Matthew D. Webb
Associate Professor
Research fields: applied econometrics and labour economics
Expertise:
• cluster robust inference
• bootstrap inference
• micro-data analysis
Refereed Publications in the Last 6 Years:
For a Complete List of Publications: Matthew Webb Google Scholar
Most Significant Career Research Contributions:
“Cluster-Robust Interference: A Guide to Empirical Practice,” (with James G. MacKinnon, and Morten Ø. Nielsen), Journal of Econometrics, Volume 232, Issue 2, 2023, Pages 272-299.
“Reworking Wild Bootstrap-Based Inference for Clustered Errors”, Canadian Journal of Economics, Volume 56, Issue 3, 2023, Pages 839-858.
“Fast and Wild: Bootstrap Inference in Stata using Boottest,” (with David Roodman, James G. MacKinnon, and Morten Ø. Nielsen), The Stata Journal, Volume 19, Issue 1, 2019, Pages 4–60.
“Randomization Inference for Difference-in-Differences with Few Treated Clusters,” (with James G. Mackinnon), Journal of Econometrics, Volume 218, Issue 2, October 2020, Pages 435-450.
“The Wild Bootstrap for Few (Treated) Clusters” (with James G. MacKinnon), Econometrics Journal, Volume 21, Number 2, June 2018, Pages 114-135.
“Wild Bootstrap Inference for Wildly Different Cluster Sizes” (with James G. MacKinnon), Journal of Applied Econometrics, Volume 32, Number 2, March 2017, Pages 233–254.
Share: Twitter, Facebook
Short URL:
https://carleton.ca/economics/?p=24577
