Corpus ID: 214733560

Difference-in-Differences for Ordinal Outcomes: Application to the Effect of Mass Shootings on Attitudes toward Gun Control

  title={Difference-in-Differences for Ordinal Outcomes: Application to the Effect of Mass Shootings on Attitudes toward Gun Control},
  author={Soichiro Yamauchi},
  • Soichiro Yamauchi
  • Published 2020
  • Mathematics, Economics
  • 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 potential outcome (parallel trends assumption) and target the additive effect. In social science research, however, many outcomes of interest are measured on an ordinal scale. This makes the linearity assumption inappropriate because the difference between two… CONTINUE READING

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    Semiparametric Difference-in-Differences Estimators
    • 1,120
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    On negative outcome control of unobserved confounding as a generalization of difference-in-differences.
    • 15
    • Highly Influential
    • Open Access
    Treatment Effects on Ordinal Outcomes: Causal Estimands and Sharp Bounds
    • 12
    • Highly Influential
    • Open Access
    Mostly Harmless Econometrics: An Empiricist's Companion
    • 7,518
    • Open Access
    Difference-in-Differences with Multiple Time Periods
    • 71
    • Open Access
    Causal inference for ordinal outcomes
    • 12
    • Open Access
    Sharp nonparametric bounds and randomization inference for treatment effects on an ordinal outcome.
    • 7
    A technique for the measurement of attitudes
    • 10,643
    Generalized Nonlinear Difference-in-Difference-in-Differences
    • 2
    • Highly Influential
    • Open Access