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Complete the bug fix for the calibrated correlations in the structural and measurement covariance matrices. 

Call   set_all_parameters  routine   in  dsge_likelihood.   Note  that
correlations between innovations are not allowed in dsge-var models.
time-shift
Stéphane Adjemian (Charybdis) 2012-06-07 15:12:10 +02:00
parent 0da05ae29d
commit 06ca265272
1 changed files with 4 additions and 38 deletions
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42
matlab/dsge_likelihood.m
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@ -209,31 +209,13 @@ if ~isequal(DynareOptions.mode_compute,1) && any(xparam1>BayesInfo.ub)
end
% Get the diagonal elements of the covariance matrices for the structural innovations (Q) and the measurement error (H).
Model = set_all_parameters(xparam1,EstimatedParameters,Model);
Q = Model.Sigma_e;
H = Model.H;
for i=1:EstimatedParameters.nvx
k =EstimatedParameters.var_exo(i,1);
Q(k,k) = xparam1(i)*xparam1(i);
end
offset = EstimatedParameters.nvx;
if EstimatedParameters.nvn
for i=1:EstimatedParameters.nvn
k = EstimatedParameters.var_endo(i,1);
H(k,k) = xparam1(i+offset)*xparam1(i+offset);
end
offset = offset+EstimatedParameters.nvn;
else
H = zeros(DynareDataset.info.nvobs);
end
% Get the off-diagonal elements of the covariance matrix for the structural innovations. Test if Q is positive definite.
% Test if Q is positive definite.
if EstimatedParameters.ncx
for i=1:EstimatedParameters.ncx
k1 =EstimatedParameters.corrx(i,1);
k2 =EstimatedParameters.corrx(i,2);
Q(k1,k2) = xparam1(i+offset)*sqrt(Q(k1,k1)*Q(k2,k2));
Q(k2,k1) = Q(k1,k2);
end
% Try to compute the cholesky decomposition of Q (possible iff Q is positive definite)
[CholQ,testQ] = chol(Q);
if testQ
@ -247,17 +229,10 @@ if EstimatedParameters.ncx
return
end
end
offset = offset+EstimatedParameters.ncx;
end
% Get the off-diagonal elements of the covariance matrix for the measurement errors. Test if H is positive definite.
% Test if H is positive definite.
if EstimatedParameters.ncn
for i=1:EstimatedParameters.ncn
k1 = DynareOptions.lgyidx2varobs(EstimatedParameters.corrn(i,1));
k2 = DynareOptions.lgyidx2varobs(EstimatedParameters.corrn(i,2));
H(k1,k2) = xparam1(i+offset)*sqrt(H(k1,k1)*H(k2,k2));
H(k2,k1) = H(k1,k2);
end
% Try to compute the cholesky decomposition of H (possible iff H is positive definite)
[CholH,testH] = chol(H);
if testH
@ -271,17 +246,8 @@ if EstimatedParameters.ncn
return
end
end
offset = offset+EstimatedParameters.ncn;
end
% Update estimated structural parameters in Mode.params.
if EstimatedParameters.np > 0
Model.params(EstimatedParameters.param_vals(:,1)) = xparam1(offset+1:end);
end
% Update Model.Sigma_e and Model.H.
Model.Sigma_e = Q;
Model.H = H;
%------------------------------------------------------------------------------
% 2. call model setup & reduction program