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...

This paper firstly describes the role of models in producing OECD global macroeconomic forecasts; secondly, reviews the OECD's forecasting track record; and finally, considers the relationship between forecast performance and models. OECD forecasts are not directly generated from a single global...

Eight years have passed since the European Central Bank (ECB) launched its Survey of Professional Forecasters (SPF). The SPF asks a panel of approximately 75 forecasters located in the European Union (EU) for their short- to longer-term expectations for macroeconomic variables such as euro area...

The present paper develops Adaptive Trees, a new machine learning approach specifically designed for economic forecasting. Economic forecasting is made difficult by economic complexity, which implies non-linearities (multiple interactions and discontinuities) and unknown structural changes (the...

The Great Recession and the subsequent period of subdued GDP growth in most advanced economies have highlighted the need for macroeconomic forecasters to account for sudden and deep recessions, periods of higher macroeconomic volatility, and fluctuations in trend GDP growth. In this paper, we...