diff --git a/doc/dynare.texi b/doc/dynare.texi
index 611683734..bafb4438a 100644
--- a/doc/dynare.texi
+++ b/doc/dynare.texi
@@ -2875,7 +2875,8 @@ The simulated endogenous variables are available in global matrix
 @defvr {MATLAB/Octave variable} oo_.endo_simul
 This variable stores the result of a deterministic simulation
 (computed by @code{simul}) or of a stochastic simulation (computed by
-@code{stoch_simul} with the @code{periods} option).
+@code{stoch_simul} with the @code{periods} option or by
+@code{extended_path}).
 
 The variables are arranged row by row, in order of declaration (as in
 @code{M_.endo_names}). Note that this variable also contains initial
@@ -2883,16 +2884,38 @@ and terminal conditions, so it has more columns than the value of
 @code{periods} option.
 @end defvr
 
+@anchor{oo_.exo_simul}
+@defvr {MATLAB/Octave variable} oo_.exo_simul
+This variable stores the path of exogenous variables during a
+simulation (computed by @code{simul}, @code{stoch_simul} or
+@code{extended_path}).
+
+The variables are arranged in columns, in order of declaration (as in
+@code{M_.endo_names}). Periods are in rows. Note that this convention
+regarding columns and rows is the opposite of the convention for
+@code{oo_.endo_simul}!
+
+@end defvr
+
 @node Stochastic solution and simulation
 @section Stochastic solution and simulation
 
 In a stochastic context, Dynare computes one or several simulations
-corresponding to a random draw of the shocks. Dynare uses a Taylor
+corresponding to a random draw of the shocks.
+
+The main algorithm for solving stochastic models relies on a Taylor
 approximation, up to third order, of the expectation functions (see
 @cite{Judd (1996)}, @cite{Collard and Juillard (2001a)}, @cite{Collard
 and Juillard (2001b)}, and @cite{Schmitt-Grohé and Uríbe (2004)}). The
 details of the Dynare implementation of the first order solution are
-given in @cite{Villemot (2011)}.
+given in @cite{Villemot (2011)}. Such a solution is computed using
+the @code{stoch_simul} command.
+
+As an alternative, it is possible to compute a simulation to a
+stochastic model using the @emph{extended path} method presented by
+@cite{Fair and Taylor (1983)}. This method is especially useful when
+there are strong nonlinearities or binding constraints. Such a
+solution is computed using the @code{extended_path} command.
 
 @menu
 * Computing the stochastic solution::  
@@ -3052,7 +3075,9 @@ periods to use in the simulations. Values of the @code{initval} block,
 possibly recomputed by @code{steady}, will be used as starting point
 for the simulation. The simulated endogenous variables are made
 available to the user in a vector for each variable and in the global
-matrix @code{oo_.endo_simul} (@pxref{oo_.endo_simul}). Default: @code{0}.
+matrix @code{oo_.endo_simul} (@pxref{oo_.endo_simul}). The simulated
+exogenous variables are made available in @code{oo_.exo_simul}
+(@pxref{oo_.exo_simul}). Default: @code{0}.
 
 @item qz_criterium = @var{DOUBLE}
 Value used to split stable from unstable eigenvalues in reordering the
@@ -3250,6 +3275,37 @@ variables of the model as function of the previous state of the model and
 shocks oberved at the beginning of the period. The decision rules are stored
 in the structure @code{oo_.dr} which is described below.
 
+@deffn Command extended_path ;
+@deffnx Command extended_path (@var{OPTIONS}@dots{}) ;
+
+@descriptionhead
+
+@code{extended_path} solves a stochastic (@i{i.e.} rational
+expectations) model, using the @emph{extended path} method presented
+by @cite{Fair and Taylor (1983)}.
+
+This function first computes a random path for the exogenous variables
+(stored in @code{oo_.exo_simul}, @pxref{oo_.exo_simul}) and then
+computes the corresponding path for endogenous variables, taking the
+steady state as starting point. The result of the simulation is stored
+in @code{oo_.endo_simul} (@pxref{oo_.endo_simul}).
+
+@optionshead
+
+@table @code
+
+@item periods = @var{INTEGER}
+The number of periods for which the simulation is to be computed. No
+default value, mandatory option.
+
+@item solver_periods = @var{INTEGER}
+The number of periods used to compute the approximate solution
+at every iteration of the algorithm. Default: @code{200}.
+
+@end table
+
+@end deffn
+
 @node Typology and ordering of variables
 @subsection Typology and ordering of variables