Coalitions on Climate Change
Jared Cory, Michael Lerner and Iain Osgood
In June 2017, President Trump announced that he was planning to withdraw the United States from the Paris Agreement, an international climate accord committing the signatories to limit climate change. Within days, a new public coalition of businesses, universities, non-governmental organizations, religious groups, and local governments had formed, called `We Are Still In’. The coalition declared in a joint statement that each member would continue to support climate action, and take the steps needed to meet the Paris Agreement’s goals. The coalition conducted a public media campaign, issuing statements and participating in social media, and provided a useful lede for journalists writing about how civil society was reacting to the Trump administration’s announcement. Ultimately, the coalition garnered more than 2000 members in 2017.
Public coalitions of this sort are relatively common in American politics, and global politics more generally. For example, public coalitions supporting particular US trade agreements; opposing the overuse of economic sanctions; and supporting (and opposing) stronger intellectual property rights are just a few examples from recent decades. These coalitions are explained in an established body of theory, which emphasizes the challenges of organizing to provide this public good of ‘outside lobbying’; and, the signaling benefits of successfully organization such a coalition. Politicians (and other persuadable groups) know that organized groups must really care about an issue. So inspired by this literature, and the `We Are Still In’ coalition, we set out to investigate the scope and membership of public coalitions interested in climate politics (whether for or against action on climate change) in the United States. In particular, we focused on locating coalitions with businesses or trade associations members.
We ended up finding 83 separate coalitions that were significantly motivated by climate change issues and which included at least some businesses as members that operated from 1990-2018. Thanks to some valuable feedback from readers and reviewers, we developed a careful coding rubric to determine in as objective a fashion as possible the position of each coalition on climate change issues. According to our coding scheme, 49 of our coalitions were strongly or weakly supportive of action to halt climate change; while 23 of our coalitions opposed (strongly or weakly) climate action. Interestingly, 7 of our coalitions that were clearly interested and engaged in climate politics never actually took a discernable public position on the matter – so we coded them as neutral. Ultimately, our coalitions included over 10000 unique firms and another 1000 unique trade associations. We describe these data in our paper “Supply Chain Linkages and the Extended Carbon Coalition” published in AJPS in 2021.
We highlight a few challenges in assembling this data on coalitions and their memberships. First, unlike other types of political activity undertaken by special interests (like lobbying or PAC contributions) there is no central repositories of data on public coalitions. Identifying as many coalitions as possible required much general web searching as well as scrutiny of coalition memberships, coalition websites, NGO websites, public documents, lobby records, and so on, to find other coalitions. A further challenge related to identifying coalitions is that individual firms or lobbyists will often attempt to create groups that look like public coalitions, but that are not or that have private memberships. Naturally, we left such `groups’ out of our data but record them in a separate document. Second, one particular challenge was that coalition memberships change over time (though often slowly and with only idiosyncratic updates). We set as a goal locating memberships at intervals of at most 4 years. Finally, firms and associations render their names in different fashion over time and across venues. Matching firm and association names and merging the different coalitions together to understand the sweep of firms’ behavior across all coalitions and over time represented a huge amount of our work.
At its core, our database is organized around coalitions. For each coalition, we have a unique list of all of its members over time and then an indicator for whether a given member was actually in the coalition in one of the years when we sampled its membership. We also cross-reference coalitions’ memberships with a master list of unique names across all coalitions, so that we may merge the data across coalitions. Using these building blocks we can create two types of data. First, we can create a cross-section of firms, associations, and other groups and a set of indicators for whether they were ever a member of any of our 83 coalitions. Using this data one could explore variation in firms’ participation across coalitions or devise simple summary measures, like how many pro-climate action coalitions has firm X been in over the past 25 years? Second, because we have some variation in time, we can also construct measures of firms’ changing participation in coalitions over time. For example, we can identify how many pro-climate coalitions a firm was a member of in a given year (or decade).
Almost all users of our firm-level data will wish to link up the data with firm and industry features. Firm-level data is available from a number of databases (and it tends to be particularly good for publicly traded firms). Connecting firms up with these data represent significant extra work because of further challenges in matching names. Soft-matching techniques available within databases or programmed by the user can speed up this work, but ultimately significant human oversight is required. These same databases often also contain information on firms’ industries which can help with connecting firms to industry-level data.