diff --git a/matlab/dsge_likelihood.m b/matlab/dsge_likelihood.m
index 83e64fbae..13f79ed6d 100644
--- a/matlab/dsge_likelihood.m
+++ b/matlab/dsge_likelihood.m
@@ -660,7 +660,7 @@ end
 %------------------------------------------------------------------------------
 
 singularity_has_been_detected = false;
-
+% First test multivariate filter if specified; potentially abort and use univariate filter instead
 if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
     if no_missing_data_flag
         if DynareOptions.block
@@ -824,6 +824,14 @@ if imag(LIK)~=0
     return
 end
 
+if isinf(LIK)~=0
+    fval = Inf;
+    info(1) = 50;
+    info(4) = 0.1;
+    exit_flag = 0;
+    return
+end
+
 likelihood = LIK;
 
 % ------------------------------------------------------------------------------
diff --git a/matlab/dsge_var_likelihood.m b/matlab/dsge_var_likelihood.m
index d5f09994c..ca3a86d2f 100644
--- a/matlab/dsge_var_likelihood.m
+++ b/matlab/dsge_var_likelihood.m
@@ -308,6 +308,14 @@ if imag(fval)~=0
     return
 end
 
+if isinf(fval)~=0
+    fval = Inf;
+    info(1) = 50;
+    info(4) = 0.1;
+    exit_flag = 0;
+    return
+end
+
 if (nargout >= 10)
     if isinf(dsge_prior_weight)
         iXX = iGXX;
diff --git a/matlab/non_linear_dsge_likelihood.m b/matlab/non_linear_dsge_likelihood.m
index 120b8e857..34ed485c4 100644
--- a/matlab/non_linear_dsge_likelihood.m
+++ b/matlab/non_linear_dsge_likelihood.m
@@ -367,3 +367,12 @@ if imag(fval)~=0
     exit_flag = 0;
     return
 end
+
+if isinf(LIK)~=0
+    fval = Inf;
+    info(1) = 50;
+    info(4) = 0.1;
+    exit_flag = 0;
+    return
+end
+
diff --git a/matlab/print_info.m b/matlab/print_info.m
index 795ecbd2d..e9985998d 100644
--- a/matlab/print_info.m
+++ b/matlab/print_info.m
@@ -116,6 +116,8 @@ if ~noprint
         error('Prior density is a complex number');
       case 49
         error('The model violates one (many) endogenous prior restriction(s)')
+      case 50
+        error('Likelihood is Inf')        
       case 51
         fprintf('\n The dsge_prior_weight is dsge_var=%5.4f, but must be at least %5.4f for the prior to be proper.\n',info(2),info(3));
         error('You are estimating a DSGE-VAR model, but the value of the dsge prior weight is too low!')