223 lines
6.9 KiB
Modula-2
223 lines
6.9 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_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 = 0 ;
|
|
|
|
[name = 'eq5']
|
|
U2_EHIC = 0 ;
|
|
|
|
[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_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;
|
|
verbatim;
|
|
Sigma_e = M_.Sigma_e;
|
|
end;
|
|
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));
|
|
% fill zeroed-out variables with random data to ensure they are not being referenced
|
|
simdata.U2_EHIC = dseries(rand(1000, 1), simdata.firstdate, 'U2_EHIC');
|
|
simdata.U2_ESTN = dseries(rand(1000, 1), simdata.firstdate, 'U2_ESTN');
|
|
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
|
|
good = [-0.806260229719792
|
|
-0.354371215026078
|
|
0.067618717060638
|
|
0.088053231576354
|
|
-0.057161898696690
|
|
-0.136999143481575
|
|
0.052047088887385
|
|
0.524022502978068
|
|
-0.110211572532150
|
|
-0.041415758049800
|
|
-0.162997606880957
|
|
0.091000830792721
|
|
0.281196660545012
|
|
1.000000000000000
|
|
1.000000000000000
|
|
-0.823354793011220
|
|
-0.337521089381118
|
|
0.025493177305917
|
|
0.059513905441361
|
|
0.016845886773011
|
|
-0.151537340795868
|
|
0.004832174649536
|
|
0.430883913061161
|
|
-0.071743697511067
|
|
1.000000000000000];
|
|
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
|