From 6d6174d6aeb84920cc0e0c573baf280684680b1c Mon Sep 17 00:00:00 2001
From: adjemian <adjemian@ac1d8469-bf42-47a9-8791-bf33cf982152>
Date: Fri, 6 Jul 2007 14:43:00 +0000
Subject: [PATCH] Added a penalty when the bvar-dsge prior is not proper (too
 small values of dsge_prior_weight).

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1343 ac1d8469-bf42-47a9-8791-bf33cf982152
---
 matlab/DsgeVarLikelihood.m | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/matlab/DsgeVarLikelihood.m b/matlab/DsgeVarLikelihood.m
index b10f44cae..83ca820bc 100644
--- a/matlab/DsgeVarLikelihood.m
+++ b/matlab/DsgeVarLikelihood.m
@@ -103,6 +103,7 @@ M_.Sigma_e = Q;
 %% Weight of the dsge prior:
 dsge_prior_weight = M_.params(strmatch('dsge_prior_weight',M_.param_names));
 
+
 %------------------------------------------------------------------------------
 % 2. call model setup & reduction program
 %------------------------------------------------------------------------------
@@ -142,6 +143,12 @@ NumberOfObservedVariables = size(options_.varobs,1);
 NumberOfLags = options_.varlag;
 k = NumberOfObservedVariables*NumberOfLags ;
 
+if dsge_prior_weight<(k+NumberOfObservedVariables)/nobs;
+    fval = bayestopt_.penalty*min(1e3,(k+NumberOfObservedVariables)/nobs-dsge_prior_weight);
+    cost_flag = 0;
+    return;
+end
+
 TheoreticalAutoCovarianceOfTheObservedVariables = ...
     zeros(NumberOfObservedVariables,NumberOfObservedVariables,NumberOfLags+1);
 TheoreticalAutoCovarianceOfTheObservedVariables(:,:,1) = tmp(mf,mf);