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

Bayesian FAVARs with Agnostic Identification 93
’SFYGT5’,’SFYGT10’,’SFYAAAC’,’SFYBAAC’,’FM1’,’FM2’,’FM3’,’FM2DQ’,’FMFBA’,’FMRRA’,’FMRNBA’,’FCLNQ’, ...
’FCLBMC’,’CCINRV’,’PMCP’,’PWSFA’,’PWFCSA’,’PWIMSA’,’PWCMSA’,’PSM99Q’,’PUNEW’,’PU83’,’PU84’,’PU85’, ...
’PUC’,’PUCD’,’PUS’,’PUXF’,’PUXHS’,’PUXM’,’LEHCC’,’LEHM’,’HHSNTN’};
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%%%%%% Bayesian FAVAR Code August 26th %%%%%
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%%%%%% DO _INPUT_STARTINGVALUES %%%%%
%%%%%% see Sequence Diagram Block A.5 %%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%% Returns starting values for all variables included in
%%%%%% the input.startingvalues structure. These are F, lam_f,
%%%%%% lam_y, R, Phi_lags and Q.
%%%%%%
%%%%%% startingvalues
%%%%%% |---------- F
%%%%%% |---------- lam_f
%%%%%% |---------- lam_y
%%%%%% |---------- R
%%%%%% |---------- Phi_lags
%%%%%% |---------- Q
function [startingvalues] = DO_INPUT_STARTINGVALUES (input)
%function [startingvalues] = DO_INPUT_STARTINGVALUES (input)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’% %
%’’’ function Get_Starting_Values = [Input_Structure] ’’’% %
%’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’’% %
% %
%switch mode ==1 %
% case Get_Starting_Values(Generated) %
% Statement 1 %
% case Get_Starting_Values(Dispersed distribution) %
% Statement 2 %
% case Get_Starting_Values(zero_values) %
% Statement 3 %
% otherwise %
% Statement 4 %
% break %
%end; %switch %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
X_st = input.xdata ./ repmat(std(input.xdata,1),input.specification.dim.T,1);
Y_st = input.specification.y ./ repmat(std(input.specification.y,1),input.specification.dim.T,1);
% first step - extract PC from X
[F,lam_f] = extract(X_st,input.specification.model.K);
% regress X on F0 and Y, obtain loadings
Lfy = olssvd(X_st(:,input.specification.model.K+1:input.specification.dim.N),[F Y_st])’;
% upper KxM block of Ly set to zero
lam_f=[lam_f(1:input.specification.model.K,:);Lfy(:,1:input.specification.model.K)];
lam_y=[zeros(input.specification.model.K,input.specification.dim.M);...
Lfy(:,input.specification.model.K+1:input.specification.model.K+input.specification.dim.M)];
% transform factors and loadings for LE normalization
[ql,rl]=qr(lam_f’);
lam_f=rl; % do not transpose yet, is upper triangular