Measuring the Effects of a Shock to Monetary Policy - Humboldt ...

102 Bayesian FAVARs with Agnostic Identification
end%for
F_reg = F_reg(:,:);
F_reg = F_reg(d+1:T,:);
% For doing inference on the Transition equation one has to first draw Q and the draw vec(Phi)
% Note that for generalization it is good to write [kappa1_prior,kappa2_prior; kappa1_post and kappa1_post]
% shortcuts
VV = V_hat’*V_hat;
FF_reg = inv(F_reg’*F_reg);
Phi_FF = inv(Omega_prior + FF_reg);
% Draw posterior Q
Q_bar = Q_prior + VV + Phi_hat’*Phi_FF*Phi_hat;
kappa1_prior = K+M+2;
kappa1_post = T+kappa1_prior;
kappa2_prior = Q_prior;
kappa2_post = Q_bar; % Scale Matrix
% Inverse Wishart draw
% df = degrees of freedom
%QW = wishrnd(inv(kappa2_post),kappa1_post);
%Q_draw = inv(QW); % =1 % 0.999
end
vec_Phi_draw = mvnrnd(vecPhi_posterior,sigma_Phi,1);
Phi_draw = reshape(vec_Phi_draw’,d*(K+M),(K+M))’;
calculation.stateSpaceStructure.Phi_bar(1:K+M,:) = Phi_draw;
Phi_draw = reshape(Phi_draw,K+M,K+M,d);
%%%%% set param_prec_obs output structure
param_prec_fac.Q_draw = Q_draw;
param_prec_fac.Phi_draw = Phi_draw;
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%%%%%% Bayesian FAVAR Code August 26th %%%%%