A bivariate second-order VAR model of money growth and inflation is specified and estimated by means of least squares. The bias of the parameter estimates is approximated in three ways and new, bias-reduced estimates are computed using the approximations. The effects of bias reduction on...

In the paper we investigate, which shocks drive inflation in small open economies. We proceed in two steps. First, we use the SVAR approach to identify the global shocks. In the second step we regress the disaggregated price indices for selected European economies - the Czech Republic, Poland...

Vector autoregressions combined with Minnesota-type priors are widely used for macroeconomic forecasting. The fact that strong but sensible priors can substantially improve forecast performance implies VAR forecasts are sensitive to prior hyperparameters. But the nature of this sensitivity is...

Vector autoregressions combined with Minnesota-type priors are widely used formacroeconomic forecasting. The fact that strong but sensible priors can substantially improve forecast performance implies VAR forecasts are sensitive to prior hyperparameters. But the nature of this sensitivity is...

We estimate the effects of domestic and international sources of macroeconomic uncertainty in three commonly studied small open economies (SOEs): Australia, Canada and New Zealand. To this end, we propose a common stochastic volatility in mean panel VAR (CSVM-PVAR), and develop an efficient...

Interest rate data are an important element of macroeconomic forecasting. Projections of future interest rates are not only an important product themselves, but also typically matter for forecasting other macroeconomic and financial variables. A popular class of forecasting models is linear...

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced...

The paper implements a consistent empirical strategy in order to investigate the behaviour of the markup over the cycle and its contribution to inflation movements.We model the price series as I(2) components and use polynomial cointegration in order to recover a long-run price schedule. We do...

This paper shows how to compute the h-step-ahead predictive likelihood for any subset of the observed variables in parametric discrete time series models estimated with Bayesian methods. The subset of variables may vary across forecast horizons and the problem thereby covers marginal and joint...

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...