/usr/share/dynare/matlab/ep_residuals.m is in dynare-common 4.4.1-1build1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | function r = ep_residuals(x, y, ix, iy, steadystate, dr, maximum_lag, endo_nbr)
% Inversion of the extended path simulation approach. This routine computes the innovations needed to
% reproduce the time path of a subset of endogenous variables.
%
% INPUTS
% o x [double] n*1 vector, time t innovations.
% o y [double] n*1 vector, time t restricted endogenous variables.
% o ix [integer] index of control innovations in the full vector of innovations.
% o iy [integer] index of controlled variables in the full vector of endogenous variables.
% o s [double] m*1 vector, endogenous variables at time t-1.
%
%
% OUTPUTS
% o r [double] n*1 vector of residuals.
%
% ALGORITHM
%
% SPECIAL REQUIREMENTS
% Copyright (C) 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/>.
global oo_
persistent k1 k2 weight
if isempty(k1)
k1 = [maximum_lag:-1:1];
k2 = dr.kstate(find(dr.kstate(:,2) <= maximum_lag+1),[1 2]);
k2 = k2(:,1)+(maximum_lag+1-k2(:,2))*endo_nbr;
weight = 0.0;
end
verbose = 0;
% Copy the shocks in exo_simul.
oo_.exo_simul(maximum_lag+1,ix) = exp(transpose(x));
exo_simul = log(oo_.exo_simul);
% Compute the initial solution path for the endogenous variables using a first order approximation.
if verbose
disp('ep_residuals:: Set initial condition for endogenous variable paths.')
end
initial_path = oo_.endo_simul;
for i = maximum_lag+1:size(oo_.exo_simul)
tempx1 = oo_.endo_simul(dr.order_var,k1);
tempx2 = bsxfun(@minus,tempx1,dr.ys(dr.order_var));
tempx = tempx2(k2);
initial_path(dr.order_var,i) = dr.ys(dr.order_var)+dr.ghx*tempx2(k2)+dr.ghu*transpose(exo_simul(i,:));
k1 = k1+1;
end
oo_.endo_simul = weight*initial_path + (1-weight)*oo_.endo_simul;
info = perfect_foresight_simulation(dr,steadystate);
if verbose>1
info
info.iterations.errors
end
r = y-transpose(oo_.endo_simul(maximum_lag+1,iy));
%(re)Set k1 (indices for the initial conditions)
k1 = [maximum_lag:-1:1];
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