Hostname: page-component-76d6cb85b7-92wsb Total loading time: 0 Render date: 2026-07-16T05:09:28.503Z Has data issue: false hasContentIssue false

The Cost of Political Action Committee Funding: Evidence on Political Action Committee Funding Refusal Across Candidate Race and Gender

Published online by Cambridge University Press:  30 January 2025

Jennifer S. K. Dudley
Affiliation:
Division of Management, Columbia Business School, USA
Olivia T. Neff*
Affiliation:
Department of Sociology, Purdue University, USA
*
Corresponding author: Olivia T. Neff; Email: oneff@purdue.edu

Abstract

Research on campaign finance suggests that Americans prefer candidates who are not funded by Political Action Committees (PACs). However, prior research has not examined how perceptions of a candidate who is PAC-funded vs. PAC-free might differ for racial minority and female candidates compared to White, male candidates. Using experimental vignettes, we test the causal impact of PAC funding, race, and gender on voter perceptions of the candidate. We find that refusing PAC funds, for example, is associated with appearing more ethical and more likely to work for voters’ interests over special interests, less corrupt, and more capable of winning elections. However, we show that race, more than gender, interacts with PAC funding to impact voter perceptions. We find that White female and male candidates benefit the most from PAC refusal. While Black female and male candidates receive little or no significant change in perceptions, Black PAC-funded candidates are perceived favorably compared to White PAC-funded candidates. Our results have implications for White and Black political candidates considering their funding strategies. Additionally, we contribute to existing literature by showing that refusing PAC funds status does not signal the same qualities for all candidates.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Race, Ethnicity, and Politics Section of the American Political Science Association
Figure 0

Figure 1. Example candidate profile for Black, female candidate in treatment group with Political Action Committee (PAC)-free candidate. Profiles were identical except for (a) the candidate photo which was varied by race and gender, (b), the candidate name which was varied for male and female candidates, and (c) the donor profile which included a funding amount for PAC-funded candidates or “refused PAC funds” for PAC-free candidates.

Figure 1

Table 1. Experimental design and question wording

Figure 2

Table 2. Count, mean, and standard deviation for dependent variables by condition

Figure 3

Figure 2. Adjusted predictions for refusing Political Action Committee (PAC) funds with 95% confidence intervals, based on linear regression with Ethical (in the left panel) and Corrupt (in the right panel) regressed on treatment (PAC-funding acceptance or refusal) and averaged overall candidates.

Figure 4

Figure 3. Adjusted predictions for refusing Political Action Committee (PAC) funds with 95% confidence intervals, based on linear regression with For The People (in the left panel) and For Donors (in the right panel) regressed on treatment (PAC-funding acceptance or refusal) and averaged over all candidates.

Figure 5

Figure 4. Adjusted predictions for refusing Political Action Committee (PAC) funds with 95% confidence intervals, based on linear regression with Winner (in the left panel) and Skilled (in the right panel) regressed on treatment (PAC-funding acceptance or refusal) and averaged over all candidates.

Figure 6

Figure 5. Adjusted predictions for refusing Political Action Committee (PAC) funds with 95% confidence intervals, based on linear regression with Ethical (in the left panel) and Corrupt (in the right panel) regressed on treatment (PAC-funding acceptance or refusal) and candidate race and gender (Black male, White male, Black female, White female). Estimates for funded candidates are presented with the empty circle; estimates for PAC-free candidates are presented with the filled-in circle.

Figure 7

Figure 6. Adjusted predictions for refusing Political Action Committee (PAC) funds with 95% confidence intervals, based on linear regression with For The People (in the left panel) and For Donors (in the right panel) regressed on treatment (PAC-funding acceptance or refusal) and candidate race and gender (Black male, White male, Black female, White female). Estimates for funded candidates are presented with the empty circle; estimates for PAC-free candidates are presented with the filled-in circle.

Figure 8

Figure 7. Adjusted predictions for refusing Political Action Committee (PAC) funds with 95% confidence intervals, based on linear regression with Winner (in the left panel) and Skilled (in the right panel) regressed on treatment (PAC-funding acceptance or refusal) and candidate race and gender (Black male, White male, Black female, White female). Estimates for funded candidates are presented with the empty circle; estimates for PAC-free candidates are presented with the filled-in circle.

Supplementary material: File

Dudley and Neff supplementary material

Dudley and Neff supplementary material
Download Dudley and Neff supplementary material(File)
File 1.2 MB