Quantitative Methods research at NYU Politics

The Politics Department at NYU has numerous offerings for PhD students interested in studying and developing quantitative methods.

The Department has a full two-year quantitative methods sequence, covering foundations of probability and data analysis, causal inference, parametric and structural modeling, machine learning, text analysis, design and analysis of field experiments, analyzing social media data, among other topics. I personally teach the PhD-level second-semester causal inference course as well as a second-year PhD-level course on advanced research design. You can see current versions of these through links on my Teaching page.

For most students, this would be more than enough, but then students occasionally also take courses on specialized topics such as machine learning, statistical programming, or advanced probability theory at the Center for Data Science or at Courant.

A few faculty in the department also advise and coauthor with students on pure and applied methodological research. Activities that I personally have been leading over the past few years include the following:

  • Pure methodological research on interference/spillover effects; partial identification for principal effects; generalization, extrapolation, and external validity for causal effects; variance estimation and frequentist inference for data exhibiting complex dependencies (see my research page);

  • Applied work on designing efficient randomized controlled trials for governance interventions (again, see my research page);

  • A graduate student methods reading group on advanced methods for inference, working through textbooks including A. van der Vaart’s Asymptotic Statistics, M. Wainwright’s High Dimensional Statistics, and J. Davidson’s Stochastic Limit Theory; and

  • A methods workshop that involves both student presentations and presentations by methodologists from other biostatistics, economics, political science, sociology, and statistics departments.

For students admitted to the PhD program and interested to learn more, please feel free to contact me.