Max Goplerud

  • Assistant Professor

Max Goplerud is an Assistant Professor of Political Science. His primary research creates new methods to facilitate political science research by leveraging the intersection of Bayesian methods and machine learning. These methods are focused on topics such as heterogeneous effects, hierarchical models, and ideal point estimation. He also is interested in understanding legislative behavior using text-as-data in a comparative context including studies on Europe, the United States, and Japan. He received his PhD from the Department of Government at Harvard University in 2020.

Courses

PS 1702 Coding & Computational Social Science  

Education & Training

  • PhD, Harvard University, 2020

Representative Publications

https://doi.org/10.1017/pan.2018.31 - Goplerud, Max. 2019. "A Multinomial Framework for Ideal Point Estimation." Political Analysis. 27(1):69-89

https://onlinelibrary.wiley.com/doi/abs/10.1111/lsq.12226 Fernandes, Jorge, Max Goplerud, and Miguel Won. 2019. "Legislative Bellwethers: The Role of Committee Membership in Parliamentary Debate." Legislative Studies Quarterly. 44(2):307-343.

Research Interests

Bayesian statistics
Machine learning
Text-as-data
Comparative political institutions
Legislative politics

CV

Area of Study