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RD in State Legislatures? Not When You Have Local Randomization.
Insights from the Field
Regression Discontinuity
Local Randomization
Causal Inference
Slim Majority
District Races
American Politics
PSR&M
2 Stata files
2 datasets
Dataverse
Estimating Slim-Majority Effects in US State Legislatures with a Regression Discontinuity Design Under Local Randomization Assumptions was authored by Leandro De Magalhaes. It was published by Cambridge in PSR&M in 2021.

The classic regression discontinuity (RD) design requires continuous variables, but legislative majorities are finite.

➡️ This paper explores an alternative: treating narrow one-seat margins as local randomized experiments.

➡️ The authors implement recent econometric tests and propose a new approach for US state legislatures.

➡️ Their method allows analysis of small seat changes without needing continuous running variables.

➡️ Key findings reveal insights into slim majority impacts on close district races.

➡️ This provides novel ways to estimate the effects of near-majority control in legislative settings.

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Political Science Research & Methods
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