Shiro Kuriwaki

Postdoctoral Scholar, Stanford University (2021-2022)

To be Assistant Professor of Political Science, Yale University (2022-)

My research focuses on democratic representation in American Politics. In an ongoing project, I study the structure of voter's party choices across levels of national, state, and local government, using cast vote records and surveys. My other projects include public opinion and Congress, election administration, and the intersection of survey statistics and causal inference. I received my Ph.D. from the Department of Government at Harvard University (2021) and my B.A. from Princeton University (2014), and previously worked at the Analyst Institute in Washington D.C.

Curriculum Vitae
Encina Hall West
Stanford University
Stanford, CA 94305

swing-D swing-R

Peer-Reviewed Publications

American Politics

Survey Statistics and Demography

Education in Political Science

Selected Working Papers


Book Project: Congressional Representation

(with Stephen Ansolabehere)

This book, tentatively titled Congressional Representation, argues that through all of the gridlock and the polarization that has plagued the government over the past three decades, the U.S. Congress remains a largely majoritarian institution. Congress acts in line with the majority of people more often than not. Building on 15 years of data on public preferences of more than 500,000 Americans, this study examines what voters know, what they care about when they vote, and how well their legislators and their Congress reflect their preferences. Representation is not a seamless or mechanical process, but it aggregates peoples' beliefs and preferences well on the important issues that face the country. Individual voters do not follow the details of congressional legislation but most know enough to hold correct beliefs about legislation and to hold their representatives accountable. For their part, legislators are highly responsive to the aggregate opinion of their districts. And, on important bills, Congress makes decisions in line with the majority of the nation. When representation fails, it is often the obstruction of one branch of government or one party.


I have taught classes on American Politics, Japanese Politics, statistics, and programming, at the undergraduate, Masters, and PhD level. I received the 2020 Dean's Excellence in Teaching Award at the Harvard Kennedy School of Public Policy for my teaching in econometrics and shepherding the use of the R statistical language in its core statistics sequence. This work included creating portable screencasts of R workflows, covering common topics in econometrics, causal inference, data science, quantitative social science.

I am a RStudio certified trainer, and have created several resources for statistics and data science for the social sciences that I hope are useful for other students and instructors. These include a workshop I co-designed on training teachers in the social sciences for teaching statistics and programming my presentations on project-oriented workflow (invited presentation, Toronto Data Workshop), introduction to version control with GitHub (source), introduction to Stata (source), and statistics notes covering Probability, Inference, and Regression written for a Masters-level statistics course (source).

On teaching writing, I edited Susan T. Fiske's writing advice: "Words to the Wise on Writing Scientific Papers" (Fiske and Kuriwaki, 2021).


About the banner image: Survey data from the Cumulative CCES, limited to validated voters in contested districts who voted for a major party in the Presidency and House. Estimates are made at the congressional district level and use Multilevel Regression Poststratification (MRP) stratifying on age, gender, education from the ACS and using House candidate incumbency status and presidential voteshare as district-level predictors. In presidential years the values represent ticket splitting (e.g. Trump voters who voted for a 2016 Democratic House candidate); in midterm years they represent party switch from the previous presidential election (e.g. Trump voters who voted for a 2018 Democratic House candidate). Districts where a Democrat and Republican candidate did not contest the general election are left blank. Figure created by Shiro Kuriwaki.

About this website: This website uses code from Minimal Mistakes, Github Pages, uses some CSS from Matt Blackwell's website at the time, and is inspired by Sarah Bouchat's website and Andrew Hall's website.