Do Citizens Hold Business Accountable for Greenwashing by Demanding More Government Intervention?

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Do citizens demand government regulation if firms are accused of greenwashing?∗

Dennis Kolcava † June 25, 2021

Abstract Environmental governance in many Western democracies relies to some extent on self-regulation by the private sector, yet this policy mode is still strongly con- tested. Proponents of introducing government regulation instead argue that voluntary corporate environmental commitments remain shallow and rarely are more than ‘greenwashing’. Can policymakers expect public opinion to be a societal control mechanism of firms’ contributions to environmental goods? I argue that citizens’ support for government regulation should increase in response to firms being accused of greenwashing. I test this argument in a survey experiment (N=2112) conducted with a representative sample of the Swiss voting population. The analysis shows that accusing firms of greenwashing reduces citizens’ confidence in the effectiveness of self-regulation and the synergy of corporate economic interest with environmental protection. However, this attitudinal shift only translates into modest updates of citizens’ regulatory preferences. Hence overall, public pressure for regulation is an unlikely societal control mechanism of corporate behaviour.

Keywords: accountability, greenwashing, public opinion, regulation, social control, survey experiment Funding: This research was supported by the Swiss National Science Foundation (SNSF) within the framework of the National Research Programme Sustainable Economy: resource-friendly, future-oriented, innovative (NRP 73 Grant: 407340 − 172363).

∗Acknowledgements: I am grateful to Thomas Bernauer, Gracia Brückmann, Vally Koubi, David Presberger, Franziska Quoss, and Lukas Rudolph for valuable comments on the research design, the survey instrument, and draft versions of the paper. I further thank Michael Brander, Jan Freihardt, Rachael Garrett and David Konisky for constructive feedback on the paper and Lukas Fesenfeld, Joachim Scholderer, and Michael Wicki for valuable comments on the research design. I thank Franziska Quoss for providing data from wave 1 of the Swiss Environmental Panel. I am grateful to Najmeh Karimian for excellent research assistance. I thank Maria Cucciniello and two anonymous reviewers for their helpful comments. †ETH Zurich, Haldeneggsteig 4, 8092 Zürich, +41798119957, [email protected]

1 1 Introduction

Efforts by political leaders in many Western democracies to move environmental impacts of human economic activity back to within planetary boundaries remain deficient to this day, even in the light of ever more daunting diagnoses (Lade et al, 2020; Wackernagel et al, 2019). The main reasons for political leaders’ inertia are distributional conflicts over societal costs of policy interventions (see, e.g. Swainson and Mahanty, 2018) not least due to private-sector actors’ reluctance to shoulder some of these costs (Kinderman, 2016). Corporate lobbying against enforceable legislation to reduce the environmental impacts of business activity likely contributes to entrenched political debates over the im- plementation of enforceable environmental policy “top-down”(see, e.g. Vesa et al, 2020). Thus, as the lowest common denominator, policymakers in many countries rely on voluntary environmental action or self-regulation by the private sector (Dauvergne, 2018; Héritier and Lehmkuhl, 2008; McCarthy and Morling, 2015). That is, they partly dele- gate the task of reducing environmental externalities from economic activity directly to firms, even though extant literature shows that voluntary corporate environmental action might not contribute towards a meaningful “greening of the economy” (Dauvergne and Lister, 2012; Hoang et al, 2018), and often deserves to be dismissed as “greenwashing” (Lyon and Montgomery, 2015). The reliance on self-regulation by firms to address environmental issues raises the question of what mechanisms lead to an expansion of top-down accountability enforced by the government if companies fail to contribute to environmental goods (Bekkers et al, 2016; Kolcava et al, 2020a). In that context, this study examines to what extent public opinion constitutes such a mechanism. Hence, this study speaks to previous research, which has examined to what extent corporate business conduct is subject to societal ‘checks and balances’ (e.g. Lyon and Montgomery, 2013; Druckman and Valdes, 2019). Prior literature

2 has categorised these societal checks and balances as either ‘private politics’ (e.g. product boycotts) or ‘public politics’ (e.g. petitions to politicians) (e.g. Druckman and Valdes, 2019; Reid and Toffel, 2009). Against this backdrop, I assess a public politics mechanism by investigating whether denunciations of ‘shallow’ voluntary corporate measures – i.e. measures exceeding regulatory floor standards only by a small margin – as greenwashing affect citizens’ public support for top-down regulation of business activity. Thereby, I build on arguments from an emerging literature on how public opinion connects corporate behaviour to political decision-makers’ choices on regulation (Dana and Nadler, 2019; Kolcava et al, 2021b; Malhotra et al, 2019). Theoretical arguments about the effect of corporate behaviour on public opinion in the literature distinguish between the effects of ‘depth’ (i.e. the extent of the commitment by firms) and ‘breadth’ (i.e. the extent of collective action by firms) on citizens’ regulatory preferences. Malhotra et al (2019) argue that even shallow environmental self-regulation can crowd out public support for top-down regulation by the government. This holds for as long as firms in a given sector are able to uphold collective action (breadth). Hence, from that perspective, shallow yet coordinated measures are the most efficient equilibrium for firms within a specific industry. After all, this scenario secures a level playing field within the industry whilst shielding firms from political pressure – that ‘shield’ being a club good (Prakash and Potoski, 2007; Potoski and Prakash, 2013). Consequently, I test whether the likely shallowness of self-regulation by firms might expose such equilibria to a political backlash by activists or citizens if the lack of environmental ambition – or even willful disclosure of false information – is publicly denounced. I test my theoretical arguments using a survey experiment, which I embed in an original survey with a representative sample of the Swiss voting age (18+) population (N=2112). From a methodological standpoint, studying societal responses to corporate

3 environmentalism using survey experiments can be very useful since survey experiments allow for the identification of causal effects. In contrast, similar work based on observa- tional data is confronted with endogeneity issues (Chrun et al, 2016). Hence, even though there is a need for caution when extrapolating from survey experiments to ‘real-world’ events (Barabas and Jerit, 2010), survey experiments can serve as the equivalent of a simulation by exploring individual responses to hypothetical scenarios and policy designs (Mutz, 2011). In the survey experiment, I randomly assign respondents to one of three treatment conditions: a placebo, a text highlighting corporate self-regulation, or a text highlighting corporate self-regulation followed by a greenwashing accusation aimed at those very same self-regulation measures. I nest the research design within two different industry contexts – i.e. environmental issues and self-regulation by firms within those industries. The empirical design and the survey instrument were pre-registered on Harvard Dataverse1. The main finding is that greenwashing allegations change citizens’ attitudes towards corporate environmental action. Specifically, accusing firms of greenwashing makes citizens more likely to perceive voluntary measures as largely ineffective. Moreover, citizens increasingly perceive that environmental protection and corporate economic interest contradict each other. Nonetheless, these accusations do not translate into movements in citizens’ regulatory preferences, i.e. increased demand for new legislation. The findings suggest several explanations for this gap: Opinion shifts differ in response to new information appear to be contingent on prior political and environmental attitudes. Moreover, specific industry contexts probably are linked to specific associations among respondents (e.g. consumer responsibility), which might condition shifts in policy preferences. In a similar vein, respondents’ preferences on policy solutions to familiar environmental problems could be immune to one-off exposure to new information on corporate behaviour due to

4 prior exposure to (and processing of) considerable quantities of similar information. Hence, this study provides insights into public opinion relevant to firms and policymakers in Switzerland and other high-income democracies. In particular, the findings underline the importance of target-setting by public authorities tied to enforceable provisions, in case firm-led voluntary environmental governance turns out to be ineffective. Comparing preferences using International Social Survey Programme data (ISSP Research Group, 2018) shows that, on average, Swiss citizens’ attitudes with respect to regulatory and environmental policy resemble attitudes of citizens in other high-income countries (see Appendix Section A.4). In particular, my study extends our grasp of the volatility of public opinion in green economy politics (Droste et al, 2016; Pitkänen et al, 2016). A thorough understanding thereof is essential because public opinion is likely an important driver of democratic leaders’ decisions on whether to rely on voluntary private-sector measures or whether to push for more top-down regulation in environmental governance (Anderson et al, 2017; Bakaki et al, 2020; Stoutenborough, 2020; Wlezien and Soroka, 2016).

2 Theory

The argument addresses whether citizens’ attitudes towards corporate environmental action and in extension, citizens’ regulatory preferences, constitute a societal control mechanism of corporate self-regulation and ﬁrms’ contributions to the provision of environmental goods. The literature on societal control mechanisms of corporate behaviour generally distinguishes between “private politics” and “public politics” mechanisms (Druckman and Valdes, 2019; Heyes et al, 2018; King and McDonnell, 2015). The term “private politics” refers to “actions by private interests, such as activists that target private agents, often in the institution of public sentiment”(Baron and Diermeier, 2007, p.600). By and large,

5 this includes different forms of activism against firms’ business conduct, most prominently by means of coordinated boycotts of firms’ products (Daudigeos et al, 2018; Endres and Panagopoulos, 2017; McDonnell et al, 2015). However, in contrast to private politics mechanisms, the question of whether corporate business conduct is subject to control via a public politics mechanism – citizens’ attitudes towards firms and citizens’ regulatory preferences in particular – is much less well understood. Besides improving business efficiency (see, e.g. Brekke and Pekovic, 2018; Chernev and Blair, 2015; Burbano, 2016), some of the main benefits of environmental action for firms materialise in the political realm (Baron, 2014; Baron et al, 2011; Fooks et al, 2013) – e.g. via regulatory pre-emption (Maxwell et al, 2000), increased political access (Werner, 2015), more lenient regulatory enforcement (Decker, 2005; Hong et al, 2019), or a strengthened market position (Urpelainen, 2011). Studies have only recently started to examine the link between corporate environmental self-regulation and citizens’ regulatory preferences as a mechanism of regulatory pre-emption. They suggest that self-regulation by firms can reduce (‘crowd out’) citizens’ support for government regulation (Kolcava et al, 2021b; Malhotra et al, 2019). Specifically, the prevalent theoretical argument has it that public responses to corporate environmental action likely depend on the extent of collective action (‘breadth’) and the ambition level of the environmental commitment by firms (‘depth’). Consequently, if companies engage in collective action to pre-empt regulation, they will probably aim to reduce industry-wide public scrutiny and/or political pressure at the lowest possible cost (Fleckinger and Glachant, 2011). Accordingly, broad but shallow environmental commitments appear to be the most likely outcome of that strategic calculus. Indeed, the high probability of shallow commitments in self-regulatory measures is reflected by an extensive amount of empirical research showing that actual environmental

6 benefits of voluntary corporate environmental action are modest (Berliner and Prakash, 2015; Prakash and Potoski, 2014). In particular, a sizable share of this work shows that, in the absence of any institutionalised oversight, self-regulation by firms is unlikely to reduce environmental impacts of business conduct substantially (Carlson et al, 2018; Mayer and Gereffi, 2010; Pye, 2019; Seymour and Harris, 2019; Taylor and Streck, 2018). However, by engaging only in shallow environmental commitments, firms expose themselves to the reputational risk of being accused of greenwashing (Delmas and Burbano, 2011; Marquis et al, 2016). In other words, they expose themselves at best to being accused of overstating marginal environmental improvements, or at worst to being accused of willful misinformation and deception (Lyon and Montgomery, 2015). Hence, I propose that the public denunciation of environmental deficiencies of voluntary corporate measures might trigger a public opinion backlash in favour of top-down regulation by the government. Thus, public opinion would serve as a societal control mechanism of corporate self-regulation. In a recent study, Kolcava et al (2021b) put forth a stylised decision-making framework R = R(P (L),M(L)), in which public demand for an additional unit of regulation (R) increases with the perceived likelihood that additional regulation reduces an environmental problem (P) and decreases with firms’ marginal cost of additional environmental action (M). P decreases, while M increases with the current extent of firms’ self-regulation L. In that framework, if firms seek to reduce public support for regulation, they may engage in voluntary measures and increase L, which would decrease P and increase M. Thus, the perceived benefit of new regulation would decrease while the perceived costs would increase, lowering demand for regulation. However, this process might unfold in the opposite direc- tion, too – greenwashing accusations could undermine the ‘signal’ citizens are supposed to receive regarding the extent of L. On the one hand, accusing firms of greenwashing

7 provides citizens with information that self-regulation is insufficient. Furthermore, greenwashing accusations imply that firms’ profit maximisation is at odds with environmental protection, which offers a potential explanation of why firms are unwilling to engage in substantial environmental commitments in the first place. Consequently, I expect that by subverting voluntary corporate environmental action, greenwashing accusations are likely to increase P and reduce M resulting in an increase in demand for government regulation R. These two steps in citizens’ opinion formation are mirrored by the following two hypotheses:

Hypothesis H1: In a specific industry context, an accusation of greenwashing is a) likely to increase citizens’ perception of self-regulation as ineffective and b) likely to decrease citizens’ perception that the economic interest of firms and environmental protection align.

Hypothesis H2: In a speciﬁc industry context, an accusation of greenwashing is likely to increase citizens’ support for intervention by the government – both in terms of greater surveillance of voluntary action and in terms of replacing voluntary action by top-down regulation.

Let us now briefly turn our attention to alternative drivers of citizens’ attitude and preference formation, which could amplify or reduce the expected effects. For one, information on greenwashing might be subject to potential messenger (e.g. media, NGO) effects. This might lead citizens, who perceive their views to be at odds with, or in line with, the messenger’s, to respectively dismiss or engage with the information on greenwashing. (Dragojlovic, 2015; Turner, 2007). Moreover, citizens might differ in their confidence in the government’s ability to effectively monitor and enforce environmental regulation (Tosun, 2012; Shimshack, 2014). For instance, citizens might be reluctant to support new government regulation due to concerns about regulatory capture (Laffont and Tirole, 1991). Finally, citizens’ preferences concerning government regulation to attain

8 environmental goals might be more or less volatile depending on their degree of ‘crystallisation’ within individuals’ complex of attitudes (Howe and Krosnick, 2017; Miller and Peterson, 2004).

3 Study Design

I test the theoretical argument using a survey experiment (Mutz, 2011), which was embed- ded in an original survey. The data was collected between 25 November and 10 December 2019, drawing one of the most sizable commercial online panels in Switzerland2, from which a quota sample of 2112 citizens of voting age (18+) was drawn. Quotas on respondents’ age, gender (interlocked with age), education, and regional provenance ensured that the sample was representative of these individual properties of the Swiss voting pop- ulation3. The survey was implemented in Switzerland’s three main languages: German, French, and Italian, and was approved by the ETH Zurich’s Ethics Review Commission (decision EK 2019-N-143). Since this study is about testing public opinion as a control mechanism, I aimed to test the theory in industries familiar to respondents, allowing for policy-relevant insights and an assessment to what extent the results hold across industries. Therefore, I tailored the survey experiment to two politically relevant industry contexts instead of using a more general, stylised survey wording. The first context was disposable plastic waste (e.g. packaging) and the voluntary reduction thereof in the retail industry. The second context was greenhouse gas (GHG) emissions by cars, and specifically, car importers’ self-regulation to reduce those emissions by increasing the share of climate-friendly (e.g. battery-electric) vehicles in their product range4. Since both industries are present in public debates (e.g. mainstream media), I relied on real-world corporate statements and media coverage in the treatment design (see, e.g. Häne, 2019; Hoffmann, 2018; Schlautmann, 2019). Respon-

9 dents were randomly assigned to complete the entire survey experiment in one of these contexts. Since the industries differ substantially on multiple dimensions, I did not formulate theoretical expectations on how the treatment effects differ across the two contexts. For one, the industries vary on already existing levels of government policy. For the retail industry, virtually no environmental regulation, standards or financial incentives (e.g. taxes) neither for retailers nor for consumers regarding plastic waste exist. In contrast, government targets (analogue to EU targets) for average CO2 emissions of Swiss importers’ car fleets have been implemented. Other than that, however, policy incentives to increase the share of climate-friendly (especially battery-electric) vehicles remain weak. Hence unsurprisingly, newly registered cars in Switzerland have the worst emissions record in Europe and the uptake of electric vehicles in Switzerland amounted only to around 2% of new car registrations in 2018 (Brückmann and Bernauer, 2020). Notably, though, the Swiss car importing and retail industries have in common that they feature favourable conditions for industry-level collective action (and thus breadth) in self-regulation. That is, both industries revolve around a small number of large companies who are member to industry-wide business associations. The order of contents within the survey experiment was the following: Respondents were first provided with introductory information on their assigned industry context and the current policy debate on that matter5. In the next step, respondents were assigned to the placebo group or one of the information treatment groups (see below). After reading the placebo or treatment vignette, respondents were confronted with the survey items operationalising the dependent variables (see below). In a first step, respondents were asked to indicate their policy preferences (items presented one by one in a randomised order). In a second step, respondents were then asked to respond to the items measuring

10 attitudes towards voluntary environmental action by ﬁrms (items presented one by one in randomised order).

3.1 Treatment Design

Respondents were assigned at random to one of ﬁve groups – one placebo group and two treatment groups per industry. Table 1 summarises the setup of the treatment vignettes. See Appendix Section A.1.1 for English translations of all the German originals. Table 1: Overview of Greenwashing Treatment Composition

Plastic Cars Plastic Cars Treatment/Group Placebo Self- Self- Green- Green- Reg. Reg. washing washing Do ﬁrms engage in No Yes Yes Yes Yes voluntary action? mention Is voluntary action No No No Yes Yes greenwashing? mention

The placebo consisted of a neutral description of a political tool called a “Motion”, which is a procedural request at the disposal of Swiss parliamentarians to suggest drafts of legislative proposals in either chamber of the Swiss Parliament6. In terms of content, the placebo transitioned well into either context introduction (see above) as in both cases, “Motions” have been put forward by members of Parliament 7. Appendix Section A.1.1 includes an English translation of the placebo. In the next step, respondents, who were assigned to one of the self-regulation treatment groups, were presented a text containing information about voluntary measures by ﬁrms before moving to the dependent variable items. Speciﬁcally, the self-regulation-vignette conveyed the following key messages:

• Retail ﬁrms (car importers) see themselves as pioneers in environmental protection.

11 • Retail ﬁrms (car importers) are reducing the environmental impacts of their business activity already.

• Retail ﬁrms (car importers) are promising substantial results of their eﬀorts soon.

As an example, an English translation of this treatment text in the retail context read as follows:

“Swiss companies in the retail trade (e.g. Migros, Coop) see themselves as pioneers in environmental protection. They are already voluntarily working intensively on how they can design packaging in an environmentally friendly manner and replace disposable plastic products. By 2025 they want to use only recyclable plastic or sustainable materials for packaging and disposable products (e.g. disposable tableware, cotton swabs). For this reason, plastic is largely replaced by plant-based materials (e.g. paper, cardboard) for these products. Retailers promise, for example, to reduce the use of plastic packaging by at least 12,000 tonnes by the end of 2020. This would mean a reduction of

almost 5% of the total plastic waste of all Swiss households.”

Participants who were assigned to one of the greenwashing treatment groups were first also confronted with the same text about self-regulation. The reason for this design was that firms need to make some public claim about their voluntary environmental efforts to reap the benefits from appearing green and, in that sense, committing greenwashing. On a related note, this experimental design replicates a real-world setting more closely, where citizens are often confronted with diverse (and potentially conflicting) pieces of information. After that, these respondents were shown an accusation of greenwashing framed and formatted to look like an excerpt from a magazine article, which conveyed the following information:

12 • Retail ﬁrms (car importers) are proﬁting from current unsustainable business practices.

• Retail ﬁrms (car importers) are exaggerating the extent to which they are environmentally progressive.

• Retail ﬁrms’ (car importers’) claims about voluntary environmental action are not trustworthy.

Hence, this treatment text translated to English in the retail context read:

Article title: “Paper is not better”

Article lead: “It makes no ecological sense for retailers to replace plastic with paper. However, by making their business appear green, retailers can sell their customers a clear conscience.”

Article text: “Sales of convenience products (e.g. salads, sandwiches) are currently growing strongly. Retail companies are benefiting greatly from this. However, finished products are available on the shelves only in disposable packaging. The retail trade has taken up the cause of using “sustainable materials” (e.g. paper) for packaging and other disposable products (e.g. cotton swabs). However, environmental experts say: “Disposable products made of paper do not perform better in the life cycle assessment than disposable products made of plastic. On the contrary: the production of paper fibres requires much more water and energy, and more chemicals must be used.” So to be genuinely environmentally friendly, the retail trade would have to sell fewer convenience products and forego good business. When companies claim that their business is environmentally friendly, suspicion is therefore called for. Frequently, this is a bold lie that we, as consumers, like to believe.”

13 Moreover, respondents in the greenwashing treatment group were shown a graphic un- derscoring the key message of the greenwashing treatment (see Appendix Section A.1.1). I further ensured that respondents understood the treatments by including a comprehen- sion check. Respondents who did not provide the correct answer were prompted to reread the treatment text. I further ensured respondents read the texts diligently by hiding the ‘next’ button in the survey for 15 seconds in the ﬁrst reading of the self-regulation-vignette (10 seconds in a potential second reading) and for 20 seconds in the ﬁrst reading of the greenwashing-vignette (15 seconds in a potential second reading). Finally, I included a manipulation check, which tasked respondents with rating the strength of retailers’ (car importers’) voluntary environmental action on a 7-point scale.

3.2 Dependent Variables

In the following, I list English translations of the original German item wordings (see also

Appendix Section A.1.2). To test Hypothesis H1, I requested respondents to report their (dis)agreement concerning statements about the effectiveness of firms’ voluntary measures on the one hand and firms’ economic interest to conduct business in an environmentally responsible way on the other hand on 7-point scales.

• The voluntary measures by retailers (car traders) substantially reduce the environmental (climate) impacts of disposable products (cars) in Switzerland.

• The protection of the environment (climate) is not in the economic interest of retailers (car traders).

Hence, if Hypothesis H1 holds, the greenwashing-treatment should decrease average agreement with the ﬁrst statement and increase average agreement with the second statement relative to both other experimental conditions. To account for alternative attitude

14 shifts, I recorded respondents’ perceptions of consumers’ responsibility (as opposed to firms’) to reduce environmental impacts of plastic waste/cars and the potential costs to consumers caused by new government regulation to curb these impacts (see Appendix Section A.1.2). Respondents’ preferences on government regulation were also operationalised by two statements requesting respondents to indicate the degree of agreement on a 7-point scale, representing two different types of intervention. The first of these items quantified support for mandatory requirements for firms to publish a formal report (i.e. government increasing surveillance/transparency of voluntary action) on their self-regulatory measures:

• New legislation should require retailers (car traders) to write a formal, public report

on how exactly they are reducing the use of disposable plastic (CO2- emissions).

The second statement elicited respondents’ support for top-down regulation (i.e. government stepping in to replace corporate self-regulation), representing a tougher test for respondents to state high support for government intervention:

• The use of disposable products, regardless of the material used (cars with petrol or diesel engines), should be drastically reduced by legislation.

If Hypothesis H2 holds, I should observe higher average agreement with both statements among respondents who were confronted with the greenwashing-treatment relative to respondents in both of the other experimental groups. I estimated a linear regression model to analyse the eﬀects of the greenwashing- treatment relative to the self-regulation-treatment and relative to the placebo. Due to small imbalances created by random assignment to the treatment groups and the industry contexts (see Appendix Tables A.1 and A.2), I included a vector of control variables in the models8. Appendix Section A.5 lists the software used in the analysis.

15 4 Results

In the empirical analysis, I first report pooled estimates of the treatment effects on the main outcome variables. Specifically, I examine whether accusations of greenwashing make citizens’ more likely to see voluntary measures as ineffective and more likely to think that environmental protection contradicts firms’ economic interest (H1). I then investigate if greenwashing accusations increase citizens’ support for government intervention (H2). In the following subsections, I explore heterogeneous treatment effects across industry contexts and individual characteristics.

4.1 How Greenwashing Aﬀects Perceptions of Self-Regulation

Figure 1: Pooled estimates of treatment effects relative to the placebo group on respondents’ perceptions of the environmental benefits of self-regulation (left, N=2037), and of the conflict between environmental protection and firms’ economic interest (right, N=2051). Responses measured on a 7-point scale. Whiskers report 95% confidence intervals. Controls included.

To begin with, I test how the treatments aﬀected the manipulation check included in the survey. This check asked respondents to rate the strength of retailers’ (car importers’) environmental eﬀorts on a 7-point scale immediately after completing the treatment section of the survey experiment. Both the self-regulation-vignette and the greenwashing-

16 vignette trigger significant and substantial movements in responses in the expected di- rections – i.e. higher ratings for self-regulation, lower ratings for greenwashing – relative to the placebo group (thus, also relative to each other) (see Appendix Table A.3). Thus, respondents received the information treatments as intended by the study design. Figure 1 illustrates the results concerning respondents’ perceptions of voluntary corporate environmental action. Relative to the placebo, the greenwashing-vignette significantly decreases respondents’ confidence in the effectiveness of voluntary measures (decrease by 0.68, on a 7-point-scale, 16.5% of the placebo group mean, significant at the 1%-level). This estimated effect is substantial – about 41% of a placebo group standard deviation. I further observe significant and substantial movements in responses to the greenwashing-vignette on the ‘not in firms’ economic interest’ outcome item. On a 7-point scale, the average agreement with the statement increases by 0.48 relative to the placebo group (11.8 % of the placebo group mean, significant at the 1%-level). This effect amounts to 24% of the placebo group standard deviation. Hence, the evidence reported in Figure 1 corroborates Hypothesis H1. Accusing firms of greenwashing indeed appears to decrease citizens’ confidence in the environmental benefits of self-regulation and in the synergy of environmental protection and corporate economic interest.

4.2 How Greenwashing Aﬀects Policy Support

In the following, I assess treatment effects on respondents’ policy preferences pooled across industry contexts (see Appendix Table A.3). I find that relative to the placebo, the greenwashing-vignette does not have substantial or statistically significant effects neither on support for mandatory reporting requirements for firms nor on support for top-down regulation. The greenwashing-vignette only induces a small difference relative to the self-regulation-vignette on respondents’ support for mandatory reporting requirements

17 Figure 2: Pooled estimates of treatment eﬀects relative to the placebo group on respondents’ support for mandatory reporting requirements (left, N=2082), and for top-down regulation (right, N=2084). Responses measured on a 7-point scale. Whiskers report 95% conﬁdence intervals. Controls included.

(increase of 0.16 on a 7-point-scale, 3.25% of the placebo group mean, significant at the 10%-level). I do not observe significant differences between the greenwashing-vignette and the self-regulation-vignette on support for top-down regulation. In sum, the results sum- marised in Figure 2 suggest that greenwashing accusations barely shift citizens’ support for government intervention and, thus, do not support Hypothesis H2. Due to random assignment to treatment/placebo, I only observe few substantial effects of control variables (see Appendix Table A.4). The results show that respondents who place themselves further to the right on the left-right scale assign higher scores to the strength of environmental commitments by retailers (car importers) in the manipulation check. Accordingly, they are also more likely to perceive environmental action by firms as effective and in firms’ economic interest. Moreover, right-leaning respondents are further associated with lower levels of support for government policy – i.e. for both mandatory reporting requirements and top-down regulation. Finally, these respondents assign higher responsibility to consumers and perceive regulation to be more costly. As expected, self- identification with the Green Party (GPS, relative to self-identification with the BDP,

18 a middle party) is associated with the opposite effects. Finally, controlling for survey duration has no substantial effect on the findings – see Appendix Table A.6.

4.3 Heterogeneity by Industry Context

Figure 3: Placebo group mean and distribution of support for mandatory reporting requirements (left, N=696) and top-down regulation (right, N=698). Responses measured on a 7-point scale. The dashed lines report 95% conﬁdence interval around the means. The dark (light) blue bars and brown (green) lines depict responses for the retail (car import) context.

In the next step, I explore variation in the treatment effects across the two industry contexts. As I did not formulate theoretical expectations, I do not draw strong conclu- sions based on the evidence reported below (see Appendix Table A.5). In both industry contexts, the greenwashing-vignette significantly and substantially decreases respondents’ perception of the effectiveness of firms’ voluntary measures. It also triggers significant and substantial positive shifts on the ‘not in firms’ economic interest’ item in both industry contexts. Hence, in general, I do not find substantial differences in treatment effects on

19 how respondents perceive corporate action. This homogeneity may be since both industry contexts are perceived as highly (and similarly) important by the respondents. Appendix Table A.7 shows that (pre-experiment) around 44% (88%) of the sample selected either Swiss cars’ GHG emissions or plastic waste as the most (a top 3) important environmental issue in Swiss politics (see also Appendix Section A.1.3). The estimated treatment effects on respondents’ policy preferences do not reach con- ventional statistical significance levels in either industry context – the exception being the effect of the greenwashing-vignette on support for reporting requirements for car importers (increase of 0.24 (0.27) relative to the placebo (self-regulation) treatment, significant at the 10% and the 5%-level). The analysis points to three potential sources of heterogeneity across contexts: Figure 3 illustrates that while support for increased transparency provisions (i.e. reporting requirements, left panel) is rather homogeneous, people are more supportive of regulating plastic waste top-down (right panel). Hence, the overall demand for government intervention seems to be higher in the retail context. Thus, the greenwashing-vignette might have hit a ‘ceiling’ in terms of increasing support for regulating plastic waste. Moreover, on average, respondents in the placebo group perceive retailers’ voluntary measures as more environmentally effective than car importers’ voluntary measures (see Appendix Figure A.1). This might have made retailers more immune to greenwashing accusations. It also aligns with the finding that in the retail context, the self-regulation- vignette significantly (relative to placebo, on the 1% level) decreases the perceived responsibility of consumers by 0.31. At the same time, the greenwashing-vignette has a positive effect of 0.42 (relative to placebo, on the 1% level) on the same outcome variable in the retail context. This might be interpreted as tentative evidence of a more volatile perception of self-efficacy among citizens (who are also consumers) in the retail context.

20 In other words, if ﬁrms greenwash, individuals may feel relatively more able to compensate for ﬁrms’ greenwashing by, e.g. being more selective when buying groceries or avoiding goods generating non-recyclable plastic waste.

4.4 Heterogeneity by Individual Characteristics

Having examined differences across industry contexts, I next test whether the results are partly driven by heterogeneous treatment effects on different types of citizens. To that end, I exploit additional information I enquired from respondents (Mutz, 2011). Specifically, I separate the main analysis by binary indicators of respondents’ environmental attitudes and political ideology. Figure 4 summarises the results – see the Figure caption for details on the sample splits. As I did not hypothesise about the relationships between these covariates and the treatments, I refrain from strong interpretations. Moreover, I did not experimentally manipulate the covariates; thus, I only observe correlational evidence. Still, these patterns might be useful to explore important variation of how greenwashing accusations affect citizens’ policy preferences. Furthermore, these patterns could be informative for future research, as they prompt us to develop hypotheses on which citizens update their opinions in response to corporate behaviour and why. On the whole, I observe that respondents on the political left, as well as respondents with a high interest in environmental problem solving – i.e. respondents holding high environmental concern, assigning high political importance to either environmental issue – reduce their support for government intervention in response to the self-regulation- vignette. The contrary effects of the greenwashing-vignette are not substantial enough to shift opinions in favour of regulation beyond the placebo baseline. The opposite seems to be the case for respondents on the political right, for respondents holding low environmental concern and respondents not assigning top priority to either

21 Figure 4: Pooled estimates of treatment effects relative to the placebo group on respondents’ support for mandatory reporting requirements (circles, left panel) and top-down regulation (triangles, right panel). Coefficients are shown for subgroups at high (“HiEC”) and low (“LoEC”) levels of environmental concern: i.e. an environmental concern score of “higher” vs. “lower or equal” than 3, the midpoint of the five-point scale developed by Diekmann and Preisendörfer (2003); for subgroups selecting (“HiPrio”) and not selecting (“LoPrio”) either cars’ GHG emissions or plastic waste as the most important environmental issue in Swiss politics (see Appendix Section A.1.3); and for subgroups on the political left (“Left”) and the political right (“Right”): i.e. “lower or equal to” vs. “higher” than 6, the midpoint of the 11-point left-right self-placement scale. “Pro-Environmental/Left’ subgroup results are depicted in red, “Con- Environmental/Right” subgroup results are depicted in blue. Whiskers report 95% confidence intervals. See Appendix Table A.8 for descriptive statistics on these subgroups within the placebo treatment group). environmental issue. That is, even the self-regulation-vignette increases support (albeit not significantly) for regulation in these subgroups. This might be interpreted as evidence

22 that respondents in these subgroups perceive government regulation as a “floor-standard” following voluntary corporate efforts. Whether this is the case is an interesting question for future research. In any case, Figure 4 illustrates that the effects of the greenwashing- vignette build on the initial treatment effect, which is why some of the coefficients reach statistical significance at the 5% level. In sum, these findings point to a decreasing marginal effect of providing specific types of information to particular groups of citizens. Greenwashing accusations might achieve a net increase in policy support among citizens featuring relatively low baseline support levels for environmental regulation. In contrast, they are unlikely to update opinions among citizens who already hold strong attitudes in favour of regulation to attain environmental goals and potentially, high ex-ante suspicions of greenwashing.

5 Conclusion

In this paper, I examine whether citizens’ attitudes and regulatory preferences constitute a societal checks and balances mechanism of voluntary environmental action by firms. Thus, I link to a politically highly relevant debate concerning the appropriate mix of mandatory government regulation and private-sector self-regulation to reduce environmental impacts of economic activity (Potoski and Prakash, 2004). Theoretically, the existing literature tells us a great deal about private politics (e.g. boycotts, campaigns targeting corporate reputation) as a control mechanism of firms’ business conduct (Druckman and Valdes, 2019; Kam and Deichert, 2020; Kitzmueller and Shimshack, 2012). By contrast, this study contributes to the literature interested in different modes of environmental public policy by assessing changes in public opinion – a public politics mechanism – in response to greenwashing allegations. In other words, this study examines if accusing firms of greenwashing is likely to shift citizens’ attitudes

23 and policy preferences such that the resulting change in public opinion could push the government towards stepping in and regulating. Thus, this study speaks to the larger matter of what societal control mechanisms for corporate behaviour exist and whether short-run responses in public pressure could be a relevant force in expanding top-down accountability (i.e. implemented by the government). In a similar vein, this study addresses to what extent cooperative self-regulation equilibria within specific industries are likely to be challenged by the public’s preference in the political arena because of their modest environmental output. The extent of this political challenge matters because collective action between firms in specific sectors might be at stake here. In other words, if public support for regulation is sensitive to public denouncements of the shallowness of voluntary environmental action, some firms might face incentives to break away from collective action, signal stronger environmental commitments and regain the political competitive edge in their interactions with policymakers (Denicolò, 2008; Sam, 2010; Werner, 2012) or citizens (Kolcava et al, 2020b). I argued that accusations of greenwashing directed at firms’ voluntary measures would induce citizens to perceive those measures as environmentally ineffective, and at the same time, reduce the extent to which citizens believe in the synergy of environmental protection and firms’ economic interest. Therefore, I further suggested that greenwashing accusations would increase citizens’ support for government intervention – i.e. for increased government surveillance of corporate activity on the one hand, and for increased government competence to replace voluntary action by mandatory provisions top-down. I tested the theoretical argument in a survey experiment with a representative sample of Swiss voting-age citizens. Thereby, I focused on two industry contexts: the voluntary reduction of disposable plastic by the retail industry and voluntary efforts by car importers to increase the share of climate-friendly vehicles in their product range. The

24 findings reveal that in both contexts, greenwashing accusations decrease citizens’ belief in the environmental effectiveness of voluntary measures and the synergy of environmental protection and firms’ economic interest. Despite that, they do not change citizens’ regulatory preferences on the whole. Hence, ultimately, as a societal control mechanism of corporate contributions to environmental goods, public pressure in favour of more government regulation appears to be of (very) limited potency. In addition, the following three inferences on citizens’ opinion formation can be drawn. First, the data analysis indicates that the substance of policy preference shifts in response to information depends on individuals’ prior political and environmental attitudes (Ny- han and Reifler, 2015; Spilker et al, 2020). In particular, the findings are consistent with arguments holding that opinion formation follows a Bayesian learning process (Bullock, 2009; Guess and Coppock, 2020; Tappin et al, 2020). Thus, empirically, greenwashing accusations tend to increase indicated levels of support for government regulation among respondents, whose prior attitudes are associated with a preference for small government (to attain environmental goals). Second, policy preferences appear to be more malleable in some industry contexts than in others. The results imply that information on corporate actions in specific industry contexts triggers different associations – e.g. regarding consumer responsibility (e.g. Lenzen et al, 2007) – which might crowd out support for government intervention. Similarly, the results suggest that citizens’ policy preferences might be relatively insensitive to information about corporate (mis)behaviour concerning familiar or politically salient environmental issues (see Appendix Table A.7). This stabil- ity could be due to a ‘pretreatment’ environment characterised by abundant information and active public debates (Slothuus, 2016; Druckman and Leeper, 2012). This type of environment might facilitate the ‘crystallisation’ of policy-related priors, and in some cases, policy preferences on the ‘ceiling’ – i.e. strongly in favour of regulation (of, e.g. plastic

25 waste). Accordingly, the findings open promising pathways for further scientific inquiry in other industry contexts. In particular, this study has concentrated on two issues located ‘downstream’ of the supply chain. Hence, citizens, who are also consumers, of high-income countries like Switzerland might perceive control over some of the environmental conse- quences of economic activity via their individual behavioural choices – e.g. when grocery shopping. Future work could systematically investigate the link between greenwashing accusations and public pressure for regulation of firms’ business conduct in ‘upstream’ contexts. In these contexts, citizens arguably perceive a rather low level of self-efficacy concerning environmental impacts of economic activity. However, future research could also test public opinion as a societal control mechanism for the behaviour of firms in other policy domains or with regard to the provision of non-environmental public goods. For example, similar questions concerning accountability arise in debates over the provision of security – a ‘traditional’ public good – which increasingly has been outsourced to private security companies, whose business conduct is often not subject to meaningful regulatory mechanisms (De Nevers, 2010). Alternatively, future studies could examine whether allegations of inequality in employment between men and women in specific companies or industries lead to increased public demand for governmental regulation of employment practices (Epifanio and Troeger, 2019). While this study focuses on a political debate in Switzerland, I argue the results address concerns and public policy controversies in other Western democratic countries. Some may want to question whether the conditions to study public support for environmental policy are distinct in Switzerland from other high-income country contexts. Even though I encourage similar research in other countries, a comparison between Swiss and other high-income countries’ citizens’ regulatory preferences based on International So-

26 cial Survey data (ISSP Research Group, 2018) indicates no substantial differences (see Appendix Section A.4). Moreover, just like Switzerland, many countries in Europe (and the European Union itself) slowly start to diminish disposable plastic waste quantities as well as to cut CO2 emissions of their car fleets (Clemente and Gabbioneta, 2017; Elliott et al, 2020; Leal Filho et al, 2019; González et al, 2019). In general terms, too, policymakers are currently defining the role of business in the EU policy agenda to foster transitions towards more sustainable economic activity – see, e.g. the European Green New Deal (Speck and Zoboli, 2017) and potential legislation on corporate supply chains (Zacharakis, 2021). Meanwhile, in the United States, environmental regulations have been rolled back substantially during the Trump administration (Tollefson, 2017) and experts warn it could take the new administration under Joe Biden years to reinstall those (Davenport, 2021; Popovich et al, 2020). In either case, a thorough understanding of voluntary corporate environmental action and its potential side effects might be more necessary than ever before (Barbaro, 2020). In particular, the prevention and sanctioning of corporate failures to contribute to environmental goods is an essential aspect of high-income democracies’ sustainable development (Renckens, 2020). My findings have important implications with that respect. Specifically, broad but shallow voluntary environmental collective action by firms is unlikely to be challenged by public pressure even if its environmental shortcomings are publicly denounced (Malhotra et al, 2019). Consequently, this emphasises the strategic value of cooperation among firms in industries, in which firms shield themselves from public pressure via industry-wide but unambitious voluntary measures. Hence, the findings cast doubt on policy designs that focus on regulating transparency – e.g. mandating corporate reporting/‘naming and shaming’ – since this approach might be insufficient to motivate firms to deepen their environmental commitments. Instead, the results suggest that substantial environmental

27 commitments by business need to be obtained via the ‘monitoring’ and ‘regulatory threat’ pillars of common environmental governance blueprints (Balleisen and Moss, 2009; Héritier and Eckert, 2008; Kolcava et al, 2021a). In concrete terms, policymakers might have to rely more on ambitious environmental targets/deadlines paired with trigger provisions to substantially increase government competence in introducing top-down rules for business conduct if a more ﬁrm-led policy approach fails to achieve those targets.

28 Data Availability Statement: Replication materials will be made available upon publication in the Journal of Public Policy Dataverse.

Ethics Statement: Respondents provided their informed consent. The study design was approved by the ETH Zurich’s Ethics Review Commission (decision EK-2019-N-143)

29 Notes

1Harvard Dataverse: https://doi.org/10.7910/DVN/SZ1OOP 2See: https://www.intervista.ch/about/?lang=en 3Samples from commercial online survey panels can be equivalent to traditional random samples in terms of representativeness (Ansolabehere and Schaﬀner, 2014; Wang et al, 2015). Appendix Section A.4 documents the representativeness of this study’s sample by comparing its distribution of environmental concern with the distribution of environmental concern in an address-based random sample of the Swiss population. 4Currently, there are no Swiss car manufacturing companies, so Switzerland imports all the vehicles sold on the market. 5Appendix Section A.1.1 provides English translations of these texts.

6For an English description, see https://www.parlament.ch/en/%C3%BCber-das-parlament/ parlamentsw%C3%B6rterbuch/parlamentsw%C3%B6rterbuch-detail?WordId=238 7For disposable plastic, see: https://www.parlament.ch/de/ratsbetrieb/suche-curia-vista/ geschaeft?AffairId=20183712, for cars and GHG, see: https://www.parlament.ch/de/ ratsbetrieb/suche-curia-vista/geschaeft?AffairId=20193472 8Gender, age group, education years, employment, rurality, language, region of Switzerland, self- placement on left-right scale, party ID, and self-stated interest in politics.

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44 Online Appendix for ‘Do citizens demand government regulation if firms are accused of greenwashing?’

A.1 Survey Instrument and Research Design

A.1.1 Wording of the Experimental Treatments (English Translation)

The following texts were used to introduce respondents to the industry contexts. Note that respondents completed the survey experiment just in one of the two contexts. Below them, I list all the treatments (translations from the German originals). “Nationalrat” and “Ständerat” are translated as “National Council” and “Council of States”.

“In the Swiss Parliament, i.e. the National Council and the Council of States, discussions are currently underway on disposable plastic products (e.g. packaging, cups): The debate is about how their use in Switzerland should be reduced. This is because crude oil is used in the manufacture of these products. This pollutes the environment. In addition, disposable plastic generates a lot of waste. Packaging accounts for more than a third of household waste in Switzerland. However, eﬀective measures to reduce the amount of disposable plastic mean higher costs (e.g. higher food prices) and more eﬀort (e.g. more time spent shopping) for consumers.”

“In Switzerland’s Parliament, i.e. the National Council and the Council of States, discussions are currently underway about the cars used in Switzer- land. The debate is about how their emissions of climate-damaging green-

house gases (especially CO2) should be reduced. Most cars are still powered

1 by petrol or diesel engines. This puts a strain on the climate. One-third of all climate-damaging greenhouse gases in Switzerland are emitted by road traﬃc. However, eﬀective measures to reduce the amount of greenhouse gases mean that drivers would have to use more cars with other types of drive (e.g. electric cars) or other means of transport.”

[screen-break]

“Parliament must, therefore, decide whether and how the consumption of disposable plastic should be reduced. The central question is: do we need government measures (for example, new legislation)? Or are voluntary measures by companies in the retail trade suﬃcient?”

“Parliament must, therefore, decide whether and how CO2 emissions should be reduced. The central question is: do we need government measures (for example, new legislation)? Or are voluntary measures by companies in the car trade suﬃcient?”

[screen-break]

Placebo text: The National Council and Council of States are discussing the context because members of the National Council have submitted a so-called “motion”. With a motion, members of the National Council and the Council of States can mandate the Federal Council to submit a draft of legislation or take a [legislative ]measure within two years. Any member of Parliament can submit a motion, and any number of other members can co-sign it. If a motion is submitted, the Federal Council allows the Council from which the

2 motion originates to vote on it. If the Council rejects the motion, it is ﬁled. Otherwise, the other Council can vote on it. If the other Council also agrees, the motion becomes a mandate to the Federal Council.

Voluntary action: Swiss companies in the retail trade (e.g. Migros, Coop) see themselves as pioneers in environmental protection. They are already voluntarily working intensively on how they can design packaging in an environmentally friendly manner and replace disposable plastic products. By 2025 they want to use only recyclable plastic or sustainable materials for packaging and disposable products (e.g. disposable tableware, cotton swabs). For this reason, plastic is largely replaced by vegetable materials (e.g. paper, cardboard) for these products. Retailers promise, for example, to reduce the use of plastic packaging by at least 12,000 tonnes by the end of 2020. This would mean a reduction of almost 5% of the total plastic waste of all Swiss households.

Voluntary action: The Swiss companies in the car trade (e.g. AMAG, Emil Frey AG) see themselves as pioneers in environmental protection. They are already voluntarily working intensively on how they could reduce the CO2- emissions of cars sold in Switzerland. They want to signiﬁcantly increase sales of cars with climate-friendly drive systems (primarily electric and hybrid cars). Most major car manufacturers have already presented plans for the production of more and more models with electric drive. Accordingly, the range of models with electric drive in Switzerland is expected to grow steadily. Car traders are promising that by the end of 2020, one in ten new cars will be an electric or hybrid car that can be charged at the socket.

3 Greenwashing:

“Title: Paper is not better

Subtitle: It makes no ecological sense for retailers to replace plastic with paper. However, by making their business appear green, retailers can sell their customers a clear conscience.

Text: “Sales of convenience products (e.g. salads, sandwiches) are currently growing strongly. Retail companies are benefiting greatly from this. However, finished products are available on the shelves only in disposable packaging. The retail trade has taken up the cause of using “sustainable materials” (e.g. paper) for packaging and other disposable products (e.g. cotton swabs). How- ever, environmental experts say: “Disposable products made of paper do not perform better in the life cycle assessment than disposable products made of plastic. On the contrary: the production of paper fibres requires much more water and energy, and more chemicals must be used.” So to be genuinely environmentally friendly, the retail trade would have to sell fewer convenience products and forego good business. When companies claim that their business is environmentally friendly, wariness is therefore called for. Frequently, this is a bold lie that we, as consumers, like to believe.”

Greenwashing:

“Title: 4x4 boom: New cars put a greater strain on the climate

Subtitle: Every second car sold has four-wheel drive. This is why CO2 emissions from new cars in 2018 are higher than in the previous year. However, by making their business appear green, car traders can sell their customers a clear conscience.

4 Text: Sales of cars with four-wheel drive (e.g. SUVs, off-road vehicles) are currently growing strongly. The companies in the car trade are benefiting greatly from this. At the same time, the car trade is taking up the cause of selling more and more climate-friendly cars (e.g. electric cars, hybrid cars). However, environmental experts say: “Although there have been major technological advances, the cars sold in Switzerland do not emit less CO2. On the contrary: emissions have increased in the last two years.” This is mainly due to the high proportion of 4x4 cars in new car sales. So to be genuinely environmentally friendly, the car trade would have to sell fewer SUVs and off-road vehicles and forego good business. When companies claim that their business is environmentally friendly, wariness is therefore called for. Frequently, this is a bold lie that we, as consumers, like to believe.”

[screen-break]

“Please have a look at the following graphic. It compares the life cycle assessment of disposable plastic and paper products.”

“Please have a look at the following graphic. It compares the proportions of electric and hybrid cars (green) that can be charged at the power outlet and 4x4 cars (brown) among new cars in 2018 (blue).”

5 A.1.2 Wording of the Dependent Variables (English Translation)

Below I list the dependent variable items recording respondents’ attitudes towards voluntary environmental action by ﬁrms and their regulatory preferences.

“Please think again about the text you have just read. Please indicate to what extent you agree or disagree with the following statements. Give your answer on a scale from 1 (disagree at all) to 7 (agree completely).

New legislation should require retailers to write a formal, public report on how exactly are reducing the use of disposable plastic.

The use of disposable products, regardless of the material used, should be drastically reduced by legislation.

The protection of the environment is not in the economic interest of retailers.

The voluntary measures by retailers substantially reduce the environmental impacts of disposable products in Switzerland.

6 Reducing the use of disposable products lies in the responsibility of consumers, not retailers.

New legislation for fewer disposable products would cause high costs for consumers in Switzerland.

New legislation should require car traders to write a formal, public report on

how exactly they are reducing CO2 emissions of cars.

The use of cars with petrol or diesel engines should be drastically reduced by legislation.

The protection of the climate is not in the the economic interest of car traders.

The voluntary measures by car traders substantially reduce the climate impacts of cars in Switzerland.

Reducing the use of cars with petrol or diesel engines lies in the responsibility of consumers, not car traders.

New legislation for fewer cars with petrol or diesel engines would cause high

costs for consumers in Switzerland.”

A.1.3 Wording of the Environmental Issues List (English Translation)

Find the list of environmental issues below; respondents were asked to pick their ‘three most salient’ ones (our translation from German). In a subsequent question respondents then ranked the three items they selected from the list.

7 “Below, you will ﬁnd a list of some environmental problems that have been discussed and written about recently. Please read the whole list ﬁrst and then select the three most important environmental problems from your perspective.

• Plastic waste - consumption of plastic in Switzerland: Pollutes land and sea, leads to microplastics in the environment, plastic production contributes to climate change.

• Peat extraction - extraction of peat in Eastern Europe for Switzerland: damages biodiversity and causes climate-damaging drainage of moors.

• Climate-damaging investments - investments by the Swiss ﬁnancial sector in economic sectors built on fossil fuels (e.g. oil sector, automotive industry): Finances business of major contributors to climate change.

• CO2 emissions from Swiss cars - High emission of greenhouse gases (e.g.

CO2) by vehicles on Swiss roads: Causes climate change and damages health.

• Asbestos - Use of hazardous substances in old buildings (e.g. asbestos) in Switzerland: if released, poisons the air and is harmful to health.

• Pesticides - Use of pesticides and fertilizers in Swiss agriculture: damages biodiversity and reduces drinking water quality.

• Clothing production - the cultivation/processing of cotton for clothing sold in Switzerland: consumes a lot of water, harms biodiversity, and damages plantation workers’ health.

• Food waste - throwing away food that is still edible by retailers and consumers in Switzerland: Causes unnecessary use of land and water.

8 • None of the problems mentioned is important for Swiss politics. ”

A.2 Appendix Tables

The following section reports tables that were not included in the main manuscript. I calculated the balance of means concerning basic socio-demographic covariates between the placebo and the two treatment groups (self-regulation and greenwashing) on the one hand (see Appendix Table A.1) and between the retail and the car import industry context groups on the other hand (see Appendix Table A.2). As was to be expected given the random assignment to the groups, no clear pattern of imbalances in the distribution of covariates was detected. However, for some variables, the balance check returns signiﬁcant diﬀerences induced by the random assignment of respondents to the above-mentioned groups.

9 Table A.1: Balance tests for placebo group vs. self-regulation treatment and greenwashing treatment groups

(1) (2)

C/mean T/mean Diﬀ-In-Means/se N C N T C/mean T/mean Diﬀ-In-Means/se N C N T agegroup==18-30 0.20 0.18 0.01 702 711 0.20 0.20 -0.01 702 699 (0.02) (0.02)

agegroup==31-45 0.24 0.27 -0.04 702 711 0.24 0.25 -0.01 702 699 (0.02) (0.02)

agegroup==46-60 0.31 0.26 0.06∗ 702 711 0.31 0.29 0.03 702 699 (0.02) (0.02)

agegroup==61-90 0.25 0.29 -0.03 702 711 0.25 0.26 -0.01 702 699 (0.02) (0.02)

education==Anlehre 0.01 0.00 0.01+ 702 711 0.01 0.01 0.00 702 699 (0.00) (0.00)

education==Berufslehre 0.47 0.44 0.02 702 711 0.47 0.48 -0.01 702 699 (0.03) (0.03)

education==Diplommittelschule, Fachmittelschule, Verkehrsschule 0.07 0.06 0.01 702 711 0.07 0.05 0.02 702 699 (0.01) (0.01)

education==Haushaltslehrjahr, Handelsschule 0.01 0.02 -0.00 702 711 0.01 0.01 0.00 702 699 (0.01) (0.01)

education==Maturität, Berufsmaturität, Lehrerseminar 0.10 0.08 0.02 702 711 0.10 0.11 -0.01 702 699 (0.02) (0.02)

education==Obligatorische Schule 0.03 0.03 -0.01 702 711 0.03 0.03 -0.00 702 699 (0.01) (0.01)

education==Universität, ETH, FH, PH, höhere Berufsausbildung 0.27 0.30 -0.03 702 711 0.27 0.26 0.01 702 699 (0.02) (0.02)

education==Vollzeitberufsschule 0.05 0.06 -0.02 702 711 0.05 0.05 -0.00 702 699 (0.01) (0.01)

education==kein Schulabschluss 0.00 0.00 0.00 702 711 0.00 0.00 -0.00 702 699 (0.00) (0.00)

employment==employed 0.55 0.55 0.00 702 711 0.55 0.56 -0.01 702 699 (0.03) (0.03)

employment==house 0.04 0.04 -0.00 702 711 0.04 0.04 -0.01 702 699 (0.01) (0.01)

employment==retired 0.24 0.28 -0.04 702 711 0.24 0.24 0.00 702 699 (0.02) (0.02)

employment==self-employed 0.07 0.04 0.02∗ 702 711 0.07 0.05 0.02+ 702 699 (0.01) (0.01)

employment==training 0.07 0.07 -0.00 702 711 0.07 0.09 -0.02 702 699 (0.01) (0.01)

employment==unemployed 0.03 0.02 0.01 702 711 0.03 0.02 0.01+ 702 699 (0.01) (0.01)

language==DE 0.72 0.71 0.01 702 711 0.72 0.76 -0.03 702 699 (0.02) (0.02)

language==FR 0.24 0.24 -0.00 702 711 0.24 0.21 0.03 702 699 (0.02) (0.02)

language==IT 0.04 0.05 -0.01 702 711 0.04 0.04 0.00 702 699 (0.01) (0.01)

urbanrural==Agglomeration 0.21 0.22 -0.01 702 711 0.21 0.24 -0.03 702 699 (0.02) (0.02)

urbanrural==NA 0.00 0.00 -0.00 702 711 0.00 0.00 0.00 702 699 (0.00) (0.00)

urbanrural==Rural 0.19 0.17 0.02 702 711 0.19 0.14 0.05∗ 702 699 (0.02) (0.02)

urbanrural==Urban 0.59 0.60 -0.01 702 711 0.59 0.62 -0.03 702 699 (0.03) (0.03)

party==BDP 0.02 0.02 0.01 702 711 0.02 0.03 -0.01 702 699 (0.01) (0.01)

party==CVP 0.05 0.06 -0.00 702 711 0.05 0.08 -0.03+ 702 699 (0.01) (0.01)

party==EVP 0.02 0.02 -0.00 702 711 0.02 0.02 -0.00 702 699 (0.01) (0.01)

party==FDP 0.15 0.12 0.03 702 711 0.15 0.11 0.04∗ 702 699 (0.02) (0.02)

party==GLP 0.12 0.15 -0.02 702 711 0.12 0.13 -0.00 702 699 (0.02) (0.02)

party==GPS 0.08 0.10 -0.03+ 702 711 0.08 0.09 -0.01 702 699 (0.02) (0.01)

party==NA 0.07 0.07 -0.00 702 711 0.07 0.08 -0.01 702 699 (0.01) (0.01)

party==None 0.14 0.13 0.01 702 711 0.14 0.12 0.02 702 699 (0.02) (0.02)

party==Other 0.02 0.02 0.00 702 711 0.02 0.02 0.00 702 699 (0.01) (0.01)

party==SP 0.17 0.16 0.00 702 711 0.17 0.16 0.00 702 699 (0.02) (0.02)

party==SVP 0.16 0.15 0.02 702 711 0.16 0.15 0.01 702 699 (0.02) (0.02)

polintr== 1.0000 0.04 0.05 -0.00 702 711 0.04 0.04 -0.00 702 699 (0.01) (0.01)

polintr== 2.0000 0.12 0.15 -0.03 702 711 0.12 0.16 -0.04∗ 702 699 (0.02) (0.02)

polintr== 3.0000 0.46 0.41 0.06∗ 702 711 0.46 0.45 0.01 702 699 (0.03) (0.03)

polintr== 4.0000 0.26 0.30 -0.04 702 711 0.26 0.25 0.02 702 699 (0.02) (0.02)

polintr== 5.0000 0.11 0.10 0.01 702 711 0.11 0.10 0.01 702 699 (0.02) (0.02)

region==GS 0.19 0.19 -0.00 702 711 0.19 0.18 0.01 702 699 (0.02) (0.02)

region==ML 0.23 0.21 0.01 702 711 0.23 0.21 0.02 702 699 (0.02) (0.02)

region==NW 0.14 0.14 -0.00 702 711 0.14 0.14 0.00 702 699 (0.02) (0.02)

region==OS 0.13 0.14 -0.01 702 711 0.13 0.15 -0.01 702 699 (0.02) (0.02)

region==TI 0.04 0.05 -0.01 702 711 0.04 0.04 0.01 702 699 (0.01) (0.01)

region==ZH 0.18 0.18 -0.00 702 711 0.18 0.20 -0.02 702 699 (0.02) (0.02)

region==ZS 0.09 0.08 0.02 702 711 0.09 0.10 -0.00 702 699 (0.01) (0.02)

wdummy 0.50 0.51 -0.01 702 711 0.50 0.51 -0.01 702 699 (0.03) (0.03)

leftright 5.66 5.5010 0.16 702 711 5.66 5.50 0.16 702 699 (0.13) (0.13)

Observations 1413 1401 Table reports placebo group and treatment group N’s means and diﬀerence in means with standard errors in parentheses (two panels, as one diﬀerent vignette treatment group per panel). * (+,**, ***) indicates p < 0.05 (0.1, 0.01, 0.001) Table A.2: Balance tests for retail group vs. car import group

(1)

C/mean T/mean Diﬀ-In-Means/se N C N T agegroup==18-30 0.20 0.19 0.02 1049 1063 (0.02)

agegroup==31-45 0.24 0.26 -0.02 1049 1063 (0.02)

agegroup==46-60 0.28 0.29 -0.02 1049 1063 (0.02)

agegroup==61-90 0.28 0.26 0.02 1049 1063 (0.02)

education==Anlehre 0.01 0.01 0.00 1049 1063 (0.00)

education==Berufslehre 0.45 0.47 -0.02 1049 1063 (0.02)

education==Diplommittelschule, Fachmittelschule, Verkehrsschule 0.06 0.06 0.01 1049 1063 (0.01)

education==Haushaltslehrjahr, Handelsschule 0.01 0.01 0.00 1049 1063 (0.01)

education==Maturität, Berufsmaturität, Lehrerseminar 0.09 0.10 -0.01 1049 1063 (0.01)

education==Obligatorische Schule 0.03 0.03 -0.00 1049 1063 (0.01)

education==Universität, ETH, FH, PH, höhere Berufsausbildung 0.29 0.27 0.02 1049 1063 (0.02)

education==Vollzeitberufsschule 0.05 0.05 0.00 1049 1063 (0.01)

education==kein Schulabschluss 0.00 0.00 -0.00 1049 1063 (0.00)

employment==employed 0.55 0.56 -0.01 1049 1063 (0.02)

employment==house 0.04 0.04 -0.00 1049 1063 (0.01)

employment==retired 0.27 0.24 0.03 1049 1063 (0.02)

employment==self-employed 0.05 0.05 -0.00 1049 1063 (0.01)

employment==training 0.07 0.08 -0.01 1049 1063 (0.01)

employment==unemployed 0.02 0.02 -0.00 1049 1063 (0.01)

language==DE 0.72 0.74 -0.01 1049 1063 (0.02)

language==FR 0.23 0.22 0.01 1049 1063 (0.02)

language==IT 0.04 0.04 -0.00 1049 1063 (0.01)

urbanrural==Agglomeration 0.23 0.22 0.01 1049 1063 (0.02)

urbanrural==NA 0.00 0.00 0.00 1049 1063 (0.00)

urbanrural==Rural 0.17 0.17 0.01 1049 1063 (0.02)

urbanrural==Urban 0.60 0.61 -0.02 1049 1063 (0.02)

party==BDP 0.02 0.02 0.00 1049 1063 (0.01)

party==CVP 0.06 0.07 -0.01 1049 1063 (0.01)

party==EVP 0.03 0.02 0.01+ 1049 1063 (0.01)

party==FDP 0.14 0.11 0.03+ 1049 1063 (0.01)

party==GLP 0.12 0.14 -0.02 1049 1063 (0.01)

party==GPS 0.08 0.10 -0.01 1049 1063 (0.01)

party==NA 0.07 0.07 -0.00 1049 1063 (0.01)

party==None 0.13 0.12 0.01 1049 1063 (0.01)

party==Other 0.02 0.03 -0.01 1049 1063 (0.01)

party==SP 0.16 0.17 -0.01 1049 1063 (0.02)

party==SVP 0.16 0.15 0.01 1049 1063 (0.02)

polintr== 1.0000 0.05 0.04 0.01 1049 1063 (0.01)

polintr== 2.0000 0.13 0.15 -0.02 1049 1063 (0.02)

polintr== 3.0000 0.43 0.45 -0.01 1049 1063 (0.02)

polintr== 4.0000 0.27 0.27 -0.00 1049 1063 (0.02)

polintr== 5.0000 0.11 0.09 0.02 1049 1063 (0.01)

region==GS 0.20 0.18 0.02 1049 1063 (0.02)

region==ML 0.22 0.21 0.01 1049 1063 (0.02)

region==NW 0.14 0.14 -0.00 1049 1063 (0.02)

region==OS 0.14 0.14 0.01 1049 1063 (0.02)

region==TI 0.04 0.04 -0.00 1049 1063 (0.01)

region==ZH 0.17 0.20 -0.02 1049 1063 (0.02)

region==ZS 0.09 0.09 -0.00 1049 1063 (0.01)

wdummy 0.50 0.52 -0.01 1049 1063 (0.02)

leftright 5.64 5.47 0.17+ 1049 1063 (0.10)

Observations 2112 Table reports control group and treatment group N’s means11 and difference in means with standard errors in parentheses (one panel, as one different industry context group per panel). * (+,**, ***) indicates p < 0.05 (0.1, 0.01, 0.001) Table A.3: How greenwashing accusations affect public opinion

Dependent variable: Vm Eﬀective No Interest Reporting Regulation Cons.Resp. Reg.Cost Manipulation (1) (2) (3) (4) (5) (6) (7) Firms Self-Regulate −0.036 −0.100 −0.124 0.007 −0.156 −0.035 0.217∗∗∗ (0.087) (0.107) (0.096) (0.100) (0.096) (0.093) (0.075)

Firms Greenwash −0.678∗∗∗ 0.477∗∗∗ 0.035 0.054 0.241∗∗ −0.061 −0.353∗∗∗ (0.086) (0.106) (0.096) (0.099) (0.096) (0.093) (0.074) 12 Constant 4.651∗∗∗ 3.384∗∗∗ 5.557∗∗∗ 5.504∗∗∗ 3.571∗∗∗ 4.718∗∗∗ 4.201∗∗∗ (0.389) (0.479) (0.436) (0.448) (0.432) (0.420) (0.337)

Control mean 4.06 4.05 4.89 4.42 4.09 4.39 3.62 Control sd 1.65 2.00 1.9 2.01 1.85 1.78 1.50 Observations 2,037 2,051 2,082 2,084 2,094 2,003 2,111

Linear regression of treatment group indicators on regulatory preferences, indicators of perceptions of corporate environmental action, and the manipulation check item (see model header). Manipulation check item wording: ‘How big or small do you consider the commitment of Swiss retailers (car traders) to become more environmentally friendly? Indicate your answer on a scale from 1 (very small) to 7 (very big).’ Standard errors displayed in parentheses. Placebo group mean and standard deviation displayed in bottom rows. Control variables (reported below) are used (gender, age group, education level, employment, rurality, language, region of Switzerland, self-placement on left-right scale, party ID, and self-stated interest in politics). **(*, ***) indicates p < 0.05 (0.1, 0.01) Table A.4: How allegations of greenwashing aﬀect public opinion – control variables

Dependent variable: Vm Eﬀective No Interest Reporting Regulation Cons.Resp. Reg.Cost Manip.Pooled (1) (2) (3) (4) (5) (6) (7) Firms Self-Regulate −0.036 −0.100 −0.124 0.007 −0.156 −0.035 0.217∗∗∗ (0.087) (0.107) (0.096) (0.100) (0.096) (0.093) (0.075)

Firms Greenwash −0.678∗∗∗ 0.477∗∗∗ 0.035 0.054 0.241∗∗ −0.061 −0.353∗∗∗ (0.086) (0.106) (0.096) (0.099) (0.096) (0.093) (0.074)

Age 31-45 −0.298∗∗ 0.246 −0.061 0.086 −0.011 −0.315∗∗ −0.135 (0.123) (0.151) (0.136) (0.141) (0.135) (0.130) (0.105)

Age 46-60 −0.207∗ −0.097 −0.051 −0.017 0.230∗ −0.120 −0.085 (0.123) (0.151) (0.136) (0.141) (0.135) (0.131) (0.105)

Age 61-90 −0.351∗∗ 0.009 −0.029 −0.248 0.299 −0.137 −0.138 (0.174) (0.214) (0.192) (0.199) (0.192) (0.185) (0.149)

Education Years −0.083∗∗∗ 0.037 −0.062∗∗ −0.058∗∗ 0.018 −0.007 −0.058∗∗∗ (0.022) (0.027) (0.024) (0.025) (0.024) (0.024) (0.019)

House Work −0.060 0.270 −0.189 −0.305 0.154 −0.002 0.069 (0.185) (0.233) (0.211) (0.216) (0.207) (0.200) (0.161)

Retired 0.212 −0.070 0.191 0.151 0.120 −0.018 0.117 (0.145) (0.179) (0.161) (0.166) (0.161) (0.154) (0.125)

Self-Employed 0.142 −0.166 −0.062 −0.011 −0.026 −0.201 0.110 (0.166) (0.203) (0.184) (0.190) (0.183) (0.179) (0.143)

Training −0.125 0.200 0.230 0.050 −0.231 −0.012 0.011 (0.162) (0.196) (0.178) (0.184) (0.177) (0.171) (0.137)

Unemployed −0.086 0.332 0.265 0.291 −0.077 −0.347 −0.130 (0.239) (0.294) (0.264) (0.270) (0.263) (0.249) (0.203)

French −0.045 0.285 0.297∗ 0.208 −0.394∗∗ 0.264 −0.217∗ (0.153) (0.191) (0.171) (0.176) (0.169) (0.166) (0.131)

Italian −0.425 2.361∗ 0.216 −0.264 −0.301 −0.833 0.191 (1.132) (1.394) (1.274) (1.315) (1.270) (1.204) (0.991)

Leftright 0.076∗∗∗ −0.055∗∗ −0.156∗∗∗ −0.211∗∗∗ 0.132∗∗∗ 0.104∗∗∗ 0.052∗∗∗ (0.022) (0.026) (0.024) (0.025) (0.024) (0.023) (0.019)

CVP 0.394 −0.208 0.268 −0.066 −0.338 −0.069 0.319 (0.270) (0.334) (0.306) (0.313) (0.302) (0.290) (0.236)

EVP 0.007 0.084 0.363 −0.105 −0.061 −0.127 −0.021 (0.331) (0.407) (0.372) (0.382) (0.369) (0.354) (0.288)

FDP 0.275 −0.101 0.134 −0.398 −0.114 −0.185 0.232 (0.253) (0.311) (0.286) (0.293) (0.283) (0.272) (0.221)

GLP −0.106 0.297 0.579∗∗ 0.286 −0.282 −0.446 0.101 (0.253) (0.311) (0.287) (0.294) (0.283) (0.272) (0.221)

GPS −0.210 0.439 1.005∗∗∗ 0.823∗∗∗ −0.431 −0.694∗∗ −0.194 (0.272) (0.334) (0.307) (0.315) (0.304) (0.292) (0.237)

PartyNA 0.344 0.237 0.326 −0.026 −0.046 0.023 0.308 (0.268) (0.330) (0.304) (0.312) (0.301) (0.289) (0.234)

No Party −0.174 0.225 0.131 −0.291 −0.275 −0.226 −0.055 (0.253) (0.311) (0.286) (0.293) (0.282) (0.271) (0.220)

Other Party −0.204 0.190 0.689∗ −0.159 −0.326 −0.523 0.067 (0.333) (0.407) (0.377) (0.389) (0.369) (0.354) (0.288)

SP 0.136 0.272 0.579∗∗ 0.080 −0.203 −0.370 0.019 (0.259) (0.319) (0.293) (0.300) (0.290) (0.279) (0.226)

SVP 0.360 0.159 0.199 −0.276 −0.172 0.144 0.354 (0.250) (0.308) (0.284) (0.290) (0.280) (0.268) (0.218)

Political Interest −0.133∗∗∗ 0.086∗ 0.035 0.092∗ 0.032 −0.119∗∗∗ −0.083∗∗ (0.042) (0.051) (0.047) (0.048) (0.046) (0.045) (0.036)

Mittelland −0.111 0.345∗ −0.134 0.049 −0.215 0.042 −0.276∗∗ (0.152) (0.189) (0.170) (0.175) (0.168) (0.165) (0.131)

North-West −0.012 0.057 −0.493∗∗ −0.023 0.114 −0.088 −0.078 (0.187) (0.232) (0.209) (0.215) (0.207) (0.203) (0.161)

East −0.076 0.313 −0.296 −0.124 −0.176 0.159 −0.223 (0.188) (0.233) (0.209) (0.215) (0.207) (0.203) (0.161)

Ticino 0.336 −2.177 0.475 0.667 −0.345 0.873 −0.512 (1.144) (1.409) (1.287) (1.329) (1.283) (1.217) (1.001)

Zurich −0.005 0.266 −0.159 0.183 0.024 0.104 −0.213 (0.180) (0.224) (0.202) (0.208) (0.200) (0.196) (0.156)

Central 0.027 −0.008 −0.082 0.362 0.039 0.070 −0.058 (0.201) (0.250) (0.225) (0.232) (0.223) (0.218) (0.173)

Rural 0.009 0.091 0.270∗∗ 0.080 −0.066 −0.161 −0.182∗ (0.114) (0.141) (0.128) (0.131) (0.127) (0.122) (0.099)

Urban −0.016 0.045 0.158 0.111 −0.238∗∗ −0.192∗∗ −0.126 (0.090) (0.110) (0.100) (0.103) (0.099) (0.096) (0.077)

Woman 0.210∗∗∗ −0.108 0.101 0.110 −0.178∗∗ −0.079 0.096 (0.075) (0.092) (0.083) (0.086) (0.083) (0.080) (0.064)

Constant 4.651∗∗∗ 3.384∗∗∗ 5.557∗∗∗ 5.504∗∗∗ 3.571∗∗∗ 4.718∗∗∗ 4.201∗∗∗ (0.389) (0.479) (0.436) (0.448) (0.432) (0.420) (0.337)

Control mean 4.06 4.05 4.89 4.42 4.09 4.39 3.62 Control sd 1.65 2.00 1.9 2.01 1.85 1.78 1.50 Observations 2,037 2,051 2,082 2,084 2,094 2,003 2,111

13 Table A.5: How allegations of greenwashing aﬀect public opinion - results by industry context

Dependent variable: Vm Eﬀective (p) Vm Eﬀective (c) No Interest (p) No Interest (c) Reporting (p) Reporting (c) Regulation (p) Regulation (c) Cons.Resp. (p) Cons.Resp. (c) Reg.Cost (p) Reg.Cost (c) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Firms Self-Regulate −0.035 −0.076 −0.266∗ 0.137 −0.219 −0.029 −0.133 0.138 −0.311∗∗ 0.023 −0.122 0.066 (0.116) (0.122) (0.147) (0.150) (0.137) (0.136) (0.128) (0.138) (0.136) (0.133) (0.125) (0.133)

14 Firms Greenwash −0.830∗∗∗ −0.537∗∗∗ 0.257∗ 0.677∗∗∗ −0.187 0.244∗ −0.043 0.175 0.419∗∗∗ 0.055 0.139 −0.305∗∗ (0.117) (0.119) (0.148) (0.146) (0.138) (0.134) (0.128) (0.135) (0.136) (0.130) (0.126) (0.131)

Constant 4.477∗∗∗ 4.571∗∗∗ 2.908∗∗∗ 3.799∗∗∗ 6.150∗∗∗ 5.067∗∗∗ 6.138∗∗∗ 5.151∗∗∗ 2.784∗∗∗ 4.354∗∗∗ 4.597∗∗∗ 4.801∗∗∗ (0.517) (0.550) (0.655) (0.678) (0.615) (0.623) (0.565) (0.626) (0.601) (0.604) (0.562) (0.606)

Control mean 4.5 3.6 3.76 4.34 4.97 4.81 5.11 3.75 3.77 4.4 4.01 4.76 Control sd 1.55 1.63 1.97 2.00 1.88 1.93 1.74 2.03 1.83 1.82 1.68 1.8 Observations 1,036 1,001 1,042 1,009 1,048 1,034 1,052 1,032 1,057 1,037 1,019 984

Linear regression of treatment group indicators on regulatory preferences and indicators of perceptions of corporate environmental action (see model header). Columns labelled with ’(p)’ denote results for the retail industry context group, columns labelled with ’(c)’ denote results for the cars industry context group. Standard errors displayed in parentheses. Placebo group mean and standard deviation displayed in bottom rows. Control variables are used (gender, age group, education level, employment, rurality, language, region of Switzerland, self-placement on left-right scale, party ID, and self-stated interest in politics). **(*, ***) indicates p < 0.05 (0.1, 0.01) Table A.6 summarises the results controlling for survey duration (no controls, pooled across industry contexts). In the restricted models (labelled ‘time’), I exclude respondents, whose total survey response duration was at or below 60% of the median duration. I do not observe substantial diﬀerences between the models restricting on survey duration and the models including all respondents.

15 Table A.6: How allegations of greenwashing aﬀect public opinion – controlling for duration

Dependent variable: Reporting Time Reporting Regulation Time Regulation (1) (2) (3) (4) Firms Self-Regulate −0.148 −0.119 0.034 0.056 (0.109) (0.102) (0.115) (0.107)

Firms Greenwash 0.094 0.093 0.130 0.112 (0.107) (0.101) (0.112) (0.106)

Constant 4.880∗∗∗ 4.886∗∗∗ 4.413∗∗∗ 4.420∗∗∗ (0.077) (0.072) (0.081) (0.075)

Control mean 4.88 4.89 4.41 4.42 Control sd 1.91 1.9 2.05 2.01 Observations 1,872 2,083 1,876 2,085

Linear regression of treatment group indicators on regulatory preferences. Models labelled ‘time’ report estimates for subgroup above 60% of median survey duration (13.4 minutes). Estimates are pooled over both industry contexts. Standard errors displayed in parentheses. Placebo group mean and standard deviation displayed in bottom rows. No control variables are used. **(*, ***) indicates p < 0.05 (0.1, 0.01)

Table A.7: Saliency of Industry Contexts

Top 3 environmental issue in Swiss politics? Top environmental issue in Swiss politics? Yes No Yes No Cars 911 137 465 583 Plastic 931 132 471 592 Total 1842 269 936 1175 Raw distribution for questions 1) “Below, you will ﬁnd a list of some environmental problems that have been discussed and written about recently. Please read the whole list ﬁrst and then select the three most important environmental problems from your perspective.” and 2) “Please now rank the environmental issues you selected in order of political importance.” See Appendix Section A.1.3 for the full list.

16 Table A.8: Policy Support for Subgroups in Placebo Treatment Group

Mandatory Reporting Top-Down Regulation Mean (7-point) Median (7-point) N Mean (7-point) Median (7-point) N HiEC 5.4 6 527 4.9 5 529 HiPrio 5.1 5 328 4.7 5 328 Left 5.3 6 459 4.9 5 459 LoEC 3.4 3 167 2.9 2 167 LoPrio 4.7 5 368 4.2 4 370 Right 4.2 5 237 3.5 3 239 Placebo group frequencies and descriptive statistics for subgroups used in Figure 4.

A.3 Appendix Figures

The following Appendix Section includes figures not included in the main manuscript. Fig- ure A.1 depicts the distributions of respondents’ (placebo group) perceptions of voluntary corporate environmental action. On average, respondents perceive voluntary environmental measures by retailers as more effective than measures by car importers. The belief that a substantial reduction of environmental impacts contradicts firms’ economic interest is uniformly distributed in both industry contexts, the scale mean being significantly lower in the retail than in the car import context. Appendix Figure A.2 reports the distribution of placebo group perceptions of regulatory cost increases and consumer responsibility.

17 Figure A.1: Baseline (i.e. only placebo group) mean and distribution of perceived effectiveness of voluntary measures (left, N=670) and the synergy of environmental protection and firms’ economic interest (right, N=685). Responses measured on a 7-point scale. The dashed lines report 95% confidence interval around the means. The dark (light) blue bars and brown (green) lines depict responses for the retail (car import) context.

18 Figure A.2: Baseline (i.e. only placebo group) mean and distribution on perceived consumer responsibility (left, N=696) and perceived cost increase due to regulation (right, N=669). Responses measured on a 7-point scale. The dashed lines report 95% conﬁdence interval around the means. The dark (light) blue bars and brown (green) lines depict responses the retail (car import) context.

19 A.4 Sample Validity and External Validity

This study’s quota sample represents the voting-age population of Switzerland on the following characteristics: age and gender (interlocked), education, and regional provenance of the participants. Figure A.3 demonstrates that comparing the distribution of an essential attitude (environmental concern), which did not constitute a quota, in the surveyed sample to the distribution of the same attitude in the ﬁrst wave of the Swiss En- vironmental Panel (an address-based random sample, dual-mode survey), does not yield substantial diﬀerences9. A Wilcoxon test shows that both samples are likely to have been drawn from the same distribution (p-value of 0.83). This implies that the quota sample is very comparable to a “traditional” random sample and thus, permits inferences on the Swiss voting population.

Figure A.3: The blue bars (N=4813) show the distribution of the environmental concern scale as measured in the ﬁrst wave of the Swiss Environmental Panel (SEP), a 2018 dual-mode survey based on a random sample of the Swiss population drawn by the Federal Statistical Oﬃce (FSO). In comparison, the red bars (N=2112), indicate the distribution of environmental concern among participants in the quota sample drawn from Intervista’s online panel.

The graphic below compares Swiss citizens’ attitudes towards regulation with regulatory preferences of citizens from other high-income countries. The graphic draws on ISSP data form the year 2016. The ISSP questionnaire 2016 focused on the “Role of Govern-

20 ment”. The Figure below shows proportions of responses on binary indicator variables based on the following survey items. The item ordering in the list corresponds to the top to bottom order of the panels in the Figure. Text in square brackets indicates piped text or a battery item. The binary categories are ordered within the Figure panels such that the top category implies attitudes in favour of more government intervention.

• On the whole, do you think it should or should not be the government’s responsibility to [impose strict laws to make industry do less damage to the environment]. (4-point scale, “deﬁnitely should be” to “deﬁnitely should not be”, response categories 2 and below coded as “Pro”)

• In general, how often do you think that major private companies in [country] do the following? [Comply with laws and regulations?]. (4-point scale, “almost always” to “almost never”, response categories 3 and over coded as “Rarely”)

• Listed below are various areas of government spending. Please show whether you would like to see more or less government spending in each area. Remember that if you say ‘much more’, it might require a tax increase to pay for it. [The environment]. (5-point scale, “spend much more” to “spend much less”, response categories 2 and below coded as “More”)

• Here are some things the government might do for the economy. Please show which actions you are in favour of and which you are against. [Less government regulation of business]. (5-point scale, “strongly in favour of” to “Strongly against”, response categories 3 and over coded as “Disagree”).

Overall, I do not observe substantial diﬀerences in attitudes towards regulatory policy between Swiss and other high-income countries’ citizens. The only notable diﬀerence

21 consists in that Swiss citizens are more likely to think that “ﬁrms comply with rules” (63% in Switzerland, 55% in other countries). This would imply that Swiss citizens perceive private-sector voluntary action as slightly more trustworthy. These ﬁndings are robust to alternative comparisons (e.g. excluding Scandinavian countries, or non-European countries).

22 Figure A.4: Proportions on binary indicators of regulatory preferences of Swiss citizens (orange, N top to bottom 1’025, 1’000, 1’026, 998) and citizen of other high-income countries (green, N top to bottom=16’100, 15’430, 16’087, 15’201). Whiskers denote 95% conﬁdence intervals. High-income countries: Australia, Belgium, Denmark, Finland, France, Germany, Iceland, New Zealand, Norway, Sweden, United Kingdom, United States

23 A.5 Software

I used R (R Core Team, 2020), including additional packages (Brewer and Harrower, 2002; Dahl et al, 2019; Elﬀ, 2019; Hlavac, 2018; Revelle, 2019; Robinson and Hayes, 2020; Solt and Hu, 2015; Wickham et al, 2019; Wilke, 2019) for the data analysis.