Associate Professor of Economics · Carleton University
Matthew D. Webb
Applied Microeconometrics · Causal Inference · Machine Learning and AI for Economic Measurement · Empirical Microeconomics
I develop and apply econometric methods for credible empirical research, with a particular focus on inference with clustered data and difference-in-differences designs. My current work also uses machine learning and AI to measure economically meaningful features in images and other complex data. I am also a Co-Director of the Centre for Economic Evidence on Migration (CEEM) at Carleton University.
Current Research
Good Controls Gone Bad: Difference-in-Differences with Covariates
Studies identification with time-varying covariates and introduces the Intersection Difference-in-Differences (DID-INT) estimator.
Paper · Software · Watch video
Improved Inference for CSDID
Cluster-jackknife inference for modern difference-in-differences estimators.
Paper · Software · Watch video
Representation Risk in Pretrained Image Encoders
Studies how plausible choices of pretrained image encoders can lead to different predictions and conclusions, and how to assess representation risk.
Paper · Software · Watch video
Research Software
The Software page is a curated guide to implementations of my research methods across Stata, R, Julia, and Python. It groups software by method, gives verified installation commands, connects each implementation to its paper, and credits the implementation author.
Latest Video
Good Controls Gone Bad: Difference-in-Differences with Covariates
Why covariate assumptions matter for difference-in-differences, and how integrated parallel trends and DID-INT can help.