Instructors

Stephane Bonhomme (University of Chicago)

Dates

17-21 August 2026

Hours

9:30 to 13:00 CEST

Format

In person

Practical Classes

Two to three optional afternoon sessions (15:00 - 17:00), led by a teaching assistant. Exact dates will be announced before the start of the course.

Intended for

Applied researchers and econometricians interested in estimating economic models using panel data.

Prerequisites

Master’s-level courses in probability and statistics, and econometrics.

Overview

This course provides applied researchers and econometricians with tools to estimate dynamic models using panel data. Particular emphasis is placed on relaxing strict exogeneity assumptions, which are widely used in empirical work-including difference-in-differences designs and event studies-but are often economically and empirically restrictive.

We will review classic methods for estimating linear dynamic panel data models with sequentially exogenous covariates. We will then discuss more recent approaches that extend these methods to settings with nonlinearities, coefficient heterogeneity, and network dynamics.

Topics

• Conceptual foundations: strict exogeneity, sequential exogeneity, and feedback
• Bias in models with dynamic feedback
• Implications for difference-in-differences and event-study designs
• Classic dynamic panel data methods I: GMM
• Classic dynamic panel data methods II: quasi-likelihood and large-T approaches
• Coefficient heterogeneity in models with dynamic feedback
• Nonlinear models with dynamic feedback
• Dynamic models in networks

Stéphane Bonhomme is the Ann L. and Lawrence B. Buttenwieser Professor in Economics and the College at the University of Chicago. Bonhomme’s work advances methodological approaches for the estimation of economic models, with a focus on panel data models and unobserved heterogeneity. His recent research includes studies of team networks, new methods for nonlinear panel data models with feedback, and models of income dynamics with aggregate shocks. Bonhomme is a Fellow of the Econometric Society. He is a former co-editor at the Review of Economic Studies and Editor of Quantitative Economics, and a Co-Director of the Big Data Initiative at the Becker Friedman Institute for Research in Economics. He earned his Ph.D. in Economics from the University of Paris I, Panthéon-Sorbonne.