The paper presents a new method to solve DSGE models with a great number of heterogeneous agents. Using tools from systems and control theory, it is shown how to reduce the dimension of the state and the policy vector so that the reduced model approximates the original model with high precision....

While DSGE models have been widely used by central banks for policy analysis, they seem to have been ineffective in calibrating the models for anticipating financial crises. To bring DSGE models closer to real situations, some of researchers have revised the traditional DSGE models. One of the...

We show how to use a simple perturbation method to solve non-linear rational expectation models. Drawing from the applied mathematics literature we propose a method consisting of series expansions of the non-linear system around a known solution. The variables are represented in terms of their...

The benefit from using second-order approximations tostochastic dynamic rational expec- tations models is explained. By example of the neoclassical growth model, this note as- sesses the accuracy of the obtained approximation. The implications for optimal policy are discussed.

We propose a simple and powerful numerical algorithm to compute the transition process in continuous-time dynamic equilibrium models with rare events. In this paper we transform the dynamic system of stochastic differential equations into a system of functional differential equations of the...

Value function iteration is one of the standard tools for the solution of the Ramsey model. We compare six different ways of value function iteration with regard to speed and precision. We find that value function iteration with cubic spline interpolation between grid points dominates the other...

We describe an algorithm that is able to compute the solution of a singular linear difference system under rational expectations. The algorithm uses the Generalized Schur Factorization and is illustrated by a simple example.

The BoltzmannGibbs distribution is currently widely used in economic modeling. One of the applications is integrated with the DSGE (Dynamic Stochastic General Equilibrium) model. However, a question that arises concerns whether the BoltzmannGibbs distribution can be directly applied, without...

Bayesian inference for DSGE models is typically carried out by single block random walk Metropolis, involving very high computing costs. This paper combines two features, adaptive independent Metropolis-Hastings and parallelisation, to achieve large computational gains in DSGE model estimation....

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time. Improved Metropolis-Hastings prefetching algorithms are presented and evaluated. It is shown how to use...