Random forest (RF) regression is an extremely popular tool for analyzing high-dimensional
data. Nonetheless, its benefits may be lessened in sparse settings due to weak predictors …

We consider the potential usefulness of a large set of electronic payments data, comprising
the values and numbers of both debit card transactions and cheques that clear through the …

Basel III seeks to improve the financial sector's resilience to stress scenarios which calls for
a reassessment of banks' credit risk models and, particularly, of their dependence on …

Agricultural baselines facilitate policy and investment decisions by governments and market
participants by providing long‐term projections about the farm sector. Despite their …

When assessing the predictive power of financial variables for economic activity,
researchers usually aggregate higher-frequency data before estimating a forecasting model …

Using a Bayesian learning model with heterogeneity across agents, our study aims to
identify the relative importance of alternative pathways through which professional …

We develop tests for the null hypothesis that forecasts become uninformative beyond some
maximum forecast horizon h∗. The forecast may result from a survey of forecasters or from …

We assess the usefulness of a large set of electronic payments data comprising debit and
credit card transactions, as well as cheques that clear through the banking system, as …

I provide a unifying perspective on forecast evaluation, characterizing accurate forecasts of
all types, from simple point to complete probabilistic forecasts, in terms of two fundamental …

Density forecasts, including the pioneering Bank of England 'fan charts', are often used to
produce forecast probabilities of a particular event. We use the Bank of England's forecast …