260 lines
6.7 KiB
Matlab
260 lines
6.7 KiB
Matlab
function disp_dr_sparse(dr,order,var_list)
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% Display the decision rules in sparse mode
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% This file is a modified version of disp_dr.m: the common parts should be factorized!
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%
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% INPUTS
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% dr [struct]: decision rules
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% order [int]: order of approximation
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% var_list [char array]: list of endogenous variables for which the
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% decision rules should be printed
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% Copyright (C) 2001-2009 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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global M_
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nx = 0;
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nu = 0;
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k = [];
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klag = [];
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k1 = [];
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nspred = 0;
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for i=1:length(M_.block_structure.block)
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nspred = nspred + M_.block_structure.block(i).dr.nspred;
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end;
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ghu = zeros(M_.endo_nbr, M_.exo_nbr*(M_.maximum_exo_lag+M_.maximum_exo_lead+1));
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ghx = zeros(M_.endo_nbr, nspred);
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for i=1:length(M_.block_structure.block)
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nx = nx + size(M_.block_structure.block(i).dr.ghx,2);
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% M_.block_structure.block(i).dr.ghx
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% M_.block_structure.block(i).equation
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% M_.block_structure.block(i).variable
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ghx(M_.block_structure.block(i).equation, M_.block_structure.block(i).variable(find(M_.block_structure.block(i).lead_lag_incidence(1: M_.block_structure.block(i).maximum_endo_lag,:))) ) = M_.block_structure.block(i).dr.ghx;
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if(M_.block_structure.block(i).exo_nbr)
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nu = nu + size(M_.block_structure.block(i).dr.ghu,2);
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ghu(M_.block_structure.block(i).equation, M_.block_structure.block(i).exogenous) = M_.block_structure.block(i).dr.ghu;
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end
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k_tmp = find(M_.block_structure.block(i).dr.kstate(:,2) <= M_.block_structure.block(i).maximum_lag+1);
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k = [k ; k_tmp];
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klag = [klag ; M_.block_structure.block(i).dr.kstate(k_tmp,[1 2])];
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k1 = [k1 ; M_.block_structure.block(i).variable(M_.block_structure.block(i).dr.order_var)'];
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end
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if size(var_list,1) == 0
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var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
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end
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nvar = size(var_list,1);
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ivar=zeros(nvar,1);
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for i=1:nvar
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i_tmp = strmatch(var_list(i,:),M_.endo_names(k1,:),'exact');
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if isempty(i_tmp)
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disp(var_list(i,:));
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error (['One of the variable specified does not exist']) ;
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else
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ivar(i) = i_tmp;
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end
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end
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disp('POLICY AND TRANSITION FUNCTIONS')
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% variable names
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str = ' ';
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for i=1:nvar
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str = [str sprintf('%16s',M_.endo_names(k1(ivar(i)),:))];
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end
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disp(str);
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%
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% constant
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%
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str = 'Constant ';
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flag = 0;
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for i=1:nvar
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x = dr.ys(k1(ivar(i)));
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if order > 1
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x = x + dr.ghs2(ivar(i))/2;
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end
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if abs(x) > 1e-6
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flag = 1;
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str = [str sprintf('%16.6f',x)];
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else
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str = [str ' 0'];
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end
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end
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if flag
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disp(str)
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end
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if order > 1
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str = '(correction) ';
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flag = 0;
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for i=1:nvar
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x = dr.ghs2(ivar(i))/2;
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if abs(x) > 1e-6
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flag = 1;
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str = [str sprintf('%16.6f',x)];
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else
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str = [str ' 0'];
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end
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end
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if flag
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disp(str)
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end
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end
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%
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% ghx
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%
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for k=1:nx
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flag = 0;
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str1 = subst_auxvar(k1(klag(k,1)),klag(k,2)-M_.maximum_lag-2);
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str = sprintf('%-20s',str1);
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for i=1:nvar
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x = ghx(ivar(i),k);
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if abs(x) > 1e-6
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flag = 1;
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str = [str sprintf('%16.6f',x)];
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else
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str = [str ' 0'];
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end
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end
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if flag
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disp(str)
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end
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end
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%
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% ghu
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%
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for k=1:nu
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flag = 0;
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str = sprintf('%-20s',M_.exo_names(k,:));
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for i=1:nvar
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x = ghu(ivar(i),k);
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if abs(x) > 1e-6
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flag = 1;
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str = [str sprintf('%16.6f',x)];
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else
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str = [str ' 0'];
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end
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end
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if flag
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disp(str)
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end
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end
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if order > 1
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% ghxx
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for k = 1:nx
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for j = 1:k
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flag = 0;
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str1 = sprintf('%s,%s',subst_auxvar(k1(klag(k,1)),klag(k,2)-M_.maximum_lag-2), ...
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subst_auxvar(k1(klag(j,1)),klag(j,2)-M_.maximum_lag-2));
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str = sprintf('%-20s',str1);
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for i=1:nvar
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if k == j
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x = dr.ghxx(ivar(i),(k-1)*nx+j)/2;
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else
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x = dr.ghxx(ivar(i),(k-1)*nx+j);
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end
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if abs(x) > 1e-6
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flag = 1;
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str = [str sprintf('%16.6f',x)];
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else
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str = [str ' 0'];
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end
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end
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if flag
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disp(str)
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end
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end
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end
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%
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% ghuu
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%
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for k = 1:nu
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for j = 1:k
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flag = 0;
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str = sprintf('%-20s',[M_.exo_names(k,:) ',' M_.exo_names(j,:)] );
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for i=1:nvar
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if k == j
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x = dr.ghuu(ivar(i),(k-1)*nu+j)/2;
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else
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x = dr.ghuu(ivar(i),(k-1)*nu+j);
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end
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if abs(x) > 1e-6
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flag = 1;
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str = [str sprintf('%16.6f',x)];
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else
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str = [str ' 0'];
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end
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end
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if flag
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disp(str)
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end
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end
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end
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%
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% ghxu
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%
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for k = 1:nx
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for j = 1:nu
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flag = 0;
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str1 = sprintf('%s,%s',subst_auxvar(k1(klag(k,1)),klag(k,2)-M_.maximum_lag-2), ...
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M_.exo_names(j,:));
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str = sprintf('%-20s',str1);
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for i=1:nvar
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x = dr.ghxu(ivar(i),(k-1)*nu+j);
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if abs(x) > 1e-6
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flag = 1;
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str = [str sprintf('%16.6f',x)];
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else
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str = [str ' 0'];
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end
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end
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if flag
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disp(str)
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end
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end
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end
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end
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end
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% Given the index of an endogenous (possibly an auxiliary var), and a
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% lead/lag, creates a string of the form "x(lag)".
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% In the case of auxiliary vars for lags, replace by the original variable
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% name, and compute the lead/lag accordingly.
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function str = subst_auxvar(aux_index, aux_lead_lag)
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global M_
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if aux_index <= M_.orig_endo_nbr
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str = sprintf('%s(%d)', deblank(M_.endo_names(aux_index,:)), aux_lead_lag);
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return
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end
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for i = 1:length(M_.aux_vars)
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if M_.aux_vars(i).endo_index == aux_index
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switch M_.aux_vars(i).type
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case 1
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orig_name = deblank(M_.endo_names(M_.aux_vars(i).orig_index, :));
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case 3
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orig_name = deblank(M_.exo_names(M_.aux_vars(i).orig_index, :));
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otherwise
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error(sprintf('Invalid auxiliary type: %s', M_.endo_names(aux_index, :)))
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end
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str = sprintf('%s(%d)', orig_name, M_.aux_vars(i).orig_lead_lag+aux_lead_lag);
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return
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end
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end
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error(sprintf('Could not find aux var: %s', M_.endo_names(aux_index, :)))
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end
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