National energy transition, local partisanship? Elite cues, community identity, and support for clean power in the United States

Energy Research & Social Science 50 (2019) 143–150

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Energy Research & Social Science journal homepage: www.elsevier.com/locate/erss

National energy transition, local partisanship? Elite cues, community identity, and support for clean power in the United States

T

Adam Mayer Department of Human Dimensions of Natural Resources, Colorado State University, 1480 Campus Delivery, Fort Collins, 80523, CO, United States

A R T I C LE I N FO

A B S T R A C T

Keywords: Clean power plan Elite cues Partisanship

The Clean Power Plan (CPP) is the most ambitious effort to date to de-carbonize the U.S. energy system, promote alternative energy sources and assist communities that will be deleteriously impacted by the decline of traditional fossil fuels. The CPP has proven controversial, with critiques raised by diverse stakeholders. Currently, the future of the CPP is in doubt with the rise of President Trump’s decidedly pro-fossil fuel EPA. Despite the controversy around the CPP, little is known about how communities impacted by changes in the energy system view this policy. In this analysis, we present results from a survey of local policy actors in Colorado and Utah—states with diverse and ample energy resources. This analysis asks how factors like community economic identity, elite partisan cues and partisan identity influence support for the CPP. Results imply that local policy actors who view fossil fuels as locally significant are less likely to support the CPP, while community economic identity around alternative energy does not increase support (even though the CPP would benefit that sector). Elite partisan cues, surprisingly, did little to alter views about the CPP while party affiliation was a powerful predictor. Implications for the local dimensions of energy policy are discussed.

1. Introduction In 2014, President Obama directed the Environmental Protection Agency to implement the Clean Power Plan (CPP) with the express goal of reducing greenhouse gas emissions after comprehensive climate change legislation failed multiple times in the U.S. Congress [1]. The CPP established carbon reduction targets for U.S. states, with relatively modest reductions required of coal-reliant states like Kentucky and West Virginia and comparatively more stringent targets for California and Washington [2,3]—emissions reductions targets were largely based on pre-existing electricity sources within that state and existing efforts to decarbonize. Reaction to the CPP among policy and industry experts was mixed. Some have critiqued the CPP’s focus on reducing emission most significantly among states that were already working to reduce their emissions [4], while it has also been lauded because it allows states to meet emission targets in extremely flexible ways [5]. Still others have raised concerns that the emissions targets might have deleterious impacts on the economies of states that rely on coal production—for instance, Godby et al. [6] argue that the CPP would damage Wyoming’s coal-dependent economy. The CPP has been described as an example of “collaborative federalism”, given its flexibility and proposed cooperative relationship between states and the federal government [7,8].

The surprising election of Donald Trump to the U.S. presidency in late 2016 cast the future of the CPP in doubt. Trump campaigned on renewing the U.S. coal industry, expressed that climate change was a hoax started by the Chinese to undermine the U.S. manufacturing sector and voiced opposition to decades-old regulations on aerosol products to protect the ozone layer [9]. The appointment of former Oklahoma Attorney General Scott Pruitt to head the EPA—who has previously sued the EPA over the CPP—signaled that the CPP would perhaps never be fully implemented. Indeed, as of the writing of this manuscript the nowousted Pruitt and his successor have initiated efforts to overturn the CPP, though this move will face several legal hurdles and likely take several years [10]. Notably, the CPP is not scheduled to be fully implemented until 2022, and several Western states are already on pace to outdo their CPP targets due to the penetration of renewables and natural gas [11]. Currently, there are many studies of the economic and environmental implications of the CPP (e.g. [12–15]). National opinion polls imply that the public has very little knowledge of the plan [16], though self-described Democrats are more supportive of the CPP than Republicans are. In general, studies of energy policy consider narrow policies or views about specific energy policies, as opposed to comprehensive transition plans like the CPP (e.g [17–21]). Given this focus, our analysis may be of interest to scholars working in other contexts around

E-mail address: [email protected]. https://doi.org/10.1016/j.erss.2018.11.020 Received 3 July 2018; Received in revised form 29 November 2018; Accepted 29 November 2018 2214-6296/ © 2018 Elsevier Ltd. All rights reserved.

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by research from political science and social psychology that rests on the notion that most people are socialized into a political identity at a relatively young age by parents, peers and other agents of socialization [42–44]. Once formed, political identities have significant consequences, primarily because they are group affiliations, leading to a phenomenon wherein people who strongly adhere to a political identity will reconcile their views with those of the rest of their group [45–47]—this tends to reduce within-group variation in viewpoints, leading to partisan polarization. Given well-documented Republican resistance to the CPP, we test the following hypothesis about partisanship:

energy transition policies—not just the narrow case of the CPP in the United States. In this paper, we consider the views of local policy actors in the Mountain West states of Colorado and Utah. These states both have diverse, vibrant economies, with ample capacity for both wind and solar power. Yet both states also have a long and often celebrated history of coal mining, have been home to significant uranium mining and are major producers of natural gas (and to a lesser extent, oil). Given the local and regional flexibility of the CPP, studying local policy actors in this context is especially important. The CPP’s collaborative federalism model, which allows for significant local and regional adaptation, and the distributed nature of renewable energy technologies makes the views of local policy actors very relevant during this era of energy transition. More broadly, there is emerging evidence of increased local coordination and activism regarding the U.S. energy transition, implying that it is important to study local policy actors (e.g. [22]). We explicitly test for the role of elite cues and partisanship in determining support for the CPP and operationalize Bell and York’s (2010) concept of “community economic identity” to investigate the affective, identity-based motivations behind support for the CPP among local policy actors. The next section discussed the relevant literature on the partisanship, elite cues, and environmental policy.

Hypothesis 1. Republican local policy actors will be less supportive of the CPP. A second consequence of the social nature of political identity is that people are often highly receptive to elite cues from leading political or media figures who share their affiliation. Often, people interpret new information in a motivated fashion to re-affirm their pre-existing political identity, rather than updating their views upon learning new facts [48,49]. Cues from elites provide a useful cognitive heuristic in the sense that people do not have to labor to learn in-depth information about complex issues. Rather, they can simply align their views with those of the dominant members of their partisan group. Cohen (2003) conducted a series of experiments to understand this partisan motivated cognition. Study participants invariably seemed to respond to elite cues, often supporting policy positions at odds with their stated preferences if told that leaders of their party endorsed said positions. For instance, Democratic-identifying study participants endorsed cuts to social welfare policies if told that congressional Democrats supported the cuts. Similarly, Republicans in the study endorsed tax increases if told that congressional Republicans were in favor of said tax increases. Cohen’s study and others (e.g. Malka and Lelkes 2010; Tesler 2017) imply that many people simply shift their views to align with those of partisan elites. One of the most effective uses of elite cues has been around climate change wherein conservative elites (e.g. media figures, political leaders) convinced a significant majority of conservatives and Republicans that climate change is a hoax or, at least, the threat of climate change is minor [25,26]). Following this work, we examine the following hypothesis regarding elite cues:

2. Background 2.1. Partisanship and elite cues Since the 1970s, researchers have consistently found that Republican politicians and members of the general public are typically less supportive of environmental regulations and less concerned about environmental problems than their Democratic counterparts [23,24]. Climate change is perhaps the most polarized issue, with significant proportions of Republican voters (or those identifying as ideologically conservative) questioning climate change science and opposing efforts to mitigate climate change [25–28]. Energy policy preferences are generally less polarized than views about climate change, but researchers still find relatively consistent gaps between Republicans and Democrats, or between liberals and conservatives. Though clean energy enjoys support among both groups, Democrats are generally more supportive of the aggressive adoption of renewables [17]. Republicans are more likely to endorse the use of hydraulic fracturing [21,29,30] and prefer a lighter regulatory regime for energy development [31,32]. Some energy policies—such as those that encourage efficiency and less government spending—may enjoy more bipartisan support than others [20,33,34] and support for wind power is not sharply polarized [35,36]. Though it is perhaps unsurprising that political identities (e.g. liberal vs. conservative, Republican vs. Democrat) exert a powerful influence on policy preferences, the significance of political identity extends far beyond the policy positions that a person endorses. Rather, even ostensibly private behaviors like household energy use are impacted by partisanship [37,38]. Researchers have long documented partisan divergence in risk perceptions related to energy technologies—wherein conservatives (or Republicans) tend to express less concern about water pollution, air pollution and other deleterious impacts of energy development [39,40,30,41]. Thus, political identities are salient not only for policy preferences—it seems that, at least in the U.S., many people rely on their political identities to inform their understanding of empirical questions about the impacts of energy. That is, political identities aren’t merely a set of policy preferences. Rather, political identities also provide guidelines about what is empirically true about the world. Given its centrality to a range of issues related to energy consumption, production and distribution, it is important to develop an operational understanding of political identity. Our analysis is informed

Hypothesis 2. Local policy actors will respond to elite cues—Republicans that are told that President Trump seeks to undo the CPP will be less likely to endorse the CPP, while Democrats who are told that President Obama introduced the CPP will be more likely to support it than those who are provided no elite cues. 2.2. Community economic identity Bell and York [50] pioneered the concept of community economic identity, documenting how the coal industry has created deep, affective bonds with the population of Appalachia despite the marked decline in employment in the industry over the last several decades. Bell and York argue that coal holds unique cultural significance for Appalachians due to the historical importance of the industry and comprehensive industry public relations efforts—such as the use of regional celebrities in the “Friends of Coal” campaign—to engender support for the industry. In an analysis heavily informed by Bell and York’s work, Blaacker, Woods and Oliver (2012) show that West Virginia college students drastically overestimate the economic benefits that the coal industry provides the state. Communities might also form identities around multiple industries that occasionally come into conflict. Gasteyer and Carrera [51] provide a useful case study to understand the conflictual nature of community economic identity. Studying a region of rural Illinois, the authors describe how industrial-scale agriculture was at the center of the area’s economy and historically the area had hosted coal mining. New mining 144

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state tax documents for Colorado and Utah to identify all cities, towns, counties, and municipal entities within both states. From there we procured email addresses from city, county and other websites to contact local policy actors. We targeted policy actors with a role in fiscal issues, economic development policy, sustainability and related areas. These included treasury staff, economic development officers, county commissioners, and other actors whose work was tied to finance or the local economy in a significant way. The study was funded by the Midwest Sociological Society.2 Using the most generous figure that includes all incompletes (i.e. n = 476), the response rate per AAPOR definition 1—the most conservative calculation—was 21.71%. Using the lower, and likely more valid, number of completions (n = 313), the response rate per AAPOR definition 1 was 14.27%.3 Demographic characteristics for the respondents can be found in Appendix A. The typical respondent took about 10 min to complete the questionnaire—as is common in online survey research, we inspected our data for respondents that completed the survey in implausibly short time but did not locate any such respondents.

techniques promised to increase coal production. Residents, motivated by concerns about its impacts on industrial agriculture, ultimately resisted the expansion of coal mining. Notably, the affected communities were not motivated by abstract environmental concerns. Rather, it seems that they rallied against coal to protect industrial agriculture, implying that community economic identity is a multi-dimensional phenomenon wherein a given community may have multiple collective identities around different industries. The consequences of this multi-dimensional understanding of community economic identity for policy is not entirely clear. Bell and York [50] and others (e.g [52–56]) have described how certain industries become a central part of a region or communities’ cultural identity, likely leading said communities to endorse policy regimes that benefit that respective industry. Extractive industries ranging from coal mining, uranium mining and milling, and oil and gas production have long been culturally significant in parts of Colorado and Utah [54,55] and the Mountain West in general (e.g [57]). Relatedly, Crowe et al. [58] report that local policy actors in southern Illinois leverage the region’s history of coal mining to make sense of potential shale gas development. However, regions are home to multiple industries and it’s not well known if people form bonds with multiple industries and how said multi-faceted community economic identities translate into policy support. Further, some research suggests that Americans don’t really care about the source of their energy, so long as they perceive it to be affordable and clean [59]. In the case of the CPP, it stands to reason that community economic identity around extractive fossil fuel industries (especially coal) might erode support but community economic identity centered on alternative and renewable energy (e.g. wind or solar) might be associated with increased support. Yet, we also note that community economic identity around wind and solar is under-studied.1 In this analysis, we test for a multi-faceted operationalization of community economic identity. The likely economic impacts of the CPP are complex, especially given that states can meet emissions targets through whatever means they deem appropriate. Still, one plausible outcome for the Mountain West is that renewable energy sources like solar and wind will likely benefit, but it will accelerate the long decline of coal and possibly put downward pressure on the use of other fossil fuels. These changes, in turn, could have secondary impacts on related industries such as manufacturing, transportation and research and development. According, our final two hypotheses are as such:

3.2. Outcome variable For our dependent variable, respondents could support or oppose the Clean Power Plan. Each participant was randomly assigned to one 2 Developing a comprehensive list of relevant policy actors in Colorado and Utah was no simple task. Most cities and counties host extensive contact information for their staff on their websites, and we could simply copy those into a database for sampling. However, a small subset of counties and cities used online contact forms and did not provide direct email addresses for staff. We submitted the link to the survey and associated documentation via these online contact forms. Unfortunately, some 2% of the identified counties, cities and municipalities did not have active websites while a few others did not provide direct contact information for specific staff members or elected officials. When possible, we contacted administrative staff (typically secretaries) to procure contact information. This route was mostly unsuccessful. We compiled 2,224 email addresses, with 18 identified as duplicates and 14 emails were non-deliverable. Typically, the duplicates occurred because of incorrect information on host websites—such as circumstances where a staff member was listed with the email address of another staff member. Non-deliverables most often resulted from misspellings and incorrect characters found on host websites. We corrected these emails as much as possible. We collected data in six waves (that is, six recruitment emails) in October and November of 2017, with 476 local policy actors attempting the survey, but only 313 completing it (a 66% completion rate). The overwhelming majority of the incompletes (about 90%) were the result of respondents who navigated to the survey website on Qualtrics but did not answer a single question. These clicks probably occurred in error, and could arguably be considered refusals. 3 Several factors coalesced to lower the response rate. First, data collection coincided with several local elections—in private communications, some policy actors explained that they were overwhelmed with their re-election campaigns and related activities and did not have the spare time to participate. Still others voiced concerns about anonymity and were worried that their opinions would be construed as representative of their local government. Despite assurances of confidentiality—we did not link responses to specific email accounts or job titles—some policy actors felt that it would be inappropriate to share their opinion. Lastly, we only used six contact attempts—that is, we emailed each respondent a maximum of six times—we suspect that other studies have used more contact attempts. We ended data collection at six attempts in part because some local policy actors began to voice complaints about repeated emails, and we wanted to avoid potential measurement error problems that can occur when respondents are highly reluctant to complete the survey [75,76]. Of course, the research team hoped for a higher response rate and larger sample, but we note that other studies of local policy actors have used roughly similar sample sizes (e.g [58,77].). Further, survey methodologists have demonstrated that response rates typically have little association with non-response bias [78–81]. The response rate could have likely been increased via mixed-mode methods, or perhaps by providing a financial incentive, but these methods were beyond the resources of this study.

Hypothesis 3. We expect that community economic identity centered on extractive industries will reduce support for the CPP Hypothesis 4. : Community economic identity around alternative energy will increase support.

3. Data, measures and methods 3.1. Data collection In the fall of 2017, we gathered data from a sample of local policy actors via an online survey hosted on the Qualtrics platform. We used 1 The authors are aware of only a single study that considers community economic identity around renewable energy sources. Fergen and Jacquet [19] studied a rural community in the U.S. that embraced wind power as a central part of its identity. Given that CEI seems to have deep historical roots, it is not yet clear if communities that host solar and wind have developed a deep sense of identity akin to the identity that some communities hold around coal, although the research on social acceptance implies the procedural fairness and co-ownership increase support [71,72]; Giordano et al. 2018) Further, there is a robust literature on climate and clean energy policy coalitions (e.g. [73,74], but to the best of our knowledge this literature has not been linked to community economic identity. Although it is beyond the scope of this manuscript, integrating these areas is fertile ground for future research.

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3.4. Models

of three experimental conditions. Respondents were either told that President Trump had signed an executive order rescinding key parts of the CPP, that the CPP was implemented by President Obama, or they were assigned no partisan information and simply asked to indicate whether they supported the CPP. Thus, the dependent variable is binary indicator of support for the CPP with about 56% of respondents in support. Full question wordings are displayed in Appendix B.

Because the dependent variable is binary, we rely on the firth logit model. The firth logit model is an alternative to standard logistic regression models that produces less biased estimates in situations of small sample size and sparse distributions [62,63]. First, we estimate a firth logistic regression model to test for effect of elite cues on CPP support. In order to do so, we employ our dichotomized predictor of Republican Party affiliation and the randomly assigned framing conditions described above (e.g. Obama introduced the CPP, Trump opposes the CPP, and no partisan information). The framing conditions are then interacted with our binary indicator of partisan identity to test for the influence of elite partisan cues. In a second model, we add in the community economic identity items. Then, we estimate two additional models that include our dichotomized indicator of Republican Party affiliation and the factor scores for community economic identity. Given the well-documented challenges with directly interpreting log-odds coefficients we provide predicted probabilities to better contextualize our results [64,65]. These probabilities are the primary focus in the analysis below, as they allow us to describe our modelling results in an intuitive manner. However, we also provide tables with regression coefficients, standard errors and McKelvey and Zavoina pseudo R2 statistics in keeping with conventional reporting practices.

3.3. Predictors In addition to the experimental conditions, we also include predictors related to community economic identity. As we noted above, the CPP would have several complex impacts on local economies. Because prior research has demonstrated that community economic identity is a subjective phenomenon (e.g. [50,60]), policy actors were asked to rate the importance of several industries to their local economy. These included tourism, oil and gas development, coal mining, agriculture, colleges and universities, alternative energy like wind and solar, high technology (defined as computers, software and the internet), brewing and distilling, manufacturing and transportation (i.e. trains, trucking). We implement factor analysis on a polychoric correlation matrix to uncover the underlying dimensionality of these items—we used the iterated principal factors method with a varimax rotation for extraction [61]. Using a factor loading of 0.3 as a cut-off, the initial factor analysis suggested that colleges and high technology loaded strongly on the first factor, manufacturing and transportation loaded on a second factor, coal and oil and gas loaded on a third factor, and alternative energy loaded on its own factor. Tourism, brewing and distilling and agriculture all had ambiguous cross-loadings and are excluded from further analysis. Together, the first three factors accounted for 99% of the variance. Table 1 provides means, standard deviations and factor loadings for these items grouped by their respective factor. For partisan identity, we include a binary indicator of whether the respondent identified as Republican or not. Sex is binary where 1=female and 2=male. 54% of the sample identified as some degree of Republican and 68% were male. We also considered, but ultimately did not include, several other predictors of uncertain theoretical importance that we determined had little empirical relationship with our dependent variable. Using polychoric correlations, we determined that education (rho = 0.09), age (rho = 0.07) and state of residence (rho = 0.03) had substantively small associations with support for the CPP. We did not include a predictor for race, primarily because there was limited variance in this variable—96% of the sample identified as white.

4. Results 4.1. Elite cues models Table 2 provides the results of the elite cues model while Fig. 1 provides probabilities for Republicans and non-Republicans at different treatment statuses. To understand the effect of elite cues, we interact the experimentally assigned elite cues with Republican status. There is a sizable gap between Republican and non-Republican policy actors irrespective of elite cues—depending upon treatment status, Republicans are about 40–80% less apt to support the CPP. Fig. 1 suggests that Table 2 Firth logit models for Elite Cues, Partisan identity and Support for the Clean Power Plan.

Question wording (ref. category is Trump) No Elite Cues Obama elite cue

Table 1 Descriptive Statistics and Factor Loadings for Community Economic Identity Items.

Republican Interaction with no elite cues

Construct/ Items Interaction with Obama elite cue Mean

SD

Loadings

Model 1 b(se)

Model 2 b(se)

0.390 (0.540) 0.677 (0.577) −1.991** (0.479) 0.219 (0.674) −1.414* (0.737)

0.485 (0.569) 0.676 (0.605) −2.120** (0.521) 0.235 (0.714) −1.375 (0.781) −0.500 (0.331) −0.547* (0.264) 0.930** (0.283) −0.807** (0.306) 0.261 (0.321) 2.962 0.404 286

Male Community Economic Identity- Manufacturing and Trans. Perceived importance- Manufacturing 2.323 Perceived importance- Transportation 2.352 Community economic identity- Colleges/ High-Tech. Perceived Importance- Colleges and University 2.733 Perceived Importance- High tech sector 2.601 Community Economic Identity- Extractive Perceived Importance- Coal 2.217 Perceived Importance- Oil and Gas 2.332 Community Economic Identity- Alternative Energy Perceived Importance- Alternative Energy (wind and 2.330 solar)

1.104 1.202

0.669 0.687

1.218 1.265

0.671 0.699

0.686 0.866

0.558 0.560

1.015

0.330

Manufacturing and Trans. Colleges/ High-Tech. Extractive Alternative Energy Constant Mckelvey and Zavoina R2 N

Note: Factor analysis performed on a polychoric correlation matrix using iterated principal factor extraction with a varimax rotation.

1.269 0.333 297

Note: * p < 0.05; ** p < 0.01, Dependent variable is support for the clean power plan (0=no support, 1=support). 146

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policy actors who score higher on the colleges/ high-tech factor are more likely to endorse the CPP, while those who scored higher on the extractive factor were more inclined to reject the CPP. Although the CPP would likely bolster alternative energy sources (e.g. wind, solar) quite significantly, policy actors who believe that the alternative energy sector is locally significant do not appear to be more apt to endorse the CPP. We calculated predicted probabilities derived from Table 3, model 2 for Republicans and non-Republicans at varying values of the extractive and college/ high technology factor scores, displayed in Fig. 2. Both panels demonstrate that Republicans are consistently less likely to support the CPP by a large margin—the gap in predicted probabilities suggests that Republicans are between 40–80% less likely to support the CPP than Non-Republicans. Panel 1 demonstrates that community economic identity around extractive industries drives both Republicans and Democrats to resist the CPP. However, Democrats that score high on this factor (e.g. near 3.5) are still more likely than Republicans of any score to endorse the CPP. Thus, while community economic identity around extractive industries is indeed a powerful factor, it does not override the importance of partisanship. Panel 2 of Fig. 2 demonstrates that local policy actors who view colleges and the high-tech sector as locally significant are consistently more likely to endorse the CPP. Indeed, non-Republicans who rate these sectors as highly important have a probability verging upon 1.0. However, partisan identity is still a powerful factor—Republicans who score very high on this variable have a probability slightly lower than non-Republicans who score at the bottom end of the scale.

Fig. 1. Probability for Support for the Clean Power Plan by elite cues treatment and Partisan Identity.

some interaction occurs between partisan identity and the elite cues treatment conditions—but this effect is rather modest and concentrated among Republicans. Among Republicans, support for the CPP was lowest for those who received the “Obama” treatment. Indeed, Republicans who were told that Obama had introduced the CPP were less likely to support the CPP than those who were told that Trump sought to rescind the act. The difference between these two probabilities is 0.14. Republicans who were given no partisan information were most likely to support the CPP. Among non-Republicans, the “Obama” framing slightly increased support, but this effect was miniscule in practical terms. In model 2, we introduce the community economic identity items. The inclusion of these items has further reduced the small effect of elite cues, and rendered the Obama elite cue non-significant (p = 0.07).

5. Discussion The purpose of this paper was to understand support for the Clean Power Plan among local policy actors in the Mountain West States of Colorado and Utah. We asked how motivated cognition—in the form of elite cues and reasoning rooted in partisan identities—influenced support. We also extended the scant literature on community economic identity, suggesting that how policy actors view their local economy may influence their views on the CPP. We tested for the role of elite cues by randomly assigning participants to framing conditions. Consistent with hypothesis 1, we found that local policy actors who identified themselves as Republicans were much less likely to support the CPP. Despite our expectations listed in hypothesis 2, elite cues appear to be a relatively modest factor. Republican local policy actors who were told President Trump has sought to dismantle the CPP were slightly less likely to support the CPP than those who were provided with no partisan elite cues while Republicans who were provided information about Obama’s endorsement of the CPP were even less likely than those who received the “Trump” framing to support the CPP. We only speculate about the origins of this seemingly idiosyncratic finding. One possible reason for the muted effect of elite cues could be the unorthodox nature of the Trump presidency and associated campaign—compared to the rest of the nation, Republican voters in the Mountain West were more skeptical of Trump. This was especially true among Utah’s large Mormon population [66]. Perhaps the unconventional aspects of Trump and his presidency render associated elite cues less powerful. We employed a multi-dimensional understanding of community economic identity. Consistent with hypothesis 3, we found that local policy actors that viewed extractive industries as important to their area were less supportive of the CPP by a large margin. We also suspected (Hypothesis 4) that community economic identity around alternative energy would increase support for the CPP, since the CPP would likely be a boon for alternative energy. However, our modelling results did not corroborate our initial suspicion as community economic identity around alternative energy had a null effect. We were surprised by this finding, but the literature on the cultural dimensions of extractive

4.2. Partisan identity and community economic identity models The next series of models (Table 3) drops the Trump and Obama framings used in the prior models. The first model includes only our indicator for Republican Party identification and male sex. In this model, Republican policy actors are significantly less likely to endorse the CPP and male sex appears to have little role. The second model adds the factor scores from the community economic identity items. In model 2, the negative effect of Republican Party identification has remained largely unchanged despite the inclusion of additional predictors. Among the community economic identity factor scores, local Table 3 Firth logit Regression for Clean Power Plan Support.

Republican Male

Model 1 b(se)

Model 2 b(se)

−2.279** (0.282) −0.336 (0.298)

−2.466** (0.313) −0.525 (0.315) −0.511* (0.259) 0.913** (0.277) −0.716* (0.300) 0.203 (0.520) 3.184 282 0.355

Manufacturing and Trans. Colleges/ High-Tech. Extractive Alternative Energy Constant N Mckelvey and Zavoina R2

2.155 282 0.293

Note: * p < 0.05; ** p < 0.01, Dependent variable is support for the clean power plan (0=no support, 1=support). 147

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Fig. 2. Probability of support for the Clean Power Plan by Community Economic Identity and Partisan Identity.

documented the “triple helix” local and regional development model, wherein industry (often technology firms) coalesces with government and universities to promote regional clusters of innovation and economic development [69,70]. Perhaps local policy actors in university towns view economic development implicitly through this triple helix model and hence generally support policies that would promote new technologies and innovation. There are several policy implications to this study. A broad conclusion of this study is that partisan identities are a powerful force among local policy actors in energy policy. Though local policy actors are often highly educated and likely more informed on complex policy issues than the public at large, our analysis indicates that they are motivated by the similar partisan biases that animate the public. Though, at least in the case of the CPP, local policy actors seem relatively resilient to elite cues. Perhaps local policy actors do have greater policy knowledge and awareness than members of the public, and are less apt to follow elite cues, suggesting that future research should engage with problems of partisanship and polarization among local policy actors. Polarization in local government may be an unexpected barrier to decarbonization, and more research is needed to understand how the blunt the influence of partisanship at the local level. An additional implication is that extractive industries likely hold a unique cultural significance for communities and policy actors who view alternative energy sources as locally important are not necessarily in support of policies to promote renewables.

industries provides some potential insights. In their seminal article, Bell and York [50] describe how the coal industry has successfully leveraged coal mining’s historical importance and cultural significance in Appalachia to build public support for the industry—even though the industry provides relatively few jobs to the region. Other research speaks to the unique cultural significance of coal mining, and extractive industries more broadly [53,67] and local extractive industries may erode support for renewables, even if renewables could provide some economic benefits [54,68]. One possible explanation for the null effect of alternative energy is that extractive industries tend to occupy a unique cultural position in the United States, conjuring up romantic imagery of an extractive past, while alternative energy does not carry with it the weight of history and cultural centrality of extractive industries. Indeed, our results suggest that building community economic identity around alternative energy sources might be one way to establish support for policies to promote these technologies. However, our crosssectional research design does not allow us to track the development of community economic identity over time, an important task for future research. We were also surprised by the relatively strong effect of community economic identity around colleges/universities and the high-tech sector. We can only offer some preliminary explanation for this unexpected finding. Like extractive industries, colleges and universities often have a very long history, potentially tracing back several decades or even centuries, perhaps leading to a more robust community economic identity around these institutions. Further, much research has Appendix A. Demographic Characteristics of Respondents

Sex Female Male

% 31.73 68.27

Education Less that High School High school graduate or GED Vocational or trade school College graduate Master's Degree Doctorate, JD or MD

% 0 0.95 3.48 32.59 33.23 7.91

Race Black or African American

% 0.32

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0.97 1.29 0.32 1.94 95.16 mean 52.63

Age

std dev 12.31

Appendix B. Randomized Clean Power Plan (CPP) Question Wordings

Elite Cue Trump opposes the clean power plan. No partisan cue. Obama supports the clean power plan

Randomized Question Wording Support As you may know, the federal government recently implemented the Clean Power Plan to reduce carbon dioxide emissions and promote renewable energy. President Donald Trump signed an executive order to end key portions of the Clean Power Plan. Do you support or oppose the Clean Power Plan? As you may know, the federal government recently implemented the Clean Power Plan to reduce carbon dioxide emissions and promote renewable energy. Do you support or oppose the Clean Power Plan? As you may know, the federal government under former President Barack Obama implemented the Clean Power Plan to reduce carbon dioxide emissions and promote renewable energy. Do you support or oppose the Clean Power Plan?

Oppose

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