Matthew Tyler

Bio

I’m an Assistant Professor in the Department of Political Science at Rice University. My research explores political methodology, with a focus on understanding and addressing measurement challenges in the study of partisan polarization and political behavior. I am a Principal Investigator on a National Science Foundation (NSF) CAREER grant, which supports my work on developing statistical solutions for survey measurement errors. I earned my PhD in Political Science from Stanford University in 2021 and hold bachelor’s degrees in Statistical Science and Mathematics from Duke University.

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Peer-Reviewed Publications

1. Tyler, Matthew, D. Sunshine Hillygus, Matthew DeBell, Ted Brader, Shanto Iyengar, Daron Shaw, Nicholas Valentino. “Why Are Surveys Struggling to Estimate Vote Shares?” Conditionally accepted, American Journal of Political Science.

2. Tyler, Matthew, Shanto Iyengar, Arjun Wilkins, et al. “Campaigns Reinforce Partisanship and Short-Term Forces: Evidence from a Large-Scale Panel Study of the 2020 US Presidential Campaign.” Conditionally accepted, Political Science Research and Methods

3. Grimmer, Justin, Michael C. Herron, and Matthew Tyler. “Evaluating a New Generation of Expansive Claims about Vote Manipulation.” 2024. Election Law Journal 23(3): 211-236. [DOI]

4. Tyler, Matthew and Shanto Iyengar. 2023. “Testing the Robustness of the ANES Feeling Thermometer Indicators of Affective Polarization.” American Political Science Review 118(3): 1570-1576. [DOI]

5. Tyler, Matthew, and Shanto Iyengar. 2023. “Learning to Dislike Your Opponents: Political Socialization in the Era of Polarization.” American Political Science Review 117(1): 347–354. [DOI]

6. Westwood, Sean J., Justin Grimmer, Matthew Tyler, and Clayton Nall. 2022. “Current Research Overstates American Support for Political Violence.” Proceedings of the National Academy of Sciences 119(12): e2116870119. [DOI]

7. Tyler, Matthew, Justin Grimmer, and Shanto Iyengar. 2022. “Partisan Enclaves and Information Bazaars: Mapping Selective Exposure to Online News.” The Journal of Politics 84(2): 1057–73. [DOI]

8. Marble, William, and Matthew Tyler. 2022. “The Structure of Political Choices: Distinguishing Between Constraint and Multidimensionality.” Political Analysis 30(3): 328–45. [DOI]

9. Fong, Christian, and Matthew Tyler. 2021. “Machine Learning Predictions as Regression Covariates.” Political Analysis 29(4): 467–84. [DOI]

Working Papers

• Tyler, Matthew. “Bounding causal effects in survey experiments with noncompliance or inattention.” [PDF]

• Tyler, Matthew, Justin Grimmer, and Sean J. Westwood. “A Statistical Framework to Engage the Problem of Disengaged Survey Respondents.” [PDF]

• Tyler, Matthew. “Counterfactual Forecasting: Causal Inference without Simultaneous Controls.” [PDF]

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