The Enduring Effects of Competitive Elections

Abstract

Research on U.S. congressional elections has placed great emphasis on the role of competitiveness, which is associated with high levels of campaign spending, media coverage, and interest group and party involvement. Competitive campaigns have been found to increase citizens' participation, engagement and learning. However, little is known about whether the effects of competitive campaigns have enduring consequences for citizens' attitudes and behavior. Analyzing a survey of citizens conducted one year after the 2006 congressional elections that includes an oversample of respondents from competitive House races, we examine whether exposure to a competitive House campaign affects voters' political knowledge and political interest as well as their consumption of political news. We find that competitive elections have positive effects that endure for at least a year beyond the campaign season, reinforcing the idea that political competition plays a robust role in American representative democracy.

Notes

1. There are a few studies that have found citizens in toss-up races actually know less about politics, but these studies only use campaign spending for measures of competitiveness. For examples, see Coleman and Manna (2000) and Lipsitz (2011).

2. CCES was completed online and fielded by the survey research firm Polimetrix, Inc., located in Palo Alto, CA. Steven Ansolabehere (MIT) was the Principal Investigator of the project and Sam Luks (YouGov/Polimetrix) served as the Project Director. Steven Ansolabehere mapped out the broad themes for the first 40 questions of the survey, called the Common Content. All 10,000 respondents completed this part of the survey. Each CCES team then drafted its own unique content that followed the Common Content. Each team received 1,000 unique respondents who completed both the Common Content and the Team Module. We designed the questionnaire for the Indiana University subsample (Carmines, 2007). Data may be obtained for purposes of replication by contacting the authors.

3. For more information regarding the weighting of the data, please see <http://projects.iq.harvard.edu/cces/book/study-design>.

4. Cronbach's alpha is 0.86 for the summated rating scale.

5. Given the large number of variables related to the competitiveness of elections there may be concern about the robustness of the results. We have estimated the models in the article but without using the lagged competiveness, open seat, and normal vote variables. The estimates obtained from these analyses are essentially the same and are presented in online Supplemental Appendix D (http://dx.doi.org/10.1080/17457289.2013.874351).

6. In the regression models reported herein, we used dichotomous variables to indicate whether the respondent identified with the Republican Party, the Democratic Party, or neither. We also replicated all of the models using a four-point scale capturing the strength of partisan identification (i.e., the traditional seven-point partisan identification variable folded at the midpoint). The results remain unchanged under this alternative specification.