We introduce a class of large Bayesian vector autoregressions (BVARs) that allows for non-Gaussian, heteroscedastic and serially dependent innovations. To make estimation computationally tractable, we exploit a certain Kronecker structure of the likelihood implied by this class of models. We...

This article investigates the estimation and inference of quantile impulse response functions. We propose a new estimation method using the local projections by Jordà (2005). We establish consistency and asymptotic normality of the estimator, thereby enabling asymptotic inference. We also...

This paper considers a multivariate system of fractionally integrated time series and investigates the most appropriate way for estimating Impulse Response (IR) coefficients and their associated confidence intervals. The paper extends the univariate analysis recently provided by Baillie and...

This paper proposes the use of the bootstrap when the system Wald test is employed to test for linear restrictions in a stationary vector autoregressive (VAR) model. The bootstrap test is conducted using the generalized least square estimator for VAR parameters, which takes account of...

In this paper, we provide evidence that fat tails and stochastic volatility can be important in improving in-sample fit and out-of-sample forecasting performance. Specifically, we construct a VAR model where the orthogonalised shocks feature Student's t distribution and time-varying variance. We...

This paper proposes a multivariate least squares Mallows averaging approach to the issue of forecast combination by vector autoregressive (VAR) model fitting. Our approach extends the current literature on frequentist least squares model/forecast averaging methods, in particular Hansen (2008),...

Building upon the insight that M1 velocity is the permanent component of nominal interest rates - see Benati (2020) - I propose a novel, and straightforward approach to estimating the natural rate of interest, which is conceptually related to Cochrane's (1994) proposal to estimate the permanent...