Training at EML

The Economic Machine Learning Lab supports training in modern econometric and machine learning methods through workshops, graduate courses, and lecture series.

These activities are designed to help students and researchers engage with tools for high-dimensional data, functional data analysis, machine learning, and economic applications.

Past Workshops and Courses

Workshop on Machine Learning in Econometrics

August 19-23, 2024Instructors: Joon Park and Yoosoon Chang

A focused workshop covering core methods in machine learning and econometrics, including large-dimensional regression, kernel methods, support vector machines, tree-based methods, and neural networks.

  • Large Dimensional Regression: PCA, Ridge and Lasso
  • Reproducing Kernel Hilbert Space: Kernel Method
  • Support Vector Machine: Linear and Kernel Trick
  • Tree-Based Approach: Random Forest and XGBoost
  • Neural Network: Vanilla and Recurrent Form
Workshop Materials

Econometrics of Big Data and Machine Learning (ECON 724)

Instructor: Joon Y. Park

This course prepares Ph.D. students for dissertation research in econometrics of big data and machine learning, both theoretical and empirical.

  • Functional Data Analysis
  • Machine Learning
Syllabus

Lectures on Econometrics of Big Data and Machine Learning

May 6-7, 2025Instructor: Simon Sokbae Lee

A lecture series on identification and estimation of persuasion effects, featuring recent work on concepts, instrumental variables, differences-in-differences, and monotonicity assumptions.