This function computes the conditional variance decomposition of a given state space model
for a subset of endogenous variables.
INPUTS
StateSpaceModel [structure] Specification of the state space model.
Steps [integer] 1*h vector of dates.
SubsetOfVariables [integer] 1*q vector of indices.
OUTPUTS
PackedConditionalVarianceDecomposition [double] n(n+1)/2*p matrix, where p is the number of state innovations and
n is equal to length(SubsetOfVariables).
SPECIAL REQUIREMENTS
[1] The covariance matrix of the state innovations needs to be diagonal.
[2] In this version, absence of measurement errors is assumed...0001 function oo_ = display_conditional_variance_decomposition(Steps, SubsetOfVariables, dr,M_,options_,oo_) 0002 % This function computes the conditional variance decomposition of a given state space model 0003 % for a subset of endogenous variables. 0004 % 0005 % INPUTS 0006 % StateSpaceModel [structure] Specification of the state space model. 0007 % Steps [integer] 1*h vector of dates. 0008 % SubsetOfVariables [integer] 1*q vector of indices. 0009 % 0010 % OUTPUTS 0011 % PackedConditionalVarianceDecomposition [double] n(n+1)/2*p matrix, where p is the number of state innovations and 0012 % n is equal to length(SubsetOfVariables). 0013 % 0014 % SPECIAL REQUIREMENTS 0015 % 0016 % [1] The covariance matrix of the state innovations needs to be diagonal. 0017 % [2] In this version, absence of measurement errors is assumed... 0018 0019 % Copyright (C) 2010-2011 Dynare Team 0020 % 0021 % This file is part of Dynare. 0022 % 0023 % Dynare is free software: you can redistribute it and/or modify 0024 % it under the terms of the GNU General Public License as published by 0025 % the Free Software Foundation, either version 3 of the License, or 0026 % (at your option) any later version. 0027 % 0028 % Dynare is distributed in the hope that it will be useful, 0029 % but WITHOUT ANY WARRANTY; without even the implied warranty of 0030 % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 0031 % GNU General Public License for more details. 0032 % 0033 % You should have received a copy of the GNU General Public License 0034 % along with Dynare. If not, see <http://www.gnu.org/licenses/>. 0035 0036 endo_nbr = M_.endo_nbr; 0037 exo_nbr = M_.exo_nbr; 0038 StateSpaceModel.number_of_state_equations = M_.endo_nbr; 0039 StateSpaceModel.number_of_state_innovations = exo_nbr; 0040 StateSpaceModel.sigma_e_is_diagonal = M_.sigma_e_is_diagonal; 0041 0042 iv = (1:endo_nbr)'; 0043 ic = dr.nstatic+(1:dr.npred)'; 0044 0045 [StateSpaceModel.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,iv,ic,exo_nbr); 0046 StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e; 0047 StateSpaceModel.order_var = dr.order_var; 0048 0049 conditional_decomposition_array = conditional_variance_decomposition(StateSpaceModel,Steps,SubsetOfVariables ); 0050 0051 if options_.noprint == 0 0052 disp(' ') 0053 disp('CONDITIONAL VARIANCE DECOMPOSITION (in percent)') 0054 end 0055 0056 vardec_i = zeros(length(SubsetOfVariables),exo_nbr); 0057 0058 for i=1:length(Steps) 0059 disp(['Period ' int2str(Steps(i)) ':']) 0060 0061 for j=1:exo_nbr 0062 vardec_i(:,j) = 100*conditional_decomposition_array(:, ... 0063 i,j); 0064 end 0065 if options_.noprint == 0 0066 headers = M_.exo_names; 0067 headers(M_.exo_names_orig_ord,:) = headers; 0068 headers = char(' ',headers); 0069 lh = size(deblank(M_.endo_names(SubsetOfVariables,:)),2)+2; 0070 dyntable('',headers,... 0071 deblank(M_.endo_names(SubsetOfVariables,:)),... 0072 vardec_i,lh,8,2); 0073 end 0074 end 0075 0076 oo_.conditional_variance_decomposition = conditional_decomposition_array;