We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with …

There has been a call for caution when using the conventional method for Bayesian inference in setidentified structural …

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using …

approach using a Bayesian MS-VAR which is net of these arbitrary components. This method allows for the consistent …

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using …

We propose a blended approach which combines identification via heteroskedasticity with the widely used methods of sign … external instruments can prove necessary when the conditions for point identification through heteroskedasticity are not met … and offers a natural solution to the labeling problem inherent in purely statistical identification strategies. As a …

This paper proposes a Bayesian approach to assess if the data support candidate set-identifying restrictions for Vector …

In this paper we propose a SVAR identification strategy to disentangle two housing demand shocks and their ensuing …

We address the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector … Autoregressions. Whilst identification issues with long-run restrictions are well documented, we demonstrate that the recent attempt …-run specifications. We offer a new spectral methodology to improve empirical identification. This new preferred methodology offers …