159 lines
4.8 KiB
Modula-2
159 lines
4.8 KiB
Modula-2
/*
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* Example 1 from F. Collard (2001): "Stochastic simulations with DYNARE:
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* A practical guide" (see "guide.pdf" in the documentation directory).
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*/
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/*
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* Copyright © 2001-2020 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 <https://www.gnu.org/licenses/>.
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*/
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var y, c, k, a, h, b;
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varexo e, u;
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parameters beta, rho, alpha, delta, theta, psi, tau;
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alpha = 0.36;
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rho = 0.95;
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tau = 0.025;
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beta = 0.99;
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delta = 0.025;
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psi = 0;
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theta = 2.95;
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phi = 0.1;
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model;
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c*theta*h^(1+psi)=(1-alpha)*y;
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k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
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*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
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y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
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k = exp(b)*(y-c)+(1-delta)*k(-1);
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a = rho*a(-1)+tau*b(-1) + e;
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b = tau*a(-1)+rho*b(-1) + u;
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end;
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initval;
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y = 1.08068253095672;
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c = 0.80359242014163;
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h = 0.29175631001732;
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k = 11.08360443260358;
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a = 0;
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b = 0;
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e = 0;
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u = 0;
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end;
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shocks;
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var e; stderr 0.009;
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var u; stderr 0.009;
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var e, u = phi*0.009*0.009;
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end;
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steady(solve_algo=4,maxit=1000);
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stoch_simul(order=1,nofunctions,hp_filter=1600,irf=0,filtered_theoretical_moments_grid=8192);
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total_var_filtered=diag(oo_.var);
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oo_filtered_all_shocks=oo_;
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stoch_simul(order=1,nofunctions,hp_filter=0,periods=2500000,nomoments);
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send_endogenous_variables_to_workspace;
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options_.nomoments=0;
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oo_unfiltered_all_shocks=oo_;
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[junk, y_filtered]=sample_hp_filter(y,1600);
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[junk, c_filtered]=sample_hp_filter(c,1600);
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[junk, k_filtered]=sample_hp_filter(k,1600);
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[junk, a_filtered]=sample_hp_filter(a,1600);
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[junk, h_filtered]=sample_hp_filter(h,1600);
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[junk, b_filtered]=sample_hp_filter(b,1600);
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verbatim;
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total_std_all_shocks_filtered_sim=std([y_filtered c_filtered k_filtered a_filtered h_filtered b_filtered]);
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cov_filtered_all_shocks=cov([y_filtered c_filtered k_filtered a_filtered h_filtered b_filtered]);
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acf = zeros(6);
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[junk, acf(:,1)] = sample_autocovariance([y_filtered ],5);
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[junk, acf(:,2)] = sample_autocovariance([c_filtered ],5);
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[junk, acf(:,3)] = sample_autocovariance([k_filtered ],5);
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[junk, acf(:,4)] = sample_autocovariance([a_filtered ],5);
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[junk, acf(:,5)] = sample_autocovariance([h_filtered ],5);
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[junk, acf(:,6)] = sample_autocovariance([b_filtered ],5);
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autocorr_filtered_all_shocks=acf(2:end,:)';
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end;
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shocks;
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var e; stderr 0;
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var u; stderr 0.009;
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var e, u = phi*0.009*0;
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end;
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stoch_simul(order=1,nofunctions,hp_filter=1600,irf=0,periods=0);
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total_var_filtered_one_shock=diag(oo_.var);
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oo_filtered_one_shock=oo_;
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stoch_simul(order=1,nofunctions,hp_filter=0,periods=2500000,nomoments);
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send_endogenous_variables_to_workspace;
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oo_unfiltered_one_shock=oo_;
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[junk, y_filtered]=sample_hp_filter(y,1600);
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[junk, c_filtered]=sample_hp_filter(c,1600);
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[junk, k_filtered]=sample_hp_filter(k,1600);
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[junk, a_filtered]=sample_hp_filter(a,1600);
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[junk, h_filtered]=sample_hp_filter(h,1600);
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[junk, b_filtered]=sample_hp_filter(b,1600);
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verbatim;
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total_std_one_shock_filtered_sim=std([y_filtered c_filtered k_filtered a_filtered h_filtered b_filtered]);
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cov_filtered_one_shock=cov([y_filtered c_filtered k_filtered a_filtered h_filtered b_filtered]);
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acf = zeros(6);
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[junk, acf(:,1)] = sample_autocovariance([y_filtered ],5);
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[junk, acf(:,2)] = sample_autocovariance([c_filtered ],5);
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[junk, acf(:,3)] = sample_autocovariance([k_filtered ],5);
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[junk, acf(:,4)] = sample_autocovariance([a_filtered ],5);
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[junk, acf(:,5)] = sample_autocovariance([h_filtered ],5);
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[junk, acf(:,6)] = sample_autocovariance([b_filtered ],5);
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autocorr_filtered_one_shock=acf(2:end,:)';
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end;
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if max(abs((1-(total_std_one_shock_filtered_sim.^2)./(total_std_all_shocks_filtered_sim.^2))*100-oo_filtered_all_shocks.variance_decomposition(:,1)'))>2
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error('Variance Decomposition wrong')
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end
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if max(max(abs(oo_filtered_all_shocks.var-cov_filtered_all_shocks)))>1e-4;
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error('Covariance wrong')
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end
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if max(max(abs(oo_filtered_one_shock.var-cov_filtered_one_shock)))>5e-5;
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error('Covariance wrong')
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end
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for ii=1:options_.ar
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autocorr_model_all_shocks(:,ii)=diag(oo_filtered_all_shocks.autocorr{ii});
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autocorr_model_one_shock(:,ii)=diag(oo_filtered_one_shock.autocorr{ii});
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end
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if max(max(abs(autocorr_model_all_shocks-autocorr_filtered_all_shocks)))>1e-2;
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error('Covariance wrong')
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end
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if max(max(abs(autocorr_model_one_shock-autocorr_filtered_one_shock)))>1e-2;
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error('Covariance wrong')
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end
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