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function dynare_estimation(var_list,dname)
% function dynare_estimation(var_list)
% runs the estimation of the model
%
% INPUTS
% var_list: selected endogenous variables vector
%
% OUTPUTS
% none
%
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2012 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 options_ oo_ M_ oo_recursive_
%% Decide if a DSGE or DSGE-VAR has to be estimated.
if ~isempty(strmatch('dsge_prior_weight',M_.param_names))
options_.dsge_var = 1;
end
var_list = check_list_of_variables(options_, M_, var_list);
options_.varlist = var_list;
if isfield(options_,'nobs')
nobs = options_.nobs;
else
nobs = [];
end
nnobs = length(nobs);
horizon = options_.forecast;
if nargin<2 || ~exist(dname) || isempty(dname)
dname = M_.fname;
end
M_.dname = dname;
if options_.mode_compute && options_.analytic_derivation,
analytic_derivation0=options_.analytic_derivation;
options_.analytic_derivation=1;
end
if nnobs > 1
for i=1:nnobs
options_.nobs = nobs(i);
M_.dname = [dname '_' int2str(nobs(i))];
dynare_estimation_1(var_list,M_.dname);
oo_recursive_{nobs(i)} = oo_;
end
else
dynare_estimation_1(var_list,dname);
end
if options_.mode_compute && options_.analytic_derivation,
options_.analytic_derivation=analytic_derivation0;
end
if nnobs > 1 && horizon > 0
mh_replic = options_.mh_replic;
rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
gend = options_.nobs;
rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
% Take the log of the variables if needed
if options_.loglinear && ~options_.logdata % and if the data are not in logs, then...
rawdata = log(rawdata);
end
endo_names = M_.endo_names;
n_varobs = size(options_.varobs,1);
if isempty(var_list)
var_list = endo_names;
nvar = size(endo_names,1);
SelecVariables = transpose(1:nvar);
else
nvar = size(var_list,1);
SelecVariables = [];
for i=1:nvar
if ~isempty(strmatch(var_list(i,:),endo_names,'exact'))
SelecVariables = [SelecVariables;strmatch(var_list(i,:),endo_names, ...
'exact')];
else
error(['Estimation: ' var_list(i,:) ' isn''t an endogenous' ...
'variable'])
end
end
end
IdObs = zeros(n_varobs,1);
for j=1:n_varobs
for i=1:nvar
iobs = strmatch(options_.varobs(j,:),var_list,'exact');
end
if ~isempty(iobs)
IdObs(j,1) = iobs;
end
end
k = 3+min(nobs(end)-nobs(1)+horizon, ...
size(rawdata,1)-nobs(1));
data2 = rawdata(end-k+1:end,:);
[nbplt,nr,nc,lr,lc,nstar] = pltorg(nvar);
m = 1;
for i = 1:size(var_list,1)
if mod(i,nstar) == 1
hfig = dyn_figure(options_,'Name','Out of sample forecasts');
m = 1;
end
subplot(nr,nc,m)
hold on
if any(i==IdObs)
k2 = find(i==IdObs);
if options_.loglinear == 1
plot(1:k,exp(data2(end-k+1:end,k2))','-k','linewidth',2);
else
plot(1:k,data2(end-k+1:end,k2)','-k','linewidth',2);
end
offsetx = 3;
else
offsetx = 0;
end
vname = deblank(var_list(i,:));
maxlag = M_.maximum_lag;
for j=1:nnobs
if mh_replic > 0
eval(['oo_.RecursiveForecast.Mean.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.MeanForecast.Mean.' ...
vname '(maxlag+1:end);']);
eval(['oo_.RecursiveForecast.HPDinf.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.MeanForecast.HPDinf.' ...
vname '(maxlag+1:end);']);
eval(['oo_.RecursiveForecast.HPDsup.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.MeanForecast.HPDsup.' ...
vname '(maxlag+1:end);']);
eval(['oo_.RecursiveForecast.HPDTotalinf.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.PointForecast.HPDinf.' ...
vname '(maxlag+1:end);']);
eval(['oo_.RecursiveForecast.HPDTotalsup.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.PointForecast.HPDsup.' ...
vname '(maxlag+1:end);']);
else
eval(['oo_.RecursiveForecast.Mean.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.forecast.Mean.' ...
vname ';']);
eval(['oo_.RecursiveForecast.HPDinf.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.forecast.HPDinf.' ...
vname ';']);
eval(['oo_.RecursiveForecast.HPDsup.' vname '(j,:) =' ...
'oo_recursive_{' int2str(nobs(j)) '}.forecast.HPDsup.' ...
vname ';']);
end
x = offsetx+nobs(j)-nobs(1)+(1:horizon);
y = eval(['oo_.RecursiveForecast.Mean.' vname '(j,:)']);
y1 = eval(['oo_.RecursiveForecast.HPDinf.' vname '(j,:)']);
y2 = eval(['oo_.RecursiveForecast.HPDsup.' vname '(j,:)']);
plot(x,y,'-b','linewidth',2)
plot(x,y1,'--g', ...
'linewidth',1.5)
plot(x,y2,'--g', ...
'linewidth',1.5)
if mh_replic
y3 = eval(['oo_.RecursiveForecast.HPDTotalinf.' vname '(j,:)']);
y4 = eval(['oo_.RecursiveForecast.HPDTotalsup.' vname ...
'(j,:)']);
plot(x,y3,'--r', ...
'linewidth',1.5)
plot(x,y4,'--r','linewidth',1.5)
end
end
% set(gca,'XTick',offsetx+[1 10 20 30 40 50 60 70 80 90]);
% set(gca,'XTickLabel',{'1';'10';'20';'30';'40';'50';'60';'70';'80';'90'});
% xlim([1 options_.forecast+10]);
if any(k==IdObs)
plot([offsetx+1 offsetx+1],ylim,'-c')
end
box on
title(vname,'Interpreter','none')
hold off
m = m + 1;
end
end
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