diff --git a/matlab/PosteriorIRF_core1.m b/matlab/PosteriorIRF_core1.m
index e2cc4a52095a57932b055b97cac962c5d469fc94..1eff387ad64115fcce0e12710c2136ebc612bbc5 100644
--- a/matlab/PosteriorIRF_core1.m
+++ b/matlab/PosteriorIRF_core1.m
@@ -189,7 +189,7 @@ while fpar<B
     end
     if MAX_nirfs_dsgevar
         IRUN = IRUN+1;
-        [fval,junk1,junk2,cost_flag,info,PHI,SIGMAu,iXX] =  DsgeVarLikelihood(deep',dataset_,options_,M_,estim_params_,bayestopt_,oo_);
+        [fval,junk1,junk2,cost_flag,info,PHI,SIGMAu,iXX] =  dsge_var_likelihood(deep',dataset_,options_,M_,estim_params_,bayestopt_,oo_);
         dsge_prior_weight = M_.params(strmatch('dsge_prior_weight',M_.param_names));
         DSGE_PRIOR_WEIGHT = floor(dataset_.info.ntobs*(1+dsge_prior_weight));
         SIGMA_inv_upper_chol = chol(inv(SIGMAu*dataset_.info.ntobs*(dsge_prior_weight+1)));
diff --git a/matlab/csminwel1.m b/matlab/csminwel1.m
index 403b9a58ed2a325cc7c22102f8c9b0f19ab95b4f..b6e38fedc0f6f0b9d61474e6a0a18b25cfd108d6 100644
--- a/matlab/csminwel1.m
+++ b/matlab/csminwel1.m
@@ -100,7 +100,7 @@ f=f0;
 H=H0;
 cliff=0;
 while ~done
-    % penalty for dsge_likelihood and DsgeVarLikelihood
+    % penalty for dsge_likelihood and dsge_var_likelihood
     objective_function_penalty_base = f;
 
     g1=[]; g2=[]; g3=[];
diff --git a/matlab/DsgeVarLikelihood.m b/matlab/dsge_var_likelihood.m
similarity index 98%
rename from matlab/DsgeVarLikelihood.m
rename to matlab/dsge_var_likelihood.m
index 322351a2c14ccb2960987ec76c631d564bdc467e..6c37fd1a468cc7ac4e586075e727ffbc059950fd 100644
--- a/matlab/DsgeVarLikelihood.m
+++ b/matlab/dsge_var_likelihood.m
@@ -1,4 +1,4 @@
-function [fval,grad,hess,exit_flag,info,PHI,SIGMAu,iXX,prior] = DsgeVarLikelihood(xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults)
+function [fval,grad,hess,exit_flag,info,PHI,SIGMAu,iXX,prior] = dsge_var_likelihood(xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults)
 % Evaluates the posterior kernel of the bvar-dsge model.
 %
 % INPUTS
diff --git a/matlab/dsgevar_posterior_density.m b/matlab/dsgevar_posterior_density.m
index 9ff74e1451dbd6d99f343340b9c324d8e55aa7f2..eca70f743903bc6961f3c217b9f152555b684eb6 100644
--- a/matlab/dsgevar_posterior_density.m
+++ b/matlab/dsgevar_posterior_density.m
@@ -47,7 +47,7 @@ if ~options_.noconstant
         bvar.NumberOfVariables;
 end
 
-[fval,cost_flag,info,PHI,SIGMAu,iXX,prior] =  DsgeVarLikelihood(deep',DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults);
+[fval,cost_flag,info,PHI,SIGMAu,iXX,prior] =  dsge_var_likelihood(deep',DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults);
 
 % Conditionnal posterior density of the lagged matrices (given Sigma) ->
 % Matric-variate normal distribution.
diff --git a/matlab/dynare_estimation_1.m b/matlab/dynare_estimation_1.m
index 80dee69cf5cc40c23050a98ec06e7316656014ea..f6df44b87e31fed0f8cc79203bab1d4a554b46a9 100644
--- a/matlab/dynare_estimation_1.m
+++ b/matlab/dynare_estimation_1.m
@@ -75,7 +75,7 @@ if ~options_.dsge_var
         objective_function = str2func('dsge_likelihood');
     end
 else
-    objective_function = str2func('DsgeVarLikelihood');
+    objective_function = str2func('dsge_var_likelihood');
 end
 
 [dataset_,xparam1, hh, M_, options_, oo_, estim_params_,bayestopt_] = dynare_estimation_init(var_list_, dname, [], M_, options_, oo_, estim_params_, bayestopt_);
diff --git a/matlab/print_info.m b/matlab/print_info.m
index c96910e3c14ad2953d479bda350ff8a54e8ad404..ab71479c41a7c1d239e54e4b68d8501f664e74b9 100644
--- a/matlab/print_info.m
+++ b/matlab/print_info.m
@@ -106,7 +106,7 @@ if ~noprint
         error('The model violates one (many) endogenous prior restriction(s)')
       case 51
         error('You are estimating a DSGE-VAR model, but the value of the dsge prior weight is too low!')
-      case 52 %DsgeVarLikelihood
+      case 52 %dsge_var_likelihood
         error('');
       case 61 %Discretionary policy
         error(['Discretionary policy: maximum number of iterations has been reached. Procedure failed. ']);