The Themed Issue Machine Learning for Economic Policy consists of 12 papers at the intersection of machine learning, nontraditional data sources and economic policymaking[...]

This study reevaluates crude oil price forecasts from state-of-the-art VAR models (Baumeister et al., 2022). Unlike Baumeister et al., who use the average-price no-change[...]

Forecast combinations, also known as ensemble models, routinely require practitioners to select a model from a massive number of potential candidates. Ten explanatory var[...]

This paper studies tail risk and its option-implied risk compensation in the crude oil market. We identify economically large premia for upside and downside tail risks th[...]

This paper assesses the usefulness of comprehensive payments data for macroeconomic predictions in Canada. Specifically, we evaluate which type of payments data are usefu[...]

Analyzing International Monetary Fund (IMF) data, we find that overly optimistic growth expectations for a country induce economic contractions a few years later. To isol[...]

Increased sovereign credit risk is often associated with sharp currency movements. Therefore, expectations of the probability of a sovereign default event can convey impo[...]

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In the empi[...]

Information on the allocation and pricing of over-the-counter (OTC) markets is scarce. Furfine (1999) pioneered an algorithm that provides transaction-level data on the O[...]

This paper provides evidence of the quality of private sector forecasts of the budget balance between 1993 and 2009 for a sample of 29 countries, grouped into advanced an[...]