diff --git a/matlab/solve_stochastic_perfect_foresight_model.m b/matlab/solve_stochastic_perfect_foresight_model.m
index d2ce4e59a07f86ab2647e09c42df8266c3d249d0..5f357901f9f0edbc0b327ec3f1f194dd204b3591 100644
--- a/matlab/solve_stochastic_perfect_foresight_model.m
+++ b/matlab/solve_stochastic_perfect_foresight_model.m
@@ -193,8 +193,8 @@ function [flag,endo_simul,err] = solve_stochastic_perfect_foresight_model(endo_s
             end
             flag = 0;% Convergency obtained.
             endo_simul = reshape(Y(:,1),ny,periods+2);%Y(ny+(1:ny),1);
-            figure;plot(Y(16:ny:(periods+2)*ny,:))
-            pause
+                                                      %            figure;plot(Y(16:ny:(periods+2)*ny,:))
+                                                      %            pause
             break
         end
         dy = -A\res;
diff --git a/tests/Makefile.am b/tests/Makefile.am
index bd5e7f5055ae2ab69b3d3335946eecac0d9f06fe..203326fcc49c273ae3c317312c5578f7fcb28901 100644
--- a/tests/Makefile.am
+++ b/tests/Makefile.am
@@ -126,6 +126,7 @@ MODFILES = \
 	second_order/ds1.mod \
 	second_order/ds2.mod \
 	ep/rbc.mod \
+	ep/rbcii.mod \
 	ep/linear.mod \
 	deterministic_simulations/deterministic_model_purely_forward.mod \
 	deterministic_simulations/rbc_det1.mod \
diff --git a/tests/ep/mean_preserving_spread.m b/tests/ep/mean_preserving_spread.m
index 9d988fe1281b9fc4d2f734c7232e88ad05b49d49..d296ec345259f673a58f2837b165d2b8edee9193 100644
--- a/tests/ep/mean_preserving_spread.m
+++ b/tests/ep/mean_preserving_spread.m
@@ -1,4 +1,4 @@
-function m = mean_preserving_spread(autoregressive_parameter)
+function m = mean_preserving_spread(autoregressive_parameter,sigma)
 % Computes the mean preserving spread for first order autoregressive process.
 %
 % The mean preserving spread m is a constant such that the mean of the process
@@ -13,6 +13,5 @@ function m = mean_preserving_spread(autoregressive_parameter)
 % AUTHOR(S) 
 %  stephane DOT adjemian AT univ DASH lemans DOT fr
 %  frederic DOT karame AT univ DASH evry DOT fr
-global M_
 
-m = M_.Sigma_e/(1-autoregressive_parameter*autoregressive_parameter);
\ No newline at end of file
+m = sigma/(1-autoregressive_parameter*autoregressive_parameter);
\ No newline at end of file
diff --git a/tests/ep/rbc.mod b/tests/ep/rbc.mod
index 35edc823ed13a87201aef9ad6c4e3e97655e5a6f..b5534f65708fb505c511b6c04617c4af9768313c 100644
--- a/tests/ep/rbc.mod
+++ b/tests/ep/rbc.mod
@@ -57,10 +57,10 @@ options_.ep.stochastic.nodes = 2;
 options_.console_mode = 0;
 
 options_.ep.stochastic.order = 0;
-ts0 = extended_path([],100);
+//ts0 = extended_path([],100);
 
 options_.ep.stochastic.order = 1;
-ts1 = extended_path([],100);
+//ts1 = extended_path([],100);
 
 options_.ep.stochastic.order = 2;
 ts2 = extended_path([],100);
diff --git a/tests/ep/rbcii.mod b/tests/ep/rbcii.mod
index 2d4046c6ada189f53c9f0f8615f8358d04add959..e4c8c300517f0c1ff85a7793ca4633ac08d152bf 100644
--- a/tests/ep/rbcii.mod
+++ b/tests/ep/rbcii.mod
@@ -26,15 +26,15 @@ sigma2  =  0.001;
     rho = 0.800;
 @#endif
 
-external_function(name=mean_preserving_spread);
+external_function(name=mean_preserving_spread,nargs=2);
 
-model(use_dll);
+model;
 
   // Eq. n°1:
   efficiency = rho*efficiency(-1) + EfficiencyInnovation;
 
   // Eq. n°2:
-  Efficiency = effstar*exp(efficiency-mean_preserving_spread(rho));
+  Efficiency = effstar*exp(efficiency-mean_preserving_spread(rho,sigma2));
 
   // Eq. n°3:
   Output = Efficiency*(alpha*(Capital(-1)^psi)+(1-alpha)*(Labour^psi))^(1/psi);
@@ -56,6 +56,27 @@ model(use_dll);
 
 end;
 
+steady_state_model;
+efficiency = 0;
+Efficiency = effstar*exp(efficiency-mean_preserving_spread(rho,sigma2));
+// Compute steady state ratios.
+Output_per_unit_of_Capital=((1/beta-1+delta)/alpha)^(1/(1-psi));
+Consumption_per_unit_of_Capital=Output_per_unit_of_Capital-delta;
+Labour_per_unit_of_Capital=(((Output_per_unit_of_Capital/Efficiency)^psi-alpha)/(1-alpha))^(1/psi);
+Output_per_unit_of_Labour=Output_per_unit_of_Capital/Labour_per_unit_of_Capital;
+Consumption_per_unit_of_Labour=Consumption_per_unit_of_Capital/Labour_per_unit_of_Capital;
+
+// Compute steady state share of capital.
+ShareOfCapital=alpha/(alpha+(1-alpha)*Labour_per_unit_of_Capital^psi);
+
+/// Compute steady state of the endogenous variables.
+Labour=1/(1+Consumption_per_unit_of_Labour/((1-alpha)*theta/(1-theta)*Output_per_unit_of_Labour^(1-psi)));
+Consumption = Consumption_per_unit_of_Labour*Labour;
+Capital = Labour/Labour_per_unit_of_Capital;
+Output = Output_per_unit_of_Capital*Capital;
+Investment = delta*Capital;
+ExpectedTerm = beta*((((Consumption^theta)*((1-Labour)^(1-theta)))^(1-tau))/Consumption)*(alpha*((Output/Capital)^(1-psi))+1-delta);
+end;
 
 @#if extended_path_version