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 0700 Research Methods in Political Science
PS 1702 Visualizing and Understanding Social Data
PS 2720 Bayesian Statistics

Education & Training

  • PhD, Harvard University, 2020

Representative Publications

Goplerud, Max and Daniel M. Smith. Forthcoming. "Who Answers for the Government? Bureaucrats, Ministers, and Responsible Parties". American Journal of Political Science.

Goplerud, Max. 2021. "Fast and Accurate Estimation of Non-Nested Binomial Hierarchical Models Using Variational Inference". Bayesian Analysis. Advance Access.

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.

Goplerud, Max. 2019. "A Multinomial Framework for Ideal Point Estimation." Political Analysis. 27(1):69-89.

 

 

 

 

Research Interests

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

CV

Area of Study