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How is Machine Learning Useful for Macroeconomic …

How is Machine Learning Useful forMacroeconomic forecasting ? Philippe Goulet Coulombe1 Maxime Leroux2 Dalibor Stevanovic2 St phane Surprenant21 University of Pennsylvania2 Universit du Qu bec Montr alThis version: February 28, 2019 AbstractWe move beyondIs Machine Learning Useful for Macroeconomic forecasting ?by addingthehow. The current forecasting literature has focused on matching specific variables andhorizons with a particularly successful algorithm. To the contrary, we study a wide rangeof horizons and variables and learn about the usefulness of the underlying features driv-ing ML gains over standard macroeconometric methods. We distinguish 4 so-called fea-tures (nonlinearities, regularization, cross-validation and alternative loss function) andstudy their behavior in both the data-rich and data-poor environments. To do so, wecarefully design a series of experiments that easily allow to identify the treatment effectsof interest.

nomic forecasting.2 However, those studies share many shortcomings. Some focus on one particular ML model and on a limited subset of forecasting horizons. Other evaluate the per-formance for only one or two dependent variables and for a limited time span. The papers on comparison of ML methods are not very extensive and do only a forecasting ...

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