diff --git a/matlab/dsge_likelihood.m b/matlab/dsge_likelihood.m
index 56c8dc2fa..53d04922c 100644
--- a/matlab/dsge_likelihood.m
+++ b/matlab/dsge_likelihood.m
@@ -352,7 +352,7 @@ if (kalman_algo == 2) || (kalman_algo == 4)
             Q = blkdiag(Q,H);
             R = blkdiag(R,eye(pp));
             Pstar = blkdiag(Pstar,H);
-            Pinf  = blckdiag(Pinf,zeros(pp));
+            Pinf  = blkdiag(Pinf,zeros(pp));
             H = zeros(pp,1);
             mmm   = mm+pp;
         end
@@ -395,7 +395,7 @@ switch DynareOptions.lik_init
     if kalman_algo == 0
         kalman_algo = 3;
     elseif ~((kalman_algo == 3) || (kalman_algo == 4))
-            error(['diffuse filter: options_.kalman_algo can only be equal ' ...
+            error(['The model requires Diffuse filter, but you specified a different Kalman filter. You must set options_.kalman_algo ' ...
                    'to 0 (default), 3 or 4'])
     end
     [Z,T,R,QT,Pstar,Pinf] = schur_statespace_transformation(Z,T,R,Q,DynareOptions.qz_criterium);
@@ -436,7 +436,7 @@ switch DynareOptions.lik_init
                 Q = blkdiag(Q,H);
                 R = blkdiag(R,eye(pp));
                 Pstar = blkdiag(Pstar,H);
-                Pinf  = blckdiag(Pinf,zeros(pp));
+                Pinf  = blkdiag(Pinf,zeros(pp));
                 H1 = zeros(pp,1);
                 mmm   = mm+pp;
             end
@@ -726,7 +726,7 @@ if (kalman_algo==2) || (kalman_algo==4)
                 Q = blkdiag(Q,H);
                 R = blkdiag(R,eye(pp));
                 Pstar = blkdiag(Pstar,H);
-                Pinf  = blckdiag(Pinf,zeros(pp));
+                Pinf  = blkdiag(Pinf,zeros(pp));
                 H1 = zeros(pp,1);
                 mmm   = mm+pp;
             end
diff --git a/matlab/dynare_estimation_1.m b/matlab/dynare_estimation_1.m
index 654de281e..1e4eeb34d 100644
--- a/matlab/dynare_estimation_1.m
+++ b/matlab/dynare_estimation_1.m
@@ -291,9 +291,9 @@ if ~isequal(options_.mode_compute,0) && ~options_.mh_posterior_mode_estimation
     end
     parameter_names = bayestopt_.name;
     if options_.cova_compute || options_.mode_compute==5 || options_.mode_compute==6
-        save([M_.fname '_mode.mat'],'xparam1','hh','parameter_names');
+        save([M_.fname '_mode.mat'],'xparam1','hh','parameter_names','fval');
     else
-        save([M_.fname '_mode.mat'],'xparam1','parameter_names');
+        save([M_.fname '_mode.mat'],'xparam1','parameter_names','fval');
     end
 end
 
diff --git a/matlab/initial_estimation_checks.m b/matlab/initial_estimation_checks.m
index f3b9ce06c..642023e0a 100644
--- a/matlab/initial_estimation_checks.m
+++ b/matlab/initial_estimation_checks.m
@@ -122,6 +122,9 @@ else
     b=0;
     fval = 0;
 end
+if DynareOptions.debug
+    DynareResults.likelihood_at_initial_parameters=fval;
+end
 DynareOptions.analytic_derivation=ana_deriv;
 
 if DynareOptions.dsge_var || strcmp(func2str(objective_function),'non_linear_dsge_likelihood')
diff --git a/tests/Makefile.am b/tests/Makefile.am
index 41cb046e3..e391108cb 100644
--- a/tests/Makefile.am
+++ b/tests/Makefile.am
@@ -169,6 +169,10 @@ MODFILES = \
 	kalman_filter_smoother/fs2000_smoother_only.mod \
 	kalman_filter_smoother/check_variable_dimensions/fs2000.mod \
 	kalman_filter_smoother/check_variable_dimensions/fs2000_ML.mod \
+	kalman/likelihood_from_dynare/fs2000_corr_ME.mod \
+	kalman/likelihood_from_dynare/fs2000_corr_ME_missing.mod \
+	kalman/likelihood_from_dynare/fs2000_uncorr_ME.mod \
+	kalman/likelihood_from_dynare/fs2000_uncorr_ME_missing.mod \
 	second_order/burnside_1.mod \
 	second_order/ds1.mod \
 	second_order/ds2.mod \
@@ -403,6 +407,9 @@ EXTRA_DIST = \
 	ms-sbvar/archive-files/specification_2v2c.dat \
 	recursive/data_ca1.m \
 	kalman_filter_smoother/fsdat_simul.m \
+	kalman/likelihood_from_dynare/fsdat_simul_corr_ME_missing.m \
+	kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME.m \
+	kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME_missing.m \
 	identification/kim/kim2_steadystate.m \
 	identification/as2007/as2007_steadystate.m \
 	estimation/fsdat_simul.m \
diff --git a/tests/kalman/likelihood_from_dynare/fs2000_corr_ME.mod b/tests/kalman/likelihood_from_dynare/fs2000_corr_ME.mod
new file mode 100644
index 000000000..304bd7929
--- /dev/null
+++ b/tests/kalman/likelihood_from_dynare/fs2000_corr_ME.mod
@@ -0,0 +1,137 @@
+/*
+ * This file is based on the cash in advance model described
+ * Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
+ * Journal of Applied Econometrics, 15(6), 645-670.
+ *
+ * The equations are taken from J. Nason and T. Cogley (1994): "Testing the
+ * implications of long-run neutrality for monetary business cycle models",
+ * Journal of Applied Econometrics, 9, S37-S70.
+ * Note that there is an initial minus sign missing in equation (A1), p. S63.
+ *
+ * This implementation was written by Michel Juillard. Please note that the
+ * following copyright notice only applies to this Dynare implementation of the
+ * model.
+ */
+
+/*
+ * Copyright (C) 2004-2013 Dynare Team
+ *
+ * This file is part of Dynare.
+ *
+ * Dynare is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * Dynare is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+var m P c e W R k d n l gy_obs gp_obs y dA;
+varexo e_a e_m;
+
+parameters alp bet gam mst rho psi del theta;
+
+alp = 0.33;
+bet = 0.99;
+gam = 0.003;
+mst = 1.011;
+rho = 0.7;
+psi = 0.787;
+del = 0.02;
+theta=0;
+
+model;
+dA = exp(gam+e_a);
+log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
+-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
+W = l/n;
+-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
+R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
+1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
+c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
+P*c = m;
+m-1+d = l;
+e = exp(e_a);
+y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
+gy_obs = dA*y/y(-1);
+gp_obs = (P/P(-1))*m(-1)/dA;
+end;
+
+steady_state_model;
+  dA = exp(gam);
+  gst = 1/dA;
+  m = mst;
+  khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
+  xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
+  nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
+  n  = xist/(nust+xist);
+  P  = xist + nust;
+  k  = khst*n;
+
+  l  = psi*mst*n/( (1-psi)*(1-n) );
+  c  = mst/P;
+  d  = l - mst + 1;
+  y  = k^alp*n^(1-alp)*gst^alp;
+  R  = mst/bet;
+  W  = l/n;
+  ist  = y-c;
+  q  = 1 - d;
+
+  e = 1;
+  
+  gp_obs = m/dA;
+  gy_obs = dA;
+end;
+
+varobs gp_obs gy_obs;
+
+shocks;
+var e_a; stderr 0.014;
+var e_m; stderr 0.005;
+corr gy_obs,gp_obs = 0.5;
+end;
+
+steady;
+
+
+estimated_params;
+alp, 0.356;
+gam,  0.0085;
+del, 0.01;
+stderr e_a, 0.035449;
+stderr e_m, 0.008862;
+corr e_m, e_a, 0;
+stderr gp_obs, 1;
+stderr gy_obs, 1;
+corr gp_obs, gy_obs,0;
+end;
+
+options_.TeX=1;
+options_.debug=1;
+
+%%default
+options_.lik_init=1;
+estimation(kalman_algo=0,mode_compute=4,order=1,datafile='../../fs2000/fsdat_simul',smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_0=oo_.likelihood_at_initial_parameters;
+%%Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=1,mode_file=fs2000_corr_ME_mode,mode_compute=0,order=1,datafile='../../fs2000/fsdat_simul',smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_1=oo_.likelihood_at_initial_parameters;
+%%Univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=3,mode_file=fs2000_corr_ME_mode,mode_compute=0,order=1,datafile='../../fs2000/fsdat_simul',smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_3=oo_.likelihood_at_initial_parameters;
+%%Diffuse Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=2,mode_file=fs2000_corr_ME_mode,mode_compute=0,datafile='../../fs2000/fsdat_simul',smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_2=oo_.likelihood_at_initial_parameters;
+%%Diffuse univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=4,mode_file=fs2000_corr_ME_mode,mode_compute=0,datafile='../../fs2000/fsdat_simul',smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_4=oo_.likelihood_at_initial_parameters;
diff --git a/tests/kalman/likelihood_from_dynare/fs2000_corr_ME_missing.mod b/tests/kalman/likelihood_from_dynare/fs2000_corr_ME_missing.mod
new file mode 100644
index 000000000..eea44b004
--- /dev/null
+++ b/tests/kalman/likelihood_from_dynare/fs2000_corr_ME_missing.mod
@@ -0,0 +1,137 @@
+/*
+ * This file is based on the cash in advance model described
+ * Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
+ * Journal of Applied Econometrics, 15(6), 645-670.
+ *
+ * The equations are taken from J. Nason and T. Cogley (1994): "Testing the
+ * implications of long-run neutrality for monetary business cycle models",
+ * Journal of Applied Econometrics, 9, S37-S70.
+ * Note that there is an initial minus sign missing in equation (A1), p. S63.
+ *
+ * This implementation was written by Michel Juillard. Please note that the
+ * following copyright notice only applies to this Dynare implementation of the
+ * model.
+ */
+
+/*
+ * Copyright (C) 2004-2013 Dynare Team
+ *
+ * This file is part of Dynare.
+ *
+ * Dynare is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * Dynare is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+var m P c e W R k d n l gy_obs gp_obs y dA;
+varexo e_a e_m;
+
+parameters alp bet gam mst rho psi del theta;
+
+alp = 0.33;
+bet = 0.99;
+gam = 0.003;
+mst = 1.011;
+rho = 0.7;
+psi = 0.787;
+del = 0.02;
+theta=0;
+
+model;
+dA = exp(gam+e_a);
+log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
+-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
+W = l/n;
+-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
+R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
+1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
+c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
+P*c = m;
+m-1+d = l;
+e = exp(e_a);
+y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
+gy_obs = dA*y/y(-1);
+gp_obs = (P/P(-1))*m(-1)/dA;
+end;
+
+steady_state_model;
+  dA = exp(gam);
+  gst = 1/dA;
+  m = mst;
+  khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
+  xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
+  nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
+  n  = xist/(nust+xist);
+  P  = xist + nust;
+  k  = khst*n;
+
+  l  = psi*mst*n/( (1-psi)*(1-n) );
+  c  = mst/P;
+  d  = l - mst + 1;
+  y  = k^alp*n^(1-alp)*gst^alp;
+  R  = mst/bet;
+  W  = l/n;
+  ist  = y-c;
+  q  = 1 - d;
+
+  e = 1;
+  
+  gp_obs = m/dA;
+  gy_obs = dA;
+end;
+
+varobs gp_obs gy_obs;
+
+shocks;
+var e_a; stderr 0.014;
+var e_m; stderr 0.005;
+corr gy_obs,gp_obs = 0.5;
+end;
+
+steady;
+
+
+estimated_params;
+alp, 0.356;
+gam,  0.0085;
+del, 0.01;
+stderr e_a, 0.035449;
+stderr e_m, 0.008862;
+corr e_m, e_a, 0;
+stderr gp_obs, 1;
+stderr gy_obs, 1;
+corr gp_obs, gy_obs,0;
+end;
+
+options_.TeX=1;
+options_.debug=1;
+
+%%default
+options_.lik_init=1;
+estimation(kalman_algo=0,mode_compute=4,order=1,datafile=fsdat_simul_corr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_0=oo_.likelihood_at_initial_parameters;
+%%Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=1,mode_file=fs2000_corr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_corr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_1=oo_.likelihood_at_initial_parameters;
+%%Univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=3,mode_file=fs2000_corr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_corr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_3=oo_.likelihood_at_initial_parameters;
+%%Diffuse Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=2,mode_file=fs2000_corr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_corr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_2=oo_.likelihood_at_initial_parameters;
+%%Diffuse univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=4,mode_file=fs2000_corr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_corr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_4=oo_.likelihood_at_initial_parameters;
diff --git a/tests/kalman/likelihood_from_dynare/fs2000_uncorr_ME.mod b/tests/kalman/likelihood_from_dynare/fs2000_uncorr_ME.mod
new file mode 100644
index 000000000..f0eb4dea4
--- /dev/null
+++ b/tests/kalman/likelihood_from_dynare/fs2000_uncorr_ME.mod
@@ -0,0 +1,137 @@
+/*
+ * This file is based on the cash in advance model described
+ * Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
+ * Journal of Applied Econometrics, 15(6), 645-670.
+ *
+ * The equations are taken from J. Nason and T. Cogley (1994): "Testing the
+ * implications of long-run neutrality for monetary business cycle models",
+ * Journal of Applied Econometrics, 9, S37-S70.
+ * Note that there is an initial minus sign missing in equation (A1), p. S63.
+ *
+ * This implementation was written by Michel Juillard. Please note that the
+ * following copyright notice only applies to this Dynare implementation of the
+ * model.
+ */
+
+/*
+ * Copyright (C) 2004-2013 Dynare Team
+ *
+ * This file is part of Dynare.
+ *
+ * Dynare is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * Dynare is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+var m P c e W R k d n l gy_obs gp_obs y dA;
+varexo e_a e_m;
+
+parameters alp bet gam mst rho psi del theta;
+
+alp = 0.33;
+bet = 0.99;
+gam = 0.003;
+mst = 1.011;
+rho = 0.7;
+psi = 0.787;
+del = 0.02;
+theta=0;
+
+model;
+dA = exp(gam+e_a);
+log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
+-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
+W = l/n;
+-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
+R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
+1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
+c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
+P*c = m;
+m-1+d = l;
+e = exp(e_a);
+y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
+gy_obs = dA*y/y(-1);
+gp_obs = (P/P(-1))*m(-1)/dA;
+end;
+
+steady_state_model;
+  dA = exp(gam);
+  gst = 1/dA;
+  m = mst;
+  khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
+  xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
+  nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
+  n  = xist/(nust+xist);
+  P  = xist + nust;
+  k  = khst*n;
+
+  l  = psi*mst*n/( (1-psi)*(1-n) );
+  c  = mst/P;
+  d  = l - mst + 1;
+  y  = k^alp*n^(1-alp)*gst^alp;
+  R  = mst/bet;
+  W  = l/n;
+  ist  = y-c;
+  q  = 1 - d;
+
+  e = 1;
+  
+  gp_obs = m/dA;
+  gy_obs = dA;
+end;
+
+varobs gp_obs gy_obs;
+
+shocks;
+var e_a; stderr 0.014;
+var e_m; stderr 0.005;
+end;
+
+steady;
+
+//stoch_simul(periods=200, order=1);
+//datatomfile('fsdat_simul_uncorr_ME', char('gy_obs', 'gp_obs'));
+
+estimated_params;
+alp, 0.356;
+gam,  0.0085;
+del, 0.01;
+stderr e_a, 0.035449;
+stderr e_m, 0.008862;
+corr e_m, e_a, 0;
+stderr gp_obs, 1;
+stderr gy_obs, 1;
+//corr gp_obs, gy_obs,0;
+end;
+
+options_.TeX=1;
+options_.debug=1;
+
+%%default
+estimation(kalman_algo=0,mode_compute=4,order=1,datafile=fsdat_simul_uncorr_ME,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_0=oo_.likelihood_at_initial_parameters;
+%%Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=1,mode_file=fs2000_uncorr_ME_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_1=oo_.likelihood_at_initial_parameters;
+%%Univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=3,mode_file=fs2000_uncorr_ME_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_3=oo_.likelihood_at_initial_parameters;
+%%Diffuse Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=2,mode_file=fs2000_uncorr_ME_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_2=oo_.likelihood_at_initial_parameters;
+%%Diffuse univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=4,mode_file=fs2000_uncorr_ME_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_4=oo_.likelihood_at_initial_parameters;
diff --git a/tests/kalman/likelihood_from_dynare/fs2000_uncorr_ME_missing.mod b/tests/kalman/likelihood_from_dynare/fs2000_uncorr_ME_missing.mod
new file mode 100644
index 000000000..7ed016b2d
--- /dev/null
+++ b/tests/kalman/likelihood_from_dynare/fs2000_uncorr_ME_missing.mod
@@ -0,0 +1,137 @@
+/*
+ * This file is based on the cash in advance model described
+ * Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
+ * Journal of Applied Econometrics, 15(6), 645-670.
+ *
+ * The equations are taken from J. Nason and T. Cogley (1994): "Testing the
+ * implications of long-run neutrality for monetary business cycle models",
+ * Journal of Applied Econometrics, 9, S37-S70.
+ * Note that there is an initial minus sign missing in equation (A1), p. S63.
+ *
+ * This implementation was written by Michel Juillard. Please note that the
+ * following copyright notice only applies to this Dynare implementation of the
+ * model.
+ */
+
+/*
+ * Copyright (C) 2004-2013 Dynare Team
+ *
+ * This file is part of Dynare.
+ *
+ * Dynare is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * Dynare is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+var m P c e W R k d n l gy_obs gp_obs y dA;
+varexo e_a e_m;
+
+parameters alp bet gam mst rho psi del theta;
+
+alp = 0.33;
+bet = 0.99;
+gam = 0.003;
+mst = 1.011;
+rho = 0.7;
+psi = 0.787;
+del = 0.02;
+theta=0;
+
+model;
+dA = exp(gam+e_a);
+log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
+-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
+W = l/n;
+-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
+R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
+1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
+c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
+P*c = m;
+m-1+d = l;
+e = exp(e_a);
+y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
+gy_obs = dA*y/y(-1);
+gp_obs = (P/P(-1))*m(-1)/dA;
+end;
+
+steady_state_model;
+  dA = exp(gam);
+  gst = 1/dA;
+  m = mst;
+  khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
+  xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
+  nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
+  n  = xist/(nust+xist);
+  P  = xist + nust;
+  k  = khst*n;
+
+  l  = psi*mst*n/( (1-psi)*(1-n) );
+  c  = mst/P;
+  d  = l - mst + 1;
+  y  = k^alp*n^(1-alp)*gst^alp;
+  R  = mst/bet;
+  W  = l/n;
+  ist  = y-c;
+  q  = 1 - d;
+
+  e = 1;
+  
+  gp_obs = m/dA;
+  gy_obs = dA;
+end;
+
+varobs gp_obs gy_obs;
+
+shocks;
+var e_a; stderr 0.014;
+var e_m; stderr 0.005;
+end;
+
+steady;
+
+//stoch_simul(periods=200, order=1);
+//datatomfile('fsdat_simul_uncorr_ME', char('gy_obs', 'gp_obs'));
+
+estimated_params;
+alp, 0.356;
+gam,  0.0085;
+del, 0.01;
+stderr e_a, 0.035449;
+stderr e_m, 0.008862;
+corr e_m, e_a, 0;
+stderr gp_obs, 1;
+stderr gy_obs, 1;
+//corr gp_obs, gy_obs,0;
+end;
+
+options_.TeX=1;
+options_.debug=1;
+
+%%default
+estimation(kalman_algo=0,mode_compute=4,order=1,datafile=fsdat_simul_uncorr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_0=oo_.likelihood_at_initial_parameters;
+%%Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=1,mode_file=fs2000_uncorr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_1=oo_.likelihood_at_initial_parameters;
+%%Univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=3,mode_file=fs2000_uncorr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_3=oo_.likelihood_at_initial_parameters;
+%%Diffuse Multivariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=2,mode_file=fs2000_uncorr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_2=oo_.likelihood_at_initial_parameters;
+%%Diffuse univariate Kalman Filter
+options_.lik_init=1;
+estimation(kalman_algo=4,mode_file=fs2000_uncorr_ME_missing_mode,mode_compute=0,order=1,datafile=fsdat_simul_uncorr_ME_missing,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+fval_algo_4=oo_.likelihood_at_initial_parameters;
diff --git a/tests/kalman/likelihood_from_dynare/fsdat_simul_corr_ME_missing.m b/tests/kalman/likelihood_from_dynare/fsdat_simul_corr_ME_missing.m
new file mode 100644
index 000000000..d04535f02
--- /dev/null
+++ b/tests/kalman/likelihood_from_dynare/fsdat_simul_corr_ME_missing.m
@@ -0,0 +1,416 @@
+% Generated data, used by fs2000.mod
+
+gy_obs          =[
+      1.0030045
+      1.0002599
+     0.99104664
+      1.0321162
+      1.0223545
+      1.0043614
+     NaN
+      1.0092127
+      1.0357197
+      1.0150827
+      1.0051548
+     0.98465775
+     0.99132132
+     0.99904153
+      1.0044641
+      1.0179198
+      1.0113462
+     0.99409421
+     0.99904293
+      1.0448336
+     0.99932433
+      1.0057004
+     0.99619787
+      1.0267504
+      1.0077645
+      1.0058026
+      1.0025891
+      0.9939097
+     0.99604693
+     0.99908569
+      1.0151094
+     0.99348134
+      1.0039124
+      1.0145805
+     0.99800868
+     0.98578138
+      1.0065771
+     0.99843919
+     0.97979062
+     0.98413351
+     0.96468174
+      1.0273857
+      1.0225211
+     0.99958667
+      1.0111157
+      1.0099585
+     0.99480311
+      1.0079265
+     0.98924573
+      1.0070613
+      1.0075706
+      0.9937151
+      1.0224711
+      1.0018891
+     0.99051863
+      1.0042944
+      1.0184055
+     0.99419508
+     0.99756624
+      1.0015983
+      0.9845772
+      1.0004407
+      1.0116237
+      0.9861885
+      1.0073094
+     0.99273355
+      1.0013224
+     0.99777979
+      1.0301686
+     0.96809556
+     0.99917088
+     0.99949253
+     0.96590004
+      1.0083938
+     0.96662298
+      1.0221454
+      1.0069792
+      1.0343996
+      1.0066531
+      1.0072525
+     0.99743563
+     0.99723703
+       1.000372
+     0.99013917
+      1.0095223
+     0.98864268
+     0.98092242
+     0.98886488
+      1.0030341
+        1.01894
+     0.99155059
+     0.99533235
+     0.99734316
+      1.0047356
+      1.0082737
+     0.98425116
+     0.99949212
+      1.0055899
+      1.0065075
+     0.99385069
+     0.98867975
+     0.99804843
+      1.0184038
+     0.99301902
+      1.0177222
+      1.0051924
+      1.0187852
+      1.0098985
+      1.0097172
+      1.0145811
+     0.98721038
+      1.0361722
+      1.0105821
+     0.99469309
+     0.98626785
+       1.013871
+     0.99858924
+     0.99302637
+      1.0042186
+     0.99623745
+     0.98545708
+      1.0225435
+      1.0011861
+      1.0130321
+     0.97861347
+      1.0228193
+     0.99627435
+      1.0272779
+      1.0075172
+      1.0096762
+      1.0129306
+     0.99966549
+      1.0262882
+      1.0026914
+      1.0061475
+       1.009523
+      1.0036127
+     0.99762992
+     0.99092634
+      1.0058469
+     0.99887292
+      1.0060653
+     0.98673557
+     0.98895709
+     0.99111967
+       0.990118
+     0.99788054
+     0.97054709
+      1.0099157
+      1.0107431
+     0.99518695
+      1.0114048
+     0.99376019
+      1.0023369
+     0.98783327
+      1.0051727
+      1.0100462
+     0.98607387
+      1.0000064
+     0.99692442
+       1.012225
+     0.99574078
+     0.98642833
+     0.99008207
+      1.0197359
+      1.0112849
+     0.98711069
+     0.99402748
+      1.0242141
+      1.0135349
+     0.99842505
+      1.0130714
+     0.99887044
+      1.0059058
+      1.0185998
+      1.0073314
+     0.98687706
+      1.0084551
+     0.97698964
+     0.99482714
+      1.0015302
+      1.0105331
+      1.0261767
+      1.0232822
+      1.0084176
+     0.99785167
+     0.99619733
+      1.0055223
+      1.0076326
+     0.99205461
+      1.0030587
+      1.0137012
+      1.0145878
+      1.0190297
+      1.0000681
+      1.0153894
+      1.0140649
+      1.0007236
+     0.97961463
+      1.0125257
+      1.0169503
+      NaN
+      1.0221185
+
+];
+
+gp_obs          =[
+      1.0079715
+      1.0115853
+      1.0167502
+      1.0068957
+      1.0138189
+      1.0258364
+      1.0243817
+       1.017373
+      1.0020171
+      1.0003742
+      1.0008974
+      1.0104804
+      1.0116393
+      1.0114294
+     0.99932124
+     0.99461459
+      NaN
+      1.0051446
+       1.020639
+      1.0051964
+      1.0093042
+       1.007068
+        1.01086
+     0.99590086
+      1.0014883
+      1.0117332
+      0.9990095
+      1.0108284
+      1.0103672
+      1.0036722
+      1.0005124
+      1.0190331
+      1.0130978
+       1.007842
+      1.0285436
+      1.0322054
+      1.0213403
+      1.0246486
+      1.0419306
+      1.0258867
+      1.0156316
+     0.99818589
+      0.9894107
+      1.0127584
+      1.0146882
+      1.0136529
+      1.0340107
+      1.0343652
+        1.02971
+      1.0077932
+      1.0198114
+       1.013971
+      1.0061083
+      1.0089573
+      1.0037926
+      1.0082071
+     0.99498155
+     0.99735772
+     0.98765026
+       1.006465
+      1.0196088
+      1.0053233
+      1.0119974
+      1.0188066
+      1.0029302
+      1.0183459
+      1.0034218
+      1.0158799
+     0.98824798
+      1.0274357
+      1.0168832
+      1.0180641
+      1.0294657
+     0.98864091
+      1.0358326
+     0.99889969
+      1.0178322
+     0.99813566
+      1.0073549
+      1.0215985
+      1.0084245
+      1.0080939
+      1.0157021
+      1.0075815
+      1.0032633
+      1.0117871
+      1.0209276
+      1.0077569
+     0.99680958
+      1.0120266
+      1.0017625
+      1.0138811
+      1.0198358
+      1.0059629
+      1.0115416
+      1.0319473
+      1.0167074
+      1.0116111
+      1.0048627
+      1.0217622
+      1.0125221
+      1.0142045
+     0.99792469
+     0.99823971
+     0.99561547
+     0.99850373
+      0.9898464
+      1.0030963
+      1.0051373
+      1.0004213
+      1.0144117
+     0.97185592
+      0.9959518
+      1.0073529
+      1.0051603
+     0.98642572
+     0.99433423
+      1.0112131
+      1.0007695
+      1.0176867
+      1.0134363
+     0.99926191
+     0.99879835
+     0.99878754
+      1.0331374
+      1.0077797
+      1.0127221
+      1.0047393
+      1.0074106
+     0.99784213
+      1.0056495
+      1.0057708
+     0.98817494
+     0.98742176
+     0.99930555
+      1.0000687
+      1.0129754
+       1.009529
+      1.0226731
+      1.0149534
+      1.0164295
+      1.0239469
+      1.0293458
+       1.026199
+      1.0197525
+      1.0126818
+      1.0054473
+      1.0254423
+      1.0069461
+      1.0153135
+      1.0337515
+      1.0178187
+      1.0240469
+      1.0079489
+      1.0186953
+      1.0008628
+      1.0113799
+      1.0140118
+      1.0168007
+       1.011441
+     0.98422774
+     0.98909729
+      1.0157859
+      1.0151586
+     0.99756232
+     0.99497777
+      1.0102841
+      1.0221659
+      0.9937759
+     0.99877193
+      1.0079433
+     0.99667692
+      1.0095959
+      1.0128804
+      1.0156949
+      1.0111951
+      1.0228887
+      1.0122083
+      1.0190197
+      1.0074927
+      1.0268096
+     0.99689352
+     0.98948474
+      1.0024938
+      1.0105543
+       1.014116
+      1.0141217
+      1.0056504
+      1.0101026
+      1.0105069
+     0.99619053
+      1.0059439
+     0.99449473
+     0.99482458
+      1.0037702
+      1.0068087
+     0.99575975
+      1.0030815
+      1.0334014
+     0.99879386
+     0.99625634
+      NaN
+     0.99233844
+
+];
+
diff --git a/tests/kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME.m b/tests/kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME.m
new file mode 100644
index 000000000..ac2057747
--- /dev/null
+++ b/tests/kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME.m
@@ -0,0 +1,406 @@
+gy_obs = [
+      1.0089434
+     0.97436837
+      1.0078602
+     0.99728812
+      1.0469033
+     0.98514927
+      1.0130718
+      1.0127905
+      1.0012276
+      1.0207597
+      1.0128382
+      1.0117555
+      1.0093849
+      1.0130848
+      1.0076878
+      1.0151714
+     0.99010787
+      0.9651508
+      1.0075909
+      1.0211352
+      1.0016703
+      1.0067838
+     0.99211778
+      1.0006245
+      1.0164224
+     0.99240467
+     0.98841006
+      1.0021161
+     0.99328172
+     0.99975511
+      0.9894502
+      1.0095403
+      1.0227135
+     0.98474395
+     0.98842474
+     0.99510226
+      1.0003444
+     0.99419424
+     0.98459156
+      1.0006202
+      1.0205175
+      1.0046155
+     0.99261284
+      1.0137533
+      1.0062878
+      0.9882274
+      1.0106694
+     0.99471339
+       1.002965
+     0.99799306
+      1.0134657
+      1.0039836
+      1.0066297
+      1.0084027
+      1.0245597
+      0.9763106
+        1.02033
+      1.0147916
+      1.0219756
+      1.0008057
+      1.0390485
+      1.0210931
+     0.99734292
+      1.0171595
+      1.0130723
+     0.99892094
+     0.98279425
+      1.0066122
+     0.98575479
+      1.0078347
+      1.0036275
+     0.98116612
+     0.99293813
+     0.98842048
+     0.97690963
+      1.0093542
+      1.0027533
+      1.0156453
+     0.99313547
+      1.0004421
+     0.99954572
+     0.98736251
+      1.0238741
+     0.98768174
+       1.000261
+     0.98722229
+     0.98398124
+      1.0072403
+      1.0009303
+     0.99628068
+     0.98538731
+     0.99218841
+       1.009118
+     0.98810044
+      1.0112788
+      1.0004868
+     0.99890858
+      1.0029751
+      1.0219324
+       1.000043
+      1.0058196
+       1.014664
+         1.0044
+      1.0067619
+      1.0008676
+     0.99532428
+     0.99224953
+     0.99444046
+      1.0003366
+      1.0221002
+     0.98855273
+      1.0187089
+     0.98416472
+      1.0006988
+     0.99933767
+      1.0084427
+      0.9910711
+     0.99630044
+      1.0041385
+     0.99578819
+     0.98859148
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diff --git a/tests/kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME_missing.m b/tests/kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME_missing.m
new file mode 100644
index 000000000..9cd0c8da1
--- /dev/null
+++ b/tests/kalman/likelihood_from_dynare/fsdat_simul_uncorr_ME_missing.m
@@ -0,0 +1,406 @@
+gy_obs = [
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