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Collective irresponsibility: corporate reputations and the role of associations in lobbying

Published online by Cambridge University Press:  21 May 2025

Christina L. Toenshoff*
Affiliation:
Institute of Political Science, Universiteit Leiden, Den Haag, Netherlands
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Abstract

Why do companies sometimes lobby legislators directly and sometimes act predominantly through business associations? Although economic factors, such as size and profitability, are well-known determinants of companies’ decision to lobby, they alone cannot explain the choice in lobbying strategies. This paper provides an explanation for why companies sometimes choose to lobby collectively: reputation. When firms want to lobby in favor of a publicly unpopular position, channeling their efforts through business associations can help them shield themselves from reputational consequences. To test this theory, this paper provides evidence from firms’ lobbying on climate change. Combining climate-friendliness ratings of corporate lobbying with an original survey experiment, it demonstrates the existence of reputational costs from lobbying alone and shows that lobbying through business associations helps firms avoid such costs. For the study of lobbying positions, these results imply important systematic differences in the positions firms take alone and collectively.

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 Vinod K. Aggarwal
Figure 0

Table 1. Regression of difference in climate-friendliness scores between individual and association lobbying

Figure 1

Figure 1. Factors driving divergence in climate-friendliness ratings.Note: Figure depicts the two drivers of the divergence in climate-friendliness scores: Differences in positions and strategic silence. All estimated probabilities are based on OLS regressions. 95% confidence intervals are cluster-boostrapped with clustering by company.

Figure 2

Figure 2. Experimental treatment groups.

Figure 3

Table 2. Six consumer choice exercises summarized

Figure 4

Figure 3. Vignette treatment effects on consumer choice between the two airlines.Note: Vignette treatment effects on choice between two airlines with 95% confidence intervals. Upper left panel: Dependent variable is binary indicator of choosing green airline’s flight. Regression pools choices across all four comparisons between two airlines’ flights, with choice-task fixed-effects and standard errors clustered by respondent. Upper right panel: Vignette treatment effects on choice between brown airline’s flight and train, with 95% confidence interval. Dependent variable is a binary measure of choosing brown airline’s flight. Lower left panel: Vignette treatment effects on choice between green airline’s flight and train, with 95% confidence intervals. Dependent variable is binary measure of choosing green airline’s flight. Lower right panel: Vignette treatment effects on stated willingness to reduce flying in the future due to climate change with 95% confidence intervals. Outcome variable measured on three-point scale (Not Willing (–1), Maybe Willing (0), Willing (1)).

Figure 5

Figure 4. Change in climate-friendliness rating of the two airlines.Note: Figure shows vignette treatment effects and 95% confidence intervals for consumers’ rating of how green the two airlines are. Ratings are measured on a scale of 0 (not climate-friendly at all) to 10 (very climate-friendly).

Figure 6

Figure 5. Vignette treatment effects on consumer choices, by climate concern.Note: The two panels present the coefficients and 95% confidence intervals for respondents’ choice between the two airlines. Underlying regressions pool the four choices that compare the two airlines and include choice-task fixed-effects. Coefficients are calculated using interaction terms between the experimental treatments and a binary measure of climate concern/support for climate policy. Standard errors are clustered by respondent.

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