This paper deals with Dynamic Stochastic General Equilibrium (DSGE) models under a multivariate student-<italic>t</italic> distribution for the structural shocks. Based on the solution algorithm of Klein (2000) and the gamma-normal representation of the <italic>t</italic>-distribution, the TaRB-MH algorithm of Chib and...

This paper provides a concise primer on the estimation of constant gain learning models. One practical concern in the estimation procedure is the initialization of the learning parameters. The popular approach in the literature relies on a training sample to estimate these quantities. We also...

Modern Bayesian tools aided by MCMC techniques allow researchers to estimate models with increasingly intricate dynamics. This paper highlights the application of these tools with an empirical assessment of optimal versus operational monetary policy rules within a standard New Keynesian...

Since the financial meltdown of 2007, advanced macroeconomic theory has delved more deeply into the question of the appropriate fiscal policy when the nominal interest rate is close to or at zero percent. Such analysis is typically conducted with the aid of New Keynesian Dynamic Stochastic...

This paper is concerned with the Bayesian estimation of non-linear stochastic differential equations when observations are discretely sampled. The estimation framework relies on the introduction of latent auxiliary data to complete the missing diffusion between each pair of measurements. Tuned...

The authors examine autoregressive time series models subject to regime switching. A Bayesian framework is develope d in which the unobserved.states, one for each time point, are treated as missing data and then analyzed using the Gibbs sampler. This approac h is straightforward because the...

Kim, Shephard, and Chib (1998) provided a Bayesian analysis of stochastic volatility models based on a fast and reliable Markov chain Monte Carlo (MCMC) algorithm. Their method ruled out the leverage effect, which is known to be important in applications. Despite this, their basic method has...

We provide a detailed summary of the large and vibrant emerging literature that deals with the multivariate modeling of conditional volatility of financial time series within the framework of stochastic volatility. The developments and achievements in this area represent one of the great success...