The Bayesian statistical paradigm provides a principled and coherent approach to
probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting …

The productivity growth slowdown in advanced economies during the early decades of the
21st century has led to renewed interest in economic measurement. Measured productivity …

This paper develops Bayesian econometric methods for posterior inference in non-
parametric mixed frequency VARs using additive regression trees. We argue that regression …

Abstract The ifo Institute is Germany's largest business survey provider, with the ifo Business
Climate Germany as one of the most important leading indicators for gross domestic product …

The COVID‐19 recession that started in March 2020 led to an unprecedented decline in
economic activity across the globe. To fight this recession, policy makers in central banks …

We develop an efficient sampling approach for handling complex missing data patterns and
a large number of missing observations in conditionally Gaussian state space models. Two …

Large Bayesian vector autoregressions with various forms of stochastic volatility have
become increasingly popular in empirical macroeconomics. One main difficulty for …

Timely characterizations of risks in economic and financial systems play an essential role in
both economic policy and private sector decisions. However, the informational content of low …

We investigate economic resilience of UK regions before, during and after the 2007/8 global
financial crisis. We date business cycle turning points in real output, employment and …

Abstract Mixed frequency Vector Autoregressions (MF-VARs) can be used to provide timely
and high frequency estimates or nowcasts of variables for which data is available at a low …