This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not globally. In this case there exists a set of isolated structural parameter points that are observationally equivalent under the imposed restrictions. Although the...

Stochastic volatility models are very flexible models able to characterize financial volatility evolution. This article explores computational capabilities based on Graphical Processing Units to simulate many Monte Carlo Markov chains in estimating stochastic volatility model parameters through...

Stochastic volatility models are very flexible models able to characterize financial volatility evolution. This article explores computational capabilities based on Graphical Processing Units to simulate many Monte Carlo Markov chains in estimating stochastic volatility model parameters through...

Vector autoregressions with Markov-switching parameters (MS-VARs) offer dramatically better data fit than their constant-parameter predecessors. However, computational complications, as well as negative results about the importance of switching in parameters other than shock variances, have...

Vector autoregressions with Markov-switching parameters (MS-VARs) fit the data better than do their constant-parameter predecessors. However, Bayesian inference for MS-VARs with existing algorithms remains challenging. For our first contribution, we show that Sequential Monte Carlo (SMC)...

Under inflation targeting inflation exhibits negative serial correlation in the United Kingdom, and little or no persistence in Canada, Sweden and New Zealand, and estimates of the indexation parameter in hybrid New Keynesian Phillips curves are either equal to zero, or very low, in all...