2018
DOI: 10.1177/1065912917749323
|View full text |Cite
|
Sign up to set email alerts
|

Detecting and Understanding Donor Strategies in Midterm Elections

Abstract: What explains how political donors decide where to give? Existing research indicates that people donate money to express support for a preferred political “team” and enjoy the emotional benefits of participating in politics. While this explains why people donate, it does little to help understand the different strategies that donors may pursue. In this paper, we use data on individual decisions as to where to allocate contributions to provide fresh insight into the strategies donors are pursuing. Our approach … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
16
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 19 publications
(17 citation statements)
references
References 32 publications
1
16
0
Order By: Relevance
“…Like formal party committees, party insiders , individuals who contribute to legislators and to state party committees, may have partisan incentives. However, evidence from Rhodes, Schaffner, and La Raja () suggests that party insiders (closely related to what the authors call “party‐oriented donors”) may contribute in less strategic patterns than other donors. Not only are individuals who mostly give to party committees less likely to be wealthy and politically engaged; they also “either demonstrate no clear strategy in their giving behavior or choose to simply focus on giving to what is arguably the most ‘obvious’ target of donations—their preferred political party” (Rhodes, Schaffner, and La Raja , 513).…”
Section: Individuals and Organizations In Campaign Financementioning
confidence: 99%
“…Like formal party committees, party insiders , individuals who contribute to legislators and to state party committees, may have partisan incentives. However, evidence from Rhodes, Schaffner, and La Raja () suggests that party insiders (closely related to what the authors call “party‐oriented donors”) may contribute in less strategic patterns than other donors. Not only are individuals who mostly give to party committees less likely to be wealthy and politically engaged; they also “either demonstrate no clear strategy in their giving behavior or choose to simply focus on giving to what is arguably the most ‘obvious’ target of donations—their preferred political party” (Rhodes, Schaffner, and La Raja , 513).…”
Section: Individuals and Organizations In Campaign Financementioning
confidence: 99%
“…The centrist tone adopted during presidential elections creates more demand for centrist causes and campaigns. By contrast, during midterm cycles, the small jurisdictions at stake represent geographically small communities of people who are more likely to share homogenous traits, life experiences, and political attitudes (Rhodes et al 2018 ). This means that in especially partisan districts, contributions will flow to correspondingly partisan candidates and causes.…”
Section: Discussionmentioning
confidence: 99%
“…Social science researchers have used LCA to analyze a wide variety of topics, including tolerance (McCutcheon, 1985; Sniderman et al, 1989), party support (Breen, 2000), opinion-changing behavior (Hill & Kriesi, 2001), citizenship norms (Hooghe et al, 2016; Hooghe & Oser, 2015; Oser & Hooghe, 2013; Sampermans et al, 2020); revolutionary groups (Beissinger, 2013), technocratic attitudes (Bertsou & Caramani, 2020), nationalist sentiment (Bonikowski & DiMaggio, 2016), democratic ideals (Hooghe et al, 2017; Hooghe & Oser, 2018; Oser & Hooghe, 2018a, 2018b), and political donor types (Rhodes et al, 2018). Although LCA is not yet widely used for the study of political participation repertoires, a handful of recent studies have used the technique to identify distinct types of political participants (e.g., Alvarez et al, 2017; Johann et al, 2020; Keating & Melis, 2017; Oser, 2017; Oser et al, 2013; Oser et al, 2014; Steenvoorden, 2018).…”
Section: Latent Class Analysis: Identifying Participation Repertoiresmentioning
confidence: 99%