124 lines
4.3 KiB
Modula-2
124 lines
4.3 KiB
Modula-2
%this is the mod file used in replication files of An and Schorfheide (2007)
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% modified to include some obvious and artificial identification failures
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% and to check whether all kronflags are working
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% created by Willi Mutschler (@wmutschl, willi@mutschler.eu)
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% =========================================================================
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% Copyright (C) 2019-2020 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 <http://www.gnu.org/licenses/>.
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% =========================================================================
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var y R g z c dy p YGR INFL INT;
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varobs y R p;
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varexo e_r e_g e_z;
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parameters sigr sigg sigz tau phi psi1 psi2 rhor rhog rhoz rrst pist gamst nu cyst dumpy dumpyrhog;
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rrst = 1.0000;
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pist = 3.2000;
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gamst= 0.5500;
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tau = 2.0000;
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nu = 0.1000;
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kap = 0.3300;
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phi = tau*(1-nu)/nu/kap/exp(pist/400)^2;
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cyst = 0.8500;
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psi1 = 1.5000;
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psi2 = 0.1250;
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rhor = 0.7500;
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rhog = 0.9500;
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rhoz = 0.9000;
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sigr = 0.2;
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sigg = 0.6;
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sigz = 0.3;
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dumpy = 0;
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dumpyrhog = 1;
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model;
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#pist2 = exp(pist/400);
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#rrst2 = exp(rrst/400);
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#bet = 1/rrst2;
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#gst = 1/cyst;
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#cst = (1-nu)^(1/tau);
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#yst = cst*gst;
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1 = exp(-tau*c(+1)+tau*c+R-z(+1)-p(+1));
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(1-nu)/nu/phi/(pist2^2)*(exp(tau*c)-1) = (exp(p)-1)*((1-1/2/nu)*exp(p)+1/2/nu) - bet*(exp(p(+1))-1)*exp(-tau*c(+1)+tau*c+dy(+1)+p(+1));
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exp(c-y) = exp(-g) - phi*pist2^2*gst/2*(exp(p)-1)^2;
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R = rhor*R(-1) + (1-rhor)*psi1*p + (1-rhor)*psi2*(y-g) + sigr*e_r;
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g = dumpyrhog*rhog*g(-1) + sigg*e_g;
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z = rhoz*z(-1) + sigz*e_z;
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YGR = gamst+100*(dy+z);
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INFL = pist+400*p;
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INT = pist+rrst+4*gamst+400*R;
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dy = y - y(-1);
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end;
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shocks;
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var e_r = 0.6^2;
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var e_g = 0.5^2;
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var e_z = 0.4^2;
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corr e_r, e_g = 0.3;
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corr e_r, e_z = 0.2;
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corr e_z, e_g = 0.1;
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end;
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steady_state_model;
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z=0; g=0; c=0; y=0; p=0; R=0; dy=0;
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YGR=gamst; INFL=pist; INT=pist+rrst+4*gamst;
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end;
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estimated_params;
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tau, 2, 1e-5, 10, gamma_pdf, 2, 0.5;
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%these parameters do not enter the linearized solution
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cyst, 0.85, 1e-5, 0.99999, beta_pdf, 0.85, 0.1;
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sigg, 0.6, 1e-8, 5, inv_gamma_pdf, 0.4, 4;
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rhoz, 0.9, 1e-5, 0.99999, beta_pdf, 0.66, 0.15;
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corr e_r,e_g, 0.3, 1e-8, 5, inv_gamma_pdf, 0.4, 4;
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corr e_z,e_g, 0.3, 1e-8, 5, inv_gamma_pdf, 0.4, 4;
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corr e_z,e_r, 0.3, 1e-8, 5, inv_gamma_pdf, 0.4, 4;
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%these parameters could only be identified from the steady state of YGR INFL and INT, however, we observer y pi R instead
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rrst, 1, 1e-5, 10, gamma_pdf, 0.8, 0.5;
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gamst, 0.55, -5, 5, normal_pdf, 0.4, 0.2;
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dumpy, 0, -10, 10, normal_pdf, 0, 1;
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%these parameters jointly determine the slope kappa of the linearized new keynesian phillips curve
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pist, 3.2, 1e-5, 20, gamma_pdf, 4, 2;
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nu, 0.1, 1e-5, 0.99999, beta_pdf, 0.1, .05;
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phi, 50, 1e-5, 100, gamma_pdf, 50, 20;
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%these parameters are pairwise collinear as one should not use both formulations for the standard error of a shock
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sigz, 0.3, 1e-8, 5, inv_gamma_pdf, 0.4, 4;
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stderr e_z, 0.3, 1e-8, 5, inv_gamma_pdf, 0.4, 4;
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%these parameters are pairwise collinear as they are multiplicative
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rhog, 0.95, 1e-5, 0.99999, beta_pdf, 0.8, 0.1;
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dumpyrhog, 1, -10, 10, normal_pdf, 1, 1;
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%these parameters are jointly not identified due to the specification of the Taylor rule
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psi1, 1.5, 1e-5, 10, gamma_pdf, 1.5, 0.25;
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psi2, 0.125, 1e-5, 10, gamma_pdf, 0.5, 0.25;
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rhor, 0.75, 1e-5, 0.99999, beta_pdf, 0.5, 0.2;
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stderr e_r, 0.2, 1e-8, 5, inv_gamma_pdf, 0.3, 4;
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end;
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steady;
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check;
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identification(parameter_set=calibration, analytic_derivation_mode=-2);
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identification(parameter_set=calibration, analytic_derivation_mode=-1);
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identification(parameter_set=calibration, analytic_derivation_mode=1);
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identification(parameter_set=calibration, analytic_derivation_mode=0); |