Conventional wisdom holds that public support for international cooperation is crucial to its viability and effectiveness. Elite debates focus heavily on procedural and outcome characteristics of international cooperation when assessing the latter. However, we know very little about whether and how citizens’ evaluation of international cooperation efforts are also based on such process and outcome considerations, as informed via cues they receive from various sources. Procedural characteristics pertain to how international cooperation and resulting agreements are established and implemented. Output characteristics pertain to how effective, costly, and advantageous international cooperation is. Based on three survey experiments in Germany and the United Kingdom (N = 3000 each), and with an empirical focus on transboundary air pollution in Europe, we examine (1) to what extent information on process and outcomes of international cooperation matters for public support, (2) whether information on the prospect of effective and advantageous outcomes reduces public demand for process improvement in international cooperation, and vice versa, and (3) whether high process quality could make citizens more tolerant of lower quality outcomes, and vice versa? The results show that, from the viewpoint of citizens, both process and outcome characteristics matter. While process-related evaluations of citizens are hardly affected by information on the prospect of high or low outcome quality, citizens are less tolerant of low outcome quality when process quality is low. These results suggest that enhancing process quality is worthwhile, particularly for policy challenges requiring long-term and incremental efforts.
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A large literature on legitimacy of international/global governance, which is a much broader concept than public support, on which we focus here, addresses this issue as well. See, e.g., Morse and Keohane (2014), Lavenex (2013), Margalit (2012), Cheneval (2011), Buchanan and Keohane (2006), Koenig-Archibugi (2004), Tallberg and Zürn (2017), Dellmuth and Tallberg (2015), Archibugi et al. (2012), Bernstein (2011), Johnson (2011), Scholte (2011), Keohane et al. (2009), Buchanan and Keohane (2006), Hooghe and Marks (2005), 2000), Bodansky (1999), Caldeira and Gibson (1995), Risse (2006), and Scharpf (1999).
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The survey instruments are available from the authors on request.
For details, see Appendix A1.1.
Hainmueller et al. (2014) list several conditions that must be met for interpreting linear regression coefficients as average marginal component effect (AMCE). We show in Appendix C1.2 that it is safe to assume that these conditions are met in our case. We also explain how the block randomization was carried out in Appendices C2 (experiment 2) and C3 (experiment 3).
For details, see Appendix A2.1.
For example, our attribute values differ in (numeric) precision. Regarding output characteristics, the conjoint attributes capture clearly specified percentage cuts, costs, and relative benefits, whereas the input characteristics are presented in a more qualitative way.
We asked study participants in the UK and Germany whether their country should leave the EU. Slightly more than 40% of UK respondents wanted the UK to leave the EU while only about 20% of the German respondents wanted Germany to leave the EU.
Results are reported in Appendices A1.5 and C1.1.
These control variables items were placed in the survey before the experimental part (age, gender, left-right self-placement, city type, and region, all of which were required at this stage of the interview for matching and blocking) as well as afterwards (stealth and sunshine democracy, conflict aversion, environmental concern and environmental vulnerability, trust in government, political efficacy, and education). We are aware that interacting (randomly assigned) treatment dummies with post-treatment covariates can introduce post-treatment bias (Gerber and Green 2012: 296–305; Montgomery et al. 2018). Thus, we interpret these results with great caution. Our decision to place most of these items after the experimental part was motivated by seeking to avoid any unwanted priming effects (Gerber and Green 2012: 99).
See Appendix A2.4.
This finding is backed by the estimation of treatment effects using the IPW difference in means estimator and its p value via randomization inference, taking into account that treatments were assigned with equal probability within homogeneous subgroups defined by gender and age group. See Appendix C2.
These regression results are presented in Appendix A2.2.
See Appendix A3.3.
See Appendix A3.1. Support was measured as the response to the following questions: “On a scale from 1 to 7, how much should the UK government support or not support this proposal?” Possible answers ranged from “not support at all” (1) to “strongly support (7).
Robustness checks show that these findings remain stable when using the IPW difference in means estimator and its p value via randomization inference. See Appendix C3.
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We thank Jonas Tallberg, Marco Steenbergen, Liliana Andonova, Thomas Risse, Michael Zürn, as well as colleagues from the NCCR Democracy for very helpful comments on earlier versions of this paper. We are also grateful to Irina Shaymerdenova, Eleanor Willi, and Lukas P. Fesenfeld for research assistance. This article was written in the context of and the survey was funded by the National Center for Competence in Research (NCCR), ‘Democracy in the 21st Century’.
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Bernauer, T., Mohrenberg, S. & Koubi, V. Do citizens evaluate international cooperation based on information about procedural and outcome quality?. Rev Int Organ 15, 505–529 (2020). https://doi.org/10.1007/s11558-019-09354-0
- International cooperation
- Public support
- Air pollution