diff --git a/matlab/solve_stochastic_perfect_foresight_model.m b/matlab/solve_stochastic_perfect_foresight_model.m
index f3c55a22e52aefe5d6bb3f0c6cd53cb662e0e320..d2ce4e59a07f86ab2647e09c42df8266c3d249d0 100644
--- a/matlab/solve_stochastic_perfect_foresight_model.m
+++ b/matlab/solve_stochastic_perfect_foresight_model.m
@@ -193,6 +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
             break
         end
         dy = -A\res;
diff --git a/tests/ep/rbc.mod b/tests/ep/rbc.mod
index 180d81f22ad82134354949c53542ba472174d192..35edc823ed13a87201aef9ad6c4e3e97655e5a6f 100644
--- a/tests/ep/rbc.mod
+++ b/tests/ep/rbc.mod
@@ -53,8 +53,15 @@ end;
 steady;
 
 options_.ep.verbosity = 0;
-options_.ep.order = 1;
-options_.ep.nnodes = 2;
+options_.ep.stochastic.nodes = 2;
 options_.console_mode = 0;
 
-ts = extended_path([],100);
\ No newline at end of file
+options_.ep.stochastic.order = 0;
+ts0 = extended_path([],100);
+
+options_.ep.stochastic.order = 1;
+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 49a0cce53d2668be8adf9075af08530781211a1b..2d4046c6ada189f53c9f0f8615f8358d04add959 100644
--- a/tests/ep/rbcii.mod
+++ b/tests/ep/rbcii.mod
@@ -68,11 +68,12 @@ end;
     options_.maxit_ = 100;
     options_.ep.verbosity = 0;
     options_.ep.stochastic.order = 0;
+    options_.ep.stochastic.nodes = 2;
     options_.console_mode = 0;
-    ts = extended_path([],1000);
+    ts = extended_path([],100);
 
     options_.ep.stochastic.order = 1;
-    sts = extended_path([],1000);
+    sts = extended_path([],100);
 
     figure(1)
     plot(ts(2,:)-ts(4,:));