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 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138
|
function oo_ = initial_condition_decomposition(M_,oo_,options_,varlist,bayestopt_,estim_params_)
% function oo_ = initial_condition_decomposition(M_,oo_,options_,varlist,bayestopt_,estim_params_)
% Computes initial condition contribution to a simulated trajectory. The field set is
% oo_.initval_decomposition. It is a n_var by n_var+2 by nperiods array. The
% first n_var columns store the respective endogenous initval contribution, column n+1
% stores the role of the shocks, while column n+2 stores the
% value of the smoothed variables. Variables are stored
% in the order of declaration, i.e. M_.endo_names.
%
% INPUTS
% M_: [structure] Definition of the model
% oo_: [structure] Storage of results
% options_: [structure] Options
% varlist: [char] List of variables
% bayestopt_: [structure] describing the priors
% estim_params_: [structure] characterizing parameters to be estimated
%
% OUTPUTS
% oo_: [structure] Storage of results
%
% SPECIAL REQUIREMENTS
% none
% 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/>.
options_.plot_shock_decomp.detail_plot = options_.initial_condition_decomp.detail_plot;
options_.plot_shock_decomp.steadystate = options_.initial_condition_decomp.steadystate;
options_.plot_shock_decomp.write_xls = options_.initial_condition_decomp.write_xls;
options_.plot_shock_decomp.type = options_.initial_condition_decomp.type;
options_.plot_shock_decomp.plot_init_date = options_.initial_condition_decomp.plot_init_date;
options_.plot_shock_decomp.plot_end_date = options_.initial_condition_decomp.plot_end_date;
% indices of endogenous variables
if size(varlist,1) == 0
varlist = M_.endo_names(1:M_.orig_endo_nbr,:);
end
[i_var,nvar,index_uniques] = varlist_indices(varlist,M_.endo_names);
varlist=varlist(index_uniques,:);
% number of variables
endo_nbr = M_.endo_nbr;
% parameter set
parameter_set = options_.parameter_set;
if isempty(parameter_set)
if isfield(oo_,'posterior_mean')
parameter_set = 'posterior_mean';
elseif isfield(oo_,'mle_mode')
parameter_set = 'mle_mode';
elseif isfield(oo_,'posterior')
parameter_set = 'posterior_mode';
else
error(['shock_decomposition: option parameter_set is not specified ' ...
'and posterior mode is not available'])
end
end
if ~isfield(oo_,'initval_decomposition')
options_.selected_variables_only = 0; %make sure all variables are stored
options_.plot_priors=0;
[oo,M,junk1,junk2,Smoothed_Variables_deviation_from_mean] = evaluate_smoother(parameter_set,varlist,M_,oo_,options_,bayestopt_,estim_params_);
% reduced form
dr = oo.dr;
% data reordering
order_var = dr.order_var;
inv_order_var = dr.inv_order_var;
% coefficients
A = dr.ghx;
B = dr.ghu;
% initialization
gend = size(oo.SmoothedShocks.(deblank(M_.exo_names(1,:))),1); %+options_.forecast;
z = zeros(endo_nbr,endo_nbr+2,gend);
z(:,end,:) = Smoothed_Variables_deviation_from_mean;
for i=1:endo_nbr
z(i,i,1) = Smoothed_Variables_deviation_from_mean(i,1);
end
maximum_lag = M_.maximum_lag;
k2 = dr.kstate(find(dr.kstate(:,2) <= maximum_lag+1),[1 2]);
i_state = order_var(k2(:,1))+(min(i,maximum_lag)+1-k2(:,2))*M_.endo_nbr;
for i=1:gend
if i > 1 && i <= maximum_lag+1
lags = min(i-1,maximum_lag):-1:1;
end
if i > 1
tempx = permute(z(:,1:endo_nbr,lags),[1 3 2]);
m = min(i-1,maximum_lag);
tempx = [reshape(tempx,endo_nbr*m,endo_nbr); zeros(endo_nbr*(maximum_lag-i+1),endo_nbr)];
z(:,1:endo_nbr,i) = A(inv_order_var,:)*tempx(i_state,:);
lags = lags+1;
end
z(:,endo_nbr+1,i) = z(:,endo_nbr+2,i) - sum(z(:,1:endo_nbr,i),2);
end
oo_.initval_decomposition = z;
end
% if ~options_.no_graph.shock_decomposition
oo=oo_;
oo.shock_decomposition = oo_.initval_decomposition;
M_.exo_names = M_.endo_names;
M_.exo_nbr = M_.endo_nbr;
options_.plot_shock_decomp.realtime=0;
options_.plot_shock_decomp.screen_shocks=1;
options_.plot_shock_decomp.use_shock_groups = '';
fig_name = options_.plot_shock_decomp.fig_name;
if ~isempty(fig_name)
options_.plot_shock_decomp.fig_name=[fig_name '_initval'];
else
options_.plot_shock_decomp.fig_name='initval';
end
plot_shock_decomposition(M_,oo,options_,varlist);
% end
|