We show how to use sequential Monte Carlo methods to estimate a heterogeneous agent New Keynesian (HANK) model featuring both nominal and real rigidities. We demonstrate how the posterior distribution may be specified as the product of the standard …
Julia implementation of the sequential Monte Carlo algorithm for approximation of posterior distributions.
Julia implementation of self-tuning tempered particle filter from Herbst and Schorfheide (2017) for likelihood evaluation of non-linear models with non-Gaussian innovations. Code is integrated into the NY Fed's package of filtering and smoothing routines for state-space models, StateSpaceRoutines.jl.
Julia package to build custom model types for simulation and estimation exercises.
This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, explore the benefits of an SMC variant we devise termed …