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Faculty & Research

The Macroeconomy as a Random Forest

14 Jan
2021
2:00 pm
English

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2021-01-14T14:00:00 2021-01-14T15:15:00 The Macroeconomy as a Random Forest Economics and Decision Sciences Department Guest speaker: Philippe Goulet Coulombe From: University of Pennsylvania Zoom Videoconference  

Economics and Decision Sciences Department

Guest speaker: Philippe Goulet Coulombe

From: University of Pennsylvania

Zoom Videoconference


 

Abstract :

“I develop Macroeconomic Random Forest (MRF), an algorithm adapting the canonical Machine Learning (ML) tool to flexibly model evolving parameters in a linear macro equation. Its main output, Generalized Time-Varying Parameters (GTVPs), is a versatile device nesting many popular nonlinearities (threshold/switching, smooth transition, structural breaks/change) and allowing for sophisticated new ones. The approach delivers clear forecasting gains over numerous alternatives, predicts the 2008 drastic rise in unemployment, and performs well for inflation. Unlike most ML-based methods, MRF is directly interpretable — via its GTVPs. For instance, the successful unemployment forecast is due to the influence of forward-looking variables (e.g., term spreads, housing starts) nearly doubling before every recession. Interestingly, the Phillips curve has indeed flattened, and its might is highly cyclical.”

Zoom link: https://hec-fr.zoom.us/j/94956531922

Participate

Add to Calendar
2021-01-14T14:00:00 2021-01-14T15:15:00 The Macroeconomy as a Random Forest Economics and Decision Sciences Department Guest speaker: Philippe Goulet Coulombe From: University of Pennsylvania Zoom Videoconference