Abstract
Brams and Kilgour (Public Choice 170:99–113, 2017) begin their recent essay on the Electoral College (EC) by pointing out the obvious, but nonetheless regularly neglected fact that noncompetitive states may have a decisive impact on EC outcomes and shape the electoral strategies of the candidates in the competitive states, especially if there is asymmetry in the partisan balances in the non-competitive states. Their contribution is to offer combinatorics insights into the implications of such asymmetries in the form of three new indicators: Winningness, Vulnerability, and Fragility. They then explore the magnitude and effects of these three measures for the presidential elections of 2000, 2004, 2008 and 2012. The major contribution of this note is to extend their analyses of these measures to an additional 34 elections: every election in the modern two-party post-Civil War era from 1868 to 2016. We find the Winningness measure to predict very well over the entire set of 38 presidential elections. Inspired by their work, we also offer a new and simpler metric for partisan asymmetries in noncompetitive states and show how it can predict the expected closeness of EC outcomes as well or better than the more complex combinatorics measures they propose.
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Notes
Colored maps (chloropleths) are now an indispensable aspect of election coverage, visually emphasizing how geography matters. CNN and other broadcasters are able, with the push of a button, to display historical comparisons of voting patterns at various levels of electoral geography.
On CNN, on election night in 2016, Wolf Blitzer quipped to Jake Tapper that “Jake, [this is] another presidential race where all eyes right now are on Florida”, to which Tapper responded “It's one of the critical states in this race. Donald Trump himself has said he doesn't see a path to the presidency for himself without the state of Florida, the 29 electoral votes.” Tapper went on to say, “the Clinton campaign knows they need Florida. They have been saying for some time they feel better about Florida than they do about states such as North Carolina,… Ohio, or Iowa”.
We will refer to Brams and Kilgour’s Public Choice paper by their names and with the B–K acronym interchangeably throughout this essay.
For example, in 2012, Brams and Kilgour point out (p. 101): “Because Barack Obama had a 233–191 electoral vote lead over Mitt Romney in the 42 noncompetitive states and the District of Columbia, he needed only 37 of the 114 electoral votes in the competitive states to win with a majority of 270 electoral votes, whereas Romney needed 79”.
In 1984, Ronald Reagan won 49 out of 51 states (including Washington, DC). Norman Ornstein, writing before the election, said “Incumbent presidents don’t often lose, particularly presidents presiding over 6% real growth and low or non-existent inflation” (quoted in CQ Press, http://library.cqpress.com/cqresearcher/document.php?id=cqresrre1984091400).
In races with third parties, a margin of victory no greater than 6%. For the purposes of this note, we concern ourselves only with the two highest vote earners and calculate accordingly.
In Table 1, Vulnerability and Fragility are defined in all elections that are competitive (17/38), and because the sample is split for Republicans and Democrats, for years in which that party’s candidate had a Winningness of 1 (Vulnerability and Fragility are always zero in these cases).
While these two elections were very close in two-party vote margin, and thus might be regarded as hard to predict, they were less so electorally. In 1960, John F. Kennedy won the EC vote by 9.1% and, in 1880, James Garfield won by 7.5%. In neither election were third-party candidacies consequential in affecting relative two-party shares.
Because of the frequent occurrence of values of 0 or 1, a perfect linear fit is impossible.
In 1992, Bill Clinton was just seven EC votes shy of having enough a majority in noncompetitive states, and could have lost the election in only five of the more than 130,000 different combinations of electoral outcomes among the competitive states, i.e., Winningness >0.99.
Another reason for choosing the ±3% value is a pragmatic one that we found only after we had done robustness checks; over both recent elections and the longer historical data: ±3% value has (marginally) greater predictive power than the often used ±5% definition of competitive state (see on-line Appendix).
Bartels (1985) has pointed out that campaigns have what he calls both “instrumental” and “ornamental” reasons for staging campaign events. Attending an event in a swing state, where a candidate’s presence could increase turnout is instrumental, while visiting a state to satisfy state parties might be ornamental. Hillary Clinton spent over $600,000 in Arizona, perhaps trying to influence lower ticket races by increasing mobilization efforts. Ultimately, Arizona, a state that has had a strong Republican tradition, became competitive in 2016.
Stromberg (2008) suggests a hockey metaphor; as a game winds down, a trailing team looking to increase the probability of tying the game pulls their goalie to provide more offensive potential, taking the risk of giving up another goal. A leading team would instead probably act to protect its lead, replacing offensive players with defensively skilled players.
This conclusion differs from that of early political science literature on campaign strategies which claimed that the most populous states would receive the bulk of campaign activities. For example, Brams and Davis (1974) offered a model that predicted campaign allocations proportional to the electoral votes of each state raised to the power of 3/2. For an early critique of the view that campaigning would necessarily focus on the most populous states, see Colantoni et al. (1975). See also Wright (2009) and Miller (2012).
Data aggregated from FairVote.org, with original data from CNN: http://www.fairvote.org/presidential_tracker_2012#2012_campaign_events
Older elections also largely conform to these expectations. Detailed campaign activities for the 1976 election are available because they were submitted into evidence for the hearing before the Subcommittee on the Constitution of the Committee on the Judiciary (S.J. Res. 28, 1979) on a bill that would abolish the Electoral College and establish a direct popular vote. The data were first used by Bartels (1985). That election shows a similar pattern of campaign activities focused on the competitive states, though there were many more (25) competitive states in 1976 than in the two most recent elections of 2012 and 2016. In 1976, 78% of all campaign events were held in the 25 battleground states, and 78% of all campaign television and radio ads were broadcast there.
Data compiled from AdAge.com, based on state-specific ad buys between October 21, 2016, and Election Day. http://adage.com/article/campaign-trail/states-where-trump-clinton-spending-most-on-advertising/306377/.
In 1964, the Goldwater campaign treated 23 states as battlegrounds (Shaw and Althaus 2017). The Goldwater campaign focused on the South, seeking to mirror the Dixiecrat revolt and pry southern states from the hands of the Democratic party which, except for the Dixiecrat revolt of 1948, had been winning them by large margins. Goldwater’s campaign went poorly except in the deep South, winning only a handful of states. All but one of the states he won were states his campaign treated as battlegrounds. The one exception was a very narrow win.
We regard both of these assumptions as quite reasonable ones to make for purposes of model tractability, but we might expect them to be falsified if electoral tides sweep in a particular direction and thus create interdependencies in vote outcomes in the competitive states.
Minor party candidacies are likely to be a problem for our analyses only in situations when they receive Electoral College votes. This has not been the case in recent elections, as no minor party candidate has won a state since George Wallace in 1968. In their assessment of minor party impact, Pattie and Johnson (2014) do not find substantial effects, and they also note that such effects have often differed in their partisan impacts. To provide a consistent coding across all elections in our dataset we ignore minor party votes and treat contests as between the two major party candidates in terms of two-party vote share.
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Acknowledgements
The authors would like to thank Daron Shaw and Scott Althaus for their data and helpful comments. They would also like to express gratitude to the journal editors William F. Shughart II and Keith Dougherty, along with the two anonymous reviewers for their constructive comments. Work on this project was supported by the Jack W. Peltason Center of the Study of Democracy at the University of California, Irvine. The first named author is a Ph.D. candidate in Political Science at the University of California, Irvine. The second named author is a Professor of Political Science at UCI and the Jack W. Peltason Chair of Democracy Studies. Replication material can be found at https://github.com/jcervas/Non-Competitive-Advantage.
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Cervas, J.R., Grofman, B. Why noncompetitive states are so important for understanding the outcomes of competitive elections: the Electoral College 1868–2016. Public Choice 173, 251–265 (2017). https://doi.org/10.1007/s11127-017-0474-4
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DOI: https://doi.org/10.1007/s11127-017-0474-4