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A0332
Title: Particle filtering with Dynare Authors:  Frederic Karame - Le Mans University (France) [presenting]
Stephane Adjemian - Le Mans University (France)
Abstract: Since the 2000s, the literature on dynamic stochastic general equilibrium (DSGE) models has evolved towards the use of higher order local approximations. This shift towards nonlinear reduced form solution has implications for the estimation of DSGE models. One now needs to use nonlinear methods, such as Sequential Monte Carlo (also known as particle filtering) to compute the likelihood of the approximated model. The aim is to present some of these developments and their implementation in Dynare, the free, user-friendly and intuitive software platform that handles a wide class of economic models, in particular DSGE and OLG models.