diff --git a/matlab/perfect-foresight-models/make_y_.m b/matlab/perfect-foresight-models/make_y_.m
index 788d6eb93..7611c9e97 100644
--- a/matlab/perfect-foresight-models/make_y_.m
+++ b/matlab/perfect-foresight-models/make_y_.m
@@ -51,6 +51,8 @@ else
     if ~isempty(ys0_)
         error('histval and endval cannot be used simultaneously')
     end
-    oo_.endo_simul = [M_.endo_histval ...
+    % the first NaNs take care of the case where there are lags > 1 on
+    % exogenous variables
+    oo_.endo_simul = [NaN(M_.endo_nbr,M_.maximum_lag-1) M_.endo_histval ...
                       oo_.steady_state*ones(1,options_.periods+M_.maximum_lead)];
 end
diff --git a/matlab/perfect-foresight-models/perfect_foresight_problem.m b/matlab/perfect-foresight-models/perfect_foresight_problem.m
index 48a6e054e..9030a5ae5 100644
--- a/matlab/perfect-foresight-models/perfect_foresight_problem.m
+++ b/matlab/perfect-foresight-models/perfect_foresight_problem.m
@@ -1,10 +1,10 @@
 function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function, Y0, YT, ...
                                            exo_simul, params, steady_state, ...
-                                           T, ny, i_cols, ...
+                                           maximum_lag, T, ny, i_cols, ...
                                            i_cols_J1, i_cols_1, i_cols_T, ...
                                            i_cols_j,nnzJ)
-% function perfect_foresight_problem(x, model_dynamic, Y0, YT,exo_simul,
-% params, steady_state, periods, ny, i_cols,i_cols_J1, i_cols_1,
+% function [residuals,JJacobian] = perfect_foresight_problem(x, model_dynamic, Y0, YT,exo_simul,
+% params, steady_state, maximum_lag, periods, ny, i_cols,i_cols_J1, i_cols_1,
 % i_cols_T, i_cols_j, nnzA) 
 % computes the residuals and th Jacobian matrix
 % for a perfect foresight problem over T periods.
@@ -19,7 +19,7 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
 % SPECIAL REQUIREMENTS
 %   None.
 
-% Copyright (C) 1996-2014 Dynare Team
+% Copyright (C) 1996-2015 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -47,7 +47,7 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
     i_rows = 1:ny;
     i_cols_J = i_cols;
 
-    for it = 2:(T+1)
+    for it = maximum_lag+(1:T)
         if nargout == 1
             residuals(i_rows) = dynamic_function(YY(i_cols),exo_simul, params, ...
                                                          steady_state,it);
diff --git a/matlab/perfect-foresight-models/perfect_foresight_solver.m b/matlab/perfect-foresight-models/perfect_foresight_solver.m
index 4c1ee15a0..049932d20 100644
--- a/matlab/perfect-foresight-models/perfect_foresight_solver.m
+++ b/matlab/perfect-foresight-models/perfect_foresight_solver.m
@@ -56,7 +56,7 @@ if options_.debug
 end
 
 initperiods = 1:M_.maximum_lag;
-lastperiods = (M_.maximum_endo_lag+options_.periods+1):(M_.maximum_endo_lag+options_.periods+M_.maximum_endo_lead);
+lastperiods = (M_.maximum_lag+options_.periods+1):(M_.maximum_lag+options_.periods+M_.maximum_lead);
 
 
 oo_ = simulation_core(options_, M_, oo_);
@@ -116,7 +116,7 @@ if ~oo_.deterministic_simulation.status && ~options_.no_homotopy
         if isequal(iteration,1)
             oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = endoinit(:,1:options_.periods);
         elseif path_with_nans || path_with_cplx
-            oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = saved_endo_simul(:,1+M_.maximum_endo_lag:end-M_.maximum_endo_lead);
+            oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = saved_endo_simul(:,1+M_.maximum_lag:end-M_.maximum_lead);
         end
         
         saved_endo_simul = oo_.endo_simul;
diff --git a/matlab/perfect-foresight-models/private/simulation_core.m b/matlab/perfect-foresight-models/private/simulation_core.m
index 81674e4a2..cb5f6d540 100644
--- a/matlab/perfect-foresight-models/private/simulation_core.m
+++ b/matlab/perfect-foresight-models/private/simulation_core.m
@@ -82,7 +82,7 @@ else
                 [y,info] = dynare_solve(@perfect_foresight_problem,z(:),options_, ...
                                  str2func([M_.fname '_dynamic']),y0,yT, ...
                                  oo_.exo_simul,M_.params,oo_.steady_state, ...
-                                 options_.periods,M_.endo_nbr,i_cols, ...
+                                 M_.maximum_lag,options_.periods,M_.endo_nbr,i_cols, ...
                                  i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
                                  M_.NNZDerivatives(1));
                 if all(imag(y)<.1*options_.dynatol.f)
@@ -122,7 +122,7 @@ if nargout>1
         else
             residuals = perfect_foresight_problem(yy(:),str2func([M_.fname '_dynamic']), y0, yT, ...
                                                   oo_.exo_simul,M_.params,oo_.steady_state, ...
-                                                  options_.periods,M_.endo_nbr,i_cols, ...
+                                                  M_.maximum_lag,options_.periods,M_.endo_nbr,i_cols, ...
                                                   i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
                                                   M_.NNZDerivatives(1));
         end