Markov-switching dynamic stochastic general equilibrium (MSDSGE) modeling has become a growing body of literature on economic and policy issues related to structural shifts. This paper develops a general perturbation methodology for constructing high-order approximations to the solutions of...

In this paper, we explore a dynamical version of by Aoki and Yoshikawa model (AYM) for an economy driven by demand. We show that when an appropriate Markovian dynamics is taken into account, AYM has different equilibrium distributions depending on the form of transition probabilities. In the...

The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a posterior distribution spanning potentially nonnested models with parameter spaces of different dimensionality. We use the method to jointly sample from an ARMA process of unknown...

In this paper, the authors explore a dynamical version of the Aoki and Yoshikawa model (AYM) for an economy driven by demand. They show that when an appropriate Markovian dynamics is taken into account, the AYM has different equilibrium distributions depending on the form of transition...

We relax the standard assumption in the dynamic stochastic general equilibrium (DSGE) literature that exogenous processes are governed by AR(1) processes and estimate ARMA (p,q) orders and parameters of exogenous processes. Methodologically, we contribute to the Bayesian DSGE literature by using...