A Direct Monte Carlo (DMC) approach is introduced for posterior simulation in theInstrumental Variables (IV) model with one possibly endogenous regressor, multipleinstruments and Gaussian errors under a flat prior. This DMC method can also beapplied in an IV model (with one or multiple...

We estimate the approximate nonlinear solution of a small DSGE model on euro area data, using the conditional particle filter to compute the model likelihood. Our results are consistent with previous findings, based on simulated data, suggesting that this approach delivers sharper inference...

This paper compares responses to monetary shocks in the EMU countries (in the pre-EMU sample) and in the New Member States (NMS) from Central Europe. The small-sample problem, especially acute for the NMS, is mitigated by using a Bayesian estimation procedure which combines information across...

This paper addresses two important questions that have, so far, been studied separately in the literature. First, the paper aims at explaining the high volatility of long-term interest rates observed in the data, which is hard to replicate using standard macro models. Building a small-scale...

This paper aims to evaluate if frictions in credit markets are important for business cycles in the U.S. and the Euro area. For this purpose, I modify the DSGE financial accelerator model developed by Bernanke, Gertler and Gilchrist (1999) by adding frictions such as price indexation to past...

We estimate a reduced-form model of credit risk that incorporates stochastic volatility in default intensity via stochastic time-change. Our Bayesian MCMC estimation method overcomes nonlinearity in the measurement equation and state-dependent volatility in the state equation. We implement on...

In this paper, we calculate the realized volatility measures using intraday data not equally spaced in time. The aim is to compare these measures with the ones from the stochastic volatility model. With this model, the data used are obtained in equal time intervals. Known facts are that the...

A number of recent papers have concluded that stochastic volatility plays a prominent role in describing the business cycle, particularly for the characterization of monetary policy. The impact of including stochastic volatility in DSGE models remains, however, unexplored. This paper therefore...

I describe algorithms for drawing from distributions using adaptive Markov chain Monte Carlo (MCMC) methods, introduce a Mata function for per- forming adaptive MCMC, amcmc(), and a suite of functions amcmc_*() allowing an implementation of adaptive MCMC using a structure. To ease use in...

In this article, we propose the Bayesian estimation of the parsimonious but effective GARCH(1,1) model with Normal innovations. We sample the parameters joint posterior distribution using the approach suggested by Nakatsuma (1998). As a first step, we fit the model to foreign exchange...