Inference on the long-run properties of a Vector Autoregression (VAR) consisting wholly of I(1) variables are made using Bayesian methods. In particular, the implications on the forecast and impulse response function distributions of directly estimating and restricting the drift parameters of...

Since Russia's invasion of Ukraine, many countries have pledged to end or restrict their oil and gas imports to curtail Moscow's revenues and hinder its war effort. Thus, the European ministers agreed to trigger a cap on the gas price. To detect the importance of the price cap for gas, we...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and compare their predictive performance with the most promising existing alternatives, namely, factor models, large scale...

With prospective payment of hospitals becoming more common, measuring their performance is gaining in importance. However, the standard cost frontier model yields biased efficiency scores because it ignores technological heterogeneity between hospitals. In this paper, efficiency scores are...

Using a panel of 24 OECD countries for the sample 1990-2019 and a standard macroeconomic framework, the paper tests the combined macroeconomic effects of climate change, environmental policies and technology. Overall, we find evidence of significant macroeconomic effects over the business cycle:...

This paper compares responses to monetary shocks in the EMU countries (in the pre-EMU sample) and in the New Member States (NMS) from Central Europe. The small-sample problem, especially acute for the NMS, is mitigated by using a Bayesian estimation procedure which combines information across...

There has been a call for caution when using the conventional method for Bayesian inference in setidentified structural vector autoregressions on the grounds that the uniform prior over the set of orthogonal matrices could be nonuniform for individual impulse responses or other quantity of...

Factor modelling extracts common information from a high-dimensional data set into few common components, where the latent factors usually explain a large share of data variation. Exploratory factor estimation induces sparsity into the loading matrix to associate units or series with those...

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock transmission mechanism. This requires the VAR parameters to be stable over the evaluation and forecast sample, or to explicitly consider parameter time variation. The earlier...