Soichiro Yamauchi
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View article: The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level
The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level Open
Debates over racial voting, and over policies to combat vote dilution, turn on the extent to which groups’ voting preferences differ and vary across geography. We present the first study of racial voting patterns in every congressional dis…
View article: Replication Data for: The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level
Replication Data for: The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level Open
Abstract: Debates over racial voting, and over policies to combat vote dilution, turn on the extent to which groups' voting preferences differ and vary across geography. We present the first study of racial voting patterns in every congres…
View article: Vote Choice and Population Size by Geography, Demographics, and Turnout
Vote Choice and Population Size by Geography, Demographics, and Turnout Open
Modeled vote choice of geographic, demographic, and turnout subgroups with survey and ecological data in the US. The current version models Presidential vote choice in 2016 and 2020 for each contemporaneous congressional district and each …
View article: Change-Point Detection and Regularization in Time Series Cross-Sectional Data Analysis
Change-Point Detection and Regularization in Time Series Cross-Sectional Data Analysis Open
Researchers of time series cross-sectional data regularly face the change-point problem, which requires them to discern between significant parametric shifts that can be deemed structural changes and minor parametric shifts that must be co…
View article: Using Multiple Pretreatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs
Using Multiple Pretreatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs Open
While a difference-in-differences (DID) design was originally developed with one pre- and one posttreatment period, data from additional pretreatment periods are often available. How can researchers improve the DID design with such multipl…
View article: Replication Data for: Change-point Detection and Regularization in Time Series Cross Sectional Data Analysis
Replication Data for: Change-point Detection and Regularization in Time Series Cross Sectional Data Analysis Open
Researchers of time series cross sectional (TSCS) data regularly face the change-point problem, which re- quires them to discern between significant parametric shifts that can be deemed structural changes and minor parametric shifts that m…
View article: Replication Data for: Using Multiple Pre-treatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs
Replication Data for: Using Multiple Pre-treatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs Open
While a difference-in-differences (DID) design was originally developed with one pre- and one post-treatment period, data from additional pre-treatment periods are often available. How can researchers improve the DID design with such multi…
View article: The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level
The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level Open
Debates over racial voting, and over policies to combat vote dilution, turn on the extent to which groups' voting preferences differ and vary across geography. We present the first study of racial voting patterns in every congressional dis…
View article: Synthetic Area Weighting for Measuring Public Opinion in Small Areas
Synthetic Area Weighting for Measuring Public Opinion in Small Areas Open
The comparison of subnational areas is ubiquitous but survey samples of these areas are often biased or prohibitively small. Researchers turn to methods such as multilevel regression and poststratification (MRP) to improve the efficiency o…
View article: Adjusting for Unmeasured Confounding in Marginal Structural Models with Propensity-Score Fixed Effects
Adjusting for Unmeasured Confounding in Marginal Structural Models with Propensity-Score Fixed Effects Open
Marginal structural models are a popular tool for investigating the effects of time-varying treatments, but they require an assumption of no unobserved confounders between the treatment and outcome. With observational data, this assumption…
View article: Using Multiple Pre-treatment Periods to Improve Difference-in-Differences and Staggered Adoption Design
Using Multiple Pre-treatment Periods to Improve Difference-in-Differences and Staggered Adoption Design Open
While a difference-in-differences (DID) design was originally developed with one pre- and one post-treatment period, data from additional pre-treatment periods are often available. How can researchers improve the DID design with such multi…
View article: Difference-in-Differences for Ordinal Outcomes: Application to the Effect of Mass Shootings on Attitudes toward Gun Control
Difference-in-Differences for Ordinal Outcomes: Application to the Effect of Mass Shootings on Attitudes toward Gun Control Open
The difference-in-differences (DID) design is widely used in observational studies to estimate the causal effect of a treatment when repeated observations over time are available. Yet, almost all existing methods assume linearity in the po…
View article: Using LASSO to Assist Imputation and Predict Child Well-being
Using LASSO to Assist Imputation and Predict Child Well-being Open
This article documents an approach to predicting children’s well-being using data from the Fragile Families and Child Wellbeing Study, which are representative of births in large U.S. cities. The authors use the least absolute shrinkage an…