:,1);
pie_obs = data(:,2);
R_obs = data(:,3);
de = data(:,4);
dq = data(:,5);
%Country: Canada
%Sample Range: 1981:2 to 2002:3
%Observations: 86
%Variables: Real GDP Growth [%], Inflation [annualized %], Nom Rate [%],
% Exchange Rate Change [%], Terms of Trade Change [%]

65
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var y y_s R pie dq pie_s de A y_obs pie_obs R_obs;
varexo e_R e_q e_ys e_pies e_A;
parameters psi1 psi2 psi3 rho_R tau alpha rr k rho_q rho_A rho_ys rho_pies;
psi1 = 1.54;
psi2 = 0.25;
psi3 = 0.25;
rho_R = 0.5;
alpha = 0.3;
rr = 2.51;
k = 0.5;
tau = 0.5;
rho_q = 0.4;
rho_A = 0.2;
rho_ys = 0.9;
rho_pies = 0.7;
model(linear);
y = y(+1) - (tau +alpha*(2-alpha)*(1-tau))*(R-pie(+1))-alpha*(tau +alpha*(2-alpha)*(1-tau))*dq(+1) + alpha*(2-alpha)*((1-tau)/tau)*(y_s-y_s(+1))-A(+1);
pie = exp(-rr/400)*pie(+1)+alpha*exp(-rr/400)*dq(+1)-alpha*dq+(k/(tau+alpha*(2-alpha)*(1-tau)))*y+alpha*(2-alpha)*(1-tau)/(tau*(tau+alpha*(2-alpha)*(1-tau)))*y_s;
pie = de+(1-alpha)*dq+pie_s;
R = rho_R*R(-1)+(1-rho_R)*(psi1*pie+psi2*(y+alpha*(2-alpha)*((1-tau)/tau)*y_s)+psi3*de)+e_R;
dq = rho_q*dq(-1)+e_q;
y_s = rho_ys*y_s(-1)+e_ys;
pie_s = rho_pies*pie_s(-1)+e_pies;
A = rho_A*A(-1)+e_A;
y_obs = y-y(-1)+A;
pie_obs = 4*pie;
R_obs = 4*R;
end;
shocks;
var e_R = 1.25^2;
var e_q = 2.5^2;
var e_A = 1.89;
var e_ys = 1.89;
var e_pies = 1.89;
end;
varobs y_obs R_obs pie_obs dq de;
estimated_params;
psi1 , gamma_pdf,1.5,0.5;
psi2 , gamma_pdf,0.25,0.125;
psi3 , gamma_pdf,0.25,0.125;
rho_R ,beta_pdf,0.5,0.2;
alpha ,beta_pdf,0.3,0.1;
rr ,gamma_pdf,2.5,1;
k , gamma_pdf,0.5,0.25;
tau ,gamma_pdf,0.5,0.2;
rho_q ,beta_pdf,0.4,0.2;
rho_A ,beta_pdf,0.5,0.2;
rho_ys ,beta_pdf,0.8,0.1;
rho_pies,beta_pdf,0.7,0.15;
stderr e_R,inv_gamma_pdf,1.2533,0.6551;
stderr e_q,inv_gamma_pdf,2.5066,1.3103;
stderr e_A,inv_gamma_pdf,1.2533,0.6551;
stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
stderr e_pies,inv_gamma_pdf,1.88,0.9827;
end;
estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_nblocks=10,prefilter=1,mh_jscale=0.5,mh_replic=0);

65
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var y y_s R pie dq pie_s de A y_obs pie_obs R_obs;
varexo e_R e_q e_ys e_pies e_A;
parameters psi1 psi2 psi3 rho_R tau alpha rr k rho_q rho_A rho_ys rho_pies;
psi1 = 1.54;
psi2 = 0.25;
psi3 = 0.25;
rho_R = 0.5;
alpha = 0.3;
rr = 2.51;
k = 0.5;
tau = 0.5;
rho_q = 0.4;
rho_A = 0.2;
rho_ys = 0.9;
rho_pies = 0.7;
model(linear);
y = y(+1) - (tau +alpha*(2-alpha)*(1-tau))*(R-pie(+1))-alpha*(tau +alpha*(2-alpha)*(1-tau))*dq(+1) + alpha*(2-alpha)*((1-tau)/tau)*(y_s-y_s(+1))-A(+1);
pie = exp(-rr/400)*pie(+1)+alpha*exp(-rr/400)*dq(+1)-alpha*dq+(k/(tau+alpha*(2-alpha)*(1-tau)))*y+alpha*(2-alpha)*(1-tau)/(tau*(tau+alpha*(2-alpha)*(1-tau)))*y_s;
pie = de+(1-alpha)*dq+pie_s;
R = rho_R*R(-1)+(1-rho_R)*(psi1*pie+psi2*(y+alpha*(2-alpha)*((1-tau)/tau)*y_s)+psi3*de)+e_R;
dq = rho_q*dq(-1)+e_q;
y_s = rho_ys*y_s(-1)+e_ys;
pie_s = rho_pies*pie_s(-1)+e_pies;
A = rho_A*A(-1)+e_A;
y_obs = y-y(-1)+A;
pie_obs = 4*pie;
R_obs = 4*R;
end;
shocks;
var e_R = 1.25^2;
var e_q = 2.5^2;
var e_A = 1.89;
var e_ys = 1.89;
var e_pies = 1.89;
end;
varobs y_obs R_obs pie_obs dq de;
estimated_params;
psi1 , gamma_pdf,1.5,0.5;
psi2 , gamma_pdf,0.25,0.125;
psi3 , gamma_pdf,0.25,0.125;
rho_R ,beta_pdf,0.5,0.2;
alpha ,beta_pdf,0.3,0.1;
rr ,gamma_pdf,2.5,1;
k , gamma_pdf,0.5,0.25;
tau ,gamma_pdf,0.5,0.2;
rho_q ,beta_pdf,0.4,0.2;
rho_A ,beta_pdf,0.5,0.2;
rho_ys ,beta_pdf,0.8,0.1;
rho_pies,beta_pdf,0.7,0.15;
stderr e_R,inv_gamma_pdf,1.2533,0.6551;
stderr e_q,inv_gamma_pdf,2.5066,1.3103;
stderr e_A,inv_gamma_pdf,1.2533,0.6551;
stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
stderr e_pies,inv_gamma_pdf,1.88,0.9827;
end;
estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_nblocks=10,prefilter=1,mh_jscale=0.5,mh_replic=0);

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/sgu_ex1.log/1.1.2.1/Sun Feb 6 15:45:32 2005//Tv3_03
/sgu_ex1.m/1.1.2.1/Sun Feb 6 15:45:32 2005//Tv3_03
/sgu_ex1.mat/1.1.2.1/Sun Feb 6 15:45:32 2005//Tv3_03
/sgu_ex1.mod/1.1.2.1/Sun Feb 6 15:45:32 2005//Tv3_03
/sgu_ex1_ff.m/1.1.2.1/Sun Feb 6 15:45:32 2005//Tv3_03
/sgu_ex1_fff.m/1.1.2.1/Sun Feb 6 15:45:32 2005//Tv3_03
D

1
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dynare_test/tests/objectives

1
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:ext:pythie.cepremap.cnrs.fr/var/lib/cvs

1
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@ -0,0 +1 @@
Tv3_03

15
tests/objectives/sgu_ex1.log Normal file
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MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS
Variables e
e 1.000000
POLICY AND TRANSITION FUNCTIONS
k a c
Constant -1.552215 0 -0.969516
(correction) 0.241022 0 -0.096072
k(-1) 0.419109 0 0.252523
e 1.397031 1.000000 0.841743
k(-1)k(-1) -0.003501 0 -0.002559
e e -0.038899 0 -0.028434
k(-1) e -0.023340 0 -0.017061

98
tests/objectives/sgu_ex1.m Normal file
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clear all
global scalv_ ex_ recur_ recurs_ ys_ y_ exe_ lgy_ lgx_ lgr_ dsmpl_ endval_
...
global endo_nbr exo_nbr iy_ ykmin_ ykmax_ xkmin_ xkmax_ zkmin_ zkmax_ iter_
...
global dynatol_ slowc_ maxit_ valf_ ys0_ recurs0_ timing_ ct_ gstep_ Sigma_e_ fname_ lgx_orig_ord_
dsmpl_=0;
dynatol_=0.00001;
maxit_=10;
slowc_=1;
timing_=0;
ct_=0;
gstep_=1e-2;
endval_=0;rplottype_=0;
fname_ = 'sgu_ex1';
logname_ = 'sgu_ex1.log';
diary off;
warning off;
delete sgu_ex1.log;
warning on;
warning backtrace;
diary sgu_ex1.log;
iter_ = 20000;
global alpha beta delta gamma rho
beta = 0.95;
delta = 1;
alpha = 0.3;
rho = 0;
gamma = 2;
lgy_ = 'a';
lgy_ = str2mat(lgy_,'c');
lgy_ = str2mat(lgy_,'k');
lgx_ = 'e';
lgx_orig_ord_ = [1];
endo_nbr = 3;
exo_nbr = 1;
recur_nbr = 0;
iy_ = [ 1 0 2];
temp = [ 3 4 5];
iy_ = [ iy_ ; temp ];
temp = [ 6 7 0];
iy_ = [ iy_ ; temp ];
ykmin_ = 1;
ykmax_ = 1;
xkmin_ = 0;
xkmax_ = 0;
zkmin_ = 0;
zkmax_ = 0;
% INITVAL
valf_ = 0;
endval_=0;
ys_ = zeros(3,1);
exe_ = zeros(1,1);
ys0_ = 0;
ex0_ = 0;
recurs0_ = 0;
ys_(3)=0;
ys_(2)=0;
ys_(1)=0;
exe_(1)=0;
if exo_nbr > 0;
ex_ =ones(iter_ + xkmin_ + xkmax_,1) * exe_';
end;
Sigma_e_ = 1;
var_list_ = [];
options.ar = 0;
options.dr_algo = 0;
options.simul_algo = 0;
options.nocorr = 1;
options.drop = 100;
options.linear = 0;
options.nofunctions = 0;
options.nomoments = 1;
options.irf = 0;
options.order = 2;
options.replic = 0;
stoch_simul(options,var_list_);
global dr_
dr_obj_ = dr_;
save sgu_ex1 dr_obj_;
diary off

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33
tests/objectives/sgu_ex1.mod Normal file
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periods 20000;
var c k a;
varexo e;
parameters alpha beta delta gamma rho;
beta = 0.95;
delta = 1;
alpha = 0.3;
rho = 0;
gamma = 2;
model;
exp(c) + exp(k) = (1-delta) * exp(k(-1)) + exp(a) * exp(k(-1))^alpha;
exp(c)^(-gamma) = beta * exp(c(+1))^(-gamma) * (exp(a(+1)) * alpha * exp(k)^(alpha-1) + 1 - delta);
a = rho * a(-1) + e;
end;
initval;
k=0;
c=0;
a=0;
e=0;
end;
Sigma_e_ = 1;
stoch_simul(nomoments,irf=0,nocorr,ar=0);
global dr_
dr_obj_ = dr_;
save sgu_ex1 dr_obj_;

11
tests/objectives/sgu_ex1_ff.m Normal file
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function z=sgu_ex1_ff(y)
z=zeros(3,1);
global ex_ it_ recur_
global alpha beta delta gamma rho
z(1) = exp(y(4))+exp(y(5)) -((1-delta)*exp(y(2))+exp(y(3))*exp(y(2))^alpha) ...
;
z(2) = exp(y(4))^(-gamma) -(beta*exp(y(7))^(-gamma)*(exp(y(6))*alpha*exp( ...
y(5))^(alpha-1)+1-delta));
z(3) = y(3) -(rho*y(1)+ex_(it_-1,1));

11
tests/objectives/sgu_ex1_fff.m Normal file
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function z=sgu_ex1_fff(y)
z=zeros(3,1);
global ex_ it_ recur_
global alpha beta delta gamma rho
z(1) = exp(y(2))+exp(y(3)) -((1-delta)*exp(y(3))+exp(y(1))*exp(y(3))^alpha) ...
;
z(2) = exp(y(2))^(-gamma) -(beta*exp(y(2))^(-gamma)*(exp(y(1))*alpha*exp( ...
y(3))^(alpha-1)+1-delta));
z(3) = y(1) -(rho*y(1)+ex_(it_-1,1));

5
tests/pi2004/idata.m Normal file
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@ -0,0 +1,5 @@
load ych.dat;
data = log(ych);
oy = data(:,1);
oc = data(:,2);
oh = data(:,3);

90
tests/pi2004/ireland.mod Normal file
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@ -0,0 +1,90 @@
var y a k c i h eoy eoc eoh oy oc oh;
varexo e eeoy eeoc eeoh;
parameters theta rho eta gam bet delta aa r11 r12 r13 r21 r22 r23 r31 r32 r33 scy shc shy;
bet = 0.99;
delta = 0.025;
theta = 0.2;
rho = 0.9959;
eta = 1.0051;
gam = 0.0045;
aa = 1.8;
r11 = 0.99;
r12 = 0;
r13 = 0;
r21 = 0;
r22 = 0.99;
r23 = 0;
r31 = 0;
r32 = 0;
r33 = 0.99;
scy = 0.0040;
shy = 0.0015;
shc = 0.0010;
model;
exp(y) = exp(a)*exp(k(-1))^theta*exp(h)^(1-theta);
a = (1-rho)*aa+rho*a(-1)+e;
exp(y) = exp(c) + exp(i);
eta*exp(k) = (1-delta)*exp(k(-1))+exp(i);
gam*exp(c)*exp(h) = (1-theta)*exp(y);
eta/exp(c) = bet*(1/exp(c(+1)))*(theta*(exp(y(+1))/exp(k))+1-delta);
eoy = r11*eoy(-1) + r12*eoc(-1) + r13*eoh(-1) + eeoy;
eoc = r21*eoy(-1) + r22*eoc(-1) + r23*eoh(-1) + scy*eeoy+eeoc;
eoh = r31*eoy(-1) + r32*eoc(-1) + r33*eoh(-1) + shy*eeoy+shc*eeoc+eeoh;
oy = y + eoy;
oc = c + eoc;
oh = h + eoh;
end;
initval;
a = 1.7;
y = 8;
c = 8;
k = 10;
i = 5;
h = 4;
eoy = 0;
eoc = 0;
eoh = 0;
oy = y;
oc = c;
oh = h;
end;
steady;
check;
estimated_params;
theta , 0.22, 0.1, 0.5;
rho , 0.99, 0.7, 0.9999;
eta , 1.0051, 1, 1.03;
gam , 0.0045, 0.001, 0.01;
aa , 1.8, 0.1, 4;
r11 , 1.4187, -2, 2;
r12 , 0.2251, -2, 2;
r13 , -0.4441, -2, 2;
r21 , 0.0935, -2, 2;
r22 , 1.0236, -2, 2;
r23 , -0.0908, -2, 2;
r31 , 0.7775, -2, 2;
r32 , 0.3706, -2, 2;
r33 , 0.2398, -2, 2;
scy , 0.0040, -2, 2;
shy , 0.0015, -2, 2;
shc , 0.0010, -2, 2;
stderr e , 0.0056, 0, 0.2;
stderr eeoy , 0.0070, 0, 0.1;
stderr eeoc , 0.0069, 0, 0.1;
stderr eeoh , 0.0018, 0, 0.1;
end;
varobs oy oc oh;
observation_trends;
oy (log(eta));
oc (log(eta));
end;
estimation(datafile=idata,mode_compute=1,nograph);

90
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var y a k c i h eoy eoc eoh oy oc oh;
varexo e eeoy eeoc eeoh;
parameters theta rho eta gam bet delta aa r11 r12 r13 r21 r22 r23 r31 r32 r33 scy shc shy;
bet = 0.99;
delta = 0.025;
theta = 0.2;
rho = 0.9959;
eta = 1.0051;
gam = 0.0045;
aa = 1.8;
r11 = 0.99;
r12 = 0;
r13 = 0;
r21 = 0;
r22 = 0.99;
r23 = 0;
r31 = 0;
r32 = 0;
r33 = 0.99;
scy = 0.0040;
shy = 0.0015;
shc = 0.0010;
model;
exp(y) = exp(a)*exp(k(-1))^theta*exp(h)^(1-theta);
a = (1-rho)*aa+rho*a(-1)+e;
exp(y) = exp(c) + exp(i);
eta*exp(k) = (1-delta)*exp(k(-1))+exp(i);
gam*exp(c)*exp(h) = (1-theta)*exp(y);
eta/exp(c) = bet*(1/exp(c(+1)))*(theta*(exp(y(+1))/exp(k))+1-delta);
eoy = r11*eoy(-1) + r12*eoc(-1) + r13*eoh(-1) + eeoy;
eoc = r21*eoy(-1) + r22*eoc(-1) + r23*eoh(-1) + scy*eeoy+eeoc;
eoh = r31*eoy(-1) + r32*eoc(-1) + r33*eoh(-1) + shy*eeoy+shc*eeoc+eeoh;
oy = y + eoy;
oc = c + eoc;
oh = h + eoh;
end;
initval;
a = 6;
y = 8;
c = 7;
k = 10;
i = 5;
h = 4;
eoy = 0;
eoc = 0;
eoh = 0;
oy = y;
oc = c;
oh = h;
end;
steady;
check;
estimated_params;
theta , 0.22;
rho , 0.99;
eta , 1.0051;
gam , 0.0045;
aa , 1.8;
r11 , 1.4187;
r12 , 0.2251;
r13 , -0.4441;
r21 , 0.0935;
r22 , 1.0236;
r23 , -0.0908;
r31 , 0.7775;
r32 , 0.3706;
r33 , 0.2398;
scy , 0.0040;
shy , 0.0015;
shc , 0.0010;
stderr e , 0.0055;
stderr eeoy , 0.0072;
stderr eeoc , 0.0057;
stderr eeoh , 0;
end;
varobs oy oc oh;
observation_trends;
oy (log(eta));
oc (log(eta));
end;
estimation(datafile=idata,nograph);

218
tests/pi2004/ych.dat Normal file
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@ -0,0 +1,218 @@
2912.874 2402.117 198.8318
2959.229 2423.837 197.3532
2955.961 2420.605 198.6
2944.613 2436.721 196.7741
2865.54 2435.214 192.1405
2837.352 2466.823 187.9169
2866.923 2465.011 185.2876
2869.69 2492.395 182.3583
3000.477 2527.61 183.9728
3085.831 2561.171 189.8728
3255.871 2686.503 196.8083
3261.025 2613.773 200.6933
3261.223 2681.19 204.7635
3206.972 2610.838 206.4334
3190.085 2639.831 205.2288
3153.084 2650.442 204.8585
3168.886 2654.884 207.0878
3173.132 2702.447 205.2592
3199.558 2706.406 206.3172
3320.152 2792.021 211.0694
3333.583 2800.407 211.3402
3346.44 2812.085 211.4742
3319.499 2799.617 209.1935
3248.271 2771.542 205.3107
3243.519 2772.147 200.5438
3268.486 2799.347 198.4387
3321.089 2829.358 196.7325
3391.751 2878.587 198.3282
3498.798 2932.503 201.0089
3576.754 2976.939 204.5467
3609.954 3003.859 206.0148
3649.965 3032.826 207.8803
3625.207 3030.321 208.5925
3618.86 3032.152 207.818
3608.703 3030.239 205.7291
3633.863 3063.106 207.7698
3634.522 3075.089 207.3511
3628.888 3071.301 205.2741
3654.03 3085.679 203.4572
3594.76 3076.223 198.9135
3503.293 3024.868 193.4752
3506.06 3040.773 189.2161
3580.923 3079.37 190.8325
3649.701 3103.69 193.5263
3722.726 3149.563 197.1324
3809.309 3187.886 200.4534
3787.083 3210.28 198.4483
3798.375 3203.989 198.1458
3865.427 3211.443 199.3042
3828.074 3242.787 198.7233
3799.687 3219.673 196.7171
3719.52 3211.349 193.664
3716.143 3198.191 190.8133
3789.954 3235.106 190.6975
3841.155 3241.368 192.1397
3910.574 3301.88 194.0709
3974.538 3330.997 194.6404
3994.347 3359.016 196.8206
4014.564 3370.705 196.2717
4017.905 3399.337 194.901
4053.971 3405.746 194.5344
4080.082 3423.602 195.9045
4131.421 3455.826 195.9157
4150.544 3470.287 195.917
4229.112 3524.024 195.5849
4272.24 3572.78 197.0242
4336.042 3623.155 197.4885
4332.184 3617.237 198.811
4465.719 3681.029 200.7368
4488.039 3707.114 201.7553
4563.691 3758.136 202.7332
4657.963 3851.754 205.0265
4769.576 3898.869 207.5881
4751.946 3898.531 208.8921
4775.072 3931.495 209.8688
4783.388 3936.299 210.2431
4770.091 3946.92 209.1094
4766.574 3984.883 207.6639
4783.135 3985.69 208.0611
4801.834 3991.937 208.7085
4894.604 4068.425 208.3597
4975.616 4118.065 209.5735
5005.671 4179.017 210.9004
5009.407 4177.453 211.3179
5086.308 4204.501 212.5445
5084.863 4213.54 213.6703
5100.858 4214.495 214.3839
5063.156 4226.537 213.5259
5036.423 4230.978 211.4778
5032.681 4228.959 208.3091
5053.799 4241.721 205.5294
4965.09 4203.845 202.0428
5116.926 4261.198 201.5087
5152.069 4275.63 201.2279
5167.576 4284.769 200.0614
5180.986 4331.279 201.1027
5237.217 4339.349 201.0968
5342.982 4395.387 202.4846
5397.077 4438.577 202.6435
5484.454 4521.399 204.6093
5599.656 4580.229 206.5316
5605.247 4551.878 207.638
5560.139 4547.278 207.561
5550.477 4512.704 208.2113
5422.633 4450.734 207.0236
5407.967 4444.172 205.7419
5341.599 4438.929 204.6589
5248.491 4344.377 200.536
5098.451 4356.942 193.2349
5127.117 4412.68 190.6
5224.673 4451.618 191.7895
5266.744 4478.207 193.5049
5416.411 4553.764 195.7526
5473.807 4575.388 195.9103
5496.508 4600.334 195.6317
5542.322 4642.48 195.9109
5620.583 4677.803 197.1447
5681.448 4680.833 199.7234
5754.575 4702.857 200.9543
5776.808 4752.082 202.373
5794.987 4757.858 202.3499
5938.233 4839.798 206.8288
5965.396 4842.542 207.8288
6002.337 4857.874 209.0832
6006.791 4867.903 210.1847
5974.557 4840.912 209.8585
5971.562 4863.66 210.2244
5937.051 4856.383 209.8079
5897.765 4830.827 208.8941
5669.422 4702.666 204.6229
5622.784 4730.812 202.7781
5752.439 4771.074 204.9687
5847.447 4774.81 206.1936
5783.328 4762.645 205.2802
5845.223 4768.572 204.8371
5751.495 4715.179 203.0329
5654.764 4729.383 200.2751
5646.146 4728.229 197.5565
5648.711 4745.201 195.2339
5635.351 4810.282 192.9487
5692.631 4841.503 192.931
5864.656 4929.513 194.9285
5984.689 4993.857 197.5937
6150.889 5061.722 201.0485
6296.581 5094.102 203.5924
6389.626 5150.168 205.4862
6433.069 5172.136 206.615
6460.989 5223.355 207.6607
6486.085 5290.602 208.5043
6538.91 5326.746 209.0396
6606.849 5410.05 209.3752
6653.043 5412.688 210.214
6664.94 5432.911 210.1493
6680.737 5476.91 209.3983
6715.628 5557.117 209.6171
6733.646 5578.244 210.0342
6748.714 5562.734 211.4856
6800.924 5617.672 212.5146
6840.249 5664.805 214.0241
6928.494 5662.19 214.9892
6947.701 5745.585 215.7109
6995.117 5771.484 216.8663
7031.88 5804.469 217.7172
7095.824 5858.734 219.2336
7145.561 5863.484 220.1136
7138.196 5874.486 220.269
7157.869 5912.841 220.1049
7154.805 5921.098 220.317
7161.057 5922.459 220.214
7161.636 5926.962 219.8513
7140.38 5935.485 218.7281
6988.206 5869.524 216.6599
6901.448 5830.479 214.2069
6921.772 5861.221 212.7658
6951.212 5865.776 212.5561
6964.494 5837.183 211.8733
7013.679 5915.408 210.9388
7101.702 5930.574 211.8948
7139.773 5958.446 211.5333
7240.504 6024.693 212.2314
7263.686 6021.066 213.0739
7309.617 6067.04 214.1464
7357.691 6122.096 215.3232
7460.728 6162.81 216.6132
7552.707 6204.697 217.5596
7666.317 6243.449 220.1539
7671.023 6273.154 221.4916
7773.38 6317.792 222.8923
7800.103 6331.551 223.6901
7801.608 6378.859 223.503
7819.518 6412.249 224.1399
7881.173 6435.988 224.4756
7942.145 6475.127 224.7463
8067.358 6527.758 226.5057
8135.065 6540.091 227.7462
8160.041 6567.023 228.9124
8246.348 6609.208 229.6994
8351.972 6625.695 231.2019
8446.197 6714.596 232.3205
8514.464 6751.037 233.8458
8708.139 6820.495 235.1582
8756.497 6905.883 235.4095
8849.165 6951.56 236.1083
8972.445 7016.94 236.9981
9053.37 7071.144 236.9439
9103.359 7150.307 237.5947
9209.004 7210.145 238.3943
9335.028 7276.898 239.4022
9429.358 7361.761 240.6652
9547.745 7400.777 240.4972
9558.757 7450.665 240.0893
9550.45 7466.543 239.5769
9462.932 7494.242 239.0031
9373.848 7502.387 237.5366
9349.589 7507.978 235.3389
9346.637 7595.472 232.4265
9459.937 7637.787 231.5627
9511.663 7656.648 231.0083

36
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var c k;
varexo x;
parameters alph gam delt bet aa;
alph=0.5;
gam=0.5;
delt=0.02;
bet=0.05;
aa=0.5;
model;
c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
end;
initval;
x = 1;
k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
c = aa*k^alph-delt*k;
end;
steady;
check;
shocks;
var x;
periods 1;
values 1.2;
end;
simul(periods=200);
rplot c;
rplot k;

37
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// check shocks on several periods
var c k;
varexo x;
parameters alph gam delt bet aa;
alph=0.5;
gam=0.5;
delt=0.02;
bet=0.05;
aa=0.5;
model;
c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
end;
initval;
x = 1;
k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
c = aa*k^alph-delt*k +1 ;
end;
steady;
check;
shocks;
var x;
periods 1:4 ;
values ([1.1, 1.2, 1.3, 1.4]') ;
end;
simul(periods=200);
rplot c;
rplot k;

39
tests/run_test.m Normal file
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function run_test()
test_files = {
'.' 'ramst';
'.' 'ramst_a';
'.' 'example1';
'.' 'example2';
'.' 't_sgu_ex1';
'arima' 'mod1';
'arima' 'mod1a';
'arima' 'mod1b';
'arima' 'mod1c';
'arima' 'mod2';
'arima' 'mod2a';
'arima' 'mod2b';
'arima' 'mod2c';
'fs2000' 'fs2000';
'fs2000' 'fs2000a';
}
results = cell(length(test_files),1);
for i=1:length(test_files)
results{i}= run_test1(test_files{i,1},test_files{i,2});
end
for i=1:length(test_files)
disp(test_files{i,2})
disp(results{i})
end
function msg=run_test1(path1,mod_file)
global options_
clear options_
old_path = pwd;
cd(path1);
msg = 'OK';
expr = ['disp(''error in ' mod_file ''');msg=lasterr;disp(msg)'];
eval(['dynare ' mod_file ' noclearall'],'eval(expr)');
cd(old_path)

40
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// example 1 from Collard's guide to Dynare
var y, c, k, a, h, b;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b(-2) + e;
b = tau*a(-1)+rho*b(-2) + u;
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
a = 0;
b = 0;
e = 0;
u = 0;
end;
Sigma_e = [ 0.000081; (phi*0.009*0.009) 0.000081];
stoch_simul(order=2,irf=0,periods=50000,simul_seed=1);

44
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// example 1 from Collard's guide to Dynare
periods 400;
var y, c, k, a, h, b, b1;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b1(-1) + e;
b = tau*a(-1)+rho*b1(-1) + u;
b1 = b(-1);
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
b1 = 0;
a = 0;
b = 0;
e = 0;
u = 0;
end;
Sigma_e = [ 0.000081; (phi*0.009*0.009) 0.000081];
stoch_simul(order=2,irf=0,simul,simul_seed=1);

44
tests/t_lag2_checka.mod Normal file
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// example 1 from Collard's guide to Dynare
periods 400;
var y, c, k, a, h, b, b1;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b1(-1) + e;
b = tau*a(-1)+rho*b1(-1) + u;
b1 = b(-1);
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
b1 = 0;
a = 0;
b = 0;
e = 0;
u = 0;
end;
Sigma_e = [ 0.000081; (phi*0.009*0.009) 0.000081];
stoch_simul(order=1,irf=0,simul,simul_seed=1);

44
tests/t_lag2a.mod Normal file
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// example 1 from Collard's guide to Dynare
periods 400;
var y, c, k, a, h, b, b1;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b1(-1) + e;
b = tau*a(-1)+rho*b1(-1) + u;
b1 = b(-1);
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
a = 0;
b = 0;
b1 = 0;
e = 0;
u = 0;
end;
Sigma_e = [ 0.000081; (phi*0.009*0.009) 0.000081];
stoch_simul(irf=0,order=1);

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// example 1 from Collard's guide to Dynare
periods 400;
var y, c, k, a, h, b, b1;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b1(-1) + e;
b = tau*a(-1)+rho*b1(-1) + u;
b1 = b(-1);
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
a = 0;
b = 0;
b1 = 0;
end;
Sigma_e = [ 0.000081; (phi*0.009*0.009) 0.000081];
stoch_simul(irf=0,periods=10000,order=2);

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// example 1 from Collard's guide to Dynare
// test options.periods
var y, c, k, a, h, b;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b(-2) + e;
b = tau*a(-1)+rho*b(-2) + u;
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
a = 0;
b = 0;
e = 0;
u = 0;
end;
Sigma_e = [ 0.000081; (phi*0.009*0.009) 0.000081];
check;
stoch_simul(order=2,irf=0,periods=400,simul_seed=1);

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var c k;
varexo x;
parameters alph gam delt bet aa;
alph=0.5;
gam=0.5;
delt=0.02;
bet=0.05;
aa=0.5;
model;
c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
end;
initval;
x = 1;
k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
c = aa*k^alph-delt*k +1 ;
end;
steady;
check;
shocks;
var x;
periods 1;
values 1.2;
end;
simul(periods=200);
rplot c;
rplot k;

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periods 20000;
var c k a;
varexo e;
parameters alpha beta delta gamma rho;
beta = 0.95;
delta = 1;
alpha = 0.3;
rho = 0;
gamma = 2;
model;
exp(c) + exp(k) = (1-delta) * exp(k(-1)) + exp(a) * exp(k(-1))^alpha;
exp(c)^(-gamma) = beta * exp(c(+1))^(-gamma) * (exp(a(+1)) * alpha * exp(k)^(alpha-1) + 1 - delta);
a = rho * a(-1) + e;
end;
initval;
k=0;
c=0;
a=0;
e=0;
end;
Sigma_e_ = 1;
stoch_simul(nomoments,nocorr,ar=0,irf=0);
global dr_
load objectives/sgu_ex1;
test(dr_.ghx,dr_obj_.ghx,1);
test(dr_.ghu,dr_obj_.ghu,2);
test(dr_.ghxx,dr_obj_.ghxx,3);
test(dr_.ghxu,dr_obj_.ghxu,4);
test(dr_.ghuu,dr_obj_.ghuu,5);
disp('TESTS OK');

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periods 200;
var y, c, k, a, h, b;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau, phi;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b(-1) + e;
b = tau*a(-1)+rho*b(-1) + u;
end;
initval;
y = 1;
c = 0.7;
h = 0.1;
k = 11;
a = 0;
b = 0;
e = 0;
u = 0;
end;
Sigma_e = [ 0.01 0.005; 0.01];
stoch_simul(irf=0);

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// test setting variance to 0
periods 400;
var y, c, k, a, h, b;
varexo e,u;
parameters beta, rho, beta, alpha, delta, theta, psi, tau;
alpha = 0.36;
rho = 0.95;
tau = 0.025;
beta = 0.99;
delta = 0.025;
psi = 0;
theta = 2.95;
phi = 0.1;
model;
c*theta*h^(1+psi)=(1-alpha)*y;
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
k = exp(b)*(y-c)+(1-delta)*k(-1);
a = rho*a(-1)+tau*b(-1) + e;
b = tau*a(-1)+rho*b(-1) + u;
end;
initval;
y = 1.08068253095672;
c = 0.80359242014163;
h = 0.29175631001732;
k = 5;
a = 0;
b = 0;
e = 0;
u = 0;
end;
Sigma_e = [ 0.000081; (phi*0.009*0.009) 0];
stoch_simul(order=1,irf=0,simul);