Splitting the difference? Causal Inference and theories of split-party delegations

Daniel M. Butler; Matthew J. Butler

doi:10.1093/pan/mpj010

Splitting the difference? Causal Inference and theories of split-party delegations

Daniel M. Butler
, Matthew J. Butler

Research output: Contribution to journal › Article › peer-review

28 Scopus citations

Abstract

We provide an introduction to the regression discontinuity design (RDD) and use the technique to evaluate models of sequential Senate elections predicting that the winning party for one Senate seat will receive fewer votes in the next election for the other seat. Using data on U.S. Senate elections from 1946 to 2004, we find strong evidence that the outcomes of the elections for the two Senate seats are independent.

Original language	English
Pages (from-to)	439-455
Number of pages	17
Journal	Political Analysis
Volume	14
Issue number	4
DOIs	https://doi.org/10.1093/pan/mpj010
State	Published - Sep 2006

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abstract = "We provide an introduction to the regression discontinuity design (RDD) and use the technique to evaluate models of sequential Senate elections predicting that the winning party for one Senate seat will receive fewer votes in the next election for the other seat. Using data on U.S. Senate elections from 1946 to 2004, we find strong evidence that the outcomes of the elections for the two Senate seats are independent.",

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AB - We provide an introduction to the regression discontinuity design (RDD) and use the technique to evaluate models of sequential Senate elections predicting that the winning party for one Senate seat will receive fewer votes in the next election for the other seat. Using data on U.S. Senate elections from 1946 to 2004, we find strong evidence that the outcomes of the elections for the two Senate seats are independent.

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JO - Political Analysis

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ER -

Splitting the difference? Causal Inference and theories of split-party delegations

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