Philippe Goulet Coulombe

I apply Machine Learning to time series econometrics. Additionally, I apply time series econometrics to climate modelling.

Research 

  1. You can find the working paper of How is Machine Learning Useful for Macroeconomic Forecasting? here. It is joint work with Dalibor Stevanovic, Maxime Leroux and Stéphane Surprenant (all from UQÀM).
  2. The latest draft of Time-Varying Parameters: A Machine Learning Approach is here
  3. || NEW  ||  Draft of Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis with Maximilian Göbel (U of Lisbon) is out on Arxiv. Slides here.
  4. || NEW  ||  Draft of Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach is on Arxiv. It is joint work with Frank Diebold, Maximilian Göbel, Glenn Rudebusch and Boyuan Zhang.
  5. || NEW  ||  The Macroeconomy as a Random Forest is on Arxiv and SSRN.
  6. || NEW  ||  Macroeconomic Data Transformations Matter is on Arxiv. It is joint work with Dalibor Stevanovic, Maxime Leroux and Stéphane Surprenant (all from UQÀM).

Misc

  • (En français) High-level interview at CISM 89.3 on applications of AI/ML in economics, with a focus on macro forecasting. Starts around 32 min.
  • Music to listen to when coding 

 

 

 

 

Teaching Assignments
Course Title
ECON 103 - Statistics for Economists (TA)

pgcpic_181002

Start Date
2016
Email
gouletc@sas.upenn.edu
Office Location
PCPSE 546

Working Papers