Mountain View
biomedical and healthCAre Data Discovery Index Ecosystem
help Advanced Search
Title: Replication data for: On The Validity Of The Regression Discontinuity Design For Estimating Electoral Effects: New Evidence From Over 40,000 Close Races      
dateReleased:
03-20-2015
downloadURL: http://dx.doi.org/10.7910/DVN/24937
ID:
doi:10.7910/DVN/24937
description:
The regression discontinuity (RD) design is a valuable tool for identifying electoral effects, but this design is only effective when relevant actors do not have precise control over election results. Several recent papers contend that such precise control is possible in large elections, pointing out that the incumbent party is more likely to win very close elections in the U.S. House of Representatives in recent periods. In this paper, we examine whether similar patterns occur in other electoral settings, including the U.S. House in other time periods, statewide, state legislative, and mayoral races in the U.S., and national or local elections in a variety of other countries. No other case exhibits this pattern. We also cast doubt on suggested explanations for incumbent success in close House races. We conclude that the assumptions behind the RD design are likely to be met in a wide variety of electoral settings and offer a set of best practices for RD researchers going forward.
description:
Eggers, Andrew C.; Fowler, Anthony; Hainmueller, Jens; Hall, Andrew B.; Snyder, James M. Jr., 2014, "Replication data for: On The Validity Of The Regression Discontinuity Design For Estimating Electoral Effects: New Evidence From Over 40,000 Close Races", http://dx.doi.org/10.7910/DVN/24937, Harvard Dataverse, V2
name:
Eggers, Andrew C.
Fowler, Anthony
Hainmueller, Jens
Hall, Andrew B.
Snyder, James M. Jr.
homePage: http://www.harvard.edu/
name:
Harvard University
ID:
SCR:011273
abbreviation:
DataVerse
homePage: http://thedata.org/
name:
Dataverse Network Project
ID:
SCR:001997