Hostname: page-component-7c8c6479df-995ml Total loading time: 0 Render date: 2024-03-27T08:51:35.721Z Has data issue: false hasContentIssue false

Did Illegal Overseas Absentee Ballots Decide the 2000 U.S. Presidential Election?

Published online by Cambridge University Press:  01 September 2004

Kosuke Imai
Affiliation:
Kosuke Imai is assistant professor in the department of politics, Princeton University (kimai@Princeton.edu)
Gary King
Affiliation:
Gary King is the David Florence Professor of Government, Harvard University (king@harvard.edu)

Abstract

Although not widely known until much later, Al Gore received 202 more votes than George W. Bush on election day in Florida. George W. Bush is president because he overcame his election day deficit with overseas absentee ballots that arrived and were counted after election day. In the final official tally, Bush received 537 more votes than Gore. These numbers are taken from the official results released by the Florida Secretary of State's office and so do not reflect overvotes, undervotes, unsuccessful litigation, butterfly ballot problems, recounts that might have been allowed but were not, or any other hypothetical divergence between voter preferences and counted votes. After the election, the New York Times conducted a six-month investigation and found that 680 of the overseas absentee ballots were illegally counted, and almost no one has publicly disagreed with their assessment. In this article, we describe the statistical procedures we developed and implemented for the Times to ascertain whether disqualifying these 680 ballots would have changed the outcome of the election. These include adding formal Bayesian model averaging procedures to models of ecological inference. We present a variety of new empirical results that delineate the precise conditions under which Al Gore would have been elected president and offer new evidence of the striking effectiveness of the Republican effort to prevent local election officials from applying election law equally to all Florida citizens.The authors are deeply grateful to the many private citizens of every political stripe who sent us comments on this paper; also to Jim Alt, Barry Burden, James Honeker, Doug Rivers, and Jonathan Wand for helpful discussions; to Henry Brady for many suggestions; and to the National Science Foundation, the National Institutes of Aging, and the World Health Organization for research support. Software to implement the methods in this article is available at http://gking.harvard.edu.

Type
SYMPOSIUM
Copyright
© 2004 American Political Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Adolph, Christopher, and Gary King. 2003. Analyzing second-stage ecological regressions: Comment on Herron and Shotts. Political Analysis 11 (1): 6576.Google Scholar
Adolph, Christopher, and Gary King, with Michael C. Herron, and Kenneth W. Shotts. 2003. A consensus on second-stage analyses in ecological inference models. Political Analysis 11 (1): 8694.Google Scholar
Anselin, Luc, and Wendy K. Tam Cho. 2002a. Spatial effects and ecological inference. Political Analysis 10 (3): 27697.Google Scholar
Anselin, Luc, and Wendy K. Tam Cho 2002b. Conceptualizing space: Reply. Political Analysis 10 (3): 3013.Google Scholar
Barbanel, Josh. 2001. How the ballots were examined. New York Times, July 15. http://www.nytimes.com/.
Barstow, David, and Don Van Natta Jr. 2001. How Bush took Florida: Mining the overseas absentee vote. New York Times, July 15. http://www.nytimes.com/.
Bartels, Larry M. 1997. Specification uncertainty and model averaging. American Journal of Political Science 41 (2): 64174.Google Scholar
Bartels, Larry M., and John Zaller. 2001. Presidential vote models: A recount. PS: Political Science and Politics 33 (1): 920.Google Scholar
Berke, Richard L. 2001. Lieberman put Democrats in retreat on military vote.” New York Times, July 15. http://www.nytimes.com/.
Bishop, Christopher M. 1995. Neural Networks for Pattern Recognition. Oxford: Oxford University Press.
Chib, Siddhartha. 1995. Marginal likelihood from the Gibbs output. Journal of the American Statistical Association 90 (432): 131321.Google Scholar
Cho, Wendy K. Tam. 1998. Iff the assumption fits …: A comment on the King ecological inference solution. Political Analysis 7: 14363.Google Scholar
Cho, Wendy K. Tam, and Brian J. Gaines. 2004. The limits of ecological inference: The case of split-ticket voting. American Journal of Political Science 48 (1): 15271.Google Scholar
DiCiccio, Thomas J., Robert E. Kass, Adrian E. Raftery, and Larry Wasserman. 1997. Computing Bayes factors by combining simulation and asymptotic approximations. Journal of the American Statistical Association 92 (439): 90315.Google Scholar
Duncan, Otis Dudley, and Beverly Davis. 1953. An alternative to ecological correlation. American Sociological Review 18 (6): 66566.Google Scholar
Erikson, Robert S., Joseph Bafumi, and Bret Wilson. 2001. Was the 2000 presidential election predictable? PS: Political Science and Politics 34 (4): 81519.Google Scholar
Fessenden, Ford, and John M. Broder. 2001. Study of disputed Florida ballots finds justices not cast the deciding vote. New York Times, November 12.
Freedman, David A., Stephen P. Klein, Michael Ostland, and Michael R. Roberts. 1998. Review of A solution to the ecological inference problem. Journal of the American Statistical Association 93 (December): 151822.Google Scholar
Goodman, Leo. 1953. Ecological regressions and the behavior of individuals. American Sociological Review 18 (6): 66364.Google Scholar
Goodman, Leo 1959. Some alternatives to ecological correlation. American Journal of Sociology 64 (6): 61024.Google Scholar
Herron, Michael C., and Kenneth W. Shotts. 2003a. Using ecological inference point estimates as dependent variables in second-stage linear regressions. Political Analysis 11 (1): 4464.Google Scholar
Herron, Michael C., and Kenneth W. Shotts 2003b. Cross-contamination in EI-R: Reply. Political Analysis 11 (1): 7785.Google Scholar
Hoeting, Jennifer A., David Madigan, Adrian E. Raftery, and Chris T. Volinsky. 1999. Bayesian model averaging: A tutorial. Statistical Science 14 (4): 382417.Google Scholar
Imai, Kosuke, and Ying Lu. 2004. Parametric and nonparametric Bayesian modeling for ecological inference in 2 × 2 tables. Technical report, Department of Politics, Princeton University.
Kass, Robert E., and Adrian E. Raftery. 1995. Bayes factors. Journal of the American Statistical Association 90 (430): 77395.Google Scholar
Kass, Robert E., Luke Tierney, and Joseph B. Kadane. 1989. Approximate methods for assessing influence and sensitivity in Bayesian analysis. Biometrika 76 (4): 66374.Google Scholar
King, Gary. 1997. A solution to the ecological inference problem: Reconstructing individual behavior from aggregate data. Princeton: Princeton University Press.
King, Gary 1999. The future of ecological inference research: A reply to Freedman et al. Journal of the American Statistical Association 94 (March): 35255.Google Scholar
King, Gary 2002. Isolating spatial autocorrelation, aggregation bias, and distributional violations in ecological inference. Political Analysis 10 (3): 298300.Google Scholar
King, Gary, Ori Rosen, and Martin A. Tanner, eds. 2004. Ecological inference: New methodological strategies. New York: Cambridge University Press.
King, Gary, and Langche Zeng. 2001. When can history be our guide? The pitfalls of counterfactual inference. http://gking.harvard.edu.
Lebow, Richard Ned. 2000. What's so different about a counterfactual? World Politics 52 (4): 55085.Google Scholar
Lewis, Steven M., and Adrian E. Raftery. 1997. Estimating Bayes factors via posterior simulation with the Laplace-Metropolis estimator. Journal of the American Statistical Association 92 (438): 64855.Google Scholar
Madigan, David, and Adrian E. Raftery. 1994. Model selection and accounting for model uncertainty in graphical models using Occam's window. Journal of the American Statistical Association 89 (428): 153546.Google Scholar
Purdum, Todd S. 2000. Counting the vote: The overview. New York Times, November 27. http:// www.nytimes.com/.
Raftery, Adrian E. 1996. Hypothesis testing and model selection. In Markov chain Monte Carlo in practice: Interdisciplinary statistics, ed. W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, 16387. London: Chapman and Hall.
Raftery, Adrian E., and Yingye Zheng. 2003. Discussion: Performance of Bayesian model averaging. Journal of the American Statistical Association 98 (464): 93138.Google Scholar
Robert, C. P. 1996. Mixtures of distributions: inference and estimation. In Markov chain Monte Carlo in practice: Interdisciplinary statistics, ed. W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, 44164. London: Chapman and Hall.
Rosen, Ori; Wenxin Jiang, Gary King, and Martin A. Tanner. 2001. Bayesian and frequentist inference for ecological inference: The R × C case. Statistica Neerlandica 55 (2): 13456.Google Scholar
Rosen, Ori, Wenxin Jiang, and Martin A. Tanner. 2000. Mixtures of marginal models. Biometrika 87 (2): 391404.Google Scholar
Zelnick, Bob. 2001. The myth of a stolen election (letter to the editor). Wall Street Journal, July 17.