dynare/tests/ecb/SUR/panel_var_diff_NB_simulatio...

250 lines
8.0 KiB
Modula-2

// --+ options: json=compute +--
/* REMARK
** ------
**
** You need to have the first line on top of the mod file. The options defined on this line are passed
** to the dynare command (you can add other options, separated by spaces or commas). The option defined
** here is mandatory for the decomposition. It forces Dynare to output another representation of the
** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations.
*/
var
U2_Q_YED
U2_G_YER
U2_STN
U2_ESTN
U2_EHIC
DE_Q_YED
DE_G_YER
DE_EHIC
;
varexo
res_U2_Q_YED
res_U2_G_YER
res_U2_STN
res_U2_ESTN
res_U2_EHIC
res_DE_Q_YED
res_DE_G_YER
res_DE_EHIC
;
parameters
u2_q_yed_ecm_u2_q_yed_L1
u2_q_yed_ecm_u2_stn_L1
u2_q_yed_u2_g_yer_L1
u2_q_yed_u2_stn_L1
u2_g_yer_ecm_u2_q_yed_L1
u2_g_yer_ecm_u2_stn_L1
u2_g_yer_u2_q_yed_L1
u2_g_yer_u2_g_yer_L1
u2_g_yer_u2_stn_L1
u2_stn_ecm_u2_q_yed_L1
u2_stn_ecm_u2_stn_L1
u2_stn_u2_q_yed_L1
u2_stn_u2_g_yer_L1
u2_estn_u2_estn_L1
u2_ehic_u2_ehic_L1
de_q_yed_ecm_de_q_yed_L1
de_q_yed_ecm_u2_stn_L1
de_q_yed_de_g_yer_L1
de_q_yed_u2_stn_L1
de_g_yer_ecm_de_q_yed_L1
de_g_yer_ecm_u2_stn_L1
de_g_yer_de_q_yed_L1
de_g_yer_de_g_yer_L1
de_g_yer_u2_stn_L1
de_ehic_de_ehic_L1
;
u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ;
u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ;
u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ;
u2_q_yed_u2_stn_L1 = 0.058397703958446 ;
u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ;
u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ;
u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ;
u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ;
u2_g_yer_u2_stn_L1 = -0.0722359286123494 ;
u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ;
u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ;
u2_stn_u2_q_yed_L1 = 0.0328744983772825 ;
u2_stn_u2_g_yer_L1 = 0.292121949736756 ;
u2_estn_u2_estn_L1 = 1 ;
u2_ehic_u2_ehic_L1 = 1 ;
de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ;
de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ;
de_q_yed_de_g_yer_L1 = 0.0401361895021082 ;
de_q_yed_u2_stn_L1 = 0.0583977039584461 ;
de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ;
de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ;
de_g_yer_de_q_yed_L1 = 0.00376679676320256;
de_g_yer_de_g_yer_L1 = 0.480506381923643 ;
de_g_yer_u2_stn_L1 = -0.0722359286123494 ;
de_ehic_de_ehic_L1 = 1 ;
model(linear);
[name = 'eq1']
diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_Q_YED ;
[name = 'eq2']
diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_G_YER ;
[name = 'eq3']
diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ res_U2_STN ;
[name = 'eq4']
U2_ESTN = u2_estn_u2_estn_L1 * U2_ESTN(-1)
+ res_U2_ESTN ;
[name = 'eq5']
U2_EHIC = u2_ehic_u2_ehic_L1 * U2_EHIC(-1)
+ res_U2_EHIC ;
[name = 'eq6']
diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_Q_YED ;
[name = 'eq7']
diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1))
+ de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_G_YER ;
[name = 'eq8']
DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ;
end;
shocks;
var res_U2_Q_YED = 0.005;
var res_U2_G_YER = 0.005;
var res_U2_STN = 0.005;
var res_U2_ESTN = 0.005;
var res_U2_EHIC = 0.005;
var res_DE_Q_YED = 0.005;
var res_DE_G_YER = 0.005;
var res_DE_EHIC = 0.005;
end;
NSIMS = 1;
options_.noprint = 1;
calibrated_values = M_.params;
Sigma_e = M_.Sigma_e;
options_.bnlms.set_dynare_seed_to_default = false;
nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS
firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values;
M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000));
names=regexp(simdata.name, 'res\w*');
idxs = [];
for j=1:length(names)
if isempty(names{j})
idxs = [idxs j];
end
end
simdata = sur(simdata{idxs});
BETA(i, :) = M_.params';
oo_ = rmfield(oo_, 'sur');
end
if NSIMS > 1
if max(abs(mean(BETA)' - calibrated_values)) > 1e-2
error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]);
end
else
if isoctave
good = [-8.352553221721005e-01
-3.197321434625048e-01
1.833371158471533e-02
5.535617069191032e-02
1.561983042003726e-02
-8.993909626264719e-02
1.711785670581707e-02
4.757720040796121e-01
-8.571091170339767e-02
-2.950787496937523e-02
-1.364615168219547e-01
3.188305976033711e-03
2.978809614745770e-01
1.000152497234268e+00
1.000581562867493e+00
-8.285078166013811e-01
-3.282738244438672e-01
1.707491564143498e-02
5.924757545427200e-02
4.811130814635710e-02
-1.066481566003144e-01
4.462314484614635e-03
4.862610106651586e-01
-7.133910570135164e-02
1.000000000000000e+00];
else
good = [-0.826686196809409
-0.346753563700393
0.063013991583949
0.074802596658698
-0.017440119721953
-0.127090614348862
0.025293280404460
0.524290302468866
-0.117611206771440
-0.027776224547132
-0.156590828735908
0.054039707976331
0.276257666502046
1.000417289621684
0.999336865129450
-0.803258152338916
-0.309594948488168
0.051602756230521
0.039275481081030
0.024897596371662
-0.096310133845385
-0.022630284059365
0.461683465196454
-0.110278113383114
1.000000000000000];
end
if max(abs(BETA' - good)) > 1e-14
error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA' - good)))]);
end
return
end
for i=1:nparampool
figure
hold on
title(strrep(M_.param_names(i,:), '_', '\_'));
histogram(BETA(:,i),50);
line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r');
hold off
end