Econometrics II

Catalog description

This course continues the econometrics sequence, turning to broader estimation paradigms and more advanced inference concepts. The course aims to give students a rigorous theoretical understanding along with a practical understanding of how to implement econometric methods. Topics include nonlinear estimation, maximum likelihood estimation, discrete choice models, generalized method of moments, bootstrapping, model selection, and panel data. Influential studies from labor economics and industrial organization will illustrate important concepts and methods.