Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure

Forecasting with Medium and Large Bayesian VARs

This paper is motivated by the recent interest in the use of Bayesian VARs for forecasting, even in cases where the number of dependent variables is large. In such cases, factor methods have been traditionally used but recent work using a particular prior suggests that Bayesian VAR methods can forecast better. In this paper, we consider a range of alternative priors which have been used with sm...

Common Drifting Volatility in Large Bayesian VARs∗

The general pattern of estimated volatilities of macroeconomic and financial variables is often broadly similar. We propose two models in which conditional volatilities feature comovement and study them using U.S. macroeconomic data. The first model specifies the conditional volatilities as driven by a single common unobserved factor, plus an idiosyncratic component. We label this model BVAR wi...

Models with a Kronecker Product Covariance Structure: Estimation and Testing

In this article we consider a pq-dimensional random vector x distributed normally with mean vector θ and the covariance matrix Λ, assumed to be positive definite. On the basis of N independent observations on the random vector x, we wish to estimate parameters and test the hypothesis H: Λ = Ψ ⊗Σ, where Ψ = (ψij) : q × q and Σ = (σij) : p × p, and Λ = (ψijΣ), the Kronecker product of Ψ and Σ. Th...

Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices

More on the Kronecker Structured Covariance Matrix

Martin Ohlson, M. Rauf Ahmad and Dietrich von Rosen, More on the Kronecker Structured Covariance Matrix, 2012, Communications in Statistics Theory and Methods, (41), 13-14, 2512-2523. Communications in Statistics Theory and Methods is available online at informaworld TM : http://dx.doi.org/10.1080/03610926.2011.615971 Copyright: Taylor & Francis: STM, Behavioural Science and Public Health Title...