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Do Campaigns Drive Partisan Turnout?

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Abstract

Although campaign strategy often, and perhaps increasingly, emphasizes the mobilization of core supporters, we know little about whether campaigns affect the partisan complexion of the electorate. We examine whether the balance of Democratic and Republican voters depends on the balance of campaign activity, the popularity of the incumbent president, and the state of the economy. Drawing on time-series cross-sectional data from state exit polls, we demonstrate that the partisan composition of voters depends on campaign activity more than on the political and economic fundamentals.

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Notes

  1. Of course, many people maintain loyalty to a group even when it is chronically unsuccessful. This is why even Wrigley Field can sell out. Diehard fans, like habitual voters, are likely to participate even when their team’s prospects are dim.

  2. We omitted New York, which, despite its large sample size (N = 1088), was clearly an outlier in terms of its partisan turnout. In particular, its partisan turnout in 2002 was skewed well toward the Republican Party. This likely stems from the exit poll’s sampling within New York. Although precise information about which precincts were included is not available in the publicly released data, no exit poll respondents are designated as living in cities with more than 500,000 people, suggesting that no precincts from New York City were included in the sample. This could help account for the skew in the sample’s partisan composition.

  3. The exit polls do not allow independents to designate a preferred party and thus do not capture independent “leaners.” We explored the impact of incorporating leaners into our measure of partisan turnout using two datasets: validated turnout in the American National Election Study (ANES) (available for 1964, 1976, 1978, 1980, 1984, 1986, 1988, and 1990), and validated turnout in the 2006 Cooperative Congressional Election Study (CCES). The correlation between our measure and the same measure with leaners was r = 0.98 across years in the ANES and r = 0.94 across states in the CCES (using only states with at least 200 cases to reduce sampling noise).

  4. House spending data from 1988 through 1998 were graciously provided by Gary Jacobson of the University of California at San Diego. The remaining House spending data and all the Senate spending data come from the Federal Election Commission. Gubernatorial spending data from 1988 through 2004 come from the Gubernatorial Campaign Expenditures database (Beyle and Jensen 2007); the data for 2006 come from the websites of the various states.

  5. Ray La Raja of the University of Massachusetts, Amherst graciously provided these data. They are calculated as dollars per 1,000 eligible voting persons. Since we do not have data for 1988, the campaign balance measure for that year does not include this measure.

  6. For example, to compute the balance of campaign spending for Democrats (D) and Republicans (R), we calculated: (D − R)/(D + R). This has the advantage of generating comparable measures even though the underlying indicators (spending, ads, visits, etc.) are on different metrics.

  7. Although this measure combines different types of campaign activities by different campaigns, some sort of combination is necessary in order to consider both presidential and midterm elections in the same analysis. Of course, partisan turnout might respond to specific types of campaign activities or activities by certain campaigns, rather than the sum of campaign activity in general. Thus, if anything, this measure imprecisely measures our construct of interest and understates the effect of campaigns.

  8. Our models also include a dummy variable for the party of the president, coded −1 (Republican) and +1 (Democrat), which accounts for the coding of the economy and presidential approval variables.

  9. Models with panel-corrected standard errors and a first-order auto-regressive component generate results very similar to those presented here (Beck and Katz 1995; Wilson and Butler 2007). These results are available on request.

  10. These data, calculated for 1988–2003, are available at http://php.indiana.edu/~wright1/.

  11. In alternative models, we replaced presidential approval with approval of the governor or either of the senators. None of these measures of approval had significant effects. At a reviewer’s suggestion, we also investigated whether there were interactions between campaign activity and either presidential approval or the state of the economy. We uncovered no statistically significant interactions.

  12. More specifically, for each party, we standardized each of the measures that comprise this index (spending on various races, presidential ads and visits, and party expenditures) and then combined those into an index.

  13. These results, and all others reported in this section, are also available from the authors. We do not present them here only for reasons of space.

  14. The effects of campaign activity are also statistically significant when we measured partisan turnout as the deviation between the exit poll percentages and the underlying macro-partisanship of the state.

  15. This analysis is somewhat in the spirit of Levitt (1994), who also sought to mitigate endogeneity by focusing on a small subset of races with fortuitous but relatively rare characteristics (in his analysis, races which featured the same opposing candidates more than once).

  16. Recall that both measures were scaled such that negative values indicated conditions more favorable to the Republican Party and positive values indicated conditions more favorable to the Democratic Party. Thus, as the absolute value of these measures increases, one of the two parties is advantaged, which should lead to a decline in the number of Independents if some of them are switching parties.

  17. A possible rejoinder is that voters could be more attentive and sensitive to campaign stimuli, rendering them more likely than the population as a whole to shift their party identification. We think this is unlikely. Habitual voters are, on average, more attentive to politics, but they are also more opinionated. Indeed, further analysis from the 2000–2004 ANES panel suggests that respondents who reported voting in both 2000 and 2004 were even less likely than the entire sample to shift their party identification.

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Correspondence to Eric McGhee.

Appendix

Appendix

See Table 4.

Table 4 Distribution of states in exit poll data

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McGhee, E., Sides, J. Do Campaigns Drive Partisan Turnout?. Polit Behav 33, 313–333 (2011). https://doi.org/10.1007/s11109-010-9127-8

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