diff --git a/tests/Makefile.am b/tests/Makefile.am index 23369fabe..509ee6e0f 100644 --- a/tests/Makefile.am +++ b/tests/Makefile.am @@ -2,6 +2,7 @@ MODFILES = \ walsh.mod \ optimizers/fs2000_6.mod \ moments/example1_hp_test.mod \ + moments/fs2000_post_moments.mod \ lmmcp/rbcii.mod \ ep/rbc_mc.mod \ estimation/TaRB/fs2000_tarb.mod \ diff --git a/tests/moments/fs2000_post_moments.mod b/tests/moments/fs2000_post_moments.mod new file mode 100644 index 000000000..995b87b73 --- /dev/null +++ b/tests/moments/fs2000_post_moments.mod @@ -0,0 +1,190 @@ +/* + * This file replicates the estimation of the cash in advance model (termed M1 + * in the paper) described in 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 prior distribution follows the one originally specified in Schorfheide's + * paper, except for parameter rho. In the paper, the elicited beta prior for rho + * implies an asymptote and corresponding prior mode at 0. It is generally + * recommended to avoid this extreme type of prior. Some optimizers, for instance + * mode_compute=12 (Mathworks' particleswarm algorithm) may find a posterior mode + * with rho equal to zero. We lowered the value of the prior standard deviation + * (changing .223 to .100) to remove the asymptote. + * + * 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 originally written by Michel Juillard. Please note that the + * following copyright notice only applies to this Dynare implementation of the + * model. + */ + +/* + * Copyright (C) 2004-2017 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 . + */ + +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; + +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, 0.100; +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,mode_compute=5, datafile='../fs2000/fsdat_simul.m', nobs=192, loglinear, mh_replic=20, mh_nblocks=1, mh_jscale=0.8,moments_varendo, +conditional_variance_decomposition=[2,2000],consider_all_endogenous,sub_draws=2); + +stoch_simul(order=1,conditional_variance_decomposition=[2,2000],noprint,nograph); +par=load([M_.fname filesep 'metropolis' filesep M_.fname '_posterior_draws1']); + +for par_iter=1:size(par.pdraws,1) + M_=set_parameters_locally(M_,par.pdraws{par_iter,1}); + info=stoch_simul(var_list_); + correlation(:,:,par_iter)=cell2mat(oo_.autocorr); + covariance(:,:,par_iter)=oo_.var; + conditional_variance_decomposition(:,:,:,par_iter)=oo_.conditional_variance_decomposition; + variance_decomposition(:,:,par_iter)=oo_.variance_decomposition; +end + +correlation=mean(correlation,3); +nvars=size(M_.endo_names(1:M_.orig_endo_nbr,:),1); +for var_iter_1=1:nvars + for var_iter_2=1:nvars + if max(abs(correlation(var_iter_1,var_iter_2:nvars:end)'-oo_.PosteriorTheoreticalMoments.dsge.correlation.Mean.(deblank(M_.endo_names{var_iter_1,:})).(deblank(M_.endo_names{var_iter_2,:}))))>1e-8 + error('Correlations do not match') + end + end +end + +covariance=mean(covariance,3); +nvars=size(M_.endo_names(1:M_.orig_endo_nbr,:),1); +for var_iter_1=1:nvars + for var_iter_2=var_iter_1:nvars + if max(abs(covariance(var_iter_1,var_iter_2)-oo_.PosteriorTheoreticalMoments.dsge.covariance.Mean.(deblank(M_.endo_names{var_iter_1,:})).(deblank(M_.endo_names{var_iter_2,:}))))>1e-8 + error('Covariances do not match') + end + end +end + +variance_decomposition=mean(variance_decomposition,3); +nvars=size(M_.endo_names(1:M_.orig_endo_nbr,:),1); +for var_iter_1=1:nvars + for shock_iter=1:M_.exo_nbr + if max(abs(variance_decomposition(var_iter_1,shock_iter)/100-oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.Mean.(deblank(M_.endo_names{var_iter_1,:})).(deblank(M_.exo_names{shock_iter,:}))))>1e-8 + error('Variance decomposition does not match') + end + end +end + +conditional_variance_decomposition=mean(conditional_variance_decomposition,4); +nvars=size(M_.endo_names(1:M_.orig_endo_nbr,:),1); +horizon_size=size(conditional_variance_decomposition,3); +for var_iter_1=1:nvars + for shock_iter=1:M_.exo_nbr + for horizon_iter=1:horizon_size + if max(abs(conditional_variance_decomposition(var_iter_1,horizon_iter,shock_iter)-oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.(deblank(M_.endo_names{var_iter_1,:})).(deblank(M_.exo_names{shock_iter,:}))(horizon_iter)))>1e-8 + error('Conditional Variance decomposition does not match') + end + end + end +end + +/* + * The following lines were used to generate the data file. If you want to + * generate another random data file, comment the "estimation" line and uncomment + * the following lines. + */ + +//stoch_simul(periods=200, order=1); +//datatomfile('fsdat_simul', char('gy_obs', 'gp_obs'));