We compare the performance of six classes of models at forecasting di↵erent types of economic series in an extensive pseudo out-of-sample exercise. Our findings can be summarized in a few points: (i) Regularized Data-Rich Model Averaging techniques are hard to beat in general and are the best...

The performance of six classes of models in forecasting different types of economic series is evaluated in an extensive pseudo out‐of‐sample exercise. One of these forecasting models, regularized data‐rich model averaging (RDRMA), is new in the literature. The findings can be summarized in...

This paper describes a large-scale Canadian macroeconomic database in monthly frequency. The dataset contains hundreds of Canadian and provincial economic indicators observed from 1981. It is designed to be updated regularly through StatCan database and is publicly available. It relieves users...

This paper proposes a simple nonlinear framework to produce real-time multi-horizon forecasts of economic activity as well as conditional forecasts that depend on whether the horizon of interest belongs to a recessionary episode or not. Our forecasting models take the form of an autoregression...

This paper tackles the prediction of the probability and severity of US recessions. We employ parsimonious Probit models to estimate the probability of a recession h periods ahead, for h varying between 1 and 8 quarters. A novel goodness-of-fit measure derived from the Kullback-Leibler...