From cfd82e28e483ff2aaf78c85212fc1c4dd40e95aa Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?St=C3=A9phane=20Adjemian=20=28Charybdis=29?=
 <stephane.adjemian@univ-lemans.fr>
Date: Thu, 18 May 2017 13:43:13 +0200
Subject: [PATCH] Added routine computing IRFs of backward looking model.

(cherry picked from commit 647505526afe93978c419c9a6dde22b664120ef3)
---
 matlab/backward/backward_model_irf.m | 112 +++++++++++++++++++++++++++
 1 file changed, 112 insertions(+)
 create mode 100644 matlab/backward/backward_model_irf.m

diff --git a/matlab/backward/backward_model_irf.m b/matlab/backward/backward_model_irf.m
new file mode 100644
index 000000000..3ee05024b
--- /dev/null
+++ b/matlab/backward/backward_model_irf.m
@@ -0,0 +1,112 @@
+function irfs = backward_model_irf(initialcondition, listofshocks, listofvariables, periods, transform)
+
+% Returns impulse response functions.
+%
+% INPUTS 
+% - initialcondition    [dseries]             Initial conditions for the endogenous variables.
+% - listofshocks        [cell of strings]     The innovations for which the IRFs need to be computed.  
+% - listofvariables     [cell of strings]     The endogenous variables which will be returned.  
+% - periods             [integer]             scalar, the number of periods.
+%
+% OUTPUTS 
+% - irfs                [struct of dseries]   
+%
+% REMARKS 
+% The names of the fields in the returned structure are given by the name
+% of the innovations listed in the second input argument. Each field gather
+% the associated paths for endogenous variables listed in the third input 
+% argument. 
+
+
+% Copyright (C) 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 <http://www.gnu.org/licenses/>.
+
+global M_ options_ oo_
+
+% Check that the model is actually backward
+if M_.maximum_lead
+    error(['simul_model_irf:: The specified model is not backward looking!'])
+end
+
+% Set the number of innovations and variables for which we want to compute the IRFs.
+nx = length(listofshocks);
+ny = length(listofvariables);
+
+% Initialization of the returned argument. Each will be a dseries
+% object containing the IRFS for the endogenous variables listed in the
+% third input argument.
+irfs = struct();
+
+% Set default value for the fourth input argument.
+if nargin<4
+    periods = 40;
+    notransform = true;
+end
+
+% Set default value for the last input argument (no transformation).
+if nargin<5
+    notransform = true;
+else
+    notransform = false;
+end
+
+% Get list of all exogenous variables in a cell of strings
+exo_names = cellstr(M_.exo_names);
+
+% Get the list of all exogenous variables in a cell of strings
+endo_names = cellstr(M_.endo_names);
+
+% Set initial condition.
+if isdates(initialcondition)
+    if isempty(M_.endo_histval)
+        error('backward_model_irf: histval block for setting initial condition is missing!')
+    end
+    initialcondition = dseries(transpose(M_.endo_histval), initialcondition, endo_names, cellstr(M_.endo_names_tex));
+end
+
+% Get the covariance matrix of the shocks.
+Sigma = M_.Sigma_e + 1e-14*eye(M_.exo_nbr);
+sigma = transpose(chol(Sigma));
+
+% Put initial conditions in a vector of doubles
+initialconditions = transpose(initialcondition{endo_names{:}}.data);
+
+% Compute the IRFs (loop over innovations).
+for i=1:length(listofshocks)
+    % Get transition paths induced by the initial condition.
+    innovations = zeros(periods+1, M_.exo_nbr);
+    oo__0 = simul_backward_model(initialconditions, periods, options_, M_, oo_, innovations);
+    % Add the shock.
+    j = strmatch(listofshocks{i}, exo_names);
+    if isempty(j)
+        error('backward_model_irf: Exogenous variable %s is unknown!', listofshocks{i})
+    end
+    innovations(2,:) = transpose(sigma(:,j));
+    oo__1 = simul_backward_model(initialconditions, periods, options_, M_, oo_, innovations);
+    % Transform the endogenous variables
+        if notransform
+        endo_simul__0 = oo__0.endo_simul;
+        endo_simul__1 = oo__1.endo_simul;
+    else
+        endo_simul__0 = feval(transform, oo__0.endo_simul);
+        endo_simul__1 = feval(transform, oo__1.endo_simul);
+    end
+    % Instantiate a dseries object (with all the endogenous variables)
+    allirfs = dseries(transpose(endo_simul__1-endo_simul__0), initialcondition.init, cellstr(M_.endo_names), cellstr(M_.endo_names_tex));
+    % Extract a sub-dseries object
+    irfs.(listofshocks{i}) = allirfs{listofvariables{:}};
+end
\ No newline at end of file