In this paper we present and describe a large quarterly frequency, macroeconomic
database. The data provided are closely modeled to that used in Stock and Watson (2012a) …

Abstract Large Bayesian VARs with stochastic volatility are increasingly used in empirical
macroeconomics. The key to making these highly parameterized VARs useful is the use of …

We propose a new variational approximation of the joint posterior distribution of the log-
volatility in the context of large Bayesian VARs. In contrast to existing approaches that are …

Time-varying parameter VARs with stochastic volatility are routinely used for structural
analysis and forecasting in settings involving a few endogenous variables. Applying these …

Bayesian vector autoregressions are widely used for macroeconomic forecasting and
structural analysis. Until recently, however, most empirical work had considered only small …

Abstract Mixed frequency Vector Autoregressions (MF-VARs) can be used to provide timely
and high frequency estimates or nowcasts of variables for which data is available at a low …

In this paper, we propose a hierarchical shrinkage approach for multi‐country VAR models.
In implementation, we consider three different scale mixtures Normals priors and provide …

We propose an alternative approach towards cost mitigation in volatility-managed portfolios
based on smoothing the predictive density of an otherwise standard stochastic volatility …

We propose an alternative approach towards cost mitigation in volatility-managed portfolios
based on smoothing the predictive density of an otherwise standard stochastic volatility …

Over the last decade, big data have poured into econometrics, demanding new statistical
methods for analysing high-dimensional data and complex non-linear relationships. A …