Who Shapes Environmental Policy? Power and Politics in the Renewable Portfolio Standards of U.S. States,1997

Abstract

Climate change has been a contentious political issue in the United States for many years. Although research at the national level has documented how fossil fuel interests have inhibited the United States from adopting a serious climate policy agenda, the situation among states is more heterogeneous. Using an original data set of 48 U.S. states from 1997 to 2020, I examine how qualitative variations in state energy policies are the product of conflicts between environmental groups, fossil fuel producers, utility providers, and political parties as they vie for power and influence. I show that Democratic party power, higher political spending from environmental organizations, lower investor-owned utility market share, higher publicly owned utility market share, and lower levels of fossil fuel production and political spending lead to more stringent policies. In contrast, weaker policies are more likely in states where the prototypical opponents of climate policy, Republican politicians and oil and gas interests, have greater power.

Keywords

environmental policy renewable portfolio standards political economy social movements

What are the forces that shape U.S. states’ policy decisions concerning climate change? Climate politics has long been a notably contested arena with a multitude of actors competing for control over the policy landscape (Basseches et al. 2022; Colgan, Green, and Hale 2021; Hughes and Urpelainen 2015). Indeed, these conflicts have only intensified throughout the twenty-first century as nations, international organizations, businesses, social movements, and others have mobilized and coalesced around different responses to climate change. In this spirit, the policy response within the federalist context of the United States has, unsurprisingly, been scattered and incoherent, with divergence both among states and between state and federal governments (Byrne et al. 2007; Karapin 2020). In the midst of this absence, subnational actors have largely stepped in to fill the policy gap (Kuramochi et al. 2020; Peng et al. 2021).

However, the lack of a unified strategy on climate change persists and has been amplified by growing polarization surrounding decarbonization and environmental protection (Egan and Mullin 2017; McCright, Xiao, and Dunlap 2014). On the one hand, opposition to these efforts has largely been driven by right-wing political movements and business interests to protect fossil fuel producers (Brulle et al. 2021; Farrell 2016; McCright and Dunlap 2010). On the other hand, environmental social movements have pushed for pro-climate policy change and environmental justice at subnational levels (Fraser and Temocin 2021; Mohai, Pellow, and Roberts 2009; Vasi and King 2019).

This article explores how this constellation of power and politics results in subtle yet important differences in the energy policies that states possess. Specifically, I focus on renewable portfolio standards (RPS), which have emerged as a prominent state-level solution to the gaps in national climate policy in the United States (Karapin 2020). However, there are important qualitative distinctions among the policies that states actually adopt. Rather than simply focusing on whether states do anything, examining variations among climate policies illuminates the ways in which different groups are able to shape aspects of policy design (Vasseur 2014).

Using an original longitudinal data set consisting of state-level data between 1997 and 2020, I examine how qualitative variations in these policies are the product of conflicts between key actors as they vie for power and influence. When a coalition of climate policy allies wins these conflicts, it can lead states to possess more stringent policies. On the other hand, in states where fossil fuel producers possess great structural power but face some pressure from energy reformers, it can lead to weaker accommodationist policies that do not threaten their structural position. Existing literature on what drives RPS adoption has pointed to the role of activist and industry political influence (Stokes 2020; Vasseur 2014), economic dependence on fossil fuels (Thombs and Jorgenson 2020; Vasseur 2014), and political party power (Coley and Hess 2012; Lyon and Yin 2010; Thombs and Jorgenson 2020; Vasseur 2014).

This article makes two key contributions to the RPS literature. First, it offers an empirical contribution by examining the effect of these forces over a longer time frame—Vasseur (2014), for instance, only examines 1998 to 2011—and adding in the ownership composition of utility providers. As others have pointed out, utility providers are important players in the adoption of state-level energy policies, including RPS (e.g., Culhane, Hall, and Roberts 2021; Delmas and Montes-Sancho 2011; Stokes 2020; Vasi and King 2019). However, existing research does not account for the role of differences in the ownership structure of utility providers in producing qualitative differences in policy content. Second, this article makes a theoretical contribution by situating RPS policies within a political economy framework that emphasizes the coalitions of market, state, and social movement actors that constitute state-level energy policy fields. As Thombs and Jorgenson (2020) note, the literature on RPS adoption makes surprisingly little use of the conceptual tools offered by political economy. To remedy this, they emphasize the relationship between states’ reliance on fossil fuel production and state government ideology in shaping RPS adoption. I expand on their contribution by examining how power differentials in the interactions between market, state, and civil society actors shape not only RPS adoption but also lead to different types of RPS.

In the sections that follow, I proceed with a discussion of what RPS are and some of the forms that they take. I then outline the theoretical literature and hypotheses that will inform the analysis and discussion sections. Results from logistic regressions show that stringent policies are more likely in states where environmental groups and Democratic politicians have greater relative power, and where publicly owned utilities have a greater market share. I also show that states with greater dependent on fossil fuel producers are more likely to possess weaker policies. I conclude with a discussion of the results and their limitations.

Renewable Portfolio Standards in the United States

RPS are a type of energy policy that aims to increase the percentage of energy generated from renewable sources by setting requirements for energy suppliers to meet by a particular date. Requirements can usually be met through the generation of renewable energy and in many cases, by purchasing Renewable Energy Certificates (RECs) on a market (Rabe 2006). As the role of emissions reduction in the United States has been considerably taken up by state governments (Karapin 2020; Peng et al. 2021), RPS policies have become one of the most widely used policy tools. First enacted in Iowa in 1983, RPS policies did not gain much traction until the late 1990s, with 38 additional states having adopted one since 1997. Ideally, these policies would both increase the supply of renewable energy at a low cost to consumers and initiate a “race-to-the-top” competition among states to increase their use of renewable energy.

However, despite their proliferation, the evidence for their ability to actually reduce emissions and increase the generation of renewable energy is mixed (Barbose et al. 2016; Carley 2009; Eastin 2014; Fischlein and Smith 2013; Prasad and Munch 2012; Upton and Snyder 2017). One major reason for this is due to the heterogeneity of policy design across state contexts. The specific energy targets, implementation stringency, and qualifying energy sources in RPS policies are at the discretion of the state and can range widely from one to the next. For instance, prior research has shown that policy stringency, such as sales or capacity mandates and higher renewable energy requirements, can significantly increase the efficacy of an RPS (Shrimali and Kniefel 2011; Yin and Powers 2010; Zhou and Solomon 2020).

In addition, some RPS policies may be expanded into “clean” or “alternative” energy standards to include nuclear energy, natural gas, “clean coal,” and other nonrenewable energy sources. For instance, West Virginia initially adopted their voluntary RPS in 2009 with a goal of 25 percent of electricity from renewable and “alternative” energy sources by 2025. However, compliance with the policy included coal, natural gas, and fuel derived from burning tires as eligible energy sources. Indeed, Jeff Herholdt, head of the West Virginia division of energy, described the state’s RPS saying, “We’re the only state that has an alternative portfolio standard that would be met with 100 percent coal” (Kunkel 2015). In contrast, California adopted its mandatory RPS in 2002 with a mandate of 60 percent of energy sales from renewable sources by 2030 and a goal of 100 percent by 2045. In addition, California’s mandate does not include any fossil fuels as eligible energy sources, relying mostly on conventional renewable sources. Thus, although these policies are widely used among U.S. states, they are far from equal, which raises the question of why this variation exists.

In this article, I focus specifically on this compliance aspect of RPS policy design. Conceptualized as a duality of “sticks” and “carrots,” I categorize policies into two types: mandatory and voluntary RPS.¹ For mandatory policies, requirements for energy suppliers are set by the state, and penalties, usually fines, can be imposed on those who fail to comply. Voluntary policies, on the other hand, are oriented around goals or targets for energy suppliers to meet with no penalties incurred for noncompliance. States may stick with one type of policy over the other or in some cases, switch between the two types of policies. Although the efficacy of mandatory policies may vary based on certain characteristics of the policy, they have still been shown to be generally more effective than voluntary ones (Shrimali and Kniefel 2011). Indeed, Martin and Saikawa (2017) compare a range of voluntary and mandatory state-level policies focused on emissions reduction (including voluntary and mandatory RPS), showing that mandatory policies consistently reduced emissions while voluntary policies did not.

Figure 1 shows the distribution of each of these types of policies adopted between 1997 and 2020. Although mandatory policies account for most of the policies adopted during this period, there are notable spikes in the adoption of voluntary policies. Specifically, in 2001, the year President Bush announced that the United States would not implement the Kyoto Protocol, and 2015, the year the Paris Agreement was adopted. Both of these are important moments in the climate politics of the United States, each plausibly placing pressure on states to appear to be embracing the transition away from fossil fuels.

Figure 1.

The distribution of the number of voluntary and mandatory renewable portfolio standards policies adopted by U.S. states, 1997–2020.

Literature and Hypotheses

Scholarship in sociology and political economy has theorized extensively on the relationship between market forces and the state in capitalist societies. In this article, I draw primarily on work building on the tradition of Polanyi (1944). Markets depend on the state for their existence and expansion, yet this conflicts with the state’s protection of society and nature from those same market forces. This tension ultimately shapes how markets are regulated by the state. In environmental sociology, scholars have proposed a similar argument, the “anthro-shift,” in which environmental risk reorients relationships between states, markets, and civil society in ways that shift between supporting and opposing environmental protection (Fisher 2024; Fisher and Jorgenson 2019). In addition, scholarship in economic sociology and political economy has followed in the Polanyian tradition to argue, against neo-classical economics, that markets are constructed with active state involvement (Block 2008; Block and Evans 2005; Fligstein 2001; Vogel 2018). This process gives rise to different policy domains, broadly defined as “a component of the political system that is organized around substantive issues” (Burstein 1991:328). These may be constituted by organizations and actors invested in a substantive issue who take each other into account as they formulate their activities (Laumann and Knoke 1987). Within policy domains, the relative power of government officials, firms, and workers are inscribed. Moreover, these are also structured around states’ ability to intervene in markets and the power of each group to shape the terms of intervention (Fligstein 2001). Thus, from this perspective, the field of policymaking can be seen as a contested terrain in which actors and coalitions compete for power and influence (Fligstein and McAdam 2011).

This scholarship offers a useful framework for understanding variation in RPS policies. In this article, I focus on the relative power of environmental organizations, fossil fuel producers, electric utilities, and political parties in the constitution of policy domains within U.S. states.

Industry and Environmental Organization Influence

Research in the social movements literature emphasizes three factors in analyzing the emergence and development of social movements: political opportunities, mobilizing structures, and framing processes (McAdam, McCarthy, and Zald 1996). Given the political hostility, hierarchical structure, and amorphousness of the issue itself, environmental social movements have historically struggled in each of these domains (McAdam 2017). In addition, fossil fuel interests constitute a powerful countermovement to environmental activism, with the ability to undermine and even reverse environmental policy victories (Stokes 2020).

However, environmental organizations have still managed to bring about some shifts in energy policy. In the United States, the presence of environmental organizations in a state increases the likelihood of adoption of a range of both renewable energy and energy efficiency policies (Ciocirlan 2008; Vasi 2009; Vasseur 2016) and the adoption of industry regulations (Kluttz 2019). Environmental movements have also utilized framing strategies to push forward environmental policies and transitions to renewable energy generation (Vasi 2006; Vasi and King 2019).

Social movement scholars have also argued that the ability to attract and deploy resources—for example, money, legitimacy, facilities, and labor—is central to social movement organizations’ enactment of social change (Jenkins 1983; McCarthy and Zald 1977). However, the degree to which resources are able to be acquired and deployed to achieve political goals is not universal but highly context-dependent (Meyer 2004). For instance, the political influence of campaign contributions from labor versus businesses can be weighed differently depending on the political context and issue visibility (Neustadtl 1990). Because the specifics of policy design can take a number of different forms, advocates (and opponents) of certain policy programs may tailor proposals to fit the opportunity structures of a particular setting (Martin 2010). The impact of environmental organizations is typically moderated by context-specific features, such as natural resources, and political and social factors (Vasi 2011). Environmental groups tend to focus their resources on locales where they have a greater chance of success. Indeed, Trachtman and Meckling (2022) show that environmental group lobbying in the United States is strongest in states with preferable political opportunities—Democratic party controlled and low-emission states.

Hypothesis 1a: States with higher amounts of political spending from environmental groups will be more likely to have mandatory RPS policies.

However, policy adoption is not necessarily followed by policy lock-in, as path dependence arguments would argue, because the prevailing status quo can still overpower policy change. Stokes (2020) argues that climate policies can make it through legislatures due to a “fog of enactment,” in which industry interests and their political allies fail to predict or understand the implications of a policy. However, these interests can still undermine or reverse policies, even after they have been passed, by lobbying legislators, court battles, and public campaigns. In other words, enactment does not guarantee policy change or lock-in because the existing political status quo endows industry interests with considerable power.

Indeed, industry actors often attempt to shape the distributional outcomes of climate policy to be more in their favor. There are numerous ways in which businesses engage in political activity (Walker and Rea 2014), which may vary according to the political and institutional context in which mobilization occurs. One common way in which companies gain political power is through monetary expenditures on political contributions and lobbying. Business interests acquire considerable power in the political process through their contributions to candidates (Clawson, Neustadtl, and Weller 1998). Indeed, prior research has shown that business mobilization through political campaign contributions in U.S. states can be conducive to the passage of more business-friendly policies (Witko 2013; Witko and Newmark 2005).

Hypothesis 1b: States with higher amounts of political spending from the oil and gas industry will be less likely to have mandatory RPS policies.

In addition to fossil fuel producers, utility companies are also an important actor with an interest in policy design. Stokes (2020) draws on cases from U.S. states to show how electric utilities, in addition to fossil fuel companies, worked to undermine RPS and net metering policies. Indeed, others have shown similar results, with utilities acting as obstacles to green energy policies (Brown and Hess 2016; Culhane et al. 2021). However, utility providers are not homogeneous but vary in their governance structures. These fall into three categories: publicly owned, cooperatively owned, and investor owned. Investor-owned utilities are the most common in the United States and tend to be the primary targets of RPS policies compared to other types of utility providers. Delmas and Montes-Sancho (2011) find that investor-owned utilities were more likely to invest in renewable capacity under an RPS mandate compared to publicly owned utilities. However, as Fischlein and Smith (2013) argue, this point overlooks how RPS targets vary across different types of utilities. Moreover, in some cases, such as municipal water sustainability, publicly owned utilities have been shown to be more effective than investor-owned ones (Homsy 2020). Indeed, RPS targets are not always directed at public or cooperatively owned utilities. When they are included, the targets are often lower than those aimed at investor-owned utilities. Thus, public and cooperatively owned utilities may respond to a possible RPS mandate differently compared to investor-owned utilities—or at least be less likely to object to one. A greater presence of public and cooperatively owned utilities might then lead to less opposition to mandatory RPS policies.

Hypothesis 2a: States for which investor-owned utilities account for a higher portion of energy sales will be less likely to have mandatory RPS policies.

Hypothesis 2b: States for which publicly owned utilities account for a higher portion of energy sales will be more likely to have mandatory RPS policies.

Hypothesis 2c: States for which cooperatively owned utilities account for a higher portion of energy sales will be more likely to have mandatory RPS policies.

Economic Dependence on Oil and Gas Production

Another facet of the fossil fuel industry’s power is rooted in political jurisdictions’ economic dependence on oil and gas production. Scholars have approached this relationship from various angles but ultimately arrive at similar conclusions. The position of fossil fuel companies within a particular economic context can grant them privileged access to the political process. Not only do fossil fuel companies serve as an important source of tax revenue for the state, but they are also an important source of jobs. This can lead to unusual coalitions between capital and labor, unified in their opposition to policies that threaten fossil fuel production and, in turn, profits and jobs (Mildenberger 2020).

In international political economy, this is referred to as the “structural power” of fossil fuel companies (Newell and Paterson 1998). Because these companies play a crucial role in the functioning of markets both domestically and globally, they are in a position to shape the terms of climate policy in ways that preserve their interests. However, there are certain contexts in which this power is diminished. Hanegraaff (2023) shows that the structural power of business is reduced in countries that are more developed, less reliant on fossil fuels, more democratic, and more vulnerable to climate change.

In organizational theory, Pfeffer and Salancik (2003) argue that resource dependence shapes relations between organizations, and that dependence on critical resources can serve as a basis for exerting influence. Kluttz (2019) applies this perspective to the case of hydraulic fracking regulation in U.S. states, arguing that states that are more economically dependent on oil and gas production are less likely to regulate the industry when the resources for fracking are available.

This relationship between fossil fuel companies and state energy policy also affects the adoption and characteristics of RPS policies. States, particularly conservative ones, with higher levels of fossil fuel production are less likely to adopt an RPS policy (Thombs and Jorgenson 2020) and are more likely to prefer weaker energy standards or have no policy at all (Vasseur 2014). Furthermore, states in which fossil fuel companies account for a higher portion of employment are also less likely to adopt RPS policies (Coley and Hess 2012). In applying these theories to the comparison of U.S. states, I argue that states in which oil and gas production constitutes a greater portion of the state’s economic output would be less likely to possess mandatory renewable energy policies.

Hypothesis 3a: States that are more economically dependent on oil and gas production will be less likely to have mandatory RPS policies.

Furthermore, fossil fuel producers’ structural power may be directed not only toward opposing mandatory policies but also toward a program of strategic accommodation, in which weaker climate policy options are preemptively endorsed to reduce the risk of more radical climate policies being passed in the future (Vormedal, Gulbrandsen, and Skjærseth 2020). Indeed, fossil fuel producers could push states to enact weaker, voluntary policies to accommodate pressure from environmentalist critics and to hedge against the risk of more radical environmental policy. Similar to how firms use “signals” to communicate their priorities to investors (Connelly et al. 2011), states may use voluntary RPS policies to simultaneously signal their commitment to fossil fuel interests while also “ceremonially” following other states in passing climate policies (Meyer and Rowan 1977).

Hypothesis 3b: States that are more economically dependent on oil and gas production will be more likely to have voluntary RPS policies.

Political Allies and Opponents of Climate Policy

Prevailing ideology and the political party control over state governments have also been raised in explaining differences in states’ renewable energy policy adoption. The success of social movement organizations, such as environmental groups, in impacting policy is strongly aided by the presence of elite allies (Soule and Olzak 2004). Indeed, Democratic party power in state governments strongly impacts both the overall adoption of RPS policies and the strength of those policies (Trachtman 2020). Partisan control also has consequences beyond the power of elected officials by serving as the context in which groups develop curated strategies and face opportunities and constraints in their efforts to shape policy (Martin 2010; McAdam et al. 1996). In addition, these processes can also mold the qualitative aspects of policy in ways that align with certain political programs and ideological commitments (Vasseur 2016).

Successful political mobilization by different actors at the state level is shaped by the opportunities presented in this context, which has historically not been favorable to environmental organizations. In the United States, environmental groups face the challenge of an American public, whose belief in climate change strongly falls along partisan lines and whose concern about climate change ranks well below other political issues (Egan and Mullin 2017). The rise of an increasingly powerful and conservative Republican party along with a powerful fossil fuel lobby has placed serious constraints on the successful mobilization of grassroots environmental movements (McAdam 2017). Furthermore, in the case of RPS policy, the partisan divide over policy adoption is exacerbated for Republican states in which fossil fuel production is a major industry (Thombs and Jorgenson 2020).

Prior research has also shown how qualitative distinctions in the energy policies that states adopt highlight important ideological factors. Hess, Mai, and Brown (2016) find that limiting the role and power of government, reducing regulations, cutting costs for businesses and consumers, and supporting the private sector are important ideological reference points for state politicians in determining their support for renewable and energy efficiency policies. In addition, they note that policies aligned with these values consistently have higher levels of support compared to government mandates. Similarly, Coley and Hess (2012) show that Republicans are more likely to vote in favor of green energy laws when they are framed as not posing any additional tax burdens, such as with Property Assessed Clean Energy (PACE) financing. In addition, renewable energy policies configured as regulatory mandates (compared to voluntary incentives) are less likely to pass states that have embraced a neoliberal policy program, such as right to work policies and cuts to welfare benefits (Vasseur 2016). Given this impact of partisan politics in state government, I predict that mandatory RPS policies should be more likely in states where the Democratic party has more power in state government.

Hypothesis 4: States in which the Democratic party has greater control over the state government will be more likely to have mandatory RPS policies.

Data and Methods

To test the outlined hypotheses, I construct an original longitudinal data set comprised of state-level policies and other characteristics for the years 1997 to 2020. I begin the data set with the year 1997 because this marks (1) the starting point for the spread of RPS policies in the United States² and (2) the beginning of a global shift in climate politics with the inaugural Conference of Parties (COP-1) meeting in Kyoto in 1997. I end the data set with the year 2020 for data availability reasons and because it is the year with the most recent RPS policy development.³ The unit of analysis in this data set is the state-year, with 48 states across 24 years, resulting in a total sample of 1,152 state-years.⁴

Dependent Variables

To measure the effect of political and economic forces on different RPS outcomes, I include three binary dependent variables. These indicate whether a given state-year has (1) any RPS policy, (2) a mandatory RPS policy, or (3) a voluntary RPS policy. For each variable, states are coded as a 1 for the years in which that policy is in effect. Because some states change the type of policy that they pursue, a single state may have values for both mandatory and voluntary variables at different points in time (e.g., voluntary policies for some years and then mandator policy for the years after). Data for these variables are collected from the North Carolina Clean Energy Technology Center’s Database of State Incentives for Renewables and Efficiency at North Carolina State University.⁵

Independent Variables

Political expenditure of industry and environmental groups

I use material contributions to political groups, actors, and causes as a basis for measuring actors’ political influence (Kluttz 2019). Specifically, I track the total political expenditure of environmental groups and the oil and gas industry to measure their relative influence (Hypotheses 1a and 1b). For each group, I calculate this as the logged sum of campaign and committee contributions, lobbying, and independent political expenditures.⁶ Contributions account for the majority of spending among these three categories. The latter two, lobbying and independent spending, occur with less frequency across state-years and have later starting points for data availability. Lobbying data begin in 2002, and independent spending data begin in 2005. These data are collected from the National Institute on Money in Politics (NIMP), which tracks state-level political donations and the industry/sector with which the donor is associated.⁷

Utility sales

Because ownership of utility providers varies across states, I include three variables measuring the market share of the different models of utility ownership. These consist of investor-owned (Hypothesis 2a), publicly owned (Hypothesis 2b), and cooperatively owned utilities (Hypothesis 2c). They are measured by taking the sum of energy sales (in megawatt-hours) for each utility ownership model as a percentage of the total energy sales in a given state-year. The data for these variables are collected from the U.S. Energy Information Administration.⁸

Oil and gas contribution to state GDP

Because fossil fuel production can play an important economic role in certain states, I include a measure of states’ economic dependence on oil and gas production (Hypotheses 3a and 3b). This is measured, in percentage terms, as the oil and gas sector’s contribution to real GDP in a given state-year (chained 2012 dollars). These data are collected from the U.S. Bureau of Economic Analysis’s Regional Economic Accounts.⁹

Democratic party control in state government

As prior research has shown, political party control plays a major role in shaping the direction of energy policy (Coley and Hess 2012; Vasseur 2014, 2016). To measure this, I create a categorical variable denoting the political offices over which the Democratic party has control in a given state-year (Hypothesis 4). The first category indicates whether the Democratic party controls only the office of the governor. The second category indicates whether the Democratic party controls only the state legislature. Finally, the third category indicates whether the Democratic party controls both the office of the governor and the state legislature. Data on state legislatures are collected from the National Conference of State Legislatures, which compiles political party majority results of biyearly state elections.¹⁰ Data on governors are collected from the Book of the States, compiled by the Council of State Government.

Controls

I include two control variables. First, I control for variation in state affluence using the median household income (2020 dollars) in a state, for which I use data from the U.S. census. Second, I account for the influence of political allies holding national political office by using a binary variable to control for years in which the United States had a Democratic president.

Analytic Strategy

Although prior quantitative research on RPS policies has primarily focused on first policy adoption (Thombs and Jorgenson 2020; Vasseur 2014), I argue that this does not capture cases of states that change qualitative aspects of their policy type over time. To address this, I estimate a multinomial logistic regression model with fixed effects, which controls for unobserved heterogeneity between states. Because this approach tests the likelihood of the presence of each type of RPS policy in a given state-year, it accounts for states that abandon one type of policy type in favor of another along with the shifts in the characteristics of the state that may drive that change. Furthermore, I lag all of the covariates by one year to capture their causal effect on the policies that states possess in a given year.

Results

Descriptive Statistics

Descriptive statistics and a correlation matrix are presented in Tables 1 and 2, respectively. For the dependent variables, roughly half (53 percent) of the state-years in the sample possess some form of RPS policy. As noted previously, most of these (40 percent) are mandatory policies, with the remaining 13 percent consisting of voluntary policies. Furthermore, 10 states switch the type of RPS policy that they possessed during this period. Five of these switched from a voluntary to a mandatory policy (Hawaii, Illinois, Minnesota, Missouri, and Virginia), and four switched from a mandatory to a voluntary policy (Kansas, Montana, Wisconsin, and Texas). Only one state (West Virginia) dropped their RPS policy altogether.

Table 1.

Descriptive Statistics.

Variables	Mean	SD	Minimum	Maximum
Any RPS policy (DV)	0.53	0.50	0	1
Mandatory RPS policy (DV)	0.40	0.49	0	1
Voluntary RPS policy (DV)	0.13	0.33	0	1
Environmental organization political expenditure (log)^a	6.95	5.22	0	17.16
Oil and gas political expenditure (log)^a	9.30	4.36	0	17.74
Oil and gas share of state GDP	1.92	4.67	0	40.69
Investor-owned utility sales (% of total)	69.28	23.08	0.06	100.00
Publicly owned utility sales (% of total)^b	15.65	16.31	0.20	96.78
Cooperately owned utility sales (% of total)^c	15.32	14.04	0.01	73.57
Democratic party power	1.20	1.18	0	3
Democratic party president	0.54	0.50	0	1
Median income	62,034.44	10,100.94	38,876	96,765

Note: N = 1,152 (48 states, 24 years). RPS = renewable portfolio standards; DV = dependent variable.

N = 1,050.

N = 1,119.

N = 1,071.

Table 2.

Correlation Matrix.

	1	2	3	4	5	6	7	8	9	10	11	12
1. Any RPS policy (DV)	1
2. Mandatory RPS policy (DV)	0.774	1
3. Voluntary RPS policy (DV)	0.358	−0.314	1
4. Environmental organization political expenditure (log)	0.224	0.246	−0.032	1
5. Oil and gas political expenditure (log)	0.042	0.036	0.009	0.569	1
6. Oil and gas share of state GDP	−0.038	−0.185	0.216	−0.046	0.225	1
7. Investor utility sales	0.076	0.133	−0.082	−0.070	−0.126	−0.348	1
8. Public utility sales	−0.024	0.050	−0.110	0.154	0.016	−0.078	−0.708	1
9. Cooperative utility sales	−0.116	−0.282	0.230	−0.138	0.054	0.534	−0.598	−0.014	1
10. Democratic party power	0.229	0.363	−0.192	0.076	−0.025	−0.166	0.158	0.093	−0.210	1
11. Democratic party president	0.047	0.052	−0.006	0.049	0.064	0	0.008	0.007	−0.009	0.045	1
12. Median income	0.393	0.340	0.088	0.160	−0.103	−0.018	0.179	−0.072	−0.120	0.173	−0.153	1

Note: RPS = renewable portfolio standards; DV = dependent variable.

Table 1 also highlight the descriptive statistics for the covariates and controls. Unsurprisingly, the mean logged political expenditure for oil and gas is higher ($9.30, SD = $4.36) than for environmental organizations ($6.95, SD = $5.22). Mean economic dependence on oil and gas is 1.92 percent of state GDP (SD = 4.67 percent), with the highest state-year being Alaska in 1997 (40.69 percent). For utility sales, investor-owned utilities are the most common of the three types, with a mean of 69.28 percent (SD = 23.08 percent), a minimum of 0.06 percent, and a maximum of 100 percent. This is followed by publicly owned utilities, with a mean of 15.65 percent (SD = 16.31 percent), a minimum of 0.20 percent, and a maximum of 96.78 percent. Finally, cooperatively owned utilities are the least common, with a mean of 15.32 percent (SD = 14.04), a minimum of 0.01 percent, and a maximum of 73.5 percent. Democratic party control is weaker on average for the state-years in the sample. Democratic party control of the White House is pretty evenly split across state-years (54 percent). The median income across state-years is $62,034 (SD = $10,101), with the highest being Maryland in 2019 ($96,765) and the lowest being Mississippi ($38,876).

Regression Results

Estimates of the logistic regression models are reported in exponentiated form as odds ratios in Table 3. Models 1 through 3 list the results for each dependent variable—any policy, voluntary policy, and mandatory policy, respectively. I use three variations (e.g., Model 1a, 1b, 1c) to separate each type of utility ownership. In this section, I focus primarily on Models 2 and 3 because these fully capture the differences between the two types of RPS policies.

Table 3.

Logistic Regression with Fixed Effects Analysis of Renewable Portfolio Standards Policies, 1997 to 2020.

	Any Policy (Model 1a)	Any Policy (Model 1b)	Any Policy (Model 1c)	Voluntary (Model 2a)	Voluntary (Model 2b)	Voluntary (Model 2c)	Mandatory (Model 3a)	Mandatory (Model 3b)	Mandatory (Model 3c)
Environmental group political expenditure (log)	1.183*** (0.0419)	1.173*** (0.0361)	1.120* (0.0508)	1.055(0.0444)	1.059(0.0492)	1.005(0.0464)	1.158*** (0.0409)	1.184*** (0.0432)	1.124* (0.0511)
Oil and gas political expenditure (log)	0.940(0.0374)	0.959(0.0339)	0.989(0.0528)	1.035(0.0479)	1.022(0.0550)	1.056(0.0552)	0.921(0.0395)	0.912* (0.0411)	0.936(0.0522)
Oil and gas share of state GDP	1.209* (0.117)	1.566*** (0.203)	1.172(0.145)	1.354** (0.152)	1.906*** (0.360)	1.266* (0.145)	0.587** (0.117)	0.682* (0.116)	0.311*** (0.0776)
Investor-owned utility market share	0.593*** (0.0400)			0.956(0.0365)			0.934*** (0.0176)
Publicly owned utility market share		1.093(0.0540)			0.417*** (0.0889)			1.274*** (0.0753)
Cooperative-owned utility market share			8.971*** (2.372)			1.393*** (0.101)			2.587*** (0.350)
Democratic party power
Democratic governor	1.075(0.327)	1.029(0.275)	2.032(0.863)	0.154*** (0.0687)	0.179*** (0.0911)	0.101*** (0.0523)	2.598** (0.784)	2.666** (0.828)	2.998** (1.070)
Democratic state legislature	2.219(1.280)	3.124* (1.634)	1.861(1.549)	0.273(0.187)	0.774(0.588)	0.126* (0.103)	7.456*** (4.021)	5.187** (2.893)	4.106* (2.772)
Democratic governor and state legislature	4.599** (2.142)	4.819*** (2.064)	10.63*** (6.652)	0.423(0.268)	0.401(0.312)	0.155* (0.118)	8.842*** (3.822)	9.067*** (4.073)	12.50*** (6.500)
Democratic party president	1.848** (0.410)	1.732** (0.352)	2.299** (0.703)	1.488(0.410)	1.055(0.335)	1.487(0.451)	1.546(0.352)	1.540(0.360)	1.435(0.401)
Median income	1.000(0.00003)	1.000(0.00003)	1.000(0.00004)	1.000*** (0.00003)	1.000* (0.00004)	1.000** (0.00004)	1.000(0.00003)	1.000(0.00003)	1.000** (0.00004)
Observations	718	692	680	377	351	358	558	539	520

Note: Exponentiated coefficients; standard errors in parentheses. Independent and control variables are lagged 1 year.

p < .05. **p < .01. ***p < .001.

As the results show, there are significant differences between states that possess mandatory RPS policies and states that possess voluntary RPS policies. Starting from the top, environmental organizations’ political spending significantly increases the likelihood of states possessing mandatory policies but not voluntary ones. In contrast, oil and gas spending places negative pressure on the likelihood of states possessing mandatory policies only when accounting for publicly owned utility market share (β = 0.912, SD = 0.0411, ρ < 0.05) while having no significant effect on voluntary policies. This confirms Hypothesis 1a and partially confirms Hypothesis 1b, which predict that mandatory policies would be more likely in states with greater amounts of environmental political spending (Hypothesis 1a) and less likely in states with higher oil and gas spending (Hypothesis 1b).

The variants of Models 2 and 3 highlight the differential effects of utility ownership types. States in which investor-owned utilities have a greater market share are less likely to possess a mandatory policy (β = 0.934, SD = 0.0176, ρ < 0.001) while having no significant effect on voluntary policies. A greater division is seen in Models 2b and 3b, which shows publicly owned utilities having opposite effects for mandatory and voluntary policies. States in which publicly owned utilities have a greater market share are more likely to possess a mandatory policy (β = 1.274, SD = 0.0753, ρ < 0.001), whereas the opposite is true for voluntary policies (β = 0.417, SD = 0.089, ρ < 0.001). Cooperatively owned utility market share has a positive effect on both mandatory (β = 2.587, SD = 0.350, ρ < 0.001) and voluntary policies (β = 1.393, SD = 0.101, ρ < 0.001), although the effect is stronger for the former. These results confirm Hypotheses 2a and 2b and partially confirm hypothesis 2c. In addition, these add more depth to the literature, which has focused on utility opposition to renewable energy policy (Brown and Hess 2016; Culhane et al. 2021; Stokes 2020).

Table 3 also shows an inverse effect of oil and gas production on the type of RPS policies that states are likely to possess. As Models 3a through 3c show, higher oil and gas contributions to state GDP consistently decrease the likelihood of a state possessing a mandatory RPS policy, supporting Hypothesis 3a. Furthermore, this effect is reversed for voluntary policies (Models 2a–2c), with higher oil and gas contributions to state GDP consistently increasing the likelihood of possessing those policies, supporting Hypothesis 3b. This contrasts with prior research suggesting that greater state-level fossil fuel production either increases the likelihood of RPS adoption (Vachon and Menz 2006) or has no significant effect (Huang et al. 2007). However, this is consistent with Vasseur (2014), who shows fossil fuel production levels to drive similar variation in states’ adoption of stringent renewable energy policies. Moreover, comparing the results from Models 2 and 3 to the results for Models 1a through 1c demonstrates the importance of qualitative distinctions between types of RPS policy. Simply focusing on states with any RPS policy would yield misleading conclusions about the role of fossil fuel production in energy policy decisions, suggesting that it always has a positive effect. Drawing attention to different types of these policies shows that this is not the case.

The results also report strong support for Hypothesis 4, which predicts that greater Democratic party power in state government will increase the likelihood of states’ possession of mandatory RPS policies. As Models 3a through 3c show, political party power is by far the strongest predictor of mandatory policy possession. In each model variant, this effect increases incrementally for each level of state political power under Democratic party control, with the strongest being full control of the office of the governor and state legislature. Voluntary policies, on the other hand, not only have a consistently negative coefficient—although inconsistently significant—but also a comparatively weaker relationship to politics. Similar to the discussion of results for oil and gas contributions to GDP, if one were to simply look at states with any RPS policy (Models 1a–1c), they would wrongly conclude the effect of political party control is inconsistent and only matters in extreme cases when there is full Democratic party control. This further highlights the importance of drawing attention to variations in state-level policies.

Discussion and Conclusion

Although the majority of states in the United States possess some form of RPS, the content of these policies can vary widely. The aim of this article has been to explain why this variation exists, drawing in particular on theories from economic sociology and political economy. This contributes to the literature on state-level energy policies in the United States generally and RPS policies in particular. The results here build on the known forces of variation in RPS enforcement stringency (Thombs and Jorgenson 2020; Vasseur 2014) by incorporating the role of utilities.

Many of the results here are consistent with the findings of others. For states that possess mandatory RPS policies, the policy landscape is dominated by the prototypical coalition of climate policy allies in the United States: environmental groups and Democratic party politicians. Viewed as a contested terrain in which coalitions compete for power (Fligstein and McAdam 2011), the conflict that occurs among these coalitions results in the establishment of a dominant policy program. However, as the results show, the really prominent force here appears to be political party power, suggesting that such conflict is heavily rooted in partisan politics. In contrast, states that possess voluntary RPS policies gesture toward state protection of the environment while still giving the market considerable freedom. In these states, the Democratic party and environmental organizations may exert some pressure but lack the power to establish a ruling coalition. Rather than run the risk of having this coalition succeed in enacting more stringent RPS, fossil fuel producers preemptively support weaker versions of these policies in the form of voluntary RPS. In other words, these policies are acceptable because they do not fundamentally threaten fossil fuel interests and may offer insurance against the risk of more stringent mandatory policies in the future.

Utility providers also showed a split in their propensity for mandatory policies. Instead of constituting a uniform block that either opposes or supports RPS, the results here show variation according to states’ composition of investor-, public-, and cooperative-owned utilities. Possession of a mandatory RPS was more likely when publicly owned utilities had a higher market share and less likely when investor-owned utilities had a higher market share. This should add some more depth to the literature, which has focused on the ways in which utilities act as obstacles to renewable energy policy (Brown and Hess 2016; Culhane et al. 2021; Stokes 2020). Indeed, this might be the case mostly with investor-owned utilities, which makes logical sense given the differences in how RPS are applied to investor-owned utilities compared to other types. In addition, this also likely reflects differences in the relevance of market incentives between public and private institutions.

This article does possess some limitations that could pose as opportunities for additional research. The operationalization of environmental organization activity only captures the highly organized facets of the environmental movement. Further research could explore how protests and other activities outside of the formal political process impact states’ energy policies. In addition, I only draw attention to qualitative distinctions in the implementation stringency of RPS policies, but one could be even more nuanced than that. Future research could dig further into the variation among these policies by focusing on features such as the specific energy targets that they aim to attain. Also, a number of questions still remain on the role of electric utilities in shaping energy policy. Future research could further disaggregate the providers in this sector to see how variation in strategies, geographical location, transition capacity, political alliances, and so on explain their activity.

Footnotes

Acknowledgements

I am grateful for the helpful comments from Neil Fligstein and Marion Fourcade on this paper.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was financially supported by the National Science Foundation’s Graduate Research Fellowship. Any findings, opinions, or conclusions discussed here do not necessarily reflect those of the National Science Foundation. Any errors are the responsibility of the author alone.

ORCID iD

Thomas Haseloff

Notes

Author Biography

Thomas Haseloff is a PhD candidate in sociology at the University of California, Berkeley. His research covers a range of topics related to political economy and economic sociology, with a particular interest in digital technologies and finance. His dissertation project examines the influence of the Silicon Valley technology sector on financial institutions after the 2008 financial crisis.

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Who Shapes Environmental Policy? Power and Politics in the Renewable Portfolio Standards of U.S. States,1997–2020

Abstract

Keywords

Renewable Portfolio Standards in the United States

Literature and Hypotheses

Industry and Environmental Organization Influence

Economic Dependence on Oil and Gas Production

Political Allies and Opponents of Climate Policy

Data and Methods

Dependent Variables

Independent Variables

Political expenditure of industry and environmental groups

Utility sales

Oil and gas contribution to state GDP

Democratic party control in state government

Controls

Analytic Strategy

Results

Descriptive Statistics

Regression Results

Discussion and Conclusion

Footnotes

Acknowledgements

Funding

ORCID iD

Notes

Author Biography

References