Philippe Goulet Coulombe, Massimiliano Marcellino, D. Stevanovic
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CAN MACHINE LEARNING CATCH THE COVID-19 RECESSION?
Based on evidence gathered from a newly built large macroeconomic dataset (MD) for the UK, labelled UK-MD and comparable to similar datasets for the United States and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine learning (ML) methods. But not all nonlinear ML methods are alike. For instance, some do not allow to extrapolate (like regular trees and forests) and some do (when complemented with linear dynamic components). This and other crucial aspects of ML-based forecasting in unprecedented times are studied in an extensive pseudo-out-of-sample exercise.
期刊介绍:
The National Institute Economic Review is the quarterly publication of the National Institute of Economic and Social Research, one of Britain"s oldest and most prestigious independent research organisations. The Institutes objective is to promote, through quantitative research, a deeper understanding of the interaction of economic and social forces that affect peoples" lives so that they may be improved. It has no political affiliation, and receives no core funding from government. Its research programme is organised under the headings of Economic Modelling and Analysis; Productivity; Education and Training and the International Economy.