Research Article

Estimating the Electoral Effects of Voter Turnout

THOMAS G. HANSFORD^a1 c1 and BRAD T. GOMEZ^a2 c2

^a1 University of California, Merced

^a2 Florida State University

Abstract

This article examines the electoral consequences of variation in voter turnout in the United States. Existing scholarship focuses on the claim that high turnout benefits Democrats, but evidence supporting this conjecture is variable and controversial. Previous work, however, does not account for endogeneity between turnout and electoral choice, and thus, causal claims are questionable. Using election day rainfall as an instrumental variable for voter turnout, we are able to estimate the effect of variation in turnout due to across-the-board changes in the utility of voting. We re-examine the Partisan Effects and Two-Effects Hypotheses, provide an empirical test of an Anti-Incumbent Hypothesis, and propose a Volatility Hypothesis, which posits that high turnout produces less predictable electoral outcomes. Using county-level data from the 1948–2000 presidential elections, we find support for each hypothesis. Failing to address the endogeneity problem would lead researchers to incorrectly reject all but the Anti-Incumbent Hypothesis. The effect of variation in turnout on electoral outcomes appears quite meaningful. Although election-specific factors other than turnout have the greatest influence on who wins an election, variation in turnout significantly affects vote shares at the county, national, and Electoral College levels.

Correspondence:

^c1 Thomas G. Hansford is Associate Professor of Political Science, University of California–Merced, 5200 North Lake Road, Merced, CA 95343 (thansford@ucmerced.edu).

^c2 Brad T. Gomez is Assistant Professor of Political Science, Florida State University, 536 Bellamy Building, Tallahassee, FL 32306 (bgomez@fsu.edu).

Footnotes

An earlier version of this article was presented at the Annual Meeting of the American Political Science Association, Boston, MA, August 28–31, 2008. We wish to thank Robert Jackson, Carl Klarner, Michael Martinez, Steve Nicholson, Alex Whalley, and the reviewers and co-editors of the APSR for their constructive comments during the writing of this article. We also wish to thank Scott Edwards of EarthInfo, Inc., for his assistance with extracting the historical weather data, as well as Dave Cowen, Courtney Russell, and, especially, Lynn Shirley from the Department of Geography at the University of South Carolina for their work and expertise in producing GIS interpolations of the weather data. Last, we thank the College of Arts and Science at the University of South Carolina, where this work commenced, for its generous financial support for this project. All errors should be attributed to the authors alone.