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# Climate Regulation and Civil Society Activism

Michela Limardi, Jordan Loper, Alexandre Volle

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Michela Limardi, Jordan Loper, Alexandre Volle. Climate Regulation and Civil Society Activism. 2025. hal-05047276v5

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Climate Regulation and Civil Society Activism*

Michela Limardi† Jordan Loper‡ Alexandre Volle§

This version: December 23, 2025

**Abstract**

This paper examines how public climate regulation shapes NGO activism against firms. Our empirical strategy leverages the irregular and low-anticipability timing of executive climate regulations, administrative actions issued outside legislative procedures, as a source of plausibly exogenous month-level variation in regulatory exposure. Using a global monthly panel of firm-targeted NGO campaigns across 78 countries (2010-2023), we find that the enactment of executive regulations leads to significant increases in climate-related activism. Event-study estimates show no pre-trends and reveal a persistent post-adoption rise in campaigning. Consistent with our conceptual framework, the effect is larger in countries with weaker enforcement capacity and among nationally oriented NGOs that are better positioned to act on domestic institutions. Together, these findings show that public regulation mobilizes civil society as an informal enforcement layer, extending climate governance beyond formal state action.

**Keywords:** Civil Society, Climate Regulation, Environmental Governance, NGO activism

**JEL classification:** L14, L31, L51, Q58

<footnote>*We are grateful to Stefan Ambec, Ricardo Dahis, Christian Gollier, Jonathan Goupille-Lebret, Benjamin Marx, Vincent Pons, Mathias Reynaert, Tanguy van Ypersele, Paul Vernus, Ekaterina Zhuravskaya and seminar participants at CERDI, TSE Environmental Workshop, UPPA, as well as attendees at the Economics & Politics Workshop at Sciences Po Paris (Reims campus) and the FAERE Annual Conference, for valuable comments and suggestions. This research was supported by the French government's *Agence Nationale de la Recherche* of the French Government under the "France 2030" program (grant ANR-16-IDEX-0001). Part of this research was conducted while Jordan Loper was visiting the Toulouse School of Economics, whose hospitality is gratefully acknowledged. All remaining errors are our own.</footnote>

<footnote>†Michela Limardi: Université de Lille, RIME.</footnote>

<footnote>‡Jordan Loper: Université Clermont Auvergne, CNRS, IRD, CERDI, F-63000, Clermont-Ferrand.</footnote>

<footnote>§Alexandre Volle: E2S UPPA, CNRS, TREE, Université de Pau & des Pays de l'Adour; email: alexandre.volle@univ-pau.fr (corresponding author).</footnote>
# 1 Introduction

As the urgency of addressing climate change intensifies, understanding the institutional architecture of global climate governance has become increasingly important. While much of the recent economic literature has focused on assessing the effectiveness of climate policies, a parallel development has garnered less empirical attention: the growing role of civil society organizations—particularly non-governmental organizations (NGOs)—in shaping corporate environmental conduct.<fnref n="1" /> As governments expand climate regulation (see Figure 1), NGOs have intensified their efforts to monitor and pressure firms (see Figure 2). These simultaneous shifts raise a central question in the political economy of climate action: Does public climate regulation activate NGO activism against firms, and if so, through what mechanisms? This paper offers one of the first empirically grounded investigations of this question, offering novel evidence on how formal regulation interacts with informal oversight in the broader climate governance framework. While classical economic frameworks often treat the state and NGOs as strategic substitutes, our findings point to a shift in this view: public regulation can amplify—rather than crowd out—civil society engagement.

A central empirical challenge in assessing the effect of public regulation on NGO activism is that both may respond to broader shifts in political attention and public preferences. To address this concern, our empirical strategy exploits the month-level timing of executive climate regulations - defined as mitigation-related decrees, administrative decisions, or policy instruments adopted directly by governments, presidents, or relevant ministries. Research in political science and public administration shows that executive actions are issued through opaque administrative channels outside legislative calendars, without public deliberation, and with substantial discretion over their timing (Djourelova & Durante, 2022; Kennedy, 2015; Smirnova, Strumsky, & Qualls, 2021). The institutional determinants of regulatory timing operate on horizons that are too slow-moving or opaque to be exploited by NGOs in their month-to-month campaigning decisions. As a result, while the decision to regulate may reflect longer-run political priorities, the timing of executive enactments provides the kind of plausibly high-frequency variation that is suitable for causal identification in our setting. We further reinforce this identification by controlling for several proxies of climate preferences and public attention - including Google Trends searches for “climate change” and the

<footnote n="1">¹NGOs are central actors in climate-related civil society activism, as they collaborate with a wide range of stakeholders and often play a pivotal role in coordinating actions. For example, *L'Affaire du Siècle*, launched in France in 2019 to denounce the French state's climate inaction, mobilized a broad spectrum of civil society—with NGOs playing a key role in the initiative.</footnote>
occurrence of climate-related natural disasters - and by using technological disasters as a falsification
test for non-climate salience shocks. Finally, we validate the identifying assumption empirically
through event-study estimates showing no pre-trends.

The interaction between public regulation and *private politics* (Baron, 2001)—understood as
NGO activism and broader civil society pressure on firms—has only recently attracted attention in
the economics literature, primarily through theoretical models (Egorov & Harstad, 2017; Krautheim
& Verdier, 2016).<fnref n="2" /> Despite its importance, systematic empirical evidence on this relationship re-
mains scarce. This paper addresses these concerns by leveraging novel panel data and exploiting
plausibly exogenous variation in the timing of climate regulation to estimate its causal effect on
NGO activism directed at firms.

Our analysis builds on Egorov and Harstad (2017), who model the strategic interaction be-
tween activists, firms, and regulators. In their framework, activism and regulation may function
as substitutes: when regulators are more active, the scope for NGOs correspondingly diminishes.
A key feature of their modeling environment is that the benefits of successful activism and the
reputational costs of failure are treated as independent of the institutional context. Our conceptual
framework highlights a complementary channel: public regulation itself can reshape NGO incen-
tives by increasing the legitimacy of their claims, strengthening the informational and legal levers
available for monitoring, and reducing the reputational risks associated with campaigning. When
regulation alters the payoff structure in this way, activism may rise rather than fall in response to
state intervention. This perspective motivates our empirical analysis, in which we examine whether
and how executive climate regulation catalyzes NGO engagement and shapes the dynamic response
of firm-targeted activism.

Using a newly assembled monthly panel covering NGO campaigns and climate regulatory activity
across 78 countries from 2010 to 2023, we show that the adoption of public climate regulation
substantially increases the probability that NGOs target firms with climate-related campaigns.<fnref n="3" />
The effect is robust to NGO, country, and month-year fixed effects, as well as time-varying country-
level controls, including public interest and climate preference shocks such as natural disasters.

<footnote n="2">²Baron (2001): “Private politics refers to the efforts of interest and activist groups to influence economic activity, directly without reliance on public institutions or officeholders.”</footnote>

<footnote n="3">³While legislative regulation—issued through formal legislative processes—is one component of public regulation, our analysis focuses exclusively on executive regulation. As discussed in section 4, executive actions (e.g., decrees or policies issued directly by governments or administrative agencies) offer stronger identification leverage, as their timing is more plausibly exogenous to short-term NGO activity. The majority of climate-related public regulation in our dataset falls into this executive category. In section 5, we present a series of tests and robustness checks to validate this identifying assumption.</footnote>
Event-study analyses reveal a persistent rise in NGO activism following regulatory enactment, with no evidence of differential pre-trends, supporting a causal interpretation.

We find that the impact of regulation on NGO activism is heterogeneous, reflecting differences in NGOs' capacity to act on institutional levers. Nationally focused NGOs—well positioned to respond to domestic regulatory contexts—exhibit the strongest responses, whereas locally oriented NGOs often lack the resources to mobilize, and international NGOs tend to prioritize global issues over domestic policy environments. Regulation also has larger effects in countries with weaker enforcement, consistent with NGOs responding strategically to institutional and regulatory incentives. Taken together, these patterns indicate that public regulation shapes both the intensity and the allocation of activist effort across organizational types and governance contexts.

Taken together, our findings show that public regulation affects more than corporate behavior: it mobilizes civil society actors to exercise informal oversight, generating reputational and accountability pressures on firms. Climate policy thus operates not only through formal mandates but also by activating NGOs to monitor and enforce compliance indirectly. By highlighting this channel, our results underscore the broader societal impact of regulatory action and provide a strong rationale for an active regulatory stance that strengthens both direct and indirect levers of climate accountability.

This paper contributes to several strands of literature. First, we contribute to the growing body of literature on the role of NGOs and non-state actors in climate governance. Previous studies have extensively documented how NGOs influence corporate behavior through reputational pressure, media campaigns, and shareholder activism (Baron, 2001; Baron & Diermeier, 2007; Couttenier & Hatte, 2016; Lyon & Maxwell, 2011). In addition, a growing body of research has emphasized the role of NGOs in monitoring and influencing corporate practices, particularly in contexts with weak formal institutions. In these settings, NGOs play a critical role in fostering sustainable corporate behavior (Daubanes & Rochet, 2019; Potoski & Prakash, 2005). While much of this work has focused on the effects of NGO campaigns, our study shifts the focus toward the determinants of NGO behavior itself. Specifically, we offer one of the first systematic analyses of how public regulation catalyzes NGO engagement, thus reframing civil society actors not only as exogenous pressure groups but also as endogenous responders to state action.

Within this broader literature, a small but influential strand has examined how NGOs and activists shape regulation before it is enacted, either through lobbying policymakers or pressuring
firms in ways that subsequently alter regulatory choices (Baron, 2014; Daubanes & Rochet, 2019; Lyon & Salant, 2013; Maxwell, Lyon, & Hackett, 2000). Our contribution is distinct. We do not study lobbying or pre-legislative influence. Instead, we focus explicitly on the ex-post phase: how regulation, once adopted, reshapes NGOs' incentives to campaign against firms.

Second, our paper contributes to the broader literature on accountability and third-party monitoring, specifically within the context of private politics—the study of how non-state actors influence public and corporate behavior outside of formal institutional channels (Baron et al., 2012; Bartley & Child, 2014; Heyes, Lyon, & Martin, 2018; Lenox & Eesley, 2009). In the realm of global governance, NGOs and activist groups have been recognized as important accountability-enhancing agents, particularly in public goods provision (Besley & Ghatak, 2007; Björkman & Svensson, 2009), global supply chains (Bartley, 2007; Koenig, Krautheim, Löhnert, & Verdier, 2025; Krautheim & Verdier, 2016), labor standards (Fontagné & Limardi, 2024; Locke, Qin, & Brause, 2007) and creditence goods markets (Baron, 2011; Volle & González, 2023). While previous research has explored how NGOs act as agents of accountability, we extend this line of inquiry into the area of climate governance, focusing on how NGOs' capacity and willingness to act are shaped by institutional contexts, particularly the informational and institutional signals generated by public regulation. In doing so, we reveal a feedback loop in which public regulation enhances civil society's capacity to hold firms accountable.

Finally, we contribute to the literature on the political economy of environmental regulation and institutional complementarities. A growing body of empirical research has assessed the effectiveness of public climate policies in reducing greenhouse gas emissions and curbing environmentally harmful behavior (Blanchard, Gollier, & Tirole, 2023; Dahis, de las Heras, & Saavedra, 2025; Dechezleprêtre, Nachtigall, & Venmans, 2023; Greenstone & Hanna, 2014; Greenstone, Pande, Ryan, & Sudarshan, 2025; Oliva, 2015; Shapiro, 2021, 2025). Complementing this work, both theoretical and empirical studies have emphasized the importance of informal institutions in supporting or substituting for weak formal enforcement (Fontagné & Limardi, 2024; Ostrom, 2010). Our study extends this literature by providing new empirical evidence that public climate regulation can mobilize civil society responses—particularly NGO activism—thereby indirectly shaping firm behavior through reputational and political channels. Specifically, we show that public regulation enhances NGO engagement, especially in countries with weaker regulatory stringency. This suggests that rather than crowding out civil society oversight, regulation can serve as a catalyst for informal accountability
mechanisms. This perspective stands in contrast to existing models that view regulation and NGO activism as strategic substitutes (Egorov & Harstad, 2017; Krautheim & Verdier, 2016), and instead highlights how regulation can activate and strengthen informal oversight by NGOs.<fnref n="4" />

The rest of the paper proceeds as follows: we begin by presenting the conceptual framework and deriving testable predictions in section 2. Next, we describe in section 3 the data and key variables used in our analysis. The empirical strategy is outlined in section 4, followed by the presentation of our main results in section 5. Finally, we investigate the mechanisms driving the observed relationship in section 6, before concluding with a discussion of the broader implications of our findings in section 7.

<figure><img src="image_3.png" /><figcaption>Figure 1: The rise of public climate mitigation regulation across 200 countries, 1995–2023</figcaption></figure>

*Note:* This figure displays the global evolution of national public climate mitigation regulation between 1995 and 2023, based on data from 200 countries. The left axis shows the annual number of new documents enacted. The total includes both legally binding laws (solid green line) and non-binding policy instruments such as strategies or directives (dashed line). Key international climate summits—Kyoto (1997), COP 15 (Copenhagen, 2009), COP 21 (Paris, 2015), and COP 26 (Glasgow, 2021)—are marked with vertical dotted lines. Source: computation from the authors, using data from *Climate Change Laws of the World*.

<footnote n="4">⁴Our findings also relate to a growing literature examining how policy interventions influence citizens’ attitudes, beliefs, and engagement with climate action. For instance, Deryugina and Shurchkov (2016), Davis and Metcalf (2016) as well as Dechezleprêtre et al. (2025) emphasize the role of information provision and perceptions of public policy in shaping climate-related behavior and support.</footnote>
<figure><img src="image_4.png" /><figcaption>Figure 2: The rise of NGO climate activism against firms, 2010–2023</figcaption></figure>

*Note:* This figure illustrates the evolution of climate-related NGO activism between 2010 and 2023. The left axis shows the annual number of campaigns targeting firms in which climate change is cited as an issue. The right axis displays the share of climate-related campaigns relative to all campaigns conducted by NGOs in a given year. The figure highlights a notable increase in both the absolute and relative frequency of climate campaigns over time. Vertical dotted lines mark the timing of major international climate summits—COP 21 (Paris, 2015) and COP 26 (Glasgow, 2021)—which coincide with periods of intensifying NGO engagement. Source: computation from the authors, using data from Sigwatch.

## 2 Conceptual Framework

Formally, the decision to engage in activism can be modeled as a benefit-cost comparison: NGOs derive benefits such as increased visibility, credibility with supporters and funders, and the possibility of influencing firms, but they must incur financial, organizational, and reputational costs. Activism occurs only when expected benefits outweigh expected costs, a structure directly comparable to standard optimization frameworks in economics.

Only a few recent theoretical contributions explicitly consider the interaction between NGO activism and public regulation. Krautheim and Verdier (2016) examine how globalization creates scope for endogenous NGO action, Daubanes and Rochet (2019) show that NGOs may emerge as checks on captured regulators, and Egorov and Harstad (2017) develop a general dynamic framework in which activism and regulation often appear as substitutes. We extend this perspective by highlighting a different channel: regulation itself can catalyze activism by reshaping the payoff structure.<fnref n="5" />

<footnote n="5">⁵In Egorov and Harstad (2017), the benefit from activism materializes whenever regulation is in place, whether achieved through self-regulation or public intervention, and does not depend directly on the activist's own actions.</footnote>
Specifically, public regulation may increase the expected benefits of activism by legitimizing NGO claims, attracting donor support, and raising the reputational returns to success. At the same time, it may lower the costs by reducing the reputational risks of failed campaigns and providing clear legal or normative benchmarks that ease monitoring. Thus, rather than displacing activism, public regulation can trigger or crowd in NGO engagement, mobilizing civil society as an informal enforcement layer.

More broadly, regulation transforms the informational and institutional environment in which NGOs operate. Public institutions not only impose rules but also create opportunities for accountability.<fnref n="6" /> Graham and Woods (2006) show how policy environments channel civil society pressures, O'Rourke (2002) documents how environmental laws in Vietnam enabled grassroots activism, and Auld and Gulbrandsen (2013) argue that public and private regulation often reinforce each other by broadening oversight and enhancing corporate accountability. In this view, regulation serves not only as a set of formal rules but also as a signal and coordination device: it legitimizes NGO claims, amplifies their authority, and provides actionable reference points that transform diffuse concern into sustained oversight.

We therefore predict a positive link from regulation to activism, focusing exclusively on the post-adoption channel. This restriction is also crucial for identification: by examining how executive regulations affect NGOs, we can exploit variation in timing to test the catalytic role of regulation.<fnref n="7" />

<footnote>Activism only affects the probability of achieving regulation, while the payoff from success is treated as exogenous. Similarly, the reputational cost of failed activism is modeled as a constant per-period flow cost, independent of the institutional environment. Our framework instead endogenizes both benefits and costs, making them functions of regulation itself.</footnote>

<footnote n="6">⁶Recent climate litigation illustrates how regulation can lower the costs and raise the legitimacy of NGO activism by providing actionable legal frameworks. In Italy, Greenpeace and ReCommon—joined by 12 citizens—filed suit against Eni in May 2023, invoking the Environmental Code (Legislative Decree No. 152/2006) to demand emission reductions consistent with the Paris Agreement. In France, NGOs brought legal action against BNP Paribas under the Duty of Vigilance Law, alleging that the bank failed to prevent environmental harm through its financing activities. These cases show how public regulation does not merely constrain firms directly but also equips NGOs with institutional levers to amplify their campaigns. Sources: Business and Human Rights website (https://www.business-humanrights.org/en/latest-news/italy-ngos-citizens-sue-energy-giant-eni-over-human-rights-climate-change-impacts-in-italys-first-climate-lawsuit/), last accessed on September 22, 2025); Osler website (https://www.osler.com/en/insights/updates/first-climate-lawsuit-against-a-commercial-bank-NGOs-take-legal-action-against-bnp-paribas-for-fund, last accessed on September 22, 2025).</footnote>

<footnote n="7">⁷While the timing of executive regulations is arguably less subject to anticipation and lobbying dynamics than legislative laws, we cannot assume full exogeneity. In section 5, we present a battery of robustness checks, including pre-trend analysis, placebo tests and controls for public interest and preference shocks, to assess the plausibility of this assumption.</footnote>
## 2.1 Testable Predictions

The conceptual framework outlined above yields three testable predictions, which we evaluate empirically in section 5 and section 6.

**Prediction 1.** *Public climate regulation increases NGO activism against firms.* By strengthening the institutional environment for monitoring and enhancing the legitimacy of climate concerns, regulation should increase the likelihood of firm-targeted NGO campaigns.

**Prediction 2.** *The marginal effect of regulation is stronger in weaker regulatory environments.*
New regulation creates larger incremental incentives where baseline enforcement capacity is limited. In such contexts, regulation provides NGOs with a new lever to act as informal monitors.

**Prediction 3.** *The effect of regulation is stronger for nationally focused NGOs.* NGOs differ in both resources and orientation. The effect of regulation is stronger for nationally focused NGOs. While international NGOs often prioritize global issues, and local NGOs may lack resources, nationally oriented NGOs combine capacity with a strong interest in domestic institutions, making them most responsive to regulatory changes.

Predictions 2 and 3 derive from the same underlying mechanism: public regulation reshapes the payoff structure of activism. By increasing the benefits and reducing the costs of campaigning, regulation creates the strongest incentives where NGOs are best positioned to exploit institutional levers (Prediction 3) and where baseline state enforcement is weakest (Prediction 2).

## 3 Data

In order to test our main predictions, we compile a novel panel dataset that merges data on (NGO) civil society activism, climate mitigation regulation, and a set of control variables accounting for potential confounders. This section outlines the construction and content of our dataset. Further details are provided in Appendix A.<fnref n="8" />

<footnote n="8">⁸See Table A1 in appendix for an exhaustive overview of our data sources.</footnote>
## 3.1 Civil society climate activism

In order to capture civil society climate activism, we use proprietary data from *Sigwatch*, a European consultancy that continuously monitors and records NGO activity against firms.<fnref n="9" /> The database is designed for corporate clients seeking to track activist pressure and reputational risk. For each campaign, *Sigwatch* identifies the NGOs involved, the targeted firms, and classifies the tone of the report—either negative or positive.<fnref n="10" /> We restrict our analysis to negative campaigns, which account for approximately 80% of all observations, as they more directly reflect adversarial pressure on firms and are more likely to represent activist scrutiny.<fnref n="11" />

We define a climate-related campaign as any report in which climate change is explicitly cited as a core issue. To maintain consistency, we focus on NGOs that have published at least one such campaign over the sample period. Table A2 in appendix provides descriptive statistics on the content of climate-related NGO campaigns. The ten most frequently cited issue categories account for 86% of all campaigns and predominantly concern fossil fuel investments, greenhouse gas emissions, and government (in)action on climate policy.

Each campaign is timestamped to the date the NGO publishes the report on its website.<fnref n="12" /> The data also include two key geographical identifiers: the country of the NGO and the country of the issue. Following Hatte and Koenig (2020), we observe a strong *proximity bias*, with NGOs generally targeting firms headquartered in their home countries. While the issue's origin may matter for local concerns like deforestation, the transnational nature of climate change and the regulatory systems involved make the NGO's country of origin the more relevant unit of analysis in our setting.

Our primary outcome variables are defined at the *NGO-month* level. The main dependent variable is a binary indicator equal to one if an NGO publishes at least one climate-related report in a given country-month. To explore extensive and intensive margins of activity, we also construct two additional outcomes: (i) the number of climate-related campaigns and (ii) the share of climate-

<footnote n="9">⁹See https://www sigwatch com/ (last accessed on September 22, 2025).</footnote>

<footnote n="10">¹⁰See Koenig (2017) for further details.</footnote>

<footnote n="11">¹¹Negative campaigns are more indicative of adversarial activism aimed at shaping firm behavior through reputational pressure (Baron, 2001; Baron & Diermeier, 2007). Empirical studies in economics and political economy have shown that such confrontational strategies are particularly salient in shaping corporate and regulatory outcomes. Moreover, negative framing is central to mobilizing public attention and signaling credibility in activist efforts (Bartley & Child, 2014; Aldashev, Limardi, & Verdier, 2015; Couttenier & Hatte, 2016). By focusing on negative campaigns, we align with the literature that emphasizes their stronger influence on firms and greater strategic relevance in private politics.</footnote>

<footnote n="12">¹²Some campaigns are carried out collectively by multiple NGOs. In such cases, we attribute the campaign to each participating NGO individually, as each organization invests resources and takes a stance on the issue. To implement this, we reshape the data at the NGO level, following the approach of Hatte and Koenig (2020).</footnote>
related campaigns relative to all NGO campaigns in that country-month. Our final panel spans from 2010 to 2023 and covers 1237 NGOs operating in 78 countries, resulting in 6,545 climate-related campaigns. To avoid bias from inactive periods, we trim each NGO's observation window to the first and last months in which they are observed reporting.

As reported in Table 1, the average number of climate-related reports per NGO-month is 0.08, highlighting the episodic nature of climate-focused campaigns. In roughly 6% of observations, NGOs issue at least one climate-related report, and the mean share of climate-related reports is 5%. Campaigning on other issues remains more frequent, with NGOs releasing other reports in 15% of the observations. On average, NGOs engage in climate campaigning once every 18.1 months, compared to 13.5 months for non-climate campaigns. This discrepancy reflects a lower baseline frequency of climate-focused activity, consistent with the idea that climate change, although increasingly salient, remains a more selective area of NGO mobilization compared to broader social or environmental issues.

Nevertheless, as illustrated in Figure 2, climate-related campaigns have been on the rise. Although these campaigns remain episodic, their frequency has notably increased over time, particularly following key climate milestones such as COP 21 in 2015 and COP 26 in 2021. This suggests that NGOs are strategically responding to significant political events within the climate arena. Moreover, the upward trend in climate-related activism aligns with the growing prominence of public regulation aimed at mitigating climate change, as shown in Figure 1. The dynamics of public regulation and private activism appear closely intertwined, with both intensifying in parallel over the past two decades.

To further illustrate the geographical dimension of climate civil society activism, Figure A1 and Figure A2 in appendix plot the cross-country distribution of climate-related active NGOs and campaigns over our sample period. These maps highlight both the concentration of campaigns in advanced economies—where NGOs are more numerous and resources for monitoring are greater—and the presence of significant activity in emerging and developing countries, particularly in Latin America and parts of Asia.<fnref n="13" /> This variation reveals important heterogeneity in the intensity of NGO engagement across countries. Importantly, our identification strategy will exploit within-country

<footnote n="13">¹³Although our sample does not cover all countries—particularly in regions where organized NGO activity is limited—the absence of observations should not be interpreted as non-random attrition. The *Sigwatch* database is explicitly designed to provide exhaustive coverage of NGO campaigns against firms, drawing directly from NGO publications and reports. Its primary objective is to inform firms about current and emerging reputational risks, which requires systematic and comprehensive monitoring of NGO activity worldwide. The resulting dataset therefore reflects the actual global distribution of NGO climate campaigns against firms, rather than selective recording.</footnote>
temporal variation in the timing of regulation, while accounting for cross-country differences in levels of activism. However, such geographic variation is informative for understanding the broader landscape of NGO activism and will be further exploited in our heterogeneity analysis aimed at exploring mechanisms.

## 3.2 Climate public regulation

To capture the presence and activity of regulators in the climate space, we rely on the *Climate Change Laws of the World* database. This dataset, compiled by the Grantham Research Institute at LSE provides a comprehensive record of national-level climate change mitigation regulations.<fnref n="14" /> Specifically, they document both legislative and executive policy instruments, offering insights into the legal frameworks and regulatory actions adopted by over 200 countries.<fnref n="15" />

To account for regulatory activity, we construct a binary variable that takes the value of one if at least one public regulatory instrument—as a publicly-driven mechanism targeting climate change mitigation—is enacted or revised by a government or a president (i.e. *executive* regulation) in a given country-month, and zero otherwise. This choice is driven by both conceptual and empirical considerations. As discussed in section 4, our empirical strategy centers on estimating the discrete behavioral response of NGOs to the occurrence of regulatory activity, rather than its intensity. This aligns with the episodic and strategic nature of NGO campaigns: what likely matters for NGOs is whether a policy window opens through a publicly-led regulatory move, not how many separate public regulatory instruments accompany it. Moreover, using a binary variable mitigates concerns over measurement error stemming from cross-country differences in how public regulatory instruments are classified, drafted, or reported. Importantly, descriptive statistics reported in Table 1 show that the average number of climate mitigation public regulatory instruments per country-month is well below one. This low frequency supports the use of a binary specification, as it captures meaningful variation without relying on sparse count data.

To illustrate cross-country variation in regulatory activity, Figure A3 and Figure A4 in appendix map the geographical distribution of climate public regulation over our sample period. These figures highlight the heterogeneity in regulatory intensity across regions, with higher concentrations

<footnote n="14">¹⁴See https://climate-laws.org/ (last accessed on September 22, 2025).</footnote>

<footnote n="15">¹⁵We exclude the United States from our analysis due to a known limitation of the regulation database, which primarily captures legislation at the national level. As many key environmental regulations in the U.S. are enacted at the state level and are not systematically recorded in our data, we are unable to reliably observe regulatory activity for this country.</footnote>
in advanced economies and emerging evidence of regulatory activity in middle-income countries. While these descriptive patterns are not the basis of our identification strategy—which relies on within-country temporal variation in the timing of executive regulation—they provide important context for understanding the global regulatory landscape in which NGOs operate. Furthermore, they highlight an additional source of heterogeneity that will be exploited in our exploration of mechanisms.

## 3.3 Additional country-level data sources

To account for time-varying country-level factors that may influence NGO campaign activity, we incorporate a set of control variables derived from external data sources. First, to capture a country's institutional capacity to enforce regulation, we include the Rule of Law indicator, sourced from the Worldwide Governance Indicators (WGI).<fnref n="16" /> This variable is available at an annual frequency and reflects perceptions of the extent to which agents have confidence in and abide by the rules of society, including the quality of contract enforcement and the functioning of the legal system.<fnref n="17" /> Second, we control for macroeconomic conditions using GDP per capita (in PPP current international USD), obtained annually from the World Bank.<fnref n="18" /> Economic development may influence both the salience of climate issues and the resources available to civil society organizations. We control for the strength of online media using an index from V-Dem that captures the availability and consumption of digital communication channels.<fnref n="19" /> This variable helps account for differences in the information environment that may shape both NGO mobilization and the visibility of climate regulation. Finally, we control climate short-term interest of the population we rely on the search term “Climate Change” across different using API of google trend.<fnref n="20" />

In addition to these baseline controls, we exploit data on climate-related natural disasters, technological disasters and COP events for further our robustness checks and exploration of mechanisms. We use data from EM-DAT (The International Disaster Database) to construct monthly measures

<footnote n="16">¹⁶See https://data.worldbank.org/indicator/ (last accessed on September 22, 2025).</footnote>

<footnote n="17">¹⁷Following Eskander and Fankhauser (2020), we transform the original variable into a relative ranking index, defined as: $\frac{rol_{ct}-rol^{min}}{rol^{max}-rol^{min}}$, where $rol_{ct}$ represents the value of the variable for a specific country $c$ at time $t$, and $rol^{min}$ and $rol^{max}$ denote the minimum and maximum values of the variable across all countries and years in the sample, respectively.</footnote>

<footnote n="18">¹⁸See https://data.worldbank.org/indicator/ (last accessed on September 22, 2025).</footnote>

<footnote n="19">¹⁹See https://www.V-Dem.net/ (last accessed on September 22, 2025). We use the variable v2smonex that we recode as follows: $\frac{v2smonex_{ct}-v2smonex^{min}}{v2smonex^{max}-v2smonex^{min}}$.</footnote>

<footnote n="20">²⁰The search term “Climate Change” (in English) aggregates all closely related variants of this expression across the dataset. Using the English term yields higher precision and recall scores in text retrieval compared to equivalent queries translated into the local languages of the countries included in the study.</footnote>
of climatological and selected meteorological events that are plausibly linked to climate change.<fnref n="21" />
Specifically, we focus on droughts, storms, floods, heat waves, and wildfires. For each country-month, we generate both a binary indicator for the occurrence of at least one disaster. Descriptive statistics for the disaster data are summarized in Table 1. On average, climate-related disasters are rare, occurring in only about 16% of country-months. We also construct a binary indicator for the occurrence of technological disasters (defined by EM-DAT as industrial, transport, and miscellaneous accidents). These events are even rarer, occurring in only about 11% of country-months on average.

Additionally, we hand-collected data on the countries hosting the Conference of the Parties (COP) climate negotiations, which are key milestones in international climate governance. Using online sources, we compiled a list of the host countries and years for each COP meeting. This variable helps capture the political significance of these events, which often catalyze heightened international attention and can trigger an uptick in climate-related NGO activity. We treat the occurrence of a COP meeting in a given country-year as an important regulatory or political event that may influence NGO mobilization, serving as a potential policy window for climate-related campaigns.<fnref n="22" />

# 4 Empirical Strategy

## 4.1 Identification Strategy

Our goal is to estimate the causal effect of public climate regulation on NGOs' climate-related activism against firms. A central challenge in this setting is that regulation and activism may be jointly determined: governments may regulate more when environmental issues are salient, or in response to pressure by civil society organizations, while NGOs may mobilize strategically as countries shift their climate policy stance. Establishing causality therefore requires isolating regulatory variation that is plausibly orthogonal to short-run changes in NGO campaigning.

To address this challenge, we focus on executive climate regulations, defined as mitigation-related decrees, administrative decisions, or policy instruments adopted directly by governments, presidents, or relevant ministries. Unlike legislation, which proceeds through highly public and

<footnote n="21">²¹See https://www.emdat.be/ (last accessed on September 22, 2025).</footnote>

<footnote n="22">²²More specifically, we construct a binary variable that equals one if a country either hosted a COP or shares a border with a COP-hosting country within the past two years. This approach captures both the geographic diffusion and temporal persistence of climate change regulation, as emphasized by Fankhauser, Gennaioli, and Collins (2016).</footnote>
<table><caption>Table 1: Summary statistics of main variables (NGO-month level, 2010–2023)</caption><thead><tr><th></th><th>Observations</th><th>Mean</th><th>Standard deviation</th><th>Min</th><th>Max</th></tr></thead><tbody><tr><td><strong>NGO climate activism</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Climate campaigns (Yes/No)</td><td>101880</td><td>0.06</td><td>0.25</td><td>0</td><td>1</td></tr><tr><td>Number of climate campaigns</td><td>101880</td><td>0.08</td><td>0.35</td><td>0</td><td>12</td></tr><tr><td>Share of climate campaigns</td><td>101880</td><td>0.05</td><td>0.22</td><td>0</td><td>1</td></tr><tr><td><strong>Public climate regulation</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Public Regulation</td><td>101880</td><td>0.19</td><td>0.39</td><td>0</td><td>1</td></tr><tr><td><strong>Country-year variables</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GDP per capita</td><td>869</td><td>24594</td><td>25465</td><td>441</td><td>134966</td></tr><tr><td>Rule of law</td><td>869</td><td>0.64</td><td>0.21</td><td>0.29</td><td>1.00</td></tr><tr><td>Online media</td><td>869</td><td>0.65</td><td>0.17</td><td>0.25</td><td>0.96</td></tr><tr><td>COP</td><td>869</td><td>0.14</td><td>0.35</td><td>0</td><td>1</td></tr><tr><td><strong>Country-month variables</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Google Trend Climate Change</td><td>10423</td><td>11.40</td><td>11.86</td><td>0</td><td>100</td></tr><tr><td>Climate disasters</td><td>10423</td><td>0.16</td><td>0.37</td><td>0</td><td>1</td></tr><tr><td>Technological disasters</td><td>10423</td><td>0.11</td><td>0.31</td><td>0</td><td>1</td></tr></tbody></table>

*Notes:* This table provides summary statistics for variables used for analysis. The unit of observation is an NGO-month. “Climate campaigns (Yes/No)” and “Public Regulation” are binary indicators. The “Share of climate campaigns” corresponds to the fraction of all campaigns by a given NGO in a month that relate to climate issues. “GDP per capita” is measured in PPP current international USD. “Rule of law” is an index from the Worldwide Governance Indicators, transformed to range from 0 to 1. Google Trend Climate Change is an index (0–100) measuring public search interest in climate change, with 100 representing peak interest over the period studied. Disaster variables are binary indicators for the occurrence of climate-related or technological disasters in the NGO’s country during the given month. “COP” is a binary indicator indicating whether the NGO’s country hosted a COP event within the past two years or shares a border with a country that hosted one.

procedurally structured parliamentary processes, executive regulations are enacted through opaque bureaucratic channels without fixed deliberation calendars (Djourelova & Durante, 2022; Kennedy, 2015; Smirnova et al., 2021). By contrast, legislative regulation involves prolonged debates and public schedules that may attract preemptive NGO pressure, challenging the exogeneity of timing. Recent studies in political sciences (Djourelova & Durante, 2022; Smirnova et al., 2021) further highlight that executive orders may arise when executive and legislative preferences diverge, suggesting that unilateral regulatory action need not reflect contemporaneous public sentiment or majoritarian approval.<fnref n="23" /> We later corroborate this institutional argument by showing, through event-study

<footnote n="23">²³Djourelova and Durante (2022) also document strategic daily timing of executive orders relative to predictable news congestion. This micro-timing relates to the publicity environment surrounding announcements rather than to the underlying policy decision and does not operate at the monthly frequency used in our analysis. At this level of</footnote>
estimates, that NGO activism exhibits no pre-trend prior to regulatory adoption, providing direct evidence against short-run reverse causality. Taken together, these insights support the view that short-run fluctuations in public climate concern or NGO mobilization are unlikely to determine the precise month in which executive climate regulations are finalized.

In our empirical setting, we do not assume that executive climate regulations are exogenous in a broad political sense. Rather, our identifying assumption concerns a narrower and more empirically grounded dimension of regulatory behavior: the month-level timing of executive enactments. We exploit the fact that executive climate regulations across our sample are adopted through administrative procedures whose precise month of issuance is shaped by internal bureaucratic sequencing, inter-agency coordination, and executive prioritization, rather than by short-run fluctuations in NGO campaigning. Our design therefore, requires that regulatory timing be orthogonal to within-month changes in NGO activism, not that governments are uninfluenced by societal preferences in general. This distinction is crucial: while the decision to regulate may reflect long-run political pressures or policy agendas, the exact month in which an executive regulation is finalized and published is plausibly unrelated to the high-frequency dynamics of NGO-firm interactions that we study.

A further concern is reverse causality: governments might adopt executive regulations in response to contemporaneous NGO pressure. This scenario is unlikely in our setting. Executive rule-making involves preparatory drafting, legal vetting, and inter-ministerial coordination, processes that unfold over timelines substantially longer than the monthly frequency of our data, making near-immediate responsiveness to NGO campaigns implausible. Moreover, the private-politics literature emphasizes that NGOs direct their efforts primarily toward corporations, seeking to shape firm behavior through reputational pressure, rather than toward governments or administrative agencies (Baron, 2001; Baron & Diermeier, 2007; Egorov & Harstad, 2017).

To address remaining concerns about omitted-variable bias, we include several proxies for public preferences and attention to climate issues into the empirical specification. Google Trends searches for “climate change” capture high-frequency shifts in public interest and information demand. Indicators for climate-related natural disasters account for exogenous increases in perceived environmental risk. In contrast, technological disasters - industrial or transport accidents - generate salient but non-climate-related shocks, allowing us to use them as a falsification test: if our estimates re-

<footnote>aggregation, such micro-timing introduces at most measurement noise rather than systematic correlation with NGO activism.</footnote>
flected broad salience cycles rather than climate-specific mechanisms, technological disasters would predict similar movements in NGO activism.

Our empirical design also leverages rich fixed effects to purge potential confounders. NGO fixed effects absorb time-invariant differences in activist intensity and organizational mission; country fixed effects capture structural heterogeneity in governance, regulatory capacity, and economic conditions; and month-year fixed effects soak up global shifts in climate attention, international news cycles, and worldwide activism trends. Together with time-varying controls, these design choices substantially restrict the scope for unobserved shocks to jointly influence regulation and NGO campaigning.

Finally, we conduct two placebo exercises that assess whether any unobserved factor could generate systematic co-movement between regulation and activism. The first examines international campaigns - activism directed at foreign rather than domestic firms - which should not respond to domestic regulatory changes. The second focuses on non-climate campaigns, which would react only if regulation induced a generalized increase in activism rather than a climate-specific response. If a broad attention shock or unobserved societal trend were driving our results, we would expect to observe spillovers into these domains.

We exploit the monthly panel structure of NGO activity and the staggered timing of executive climate regulations across countries. Our baseline specification estimates:

$$ \textit{Climate Reports}_{ict} = \beta \textit{Public Regulation}_{ct} + \mathbf{X}'_{ct}\lambda + \gamma_i + \mu_c + \tau_t + \epsilon_{ict} \quad (1) $$

where: (i) Climate Reports$_{ict}$ captures whether NGO i published at least one climate-related campaign in country c and month t; (ii) Public Regulation$_{ct}$ is a binary indicator equal to 1 if at least one executive climate mitigation regulation was enacted in that country-month; (iii) X$_{ct}$ includes time-varying controls for institutional capacity (rule of law), macroeconomic conditions (GDP per capita), media environment (online media index), and public interest (Google Trends for “climate change”); (iv) $\gamma_i$, $\mu_c$ and $\tau_t$ are NGO, country, and month-year fixed effects.

Our identification requires that, conditional on fixed effects and controls, the precise month of executive regulation adoption is not driven by short-term changes in NGO activism against firms.

Identification comes from within-NGO changes in activism across countries that either experience or do not experience an executive regulatory shock in a given month. The specification conditions on time-invariant NGO characteristics, structural cross-country differences, and global
month-year shocks through NGO, country, and month-year fixed effects. Under this design, the coefficient $\beta$ captures how NGO activism responds to executive regulation, conditional on monthly country-level measures of climate attention, annual country controls, and the full set of fixed effects.

To assess the validity of our identifying assumption, we exploit the monthly granularity of our data through an event-study specification.<fnref n="24" /> This design leverages high-frequency event-time variation around the enactment of executive climate regulations, allowing us to examine the dynamic response of NGOs while directly testing for the absence of pre-trends.<fnref n="25" /> We estimate

$$ \textit{Climate Reports}_{ict} = \sum_{k=-K}^{K} \beta_k \textit{Public Regulation}_{c,t-k} + \mathbf{X}'_{ct}\lambda + \gamma_i + \mu_c + \tau_t + \epsilon_{ict} \quad (2) $$

where $k$ indexes months relative to the regulatory enactment. The coefficients $\beta_k$ trace the evolution of NGO activity before and after the policy change. A flat pre-treatment trajectory provides evidence consistent with the parallel-trends requirement of our identification strategy. The post-treatment dynamics, in turn, reveal both the magnitude and timing of the regulatory effect.

The pattern of $\beta_k$ in the post-adoption period also offers insight into the mechanisms at play. If the effect operated primarily through short-lived visibility or salience shocks - where regulation temporarily draws attention to climate issues - we would expect a sharp but transitory spike in activism. Conversely, a more persistent increase would be consistent with regulation altering NGOs' campaign incentives by affecting the expected benefits or costs of mobilization, as suggested by our conceptual framework. Examining these dynamic responses therefore strengthens the causal interpretation of our estimates and provides suggestive evidence on the channels through which regulation influences NGO behavior.<fnref n="26" />

# 5 Results

## 5.1 Dynamic responses to public regulation

To examine the timing and persistence of NGO responses to climate public regulation, we implement an event-study framework (see Equation 2) that traces changes in NGO campaign behavior

<footnote n="24">²⁴Each regulation defines an independent event window. In cases of overlapping treatment periods, observations affected by concurrent regulations are assigned missing values to prevent contamination of the estimated dynamic effects, and the event window resumes post-overlap.</footnote>

<footnote n="25">²⁵Because executive regulations are recurrent and non-absorbing, a standard staggered DiD framework with a single adoption date per country is inappropriate and risks comparison across partially treated cohorts. The event-study design avoids these pitfalls and focuses directly on dynamic responses.</footnote>

<footnote n="26">²⁶We formally examine mechanisms in section 6.</footnote>
relative to the month of regulatory enactment. This approach allows us to test for the presence of anticipatory behavior, assess the persistence of regulatory effects, and explore whether the intensity of the response evolves over time.

Figure 3 plots estimated coefficients from an event-time specification, where the omitted category is the month immediately preceding regulation (month -1). The dependent variable is the same as in our baseline: a binary indicator for whether an NGO targets a firm with a climate-related campaign in a given month. All regressions include NGO, country, and month-year fixed effects, along with country-year controls.

The dynamic estimates reveal several key insights. First, the coefficients for the pre-regulation period (months -6 and earlier to -1) are close to zero and statistically insignificant. This absence of pre-trends supports our identification strategy and suggests that NGO climate activism against firms does not systematically anticipate upcoming regulation.

Second, starting in the month of regulation (month 0), we observe a clear and increasing effect on the probability of climate-related NGO campaigns. The estimated effect rises from approximately 0.007 in the month of enactment to roughly 0.014 in month +1 and peaks close to 0.026 by month +6 and later. Relative to the sample mean of 0.064, this corresponds to a roughly 11% increase in the first month and a 41% increase six months after regulation. This upward trajectory indicates that regulation does not merely trigger a short-lived response but generates a persistent—and intensifying—shift in NGO activity.<fnref n="27" /> Importantly, we find highly similar dynamics when repeating the event-study at the country-month level: the aggregate intensity of climate-related campaigns likewise rises persistently after regulation, confirming that the effect holds both at the micro level of NGOs and at the aggregate level of civil society mobilization (see Figure B3 in appendix).

This dynamic pattern is consistent with the mechanisms highlighted in our conceptual framework. By establishing clear benchmarks and increasing the expected payoff of activism, regulation provides NGOs with enduring tools and incentives to engage. The amplification of activism over time likely reflects both the reduced costs of campaigning — as regulation lowers reputational risks — and the increased benefits from leveraging new institutional and informational standards.<fnref n="28" />

These results show that climate public regulation induces a sustained and growing shift in NGO

<footnote n="27">²⁷Qualitatively similar results using the count and share of climate-related campaigns as dependent variables are shown in Figure B1 and Figure B2 in the appendix.</footnote>

<footnote n="28">²⁸In section *section 6*, we examine these mechanisms more directly by exploring heterogeneity across NGO characteristics and institutional environments, thereby identifying the conditions under which regulation most effectively mobilizes civil society.</footnote>
behavior—one that cannot be explained by trends, anticipation, or general activism.

<figure><img src="image_5.png" /><figcaption>Figure 3: Climate Public Regulation and NGO activism against Firms</figcaption></figure>

*Notes:* This figure plots the estimates $\beta_k$ and 95% confidence intervals (robust to two-way clustering at the NGO and country × month levels) from event-study specification Equation 2, exploring the dynamic effects of climate public regulation on NGO activism against firms. The unit of observation is an NGO-month. The outcome variable is a binary indicator for whether an NGO launched at least one climate-related campaign in a given country-month. The x-axis denotes the number of months relative to the introduction of a public climate regulation ($t = 0$). The omitted reference period is $t = -1$. The specification includes NGO, country and month-year fixed effects, as well as baseline country-year controls: GDP per capita, an index of the rule of law as well as an index of the presence of online media, and the country-month variation in Google Trends for “Climate Change”.

## 5.2 Public regulation and NGOs climate campaigns against firms

**Main findings.** Table 2 presents our main estimates of the effect of public climate change mitigation regulation on NGO climate campaign behavior toward firms. This analysis directly tests Prediction 1 from our conceptual framework, which posits that public regulation—by increasing either the salience or enforceability of climate concerns—should raise the likelihood that firms are targeted by NGO activism. The unit of observation is NGO-month, and the outcome variables
capture different dimensions of climate-related activism: whether an NGO targets a firm with a climate-related campaign (columns 1–2), the number of such campaigns (columns 3–4), and the share of NGO campaigns against firms that are climate-related (columns 5–6).

Across all specifications, we find that the introduction of climate public regulation leads to a statistically and economically meaningful increase in climate-related NGO activity. Columns (1) and (2) examine the extensive margin, where the dependent variable is a binary indicator equal to one if an NGO initiates a climate-related campaign against a firm in a given month. The coefficient on climate public regulation is 0.009, statistically significant at the 1% level. Given a mean incidence rate of 6.4%, this corresponds to a roughly 14% increase in the probability of NGO-firm climate campaigning following regulatory action. The estimated effect remains stable when we include country-year controls in column (2), suggesting that the result is not confounded by contemporaneous national trends in governance, economic development or media landscape.

Columns (3) and (4) shift to the intensive margin, using the number of climate-related campaigns as the dependent variable. Again, we find that climate public regulation significantly increases NGO activity: the coefficient is 0.016 (significant at the 1% level), with similar magnitudes in both baseline and country-year controlled specifications.<fnref n="29" /> These findings indicate that NGOs respond to public regulation not only by expanding their coverage to new firms but also by intensifying their scrutiny of previously monitored targets.

Finally, columns (5) and (6) examine whether regulation affects the focus of NGO campaigns by measuring the share of total firm-level NGO campaigns that are climate-related. The estimated coefficient on Public Regulation is 0.008, again significant at the 1% level in our preferred specification. This suggests that regulation induces NGOs to reallocate their efforts toward climate-specific issues, even when overall activism remains constant. Column (6) includes country-year controls, and the estimated effect is stable, further reinforcing the robustness of the result.

All specifications include NGO fixed effects, month-year fixed effects, and country fixed effects, with additional country-year controls in columns (2), (4), and (6). Identification is therefore based on within-NGO, within-country, within-month variation, netting out unobserved temporal and geographic heterogeneity. The estimates indicate that executive climate regulation increases the probability that firms are targeted by NGOs, raises the intensity of this targeting, and shifts a greater share of campaigns toward climate-related issues. Taken together, these findings suggest that public regulation shapes not only firm behavior through direct compliance channels, but also

<footnote n="29">²⁹Qualitatively similar results using PPML estimations are reported in appendix Table B1.</footnote>
the broader ecosystem of climate accountability. By mobilizing civil society watchdogs, regulation
induces a reallocation of activist attention and resources toward environmental monitoring and
reputational pressure. In this way, NGOs serve as responsive actors in the broader institutional
landscape of climate governance, reinforcing the reach of formal policy through informal channels.

For the remainder of the paper we focus on the extensive margin—the binary indicator of whether
an NGO targets a firm with a climate-related campaign. The choice is motivated by both theoret-
ical and empirical considerations. First, given the monthly granularity of our data, the extensive
margin captures the most immediate and discrete response of NGOs to public regulation. Second,
as shown in the previous section, our findings are highly consistent across alternative outcome mea-
sures (extensive, intensive, and compositional), with similar effect sizes relative to the respective
means.<fnref n="30" /> Focusing on the extensive margin therefore simplifies interpretation without sacrificing
generality.

**Country-month aggregation: evidence of collective mobilization.** To complement our NGO-level analysis, we aggregate the data to the country-month level, weighting observations by the number of NGOs observed in each country-month (Table 3). This exercise shifts the focus from individual organizations to the collective mobilization of civil society in response to public regulation.

The results show that public climate regulation is associated with stronger aggregate NGO activism against firms. In particular, regulation significantly increases both the number and the share of climate-related campaigns within a country-month (columns 3–6). While the effect on the likelihood of observing any campaign is less precisely estimated (columns 1–2), the overall pattern indicates that regulatory action leads to more intense and more climate-focused NGO activity.

Taken together, these results highlight that regulation not only shapes the behavior of individual
NGOs but also amplifies the aggregate intensity of climate-related civil society pressure at the
country level. In practice, when governments act, NGOs already active in climate issues expand
their campaigns, generating a stronger collective accountability signal toward firms. This aggregate
evidence reinforces our baseline findings and underscores the role of regulation in catalyzing broader
societal oversight.

<footnote n="30"><sup>30</sup>The consistency of the results aligns with the descriptive statistics in section 3: both the number and share of climate-related NGO campaigns exhibit highly binary distributions in our sample. As a result, these outcomes are strongly correlated with the extensive margin (i.e., the climate campaign indicator). We nevertheless report in appendix tables and figures exploring the intensive margin. They are qualitatively similar throughout.</footnote>
<table><caption>Table 2: Climate Public Regulation and NGO climate activism against Firms</caption><thead><tr><th rowspan="3">Dependent variable</th><th colspan="6">Climate campaigns</th></tr><tr><th colspan="2">Yes/No</th><th colspan="2">Number</th><th colspan="2">Share</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.009***<br>(0.003)</td><td>0.009***<br>(0.003)</td><td>0.016***<br>(0.005)</td><td>0.016***<br>(0.005)</td><td>0.008**<br>(0.003)</td><td>0.008**<br>(0.003)</td></tr><tr><td>GDP per capita</td><td></td><td>-0.000<br>(0.000)</td><td></td><td>0.000<br>(0.000)</td><td></td><td>-0.000<br>(0.000)</td></tr><tr><td>Rule of law</td><td></td><td>-0.026<br>(0.111)</td><td></td><td>-0.025<br>(0.183)</td><td></td><td>-0.007<br>(0.092)</td></tr><tr><td>Online media</td><td></td><td>0.043<br>(0.037)</td><td></td><td>0.110*<br>(0.064)</td><td></td><td>0.040<br>(0.031)</td></tr><tr><td>Google Trend Climate Change</td><td></td><td>0.000<br>(0.000)</td><td></td><td>0.000<br>(0.000)</td><td></td><td>0.000<br>(0.000)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>101880</td><td>101880</td><td>101880</td><td>101880</td><td>101880</td><td>101880</td></tr><tr><td>Mean dep. var.</td><td>0.064</td><td>0.064</td><td>0.080</td><td>0.080</td><td>0.054</td><td>0.054</td></tr><tr><td>R<sup>2</sup></td><td>0.161</td><td>0.161</td><td>0.222</td><td>0.222</td><td>0.128</td><td>0.128</td></tr></tbody></table>

*Notes*: This table presents OLS estimates of the effect of public climate regulation on various measures of NGO climate activism against firms. The unit of observation is an NGO-month. The dependent variables are, respectively, a binary indicator for whether at least one climate-related report was issued (columns 1–2), the number of climate-related reports (columns 3–4), and the share of climate-related reports among all reports (columns 5–6) in a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Columns (2), (4), and (6) additionally include country-year controls: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.

## 5.3 Robustness

We now turn to potential threats to our identification strategy, assessing whether the effect of public climate regulation on NGO activism could be confounded by alternative sources of endogeneity. Specifically, we address: (i) pre-existing trends in NGO activism, (ii) potential timing or measurement error in the coding of regulatory events, (iii) coinciding global climate governance milestones such as COP summits, and (iv) salience shocks that might independently raise climate visibility. In addition, we conduct two placebo exercises—(v) analyzing international campaigns and (vi) focusing on NGOs that never engage in climate activism—to verify that our results are not simply
<table><caption>Table 3: Climate Public Regulation and NGO activism against Firms - Country-month analysis</caption><thead><tr><th rowspan="3">Dependent variable</th><th colspan="6">Climate campaigns</th></tr><tr><th colspan="2">Yes/No</th><th colspan="2">Number</th><th colspan="2">Share</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.014<br>(0.016)</td><td>0.014<br>(0.016)</td><td>1.205***<br>(0.240)</td><td>1.117***<br>(0.226)</td><td>0.022**<br>(0.009)</td><td>0.022**<br>(0.010)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td></td><td>✓</td><td></td><td>✓</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>10423</td><td>10423</td><td>10423</td><td>10423</td><td>10423</td><td>10423</td></tr><tr><td>Mean dep. var.</td><td>0.213</td><td>0.213</td><td>0.784</td><td>0.784</td><td>0.107</td><td>0.107</td></tr><tr><td>R<sup>2</sup></td><td>0.491</td><td>0.492</td><td>0.588</td><td>0.610</td><td>0.295</td><td>0.296</td></tr></tbody></table>

Notes: This table presents estimates of the effect of public climate regulation on country-month level NGO activism against firms. The unit of observation is a country-month. Observations are weighted by the number of NGOs observed per country-month. The dependent variables are, respectively, a binary indicator for whether at least one climate-related report was issued (columns 1–2), the number of climate-related reports (columns 3–4), and the share of climate-related reports among all reports (columns 5–6) in a given country-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are clustered at the country level and reported in parentheses.

*** p<0.01, ** p<0.05, * p<0.10.

capturing systematic or global shifts in civil society mobilization. Together, these tests strengthen the causal interpretation of our findings by ruling out alternative explanations and showing that the effects we uncover are specific to climate-related NGO activism in domestic contexts.

**Pre-trends in NGO activism.** A key identification concern is that changes in NGO behavior might precede regulation, reflecting endogenous trends in activism or informal anticipation. To address this, columns (1) and (2) of Table 4 include one- and two-month lags of the dependent variable as controls. These lagged outcomes are strong predictors of current campaign activity, consistent with the persistence of NGO behavior. Crucially, however, the coefficient on climate public regulation remains positive (0.009) and statistically significant, suggesting that the estimated effect is not driven by underlying momentum or pre-existing trends in NGO activism.<fnref n="31" />

<footnote n="31">³¹Qualitatively similar results using the count and share of climate-related campaigns as dependent variables are</footnote>
**Timing and measurement error.** Columns (3) and (4) of Table 4 test the sensitivity of our results to alternative codings of the timing of public regulation by using one- and two-month lags of the regulation variable. The estimated effects remain statistically significant and of similar magnitude to our baseline estimates, suggesting that our results are not driven by transitory measurement error or misalignment between the recorded date of regulation and the actual timing of NGO response. Notably, the coefficients on lagged regulation are also statistically significant, suggesting that the impact of regulation on NGO activism unfolds dynamically.<fnref n="32" /> We examine this dynamic pattern more formally in an event-study analysis in the next subsection.

**Global climate governance events.** While our main specification includes a rich set of fixed effects—including month-year fixed effects that account for global temporal shocks, and country fixed effects that absorb time-invariant national characteristics—we further test the robustness of our results to time-varying, country-specific exposure to global climate diplomacy. In particular, we examine the influence of the United Nations Framework Convention on Climate Change (UNFCCC) Conferences of the Parties (COPs), which serve as focal points for international climate negotiations and often generate global media attention, civil society mobilization, and domestic policy responses.

These events could represent potential confounders if, for example, hosting or being geographically proximate to a COP increases both the likelihood of adopting climate regulation and the intensity of NGO mobilization. To address this concern, we construct a binary variable equal to one if a country hosted, or shared a border with a country that hosted, a COP summit within the previous two years. This flexible specification allows us to account for both spatial diffusion and temporal persistence in the influence of global climate events (Fankhauser et al., 2016).

We add this control in columns (5) and (6) of Table 4.<fnref n="33" /> Importantly, in column (6)—our most saturated model that includes lagged values of climate campaigns and regulation, as well as the COP proximity control—the estimated effect of current public regulation on NGO climate campaigns remains positive, statistically significant, and almost unchanged in magnitude (0.008).

<footnote>reported in appendix Table B2 and Table B3, respectively.</footnote>

<footnote n="32">³²Qualitatively similar results using the count and share of climate-related campaigns as dependent variables are reported in appendix Table B2 and Table B3, respectively.</footnote>

<footnote n="33">³³We refrain from including the COP proximity variable in our baseline specification due to concerns about “bad controls”—that is, variables that may themselves be affected by the treatment or that could absorb part of the regulatory pathway through which NGOs respond. In other words, since COP events can influence national regulation, conditioning on them may introduce post-treatment bias. We therefore use this control only in robustness checks to demonstrate that our main result is not spurious or confounded by global events.</footnote>
This stability suggests that our key result is not driven by unobserved regional shocks associated with COPs or other omitted variables related to international climate momentum.

Interestingly, the coefficient on the COP proximity variable itself is positive and statistically significant (0.008-0.009, significant at 5%), indicating that countries exposed to a recent COP summit—either by hosting or geographic proximity—experience an increase in climate-related NGO campaigns. This aligns with existing evidence that global summits can shape domestic discourse and civil society behavior (Fankhauser et al., 2016). Quantitatively, the COP effect is non-trivial: it is comparable in size to the regulation coefficient and suggests that COP events can serve as catalysts for activism even outside the direct regulatory process. Taken together, these findings from column (6) strongly support the robustness and substantive importance of our main result: public regulation acts as a meaningful trigger for NGO climate campaigns, even when accounting for global events, regulatory dynamics, and time-varying domestic shocks.<fnref n="34" />

**Climate preferences.** A remaining concern is that our baseline estimates might capture additional omitted factors that simultaneously affect both the adoption of regulation and NGO activism. In particular, the *climate preferences*, shaped by exogenous shocks or by the media environment, could drive both variables. If so, our results could reflect correlated attention dynamics rather than a causal effect of regulation. It is important to notice that NGOs and public regulators operate on distinct temporal scales: NGOs can rapidly adjust to short-term climate preference shocks, while public regulation follows a longer-term process. Our baseline specification already accounts for the broader media landscape, using V-DEM data on the presence and consumption of online media and public interest relying on Google trends. This ensures that our results are not confounded by differences in media penetration, or public attention which could systematically affect the visibility of environmental issues and the responsiveness of NGOs and governments. In addition, we explicitly control for two types of preference shocks in Table 5. First, climate-related natural disasters (e.g., floods, droughts, storms) plausibly increase public concern for climate action. Second, technological disasters (e.g., industrial accidents), while similarly disruptive, are less directly linked to climate narratives and, therefore, provide a useful placebo. The results show that NGOs respond to climate disasters but not to technological disasters, consistent with previous work on selective response to climate preferences (Araujo, Costa, & Garg, 2024; Couttenier & Hatte, 2016; Dai, Kesternich,

<footnote n="34">³⁴Qualitatively similar results using the count and share of climate-related campaigns as dependent variables are reported in appendix Table B2 and Table B3, respectively.</footnote>
<table><caption>Table 4: Climate Public Regulation and NGO activism against Firms - Robustness checks</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="6">Climate campaigns (Yes/No)</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.008***<br>(0.003)</td><td>0.009***<br>(0.003)</td><td>0.008**<br>(0.003)</td><td>0.008**<br>(0.003)</td><td>0.008**<br>(0.003)</td><td>0.008**<br>(0.003)</td></tr><tr><td>Climate reports (Yes/No)<sub>t-1</sub></td><td>0.070***<br>(0.010)</td><td>0.066***<br>(0.009)</td><td></td><td></td><td></td><td>0.066***<br>(0.009)</td></tr><tr><td>Climate reports (Yes/No)<sub>t-2</sub></td><td></td><td>0.057***<br>(0.009)</td><td></td><td></td><td></td><td>0.057***<br>(0.009)</td></tr><tr><td>Public Regulation<sub>t-1</sub></td><td></td><td></td><td>0.007**<br>(0.003)</td><td>0.007**<br>(0.003)</td><td></td><td>0.007**<br>(0.003)</td></tr><tr><td>Public Regulation<sub>t-2</sub></td><td></td><td></td><td></td><td>0.006*<br>(0.003)</td><td></td><td>0.005<br>(0.003)</td></tr><tr><td>COP</td><td></td><td></td><td></td><td></td><td>0.009**<br>(0.004)</td><td>0.008**<br>(0.004)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>100640</td><td>99400</td><td>101880</td><td>101880</td><td>101880</td><td>99400</td></tr><tr><td>Mean dep. var.</td><td>0.065</td><td>0.065</td><td>0.064</td><td>0.064</td><td>0.064</td><td>0.065</td></tr><tr><td>R<sup>2</sup></td><td>0.167</td><td>0.172</td><td>0.161</td><td>0.161</td><td>0.161</td><td>0.172</td></tr></tbody></table>

*Notes:* This table presents robustness checks for the effect of public climate regulation on NGO activism against firms. The unit of observation is an NGO-month. The dependent variable is a binary indicator for whether at least one climate-related report was issued by a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. Specifications (1) and (2) control for lagged binary indicator of NGO climate campaigns (up to 2 months). Specifications (3) and (4) control for lagged public climate regulation (up to 2 months). Specification (5) controls for a binary variable indicating whether the NGO’s country hosted a COP event within the past two years or shares a border with a country that hosted one. Specification (6) includes all controls simultaneously. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.

Löschel, & Ziegler, 2015; Heyes et al., 2018; Hoffmann, Muttarak, Peisker, & Stanig, 2022; Shi, Visschers, Siegrist, & Arvai, 2016). Crucially, the coefficient on public regulation remains stable across all specifications.

Taken together, these results confirm that while NGOs are sensitive to preference shocks, the effect of public regulation is not explained by climate preference alone.

**Placebo: International NGO campaigns.** A key concern is that the observed effect of public
<table><caption>Table 5: The Influence of Climate Public Regulation and Climate Preferences on NGO activism against Firms</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="3">Climate campaigns (Yes/No)</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.009***<br>(0.003)</td><td>0.009***<br>(0.003)</td><td>0.009***<br>(0.003)</td></tr><tr><td>Climate disasters</td><td>0.006**<br>(0.003)</td><td>-0.001<br>(0.004)</td><td>0.006**<br>(0.004)</td></tr><tr><td>Technological disasters</td><td></td><td>-0.001<br>(0.004)</td><td>-0.001<br>(0.004)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>101880</td><td>101880</td><td>101880</td></tr><tr><td>Mean dep. var.</td><td>0.064</td><td>0.064</td><td>0.064</td></tr><tr><td>R<sup>2</sup></td><td>0.161</td><td>0.161</td><td>0.161</td></tr></tbody></table>

*Notes:* This table examines the impact of climate public regulation on NGO activism against firms, exploring the role of climate preferences factors such as climate and technological disasters. The unit of observation is an NGO-month. The dependent variable is a binary indicator for whether at least one climate-related report was issued by a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. “Climate disasters” and “Technological disasters” are binary indicators for the occurrence of climate-related and technological disasters in the NGO’s country during the given month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.

regulation on NGO activism could reflect coincidental global trends in civil society mobilization, rather than a causal response to national regulatory change. To probe this, we exploit heterogeneity between national campaigns—those in which NGOs target firms headquartered in their own country—and international campaigns, where NGOs target firms abroad. Following Hatte and Koenig (2020), this distinction captures the well-documented proximity bias in NGO activism.

If our estimates were driven by spurious correlation with global activism cycles, we should expect public regulation to predict both national and international campaigns. By contrast, if the effect
reflects domestic regulatory environments shaping NGO behavior, the effect should be concentrated in national campaigns only.

Table 6 confirms the latter. Public regulation significantly increases the likelihood and number of national campaigns (columns (1)–(2)), but has no measurable impact on international campaigns (columns (3)–(4)). The point estimates for international outcomes are close to zero and statistically insignificant. This sharp divergence underscores that NGOs respond specifically to domestic regulatory contexts rather than to global activism waves. Moreover, the baseline frequencies differ markedly: NGOs initiate national campaigns in 5.2% of months (mean count 0.062), compared to just 1.6% of months (mean count 0.018) for international campaigns.

We interpret this as a placebo validation exercise: the absence of effects on international campaigns strengthens the causal interpretation of our main findings, confirming that they are not mechanically driven by global shocks to NGO activity but by domestic regulatory signals.

<table><caption>Table 6: Climate Public Regulation and National vs. International NGO activism against Firms</caption><thead><tr><th rowspan="3">Dependent variable</th><th colspan="2">National campaigns</th><th colspan="2">International campaigns</th></tr><tr><th>Yes/No</th><th>Number</th><th>Yes/No</th><th>Number</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.008**<br>(0.003)</td><td>0.012***<br>(0.005)</td><td>0.002<br>(0.002)</td><td>0.003<br>(0.002)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>101880</td><td>101880</td><td>101880</td><td>101880</td></tr><tr><td>Mean dep. var.</td><td>0.052</td><td>0.062</td><td>0.016</td><td>0.018</td></tr><tr><td>R<sup>2</sup></td><td>0.139</td><td>0.178</td><td>0.112</td><td>0.144</td></tr></tbody></table>

*Notes*: This table presents estimates of the effect of public climate regulation on national and international NGO activism against firms. The unit of observation is an NGO-month. The dependent variables are binary indicators for national (columns (1) and (2)) and international (columns (3) and (4)) campaigns. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
**Placebo: non-climate NGO activism.** To further strengthen the causal interpretation of our findings, we conduct a placebo exercise using non-climate-related NGO campaigns as the dependent variable.<fnref n="35" /> If public climate regulation simply captures a broader shift in NGO activism or general policy salience—rather than a targeted response to climate policy—we would expect to observe similar effects on unrelated forms of NGO activity. Table 7 reports the results of this placebo test using both the extensive (column 1) and intensive (column 2) margins of non-climate NGO campaigns.<fnref n="36" /> In both cases, the coefficient on climate public regulation is close to null in magnitude and statistically insignificant. These null results suggest that the observed effects are not driven by generic increases in NGO activism or unobserved confounders affecting all types of campaigns. Instead, the effect of public climate regulation appears to be specific to climate-related activism, supporting a targeted behavioral response by NGOs to regulatory shifts in the climate domain.

# 6 Mechanisms

Our conceptual framework suggests that public regulation can actively shape NGO behavior by altering the incentives for activism. Two interrelated mechanisms are central. First, regulation creates clear institutional benchmarks that NGOs can use to monitor firms and hold them accountable, with particularly strong effects in contexts where formal enforcement is weak. Second, regulation changes the expected payoff of activism by increasing potential benefits and lowering associated costs. Together, these channels imply that regulation can mobilize civil society to strengthen oversight and sustain pressure on firms. In the following section, we test these predictions empirically, leveraging heterogeneity across countries and NGOs to uncover how and where these mechanisms operate.

## 6.1 Heterogeneity by Regulatory Environment

Prediction 2 posits that regulation should have the largest marginal effect where baseline enforcement is weak, as NGOs gain the most from newly created institutional levers. To test this prediction, we use a country-year level climate related regulatory stringency index compiled by the OECD in

<footnote n="35">³⁵For this placebo exercise, we restrict the analysis to NGOs that exclusively engage in non-climate-related campaigns (i.e. non-climate NGOs).</footnote>

<footnote n="36">³⁶Note that, by construction, the share of non-climate campaigns for NGOs that never engage in climate-related activism is equal to 100%. For this reason, we focus on the count of non-climate campaigns to assess intensive margin effects in the placebo analysis.</footnote>
<table><caption>Table 7: Climate Public Regulation and Non-Climate NGO activism against Firms</caption><thead><tr><th rowspan="3">Dependent variable</th><th colspan="2">Non-climate campaigns</th></tr><tr><th>Yes/No</th><th>Number</th></tr><tr><th>(1)</th><th>(2)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>-0.002<br>(0.003)</td><td>-0.003<br>(0.003)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>123849</td><td>123849</td></tr><tr><td>Mean dep. var.</td><td>0.083</td><td>0.092</td></tr><tr><td>R<sup>2</sup></td><td>0.075</td><td>0.102</td></tr></tbody></table>

Notes: This table reports the results of a placebo test, examining the effect of public climate regulation on non-climate NGO activism against firms. The unit of observation is an NGO-month. The dependent variables are binary indicators for non-climate campaigns (column (1)) or a count variable (column (2)). “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.

the Climate Actions and Policies Measurement Framework (CAPMF) (Nachtigall et al., 2024). We compute the in-sample median value of this index across countries, averaged over time, to construct a time-invariant benchmark.<fnref n="37" /> We then split the sample into two groups: countries with average stringency below the in-sample median, and those above it.<fnref n="38" />

These results provide evidence that regulation amplifies expected benefits and reduces costs most effectively where formal enforcement is limited. The heterogeneity in effect sizes supports

<footnote n="37">³⁷The CAPMF database provides regulatory stringency measures for 46 of the 78 countries included in our baseline analysis. Reassuringly, as we report in Table B6 in appendix, our baseline estimate of the effect of public regulation on NGO climate activism remains virtually unchanged in this restricted sample.</footnote>

<footnote n="38">³⁸Splitting the sample by in-sample median stringency results in subsamples of unequal size. This asymmetry reflects the fact that most NGOs in our dataset are active in countries with relatively stringent climate regulation, leading to a higher concentration of observations in the above-median group.</footnote>
the mechanism that institutional benchmarks empower NGOs to act as informal monitors, demonstrating that regulation can mobilize civil society by altering the incentives for activism in contexts where enforcement gaps exist.

<table><caption>Table 8: The Effect of Climate Public Regulation on NGO activism against Firms: Heterogeneity by Regulatory Stringency</caption><thead><tr><th rowspan="3">Dependent variable<br>Samples</th><th colspan="4">Climate campaigns (Yes/No)</th></tr><tr><th colspan="2">&lt; Median PR stringency</th><th colspan="2">≥ Median PR stringency</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.019**<br>(0.009)</td><td>0.019**<br>(0.009)</td><td>0.007*<br>(0.004)</td><td>0.007*<br>(0.004)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Disasters controls</td><td></td><td>✓</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>13200</td><td>13200</td><td>79644</td><td>79644</td></tr><tr><td>Mean dep. var.</td><td>0.044</td><td>0.044</td><td>0.071</td><td>0.071</td></tr><tr><td>R<sup>2</sup></td><td>0.091</td><td>0.091</td><td>0.176</td><td>0.176</td></tr></tbody></table>

Notes: This table presents the results of analyzing heterogeneities in the effect of public climate regulation on NGO activism, differentiated by the stringency of regulation (using the OECD index). The unit of observation is an NGO-month. The dependent variable is a binary indicator for whether at least one climate-related report was issued by a given NGO-month. The sample is split based on whether the NGO's country's Public Regulation stringency is below (columns 1-2) or above (columns 3-4) the in-sample time-invariant country-level median value. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Disasters controls include binary indicators for the occurrence of climate-related and technological disasters in the NGO's country during the given month. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.

## 6.2 Heterogeneity by NGO Capacity and Orientation

Prediction 3 suggests that regulation's impact varies with the NGO's ability to act on institutional levers. While we do not observe NGO payoff structures directly, geographical scope serves as a proxy for capacity and domestic focus. Using an index of NGO geographical scope, we classify
organizations as local, national, or international.<fnref n="39" /> Locally oriented NGOs often lack the resources to mobilize, whereas international NGOs tend to prioritize global issues over domestic regulatory contexts. Nationally focused NGOs combine sufficient resources with a strong domestic orientation, making them most capable of responding to executive regulations. We then split the sample into these three groups.<fnref n="40" />

Table 9 shows that nationally focused NGOs increase climate campaigns by 1.1 percentage points (16% relative to a 6.7% baseline), whereas both local and international NGOs exhibit non-significant minimal response (0–0.1 percentage points and 0.03 percentage points respectively).<fnref n="41" />

These patterns indicate that regulation mobilizes actors who are both capable and institutionally positioned to respond. Geographical scope, as a proxy for capacity and domestic orientation, helps reveal the payoff-channel mechanism: regulation strengthens incentives most for actors with sufficient resources and alignment with domestic institutions. The heterogeneity across NGO types underscores that the effect of regulation is context-dependent, operating through the combination of benefits, costs, and organizational capacity.

# 7 Conclusion

How public regulation mobilizes civil society remains a central question in political economy. This paper examines the relationship between climate public regulation and NGO activism against firms, using a novel monthly dataset across 78 countries from 2010 to 2023. Our analysis provides credible causal evidence that public regulation systematically increases climate-related NGO campaigns, both at the level of individual organizations and in aggregate. Rather than crowding out civil society pressure, regulation appears to activate and sustain it.

The event-study design demonstrates that these effects are not anticipatory but emerge sharply at the time of regulatory enactment and persist well beyond, with activism intensifying in subsequent months. This dynamic response underscores the role of regulation in reshaping the incentives for

<footnote n="39">³⁹We use variable *ngo_power* in *Sigwatch* dataset and classify NGOs as follows: “local” if *ngo_power* = 0.5, “national” if *ngo_power* = 1, and “international” if *ngo_power* > 1. For example, in France, national NGOs include organizations such as “Amis de la Terre” and “Attac France”, whereas local NGOs operate at city or regional levels, such as “Action Climat Paris” or “Bretagne Vivante”. “Attac International” and “International Federation for Human Rights” are examples of International NGOs campaigning in France.</footnote>

<footnote n="40">⁴⁰Note that information on NGOs’ geographical scope is missing for approximately 0.38% of observations. As we report in Table B9 in appendix, baseline estimates are virtually unchanged when these observations are excluded from the sample.</footnote>

<footnote n="41">⁴¹Qualitatively similar results using the count and share of climate-related campaigns as dependent variables are reported in appendix Table B10 and Table B11, respectively.</footnote>
<table><caption>Table 9: The Effect of Climate Public Regulation on NGO activism against Firms: Heterogeneity by NGO geographical scope</caption><thead><tr><th rowspan="3">Dependent variable<br>Samples</th><th colspan="6">Climate campaigns (Yes/No)</th></tr><tr><th colspan="2">Local NGO</th><th colspan="2">National NGO</th><th colspan="2">International NGO</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.000<br>(0.006)</td><td>0.000<br>(0.006)</td><td>0.011***<br>(0.004)</td><td>0.011***<br>(0.004)</td><td>0.003<br>(0.007)</td><td>0.003<br>(0.007)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Disasters controls</td><td></td><td>✓</td><td></td><td>✓</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>10392</td><td>10392</td><td>71625</td><td>71625</td><td>19479</td><td>19479</td></tr><tr><td>Mean dep. var.</td><td>0.041</td><td>0.041</td><td>0.067</td><td>0.067</td><td>0.065</td><td>0.065</td></tr><tr><td>R<sup>2</sup></td><td>0.087</td><td>0.087</td><td>0.173</td><td>0.173</td><td>0.157</td><td>0.157</td></tr></tbody></table>

Notes: This table presents the results of analyzing heterogeneities in the effect of public climate regulation on NGO activism, differentiated by the geographical scope of NGOs. The unit of observation is an NGO-month. The dependent variable is a binary indicator for whether at least one climate-related report was issued by a given NGO-month. The sample is split based on whether the NGO's geographical scope is local (columns 1-2), national (columns 3-4) or international (columns 5-6). "Public Regulation" is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for "Climate Change". Disasters controls include binary indicators for the occurrence of climate-related and technological disasters in the NGO's country during the given month. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.

NGOs to engage.

Our exploration of mechanisms highlights two central channels. First, regulation provides institutional benchmarks that NGOs can invoke to hold firms accountable, especially where formal enforcement capacity is limited. Second, regulation alters the payoff structure of activism by raising potential benefits and reducing costs, particularly for NGOs that are nationally focused and domestically oriented. Both heterogeneity by regulatory environment and NGO scope lend empirical support to these mechanisms, showing that regulation is most effective where enforcement gaps exist and where actors are positioned to exploit new institutional levers.

Together, these findings contribute to a more nuanced view of climate governance. Regulation does not act solely through its direct legal mandates; it also mobilizes informal oversight by civil society, thereby reinforcing accountability pressures on firms. This perspective suggests that effective
climate policy can extend beyond formal compliance to activate a broader ecosystem of monitoring
and reputational enforcement.

Future research could build on these results by investigating how firms adapt to this dual source of pressure from state and non-state actors, and by examining whether similar dynamics arise in other policy domains. For policymakers, the key implication is that regulatory interventions can generate spillovers into civic accountability: by providing clear benchmarks and lowering the costs of engagement, they empower NGOs to act as enduring monitors of corporate climate behavior.
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# Appendix

## A Data

This data appendix first presents the list of data sources used in the analysis. We then detail the construction of our main variables, focusing on public climate regulation and NGO activism.

### A.1 Data sources

We collect data from 7 different sources: Sigwatch, Grantham Research Institute, EM-DAT, V-Dem, World Bank, OECD, Google Trends, and United Nations.

<table><caption>Table A1: Descriptions and sources of variables</caption><thead><tr><td>Variable</td><td>Definition and measure</td><td>Source</td></tr></thead><tbody><tr><td>Climate campaigns (Yes/No)</td><td>1 if an NGO publishes at least one climate-related campaign in a given country-month</td><td>Sigwatch</td></tr><tr><td>Number of climate campaigns</td><td>Number of climate-related campaigns in a given country-month</td><td>Sigwatch</td></tr><tr><td>Share of climate campaigns</td><td>Number of climate campaigns divided by the total number of campaigns in a given country-month</td><td>Sigwatch</td></tr><tr><td>National campaigns</td><td>A climate campaign that is counted if the corresponding value of the geographical reach is local or national</td><td>Sigwatch</td></tr><tr><td>International campaigns</td><td>A climate campaign that is counted if the corresponding value of the geographical reach is international</td><td>Sigwatch</td></tr><tr><td>Climate NGO</td><td>An NGO that reported at least one climate campaign between 2010–2023</td><td>Sigwatch</td></tr><tr><td>Non-climate NGO</td><td>An NGO that did not report any climate campaigns between 2010–2023</td><td>Sigwatch</td></tr><tr><td>Non-climate campaigns</td><td>Campaigns of non-climate NGOs</td><td>Sigwatch</td></tr><tr><td>Public Regulation</td><td>1 if at least one climate mitigation policy or law was enacted in a given country-month</td><td>Grantham Research Institute</td></tr><tr><td>GDP per capita</td><td>Measured in PPP current international USD</td><td>World Bank</td></tr><tr><td>Rule of law</td><td>An index from the Worldwide Governance Indicators, transformed to range from 0 to 1</td><td>World Bank</td></tr><tr><td>Online media</td><td>An index from V-Dem, transformed to range from 0 to 1</td><td>V-Dem</td></tr><tr><td>Google Trend Climate Change</td><td>An index from Google Trends measuring research interest in the term “Climate Change” (0 to 100), where 100 corresponds to the peak interest given the country during the studied period</td><td>Google Trends</td></tr><tr><td>COP</td><td>1 if the country hosted a COP in the last 2 years, or is neighboring such a host country</td><td>United Nations</td></tr><tr><td>Climate disasters</td><td>1 if a drought, storm, flood, heat wave, or wildfire started in a given country-month</td><td>EM-DAT</td></tr><tr><td>Technological disasters</td><td>1 if a technological disaster occurred in a given country-month</td><td>EM-DAT</td></tr><tr><td>PR Stringency</td><td>Relies on the in-sample CAPMF measure of policy stringency, defined as the degree to which policies incentivize emissions reductions</td><td>OECD</td></tr></tbody></table>
## A.2 Creation of variables

### A.2.1 Climate public regulation

Our objective is to capture the monthly climate-related regulatory activity within a specific country. Our raw data comes from the *Climate Change Laws of the World* dataset, compiled by the Grantham Research Institute at LSE (see https://climate-laws.org/). The procedure we use is consistent across all types of regulation and is as follows:

1. We retain documents based on their Family ID, which represents a specific instance of regulatory activity, even though a Family ID may encompass multiple legal documents. We include only regulations related to mitigation.

2. Since regulatory activity extends beyond the release of new regulations, we reshape the data based on the specific modifications or revisions each Family ID has undergone.

3. European countries are subject to EU environmental regulations. Following the approach of Eskander and Fankhauser (2020), we assign these regulations to each EU member state to accurately reflect climate regulation activity.

4. These legal documents can originate from the executive, the legislature, or international bodies. Our main specification relies only on legal documents related to the executive. More details can be found in section 3.

By following these steps, we derive the main variable used in our study: a binary variable indicating whether an executive climate regulation was enacted in a given country x month-year.

### A.2.2 NGO climate activism

Our objective is to capture the monthly activity of NGO activism related to climate change. Our raw data comes from *Sigwatch* (see https://www sigwatch com/). *Sigwatch* is a European consultancy that continuously monitors and records NGO campaigns directed at firms. A full description of the data can be found in Koenig (2017). The procedure we use is as follows:

1. We retain only negative reports and classify the campaigns using the list provided in Table A2.
2. Following Hatte and Koenig (2020), we reshape the database by NGO. Each observation thus represents a negative report from an NGO targeting a specific firm, focused on a particular climate-related issue, and occurring on a specific date.

3. NGOs are classified as climate NGOs if they issued at least one climate-related report between 2010 and 2023. Otherwise, they are classified as non-climate NGOs.

4. We partially rebalance the panel by coding as zero the months in which an NGO did not issue any reports. To avoid artificially inflating the number of null observations, we restrict this imputation to the period between the first and last month in which the NGO is observed to be active.

Following these steps, we construct our main outcomes variable measured at the NGO × month-year level: a binary variable indicating whether a NGO issued climate-related reports against firm(s), the number of such reports, as well as the proportion of a NGO reports that are climate-related. We provide the list of climate-related issues raised in NGO reports in Table A2.

<table><caption>Table A2: Most frequent issues raised by NGOs relative to climate change (2010–2023)</caption><thead><tr><td>Issue</td><td>%</td></tr></thead><tbody><tr><td>Financial institutions & carbon, divestment</td><td>25.9</td></tr><tr><td>Oil, gas, coal & climate change</td><td>25.7</td></tr><tr><td>Coal, oil & gas and climate change</td><td>6.1</td></tr><tr><td>Climate change - state/government action</td><td>5.0</td></tr><tr><td>Corporate efforts to reduce GHG emissions</td><td>3.9</td></tr><tr><td>Automotive carbon emissions and fuel efficiency</td><td>3.5</td></tr><tr><td>Aviation & climate change</td><td>3.0</td></tr><tr><td>Climate change - risk to citizens, business, govt</td><td>2.6</td></tr><tr><td>Carbon taxes/pricing, fossil fuel subsidies</td><td>2.0</td></tr><tr><td>Agriculture contribution to climate change</td><td>2.0</td></tr></tbody></table>

Notes: This table reports the list of the top 10 most frequent climate-related issues raised by NGOs in campaigns tracked by *Sigwatch* between 2010 and 2023. Percentages reflect the share of total climate-related campaigns mentioning each issue. Categories are not mutually exclusive, as a single campaign can reference multiple issues. The list includes both major themes (e.g., fossil fuels, divestment) and more specific or less frequent concerns (e.g., peat in compost, ocean acidification).
<figure><img src="image_6.png" /><figcaption>Figure A1: Number of climate-related NGOs per country (in-sample, 2010-2023)</figcaption></figure>

Source: Authors’ calculations using data from Sigwatch

<figure><img src="image_7.png" /><figcaption>Figure A2: Total number of NGOs’ climate-related reports per country (in-sample, 2010-2023)</figcaption></figure>

Source: Authors’ calculations using data from Sigwatch
Figure A3: Total number of climate change mitigation-related executive regulations per country (in-sample, 2010-2023)

<figure><img src="image_8.png" /></figure>

Source: Authors' calculations using data from the Grantham Research Institute

Figure A4: Average yearly number of climate change mitigation-related executive regulations per country (in-sample, 2010-2023)

<figure><img src="image_9.png" /></figure>

Source: Authors' calculations using data from the Grantham Research Institute
B Additional tables and figures

<table><caption>Table B1: Climate Public Regulation and NGO activism against Firms - PPML estimations</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="2">Number of Climate campaigns</th></tr><tr><th>(1)</th><th>(2)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.098**<br>(0.042)</td><td>0.096**<br>(0.042)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>101880</td><td>101880</td></tr><tr><td>Mean dep. var.</td><td>0.080</td><td>0.080</td></tr><tr><td>Pseudo-R<sup>2</sup></td><td>0.284</td><td>0.284</td></tr></tbody></table>

Notes: This table presents PPML estimations of the effect of public climate regulation on NGO activism against firms. The unit of observation is an NGO-month. The dependent variable is the number of climate-related reports issued by a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Column (2) additionally includes country-year controls: GDP per capita and an index of the rule of law, as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B2: Climate Public Regulation and NGO activism against Firms - Robustness checks</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="6">Climate campaigns (Number)</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.015***<br>(0.005)</td><td>0.015***<br>(0.005)</td><td>0.016***<br>(0.005)</td><td>0.015***<br>(0.005)</td><td>0.016***<br>(0.005)</td><td>0.014***<br>(0.005)</td></tr><tr><td>Climate reports (Number)<sub>t-1</sub></td><td>0.156***<br>(0.018)</td><td>0.140***<br>(0.016)</td><td></td><td></td><td></td><td>0.140***<br>(0.016)</td></tr><tr><td>Climate reports (Number)<sub>t-2</sub></td><td></td><td>0.091***<br>(0.015)</td><td></td><td></td><td></td><td>0.091***<br>(0.015)</td></tr><tr><td>Public Regulation<sub>t-1</sub></td><td></td><td></td><td>0.009*<br>(0.005)</td><td>0.009*<br>(0.005)</td><td></td><td>0.006<br>(0.005)</td></tr><tr><td>Public Regulation<sub>t-2</sub></td><td></td><td></td><td></td><td>0.009*<br>(0.005)</td><td></td><td>0.006<br>(0.005)</td></tr><tr><td>COP</td><td></td><td></td><td></td><td></td><td>0.013*<br>(0.008)</td><td>0.011*<br>(0.006)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>100640</td><td>99400</td><td>101880</td><td>101880</td><td>101880</td><td>99400</td></tr><tr><td>Mean dep. var.</td><td>0.081</td><td>0.081</td><td>0.080</td><td>0.080</td><td>0.080</td><td>0.081</td></tr><tr><td>R<sup>2</sup></td><td>0.243</td><td>0.252</td><td>0.222</td><td>0.222</td><td>0.222</td><td>0.252</td></tr></tbody></table>

Notes: This table presents robustness checks for the effect of public climate regulation on NGO activism against firms. The unit of observation is an NGO-month. The dependent variable is the number of climate-related reports issued by a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. Specifications (1) and (2) control for lagged binary indicator of NGO climate campaigns (up to 2 months). Specifications (3) and (4) control for lagged public climate regulation (up to 2 months). Specification (5) controls for a binary variable indicating whether the NGO’s country hosted a COP event within the past two years or shares a border with a country that hosted one. Specification (6) includes all controls simultaneously. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B3: Climate Public Regulation and NGO activism against Firms - Robustness checks</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="6">Climate campaigns (Number)</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.098**<br>(0.042)</td><td>0.008***<br>(0.003)</td><td>0.007**<br>(0.003)</td><td>0.007**<br>(0.003)</td><td>0.008**<br>(0.003)</td><td>0.007**<br>(0.003)</td></tr><tr><td>Climate reports (Share)<sub>t-1</sub></td><td></td><td>0.047***<br>(0.008)</td><td></td><td></td><td></td><td>0.047***<br>(0.008)</td></tr><tr><td>Climate reports (Share)<sub>t-2</sub></td><td></td><td>0.037***<br>(0.008)</td><td></td><td></td><td></td><td>0.037***<br>(0.008)</td></tr><tr><td>Public Regulation<sub>t-1</sub></td><td></td><td></td><td>0.005*<br>(0.003)</td><td>0.005*<br>(0.003)</td><td></td><td>0.005*<br>(0.003)</td></tr><tr><td>Public Regulation<sub>t-2</sub></td><td></td><td></td><td></td><td>0.005<br>(0.003)</td><td></td><td>0.004<br>(0.003)</td></tr><tr><td>COP</td><td></td><td></td><td></td><td></td><td>0.008**<br>(0.003)</td><td>0.008**<br>(0.003)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td></td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>101880</td><td>99400</td><td>101880</td><td>101880</td><td>101880</td><td>99400</td></tr><tr><td>Mean dep. var.</td><td>0.080</td><td>0.055</td><td>0.054</td><td>0.054</td><td>0.054</td><td>0.055</td></tr><tr><td>R<sup>2</sup></td><td></td><td>0.135</td><td>0.128</td><td>0.128</td><td>0.128</td><td>0.136</td></tr></tbody></table>

Notes: This table presents robustness checks for the effect of public climate regulation on NGO activism against firms. The unit of observation is an NGO-month. The dependent variable is the share of reports issued by a given NGO-month that are climate related. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. Specifications (1) and (2) control for lagged binary indicator of NGO climate campaigns (up to 2 months). Specifications (3) and (4) control for lagged public climate regulation (up to 2 months). Specification (5) controls for a binary variable indicating whether the NGO’s country hosted a COP event within the past two years or shares a border with a country that hosted one. Specification (6) includes all controls simultaneously. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses. *** p<0.01, ** p<0.05, * p<0.10.
<figure><img src="image_10.png" /><figcaption>Figure B1: Climate Public Regulation and NGO activism against Firms - Number of campaigns</figcaption></figure>

*Notes*: This figure plots the estimates $\beta_k$ and 95% confidence intervals (robust to two-way clustering at the NGO and country × month levels) from event-study specification Equation 2, exploring the dynamic effects of climate public regulation on NGO activism against firms. The unit of observation is an NGO-month. The x-axis denotes the number of months relative to the introduction of a public climate regulation ($t = 0$). The omitted reference period is $t = -1$. The specification includes NGO, country and month-year fixed effects, as well as baseline country-year controls: GDP per capita, an index of the rule of law as well as an index of the presence of online media, and the country-month variation in Google Trends for "Climate Change".
<figure><img src="image_11.png" /><figcaption>Figure B2: Climate Public Regulation and NGO activism against Firms - Share of campaigns</figcaption></figure>

*Notes*: This figure plots the estimates $\beta_k$ and 95% confidence intervals (robust to two-way clustering at the NGO and country × month levels) from event-study specification Equation 2, exploring the dynamic effects of climate public regulation on NGO activism against firms. The unit of observation is an NGO-month. The outcome variable is the share of campaigns launched by an NGO in a given country-month that are climate-related. The x-axis denotes the number of months relative to the introduction of a public climate regulation ($t = 0$). The omitted reference period is $t = -1$. The specification includes NGO, country and month-year fixed effects, as well baseline country-year controls: GDP per capita, an index of the rule of law as well as an index of the presence of online media, and the country-month variation in Google Trends for “Climate Change”.
<figure><img src="image_12.png" /><figcaption>Figure B3: Climate Public Regulation and NGO activism against Firms - Country-month analysis</figcaption></figure>

*Notes*: This figure plots the estimates $\beta_k$ and 95% confidence intervals (robust to clustering at the country level) from a country-month level variant of event-study specification Equation 2, exploring the dynamic effects of climate public regulation on NGO activism against firms. The unit of observation is a country-month. Each observation is weighted by the number of climate NGOs in each country-month. The outcome variable is the total number of climate-related campaigns launched by NGOs in a given country-month. The x-axis denotes the number of months relative to the introduction of a public climate regulation ($t = 0$). The omitted reference period is $t = -1$. The specification includes NGO, country and month-year fixed effects, as well baseline country-year controls: GDP per capita, an index of the rule of law as well as an index of the presence of online media, and the country-month variation in Google Trends for "Climate Change". The specification also controls for the number of active climate NGOs at the country-month level.
<figure><img src="image_13.png" /><figcaption>Figure B4: Climate Public Regulation and activism of Non-Climate NGO against Firms (Placebo Group) - Number of campaigns</figcaption></figure>

*Notes:* This figure plots the estimates $\beta_k$ and 95% confidence intervals (robust to two-way clustering at the NGO and country × month levels) from the placebo event-study specification (Equation 2), exploring the dynamic relationship between public climate regulation and non-climate NGO activism against firms. The unit of observation is an NGO-month. The outcome variable is the number of non-climate campaigns launched by a non-climate NGO in a given country-month. The x-axis denotes the number of months relative to the introduction of a public climate regulation ($t = 0$). The omitted reference period is $t = -1$. The specification includes NGO, country and month-year fixed effects, as well baseline country-year controls: GDP per capita, an index of the rule of law as well as an index of the presence of online media, and the country-month variation in Google Trends for “Climate Change”.
<table><caption>Table B4: The Influence of Climate Public Regulation and Climate Preferences on NGO activism against Firms - Number of climate campaigns</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="3">Climate campaigns (Number)</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.016***<br>(0.005)</td><td>0.016***<br>(0.005)</td><td>0.016***<br>(0.005)</td></tr><tr><td>Climate disasters</td><td>0.009*<br>(0.005)</td><td></td><td>0.009*<br>(0.005)</td></tr><tr><td>Technological disasters</td><td></td><td>0.001<br>(0.006)</td><td>0.001<br>(0.006)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>101880</td><td>101880</td><td>101880</td></tr><tr><td>Mean dep. var.</td><td>0.080</td><td>0.080</td><td>0.080</td></tr><tr><td>R<sup>2</sup></td><td>0.222</td><td>0.222</td><td>0.222</td></tr></tbody></table>

Notes: This table examines the impact of climate public regulation on NGO activism against firms, exploring the role of climate preferences factors such as climate and technological disasters. The unit of observation is an NGO-month. The dependent variable is the number of climate-related reports issued by a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. “Climate disasters” and “Technological disasters” are binary indicators for the occurrence of climate-related and technological disasters in the NGO’s country during the given month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B5: The Influence of Climate Public Regulation and Climate Preferences on NGO activism against Firms - Share of climate campaigns</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="3">Climate campaigns (Share)</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.008***<br>(0.003)</td><td>0.008**<br>(0.003)</td><td>0.008***<br>(0.003)</td></tr><tr><td>Climate disasters</td><td>0.004*<br>(0.003)</td><td></td><td>0.004*<br>(0.003)</td></tr><tr><td>Technological disasters</td><td></td><td>-0.001<br>(0.004)</td><td>-0.001<br>(0.004)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>101880</td><td>101880</td><td>101880</td></tr><tr><td>Mean dep. var.</td><td>0.054</td><td>0.054</td><td>0.054</td></tr><tr><td>R<sup>2</sup></td><td>0.128</td><td>0.128</td><td>0.128</td></tr></tbody></table>

Notes: This table examines the impact of climate public regulation on NGO activism against firms, exploring the role of climate preferences factors such as climate and technological disasters. The unit of observation is an NGO-month. The dependent variable is the share of reports issued by a given NGO-month that are climate related. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. “Climate disasters” and “Technological disasters” are binary indicators for the occurrence of climate-related and technological disasters in the NGO’s country during the given month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B6: Climate Public Regulation and NGO climate activism against Firms - Subsample with information about country's regulatory stringency</caption><thead><tr><th rowspan="3">Dependent variable</th><th colspan="6">Climate campaigns</th></tr><tr><th colspan="2">Yes/No</th><th colspan="2">Number</th><th colspan="2">Share</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.009**<br>(0.004)</td><td>0.009**<br>(0.004)</td><td>0.016***<br>(0.006)</td><td>0.017***<br>(0.006)</td><td>0.008**<br>(0.003)</td><td>0.008**<br>(0.003)</td></tr><tr><td>GDP per capita</td><td></td><td>-0.000<br>(0.000)</td><td></td><td>-0.000<br>(0.000)</td><td></td><td>-0.000<br>(0.000)</td></tr><tr><td>Rule of law</td><td></td><td>0.040<br>(0.142)</td><td></td><td>0.097<br>(0.235)</td><td></td><td>0.045<br>(0.118)</td></tr><tr><td>Online media</td><td></td><td>0.048<br>(0.039)</td><td></td><td>0.119*<br>(0.068)</td><td></td><td>0.045<br>(0.033)</td></tr><tr><td>Google Trend Climate Change</td><td></td><td>0.000<br>(0.000)</td><td></td><td>0.000<br>(0.001)</td><td></td><td>0.000<br>(0.000)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>92844</td><td>92844</td><td>92844</td><td>92844</td><td>92844</td><td>92844</td></tr><tr><td>Mean dep. var.</td><td>0.068</td><td>0.068</td><td>0.085</td><td>0.085</td><td>0.057</td><td>0.057</td></tr><tr><td>R<sup>2</sup></td><td>0.165</td><td>0.165</td><td>0.225</td><td>0.226</td><td>0.132</td><td>0.132</td></tr></tbody></table>

*Notes:* This table presents OLS estimates of the effect of public climate regulation on various measures of NGO climate activism against firms, on the subsample of NGOs with non-missing information about their country's regulatory stringency. The unit of observation is an NGO-month. The dependent variables are, respectively, a binary indicator for whether at least one climate-related report was issued (columns 1-2), the number of climate-related reports (columns 3-4), and the share of climate-related reports among all reports (columns 5-6) in a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Columns (2), (4), and (6) additionally include country-year controls: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B7: The Effect of Climate Public Regulation on NGO activism against Firms: Heterogeneity by Regulatory Stringency - Number of climate campaigns</caption><thead><tr><th rowspan="3">Dependent variable<br>Samples</th><th colspan="4">Climate campaigns (Number)</th></tr><tr><th colspan="2">&lt; Median PR stringency</th><th colspan="2">≥ Median PR stringency</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.019**<br>(0.009)</td><td>0.019**<br>(0.009)</td><td>0.014**<br>(0.006)</td><td>0.014**<br>(0.006)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Disasters controls</td><td></td><td>✓</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>13200</td><td>13200</td><td>79644</td><td>79644</td></tr><tr><td>Mean dep. var.</td><td>0.048</td><td>0.048</td><td>0.091</td><td>0.091</td></tr><tr><td>R<sup>2</sup></td><td>0.095</td><td>0.095</td><td>0.236</td><td>0.237</td></tr></tbody></table>

Notes: This table presents the results of analyzing heterogeneities in the effect of public climate regulation on NGO activism, differentiated by the stringency of regulation (using the OECD index). The unit of observation is an NGO-month. The dependent variable is the number of climate-related reports issued by a given NGO-month. The sample is split based on whether the NGO's country's Public Regulation stringency is below (columns 1-2) or above (columns 3-4) the in-sample time-invariant country-level median value. "Public Regulation" is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. "Climate disasters" and "Technological disasters" are binary indicators for the occurrence of climate-related and technological disasters in the NGO's country during the given month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for "Climate Change". Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B8: The Effect of Climate Public Regulation on NGO activism against Firms: Heterogeneity by Regulatory Stringency - Share of climate campaigns</caption><thead><tr><th rowspan="3">Dependent variable<br>Samples</th><th colspan="4">Climate campaigns (Number)</th></tr><tr><th colspan="2">&lt; Median PR stringency</th><th colspan="2">≥ Median PR stringency</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.019**<br>(0.008)</td><td>0.019**<br>(0.008)</td><td>0.006*<br>(0.003)</td><td>0.006*<br>(0.003)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Disasters controls</td><td></td><td>✓</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>13200</td><td>13200</td><td>79644</td><td>79644</td></tr><tr><td>Mean dep. var.</td><td>0.039</td><td>0.039</td><td>0.060</td><td>0.060</td></tr><tr><td>R<sup>2</sup></td><td>0.088</td><td>0.088</td><td>0.140</td><td>0.140</td></tr></tbody></table>

*Notes*: This table presents the results of analyzing heterogeneities in the effect of public climate regulation on NGO activism, differentiated by the stringency of regulation (using the OECD index). The unit of observation is an NGO-month. The dependent variable is the share of reports issued by a given NGO-month that are climate related. The sample is split based on whether the NGO's country's Public Regulation stringency is below (columns 1-2) or above (columns 3-4) the in-sample time-invariant country-level median value. "Public Regulation" is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. "Climate disasters" and "Technological disasters" are binary indicators for the occurrence of climate-related and technological disasters in the NGO's country during the given month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for "Climate Change". Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B9: Climate Public Regulation and NGO climate activism against Firms - Subsample with information about NGOs geographical scope</caption><thead><tr><th rowspan="3">Dependent variable</th><th colspan="6">Climate campaigns</th></tr><tr><th colspan="2">Yes/No</th><th colspan="2">Number</th><th colspan="2">Share</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.009***<br>(0.003)</td><td>0.009***<br>(0.003)</td><td>0.016***<br>(0.005)</td><td>0.016***<br>(0.005)</td><td>0.008**<br>(0.003)</td><td>0.008***<br>(0.003)</td></tr><tr><td>GDP per capita</td><td></td><td>0.000<br>(0.000)</td><td></td><td>0.000<br>(0.000)</td><td></td><td>-0.000<br>(0.000)</td></tr><tr><td>Rule of law</td><td></td><td>-0.027<br>(0.111)</td><td></td><td>-0.026<br>(0.183)</td><td></td><td>-0.008<br>(0.093)</td></tr><tr><td>Online media</td><td></td><td>0.042<br>(0.037)</td><td></td><td>0.108*<br>(0.065)</td><td></td><td>0.039<br>(0.031)</td></tr><tr><td>Google Trend Climate Change</td><td></td><td>0.000<br>(0.000)</td><td></td><td>0.000<br>(0.000)</td><td></td><td>0.000<br>(0.000)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Observations</td><td>101676</td><td>101496</td><td>101676</td><td>101496</td><td>101676</td><td>101496</td></tr><tr><td>Mean dep. var.</td><td>0.064</td><td>0.064</td><td>0.080</td><td>0.080</td><td>0.054</td><td>0.054</td></tr><tr><td>R<sup>2</sup></td><td>0.161</td><td>0.161</td><td>0.222</td><td>0.222</td><td>0.128</td><td>0.128</td></tr></tbody></table>

Notes: This table presents OLS estimates of the effect of public climate regulation on various measures of NGO climate activism against firms, on the subsample of NGOs with non-missing information about their geographic scope. The unit of observation is an NGO-month. The dependent variables are, respectively, a binary indicator for whether at least one climate-related report was issued (columns 1-2), the number of climate-related reports (columns 3-4), and the share of climate-related reports among all reports (columns 5-6) in a given NGO-month. “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Columns (2), (4), and (6) additionally include country-year controls: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B10: The Effect of Climate Public Regulation on NGO activism against Firms: Heterogeneity by NGO geographical scope - Number of climate campaigns</caption><thead><tr><th rowspan="3">Dependent variable<br>Samples</th><th colspan="6">Climate campaigns (Number)</th></tr><tr><th colspan="2">Local NGO</th><th colspan="2">National NGO</th><th colspan="2">International NGO</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.002<br>(0.009)</td><td>0.002<br>(0.009)</td><td>0.022***<br>(0.007)</td><td>0.022***<br>(0.007)</td><td>-0.001<br>(0.009)</td><td>-0.001<br>(0.009)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Disasters controls</td><td></td><td>✓</td><td></td><td>✓</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>10392</td><td>10392</td><td>71625</td><td>71625</td><td>19479</td><td>19479</td></tr><tr><td>Mean dep. var.</td><td>0.045</td><td>0.045</td><td>0.086</td><td>0.086</td><td>0.080</td><td>0.080</td></tr><tr><td>R<sup>2</sup></td><td>0.106</td><td>0.106</td><td>0.238</td><td>0.238</td><td>0.194</td><td>0.194</td></tr></tbody></table>

*Notes*: This table presents the results of analyzing heterogeneities in the effect of public climate regulation on NGO activism, differentiated by the geographical scope of NGOs. The unit of observation is an NGO-month. The dependent variable is the number of climate-related reports issued by a given NGO-month. The sample is split based on whether the NGO's geographical scope is local (columns 1-2), national (columns 3-4) or international (columns 5-6). “Public Regulation” is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for “Climate Change”. Disasters controls include binary indicators for the occurrence of climate-related and technological disasters in the NGO's country during the given month. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.
<table><caption>Table B11: The Effect of Climate Public Regulation on NGO activism against Firms: Heterogeneity by NGO geographical scope - Share of climate campaigns</caption><thead><tr><th rowspan="3">Dependent variable<br>Samples</th><th colspan="6">Climate campaigns (Share)</th></tr><tr><th colspan="2">Local NGO</th><th colspan="2">National NGO</th><th colspan="2">International NGO</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Public Regulation</td><td>0.001<br>(0.006)</td><td>0.001<br>(0.006)</td><td>0.009***<br>(0.003)</td><td>0.009***<br>(0.003)</td><td>0.005<br>(0.006)</td><td>0.005<br>(0.006)</td></tr><tr><td>NGO FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Month-Year FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country FEs</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Country-year controls</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>Disasters controls</td><td></td><td>✓</td><td></td><td>✓</td><td></td><td>✓</td></tr><tr><td>Observations</td><td>10392</td><td>10392</td><td>71625</td><td>71625</td><td>19479</td><td>19479</td></tr><tr><td>Mean dep. var.</td><td>0.040</td><td>0.040</td><td>0.056</td><td>0.056</td><td>0.055</td><td>0.055</td></tr><tr><td>R<sup>2</sup></td><td>0.086</td><td>0.086</td><td>0.139</td><td>0.140</td><td>0.120</td><td>0.120</td></tr></tbody></table>

Notes: This table presents the results of analyzing heterogeneities in the effect of public climate regulation on NGO activism, differentiated by the geographical scope of NGOs. The unit of observation is an NGO-month. The dependent variable is the share of reports issued by a given NGO-month that are climate related. The sample is split based on whether the NGO's geographical scope is local (columns 1-2), national (columns 3-4) or international (columns 5-6). "Public Regulation" is a binary variable indicating whether at least one climate mitigation executive regulation was enacted in a given country-month. All specifications include NGO, country, and month-year fixed effects. Country-year controls include: GDP per capita, an index of the rule of law as well as an index of the consumption of online media, and the country-month variation in Google Trends for "Climate Change". Disasters controls include binary indicators for the occurrence of climate-related and technological disasters in the NGO's country during the given month. Standard errors are two-way clustered at the NGO and country × month-year levels and reported in parentheses.*** p<0.01, ** p<0.05, * p<0.10.