This Program for Economic Research (PER)’s Spring Mini Course will be held in two parts.
Part I: Thursday, April 2, 2020, 3:30-5:30pm (Uris 140) (get directions)
Part II: Friday, April 3, 2020, 3:30-5:30pm (Uris 331) (get directions)
*Open to current Columbia University students only
Jesús Fernández Villaverde, Professor of Economics, University of Pennsylvania.
Machine learning tools offer many intriguing possibilities for macroeconomists (and economists in general).
First, we can use machine learning tools such as deep learning and reinforcement learning to solve models with hundreds of state variables efficiently. Second, we can use machine learning to extract information from unstructured sources of data (text, images, social media) to estimate both reduced-form and structural dynamic economic models.
In this course, we will introduce some of these tools and illustrate how they can be applied in macroeconomics. While the applications will focus on macroeconomics, students from I.O., finance, labor economics, and other fields will find that most of what we will cover can be applied to their research areas. We will not assume further macro knowledge than the background from the first-year Ph.D. sequence.
Slides and codes will be available before the lectures.