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Dynare is a pre-processor and a collection of GAUSS, MATLAB or SCILAB routines which solve non-linear models with forward looking variables. It is the result of research carried at CEPREMAP by several people (see Laffargue, 1990, Boucekkine, 1995, and Juillard, 1996, Collard and Juillard 2001a and 2001b). Although it can be put to other use, Dynare has been built in order to study the transitory dynamics of non-linear models with consistent expectations.
When the framework is deterministic, Dynare can be used for models with the assumption of perfect foresight. Typically, the system is supposed to be in a state of equilibrium before a period "1" when the news of a contemporaneous or of a future shock is learned by the agents in the model. The purpose of the simulation is to describe the reaction in anticipation of, then in reaction to the shock, until the system returns to the old or to a new state of equilibrium. In most models, this return to equilibrium is only an asymptotic phenomenon, which one must approximate by an horizon of simulation far enough in the future. Another exercise for which Dynare is well suited is to study the transition path to a new equilibrium following a permanent shock.
For deterministic simulations, Dynare uses a Newton-type algorithm, first proposed by Laffargue (1990), instead of a first order technique like the one proposed by Fair and Taylor (1983), and used in earlier generation simulation programs. We believe this approach to be in general both faster and more robust. The details of the algorithm used in Dynare can be found in Juillard (1996).
In a stochastic context, Dynare computes one or several simulations corresponding to a random draw of the shocks. Starting with version 2.3 (not available for GAUSS), Dynare uses a second order Taylor approximation of the expectation functions (see Judd, 1996, Collard and Juillard, 2001a, 2001b, and Schmitt-Grohe and Uribe, 2002).