Missing voters, missing data: using multiple imputation to estimate the effects of low turnout

Patrick Bernhagen, Michael Marsh

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In recent years, different methods have been proposed to estimate the political effects of low voter turnout. This article contributes to the discussion by assessing the performance of multiple imputation in estimating the partisan effects of low turnout. Using the 2002 Irish General Election as a case study, we demonstrate how multiple imputation can be used to fill in the vote choices of non-voters. We verify simulations and reported turnout against official data and compare the results to those from alternative, maximum likelihood methods. While the methods differ in their ability to simulate vote choice correctly, these differences are generally not large enough to affect the counterfactual estimation of election results under universal turnout. To asses the generality of this finding, we also compare the different methods across 30 elections in the Comparative Study of Electoral Systems dataset. Multiple imputation produces on average higher turnout effects than multinomial logit methods and the differences increase as turnout goes down. System variables such as the number of parties do not affect the differences in results between methods.
Original languageEnglish
Pages (from-to)447-472
Number of pages36
JournalJournal of Elections, Public Opinion and Parties
Volume20
Issue number4
DOIs
Publication statusPublished - 2010

Fingerprint Dive into the research topics of 'Missing voters, missing data: using multiple imputation to estimate the effects of low turnout'. Together they form a unique fingerprint.

  • Cite this