Social Problems, 2016, 63, 284-301 doi 10.1093socprospw00.docx

Social Problems, 2016, 63, 284-301
doi: 10.1093/socpro/spw007
Article O X FO R D
Incentives or Mandates? Determinants of
the Renewable Energy Policies of U.S.
States, 1970-2012
Michael Vasseur
RAND Corporation
ABSTRACT
Why might states adopt policy instruments of one type over
another, and how does this
choice impact the overall portfolio of policy instruments a state
adopts? To address these
questions this article examines renewable energy policy
instrument adoption by U.S. states
and argues that states adopt instruments of different types based
on their state-level eco-
nomic, political, institutional, and cultural characteristics. I test
these claims by examining
the tax incentive- and regulatory mandate-based policy
instruments adopted to promote re-
newable energy generation by U.S. states over a 40-year period.
Using random effects
Poisson regression analysis, I find that state affluence,
environmental movement organiza-
tion density, and fossil fuel production predict the number of
policies a state is likely to

adopt, while an affinity for a neoliberal ideology, U.S. senators
environmental voting re-
cords, and prior policy actions predict the types of policies a
state adopts. These results re-
inforce perceptions of economic factors as key predictors of
renewable energy policy, but
also highlight the importance of less frequently examined
cultural factors for explaining a
state’s portfolio of policies. These analyses offer a robust
picture of the relationship between
tax incentive and regulatory mandates, the two types of
programmatic approaches that have
dominated many policy domains in the United States over the
past 40 years.
KEYWORDS: renewable energy; fiscal policy; subnational
politics; regulation;
neoliberalism.
Research on renewable energy policy adoption has tended to
focus on how U.S. states come to adopt
a particular policy instrument at a given point in time (Chandler
2009; Coley and Hess 2012; Daley
and Garand 2005; Fowler and Breen 2013; Huang et al. 2007;
Vachon and Menz 2006; Yi and
Feiock 2012), or how a specific energy industry develops in a
state (Campbell 1988; Jasper 1990;
Podobnik 2006; Sine and Lee 2009; Vasi 2006, 2009, 2011).
Given that most U.S. states adopt mul-
tiple, often very different, policy instruments within the same
domain, this scholarly focus on single
policy instrument adoption sidelines important questions. For
all we have learned about how states
adopt individual policy instruments, we know much less about
the processes that shape the overall

The author wishes to thank Brian Steensland, Clem Brooks,
Patricia McManus, Fabio Rojas, and the anonymous Social
Problems re-
viewers for insightful comments and suggestions on prior drafts.
This research was assisted by a fellowship from the Dissertation
Proposal Development Fellowship Program of the Social
Science Research Council with funds provided by the Andrew
W. Mellon
Foundation. A prior version was presented at the 2014 American
Sociological Association Annual Meeting. Direct
correspondence
to: Michael Vasseur, RAND Corporation, 4570 Fifth Avenue,
5600, Pittsburgh, PA 15213. E-mail: mvasseur(S)rand.org.
© The A uthor 2016. Published by Oxford University Press on
behalf of the Society for the Study o f Social Problems. All
rights reserved.
For permissions, please e-mail: journals.permissions(2)oup.com
. 284
Determinants o f the Renewable Energy Policies o f U.S. States
• 285
portfolio of policies that states adopt. An accounting of a state’s
portfolio of policies is vital to under-
standing how policy instruments relate to each other. This
omission is potentially significant because
the factors that influence how many policy instruments a state
adopts in a policy domain may not be
the same as those influencing the types of policy instruments a
state adopts. Furthermore, examining
the adoption of individual policy instruments in isolation
muddles the relationships between the in-

struments themselves. Accounts of policy making focused on
consistent state action emphasize the
process by which a state comes to favor policy instruments of
one type over all others. In this view
only a limited number of policy instruments will be adopted in a
state, and the expectation is that
they will be similar to each other. At best, the resulting
instruments might be unrelated to each other,
but it is seen as more likely that the adoption of a policy
instrument of one type decreases the odds
of a state adopting a different type of policy instrument. A shift
to an analysis of a state’s entire port
folio of policies allows for the possibility that state policy
actions might be consistent with a more
general orientation.
Questions of policy instrument type are of increasing
importance in the polarized political context
of the contemporary United States. Specifically, in a political
climate where a policy’s relationship to
broader narratives surrounding taxation or regulation is central
to its feasibility, it is important to
understand how states have adopted their portfolio of policies
vis-a-vis incentives and mandates. The
renewable energy policies of U.S. states offer an opportunity to
examine incentive- and mandate-
based policies in a well-delimited policy domain. This
distinction is especially important given the
central role of states in addressing global climate change in the
U.S. context. Even when spurred on
by federal pressure to date it has been left up to various states
to craft their own plans for emission re-
duction (EPA 2014). With no signs that climate change will
emerge as an issue addressed by federal
legislation in the near future a more complete understanding of
state’s portfolios of policies will be

key. To do this, I build on and extend existing accounts of the
determinants of energy policy.
I follow a perspective that argues that patterns of state policy
instrument adoption result from a
combination of state-level political interests, policy-making
institutions, and ideational factors such as
culture, discourse, or policy ideas (Beland and Cox 2011;
Campbell 2002; Lieberman 2002;
Padamsee 2009). Interest-based explanations focus on political
actors, including both politicians and
outside forces. These accounts examine how actors use policy to
improve their chances at reelection.
Institutional accounts show that the structure of formal policy-
making institutions influences policy
adoption. Ideational accounts focus on how actors interpret the
problems and policy solutions being
considered, and how views of legitimacy both constrain and
enable policy choices.
Research on energy policy has typically not accounted for
political explanatory factors beyond
those concerning electoral interests. This omission is not
surprising; existing research on renewable
energy has been historically dominated by economically
deterministic views. Until relatively recently
the distribution of energy producing resources was all that was
considered important for understand-
ing a state’s energy policy (see Lowry 2008 for a discussion and
critique of these views). Building
upon this existing approach and its insights, a logical next step
is to account for the politics of the
elites controlling access to these resources and the potential
importance of states’ broader institu
tional and cultural contexts.

Research in other policy domains has shown that political
institutions and culture impact the kind
of policy instruments a state adopts. To the extent that policy
actions are consistent with a broader
orientation or strategy of action, institutional and cultural
factors shape a state’s portfolio of policies
through a variety of mechanisms. Whether though specifying
the means seen as appropriate to reach
some policy end (Dobbin 1994), establishing separate policy
tracks (Hacker 2002), forming styles of
policy action (Jasper 1990), or locking states into a path
through feedback mechanisms (Pierson
2000), institutional and cultural factors influence policy
adoption. Recognizing these types of influ-
ences means that the content of a state’s portfolio of policies is
not simply a hasty assembly of what-
ever problems require attention at the moment and what
solutions are in the air at a given point in
time (Baumgartner and Jones 1993; Kingdon [1995] 2004).
Instead, policy content is a product of
286 . Vasseur
the structure of a state’s economy, the features of its political
landscape, and the affinities established
by its institutions and political culture. As analysis moves
beyond the adoption of individual policies
and to an examination of the broader portfolio of policies held
by states, assessing the impact of these
institutional and cultural factors is vital.
RENEWABLE ENERGY P O L I C I E S IN U.S. STATES
Renewable energy policy in the United States serves as
excellent opportunity to examine policy port-

folios, as states have taken a variety of actions in this domain.
These actions tend towards one of two
strategies of policy action: tax incentives or regulatory
mandates.1 These policy strategies assume dif-
ferent views of how social change occurs. Incentives rely on an
aggregation of individual actions to
create change, while mandates rely on top-down demands levied
by the state. Importantly, both strat-
egies are centered on the goal of producing more renewable
energy within a state, even if they do so
by different means.
How do states choose between incentives and mandate strategies
when adopting policy instru-
ments? This question is central in research within the
framework of fiscal sociology (Martin,
Mehrotra, and Prasad 2009). Research in this area examines
how governments, especially in the
United States, forge social policy through the tax code,
specifically incentives defined as tax expend-
itures (Hacker 2002; Howard 1997). Tax expenditures are
income that would be collected by the
government if not for exemptions added to the tax code for
behaviors the government wishes to pro-
mote, such as buying a home or having children. While
generally thought of as equivalent to direct
state spending from a budgetary standpoint (see Prasad 2011,
however), tax expenditure policies arise
in the area of social policy through different conditions than
more traditional state interventions.
Factors such as divided partisan government, the relatively
limited involvement of interest groups or
social movements, and the use of tax expenditures in past policy
domains are all associated with an
increased likelihood of a tax expenditure being adopted (Hacker
2002; Howard 1997, 2007, 2009).

A more socio-legal perspective highlights that these differences
are what lead to the more desirable
qualities of using the tax code to promote social change. These
include the fact that using existing
political infrastructure in the tax code, compared to creating a
new governance program, is more effi-
cient, as it does not require new administration. It is also more
equitable as it is harder for any one
interest group to dominate the program’s administration
(Zelinsky 1993). In this view, the primary
difference between direct spending and tax expenditures is the
reaction a given policy form elicits
from lawmakers and citizens (Zelinsky 2004). Regardless of the
paradigm employed, scholars of so-
cial policy have identified important differences in the process
of adopting tax incentive-based policies
compared to more direct state actions.
U.S. states have adopted policies to promote the generation of
renewable energy that fit two
broader categories. The first category of policy widely adopted
by U.S. states is tax incentives. These
include deductions, credits, or rebates on personal or business
taxes for renewable energy generation,
or the remittance of property or sales taxes for the purchase of
renewable energy generation systems.
These policies use the tax code to provide incentives for the
generation of renewable energy through
the state avoiding the collection of revenues it would otherwise
be entitled to. These policies are de-
signed to provide an enticement for individuals or corporations
to enter the renewable energy mar-
ket, without the direct state intervention in shaping such a
market.

The second category of widely adopted policy is regulatory
mandates. These policies directly
intervene in the relationship between utility companies and
consumers. One example is energy port-
folio standards that mandate that electric utilities produce a
certain percentage of their electricity
from renewable sources or face a penalty. Other mandate
policies include those that require a disclos-
ure of the sources used in a utility company’s electricity
generation, and those that force utility
1 As of 2012, all but four states (Alabama, Arkansas,
Mississippi, and Wyoming) have adopted at least one of these
policies.
Incentive policy adoption began in the mid-1970s. Mandate-
based policies became widely adopted in the mid to late 1990s.
Determinants o f the Renewable Energy Policies ofU.S. States
287
Table 1. Categories of Renewable Energy Policies adopted by
U.S. States
Tax Incentives Regulatory Mandates
Income tax Energy portfolio standards
Corporate tax Cap and trade program
Sales tax Public benefits funds
Property tax Generation source disclosure
Tax rebate Green power purchasing option
companies to offer consumers the option to purchase power
from green sources for a fee. Two other
policies in this area, public benefit funds and cap-and-trade

programs, are known as consumption
taxes on electricity. In the case of public benefits funds, this is
a surcharge on each unit of electricity
consumed. This surcharge is normally set aside for a fund
whose sole purpose is to fund new renew-
able energy projects within the state. Cap-and-trade policies do
not directly tax energy consumption,
but instead tax carbon emissions, producing the same end result.
All of these policies involve more
coercive state action compared to incentive-based policies.
Importantly, regardless of the type of action used, these policies
represent the exercise of state
power; in neither case is the development of renewable energy
left entirely to the market. Currently,
producing energy from renewable sources costs more than doing
so from fossil fuels. Policy elites rec-
ognize this and know that without state action renewable energy
production is unlikely to increase at
a substantial rate. If states want to produce more renewable
energy, they must act. These actions vary
in their content, but all of these policy instruments incorporate
aspects of market logic and are funda-
mental examples of state action. Table 1 summarizes the
policies and categories examined in this
article.
Impact o f Interests, Institutions, and Ideational Factors on
Renewable Energy Policy
Research on energy policy has overwhelmingly focused on
economic and political interests in predict-
ing the adoption of regulatory mandate policies (for an
exception, see Fowler and Breen 2013).
States are thought to be more likely to adopt renewable energy
policies if they have available renew-
able energy resources (Chandler 2009; Vasi 2006) and do not

produce fossil fuels (Coley and Hess
2012; Huang et al. 2007; Vachon and Menz 2006). Other
research highlights the importance of state
affluence as a predictor of energy and environmental policies
(Daley and Garand 2005; Ringquist
1993; Vachon and Menz 2006). It is clear that economic
concerns impact energy policy.
Beyond economic factors, scholars have identified two political
interests associated with the adop-
tion of renewable energy policy: the partisanship of state
political elites and the capacity of environ-
mental social movements. Studies of the determinants of state
renewable energy policy have
frequently noted the importance of state politicians on policy
adoption. States with more Democratic
(Coley and Hess 2012; Fowler and Breen 2013) or liberal
(Chandler 2009; Vachon and Menz 2006;
Yi and Feiock 2012) politicians are more likely to enact
renewable energy policies. Beyond polit-
icians, more environmental social movements in a state increase
the likelihood of renewable energy
policy adoption (Podobnik 2006; Vasi 2006, 2009, 2011). This
research suggests that states adopt re-
newable energy policies through a combination of political
interests and a desire to avoid disrupting
the prevailing economic conditions of a state. From this
perspective we should expect that states with
favorable political interests and economic conditions will be
more likely to adopt renewable energy
policies. As these studies have focused overwhelmingly on
mandate outcomes, it remains uncertain
whether the policies adopted will be incentives or mandates.
Institutional and cultural factors have received less attention in
research on renewable energy pol-

icy than interest-based accounts, but are likely to be important
predictors of renewable energy policy
288 . Vasseur
content. I expect political institutions to influence policy
adoption through two mechanisms: the
openness of the political process, and as a measure of a state’s
capacity to administer policies effect-
ively. State legislative systems differ in the degree to which
legislative change is possible outside of
the legislature, especially in the realm of citizen engagement in
the legislative processes. Some states
keep legislative power tightly held by their legislative bodies,
while others allow for a range of citizen
actions to advance legislation without the legislatures. These
actions, known as direct democracy, in-
clude referendums, initiatives, and related ways to bypass state
legislatures. States that allow direct
democratic actions represent not just a different system of
legislative action, but also a broader under-
standing of politics than states with a more closed process. As
such we might expect different policy
actions to be taken on the basis of direct democracy.
The other way political institutions impact renewable energy
policies is through a state’s capacity
to administer regulations and governance programs. Capacity to
govern has long been recognized as
a key factor in pollution control policies (Ringquist 1993), and
there is reason to expect it will matter
for renewable energy policies as well. If a state lacks
sophisticated political institutions, or has not in-
vested in the development of bureaucratic organizations, it

would be unlikely for it to engage in ef-
forts to promote social change that require new regulatory
infrastructures in order to function. These
states simply would not have the capacity to construct and
administer the additional infrastructure
required to manage these new regulatory programs. For
example, states with legislatures that are
rarely in session, or with governors who lack mechanisms to
influence the policy process, have less of
an ability to administer new regulatory programs than states
with more sophisticated political
institutions.
Beyond political interests and institutions, I expect that
ideational factors, specifically political cul-
ture, will also influence renewable energy policy adoption. By
political culture I refer to normative
paradigms held by political elites (Campbell 2002). These
paradigms influence policy adoption by
limiting the range of policy instruments that are perceived as
desirable or legitimate solutions
(Campbell 2002; March and Olsen 1989; Padamsee 2009;
Skrentny 1996; Steensland 2008). Rather
than assess these paradigms in general terms, I isolate specific,
and measurable, aspects of political
culture to compare alongside traditional interest and
institutional factors. In place of a general meas-
ure of political culture I address two specific dimensions,
environmental culture and neoliberal ideol-
ogy. Environmental culture assesses the degree to which state
policies consistently favor issues of
environmental protection. In these states norms regarding the
environment, and the appropriate
lengths the government should go to protect it, will differ from
less environmentally friendly states.
These norms will then lead to different sets of policy

instruments being adopted.
The other aspect of political culture I focus on is a state’s
normative orientation toward involve-
ment in market activity. In some states these orientations
manifest as a general inclination against any
form of regulatory policy, regardless of the policy domain
involved. I deem states in which this orien-
tation manifests as having an affinity for a neoliberal ideology.
These affinities arise based on histor-
ical patterns of party politics and alignment with business
interests (Prasad 2006). Neoliberal
ideology is usually thought to contain three primary
dimensions: a focus on reducing the welfare
state, opposition to redistributive tax policies, and minimal
regulations on industrial policies and labor
markets (Campbell and Pedersen 2001; Prasad 2006). Each of
these dimensions represents a distinct,
but related, avenue by which a preference for the market over
the state is expressed and how re-
sources should be distributed in a society. This preference stems
in part from a view of the market as
not only a legitimate means of distributing resources in society
but a moral one (Somers and Block
2005). States conforming to this ideology would be unlikely to
adopt any form of mandate that inter-
feres with market activity in any policy domain. In order to
ascertain the impact of neoliberal ideol-
ogy on policy adoption, any measure used must draw on policy
experiences with policies far enough
removed from renewable energy so as not to conflate a general
inclination against regulations with a
lack of regulation in one specific instance.

Determinants of the Renewable Energy Policies of U.S. States .
289
Taken together, these accounts suggest three broad arguments:
one based on the impact of eco-
nomic and electoral interests, another focused on state
institutional capacity, and a third that empha-
sizes a state’s cultural orientations towards regulation and the
environment. I expect to see different
political factors, or combinations thereof, influence the
adoption of policy instruments associated
with different strategies. Incentive policies are generally
thought of as interest based and will be heav-
ily influenced by economic and political factors. As incentives
use an existing governance infrastruc-
ture, the tax code, they will be less reliant on sophisticated
political institutions than mandate-based
policies. More broadly speaking, mandates must contend with
broader cultural views of regulations
and the market if a state is going to adopt them. Assessing these
expectations requires examining the
adoption of incentive- and mandate-based policies while
accounting for economic, interest-based, in-
stitutional, and cultural factors simultaneously.
DATA AND MEASURES
To test these claims this article draws on an original
longitudinal data set of U.S. states’ characteristics
and policy actions. Drawing from a variety of secondary sources
data was assembled every year start-
ing in 1970, the start of what is generally considered the
"environmental decade” and an era that saw
sustained pressure on environmental issues enter the political
sphere. Data collection stops in 2012
as the most recent available data for many predictors. The unit
of observation in these data is the

state-year, with 43 observations per state and a final analysis
sample of 2,103 state-years.2 3 Descriptive
statistics and a pairwise correlation matrix of all variables are
presented in Table 2.
I use two dependent variables in the analysis to follow. Each is
a count of policy instruments of
each type adopted by a state in a given year. I chose to use a
count of the policy instruments as a meas-
ure of strength given the uncertainty surrounding the
effectiveness of these policies. Given that at this
point it is unclear to scholars, let alone policy elites, which of
these mechanisms will be most effective
I find it reasonable to assume that states that adopt a wider
range of possible solutions are more com-
mitted to renewable energy generation. This suggests that the
surest way to measure a state’s commit
ment to renewable energy is by counting the different methods
they are employing to promote it. ’
Tax incentives include personal or corporate income tax
expenditures, property or sales tax ex-
emptions, and tax rebates for the production of renewable
energy or renewable energy systems.
Regulatory mandates include renewable energy portfolio
standards, mandatory generation disclos-
ures, green power purchasing options as well as public benefits
funds and cap and trade programs. All
data on these policies are drawn from the Database of State
Incentives for Renewables & Efficiency
(DSIRE), a collection of state-level regulatory environments
maintained by the North Carolina Solar
Center and the Interstate Renewable Energy Council (DSIRE
2012). A state was considered to have
a policy instrument if a review of the corresponding bill or
statute included the specified mechanism

for increased generation of renewable energy from wind, solar,
or geo-thermal sources.4 Policies
focused solely on other potential sources of renewable energy
generation, most prominently
2 As mandate policy instruments do not spread widely until the
1990s additional models were fit for this outcome that omit data
for 1970-1989. These models produce substantively similar
results.
3 Another possible metric could be the relative strength of the
policies adopted. This is certainly an interesting possibility, and
highly appropriate for some policy domains, but largely not for
renewable energy policy. It is certainly true that early adopting
states adopt weaker policies to start than later adopters, but the
early adopting states frequently amend their policies upward to
match the new standards. Examining states in 2012 I find no
significant variation in the strength o f these policies. I suspect
that
much of this change is technological in nature. As renewable
energy generation technologies become more advanced policy
elites
modify proposals to keep up with these developments. Given
this lack of variation I continue to use the count of policy
instru-
merits adopted as the best longitudinal measure available.
4 If a state later repeals or defiinds a policy instrument the
count for that state decreases. During the time period under
study in-
stances of this are relatively rare. Several states have seen bills
introduced that would restrict renewable energy generation, but
most o f these repeal efforts have not been successful. This will
surely be an issue for future research in this policy domain, but
does not greatly impact the time period examined in this study.

290 Vasseur
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. 291
hydroelectric and bio fuels, are omitted from analysis given
controversy surrounding their environ-
mental impacts.
Economic concerns are a key factor driving energy policy. Data
on a state’s economic conditions
was assembled from three sources. The first, production of
fossil fuels, is a time-invariant covariate
measuring if a state has produced coal, oil, or natural gas for
the majority of the years under examin-
ation. This was determined by consulting the total production
from these energy types as listed in the
State Energy Data System, a repository on energy production
and consumption by states from 1970
through 2010 assembled and hosted by the U.S. Department of
Energy (2010). I choose to use fossil
fuel production as a measure of a state’s energy economy as it
is the most inclusive measure available.
Past research has focused primarily on coal (Huang et al. 2007;
Vachon and Menz 2006) to the exclu-
sion of other energy sources. To avoid giving undo weight to a
single energy type when all are import-
ant drivers of energy politics in the United States, I utilize
fossil fuel extrachon as the broadest

measure available. I use a binary measure to highlight the
greater difference between producing and
non-producing states, rather than focus on the more limited
variation within producing states.s
Another key economic factor is the potential resources for
renewable energy in a state. Given that
the majority of renewable energy produced in the United States
comes from wind power, I operation-
alize renewable energy potential as a state’s average annual
wind speed.5 6 Wind speed data is time in-
variant and measured as of 1978. This measure is time invariant
as there is very little change in wind
speed over time, but far more variation between states. These
data are drawn from the U.S. Statistical
Abstract (U.S. Census Bureau 2012). For states with multiple
measurement sites, averages were taken
when calculating state totals. As a final economic factor I
control for the affluence of a state as past
studies have pointed to average income as a key predictor of
state energy and environmental policy
(Daley and Garand 2005; Ringquist 1993; Vachon and Menz
2006). Affluence is measured as a time
varying measure of median annual household income of a state
in thousands of 2011 dollars (U.S.
Census Bureau 2012).
Other factors that influence energy policy are political in
nature. Key among these is political inter-
ests, which I define as the partisanship of political elites and the
presence of environmental move-
ments. Following past research (Coley and Hess 2012), control
of state political institutions by
sympathetic elites is operationalized as control of a state’s
political institutions by the Democratic
Party. Drawing on data from the Book of the States (Council of

State Government 1979-2012) I
counted the number of political institutions, including both
legislative chambers and the office of the
governor, ranging from 0 to 3, controlled by the Democratic
Party in a given state-year. Control of a
chamber was defined as having the majority of the legislators in
that chamber.7
5 Using a continuous time-varying measure o f fossil fuel
extraction, logged to account for the skewed nature of the data,
does not
substantively change the results presented.
6 Given its dominance relative to other forms o f renewable
energy I focus this measure on wind energy. I avoid the use of a
meas-
ure of sunny days in area, data also collected by the National
Oceanic and Atmospheric Administration (NOAA), as the link
be-
tween this measure and an area’s suitability for solar power
generation is less clear than wind speed and wind power.
Additionally, despite its present surge, solar power is simply
not a major source o f power generation in the United States.
According to the Energy Information Administration’s (2015)
data wind energy accounted for just over 4 percent o f total
energy
generation in 2013. By comparison, solar accounted for roughly
a quarter o f one percent (U.S. Census Bureau 2012), the
smallest
value listed. Nevertheless, a more comprehensive measure for
renewable energy potential, including solar, wind, geothermal,
and
other sources (Deyette et al. 2003), was tested and did not
change the conclusions offered. While more encompassing this
meas-
ure is no t available for all states (Alaska and Hawaii). O ut o f

a desire to keep as many observations in the analysis as possible
I
maintain the wind speed item in presentation.
7 The federated system of government in the United States
introduces diversity in the political systems enacted by states.
In order
to facilitate comparisons across states an attem pt was made to
standardize political institutions. Com m on among these differ-
ences are how states deal with a chamber that results in an equal
num ber o f legislatures from each party. States use a variety of
techniques for deciding control in these cases, for ease o f
comparison I coded control based on the party affiliation of the
major-
ity leader of the chamber. Furthermore, independent legislatures
were counted as part of the Democratic Party only if they held
Green or progressive affiliation. Additionally, two states do not
record the partisanship of their state legislators during all or
part
o f the period under study. W hen this information could not
obtained those state years were excluded from analysis. This
removes
all o f Nebraska’s observations and the first four years o f
observations for Minnesota.
292 . Vasseur
I also account for the density of environmental movements with
a count of the number of envir-
onmental movement organizations (EMOs) active within a given
state-year. These counts come
from the Policy Agendas Project Encyclopedia of Associations
Database.8 The Encyclopedia of
Associations, Volume 1, National Organizations of the U.S.

(EA) (Gale Research Inc. 1956-2010) pro-
vides a census of national social movement organizations, and
has been used by many social move-
ment scholars to establish measures of social movement density
(Andrews and Edwards 2005;
Johnson 2006, 2008; Johnson, Agnone and McCarthy 2010;
Johnson and Frickel 2011; Martin,
Baumgartner, and McCarthy 2006; Minkoff 1997, 1999; Van
Dyke and Soule 2002; Vasi and Strang
2009; Walker, McCarthy, and Baumgartner 2011). The Policy
Agendas Project data set provides a
count of these movement organizations every five years, which I
expanded to 2010. Following past
studies, (Johnson 2008; Johnson and Frickel 2011) groups were
selected if their primary purpose was
environmental conservation/protection or the production of
renewable energy. This was established
through use of keywords, headings, association name, and
organizational description.9 Once a group
was located I obtained a state address, and calculated state-year
counts of movement organizations.
While there is some concern about bias in the groups reported in
the EA (see Brulle et al. 2007 and
Johnson and Frickel 2011) the EA remains a valid measure of
EMO density within a state-year.
Concerns over bias in the EA center on the fact that an
organization’s size and its proximity to
Washington, DC, increase the probability of being listed in the
EA (Brulle et al. 2007). Certainly
there are movement organizations not reported in the EA that
are active in the United States, but
aside from a potential DC bias, there is no reason to expect any
bias on the basis of organization size
is not constant across states.
In order to assess a state’s capacity to adopt new legislation and

administer new programs I ac-
count for the openness and sophistication of a state’s political
institutions. I measure a state’s political
institutions in three dimensions: the availability of direct
democracy, the professionalism of the state’s
legislature, and the governor’s power. These measures account
for the relative capacity of the two
most important political institutions in a state, and the ability of
citizens to engage in direct legislative
actions. Direct democracy is important to account for as some
states have adopted renewable energy
policies through this process. These are relatively few in
number. To be clear, the vast majority of
policy instruments are adopted through legislative channels, but
I believe it is still important to ac-
count for this alternative avenue. Direct democracy is measured
as a non-time varying indicator vari-
able for whether a state allows citizen initiatives during the
period its renewable energy policies were
adopted. This data is drawn from the Initiative and Referendum
Institute (2013). I focus on the gen-
eral category of legislative initiatives as a way for citizens to
bypass the legislature rather than the
more restrictive constitutional amendments as this is the most
likely direct democracy avenue renew-
able energy policies take.
The relative sophistication of a state’s political institutions
helps determine their capacity to adopt
new regulatory programs. More sophisticated legislatures have
greater time and expertise to engage
in the often technical debates surrounding energy policy, and
are associated with increased resources
for the administration and maintenance of regulatory policy
instruments once adopted. Simply put, it
is easier for a highly professional state to adopt a technically

demanding policy, such as cap-and-trade,
for example, than it is for a legislature composed of
understaffed part-time legislators. Legislative pro-
fessionalism is measured using the Squire index (Squire 2007).
This measure is a ratio of the
8 The data used here were originally collected by Frank R.
Baumgartner and Bryan D. Jones, with the support of National
Science
Foundation (NSF) grant numbers SBR 9320922 and 0111611,
and were distributed through the Departm ent of Government at
the University of Texas at Austin. Neither NSF nor the original
collectors of the data bear any responsibility for the analysis re-
ported here.
9 Keywords used following Johnson 2008 were: conservation,
wildlife conservation, environment, environmental quality,
environ-
mental protection, environmental health, toxic exposure, nuclear
energy, ecology, pollution control, and hazardous waste. Given
my focus on renewable energy policy I added keywords: solar
energy, wind energy, and organizations in the general energy
key-
word with a focus on efficiency or renewable/sustainable
energies.
293
professionalism of a state s legislature relative to the U.S.
Congress across three dimensions: staff,
compensation, and time in session. Changes in level of
professionalism are not drastic over time, but
nevertheless the index is calculated at five points in time (1979,

1986, 1996, 2003, 2009) based on
available component data. I utilize a measure of governor’s
power following Krupnikov and Shipan
(2012) that averages five different factors related to the
governor’s ability to directly influence fiscal
issues in their state. Governors’ power is potentially relevant as
many of the incentive policy instru-
ments are adopted as part of broader fiscal or budgetary
policies.
A final set of factors, tapping political culture, measure a
state’s environmental culture and its affin-
ity for neoliberal ideology. I measure environmental culture as
the average of the state’s U.S. Senators
League of Conservation Voters scores (LCV 2012). The League
of Conservation Voters (LCV) has
maintained a ranking of every U.S. Congress member’s
environmental voting record since the early
1970s, and represents a longitudinal, state-specific measure of
the degree to which statewide elected
officials in a state vote in favor of environmental protection
causes. I focus on senators to capture
statewide, rather than district-based, environmental affinity, and
to ensure that the votes tallied in
each year are of similar scope in their environmental
impact.10’11
I measure neoliberal ideology in two ways, each addressing a
different aspect of the ideology.12
First, I account for states that engage in relatively little public
welfare spending with a binary measure
(U.S. Census Bureau various years).13 These low spending
states reflect a neoliberal focus on less
government involvement in society, especially as it relates to
social safety net programs. Secondly, I
also assess a state s opposition to regulation by including a

measure of which states have adopted a
right-to-work policy by a given year. Right-to-work policies
make unionization more difficult in a state
and are consistent with broader neoliberal ideology preferences
regarding market supremacy. I do
not expect that right-to-work policies themselves are associated
with renewable energy policy, but in-
stead they serve as an indicator of states that seek to minimize
state interference in the market.14 As
right-to-work policies are associated with an inclination against
regulations more broadly, and are not
restricted to environmental policy, with this measure included I
am better positioned to observe how
political culture in general influences the policy orientation a
state will pursue when adopting policies.
I measure right-to-work policies as a time-variant binary
variable for if a state has adopted a right-to-
10 Another commonly used measure of environmental culture is
single-year scorecards of state polices produced by other
environ-
mental interest groups. These measures might be more directly
relevant to state politics, but they suffer two flaws compared to
LCV scores. First, they are not longitudinal. Few environmental
groups have existed continuously since the 1970s, and thus
most scorecards cover only a single year from relatively late in
the time period under study. Secondly, many of these indices
draw on the exact policy instruments I am predicting adoption
of. In order to avoid causality problems and to capture a time-
variant measure I prefer the LCV scores.
I I One other measure examined was the share of state spending
devoted to natural resource conservation, promotion, and devel-
opm ent (U.S. Census Bureau various years). The definition o f
this spending is broad, including everything from forest
conserva-

tion to flood control efforts. This measure was never significant
and did not change any of the results presented. Given the wide
definition and lack of significance, and out of a desire to
conserve degrees o f freedom in the models presented, I omit
this meas-
ure from presentation.
12 Another measure, examining the degree to which a state’s
tax environment is regressive, was tested but ultimately not
included
in this article. I assembled data on state tax revenue to assess
the degree to which states drew their revenue from tax
mechanisms
that did no t offer variable rates based on income. These
mechanisms include sales tax and licenses or user fees,
compared to
more progressive income or capital gains taxes. I focus on a
state’s regressive tax environment rather than something like
tax
cuts, to ease comparisons between states. Many states already
have no income tax, leaving politicians with nothing to cut.
Instead, I focus on the underlying issue that neoliberal ideology
drives towards, flattening the overall tax rate paid by
individuals.
For that reason I believe this measure o f regressive tax
environments captures at the state level a similar underlying
concept to
federal tax cuts. This measure was not significant in bivariate
analysis and proved highly correlated with right-to-work status
and
low welfare spending. As such I omit it from the presented
models.
13 Low welfare spending is defined as less than 20 percent of
state revenues, roughly the average of state welfare spending
during

the time period under study. Slight modifications to this cut
point do not substantively change the results presented. A
binary
measure is used to avoid the skewed distribution of this measure
and to facilitate comparison to the right-to-work measure and
over time.
14 Testmg an additional item, Elizar’s (1972) three-political
culture model suggests that the right to work measures capture
much
of the same variation as what Elizar calls traditional political
culture.
294 . V asseur
work policy by a given year using data drawn from the National
Council of State Legislators (NCSL
2014).15 These measures capture the two most prominent
aspects of neoliberal ideology, a limited
welfare state and a preference for a market-based industrial
policy.
Logic of Analysis
To assess the impact of these state-level factors on the number
of policy instruments of the various
types adopted by a state I fit a series of random effects
longitudinal Poisson regression models.16 For
each outcome three models are fit. The first includes economic
factors and political interests. The se-
cond model adds controls for institutional and cultural factors.
The third model controls for the num-
ber of policy instruments of the other type adopted by a state.
All models are fit with robust standard

errors to correct for possible level-two overdispersion (Rabe-
Hesketh and Skrondal 2012). In each
model time is specified using indicator variables for decade.17
RESULTS AND D IS C U S SIO N
The results of the models predicting tax incentive policy
instruments, presented in Table 3, are con-
sistent with a view of energy policy as economic and political
interest based. Both higher levels of an-
nual income and increased environmental movement
organization density predict adopting more
incentive-based policy instruments. On the other hand, states
that produce fossil fuels are predicted
to adopt significantly fewer incentives. These results are
consistent with the addition of the institu-
tional and cultural factors in Model 2, none of which prove
significant for this outcome. This model
is what would be expected from the energy policy literature;
states that have higher levels of affluence
and more environmental movement organizations are motivated
to act, and those that produce fossil
fuels are less likely to enact policies that challenge their current
economic interests. A model based
on economic and political interests, as dominates the broader
energy policy literature, fits for incen-
tives, but this is not entirely the case for mandate-based
policies.
Similar models are presented in Model 4 and Model 5 in Table
4. The pattern of results observed
across these models is clear, but no longer entirely consistent
with an economic and political interest-
based account of energy policy. As with tax incentives, states
with more environmental movement or-
ganizations and higher income adopt more regulatory mandates.
Additionally, increasing LCV scores

increases regulatory mandate adoption. On the other hand,
having a right-to-work law and/or having
low welfare spending significantly reduces the odds a state will
adopt a mandate-based instrument.
This indicates that states that have adopted a set of policies
consistent with a neoliberal ideology are
dramatically less likely to enact policies that intervene between
the consumer and electricity produ-
cers when compared to other states. This effect is independent
of a state’s more general environmen
tal orientation.
15 Most right-to-work laws were adopted well before 1970. In
fact, many states adopted them in the 1940s and 50s. Only six
states
adopted these laws during the period under study, and most of
those did so well before adopting any renewable energy
policies.
As such, changing right-to-work to a time-varying binary
variable does not change the results presented.
16 A Mundlak test for the suitability of random coefficients
provides no evidence against using random coefficients: tax
incentives
(Chi2 = 3.96, df = 6, p = .5556); regulatory mandates (Chi2 =
6.18, df = 6, p = .2894). Additionally, examinations of the
dis-
crete change in probabilities o f a state-year having a zero, one,
or two plus count for each outcome is not seen across the
signifi-
cant independent variables. This suggests that there is no t a
substantively different process for going from a zero to a one
count
as there is for further policy action, thus I use the count models
in place of event history models of these transitions.

17 O ther specifications of time examined including omitting it
entirely, using a linear specification, and using a second order
poly-
nomial specification. Changing the specification of time in
these models changes the substantive conclusion for only the
Democratic power covariate in the mandate models. W ith some
specifications of time and some alternative specifications of
Democratic power (for example separating governors from
legislative chambers, using percentages of Democrats)
individual co-
efficients are significant at the .05 level. Given the dependence
of this result on specification I believe this is an issue o f
colinear-
ity between predictors. As there is no evidence of a significant
relationship between Democratic power and either type of
policy
adoption with other predictors omitted, regardless of the
specification o f time, and that removing it from the model does
not
change any of the other effects observed, I maintain the
traditional 0 to 3 scale in presentation.
295
Table 3. Odds Ratios from Random Effects Longitudinal
Poisson Models of Tax Incentive
Adoption
(1)
Base Model
(2)
Institutions and Culture

(3)
Policy Portfolio
Policy po rtfo lio
T o ta l m a n d a te policies .894
( - 1 . 3 2 )
E co n o m ic factors
H o u se h o ld in co m e0 1.018** 1.018** 1.019**
(2.94) (2.89) (3.14)
Fossil fuel p ro d u c tio n .426** .538+ .521*
( - 2 . 6 0 ) ( - 1 . 9 1 ) ( - 2 . 0 8 )
Average w in d sp e e d 6 1.029 1.035 1.041
(.28) (.31) (.36)
Political interests
D em o cratic p o w e rc 1.007 .998 1.019
(.11) ( - . 0 3 ) (.34)
E M O density 1.075* 1.069* 1.066*
(2 .29) (2 .30) (2.36)
Political in stitu tio n s
D irect dem ocracy .638 .649
( - 1 . 3 0 ) ( - 1 . 2 4 )
Legislative professionalism 1.000 1.001
( - . 0 5 ) (.24)
G o v ern o r pow er .980 .964
( - . 0 9 ) ( - . 1 6 )
N eoliberal affinity

R ight-to-w ork 1.081 1.027
(.17) (.06)
L ow w elfare spending .798 .821
( - 1 . 3 8 ) ( - 1 . 3 5 )
E n v iro n m en tal culture
L C V scores 1.003 1.003
(.96) (1.19)
State-level in te rc e p t .174 .111 .118
(.60) (.37) (.41)
S tate-year in te rc e p t 1.091 1.051 1.061
B IC 3,467.716 3,501.051 3,498.456
N = 2,103 state-years
Notes: Exponentiated coefficients; z statistics in parentheses,
models fit with robust standard errors. Controls for decade
included in model
(n o t shown).
“Median annual household income in thousands o f 2011
dollars.
Miles p er hour.
C h am b ers o f state legislator plus governorship controlled by
the Democratic Party.
i p < .10 *p < .05 **p < .01 ***p < .001 (two-tailed tests)
296 Vasseur
Table 4. Odds Ratios from Random Effects Longitudinal
Poisson Models o f Regulatory
Mandate Adoption

( 4 ) (5) (6 )
Base M odel Institutions and Culture Policy Portfolio
Policy portfolio
T otal incentive policies 1.245***
(4.19)
Econom ic factors
H ousehold incom e11 1.053*** 1.063*** 1.059***
(3.85) (4.62) (4.00)
Fossil fuel production .319+ .655 .642
( - 1 .8 3 ) ( - . 8 0 ) ( - . 8 4 )
Average wind speed*" 1.102 1.164 1.150
(.62) (.91) (.91)
Political interests
Dem ocratic pow erc 1.050 .997 .957
(1.35) ( - . 0 9 ) ( - 1 .1 6 )
EM O density 1.044** 1.036* 1.038*
(2.81) (1.98) (1.97)
Political institutions
D irect democracy .939 .987
( - . 1 2 ) ( - . 0 2 )
Legislative professionalism 1.002 1.000
(.50) (.02)
Governor power .584 .569
( - 1 .2 9 ) ( - 1 .4 3 )
Neoliberal affinity

Right-to-work .321* .303*
( - 2 .2 3 ) ( - 2 .3 7 )
Low welfare spending .502*** .515***
( - 4 .2 0 ) ( - 4 .2 0 )
Environm ental culture
LCV scores 1.006** 1.004*
(2.83) (2.07)
State-level intercept 1.256 .755 .647
(3.44) (1.91) (1.70)
State-year intercept 1.874 1.459 1.382
BIC
N = 2,103 state-years
1,732.840 1,737.512 1,730.746
Notes: Exponentiated coefficients; z statistics in parentheses,
models fit with robust standard errors. Controls for decade
included in model
(n o t shown).
‘'Median annual household income in thousands o f 2011
dollars.
^Miles per hour.
cChambers o f state legislator plus governorship controlled by
the Democratic Party.
i p < .10 *p < .05 **p < .01 ***p < .001 (two-tailed tests)
297
Table 5. Predicted Number of Policies Adopted by Policy Type,

Fossil Fuel Production, and
Neoliberal Status0
Total Incentives Mandates Difference
Neither 3.40 2.09 1.31 .78
Neoliberal 2.09 2.00 .09 1.91
Fossil fuel only 2.11 1.04 1.07 -.0 3
Both 1.06 .99 .07 .92
“Predictions based on institutional and cultural models for each
outcomes (M odels 2 and 5) with all other covariates held at
their mean.
Neoliberal states are those with right-to-work laws and low
welfare spending. Changing levels o f environmental m ovement
organizations and
income changes the overall level o f activity, b u t does n o t
change the ordering o f categories or the relative difference
between incentive and
mandate policies. Predictions are for the final year o f data
(2012) to model ending conditions for states.
The final models in each table, Models 3 and 6, present the
relationship between these two out-
comes as net of the predictors. These policies are not unrelated,
nor does adopting one kind of policy
decrease the odds of adopting a policy of the other type. Instead
there is a significant increase in the
odds of a state adopting a regulatory mandate for each tax
incentive it has already adopted, but the re-
verse does not yield a significant relationship. This suggests
that these policy orientations are not
zero sum, especially when seen in their historically contingent
context. Tax incentive policies first ap-
pear in the mid-1970s, while regulatory mandates were not
widely adopted until almost 20 years later.

Understanding this result requires a reorientation of views of
policy sequencing away from a focus on
policy instrument type and towards broader policy orientations.
It is certainly true that conditions in
some states lead to a noted preference for incentives or
mandates, but other states adopt policies
based on a commitment towards increasing renewable energy
generation. These states are not ori-
ented toward a specific type of policy instrument but instead
toward a broader goal of increasing re-
newable energy generation by any means available. They adopt
incentives as they first become
available and later add mandates as those policies develop.
From a policy content point of view, these
states have adopted a mixed approach to renewable energy
policy.
This mixed approach to renewable energy policy is a distinct
orientation unto itself, but is not one
that could be identified by examining idiosyncratic policy
adoption or only studying the first policy
instrument adopted. This mixed approach is reflected by the
significant relationship in Model 6.
States are more likely to engage in mandate-based policies if
they already have incentive-based poli-
cies. Therefore, two dominant strategies of action can be
observed: some states adopt a mixed ap-
proach while others adopt a primarily (or exclusively)
incentive-based orientation. What state-level
factors distinguish these active states from those that take
relatively few policy actions?
State policy action can be explained by traditional political
interests and economic factors.
Renewable energy policies are adopted in states in which they
do not threaten existing interests. As

seen in the prior results, more affluent states with more
environmental movement organizations and
that do not produce fossil fuels will adopt more renewable
energy policies. These factors are consist-
ent for both incentives and mandates. This suggests that similar
conditions spur states to policy ac-
tion in general, but what factors account for differences in the
type of policy a state adopts?
The content of state policy is best explained by political culture
in the form of an affinity for a neo-
liberal ideology beyond energy policy. Table 5 presents the
expected policies adopted by states as of
2012, separated by policy type and by all possible combinations
of fossil fuel production and neo-
liberal status. This table illustrates two key points. First, states
that do not produce fossil fuels adopt
more policies regardless of neoliberal status. Secondly,
neoliberal states show the largest difference
between their incentive and mandate-based policies. States that
are not neoliberal and do not pro-
duce fossil fuels take a more balanced approach. Neoliberal
states, on the other hand, skew heavily to-
wards incentive-based policies regardless of their fossil fuels
status. States that do not produce fossil
298 • Vasseur
fuels but are neoliberal adopt an average of two incentive
policies, no different from similar non-
neoliberal states. They differ sharply when it comes to
mandates, from an average of 1.3 policies to
less than a tenth of a policy. Thus even if it is a state’s
economic characteristics and political interests

that determine how many policies a state is likely to adopt, it is
that state’s political culture that deter-
mines what kind of policies they enact. This divide reinforces
the need to examine broader policy
orientations, not simply individual policy adoption, in order to
account for all facets of the policy
adoption process.
C O N C L U S I O N
This project contributes to our understanding of policy adoption
by examining a state’s broader port
folio of policies rather than idiosyncratic policy adoption. This
shift demonstrates that traditional eco-
nomic and electoral interest-based factors are excellent
predictors of how many policies a state is
likely to adopt, but do far less to explain what kind of policies a
state will enact. To understand policy
content, a broader conception of politics that includes
institutional and cultural factors is required.
Adding these factors clarifies the process by which states select
the content of their policies.
Specifically, even when accounting for a state’s general
environmental orientation, a state’s affinity for
neoliberal ideology by way of having a right-to-work law or low
welfare spending is associated with
adopting an incentive-only orientation. I show that states that
are adverse to market intervention in
union organizing carry that aversion over to the largely
unrelated area of renewable energy politics.
Given the centrality of the incentive versus mandate debate in
contemporary American political dis-
course, using right-to-work laws as a quantifiable and easily
comparable measure of political culture
regarding regulation has the potential to be informative for
future research across a variety of policy
domains. Be it social program spending, the privatization of

education, or the establishment of local
healthcare markets, there are reasons to suspect that this
measure will prove fruitful for analysis be-
yond renewable energy policy.
In addition, viewing policies as a result of an overall policy
orientation lends clarity to the diversity
of actions undertaken by U.S. states in the domain of renewable
energy policy. States adopt a variety
of policies and do so with little consistency regarding
individual policy types. It is rarely the case that
a state adopting a policy of one kind will necessarily result in
adoption of a related policy or not hav-
ing any policies of a different type. This could lead to a view of
policy adoption as random or idiosyn-
cratic if the focus of analysis remains on the individual policies.
If analysis instead focuses on the
entire portfolio of policies, as I have done, state actions have an
overall consistency with a broader
policy orientation. In the contemporary United States, states
adopt one of two strategies of action, ei-
ther incentive based or a mixed approach. Relatively few states
adopt a mandate-only approach. If
states are going to act in this domain they will almost certainly
adopt incentive-based policies, and
some will add mandates as well. This is likely based on the
historical sequencing of policy adoption,
with tax incentives first adopted in the 1970s and regulatory
mandates not seeing widespread adop-
tion until the late 1990s. This insight further reinforces the
continued importance of understanding
the relationship between strategies based on tax incentive and
regulatory mandate policies in contem-
porary American politics. Examining a state’s general policy
orientations expands the definitions of
consistency in state policy action to better reflect political

reality.
The approach in this article demonstrates the ability to examine
what kinds of policies a state
adopts, but the question remains: why does the type of policy
matter? Policy type matters for two
reasons. First, ignoring policy type in favor of only policy
action obscures the complex nature of polit-
ical reality. Prior research has noted this across other policy
domains. For example, Jacob Hacker
(2002) demonstrates that the United States is no longer a
welfare laggard if more varieties of policies
are considered social policy. In this case a focus on policy
content redefines one of the central moti-
vating questions for policy scholars of the past decades. In
order to gain an accurate picture of the
policy process, it is vital to understand both policy action and
the content of the adopted policies.
. 299
Another impact of policy type is seen when examining real-
world efficacy. It is still unclear if the
renewable energy policies studied here will actually be effective
at increasing renewable energy gener-
ation or reducing carbon dioxide emissions in the states that
adopt them (Carley 2009; Prasad and
Munch 2012). The existing evidence on effectiveness clusters
among the most coercive regulatory
mandates. Consumption taxes have been shown to be more
effective than other renewable energy
policies (Prasad 2010; Prasad and Munch 2012). If these results
hold as more state policies come

into effect, it suggests that incentives alone are not enough; a
top-down, mandate-based approach is
required to meaningfully address the problems these policies
were designed to solve.
Beyond a focus on policy portfolios and orientations of action,
this study also contributes to a
broader literature on fiscal sociology by expanding its focus on
tax incentives to a policy domain that
has received less attention from scholars. As fiscal sociology
continues to develop, it will expand be-
yond the confines of social policy and into other domains in
which tax incentives are favored instru-
ments of promoting social change. In applying the theories from
fiscal sociology to renewable energy
policy this project does just that. In the current American
political climate, incentive-based policies
are the only actions taken at a federal level regarding renewable
energy, and are preferred across a
range of policy domains. These insights into how states decide
on the content of their policies are
vital to understanding the future politics of climate change in
the U.S. context. As renewable energy
policy and climate change in general continue to be debated in
the United States, research on the
subject must expand and incorporate insights from other
political fields in order to remain relevant.
REFERENCES
Andrews, Kenneth T. and Bob Edwards 2005. The
Organizational Structure of Local Environmentalism.”
Mobilization
10(2):213-34.
Baumgartner, Frank R. and Bryan D. Jones 1993. Agendas and
Instability in American Politics. Chicago: University of

Chicago Press.
Beland, Daniel and Robert Henry Cox 2011. Ideas and Social
Politics in Social Science Research. New York: Oxford
University Press.
Brulle, Robert, Liesel Hall Turner, Jason Carmichael, and J.
Craig Jenkins. 2007. “Measuring Social Movement
Organization Populations: A Comprehensive Census of U.S.
Environmental Movement Organizations.”
Mobilizations 12(3): 195-211.
Campbell J. L. and O. K. Pedersen, eds. 2001. The Rise of
Neoliberalism and Institutional Analysis. Princeton, NJ:
Princeton University Press.
Campbell, John L. 1988. Collapse of an Industry: Nuclear
Power and the Contradictions of U.S. Policy. Ithaca, NY and
London, UK: Cornell University Press.
------. 2002. “Ideas, Politics, and Public Policy.” Annual
Review of Sociology 28(l):21-38.
Carley, Sanya. 2009. “State Renewable Energy Electricity
Policies: An Empirical Evaluation of Effectiveness” Energy
Policy 37:3071-81.
Chandler, Jess. 2009. “Trendy
Solution
s: Why Do States Adopt Sustainable Energy Portfolio
Standards?” Energy Policy

37:3274-81.
Coley, Jonathan S. and David J. Hess 2012. Green Energy Laws
and Republican Legislators in the United States.”
Energy Policy 48(2012):576-83.
Council of State Government. 1979-2012. Book of the States.
Volumes 23-44. Chicago: Council of State Governments.
Daley, Dorothy M. and James C. Garand 2005. Horizontal
Diffusion, Vertical Diffusion, and Internal Pressure in State
Environmental Policymaking, 1989-1998.” American Politics
Research 33(5):615-44.
Database of State Incentives for Renewables & Efficiency
(DSIRE). 2012. “Rules, Regulations & Policies for Renewable
Energy. Retrieved May 8, 2015 (www.dsireusa.org/).
Deyette, Jeff, Steve Clemmer, and Deborah Donovan 2003.
Plugging in Renewable Energy: Grading the States.
Washington, DC: Union of Concerned Scientists.
Dobbin, Frank. 1994. Forging Industrial Policy: The United
States, Britain, and France in the Railway Age. New York:
Cambridge University Press.

Elizar, Daniel J. 1972. American Federalism: A View from the
States. New York: Thomas Y. Crowell Company.
Energy Information Administration. 2015 “U.S. Energy
Generation by Source.” Retrieved May 8, 2015 (www.eia.gov/
tools/faqs/faq.cfm ?id=427& t=3).
http://www.dsireusa.org/
http://www.eia.gov/
300 . Vasseur
Fowler, Luke and Joseph Breen 2013. “The Impact of Political
Factors on States’ Adoption of Renewable Portfolio
Standards.” The Electricity Journal 26(2):79-94.
Gale Research. Inc. 1956-2010. The Encyclopedia of
Associations, Volume 1, National Organizations of the U.S.
Detroit,
MI: Gale Research Co.
Hacker, Jacob S. 2002. The Divided Welfare State: The Battle
over Public and Private Social Benefits in the United States.
Cambridge, UK: Cambridge University Press.

Howard, Christopher. 1997. The Hidden Welfare State: Tax
Expenditures and Social Policy in the United States.
Princeton, N J: Princeton University Press.
----- . 2007. The Welfare State Nobody Knows: Debunking
Myths About U.S. Social Policy. Princeton, NJ: Princeton
University Press.
----- . 2009. “Maxing Taxes the Life of the Party.” Pp. 86-101
in The New Fiscal Sociology: Taxation in Comparative and
Historical Perspective, edited by I. W. Martin, A. K. Mehrotra,
and M. Prasad Cambridge, UK: Cambridge University
Press.
Huang, Ming-Yuan, R. Janaki, R Alavalapati, Douglas R
Carter, and Matthew H. Langholtz 2007. “Is the Choice of
Renewable Portfolio Standards Random?” Energy Policy
35:5571-75.
Initiative and Referendum Institute. 2013, “State-by State List
of Initiative and Referendum Provisions.” Retrieved May
8, 2015 (www.iandrinstitute.org/statewide_i%26r.htm).
Jasper, James M. 1990. Nuclear Politics: Energy and the State

in the United States, Sweden, and France. Princeton, NJ:
Johnson, Erik W. 2006. “Changing Issue Representation among
Major United States Environmental Movement
Organizations.” Rural Sociology 7l(l):132-54.
----- . 2008. “Social Movement Size, Organizational Diversity
and the Making of Federal Law.” Social Forces 86(3): 1-28.
Johnson, Erik W., Jon Agnone, and John D. McCarthy 2010.
“Movement Organizations, Synergistic Tactics, and
Environmental Public Policy.” Social Forces 88(5):2267-92.
Johnson, Erik W. and Scott. Frickel 2011. “Ecological Threat
and the Founding of U.S. National Environmental
Movement Organizations, 1962-1998.” Social Problems
58(3):305-29.
Kingdon, John W. [1995] 2004. Agendas, Alternatives, and
Public Policies. New York: HarperCollins.
Krupnikov, Yanna and Charles Shipan 2012. “Measuring
Gubernatorial Budgetary Power: A New Approach.” State
Politics and Policy Quarterly 12(4):438-55.
League of Conservation Voters (LCV). 2012. “National

Environmental Scorecard.” Retrieved May 8, 2015 (www.lcv.
°rg /).
Lieberman, Robert C. 2002. “Ideas, Institutions, and Political
Order: Explaining Political Change.” American Political
Science Review 96:697-711.
Lowry, William R 2008. “Disentangling Energy Policy from
Environmental Policy.” Social Science Quarterly
89(5): 1194-211.
March, James G. and Johan P. Olsen 1989. Rediscovering
Institutions: The Organizational Basis of Politics. New York:
The Free Press.
Martin, Andrew W., Frank R Baumgartner, and John D.
McCarthy 2006. “Measuring Association Populations
Using the Encyclopedia of Associations: Evidence from the
Field of Labor Unions.” Social Science Research
35(3):771-78.
Martin, Isaac William, Ajay K. Mehrotra, and Monica Prasad
2009. The New Fiscal Sociology: Taxation in Comparative
and Historical Perspective. Cambridge, UK: Cambridge

University Press.
Minkoff, Debra C. 1997. “The Sequencing of Social
Movements.” American Sociological Review 62(5):779-99.
------. 1999. “Bending with the Wind: Strategic Change and
Adaption by W omen’s and Racial Minority Organizations.”
American Journal of Sociology 104(6):1666-703.
National Conference of State Legislatures (NCSL). 2014.
“Right-to-Work States.” Retrieved May 8, 2015 (www.ncsl.
org/research/labor-and-employment/right-to-work-laws-and-
bills.aspx).
Padamsee, T. J. 2009. “Culture in Connection: Re-
Contextualizing Ideational Processes in the Analysis of Policy
Development.” Social Politics: International Studies in Gender,
State & Society 16(4):413-45.
Pierson, Paul. 2000. “Increasing Returns, Path Dependence, and
the Study of Politics.” American Political Science Review
94:251-67.
Podobnik, Bruce. 2006. Global Energy Shifts: Fostering
Sustainability in a Turbulent Age. Philadelphia: Temple
University

Press.
Prasad, Monica. 2006. The Politics of Free Markets: The Rise of
Neoliberal Economic Policies in Britain, France, Germany
and the United States. Chicago: The University of Chicago
Press.
http://www.iandrinstitute.org/statewide_i%26r.htm
http://www.lcv
http://www.ncsl
. 301
----- . 2010. “Taxation as Regulatory Tool: Lessons from
Environmental Taxes in Europe.” Pp. 363-90 in Governments
and Markets: Toward a New Theory of Regulation, edited by E.
J. Balleisen and D. A. Moss. Cambridge, UK:
Cambridge University Press.
------. 2011. "Tax ‘Expenditures’ and Welfare States: A
Critique.” The Journal of Policy History 23(2):2Sl-66.
Prasad, Monica and Steven Munch 2012. “State-Level

Renewable Electricity Policies and Reduction in Carbon
Emissions.” Energy Policy 45:237-42.
Rabe-Hesketh, Sophia and Anders Skrondal 2012. Multilevel
and Longitudinal Modeling Using Stata: Volume II
Categorical Responses, Counts, and Survival. College Station,
TX: Stata Press.
Ringquist, Evan J. 1993. Environmental Protection at the State
Level. Armonk, NY: M. E. Sharpe.
Sine, Wesley D. and Brandon H. Lee 2009. “Tilting at
Windmills? The Environmental Movement and the Emergence
of the U.S. Wind Energy Sector.” Administrative Science
Quarterly 54:123-55.
Skrentny, John David. 1996. The Ironies of Affirmative Action,
Politics, Culture, and Justice in America. Chicago:
University of Chicago Press.
Somers, Margaret R and Fred F. Block 2005. “From Poverty to
Perversity: Ideas, Markets and Institutions over 200
Years of Welfare Debate.” American Sociological Review
70:260-87.
Squire, Peverill. 2007. “Measuring State Legislative

Professionalism: The Squire Index Revisited.” State Politics and
Policy Quarterly 7:211-27.
Steensland, Brian. 2008. The Failed Welfare Revolution:
America’s Struggle over Guaranteed Income Policy. Princeton,
NJ:
U.S. Census Bureau. 1970, 1975, 1980, 1990, 1995, 2000, 2010.
“Annual Survey of State Government Finances.”
Retrieved May 8, 2015
(www.census.gov/govs/state/historical_data.html).
------. 2012. Statistical Abstract of the United States Congress,
131st Edition. Retrieved May 8, 2015 (www.census.gov/
com pendia/statab/>).
U.S. Department of Energy. 2010. “States Energy Data System.”
Retrieved May 8, 2015 (www.eia.gov/state/seds/).
U.S. Environmental Protection Agency (EPA). 2014. “Clean
Power Plan.” Retrieved May 8, 2015 (www.epa.gov/clean
powerplan/clean-power-plan-exis ting-power-plants).
Vachon, Stephan and Fredric C. Menz 2006. The Role of Social,
Political, and Economic Interests in Promoting State

Green Electricity Policies.” Energy Policy 9(7):652-62.
Van Dyke, Nella and Sarah A. Soule 2002. “Structural Social
Change and the Mobilizing Effect of Threat: Explaining
Levels of Patriot and Militia Organizing in the United States.”
Social Problems 49(4):497-520.
Vasi, Ion Bodgan. 2006. “Organizational Environments,
Framing Processes, and the Diffusion of the Program to
Address Global Climate Change among Local Governments in
the United States.” Sociological Forum 2l(3):439-66.
----- . 2009. “Social Movements and Industry Development: The
Environmental Movement’s Impact on the Wind
Energy Industry.” Mobilization: An International Journal
14(3):315-36.
------. 2011. Winds of Change: The Environmental Movement
and the Global Development of the Wind Energy Industry.
New York: Oxford University Press.
Vasi, Ion Bodgan and David Strang 2009. “Civil Liberty in
America: The Diflbsion of Municipal Bill of Rights
Resolutions after the Passage of the U.S. Patriot Act.” American

Journal o f Sociology 114(6): 1716-64.
Walker, Edward T., John D. McCarthy, and Frank Baumgartner
2011. “Replacing Members with Mangers? Mutualism
among Membership and Nonmembership Advocacy
Organizations in the United States.” American Journal of
Sociology 116(4):1284-337.
Yi, Hongtao and Richard C. Feiock 2012. “Policy Tools
Interactions and the Adoption of State Renewable Portfolio
Standards.” Review of Policy Research 29(2): 193-206.
Zelinsky, Edward A. 1993. “James Madison and Public Choice
at Gucci Gulch: A Procedural Defense of Tax
Expenditures and Tax Institutions.” The Yale Law Journal
102(5): 1165-207.
------. 2004. “Do Tax Expenditures Create Framing Effects?
Volunteer Firefighters, Property Tax Exemptions, and the
Paradox of Tax Expenditure Analysis.” Virginia Tax Review
24:798-825.
http://www.census.gov/govs/state/historical_data.html
http://www.census.gov/
http://www.eia.gov/state/seds/

http://www.epa.gov/clean
Copyright © 2016 The Society for the Study of Social Problems.
Scientific Basis for Environmental Regulation
Public Disclosure and Federal Rulemaking and Advisory
Activities
The scientific basis o f regulation is a long-standing is-sue. In
the 114th Congress, two bills have been referred
for House floor consideration (H.R. 1029 and H.R. 1030)
that would address the public disclosure and transparency
o f scientific and technical information used as the basis for
environmental regulations and other related actions o f the
Environmental Protection Agency (EPA). A bill addressing
similar purposes has been introduced in the Senate (S. 343).
Both H.R. 1029 and H.R. 1030 would amend the En-
vironmental Research, Development, and Dem onstration
Authorization Act o f 1978 (ERDDAA), as amended, to
require public disclosure o f scientific and technical infor-

mation that EPA uses as a basis for agency action. Some
critics have argued that the bills may implicate confidenti-
ality and privacy of personal information if scientific and
technical documents or other materials contain such infor-
mation (e.g., personal health conditions or effects and per-
sonal identifying inform ation about individuals who
voluntarily participate in hum an testing). However, certain
statutes, such as the Freedom o f Information Act (FOIA)
and the Privacy Act, address what information the Federal
Government is required or perm itted to disclose. Both bills
would be implemented in the context of these statutes.
In addition to provisions that address public disclosure,
H.R. 1029, the EPA Science Advisory Board Reform Act
o f 2015, would revise the process for selecting members of
EPA’s Science Advisory Board (SAB), address potential con
flicts o f interest between board mem ber affiliations and
matters subject to board review, and revise the board’s role
in advising EPA on consideration o f scientific information
in carrying out the agency’s mission.
■ EPA Science Advisory Board Reform Act
As reported by House Committee Report 114-33 on March
2, 2015, H.R. 1029 would amend Section 8 o f ERDDAA

From the Library o f Congress, Congressional Research Service
CRS Insights report Scientific Basis o f Environmental Pro-
tection Agency Actions: H.R. 1029 and H.R. 1030, March
11, 2015. See http://fas.org/sgp/crs/misc/IN10244.pdf.
to “provide for Science Advisory Board member qualifica
tions, public participation, and for other purposes.” Vari
ous provisions o f the bill would codify in statute certain
existing procedures that are similar in practical terms,
whereas other provisions would establish new requirements.
The bill would establish a nom ination and selection pro-
cess for members o f the SAB.
The Federal Advisory Com m ittee Act (FACA) is the
general statute that governs the establishment o f the SAB
and other Federal advisory committees across departments
and agencies. FACA also establishes various requirements
for public involvement in Federal advisory committee ac-
tivities. H .R. 1029 would expand public involvement re-
quirements for SAB only.
The nom ination and selection process for the SAB pro-
posed in H.R. 1029 would include opportunities for pub-
lic involvement and require public disclosure of

qualifications and affiliations (including financial interests)
o f nominees to the board. Additionally, the bill would di-
rect the composition o f SAB membership to include repre-
sentation from state, local, or tribal governments and would
explicitly exclude “registered lobbyists.”
In addition to membership, H.R. 1029 would address
the role o f the board in conducting scientific reviews, in-
cluding the avoidance o f potential conflicts o f interest in
instances in which a member may be associated with activi-
ties subject to the board’s review. T he bill would also ex-
pand the documents subject to SAB review to include draft
or proposed risk or hazard assessments, criteria documents,
standards, limitations, or regulations.
T he bill would also amend Sections 8(h) and 8(i) of
ERDDAA in their entirety. The new Section 8(h) would
require EPA to make all reports and relevant scientific in-
formation available to the public concurrently when that
information is made available to the SAB. T he bill would
further require certain levels of public involvement in spe-
cific stages o f board reviews, from the development o f the
scope o f a review to the performance o f the review. The bill
would also require that SAB reviews be made publicly avail-
able in the Federal Register. In recent years, the board has

typically released its findings on EPA’s website.
Continued on page 3 2
6 C o n g re s s io n a l D ig e st ■
www.CongressionalDigest.com ■ May 201 5
http://fas.org/sgp/crs/misc/IN10244.pdf
http://www.CongressionalDigest.com
Scientific Basis CBO Cost Analysis
Continued fro m page 6
The new Section 8(i) would require the SAB to focus its
reviews on rendering scientific determinations, “strive to avoid
making policy determinations or recommendations,” “clearly”
communicate scientific uncertainties, and disclose dissenting
views among board members. The bill would also require the
SAB to periodically assess whether its reviews are “addressing
the most important scientific issues affecting” EPA.
Although H.R. 1029 would establish specific require-
ments for the membership and operations o f the SAB, the

bill would also clarify that none o f its provisions would sup-
plant requirements o f two other laws — FACA and the Eth-
ics in Government Act of 1978. B
■ Secret Science Reform Act
As reported on March 2, 2015, H.R. 1030, the Secret Sci-
ence Reform Act o f 2015 (House Committee Report 114-
34) would broadly address the public availability of scientific
and technical information used to support specific catego-
ries of EPA actions. H.R. 1029, discussed above, would ad-
dress the public availability o f EPA scientific and technical
information more specifically in the context of SAB reviews.
H.R. 1030 would amend Section 6(b) of ERDDAA to
authorize EPA to propose, finalize, or disseminate informa-
tion on specific types of “covered actions” only if the scien
tific and technical information relied on to support those
actions are “the best available science,” specifically identified,
and made publicly available online. The bill defines these cov-
ered actions to include risk, exposure, or hazard assessments;
criteria documents; standards; limitations; regulations; regu-
latory impact analyses; or guidance. Scientific and technical
information is defined as materials, data, and research proto-
cols; computer codes and models; facts; and methodologies.

Although H.R. 1030 would generally require public
disclosure of scientific and technical information, the bill
would limit this requirement to such information only to
the extent that the inform ation would be necessary “for
independent analysis and substantial reproduction of re-
search results.” Information not necessary for these purposes
would not require disclosure under the bill but would be
subject to EPA’s discretion and other applicable statutes such
as FOIA and the Privacy Act.
Whereas H.R. 1030 would establish these responsibili-
ties o f EPA, the bill would limit the agency to obligating
no more than $ 1 million in annual appropriations for these
specific disclosure purposes. ■
C ontinued fro m page 10
Thus, the costs o f implementing H.R. 1030 would ul-
timately depend on how EPA adapts to the bill’s require
ments. (It w ould also depend on the availability of
appropriated funds to conduct the additional data collec-
tion and database construction activities and related coor-
dination and reporting activities under the legislation.)

CB O expects that EPA would modify its practices, at
least to some extent, and would base its future work on fewer
scientific studies, and especially those studies that have eas-
ily accessible or transparent data. Any such modification o f
EPA practices would also have to take into consideration
the concern that the quality o f the agency’s work could be
compromised if that work relies on a significantly smaller
collection of scientific studies; we expect that the agency
would seek to reduce its reliance on numerous studies with-
out sacrificing the quality o f the agency’s covered actions
related to research and development.
O n balance — recognizing the significant uncertainty
regarding EPA’s potential actions under the bill — CBO ex-
pects that the agency would probably cut the num ber of
studies it relies on by about one-half and that the agency
would aim to limit the costs o f new activities required by
the bill, such as data collection, correspondence and coor-
dination with study authors, construction o f a database to
house necessary information, and public dissemination of
such information.
As a result, CBO estimates the incremental costs to the
agency would be around $250 million a year initially, sub-
ject to appropriation o f the necessary amounts. In our as-

sessment, that figure lies near the middle of a broad range
o f possible outcomes under H.R. 1030. CBO expects that
the additional costs to im plem ent the legislation would
decline over time as EPA became more adept and efficient
at working with authors and researchers to ensure that the
data used to support studies are provided in a standardized
and replicable form. ■
32 C o n g r e s s i o n a l D ig e s t ■ w w w .C o n g re s s io
n a lD ig e s t.c o m ■ M a y 201 5
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Contents lists available at ScienceDirect
Energy Policy
journal homepage: www.elsevier.com/locate/enpol
Natural gas and spillover from the US Clean Power Plan into
the Paris
Agreement
Jeffrey C. Peters
James S. McDonnell Postdoctoral Fellow in Studying Complex
Systems, Department of Management Science & Engineering
and Energy Modeling Forum,
Stanford University, United States
A R T I C L E I N F O
Keywords:
Natural gas
Clean Power Plan
Bridge fuel
Fugitive emissions
Paris Agreement

Electric power
A B S T R A C T
Climate change has been identified as one of the today's great
challenges, and mitigation likely requires policy
intervention. As such, in 2015 the United States introduced the
Clean Power Plan (CPP) which aims to reduce
CO2 emissions from electricity production 32% from 2005
levels by 2030 and the Paris Agreement, which seeks
to reduce national greenhouse gas (GHG) emissions, measured
by global warming potential (GWP), 28% from
2005 levels by 2025. However, it remains unknown how the
more narrowly-scoped CPP might affect the ability
to achieve wider-scoped national GHG targets like the Paris
Agreement. In our current state-of-world,
characterized by inexpensive natural gas, the CPP will be met
through large shifts from high-emitting coal
power to less-emitting natural gas power, which translates to a
9.6% reduction in total US 100-year GWP
without accounting for the fugitive methane. Spillover from
fugitive methane could cut this reduction modestly
by 0.2–1.4% or as much as 4.4% if evaluated using 20-year
GWP – elucidating how different assumptions leads
to different perspectives of natural gas as a "bridge fuel". The

results here demonstrate the need to coordinate
policies – either through additional policy (e.g. regulation of
fugitive methane) or a larger-scoped CPP that
includes upstream activities.
1. Introduction
In 2015, the United States Environmental Protection Agency
(EPA)
announced the Clean Power Plan (CPP) with a projection to
reduce CO2
emissions from the electric power generation 32% from 2005
levels by
2030. The EPA identified: i) improving the heat rate of existing
coal
plants, ii) substituting gas power in place of coal power at
existing
plants, and iii) substituting zero-emitting renewable power in
place of
coal power as the three best system building blocks for
achieving the
32% reduction target (Clean Power Plan, 2015).1
The second building block is a key mechanism, because gas
combustion emits approximately half the CO2 emissions of coal

combustion in electricity generation. Following the sharp
decline in
gas prices as a result of the US shale boom, several studies
indicate that
the most economic way of meeting the nationwide emission
target is, at
least in part, via fuel-switching from high-emitting coal power
to lower-
emitting natural gas as well as further capacity expansion in gas
power.
In fact, this transition can be observed prior to the CPP in data
following the fall in gas prices in 2008–2009 (see Fig. 1).
The fall in natural gas price raised the idea of gas as a "bridge
fuel"
to a low-carbon electricity future, with much debate (Kerr,
2010;
Howarth et al., 2011; Levi, 2013; Shearer et al., 2014; Howarth,
2014;
Davis and Shearer, 2014). While this debate continues, Fig. 1
demon-
strates that relatively inexpensive natural gas has already led to
fuel-
switching from coal power to gas power as well as a decline in

total
electricity sector CO2 emissions. When measured by CO2
emissions in
the electricity sector, it is reasonable to state the natural gas is,
at least,
a short-term bridge fuel.
Because natural gas (i.e. methane) is 86 times more potent than
CO2 in terms of GWP over a 20-year period and 34 times more
potent
over a 100-year horizon (Myhre et al., 2013), one of the more
recent
concerns about increased gas power production is the
accompanying
methane emissions from extraction and transmission that occur
prior
to combustion in the power plant.2 While it is difficult to
generalize
pipeline specifications serving gas power plants across the
entire
United States, it stands to reason that increased demand for gas
power
http://dx.doi.org/10.1016/j.enpol.2017.03.039
Received 19 August 2016; Received in revised form 17 March

2017; Accepted 18 March 2017
E-mail address: [email protected]
1 Demand-side management is another key mechanism for
reducing electricity sector emissions. This study uses EIA
Annual Energy Outlook projections of future electricity demand
(EIA, 2016b), which treats energy efficiency implicitly.
2 Aerial observations have shown that atmospheric methane has
increased over the past decade; however, isotope signatures
indicate that the increase may not be attributable to oil
and gas extraction (Schwietzke et al., 2016; Schaefer et al.,
2016; and Nisbet et al., 2016). These studies assume that
methane isotopes from shale and conventional sources are
identical;
however, Golding et al. (2013) suggest that isotopes from shale
sources may be slightly different.
Energy Policy 106 (2017) 41–47
Available online 22 March 2017
0301-4215/ © 2017 Elsevier Ltd. All rights reserved.
MARK

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http://www.elsevier.com/locate/enpol
http://crossmark.crossref.org/dialog/?doi=10.1016/j.enpol.2017.
03.039&domain=pdf
will not contribute significant additional methane leakage
across the
distribution network (i.e. the part of the network that serves
munici-
palities and households), which accounts for approximately 20%
of
methane leakage (EPA, 2014).3 Estimates of fugitive emissions
from
production, gathering, boosting, processing, transmission, and
storage
range from 1.1% (EPA, 2016) to 5.6% (the mean of the high-end
of
conventional and shale gas development minus distribution from
Howarth et al., 2011) of total production, with a majority of
studies

settling slightly above the low-end EPA value (Brandt et al.,
2014;
Lyon, 2016).4 In an effort to address fugitive emissions, the
EPA
established a federal rule seeking to reduce fugitive emissions
by 40–
45% (New Sources Performance Standards, 2016). Whether this
target
will be met through the regulation remains to be seen.
Regardless of what the actual rate may be in 2030, these
fugitive
emissions would not fall within the current scope of the CPP,
but are
still relevant in climate change mitigation. Despite its limited
scope, the
CPP is cited as a major component of the US contribution to the
United
Nations' Paris Agreement, a more broadly-scoped target that
seeks to
reduce net US greenhouse gas (GHG) emissions, measured by
100-year
global warming potential (GWP), by 28% from 2005 levels by
2025 (US
Department of State, 2016).

It remains unknown how the more narrowly-scoped CPP (i.e.
CO2
emissions in the US electricity sector) might spillover into
wider-
scoped national GHG targets like the Paris Agreement. A
spillover
effect is a situation where an activity has an unintended
consequence
on another seemingly unrelated activity. In terms of the CPP,
the
spillover is cross-sectoral in that emissions may increase in
sectors
outside the scope of the mitigation policy (i.e. outside the CO2
emissions in the electricity sector). This idea echoes arguments
for
life-cycle instead of production-based emission policies as well
as for
life-cycle accounting in the study of energy and economic
systems (e.g.
Burnham et al., 2011; Weber and Calvin, 2012).
The question here is: how will the CPP mechanisms, designed to
reduce CO2 emissions in the electricity sector, affect broader
climate

change mitigation goals like the Paris Agreement considering
the
spillover from fugitive methane emissions? In the process of
answering
this question this article provides: i) life-cycle emission
analysis
combined with energy-economic modeling of the electricity
sector, ii)
clarity in the debate about whether natural gas is or is not a
bridge fuel,
and iii) a consensual path forward that would help reduce policy
spillover through measurement and policy adjustment to
mitigate
fugitive methane emissions.
Section 2 introduces the scenario planning framework and
energy-
economic model used to explore the interaction between the
CPP and
the Paris Agreement targets. The four scenarios explore
technological
contributions to total US electricity generation in 2030 under
low and
high natural gas prices, with or without CPP implementation.

Section 3
describes the specific data and assumptions used to project
technolo-
gical contributions to 2030 US electricity production and the
accom-
panying emissions from both combustion and fugitive
emissions.
Section 4 discusses the scenario results and the fugitive
emissions for
the four scenarios. Section 5 draws conclusions from the
analysis and
suggests a path forward through measurement and policy that
could be
met with broad consensus to reduce spillover from the CPP into
broader climate change mitigation objectives like the Paris
Agreement.
2. Methodology
There is, of course, great uncertainty in answering the question
of
spillover. First, models that predict large shifts to gas power
assume
that current natural gas prices represent a new normal. This may
not be

the case due to price rebound effects, especially in the face of
possible
liquefied natural gas exports, or even moratoriums on horizontal
drilling and hydraulic fracturing (i.e. fracking). Second, the
CPP itself
faces legal challenges in the Trump Administration, US
Congress, as
well as the US Supreme Court where it is, at the time of
publication, put
on hold. Third, the GWP of fugitive emissions depends on
assumption
regarding the emission rate, effectiveness of EPA regulation,
and the
time horizon of the analysis. The following sections describe
the
scenario-based analysis using an energy-economic model to
project
technological contributions to US electricity generation and the
corre-
sponding CO2 emissions from combustion as well as fugitive
methane
emissions from expanding gas infrastructure.
2.1. Scenario analysis

The uncertainty in the spillover question is well-suited for
scenario
planning where different “states-of-the-world” are simulated in
the
same modeling regime in order to tease out the important
mechanisms
and assumptions leading to different projections of the future.
The four
scenarios here assume pre- or post-shale boom gas prices (2007
and
Fig. 1. US electricity sector CO2 emissions drop because of
fuel-switching from coal to gas power as a result of falling gas
prices following the shale gas boom in 2008. Source: EIA,
2016a.
3 Continued low gas prices could lead to increased gas demand
in households,
businesses, and industries where total fugitive emission rates
could be higher because
these sectors us the distribution network. This impact is not
explored in this particular
work.
4 Schneising et al. (2014) suggests fugitive emissions from

shale plays could be much
higher than the high-end used in this article; however, this
estimate seems to be an
outlier from the wide body of literature that fits into the range
used here. The
implications of using the Schneising et al. (2014) estimate is
straightforward in the
results (that is, more fugitive emissions than the high-end
presented here).
J.C. Peters Energy Policy 106 (2017) 41–47
42
2014 prices, respectively) in combination with or without CPP
im-
plementation using an effective CO2 tax on combustion.
Table 1 shows the underlying future perspective of these four
scenarios. The high gas price (HG-) scenario uses the 2007
price of
natural gas, which can be interpreted as either that the shale gas
boom

is a short-lived phenomena or that state or federal moratoriums
ban
the practice of fracking. This could be described as the "past as
future"
scenario, where the impact from the shale gas boom quickly
dissipates.
The low gas price (LG-) uses the 2014 gas price and can be
interpreted
as an optimistic outlook for the price of shale gas as the "new
normal"
due to sufficient reserves, a high elasticity of supply from the
reduced
cost and timeline of drilling unconventional wells, and
continued
technological advance in drilling. The business-as-usual (-BAU)
sce-
narios assume that coal regulation and investment tax credits for
wind
and solar are maintained to 2030, while the CPP (-CPP)
scenarios use
an additional tax on CO2 to meet the 32% reduction target of
the CPP.
Section 2.2 describes the model used to project technological
contributions to electricity production and emissions in 2030.

Section
3 describes the additional data and assumptions that are used in
the
model to study the four scenarios.
2.2. Electricity sector and emission projections
These four scenarios are analyzed using a non-linear partial
equilibrium energy-economic model that projects US electricity
gen-
eration by technology and their associated emissions (Peters and
Hertel, 2017). The set of technologies included in the model
are:
nuclear, coal, gas base load (e.g. combined-cycle), gas peak
load (e.g.
combustion turbine), oil, hydroelectric, wind, solar, and other
(pri-
marily consisting of geothermal and waste) power. Short-run
changes
in utilization with existing capacity in response to prevailing
economic
conditions, such as the gas price drop, are tied to longer-run
capacity
additions and retirements via returns to capital making it an
ideal

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