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Abstract
The 2016 general election presented an unusual challenge to Republican congressional candidates: whether to market one’s campaign as aligned with or against Donald Trump’s controversial candidacy. In this paper, we determine what district and member-level factors influence candidate endorsements of Trump for president. Second, we study if the endorsements hurt candidates on Election Day. We find that underlying political partisanship, as measured by Mitt Romney’s 2012 vote share in congressional districts, predicts much of incumbents’ support for Trump, and that candidates’ support did not harm them in the general election.
Notes
1 Gattis, Paul. (2016). Martha Roby, Who Condemned Trump, Ekes out Reelection Win to Congress. Alabama Media Group.
2 Fahrenthold, David A. (2016). Trump Recorded Having Extremely Lewd Conversation About Women in 2005. The Washington Post.
3 Although there have been many scandal plagued candidates such as Bill Clinton in 1996, the 2016 election appears to be the first modern campaign where endorsing the top of the ticket might hurt congressional candidates en masse. Newspapers, however, are less likely to toe the line and will withhold endorsements depending on the candidate.
4 Lopez, German, Nelson, Libby, and Prokop, Andrew. (2016). Once You Know Trump’s History, What His Campaign has Done is Unsurprising. That Makes Him Scarier. Vox.
5 Trump won 230 congress districts compared to 205 for Hillary Clinton. Wolf, Stephen. (2017) “Daily Kos Elections presents the 2016 presidential election results by congressional district.”
6 Rosenthal, Howard. (2016). Why do White Men Love Donald Trump so much? The Washington Post.
7 We have an intercoder reliability of 80–94% agreement on all non-ordinal variables, from a sample of 20 Democrats and 20 Republicans. For our ordinal variable, support for Trump, the weighted Kappa for the interrater reliability is 89 percent. We do not analyze uncontested races, races in California and Washington that featured either two Democrats or two Republicans, and all races from Louisiana because of the state’s unique blanket primary system. We also exclude races in which there were no social media posts or media coverage of the Republican because it was impossible to determine their level of support for Trump. For races in which there was only one major party candidate, third party candidates were included if the candidate received at least 10 percent of the vote share because of the expectation that third party candidates may have fared better in 2016 than in prior elections.
8 In our original data collection, we identified a seven-level ordinal scale of support for Trump, ranging from zero (voiced opposition) to seven (campaigned with Trump). We found, however, that some categories were analytically indistinguishable from others when considering candidate positions. For example we categorized a two as “Never Hillary” and a three as “supporting the Republican nominee,” but many candidates did both interchangeably. Moreover, we found that some categories contained too few observations and were therefore not appropriate to include as categories in an ordered logit model.
9 McAdams, Ann. (2016) Rouzer: Unprecedented Level of Media Bias Against Trump. Fox 10.
10 Stratford, Michael. (2016). Politico Pro Q&A: Rep. Virginia Foxx. Politico Pro.
11 Mollot, Sabina. (2016). Maloney’s Opponent Calls National Debt, Gridlock Top Issues. Town & Village.
12 McKelvey, Wallace. (2016). ‘I Will be Supporting the Republican Ticket’: Pa. Congressmen Speak Out on Donald Trump. Penn Live.
13 Roger Marshall to “Reluctantly Continue to Support” Trump. (2016) KWCH12.
14 The category no voiced opposition does not include candidates from whom we could find no communication about Trump in the media. We consider these observations missing and drop them from the data set.
15 Eldeib, Duaa. (2016). Would-be Duckworth Successors Clash on Trump, Clinton. Chicago Tribune.
16 Unfortunately, we are unable to measure the ideology of challengers since they have not served in Congress and do not have NOMINATE scores. While Bonica (Citation2014) provides a measure of ideology based off of campaign contributions, it is not the same as a member’s voting behavior while in Congress. On this point, see Rogers (Citation2017).
17 We would like to thank Gary Jacobson for providing us with these data.
18 Determining the ideology of challengers prior to holding office can be complicated. On this point see Crespin, Gold, and Rohde (Citation2006).
19 A Sobel-Goodman test confirms that indeed, Romney vote share is a mediating influence on level of support for Trump.
20 (2016). Joe Heck and Cresent Hardy to “Celebrate” Election Night with Donald Trump’s Campaign. Nevada Democrats.
21 Scheider, Elena. (2016). Heck, Hardy Withdraw Trump Support in Nevada. Politico.
22 Boucher, Dave. (2016). Marsha Blackburn, Diane Black Still Back Donald Trump. The Tennessean.
23 Akin, Stephanie. (2016). Elise Stefanik’s Cautious Dance with Trump. Roll Call.
24 Derrick, Mike. (2016). Independent: Rep. Elise Stefanik puts Donald Trump ahead of the North Country. Youtube. https://www.youtube.com/watch?v=JYLxGGxYS14
25 Terris, Ben. (2016). Youngest Female Lawmaker says Social Media is Just Part of the Job. The Washington Post.
26 Henson, Ronald J. (2016). Paul Babeu, Martha McSally, Struggle to Respond to Donald Trump Fallout. The Arizona Republic.
Additional information
Notes on contributors
Jessica M. Hayden
Jessica Hayden is a Assistant Professor at Western Carolina University. She is the co-author of Congressional Communication in the Digital Age (Routledge, July 2017).
Sarina Rhinehart
Sarina Rhinehart is a graduate fellow at the Carl Albert Congressional Research and Studies Center at the University of Oklahoma.
Michael H. Crespin
Michael H. Crespin is a Professor of Political Science and Director of the Carl Albert Congressional Research and Studies Center at the University of Oklahoma. His research on the U.S. Congress has appeared in the American Journal of Political Science, the Journal of Politics, as well as Legislative Studies Quarterly.