T. Ryan Johnson

About Me

I use big administrative data, geographic information systems (GIS), and formal mathematical models of choice to study how institutional rules and market forces shape the behavior and attitudes of individuals.

Research Interests

• American Politics: representation and electoral systems
• Political Methodology: Bayesian statistics, causal inference, spatial statistics
• Formal Theory: political economy, structural estimation

Publications

Working Papers

• "Kriging for Robust Standard Errors"
• "On using a random effect with a Gaussian process prior instead of a spatial trend"

Research in Progress

• "Flood Risk and Turnout"
• "Modeling Spatial Effects with Gaussian Processes"
• "Estimating the Random Coefficients Logit with Voter Files"

Software

• gpd (Gaussian process derivatives), an addon for the gpml toolkit

Teaching

     Saint Louis University, Department of Computer Science

• Introduction to Computer Science: Taming Big Data - CSCI 1070 (Fall 2024)

     Saint Louis University, Department of Earth and Atmospheric Sciences

• Introduction to Geographic Information Systems - GIS 4010/5010 (Fall 2024)

     Washington University in St. Louis, Department of Political Science

         TA for PhD courses:

• Math Camp (Summer 2021, Summer 2022)
• Applied Statistical Programming (Spring 2022)
• Formal Models of Political Institution (Fall 2021)
• American Political Institutions (Fall 2021)
• Causal Inference (Spring 2021)
• Computational Social Science (Fall 2020)
• Theories of Individual and Collective Choice II (Spring 2020)
• Mathematical Modeling (Fall 2019)

     Sam Houston State University, Department of Mathematics & Statistics

• Developmental Mathematics II (Fall 2011, Spring 2012, Fall 2012, Spring 2013)

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