Missing Voters, Missing Data: Using Multiple Imputation to Estimate the Effects of Low Turnout Patrick Bernhagen University of Aberdeen Department of Politics and International Relations Edward Wright Building, Dunbar Street Aberdeen, AB24 3QY United Kingdom Tel: +44 1224 27 2720 Fax: +44 1224 27 2552 Email: P.Bernhagen@abdn.ac.uk Michael Marsh Trinity College Dublin Department of Political Science Dublin 2 Ireland Phone: +353 1 608 1070 Fax: +353 1 677 0546 Email: mmarsh@tcd.ie This version: 24 th November 2009 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 maximum likelihood methods. While the methods differ in their ability to simulate vote choice correctly, these differences are normally 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.