Econometric Machine Learning Methods and Models

1 Course Unit

This course covers econometric methods, machine learning methods, and their interface, focusing on aspects of estimation, inference, and prediction in causal and non-causal environments. Topics may include Bayesian learning; recursive estimation and optimal filtering; randomized controlled trials and their approximation; latent variables; classification; topic analysis; LDA models; neural networks; random forests; regularization (shrinkage, selection, ...); network estimation and description. Fall or Spring Prerequisite: ECON 2300 AND ECON 2310 AND (MATH 1400 OR MATH 1070) AND (MATH 1410 OR MATH 1080) 1 Course Unit