Add unit tests for correctness of smoother results
parent
a534b63383
commit
df54e8fcab
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@ -191,6 +191,11 @@ MODFILES = \
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kalman/likelihood_from_dynare/fs2000_uncorr_ME.mod \
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kalman/likelihood_from_dynare/fs2000_uncorr_ME_missing.mod \
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second_order/burnside_1.mod \
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kalman_filter_smoother/compare_results_simulation/fs2000_ML.mod \
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kalman_filter_smoother/compare_results_simulation/fs2000_ML_loglinear.mod \
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kalman_filter_smoother/compare_results_simulation/fs2000.mod \
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kalman_filter_smoother/compare_results_simulation/fs2000_loglinear.mod \
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second_order/burnside_1.mod \
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second_order/ds1.mod \
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second_order/ds2.mod \
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ep/rbc.mod \
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@ -479,6 +484,7 @@ EXTRA_DIST = \
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kalman/likelihood_from_dynare/fsdat_simul_corr_ME_missing.m \
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kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME.m \
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kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME_missing.m \
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kalman_filter_smoother/compare_results_simulation/fsdat_simul_logged.m \
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identification/kim/kim2_steadystate.m \
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identification/as2007/as2007_steadystate.m \
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estimation/fsdat_simul.m \
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@ -0,0 +1,158 @@
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/*
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* This file replicates the estimation of the cash in advance model described
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* Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
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* Journal of Applied Econometrics, 15(6), 645-670.
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*
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* The data are in file "fsdat_simul.m", and have been artificially generated.
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* They are therefore different from the original dataset used by Schorfheide.
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*
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* The equations are taken from J. Nason and T. Cogley (1994): "Testing the
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* implications of long-run neutrality for monetary business cycle models",
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* Journal of Applied Econometrics, 9, S37-S70.
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* Note that there is an initial minus sign missing in equation (A1), p. S63.
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*
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* This implementation was written by Michel Juillard. Please note that the
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* following copyright notice only applies to this Dynare implementation of the
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* model.
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*/
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/*
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* Copyright (C) 2004-2010 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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var m P c e W R k d n l gy_obs gp_obs y dA;
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varexo e_a e_m;
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parameters alp bet gam mst rho psi del;
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alp = 0.33;
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bet = 0.99;
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gam = 0.003;
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mst = 1.011;
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rho = 0.7;
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psi = 0.787;
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del = 0.02;
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model;
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dA = exp(gam+e_a);
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log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
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-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(+1)*P(+1)*m(+1))=0;
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W = l/n;
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-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
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R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
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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;
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c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
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P*c = m;
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m-1+d = l;
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e = exp(e_a);
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y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
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exp(gy_obs) = dA*y/y(-1);
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exp(gp_obs) = (P/P(-1))*m(-1)/dA;
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end;
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shocks;
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var e_a; stderr 0.014;
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var e_m; stderr 0.005;
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end;
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steady_state_model;
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dA = exp(gam);
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gst = 1/dA;
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m = mst;
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khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
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xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
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nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
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n = xist/(nust+xist);
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P = xist + nust;
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k = khst*n;
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l = psi*mst*n/( (1-psi)*(1-n) );
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c = mst/P;
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d = l - mst + 1;
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y = k^alp*n^(1-alp)*gst^alp;
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R = mst/bet;
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W = l/n;
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ist = y-c;
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q = 1 - d;
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e = 1;
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gp_obs = log(m/dA);
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gy_obs = log(dA);
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end;
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steady;
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check;
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estimated_params;
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alp, beta_pdf, 0.356, 0.02;
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bet, beta_pdf, 0.993, 0.002;
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gam, normal_pdf, 0.0085, 0.003;
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mst, normal_pdf, 1.0002, 0.007;
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rho, beta_pdf, 0.129, 0.223;
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psi, beta_pdf, 0.65, 0.05;
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del, beta_pdf, 0.01, 0.005;
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stderr e_a, inv_gamma_pdf, 0.035449, inf;
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stderr e_m, inv_gamma_pdf, 0.008862, inf;
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end;
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varobs gp_obs gy_obs;
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estimation(order=1,datafile=fsdat_simul_logged,consider_all_endogenous,nobs=192,mh_replic=2000, mh_nblocks=1,smoother, mh_jscale=0.8);
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ex_=[];
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for shock_iter=1:M_.exo_nbr
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ex_=[ex_ oo_.SmoothedShocks.Mean.(deblank(M_.exo_names(shock_iter,:)))];
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end
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ex_ = ex_(2:end,:);
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% ex_ = zeros(size(ex_));
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y0=[];
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for endo_iter=1:M_.endo_nbr
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y0 = [y0;
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oo_.SmoothedVariables.Mean.(deblank(M_.endo_names(endo_iter,:)))(1)];
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end;
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%make sure decision rules were updated
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[oo_.dr,info,M_,options_] = resol(0,M_,options_,oo_);
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dr = oo_.dr;
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iorder=1;
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y_=simult_(y0,dr,ex_,iorder);
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fsdat_simul_logged;
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%Needs bigger tolerance than ML, because transformation from parameters to steady states is not linear and steady state at mean parameters is not mean of steady states
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if mean(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-(gy_obs(1:options_.nobs))))>1e-3 ||...
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mean(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.Mean.gy_obs))>1e-3 ||...
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mean(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-(gp_obs(1:options_.nobs))))>1e-1 ||...
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mean(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.Mean.gp_obs))>1e-2
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error('Smoother is wrong')
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end
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% figure
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% plot((gy_obs))
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% hold on
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% plot(y_(strmatch('gy_obs',M_.endo_names,'exact'),:),'r--')
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%
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% figure
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% plot((gp_obs))
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% hold on
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% plot(y_(strmatch('gp_obs',M_.endo_names,'exact'),:),'r--')
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@ -0,0 +1,163 @@
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/*
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* This file replicates the estimation of the cash in advance model described
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* Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
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* Journal of Applied Econometrics, 15(6), 645-670.
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*
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* The data are in file "fsdat_simul.m", and have been artificially generated.
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* They are therefore different from the original dataset used by Schorfheide.
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*
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* The equations are taken from J. Nason and T. Cogley (1994): "Testing the
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* implications of long-run neutrality for monetary business cycle models",
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* Journal of Applied Econometrics, 9, S37-S70.
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* Note that there is an initial minus sign missing in equation (A1), p. S63.
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*
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* This implementation was written by Michel Juillard. Please note that the
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* following copyright notice only applies to this Dynare implementation of the
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* model.
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*/
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/*
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* Copyright (C) 2004-2010 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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var m P c e W R k d n l gy_obs gp_obs y dA;
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varexo e_a e_m;
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parameters alp bet gam mst rho psi del theta;
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alp = 0.33;
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bet = 0.99;
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gam = 0.003;
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mst = 1.011;
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rho = 0.7;
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psi = 0.787;
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del = 0.02;
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theta=0;
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model;
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dA = exp(gam+e_a);
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log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
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-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;
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W = l/n;
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-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
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R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
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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;
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c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
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P*c = m;
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m-1+d = l;
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e = exp(e_a);
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y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
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exp(gy_obs) = dA*y/y(-1);
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exp(gp_obs) = (P/P(-1))*m(-1)/dA;
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end;
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steady_state_model;
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dA = exp(gam);
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gst = 1/dA;
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m = mst;
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khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
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xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
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nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
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n = xist/(nust+xist);
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P = xist + nust;
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k = khst*n;
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l = psi*mst*n/( (1-psi)*(1-n) );
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c = mst/P;
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d = l - mst + 1;
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y = k^alp*n^(1-alp)*gst^alp;
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R = mst/bet;
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W = l/n;
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ist = y-c;
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q = 1 - d;
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e = 1;
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gp_obs = log(m/dA);
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gy_obs = log(dA);
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end;
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shocks;
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var e_a; stderr 0.014;
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var e_m; stderr 0.005;
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end;
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varobs gp_obs gy_obs;
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steady;
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check;
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estimated_params;
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alp, 0.356;
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gam, 0.0085;
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mst, 1.0002;
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rho, 0.129;
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psi, 0.65;
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del, 0.02;
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stderr e_a, 0.035449;
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stderr e_m, 0.008862;
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end;
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estimation(order=1,datafile='fsdat_simul_logged', nobs=192, forecast=8,smoother,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only) m P c e W R k d y gy_obs;
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% write shock matrix
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ex_=[];
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for shock_iter=1:M_.exo_nbr
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ex_=[ex_ oo_.SmoothedShocks.(deblank(M_.exo_names(shock_iter,:)))];
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end
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%select shocks happening after initial period
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ex_ = ex_(2:end,:);
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%get state variables at t=0
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y0=[];
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for endo_iter=1:M_.endo_nbr
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y0 = [y0;
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oo_.SmoothedVariables.(deblank(M_.endo_names(endo_iter,:)))(1)];
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end;
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%make sure decision rules were updated
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[oo_.dr,info,M_,options_] = resol(0,M_,options_,oo_);
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dr = oo_.dr;
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iorder=1;
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%run simulation
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y_=simult_(y0,dr,ex_,iorder);
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fsdat_simul_logged;
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if max(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-gy_obs(1:options_.nobs)))>1e-10 ||...
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max(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.gy_obs))>1e-10 ||...
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max(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-gp_obs(1:options_.nobs)))>1e-10 ||...
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max(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.gp_obs))>1e-10
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error('Smoother is wrong')
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end
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% figure
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% subplot(2,1,1)
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% plot(log(gy_obs))
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% hold on
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% plot(y_(strmatch('gy_obs',M_.endo_names,'exact'),:),'r--')
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%
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% figure
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% subplot(2,1,2)
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% plot(log(gp_obs))
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% hold on
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% plot(y_(strmatch('gp_obs',M_.endo_names,'exact'),:),'r--')
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@ -0,0 +1,150 @@
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/*
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* This file replicates the estimation of the cash in advance model described
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* Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
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* Journal of Applied Econometrics, 15(6), 645-670.
|
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*
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* The data are in file "fsdat_simul.m", and have been artificially generated.
|
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* They are therefore different from the original dataset used by Schorfheide.
|
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*
|
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* The equations are taken from J. Nason and T. Cogley (1994): "Testing the
|
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* implications of long-run neutrality for monetary business cycle models",
|
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* Journal of Applied Econometrics, 9, S37-S70.
|
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* Note that there is an initial minus sign missing in equation (A1), p. S63.
|
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*
|
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* This implementation was written by Michel Juillard. Please note that the
|
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* following copyright notice only applies to this Dynare implementation of the
|
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* model.
|
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*/
|
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/*
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* Copyright (C) 2004-2010 Dynare Team
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*
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* This file is part of Dynare.
|
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*
|
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* Dynare is free software: you can redistribute it and/or modify
|
||||
* it under the terms of the GNU General Public License as published by
|
||||
* the Free Software Foundation, either version 3 of the License, or
|
||||
* (at your option) any later version.
|
||||
*
|
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* Dynare is distributed in the hope that it will be useful,
|
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
* GNU General Public License for more details.
|
||||
*
|
||||
* You should have received a copy of the GNU General Public License
|
||||
* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
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*/
|
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var m P c e W R k d n l gy_obs gp_obs y dA;
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varexo e_a e_m;
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parameters alp bet gam mst rho psi del theta;
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alp = 0.33;
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bet = 0.99;
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gam = 0.003;
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mst = 1.011;
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rho = 0.7;
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psi = 0.787;
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del = 0.02;
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theta=0;
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model;
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dA = exp(gam+e_a);
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log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
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-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;
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W = l/n;
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-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
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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;
|
||||
|
||||
varobs gp_obs gy_obs;
|
||||
|
||||
steady;
|
||||
check;
|
||||
|
||||
estimated_params;
|
||||
alp, 0.356;
|
||||
gam, 0.0085;
|
||||
mst, 1.0002;
|
||||
rho, 0.129;
|
||||
psi, 0.65;
|
||||
del, 0.02;
|
||||
stderr e_a, 0.035449;
|
||||
stderr e_m, 0.008862;
|
||||
end;
|
||||
|
||||
estimation(order=1,datafile='../fsdat_simul',loglinear, nobs=192, forecast=8,smoother,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only) m P c e W R k d y gy_obs;
|
||||
|
||||
% write shock matrix
|
||||
ex_=[];
|
||||
for shock_iter=1:M_.exo_nbr
|
||||
ex_=[ex_ oo_.SmoothedShocks.(deblank(M_.exo_names(shock_iter,:)))];
|
||||
end
|
||||
|
||||
%select shocks happening after initial period
|
||||
ex_ = ex_(2:end,:);
|
||||
|
||||
%get state variables at t=0
|
||||
y0=[];
|
||||
for endo_iter=1:M_.endo_nbr
|
||||
y0 = [y0;
|
||||
oo_.SmoothedVariables.(deblank(M_.endo_names(endo_iter,:)))(1)];
|
||||
end;
|
||||
|
||||
%make sure decision rules were updated
|
||||
[oo_.dr,info,M_,options_] = resol(0,M_,options_,oo_);
|
||||
|
||||
dr = oo_.dr;
|
||||
iorder=1;
|
||||
%run simulation
|
||||
y_=simult_(y0,dr,ex_,iorder);
|
||||
|
||||
fsdat_simul;
|
||||
|
||||
if max(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-log(gy_obs(1:options_.nobs))))>1e-10 ||...
|
||||
max(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.gy_obs))>1e-10 ||...
|
||||
max(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-log(gp_obs(1:options_.nobs))))>1e-10 ||...
|
||||
max(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.gp_obs))>1e-10
|
||||
error('Smoother is wrong')
|
||||
end
|
|
@ -0,0 +1,176 @@
|
|||
/*
|
||||
* This file replicates the estimation of the cash in advance model described
|
||||
* Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
|
||||
* Journal of Applied Econometrics, 15(6), 645-670.
|
||||
*
|
||||
* The data are in file "fsdat_simul.m", and have been artificially generated.
|
||||
* They are therefore different from the original dataset used by Schorfheide.
|
||||
*
|
||||
* 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.
|
||||
*
|
||||
* This implementation was written by Michel Juillard. Please note that the
|
||||
* following copyright notice only applies to this Dynare implementation of the
|
||||
* model.
|
||||
*/
|
||||
|
||||
/*
|
||||
* Copyright (C) 2004-2010 Dynare Team
|
||||
*
|
||||
* This file is part of Dynare.
|
||||
*
|
||||
* Dynare is free software: you can redistribute it and/or modify
|
||||
* it under the terms of the GNU General Public License as published by
|
||||
* the Free Software Foundation, either version 3 of the License, or
|
||||
* (at your option) any later version.
|
||||
*
|
||||
* Dynare is distributed in the hope that it will be useful,
|
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
* GNU General Public License for more details.
|
||||
*
|
||||
* You should have received a copy of the GNU General Public License
|
||||
* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
||||
*/
|
||||
|
||||
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(+1)*P(+1)*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_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;
|
||||
|
||||
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;
|
||||
|
||||
estimation(order=1, datafile='../fsdat_simul', nobs=192, loglinear, mh_replic=2000, mh_nblocks=1,smoother, mh_jscale=0.8);
|
||||
|
||||
ex_=[];
|
||||
for shock_iter=1:M_.exo_nbr
|
||||
ex_=[ex_ oo_.SmoothedShocks.Mean.(deblank(M_.exo_names(shock_iter,:)))];
|
||||
end
|
||||
|
||||
ex_ = ex_(2:end,:);
|
||||
% ex_ = zeros(size(ex_));
|
||||
y0=[];
|
||||
for endo_iter=1:M_.endo_nbr
|
||||
y0 = [y0;
|
||||
oo_.SmoothedVariables.Mean.(deblank(M_.endo_names(endo_iter,:)))(1)];
|
||||
end;
|
||||
|
||||
%make sure decision rules were updated
|
||||
[oo_.dr,info,M_,options_] = resol(0,M_,options_,oo_);
|
||||
|
||||
dr = oo_.dr;
|
||||
iorder=1;
|
||||
% if options_.loglinear
|
||||
% y0=exp(y0);
|
||||
% end
|
||||
y_=simult_(y0,dr,ex_,iorder);
|
||||
|
||||
fsdat_simul;
|
||||
|
||||
if mean(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-log(gy_obs(1:options_.nobs))))>1e-3 ||...
|
||||
mean(abs(y_(strmatch('gy_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.Mean.gy_obs))>1e-3 ||...
|
||||
mean(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-log(gp_obs(1:options_.nobs))))>1e-3 ||...
|
||||
mean(abs(y_(strmatch('gp_obs',M_.endo_names,'exact'),:)'-oo_.SmoothedVariables.Mean.gp_obs))>1e-3
|
||||
error('Smoother is wrong')
|
||||
end
|
||||
|
||||
% figure
|
||||
% plot(log(gy_obs))
|
||||
% hold on
|
||||
% plot(y_(strmatch('gy_obs',M_.endo_names,'exact'),:),'r--')
|
||||
%
|
||||
% figure
|
||||
% plot(log(gp_obs))
|
||||
% hold on
|
||||
% plot(y_(strmatch('gp_obs',M_.endo_names,'exact'),:),'r--')
|
Loading…
Reference in New Issue