Even though the global contagion effects of the financial crisis have been well documented, the transmission mechanism as well as the nature of the volatility spillovers among the US, EU and the BRIC markets has not been systematically investigated. To examine the dynamic linear and nonlinear...

This paper proposes a Bayesian nonparametric modeling approach for the return distribution in multivariate GARCH models. In contrast to the parametric literature the return distribution can display general forms of asymmetry and thick tails. An infinite mixture of multivariate normals is given a...

We propose a new method for estimating the covariance matrix of a multivariate time series of nancial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the nal covariance estimate. We extend the...

We develop methods for Bayesian inference in vector error correction models which are subject to a variety of switches in regime (e.g. Markov switches in regime or structural breaks). An important aspect of our approach is that we allow both the cointegrating vectors and the number of...

The time profile of inflation in China resembles the one experienced in major industrial countries. Given the uncertainty surrounding the sources of economic shocks, this paper compares results from three sets of alternative identification conditions, namely the standard Blanchard-Quah approach,...

A notable feature of the 1920s and 1930s is the volatility in several key macroeconomic aggregates, and this feature used to econometrically identify the reaction of the Fed to stock market developments. The volatility of economic activity may have contributed to deepening the divisions among...

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.

We empirically test the hypothesis that stock market illiquidity affects real UK GDP growth using data over the period 1989q1-2012q2. We conduct our empirical exercise within a standard linear model as well as a non-linear model, which allows for regime switching behavior in terms of a liquid...

This paper develops methods for automatic selection of variables in Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic linear and nonlinear models, as well as models of large...

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with...