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Political Behavior

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01.06.2009 | Original Paper

The Consequences of Battleground and “Spectator” State Residency for Political Participation

verfasst von: Keena Lipsitz

Erschienen in: Political Behavior | Ausgabe 2/2009

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Abstract

This study uses pooled NES and state-level turnout data from 1988 through 2004 to assess whether a participation gap is emerging in the United States between the residents of battleground and non-battleground states in presidential elections. The analysis finds that Electoral College (EC) participatory disparities are more likely to occur in voting and meeting attendance than in donating and political discussion. Moreover, it suggests that such disparities are more likely to occur when presidential elections are nationally competitive. The study also demonstrates that when participatory gaps do occur they are the result of a surge in participation among battleground state residents—not of citizen withdrawal in safe states, as many EC critics contend.

Vorheriger Artikel Shot by the Messenger: Partisan Cues and Public Opinion Regarding National Security and War

Nächster Artikel The Consequences of Concurrent Campaigns for Citizen Knowledge of Congressional Candidates

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To view other newspaper articles, editorials, and columns making similar claims, visit the National Popular Vote’s media archive at http://www.nationalpopularvote.com/.

Both Jennifer Wolak’s (2006) study and another conducted by Jim Gimpel and his colleagues (2007) assess how state competitiveness affects an index of participatory acts. While such a measure captures how much an individual participates more generally, it does not allow us to assess how state competitiveness affects individual forms of participation.

To be more precise, Costas Panagopoulos and Daniel Bergan (2006) found that state competitiveness had no effect on the amount of money raised by candidates in 2004, while Jim Gimpel and his colleagues found inconsistent effects with Republicans more likely to generate money in battleground states and Democrats less likely to do so (2006, 636). One should note that both of these studies examine the effect of state competitiveness on total contributions, whereas I am interested in the effect of it on the percentage of the population donating. The extant literature does not speak directly to this question.

The NES does ask respondents if they tried to persuade someone to vote for a particular candidate during the campaign. Advocacy, however, is just one form of political discussion. Since I am interested in the question of whether battleground state residency encourages people to talk about politics for any reason, I use the current measure.

These claims are admittedly suggestive given the fact that I am examining only five elections.

The author acknowledges that the use of self-reported data is not ideal. This is one reason why I use state-level turnout data, rather than the self-reported voting data provided by the NES. In terms of the meeting attendance, donating, and discussion measures, I am assuming that any error in these measures is randomly distributed across the various types of states (battleground, safe, etc.) examined. Since I am interested in a comparison across this range of campaign contexts, any error associated with these measures should not bias my results.

The one exception is the categorization of states from the perspective of the Dole campaign in 1996. For a discussion of how Daron Shaw developed these measures, see Shaw 1999b for the 1988–1996 presidential election years and chapter 3 of Shaw 2006 for an explanation of his 2000 and 2004 coding.

It is possible that there will be a direct effect as well: residents of the state may recognize how close the election is, which in turn, may encourage them to get involved.

The NES donating question does not refer specifically to presidential campaigns, which means a person who responds “yes” to it may have made a political contribution to any number of political races. A recent study found, however, that the presence and competitiveness of local campaigns “does not generally improve Republican or Democratic fundraising” (Gimpel et al. 2006, p. 636). Moreover, the analysis controls for the presence of a Senate race in the state. Finally, the fact that the donating question does not refer specifically to presidential campaigns stacks the analysis against finding a presidential state competitiveness effect, yet the analysis reveals one.

For clarity of presentation, I have provided the trend lines for just two categories—the most competitive and the least competitive—of state competitiveness. See Figure 1 in the Supplementary Materials for graphs with all five categories depicted.

All of the differences I have discussed were statistically significant at p < .05 or better.

This is especially true of the EC participation gaps in meeting attendance and voting. Even though such a gap emerged in political discussion in 2004, levels of political discussion plummeted across the country from their 2000 levels.

See Table 6 in the Supplementary Materials for the results of the HLM analyses.

The strength of partisanship and partisan identification have been interacted by creating a dummy variable for each of the possible categories resulting from such an interaction. This avoids the problems of interpretation associated with the fact that scoring a “0” on the strength of partisanship measure determines whether one is an Independent. The omitted category in the analysis is pure Independent. I combined Independents leaning towards the Democrats with weak Democrats and Independents leaning towards the Republicans with weak Republicans because these categories of individuals behaved in a similar manner.

To test Wolak’s (2006) contention that the partisan composition of a state may drive political participation rather than its battleground state status, I ran all of my pooled models using the same aggregated CBS News/New York Times national polls data collected by Gerald Wright, John McIver, and Robert Erikson (http://php.indiana.edu/~wright1/cbs7603_pct.zip) and found it did not diminish the battleground state effect on any of the forms of participation examined here. However, the percentage of independents in the state did have a significant independent effect on intention to vote.

1988 (as well as the interaction term) is omitted in the first two models and 1992 in the third because the question about political discussion was not asked in 1988.

By “typical” I mean an employed, white, male respondent who is a strong Democrat, registered to vote, does not live in the south, and has a Senate race going on in his state. The year is set for the year in question and the interaction terms are also set to reflect the year in question as well as the level of state competitiveness that I am depicting in the charts (i.e. “Safe” and “Battleground”). All other variables in the analysis, such as age and education, are set to their mean.

The NES question about political discussion is typically asked on the post-election survey. Thus, the elevated levels of discussion in 2000 were likely due to the events surrounding the Florida recount.

I also examined whether believing the race is close in your state—another form of internal motivation—accounted for any of the EC participatory differences, but it did not. In the model explaining reported voting, believing the presidential race in one’s own state is close does increase the likelihood that individuals will vote, but—strangely—residing in a competitive state is a weak predictor of whether a person believes the race in his or her state is close. The correlation between the two is a miniscule .02.

All of these models can be found in Tables 2–5 of the Supplementary Materials.

See Table 1 in the Supplementary Materials for the full model showing the effect of state competitiveness on reported voting and Figure 2 for the predicted probability graph.

It is also possible that the causal arrow points in the opposite direction, i.e. the people who attended meetings in battleground states learned from their experience. Political knowledge, however, is recognized as being one of the most significant predictors of political participation, so it is more likely that the first interpretation holds.

Each of the models includes a single mechanism, so political knowledge is not accounted for in this model.

The portion of the participatory difference that is explained when all of the mechanisms are included is smaller than the sum of all the percentages explained in the previous models because the explanatory variables are correlated.

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Titel: The Consequences of Battleground and “Spectator” State Residency for Political Participation
verfasst von: Keena Lipsitz
Publikationsdatum: 01.06.2009
Verlag: Springer US
Erschienen in: Political Behavior / Ausgabe 2/2009
Print ISSN: 0190-9320
Elektronische ISSN: 1573-6687
DOI: https://doi.org/10.1007/s11109-008-9068-7

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