Commit d5900f28 authored by Stéphane Adjemian's avatar Stéphane Adjemian
Browse files

Added test files for non linear filters.

parent 8de93c21
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i_obs = series(:,3) ;
ti = [1950:0.25:1997.75] ;
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series = data_q ;
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l = series(:,2) ;
i = series(:,3) ;
ti = [1950:0.25:1997.75] ;
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series = data_q' ;
y_obs = series(:,1) ;
l_obs = series(:,2) ;
i_obs = series(:,3) ;
ti = [1950:0.25:1997.75] ;
data_q = [1.75099898532524,1.88377522785224,1.82003384950276,1.79192500364633,1.79317796107537,1.68381206890961,1.80084423220119,1.76688816539747,1.68226379939794,1.70715497573728,1.78665747882670,1.76656199811818,1.82112098249077,1.83388660164881,1.66153116749576,1.79683688815731,1.63937012470471,1.78762597080198,1.96638496958139,1.91280475171796,1.98733302932857,1.91998022255272,1.85184795818947,1.92088283303560,1.95917363716785,1.87182739269960,1.85360779647389,1.75057355234880,1.82613416827614,1.75905253768494,1.63450539745340,1.59767532743253,1.74168300693605,1.79009863643890,1.70751041575409,1.71730301478936,1.72083214417206,1.70569426018781,1.75558560495033,1.67882125908321,1.73692396532595,1.71720405160688,1.72380320499742,1.70124155031073,1.61006406929136,1.53169147650429,1.59696636539655,1.59453002648770,1.58922522836069,1.50246526660034,1.58971613498795,1.62425965013017,1.53736746769662,1.51935849611235,1.55610338399127,1.44612192063113,1.45222650696077,1.46079990608392,1.54814407602635,1.47366183297459,1.44668106519977,1.41051715472427,1.40549325262455,1.49798728074593,1.55965219062220,1.56685038822996,1.59553831957390,1.69202531052370,1.73531800531140,1.70762944707272,1.64444103630337,1.69760879087414,1.66596723045108,1.59202282184040,1.63063045779294,1.62657877212236,1.54925415062340,1.48747191764060,1.37160242467154,1.48038405969598,1.57518680160176,1.61016234683505,1.65854595882691,1.57738006343844,1.62538407575016,1.55827971955698,1.53985286031546,1.53270077040017,1.56052181318552,1.58700721037477,1.61976310464995,1.68552347483654,1.61601942793725,1.73208541377223,1.71891420525012,1.61716713056029,1.55992664815474,1.65470474944168,1.72472990949148,1.76616986088462,1.81675351140158,1.82728538731964,2.01868199473407,1.96505386951791,1.90989180329838,1.94687517191194,1.95162765545470,1.99152074532869,1.95107712558405,1.97717980771856,1.82041111117966,1.75254901153440,1.82974701820688,1.89961594871768,1.97373525239950,1.96085266593417,1.89332408558892,1.86864487797989,1.91204000351969,1.99057679481696,1.86235373579364,1.95550712988684,2.01322179458407,2.00694740330004,2.10137982806924,2.07111662476806,1.99350173156379,1.85834036445334,1.82148067400730,1.92219968437173,1.93607643965025,2.03448207685022,1.78012844009432,1.82305143977338,1.86938144479007,1.88017408192325,1.92620806770279,1.99973797254618,1.93961651315404,2.00414986931471,2.03499348665613,2.00991887724681,1.86849635041043,1.98830760698266,2.08149166965573,2.03787509940085,2.04599486974865,2.12573574697528,2.05080285337310,1.95781096551530,1.85373980453924,1.72119219895464,1.57703150314295;0.312104439663603,0.329371355145864,0.325372475082418,0.323407644126460,0.323430134592878,0.316319910362266,0.324049818736011,0.321601411692119,0.316150888475227,0.317821842351679,0.322804671102699,0.321401970017840,0.325115970736196,0.325508393807138,0.314524287124156,0.323165813529310,0.312844387901606,0.322741931957645,0.333515096803788,0.330224541893082,0.334361915557460,0.330476733685138,0.326065666112615,0.330314147796851,0.332228386721703,0.327070073860872,0.325873066213973,0.319180404014639,0.324010393232609,0.319851116768829,0.311375873293146,0.308896339746293,0.318728191927692,0.321731259385984,0.316499585712051,0.317116419246221,0.317433469427431,0.316255484000383,0.319670906567351,0.314510065270998,0.318407157603747,0.317001154827376,0.317604221226243,0.316240696693449,0.309731058488978,0.304415853726742,0.309355919885048,0.309123873819026,0.308926108611772,0.302708196466963,0.309403154422463,0.311835641680429,0.305175092605397,0.304086429911625,0.307118986227246,0.298941417446540,0.299695961966452,0.300503155962397,0.307077196151450,0.301497201655624,0.299772972628439,0.296945489633266,0.296833169486354,0.304483015929302,0.308543662679929,0.309301626074895,0.311274498526832,0.317936601675223,0.320830001112260,0.318651773414279,0.314521192581214,0.318162484631600,0.315862901030572,0.310711002886469,0.313485646110155,0.313248914764525,0.307736281310499,0.303510550997458,0.294470863334811,0.303375705458699,0.310351709788193,0.312770945333348,0.315896091376809,0.310264056952200,0.313792342258700,0.308967461164588,0.307708545176780,0.307092914248454,0.309344448311592,0.311353123010647,0.313601722966305,0.317830232167858,0.313336734706608,0.320971371020627,0.319998054023955,0.313062461567068,0.309182868166211,0.315860627424213,0.320347442460061,0.322928866498264,0.326242503081692,0.326572182514262,0.337717374907240,0.334331484422776,0.331247652358321,0.332974203712223,0.333071100770716,0.335244074652961,0.332703246081269,0.334182475854777,0.324535127948382,0.320226271619975,0.325233940142540,0.329327960230965,0.333598362798684,0.332723190726392,0.328624905260878,0.326915911700001,0.329526397310549,0.334020664799165,0.326212273802724,0.331904380557907,0.334981188389848,0.334460038254862,0.339840618130387,0.338040580433070,0.333271411935834,0.325100327368298,0.322814414722503,0.329000115798743,0.329588975262892,0.335467073864594,0.319858259045060,0.32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;
series = data_q' ;
y = series(:,1) ;
l = series(:,2) ;
i = series(:,3) ;
ti = [1950:0.25:1997.75] ;
\ No newline at end of file
var k A c l i y y_obs l_obs i_obs;
varexo e_a,e_y,e_i,e_l ;
parameters alp bet tet tau delt rho ;
alp = 0.4;
bet = 0.99;
tet = 0.357 ;
tau = 50 ;
delt = 0.02;
rho = 0.95;
model;
c = ((1 - alp)*tet/(1-tet))*A*(1-l)*((k(-1)/l)^alp) ;
y = A*(k(-1)^alp)*(l^(1-alp)) ;
i = y-c ;
k = (1-delt)*k(-1) + i ;
log(A) = rho*log(A(-1)) + e_a ;
(((c^(tet))*((1-l)^(1-tet)))^(1-tau))/c - bet*((((c(+1)^(tet))*((1-l(+1))^(1-tet)))^(1-tau))/c(+1))*(1 -delt+alp*(A(1)*(k^alp)*(l(1)^(1-alp)))/k)=0 ;
y_obs = y + e_y ;
l_obs = l + e_l ;
i_obs = i + e_i ;
end;
steady;
shocks;
var e_a; stderr 0.035;
var e_y; stderr 0.000158;
var e_l; stderr 0.00011;
var e_i; stderr 0.0000866;
end;
steady;
estimated_params;
alp, uniform_pdf,,, 0.0001, 1;
bet, uniform_pdf,,, 0.75, 0.999;
tet, uniform_pdf,,, 0.0001, 1;
tau, uniform_pdf,,, 0.0001, 100;
delt, uniform_pdf,,, 0.0001, 0.05;
rho, uniform_pdf,,, 0.0001, 0.999;
stderr e_a, uniform_pdf,,, 0.00001, 0.1;
stderr e_y, uniform_pdf,,, 0.00001, 0.1;
stderr e_l, uniform_pdf,,, 0.00001, 0.1;
stderr e_i, uniform_pdf,,, 0.00001, 0.1;
end;
estimated_params_init;
alp, 0.4;
bet, 0.99;
tet, 0.357 ;
tau, 3;
delt, 0.02;
rho, 0.95;
stderr e_a, .035;
stderr e_y, .000158;
stderr e_l, .0011;
stderr e_i, .000866;
end;
varobs y_obs l_obs i_obs;
options_.particle_filter.algorithm = 'sequential_importance_particle_filter';
options_.particle_filter.initialization = 1;
estimation(datafile=data_benchmark,order=2,nobs=100,mh_replic=0,mode_compute=8,mode_check);
// This file deals with the resolution and estimation of a basic DSGE model with
//employment for comparison with the benchmark in Gauss which solves with
//the same particular filter but global methodology.
//
// January 2010
var k A c l i y;
varexo e_a;
parameters alp bet tet tau delt rho ;
alp = 0.4;
bet = 0.99;
tet = 0.357 ;
tau = 50 ;
delt = 0.02;
rho = 0.95;
model;
c = ((1 - alp)*tet/(1-tet))*A*(1-l)*((k(-1)/l)^alp) ;
y = A*(k(-1)^alp)*(l^(1-alp)) ;
i = y-c ;
k = (1-delt)*k(-1) + i ;
log(A) = rho*log(A(-1)) + e_a ;
(((c^(tet))*((1-l)^(1-tet)))^(1-tau))/c - bet*((((c(+1)^(tet))*((1-l(+1))^(1-tet)))^(1-tau))/c(+1))*(1 -delt+alp*(A(1)*(k^alp)*(l(1)^(1-alp)))/k)=0 ;
end;
steady;
resid(1);
shocks;
var e_a; stderr 0.007;
end;
steady;
estimated_params;
alp, uniform_pdf,,, 0.0001, 1;
bet, uniform_pdf,,, 0.75, 0.999;
tet, uniform_pdf,,, 0.0001, 1;
tau, uniform_pdf,,, 0.0001, 100;
delt, uniform_pdf,,, 0.0001, 0.05;
rho, uniform_pdf,,, 0.0001, 0.999;
stderr e_a, uniform_pdf,,, 0.00001, 0.1;
stderr y, uniform_pdf,,, 0.00001, 0.1;
stderr l, uniform_pdf,,, 0.00001, 0.1;
stderr i, uniform_pdf,,, 0.00001, 0.1;
end;
estimated_params_init;
alp, 0.4;
bet, 0.99;
tet, 0.357 ;
tau, 3;
delt, 0.02;
rho, 0.95;
stderr e_a, .035;
stderr y, .0175;//.00158;
stderr l, .00312;//.0011;
stderr i, .00465;//.000866;
end;
varobs y l i;
options_.particle_filter.algorithm = 'sequential_importance_particle_filter';
options_.particle_filter.initialization = 1;
estimation(datafile=data_risky_perturb2,order=2,nobs=100,mh_replic=0,mode_compute=8,mode_check);
\ No newline at end of file
function [ys,check,penlt] = mze_steadystate(ys,exe)
global M_
persistent idx NumberOfParameters NumberOfEndogenousVariables
persistent load_parameters fill_ys
if isempty(idx)
NumberOfParameters = M_.param_nbr;
NumberOfEndogenousVariables = M_.orig_endo_nbr;
load_parameters = [];
for i = 1:NumberOfParameters
load_parameters = [ load_parameters deblank(M_.param_names(i,:)) ' = M_.params(' int2str(i) '); '];
end
fill_ys = [];
for i = 1:NumberOfEndogenousVariables
fill_ys = [fill_ys 'ys(' int2str(i) ') = ' deblank(M_.endo_names(i,:)) '_ss' '; '];
end
idx = 1;
end
% Do not call matlab's routine!
eval(load_parameters);
ys = zeros(NumberOfEndogenousVariables,1);
check = 0;
k_ss = -(alp-1)*(alp^(1/(1-alp)))*(bet^(1/(1-alp)))*((bet*(delt-1)+1)^(alp/(alp-1)))*tet;