When Do Agencies Have Agency?: Bureaucratic Noncompliance
in the EPA
Miranda Yaver
Columbia University
[email protected]
July 13, 2014
This paper raises a question that is little-discussed yet central to lawmaking and policy implementation in the American separation-of-powers system: Under what institutional
conditions do we observe variation in bureaucratic compliance with legislative dictates in contemporary statutory implementation? The paper challenges the assumptions of conventional
delegation models and holds that variation in institutional conflict and oversight of agencies
fundamentally reshape agencies’ latitude as active policymakers. I answer this question in
the context of the Environmental Protection Agency from 1973-2008 using a novel and original dataset on noncompliance. The study provides the first empirical analysis of the extent
of, and the conditions underlying bureaucratic noncompliance in policy implementation in
the US, providing support for the hypotheses that amid heightened inter-branch ideological
conflict, the EPA increasingly deviates from congressional preferences in implementing the
delegating statutes.
Ph.D. Candidate in Department of Political Science at Columbia University. I am grateful to the Tobin
Project for providing valuable financial support for this research. Sean Gailmard, Ira Katznelson, George
Krause, Jeff Lax, Sharece Thrower, and Mike Ting provided helpful comments and suggestions. I am
especially indebted to Sean Farhang and Greg Wawro for their detailed comments on multiple versions of
the paper. All errors and omissions are of course my own. Ethan Cramton and Lara Chehab provided
valuable research assistance.
1
The 1980s were marked by heated inter-branch conflict over the proper role of the Environmental Protection Agency in implementing environmental legislation. Even a cursory
glance at headlines on environmental policy during this period reveals dozens if not hundreds
of accounts of lawsuits requiring the EPA to enforce legislation under its jurisdiction, and
alleging failures in its implementation. These battles call attention to the importance of
understanding better the conditions driving agencies to seek to shift policies toward their
preferences in statutory implementation rather than adhering to the delegating statutes, and
the policy implications of these decisions.
With the development of the modern regulatory state came great expectations about
the role of government in providing services to its citizens, leading to a marked increase in
regulation and congressional delegation to better facilitate that policymaking. But while
these statutes lay out policy goals, there is much variation in the clarity with which they
specify policy details to be carried into action. Much ink has been spilled in the political
science literature on inter-branch conflict and delegation in lawmaking by statute, calling
attention to congressional strategy in allocating discretion to agencies as well as to courts
(see, e.g., Epstein & O’Halloran 1999; Huber & Shipan 2002; Farhang 2010). Yet for all
this discussion of conditions underlying congressional delegation to other institutional actors
(namely, agencies), there has been little scholarly attention to statutory implementation and
the consequences of these delegation decisions.1
While much of the extant research on the separation of powers in lawmaking emphasizes
the institutional design elements of laws, the “agency theory” synthesis in response to Lowi
and others’ concerns of congressional abdication suffers from the problematic assumption
that agencies cannot take actions that Congress does not at some level prefer, even though
they may in truth be capable of deviating from their discretionary windows. That is, com1
While Patashnik (2008) provides an excellent qualitative treatment of the aftermath of major policy
enactments, his emphasis is on their overarching sustainability, as opposed to the subtler changes in state
capacity, and we know little about the larger scale extent of these dynamics.
2
mon delegation models claim that Congress will (1) delegate to an agency but (2) impose
procedural controls, and (3) the agency will comply in order to avoid punishment. However,
a number of important conditions reshape the likelihood of the agency suffering consequences
for defections. This is particularly relevant given that many of the most significant laws being implemented were passed several Congresses ago. Agencies implement laws passed by
the 110th Congress as well as laws passed amid the New Deal, and the policy preferences of
these Congresses may be highly divergent. This calls into question the appropriate administrative implementation given the preferences of the legislative principal(s). The extent to
which compliance with statutory implementation is a reality in the US can importantly call
into question Moe’s claim that in the American separation of powers system, “[w]hatever is
formalized will tend to endure” (Moe 1990, 240).
While awareness of the rules is key with respect to predicting degrees of compliance
with laws, “normative and social motivations for compliance are as influential as calculated
motivations in bringing about compliance” (Winter & May 2001, 1692). Thus, while this
paper is a far cry from characterizing administrative actors as engaging in rampant lawbreaking, they have adequate room to skirt the edges of their allocated authority (even
extending beyond it) given a combination of normative and social incentives that extend
beyond the text of the laws that they are tasked with implementing. The question then
arises, If Congress passes a law and the bureaucracy is not bound by it, in what sense is
law supreme, in what sense does it bind the executive, and in what sense does popular
will determine the general course of public policy? This article argues that the literature’s
failure to link congressional delegation choices to the ultimate implementation decisions and
policy outcomes is a severe shortcoming if we want to understand the effects of institutional
dynamics on public policy.
In working to correct this deficit, the paper seeks to answer a little-discussed, but nevertheless central question about American lawmaking: Under what institutional conditions
3
do we observe variation in bureaucratic compliance with legislative dictates in contemporary
statutory implementation? Answering this question enables us to understand better the
extent of and conditions contributing toward bureaucratic noncompliance and implementation outcomes amid inter-branch conflict. It supports Wood’s (1992) claim that we gain
important insights by examining not a single federal structure, but rather the complexities
of the system of implementation, and holds that the predominant political conditions of
polarization and gridlock open new doors for agencies to be more active policymakers than
the extant literature acknowledges. It sheds important new light on the extent the rule of
law is a reality in the United States, and the mechanisms underlying statutory policy change
in the American political process.
Applying these questions of bureaucratic drift to the Environmental Protection Agency
(EPA) from 1973-2008, the article argues that given varied conditions in partisan conflict
between the branches and within the legislature, agencies’ incentives to comply with the
delegating statutes are fundamentally reshaped in ways not fully recognized in the political
science literature to date. While oversight mechanisms can work to keep these agencies in
check, the multiplicity of oversight actors can create further opportunities for agencies to exploit coordination problems and set policies closer to their preferences. These deviations from
the authorizing statutes can compromise potentially well-established bureaucratic autonomy
as Congress observes that its trusted agents are no longer using that latitude consistent
with its preferences. And relatedly, given the ample potential for these agency defections,
Congress can carve out for itself a more active role in the lawmaking game by continuing to
revise policy substance and implementation to better control its agents.
I begin by discussing my conceptualization of bureaucratic noncompliance and the implementation strategies involved, proceed with a brief discussion of my selection of the case
of the EPA, and move on to discuss the novel and original dataset with which I test my core
hypotheses. I find strong support for the claim that inter-branch partisan conflict is a strong
4
predictor of compliance by the Environmental Protection Agency, though there is less clear
support for my claim about the effect of multiple principals.
Understanding Bureaucratic Noncompliance
The many veto players at work in the American political process virtually guarantee
that the key actors in the branches will have divergent preferences over policy. The paper’s
emphasis on noncompliance seeks to explain agencies’ incentives and their responses to increases in the polarization in which they operate. I adopt Wilson’s (1989) assumption that
bureaucrats hold preferences about their personal condition – such as self-promotion, power,
prestige, and financial reward – and about the policy in which they are engaged. In turn,
noncompliance by these politicized agency heads grows out of their combined incentives over
both political and policy influence, particularly with respect to domains of high salience
and/or partisan conflict. It then results in agencies carving out greater opportunities to be
active policymakers regardless of the status quo location.
While the paper focuses on a single agency – the Environmental Protection Agency –
instances of noncompliance can be found across a number of domains. Carpenter (2010) calls
attention to two such episodes within the Food and Drug Administration, from different
political parties and each resulting in ultimate rejection of the agency’s efforts such that
policy retreated to its prior state.2 Johnson (2011) calls attention to the patterns and
persistence of racial discrimination in the US Department of Agriculture’s loans and subsidies
to black farmers, even decades after Congress’s passage of the Civil Rights Act. Moreover, the
1980s saw multitudes of complaints by private parties and interest groups alleging negligence
on the part of the EPA and the Equal Employment Opportunity Commission, to name a
few. Thus, from consumer protection to environmental protection to civil rights, there have
2
The first (Democratic) move by the FDA was made by then-FDA Commissioner David Kessler, whose
efforts to regulate tobacco were struck invalid in FDA v. Brown & Williamson Tobacco Corp. Additionally,
conservative and libertarian forces sought to extend the FDA’s power over pharmaceuticals on a federalist
dimension in 2001 with the introduction of state tort preemption. However, the Supreme Court also struck
down these efforts in Wyeth v. Levine.
5
been a number of salient battles over the proper extent of administrative enforcement of
federal statutes.
In exploring these phenomena, this paper departs from a number of conventional models of congressional delegation that assume faithful agency execution of legislative dictates –
that is, with the will of their principal(s) – and instead extends the few models that allow for
bureaucratic subversion. Despite Epstein & O’Halloran’s (1999) emphasis on constraints on
agency discretion, which in theory successfully preclude drift from congressional preferences,
Gailmard (2002) examines a legislature’s delegation of implementation power to an imperfectly controlled bureaucrat who can subvert the legislature by stepping beyond the bounds
of explicitly delegated authority. In delegating to agencies that Congress nevertheless takes
measures to control (e.g., Epstein & O’Halloran 1999; Huber & Shipan 2002; McNollGast
1987, 1989), there is a problem of restricting the agent’s ability to choose unauthorized policies. Even well-designed administrative procedures allow for some degree of bureaucratic
drift, and agencies are commonly thought to be ideological actors whose preferences may
well diverge from what the statute provides (see, e.g., Clinton & Lewis 2008). Agencies can
choose policies beyond what the legislature authorized, but the farther beyond the bounds of
delegated authority, the greater the likelihood of being exposed, and the higher the potential
costs (Gailmard 2002). Similarly, Huber & McCarty (2004) allow that the policy that the
bureaucrat sets (a − ω) may or may not comply with the statute, though they do not require
that such noncompliance be intentional on the part of the bureaucrat. While overt acts of
punishment for noncompliance may at first blush appear rare, given that punishment for
noncompliance effectively represents off-equilibrium paths, there is likely to be a plethora
of unobserved agency noncompliance in which they successfully shift policy consistent with
their preferences.
Of course, discussing bureaucratic noncompliance begs the question: noncompliance with
what? There is a little-discussed principal agent problem in statutory implementation, which
6
is that while Congress writes the laws, the authorizing Congress does not engage in much of
the ex post monitoring of the agents to whom it delegates because the coalition changes (to
varying degrees) every two years. This phenomenon is analogous to delegation by cabinet
ministers in parliamentary systems, in which the principal delegating to the bureaucrat is,
unlike a common assumption in delegation models of the United States, not a stable principal
(Huber & Lupia 2001, 19).
I argue that contrary to the dominant Congress-agency principal-agent relationships specified in delegation models, there are in fact two legislative principals, one of which lays out
provisions for ex ante bureaucratic control in drafting the authorizing legislation (e.g., reporting and consultation requirements), and the subsequent legislative principal engages in
ex post control consistent with their policy preferences, but potentially at the cost of enforcing the letter of the law as opposed to their own preferred outcomes. The expectation
given conventional understandings of the judiciary is that courts interpreting statutes would
expect compliance with the enacting Congress – that is, the statutory text.3 Yet given the
various models of congressional relationships with bureaucracy, there is reason to expect that
agencies would see value in implementing in accordance with the preferences of their current
principals – the contemporary Congress – rather than upholding outdated statutory provisions. After all, it is the Congress currently in power that is empowered to punish an agency
for what it perceives as transgressions, and there is a legitimate question as to whether the
108th Congress would seek to uphold the statutory bargain struck by the 88th Congress,
as opposed to seeking to push policy toward its own preferences. Thus, agencies can fail to
comply with either the text written by the authorizing Congress – which raises questions
of to what extent we observe the rule of law as opposed to the substitution of bureaucratic
preferences – or with the contemporary Congress to which it can be held accountable, which
is consistent with the more common delegation and bureaucratic control stories of American
3
Landes & Posner (1975) hold that courts “do not enforce the moral law or ideals of neutrality, justice,
or fairness; they enforce the ‘deals’ made by effective interest groups with earlier legislatures.”
7
institutions. To which of these political principals agencies are most attentive (and under
what conditions) is an issue not confronted directly by the delegation literature, and one
that this project seeks to explore.
The Strategy of Noncompliance
Theory suggests that agencies will comply with the statute rather than defect and suffer
adverse consequences such as the retraction of enforcement powers or funds with which to
operate. Yet a number of factors fundamentally alter agencies’ incentive structure, affecting
compliance and the likelihood of being identified and punished for that subversion. That
is, in the absence of a genuine likelihood of punishment, the congressional majority and the
administrative agency may be playing a fundamentally different game.
I hold that the expected value of noncompliance in policy implementation is a function
of the agency’s expected benefit if prevailing in moving policy toward its preferences, as
well as the costs of not complying. The expected benefit of noncompliance is the payoff of
moving policy if implemented successfully, but one must account for the expected costs of
punishment if caught defecting, such as the reduction of funds or discretionary authority,
or the imposition of stricter deadlines for implementing the statutory provisions under its
jurisdiction. Noncompliance is made an attractive option for the agency when the expected
value of noncompliance is positive – that is, when the benefits outweigh the costs of the
strategy.
The expected benefit will be affected by the extent to which the agency would be moving
policy by not complying with legislative dictates, and thus is a factor of issue salience as well
as ideological discrepency between the status quo policy and the agency’s own preferences
over policy. As such, this benefit should be greater among more significant laws and amid
heightened legislative-executive ideological distance as opposed to amid unified government,
when preferences are better aligned across the branches. Moreover, if the status quo location
is close to the agency’s preferences, then there will be little room for policy movement, and
8
thus will not likely provide adequate motivation to deviate and risk punishment.
The probability of successfully implementing the new policy depends on the agency’s
autonomy, as well as the complexity of the issue at hand. With implementation power
concentrated within a single agency, there is more freedom to shift the policy location,
whereas administrative fragmentation should constrain agency capacity (Farhang & Yaver
2013). While Maltzman & Shipan (2008) do not take on issues of agencies’ statutory enforcement, they observe less durability among more complex laws, which are more prevalent
amid heightened ideological conflict. Thus, I hold that having fewer competing administrative actors should raise the probability of effectively implementing the preferred policy,
while that probability will decline amid more fragmentation (and thus less autonomy) or
more statutory complexity.
The agency does not suffer any costs if complies, and the costs of noncompliance increase
as a function of the distance outside of the allotted discretionary window. The expected
likelihood of punishment will be driven by a number of factors, including the size of the
majority party in Congress and the extent of partisan division within it, and whether the
agency wants to pursue a policy that is higher or lower than that set by the authorizing
statute. That is, the agency’s choice set does not include only comply or not, but rather
to regulate more than the statute provides, regulate less than the statute provides, or to
implement policy in accordance with the statute.4 And while Congress can utilize the power
of the purse to constrain an agency from taking actions beyond the statute, there are fewer
tools at Congress’s disposal in controlling an agency that wants to underenforce the statute
with which it fundamentally disagrees (Ting 2002).
Thus, the dynamics of congressional control of the bureaucracy are asymmetric depending
upon the pro- versus anti-regulatory nature of the agency with respect to the law it is tasked
4
That is, if x denotes policy and d denotes the level of delegation by Congress, then the agency may
choose to comply by setting x = d, or it may choose x < d if it seeks to deregulate relative to the legislature’s
preference, or it may choose x > d if it seeks a more aggressive policy than that set by the statute.
9
with implementing. With higher levels of legislative conflict, the likelihood of punishment
declines given the difficulty of passing legislation that would curb agency behavior. However,
with a large partisan majority held by the opposing party, there is greater potential for costly
punishment for noncompliance, which in turn affects the overall expected value of pushing
policy from the rule of law to the agency’s preferences over policy and motivates a higher
level of bureaucratic compliance. And the ways in which these factors interact should give
us better leverage in understanding the conditions under which agencies test the boundaries
of their authority, and succeed or fail in doing so.
Hypotheses about Bureaucratic Noncompliance
A well-established literature has called attention to congressional efforts to impose constraints and reduce administrative discretion amid divided government and electoral uncertainty so as to guard against bureaucratic drift in statutory implementation (e.g., Epstein &
O’Halloran 1999; Huber & Shipan 2002; Farhang 2010; Moe 1989). Moe argues that, even
aside from ideological differences between Congress and the president, there are fundamental
institutional divisions which will give the branches different preferences over the exercise of
bureaucratic authority. As compared to presidents and the bureaucrats they appoint, legislators are influenced more by particularistic than national interests and are more subject
to interest group pressure, potentially leading to divergent preferences over regulatory implementation (Moe 1989; Moe 1990). Horn & Shepsle (1989) similarly hold that enacting
coalitions must try to protect the deal it has struck at enactment from the predations of
various actors. Thus, legislators and the interest groups that influence them strive to create
agency structures calculated to implement their policy preferences while tightly constraining
discretion so as to insulate policy, to the degree possible, from executive subversion. Given
these concerns about subversion under conditions of institutional disagreement – and in particular under heightened legislative-executive ideological distance – I expect that agencies
will be most inclined to seek to shift policy from the statute toward its preferred implemen10
tation under such conditions of divided government and ideolgical conflict over key policy
interests. Thus:
H1 : Agencies will be more likely to deviate from the statute when there is higher ideological
divergence between the legislative and executive branches, except when the opposing political
party in Congress is well-positioned to pass legislation to punish the agency.
A number of factors may affect the likelihood of identifying noncompliance and in turn,
imposing costs for that behavior. While Gailmard (2002) identifies as subversion costs as
lawsuits or loss of budgets or status, this project considers also the statutory adjustment of
discretionary windows, which of course relies upon a congressional coalition eager and able
to pass new legislation. A rich literature on Congress has explored the causes and consequences of legislative conflict, which arises given individual legislators’ preferences relative
to the location of the status quo,5 as well as the important role of the filibuster as a tool
to embolden minorities to block legislation that lacks supermajority support in the Senate
(Wawro & Schickler 2006). Given the numerous veto points in the legislative process, lawmaking becomes increasingly costly when there is diversity of preferences over policy. Thus,
amid narrow partisan majorities or greater partisan differences within or across the chambers
of Congress, there is compromised ability to pass legislation to shift the policy location.
In the face of such legislative conflict, agencies may therefore perceive a lesser threat of
such statutory punishment given the elevated transaction costs of lawmaking, which requires
considerable effort on the part of Congress. That is, to be punished by the legislature,
there must be some threshold level of cohesion sufficient to pass a law that would retract
agency capacity, and committees cannot credibly threaten to introduce legislation under
certain circumstances (see also Ferejohn & Shipan 1990). I examine the degree of legislative
cohesion versus conflict based on the size of the legislative majority, and based on the degree
of ideological distance between the chambers. Thus:
5
See, e.g., Brady & Volden 2008; Krehbiel 1998.
11
H2 : Agencies will less likely to deviate from the statute when the transaction costs of
lawmaking are lowered by large majority coalitions or ideological cohesion betwene the House
and Senate.
Gailmard (2002) lists among the factors affecting subversion costs the congressional committees with oversight jurisdiction. Moreover, oversight challenges can arise from having
multiple principals, with information leakages and collective action problems compromising
collective control over agents (Gailmard 2009). These problems can lead to the underprovision of congression oversight of agencies, leading Gailmard (2009) to conclude that
redundancy in oversight jurisdiction will not necessarily increase its effectiveness.
Given this limitation in effective oversight, one might expect that having more actors
with power or influence over an agency (e.g., congressional committees and subcommittees,
the president, interest groups) should reduce subversion costs and thus increase the range of
non-delegated policy where agencies can implement without a high likelihood of punishment.
Such challenges of multiple principals can arise not only within, but also across Congresses
when there are great ideological departures from a law’s enacting coalition. Bawn (1995)
raises as a limitation her own analysis that her model treats the legislature as a single decisionmaker with coherent preferences, whereas more recent work on legislative-executive
conflict has examined multiple legislative principals (e.g., House, Senate, committees) exercising influence over the executive branch. And as Clinton et al (2013) demonstrate,
fragmentation of legislative oversight of agencies among committees is quite striking, which
we can expect is one of many examples of the limitations on bureaucratic control that in
turn shape agency behavior:
H3 : Agencies will be more likely to deviate from the statute when there are multiple
principals seeking to influence it, as indicated by greater NOMINATE differences between
the current and authorizing Congresses and by a greater presence of interest groups.
Of course, the presence of multiple political principals can potentially reduce incentive
to deviate, given the increased number of monitors capable of detecting noncompliance. Yet
12
when the principals are in tension with one another, the conflicting goals and pressures on
the agency should sway the agency’s implementation strategy in ways likely to induce that
noncompliance.
While one might plausibly expect that noncompliance would only occur in a single period
– that is, that an agency capitalizes on its expanded capacity, is punished, and complies
moving forward so as not to suffer adverse consequences again – examination of a time series
plots suggest that there are ebbs and flows in noncompliance over the full range of the study.
This provides evidence in support of my claim that it is in fact an ongoing, dynamic interbranch game at work. Below I provide empirical tests of these hypotheses within the context
of the Environmental Protection Agency.
Other Predictors of Noncompliance
The hypotheses above capture the dominant institutional dynamics that I expect to
shape agency compliance (or lack thereof), but they are by no means exclusive. Huber &
McCarty (2004) hold that low bureaucratic capacity diminishes bureaucrats’ incentives to
comply with legislation, thus reducing politicians’ ability to hold bureaucrats to effecting policy consistent with their preferences. Yet their resource-based conceptualization of capacity
departs markedly from my operationalization of this concept to be more parallel to Carpenter’s (2001) analysis of bureaucratic autonomy, according to which agencies may achieve that
autonomy in policy implementation by building organizational reputations for efficiency. It
is with this line of argument that Carpenter puts bureaucratic politics at the center of state
transformations, recognizing bureaucrats as politicians and challenging what he sees as the
misguided conception of policy analysis that holds “[f]irst comes a social movement, then
comes legislation... then comes rote administrative implementation” (Carpenter 2000, 123).
Rather, agencies’ important roles as policymakers must be understood better.
I consider administrative capacity to be the ability of an administrative agency to effectuate policy consistent with its policy preferences in the separation-of-powers system, and
13
it can vary given – among other things – the manner in which Congress structures policy implementation. On the one hand, the increasing congressional fragmentation of the
administrative state (Farhang & Yaver 2013) may reduce agency incentives to execute the
statute faithfully, instead shirking responsibilities. Yet dispersing power across multiple
actors should operate as a meaningful constraint on agency behavior, forcing compromise
among administrators with different preferences and interests as well as creating competition
among them. While Lewis does not view administrative fragmentation as being necessarily
bad, he holds ultimately that “agencies that are not designed to be effective will not be,” and
that such choices in bureaucratic structure of policy are made “most immediately to remove
certain policies from presidential political influence” (2003, 7). Thus, if this legislative strategy is effective, administrative actors will be kept more or less in check rather than leaving
noticeable room for bureaucratic drift in policymaking given the added coordination and
compromise required to implement. I thus expect there to be a negative association between
fragmentation of implementation power and agency deviations from legislative dictates.
Furthermore, with greater policy salience and significance, the stakes in policy implementation are raised relative to ordinary legislation over which we may be less likely to observe
institutional conflict (see, e.g., Cameron 2000). And while this will have the likely effect of
increasing congressional monitoring of how agencies implement those policies, I argue that
it will nevertheless be within this policy domain that we are most likely to observe agencies
having strong preferences over implementation, and where ideological disagreements are most
likely to play out. I additionally expect that ideological proximity between the DC Circuit
and other branches will shape the extent to which Congress and the court will intervene in
bureaucratic policymaking given perceived noncompliance in implementation.
Why the EPA?
The Environmental Protection Agency serves as a compelling case for examining the interplay between congressional preferences in lawmaking and administrative implementation,
14
but with sufficient variation over time to avoid selection on the dependent variable of bureaucratic noncompliance. Moe calls attention to the inefficiencies built into the structure
of the EPA, which he holds was “never designed as a coherent organization. Its presidential
creators pulled together disparate programmatic units under one roof, viewing this as a first
step toward a coherent organizational structure... Throughout its life, the EPA has been
hobbled by its programmatic inheritance” (1989, 317). He adds that amid extensive conflict
among Congress, the executive branch, and environmental interest groups, the EPA was
burdened with cumbersome procedures, requirements, and deadlines, which left it lacking in
the capacity to effectively analyze environmental problems or justify its policy decisions.
One can scarcely search records of the Environmental Protection Agency without finding
numerous accounts of states and interest groups suing the agency to mandate enforcement of
environmental standards over recent recades. Implementation problems in the EPA reached
a notable peak amid President Ronald Reagan’s “regulatory relief” efforts, which sought to
markedly scale back federal regulatory efforts in this domain. Farhang notes that Reagan
sought to withdraw the administrative enforcement machinery, dramatically reducing the
EPA’s budget and staffing as well as seeking to cut back on private environmental lawsuits
that could threaten the administration’s efforts to reregulate environmental policy (2011,
676). Landy et al observe that administrative turbulence between 1980 and 1982 led to
sharp curtailment of environmental enforcement efforts, with a 50% decline in the number
of cases that the EPA referred to the Justice Department and approximately a 33% decline
in the number of enforcement orders that the EPA issued (1990, 249). It was during this
period that the EPA sought actively to shift environmental enforcement from the federal
government to the states, with crippling blows to the EPA budget rendering the agency
often incapable of carrying out even simple regulatory responsibilities (Id at 272).
Wood & Waterman (1993) likewise call attention to the importance of understanding
bureaucratic adaptation within the context of the Environmental Protection Agency. They
15
argue that bureaucratic behavior can be shaped by discrete events, progressive events, and
other sweeping shifts in the policy environment in which the agencies operate. While they are
correct to comment that “[p]ast models of politics and the bureaucracy ignored the complex
stimulus environment of the bureaucracy” (1993, 499), their restriction of analysis to referrals for litigation6 leaves many important questions unanswered, such as other institutions’
responses to the agency outputs that they identify.
While the EPA’s implementation under the Reagan Administration is in a sense a model
example of the regulatory behavior under my microscope, its enforcement has not perpetually
waned, with Democratic administrations typically seeking to make the agency less anemic in
its regulatory capacity. Thus, in addition to being a highly salient case, there is substantial
variation in partisan composition and regulatory support for the agency over time which
allows me to assess the effects of inter-branch conflict on agency implementation behavior
and to test the hypotheses discussed above.
The Alternative Hypothesis: Agency Learning
This paper argues that bureaucratic noncompliance is driven systematically by ongoing
separation-of-powers policy battles among the branches. However. given the challenges
raised by statutory complexity (see, e.g., Melnick 1991), there is the alternative hypothesis
that agencies are not actively choosing not to comply, but rather are uncertain about the
meaning (or intended meaning) of the statute that they are tasked with implementing.
Consistent with this alternative story, Winter and May (2001) note that at least some level of
awareness of rules was expected of entities in order to comply with environmental regulations,
with entities with little awareness having limited compliance. In such a setting, declines in
agency punishment would constitute the agency’s learning about the proper interpretation
6
They acknowledge directly that it captures only a single dimension of enforcement, but defend the
measure on the grounds that it “reflects the willingness of program offices to pursue implementation through
to final conclusion” (Wood & Waterman 1993, 499). However, it fails to capture the important roles of the
legislature and courts in monitoring compliance or lack thereof.
16
of the law before them.
If agency learning is in fact the process that is at work, one would expect to find that
at time t0 , Congress passes a given law; the agency then attempts with only mixed success
to interpret thhat law and in doing so experiences a dramatic increase in litigation and
“noncompliance”; through this litigation and the suits’ resolution, the agency learns the
proper interpretation of the statute; and thus one observes a sharp decline and then plateau
in punishment for agency transgressions in implementing.
Testing this alternative hypothesis is a relatively simple task through examination of time
series plots of the statute-level noncompliance measure for laws passed since 1973, the start
of this study. Figure 1 plots the patterns in bureaucratic punishment over time in four laws
– the Clean Air Act, the Federal Water Pollution Control Act, the Resource Conservation
and Recovery Act, and the Toxic Substances Control Act – as indicated by both of the
dependent variables used in the study and discussed in greater depth below. While there
are noticeable spikes in noncompliance in the earlier part of the time series for some of
the laws in the sample, the plots nevertheless reveal marked ongoing volatility in the levels
of punishment. This is strongly suggestive of a more systematic factor at work in driving
bureaucratic behavior. Thus, while statutory complexity may to xome extent compromise
the inherent “truth” of a law, this does not appear to be the main factor at work in the
processes that this paper analyzes.
Empirical Model
The Dependent Variable: Bureaucratic Noncompliance. Measuring bureaucratic
noncompliance is no easy task, and no empirical work to date (as far as I am aware) has sought
to capture this behavior systematically. I provide two novel measures of noncompliance – one
to measure noncompliance with the text of the statute ( the delegating congressional principal), and one to measure deviations from Congress’s preferred statutory implementation
(the principal currently empowered to impose sanctions).
17
To measure noncompliance with the text, I identified through Lexis searches of each
statute the 567 DC Circuit cases from 1973 through 2008 in which the EPA was the defendant, and read each majority opinion to determine whether the agency lost on substantive
grounds. While the district courts are typically the first venue of litigation, suits against
administrative agencies often go straight to the appellate courts, making this an appropriate
level of analysis. I restricted the analysis to the DC Circuit because of its status as the main
circuit addressing Administrative Procedure Act cases and other suits against agencies. The
predominant reasons for the EPA’s loss was the issuing of rules or enforcement that were
inconsistent with the delegating statutes, or causing unreasonable delay in enforcing the acts
under its jurisdiction. In assessing whether the EPA was found noncompliant, I excluded
those cases that were decided on procedural grounds (e.g., standing or notice and comment
procedures).7 Using these criteria, I found that the EPA lost 129 (or approximately 23%)
of these cases.8 This measure EPA Suits Lost is the percentage of EPA losses per law per
Congress (see Table 2 for summary statistics).9 [Table 2 goes here.]
The second measure, Agency Curbing, captures congressional dissatisfaction with the
EPA’s implementation. Following Clark’s (2011) original court curbing data collection, I
measured agency curbing through the introduction of bills from the 93rd to the 110th Congresses for which the CRS bill summaries indicated that the bill sought to control the EPA’s
behavior by (1) requiring that the EPA take new regulatory actions (e.g., the issuing of new
rules, the imposition of sanctions for violators), (2) prohibiting the EPA from taking certain
regulatory actions or otherwise withdrawing EPA authority (e.g., rescinding EPA funds or
7
Among the language determined to count as noncompliance were “regulation violated Clean Air Act”
(American Corn Growers Association v. EPA, 2002), “EPA abused its discretion in promulgating Tribe’s
redesignation” (Administrator, State of Ariz. v. EPA, 1998), and “[EPA’s rule] was unreasonable and
arbitrary” (Kennecott Corp. v. EPA, 1979).
8
An additional 49 cases were lost due to procedural matters such as notice and comment regulations. It
typically is the case that those issues settled by the EPA pertain to agency inaction – potentially simply due
to strict deadlines or insufficient resources – whereas those cases reaching the courts are over substantive
matters of implementation that had been carried out.
9
The results are virtually unchanged if restricting lawsuits to those brought by businesses and interest
groups, thus omitting the lawsuits brought by states and cities.
18
transferring its authority to another agency), and/or (3) imposing new oversight procedures
such as reporting or consultation requirements. Conducting THOMAS word searches for
each of the 26 laws under the EPA’s jurisdiction, I identified the 5,398 bills introduced that
worked to revise the laws, each of which were hand-coded from the CRS summaries available on THOMAS. I restrict analysis to the bills introduced by members of the president’s
party, 960 of which sought to curb the behavior of the Environmental Protection Agency. A
random sample of 100 bills were double coded for reliability, and there was no inconsistency
in the codes assigned.
Examining this subset of bills enables me to dramatically reduce the likelihood that what
is being captured is simply legislative-executive conflict. That is, I argue that by restricting
analysis to bills brought to curb the behavior of agencies of the legislators’ party, one can
more easily attribute the action to bureaucratic behavior than to mere disagreement over
policy location.10 This restriction to action by the president’s party – that is, Democratic
dissatisfaction with Democratic enforcement and vice versa – provides this measure with
greater validity as an indicator of bureaucratic noncompliance.
While there is reason to suspect that requiring an agency to take on new regulatory
tasks might not operate as punishment of the administrative agency,11 Figure 2 confirms
that the three curbing variables exhibit similar patterns over the sample time frame, and the
performance of factor analysis revealed that the information loaded on a single factor with
an eigenvalue of 2.32.12 [Figure 2 goes here] This lends credence to my claim that the three
variables are tapping into a single core dimension, which I argue is congressional punishment
over perceived transgressions from statutes. This is supported further by the fact that the
10
In an alternative specification, I restricted the analysis to those majority party bill introductions that
had 15 or more cosponsors – an even higher threshold level of support in order to be included – and the
results were virtually unchanged.
11
That is, Congress may be signalling intentional foot-dragging by the agency, but it may also simply
desire that the agency take on greater regulatory responsibility. I argue that these effects can be better
disentangled in the lawsuits measure due to the patterns of settlements.
12
A factor with an eigenvalue of at least 1 indicates that it explains more variance than would a single
variable.
19
requirements included in this variable are all mandatory rather than discretionary, and thus
they do contribute toward the micromanagement of the agency’s regulatory actions, whereas
the inclusion of discretionary rules and requirements would have been endowing the agency
with greater latitude. As a robustness check, I estimate a model restricted to the 475 bills
from members of the president’s party which only prohibit or further oversee agency actions
and in which I average the standardized prohibitions and oversight scores, and the results
strengthen.
Measures of Institutional Conflict. Divided Government is a dummy variable coded
as 1 when the president’s party controls both chambers of Congress, and 0 otherwise. The
performance of a difference-in-means test reveals nearly a standard deviation increase in
agency deviations from congressional preferences in implementation amid divided government, significant at the .001 level. Margin of Control is the absolute value of the percentage
of seats held by the majority party. With a large margin of control in Congress, a party has
lower transaction costs associated with passing legislation to curb the powers of an agency
subverting its dictates. Thus, I expect that large margins of control will be associated with
more compliance by the EPA if that majority has a different agenda than the agency. I
interact Party Margin with Divided Government because I expect that the effects of a large
partisan majority on bureaucratic behavior will be shaped considerably by whether that
party holding considerable versus narrow control is of the same or the opposing political
party. That is, a large margin of support within one’s own party may not serve as a check on
implementation behavior, but the constraint could prove quite considerable if the opposing
party controls a large percentage of the seats in Congress. I expect the coefficient on the
interaction to be significant and negative.
To measure the extent to which the legislature is divided – and thus less capable of
passing new legislation that would punish an agency for its transgressions – I use the measure Chamber Difference, which is the first-dimension Common Space NOMINATE distance
20
(Poole and Rosenthal 1997) between the House and Senate means. Successful policy adoption requires some overlap in preferences between key political actors in both of the chambers
of Congress. With greater distance between the chambers, there will be higher transaction
costs associated with passing legislation, which in turn creates greater opportunities for the
EPA to move policy closer to its preferences. Thus, I expect the effect to be significant and
positive.
Other Political Environment Variables. Because of the potentially meaningful effects of interest group lobbying, I estimate from the Policy Agendas project the number of
interest groups that are active on environmental policy, forming the variable Environmental
Interest Groups. I expect that interest group activity will have a significant effect on bureaucratic behavior in statutory implementation.13 However, the effect conceivably could go
in either direction. Gordon & Hafer (2005) call attention to the important role of interest
group pressures and their “flexing of muscles,” holding that if companies communicate intentions to fight agency decisions through subsequent political actions, agencies may choose
to regulate less or regulate elsewhere, despite what the statute specifies. Thus, there is a
challenge of multiple competing principals – Congress and interest groups – which may drive
agencies to deviate from the statutes under their jurisdiction. However, depending upon
the composition of these interest groups – whether they are predominantly pro-regulation,
anti-regulation, or a balance – the added presence of interest groups could serve a monitoring function. After all, the threat of interest group litigation against the EPA may help to
preclude subversion of legislative intent. The crudeness of this measure will not enable me
to untangle these different potential effects.
To estimate further the potential problems arising from multiple principals, I include
the variable NOMINATE Distance, which is the absolute value of the distance between
the authorizing Congress’s first-dimension NOMINATE mean and that of the contemporary
13
I take the log of the value, but presenting the raw count produces similar results.
21
Congress. This will allow me to estimate to what extent agencies’ noncompliance increases
with more divergence between the principal of the authorizing Congress and the principal
that is actually empowered to punish an agency for its transgressions
Legislative-Executive distance is the the absolute value of the first-dimension NOMINATE
distance between the congressional floor mean and the President. To use the president’s
ideology to proxy for that of the administrative agency is imperfect, particularly given that
the American separation-of-powers system virtually guarantees that there will not be perfect
compatibility of preferences and incentives between the president and the bureaucracy within
his branch.14 However, it should allow me to gauge over time to what extent preference
divergence as measured in a finer-grained form than mere divided government creates greater
incentives for the agency to defect.15 To account for the role of judicial ideology, I utilized
the Giles, Hettinger, and Pepper scores of judges on the US Court of Appeals for the DC
Circuit, and estimated the absolute value of the distance between the DC Circuit median
and that of Congress (Floor-DC Circuit Distance) and the absolute value of the distance
between the DC Circuit median and the president (DC Circuit-President Distance).
Because partisan ideology should predict well the direction the agency would opt to push
policy (whether higher or lower than the statute), I include the dummy variable Democratic
President. There are a number of limitations to effective control of agents seeking to do less
than the statute dictates, and I expect that the party of the president can be treated as a
proxy for these preferences over implementation, particularly given the Democratic Party’s
strong ties to environmental policy.16
14
Krause & Dupay (2009) note, however, that effective presidential control of bureaucracy requires the
proper coordination among political executives, who must comply with presidential intent.
15
Measuring ideological distance among different branches over time presents a number of methodological
challenges. The time-invariant nature of the Clinton & Lewis (2008) ideal point estimates and the shorter
time span of the Bonica et al (2013) estimates render the president’s ideology the most practical for the
purpose of this paper. The inclusion of both divided government and this distance measure does not appear
to present problems of multicollinearity.
16
This may be more true of enforcement than of rulemaking, for which the same standards apply for rule
adoption and recission.
22
Given the natural ebbs and flows in the extent of environmental regulation over time
in ways that are not correlated with my outcome variable of noncompliance (e.g., an oil
spill), I control for the Total EPA Legislating, which is the number of bills introduced that
addressed the Environmental Protection Agency in some way, and the Total EPA Litigation.
Finally, I account the the Time – with the unit of analysis ranging from the 93rd to the
110th Congresses – to control for a linear time trend over the sample.17
Law-Level Measures. I first identified from the EPA’s website each of the 26 laws
within its the jurisdiction. For each of these statutes, I determined the level of administrative fragmentation, which is a factor score incorporating information from the numbers of
implementing administrative actors and agencies, and the number of instances of overlapping
jurisdiction over policy space in each of the laws. These actors and entities were identified
based on the text of the law and whether they were involved in implementing core regulatory
functions (rulemaking, sanctions, hearings, or lawsuits). These values then form an index,
rescaled to be positive and ranging from 0 to 4.34.18 Farhang & Yaver (2013) argue that
congressional fragmentation of the state constrains the executive branch given the need to
coordinate across numerous actors and agencies, in addition to facilitating the legislature’s
goal of maintaining a “sticky” status quo. Thus, I expect higher levels of fragmentation to
be associated with more constraints on the EPA’s implementation.
I assigned policy codes to each of the 26 laws under the EPA’s jurisdiction, falling into the
following categories: Air & Water, Public Health & Safety, Public Land and Animals, Energy,
and Hazardous Waste. Each of these policy categories was coded as a dummy variable, and
included these as policy fixed effects in the models presented below. Finally, Significant Law
is a dummy variable taking the value of 1 if it was identified by Mayhew (2005) as significant,
and 0 otherwise.19 . Table 1 provides a summary of the variables included. [Table 1 here].
17
Including quadratic and cubic time trends does not substantively affect the main findings of the paper.
To create the index, I averaged the standardized scores. However, a factor score performed equivalently.
19
An exception is the Federal Food, Drug, and Cosmetic Act (1938), which was passed before the start of
18
23
Estimation Method. After identifying the laws under the jurisdiction of the Environmental Protection Agency, I measured each of the dependent and independent variables at
the statute level for the the 93rd through the 110th Congresses. This comprised a dataset of
398 observations.20 This data structure enables me to estimate from Congress to Congress
in the sample both the institutional and law-level characteristics that shape agency implementation behavior.
Given this data structure, it is appropriate to use a time series cross-sectional model,
whereby the data consist of comparable time series data observed on different units – in
this case, statutes – in turn allowing one to test theories of both cross-sectional and crosstemporal variation. A challenge in applying this procedure to the EPA data is that some of
the laws under the EPA’s jurisdiction were passed recently, thus leaving fewer observations
for those units and giving greater weight to older laws than to those that are newer. Given
Beck’s (2010) recommendation of cross-validation of units within time-series cross-sectional
data, I compared the full dataset to the the data from laws enacted between the 93rd and
the 110th Congress, as well as to the laws enacted from the 93rd Congress or earlier (that is,
those laws with balanced panels). I find that the results from the 93rd-forward laws closely
parallel the results of the full estimation, and while the strength of the specification with
older laws is of a weaker level of significance (with results around p=.10), the direction of
the effects remain the same. Thus, I have reason to believe that the results are not being
driven simply by a subsample of the laws within my analysis.
The dependent variable Agency Curbing is a factor score that ranges from 0 to 3.595
with a mean of 1.25. The dependent variable of EPA Lawsuits Lost is the percentage of DC
Circuit cases that the EPA lost on substantive grounds, and it ranges from 0 to 1 with a
mean of 0.16. I estimate the effects using Ordinary Least Squares using the Prais Winsten
Mayhew but has a high level of significance, as indicated by its Lapinski & Clinton (2006) significance score
of 0.819. Thus, I treat the law as significant.
20
Thus, the data comprise 26 laws over 19 Congresses. However, 14 of the 26 laws were passed after the
93rd Congress, such that there are fewer observations for those laws.
24
method technique, with correlated panel-corrected standard errors to account for temporal
variation.21 Because performing statistical analysis of relationships between nonstationary
time series can lead to spurious results, I use the Harris-Tzavalis test to test to confirm
whether the dataset contains a unit root. I find overwhelming evidence against the null
hypothesis of a unit root and thus conclude that the data are stationary. Performance
of the Wooldridge test for autocorrelation in panel data produced a highly significant test
statistic, indicating the presence of first-order autocorrelation in the data. After examining
the autocorrelations across different panels (statutes), I specify in the model that there is
AR(1) correlation within the panels, and that the coefficient of the AR(1) process is specific
to each panel. The effects of OLS can be interpreted directly, with a unit change in the
independent variable yielding a β-unit change in the dependent variable.22
Findings of Noncompliance with Current Congress
I begin by discussing the model estimating the conditions driving agencies to deviate
from Congress’s preferred implementation, as indicated by the Agency Curbing composite
measure. I first estimated a parsimonious model to ensure that the effects are not an artifact
of certain control variables, and the results produced comparable results, thus giving me
confidence in their robustness. The full estimations are presented in Model 1 of table 3.
[Table 3 here]
I find that the main effect of a move from unified to divided government is associated
with a .11-unit increase in agency curbing, though it falls short of significance at the .10
level. However, the theory discussed above is bolstered by the positive and significant effect
of floor-president distance, a unit change in which yields a .67-unit increase in bureaucratic
punishment by Congress. It is reasonable to expect that rather than focusing on the signif21
While the EPA lawsuits variable is not strictly speaking continuous, it has a wide range, and using a
negative binomial specification instead does not produce meaningfully different results.
22
Running instead time series OLS models with random effects to allow for unit heterogeneity produces
comparable results on the key variables of interest.
25
icant and positive independent effect of Margin of Control, the more meaningful variable is
the interaction, given that a large partisan majority in the president’s party would not be
expected to serve as a threat to the agency, whereas under conditions of divided government
and a large majority in Congress, there will be both inter-branch ideological disagreement
as well as a considerable ability of the opposing party to punish an agency seeking to move
policy from the status quo toward its preferred location. The effect of the interaction between Divided Government and Margin of Control is extraordinarily powerful and negative –
approximately a three standard deviation decline – which is consistent with my expectation
that amid partisan conflict with the opposing party holding a large majority, the low costs of
statutory punishment of the EPA will make noncompliance an unlikely avenue for the EPA to
take in equilibrium. That is, the agency will be more inclined to avoid potential punishment
from Congress when it is well-equipped to punish.23 While the coefficient on the interaction
is highly significant and in the expected direction, interpreting the magnitude of interaction
effects with a continuous variable (margin of control ) presents a number of difficulties. For
this reason, I present in Figure 3 a plot of the effect of this interaction term in the full model
with 95 percent confidence intervals, revealing not just a sharp negative trend, but a narrow
bandwidth around the estimates, giving me greater confidence in interpreting the effect of
this key variable. [Figure 3 goes here]
My expectation was that division within Congress as measured by ideological divergence
between the House and Senate translates into a marked and highly significant increase in
bureaucratic noncompliance by the EPA. Surprisingly, this effect ultimately is significant
and negative, though this may be a consequence of the dependent variable being a measure
of legislative activity, which may decline amid heightened legislative conflict even looking at
this earlier stage of the legislative cycle.24 Also contrary to my expectations, the effect of
23
As a robustness check, I dropped the policy fixed effects from the models and it did not have a meaningful
effect on the results.
24
This is also true when looking instead to the NOMINATE distance between the medians of the majority
and minority parties of Congress.
26
NOMINATE distance between the enacting and monitoring Congresses is negatively associated with bureaucratic punishment, significant at the .10 level, though this may indicate the
agency’s ability to accurately gauge the preferences of the Congress currently empowered to
punish it as opposed to adhering strictly to the statutory text.
Increases in the extent of environmental interest group activity appears not to affect noncompliance measured through agency curbing activity. Bureaucratic punishment appears less
likely within the domain of significant legislation, which is inconsistent with my expectation
that policy battles are less likely to be waged over more ordinary legislation than when there
are high costs associated with losing. However, there is the possibility that the effects are
mixed. That is, while agencies may feel more compelled to move policy toward their preferences when the stakes are higher (e.g., within the domain of legislative significance and
salience), the legislature is also likely to be more watchful within this regulatory context,
thus suggesting more effective oversight to keep agencies in line. I argue in the paper that
statutory fragmentation should have a constraining effect on agencies’ ability to pull policy
away from the status quo location. That is, congressional efforts at fragmenting administrative power are aimed at inducing a status quo bias, and thus there should be less need
for punishment in highly fragmented settings. The effects revealed here are in the expected
direction – significant and negative – with a unit increase in fragmentation associated with
a 0.12-unit decrease in agency curbing activity by Congress. A move from being a Republican to a Democratic president is associated with a .12-unit increase in in agency curbing,
significant at the .10 level, an effect that is modest but consistent with my expectation that
one can more easily control a Republican agency given its propensity to regulate less rather
than more than the policy set by the statute (that is, Democratic agencies would be more
likely to get into trouble). And consistent with my expectations, ideological distance between Congress and the DC Circuit is positively associated with agency curbing given its
lower level of trust in the judiciary to act an overseer of the agency’s actions.
27
As a robustness check in table 4 in the Appendix, for each of the three variables identified
in the bills introduced, I estimate panel negative binomial specifications with unit random
effects. I argue that all three of these measures – Requirements, Prohibitions, and Oversight
– are, in conceptually distinct ways, constraining the agency so that it no longer has free
reign in its implementation, a claim that is supported by the variables all loading heavily
on a single factor. Because these are non-linear models, the effects cannot be interpreted
directly. To interpret the β parameters of the negative binomial model, which accounts for
the overdispersion in the models, an x-unit increase in the independent variable translates
to an exp( xi βi ) change in the dependent variable. All of the individual models provide
further evidence of the strong and positive independent effect of divided government on
bureaucratic defections, as well as the strong negative effect that divided government with a
large partisan majority has on the EPA’s noncompliance willingness to transgress its bounds
given the elevated risk of punishment for misbehavior.
Noncompliance with Statutory Text
The above analysis of agency curbing sheds important new light on agency deviations
from congressional preferences in statutory implementation, but does not answer clearly the
rule of law question regarding adherence to statutory text. For that, I turn to the EPA
Suits Lost dependent variable, the results of which are presented in table 3 alongside the
agency curbing specification. I expect that considering these lawsuits against the EPA will
provide novel insights about adherence to statutory text given variation in political and legal
conditions, with the Court of Appeals able to assess whether the agency in fact contravened
its regulatory authority under the statutes within its jurisdiction.
A move from unified to divided government is associated with a 0.22 unit increase the
EPA’s loss rate, significant at the .05 level. Also consistent with the models discussed above,
the interaction of divided government and the opposing political party has a strong and
negative association with EPA noncompliance, such that the other party’s ability to punish
28
appears to well-moderate the agency’s actions (see Figure 4). [Figure 4 goes here] Unlike
in the agency curbing model, the ideological distance between the president and the floor
of Congress is not statistically significant. While theory suggests that heightened interchamber divergence should empower the EPA to pull policy closer to its own preferences
absent credible threats of passing legislation to punish, here Chamber Distance is in the
expected (positive) direction but falls below conventional levels of statistical significance.
While fragmenting across implementing actors is with the mindset of insulating policy
and thus potentially increasing a future Congress’s dissatisfaction with the “sticky” status quo, its effect on the EPA’s substantive losses in court does not appear significant.
And consistent with my expectations (though in contrast with the agency curbing model
specification discussed above), increased NOMINATE distance between the delegating and
monitoring legislative principals is associated with over a two standard deviation increase
in EPA losses in the DC circuit, significant at the .001 level. Thus, as the agency finds
itself caught in conflict between the statutory text and the principal empowered to punish
it if dissatisfied, it is markedly more likely to find itself in accordance with the currently
empowered principal but not with the law in place, in turn being punished in the DC Court
of Appeals as it resolves the proper reach of the agency’s authority and obligations under
the statutes. The increased presence of environmental interest groups does not appear to
affect the EPA’s likelihood of losing in court on substantive grounds. While a law’s status as
being significant is negatively-signed as in the models discussed above, the substantive effect
of legislative significance on agency losses in court is very small. Unlike with the agency
curbing model discussed above, the party of the president does not appear to meaningfully
impact the EPA’s likelihood of losing in the DC circuit.
Perhaps most surprisingly, increases in ideological distance between the president (a
rough proxy for the agency’s ideology) and the DC Circuit is associated with significantly
fewer losses in court. Intuitively, one would expect that as the DC Circuit more strongly
29
disagrees with the preferences of the agency that it oversees, it will be more likely to find its
actions unlawful. However, the finding may be a reflection of the agency’s strategic behavior
in deciding whether to settle, with more settlements occurring when the agency is more
ideologically opposed to the DC Circuit judges who would handle their case.
Further work should explore why the EPA Lawsuits Lost and Agency Curbing dependent
variables produce different results with respect to a number of key variables. Of course,
the measures are tapping into different dynamics with respect to the EPA’s noncompliance.
While capturing the conditions underlying agency deviations from congressional preferences
does not engage with issues of statutory interpretation and the rule of law, examining EPA
losses in court over implementation relies on a number of complex dynamics including the
composition of legal cases brought before the court and interpretations of the legislative
bargains struck by previous congressional coalitions. These observed cases could, therefore,
be understood as off-equilibrium outcomes resulting from agency “mistakes,” with much
more unobserved noncompliance beneath the surface, though this would again suggest that
reliance upon these cases provides a harder test for my data rather than producing a falsely
positive result.25
Conclusions
This paper provides the first large-scale examination of agency implementation and sheds
new light on the extent of the rule of law in a world of bureaucratic governance. It provides
robust support for the theory that when legislative-executive preferences diverge, the Environmental Protection Agency takes more actions that deviate from Congress’s preferred
implementation of the delegating statutes, as well as from the statutory text itself, in order to pull policy toward its preferred location. The project sheds important new light on
25
While a reasonable conclusion to be drawn might be insufficient resources with which to achieve the
regulatory agenda in full, thus leading to noncompliance or the appearance of it, the vast majority of
settlements are deadline suits that more directly relate to the agency’s ability (as opposed to inclination) to
comply, whereas the cases examined for these purposes more specifically target actions in contravention of
the implementing statutes.
30
longer-term issues related to bureaucratic autonomy, suggesting that while there may be a
number of reasons why an agency can initially carve out a space for its autonomous policymaking, that autonomy is far from path-dependent if it deviates too far from the preferences
of other institutional actors. Thus, in an era of nearly-constant partisan division as well as a
fragmented oversight apparatus, there are clear reasons to rethink the traditional delegation
story and look farther downstream at the policy outcomes that we ultimately observe upon
legal implementation.
In addition to providing the first evidence of these agency deviations, it calls attention
to the need to address the ultimate distributive politics effects of these defections. That is,
who gains or loses as a consequence of the EPA’s implementation behavior when complying
or not? This is an important subject of further inquiry. The paper also has implications that
extend beyond the United States to other legislatures and their control of an administrative
apparatus, as well as the broader literature on organizational behavior, which may help us to
understand better the conditions under which we observe effective control within hierarchies
and when drift from agents becomes unacceptable to their principal(s).
It is worth emphasizing that the above analysis of bureaucratic noncompliance focuses
only on observed noncompliance, rather than an absolute level of agency deviations. That is,
it is the agency either misjudging its likelihood of punishment from the judiciary or potentially acting in spite of the position of the other institutional actors. A more ideal measure
would capture directly the acts of deviation from the statutes under their jurisdiction. However, given the broader range of administrative deviations that go unpunished,26 the results
presented are likely to be marked underestimations of the true effects at work, and presented harder tests of my core hypotheses. Thus, this paper brings to light the importance
of understanding better these agency actions and their impact on the legal landscape.
26
This is consistent with the literature on veto bargaining, according to which much of the inter-branch
interactions are shaped not by observed vetoes, but rather by threats and the potential, or lack thereof, for
their use vis-a-vis Congress (Cameron 2000).
31
The counterintuitive effects intra-branch conflict on bureaucratic punishment remains a
puzzle that deserves further inquiry. Of course, the changing litigation environment over time
– and thus the changing pool of lawsuits – has critical consequences with respect to the cases
brought to court and the holdings that ultimately are rendered and reflected in the dependent
variable. What is clear from the results is that the EPA’s calculus in considering its current
principal (the Congress in power) versus its delegating principal (the authorizing Congress)
and the statute that it drafted is meaningfully different, giving credence to this paper’s
claim that scholars should be more explicit about assumptions regarding the more precise
nature of the principal-agent relationship between Congress(es) and administrative agencies.
Whether these differences are driven by the study’s restriction to a single policy domain
– with policy substance potentially having a meaningful effect on inter-branch interactions
over implementation and how we ought to model these relationships – is a question that will
be answered in future work extending to additional agencies. However, this paper makes a
significant advance in exploring post-delegation implementation, and the conditions under
which bureaucratic control breaks down.
32
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35
Table 1: Description of Variables
Dependent Variables
Agency Curbing
Requirements
Prohibitions
Oversight
Lawsuit Losses
Description
Composite measure of agency curbing bills introduced by members
of the President’s party
Bills requiring that the EPA take new regulatory actions
Bills prohibiting the EPA from taking regulatory actions
Bills imposing on the EPA new oversight provisions (report req, etc.)
Percentof EPA suits lost in DC Circuit
Independent Variables
NOMINATE Distance
Description
Common Space NOMINATE distance between authorizing and
contemporary Congress
Divided Government
0 when the President’s party controls both chambers, 1 otherwise
Party Margin
Margin of seats by which the congressional majority is in control
Chamber Difference
Difference in Common Space NOMINATE means of House and Senate
Environmental Groups
Log(Number of interest groups annually active on environment)
(Policy Agendas Project)
Fragmentation
Factor score from number of administrative actors, agencies, and
instances of over overlapping jurisdiction among actors/agencies
Significant
1 if the statute is significant, 0 otherwise
Legislative-Executive Distance NOMINATE distance between the floor mean and the President
Total EPA Legislating
Sum of bills introduced by any member of Congress that addressed
the EPA in some way
Total EPA Lawsuits
Total suits brought against the EPA in the DC Circuit per Congress
Floor-DC Circuit Distance
Ideological distance between congressional floor median NOMINATE
score and the median DC Circuit GHP score
President-DC Circuit Distance Ideological distance between President’s NOMINATE score and the
median DC Circuit GHP score
36
Table 2: Summary Statistics
Dependent Variables
Lawsuit Losses
Requirements
Prohibitions
Oversight
Agency Curbing
Political Environment Variables
Divided Government
Margin of Control
Divided Government x Margin
Chamber Distance
NOMINATE Distance
Environmental Interest Groups (log)
Floor-President Distance
Total EPA Legislating
Total EPA Lawsuits
Floor-DC Circuit Distance
President-DC Circuit Distance
Law Characteristics
Fragmentation
Significant
Mean
SD
Min
Max
0.159
10.271
3.771
6.417
0.769
0.205
13.972
4.738
8.381
0.946
0
0
0
0
0
1
66
21
31
3.805
0.613
0.488
0.100
0.085
0.057
0.075
0.019
0.016
.056
.039
5.097
0.464
0.482
0.076
213.568 123.573
16.387 10.022
0.114
0.074
0.486
0.125
0
0
0
0.000
0
3.867
0.312
0
1
0.014
0.294
1
0.291
0.285
0.048
.170
5.622
0.600
395
46
0.251
0.822
-1.376
0
2.966
1
0
0.530
37
0.882
0.500
Table 3: Bureaucratic Noncompliance
Model 1
Agency Curbing
0.105
(0.072)
2.715***
(0.513)
-3.168***
(0.505)
-2.086*
(1.005)
-1.203+
(0.672)
0.002
(0.060)
-0.545**
(0.184)
-0.118**
(0.047)
0.671*
(0.288)
0.130+
(0.077)
0.083***
(0.011)
-0.001
(0.001)
0.427+
(0.235)
Divided Government
Margin of Control
Divided Govt x Margin
Chamber Distance
NOMINATE Distance
Environmental Groups
Significant Law
Statutory Fragmentation
Floor-President Distance
Democratic President
Congress
Total EPA Legislating
Floor-DC Circuit Distance
Total EPA Lawsuits
President-DC Circuit Distance
Intercept
-8.278***
(1.026)
Yes
0.33
346
Policy Fixed Effects
R2
Total Observations
∗∗∗
p < .001,∗∗ p < .01,∗ p < .05,+ p < .10
38
Model 2
Lawsuit Losses
0.220*
(0.100)
1.646**
(0.591)
-1.421*
(0.641)
2.128
(1.961)
0.539***
(0.101)
-0.085
(0.058)
-0.030***
(0.005)
-0.001
(0.001)
-0.646
(0.443)
-0.063
(0.069)
-0.023**
(0.009)
0.004
(0.003)
-0.432*
(0.217)
3.182***
(0.812)
Yes
0.75
346
Figure 1: Bureaucratic Punishment Over Time
Pct. DC Circuit Losses
Agency Curbing
RCRA
TSCA
Clean Air Act
FWPCA
RCRA
TSCA
1
0
-1
0
.5
1
2
0
-1
0
.5
1
1
FWPCA
2
Clean Air Act
111
108
105
102
39
99
Congress
96
93
111
108
105
102
99
96
93
111
108
105
102
99
96
93
111
108
105
102
99
96
93
Congress
Figure 2: Lowess Smoothers of Agency Curbing Over Time
Prohibitions
0
-1
5
0
1
2
10 15 20
3
Agency Curbing Composite
0
0
20
10
40
20
60
30
111
80
111
109
Oversight
109
Requirements
107
Congress
107
105
103
101
99
97
95
93
111
109
107
105
103
101
99
97
95
93
Congress
Congress
40
105
103
101
99
97
95
93
111
109
107
105
103
101
99
97
95
93
Congress
Figure 3: Interaction Effect on Agency Defections
41
Figure 4: Interaction Effect on EPA Lawsuit Losses
42
Appendix
Coding Agency Curbing Bills:
Examples of what was considered a requirement: Requiring the EPA to promulgate
rules/regulations, set standards, enforce violations, or approve permits.
Examples of what was considered a prohibition: Formally disapproving of EPA rules,
prohibiting it from imposing sanctions or enforcing provisions, transfering enforcement authority from the EPA to another agency, delaying EPA rules, or rescinding funds with which
to implement its programs.
Examples of what was considered oversight: Reporting requirements, consultation requirements, spending limits, time limits, public hearings, direct oversight.
Examples of what was not considered relevant: appropriations bills that do not specifically involve a reduction of funds to the EPA or programs within it, authorizing but not
requiring the Administrator of the EPA to take action, establishing offices within the EPA
but not requiring that the EPA itself take regulatory action, requirements of actors other
than the EPA, requiring that other actors consult with the EPA, or mentioning the EPA
in passing but not actually regulating it. No discretionary language was counted, as it was
construed as adding to, rather than reducing bureaucratic capacity to regulate.
43
Table 4: NBREG Models of Individual Agency Curbing Actions
Divided Government
Margin of Control
Divided Govt x Margin
Chamber Distance
NOMINATE Distance
Environmental Groups
Significant Law
Statutory Fragmentation
Floor-President Distance
Democratic President
Congress
Total EPA Legislating
Floor-DC Circuit Distance
Intercept
Policy Fixed Effects
Total Observations
∗∗∗
Model 3
Requirements
0.987***
(0.287)
9.006***
(1.837)
-11.724***
(2.699)
-0.645
(6.247)
-1.898
(1.127)
1.165***
(0.238)
-1.304**
(0.399)
-0.016
(0.187)
2.750*
(1.327)
0.118
(0.219)
0.074***
(0.021)
0.002
(0.002)
2.318***
(0.620)
-12.145***
(2.849)
Yes
346
p < .001,∗∗ p < .01,∗ p < .05
44
Model 4
Model 5
Prohibitions Oversight
1.283***
2.349***
(0.296)
(0.237)
11.235***
13.364***
(1.894)
(1.444)
-14.242***
-24.017***
(2.799)
(2.410)
-9.621
-32.982***
(6.685)
(5.840)
-0.619
-0.918
(1.055)
(0.806)
0.959***
1.003***
(0.227)
(0.204)
-3.148***
-3.183***
(0.807)
(0.824)
0.870*
0.717*
(0.405)
(0.371)
5.212***
7.175***
(1.317)
(0.959)
-0.204
-0.727***
(0.234)
(0.189)
0.116***
0.095***
(0.020)
(0.017)
0.001
-0.001
(0.002)
(0.001)
3.157***
0.275
(0.592)
(0.450)
-14.689***
-13.060***
(3.013)
(2.372)
Yes
Yes
346
346
Table 5: Agency Constraints (Prohibitions and Oversight Composite)
Model 6
Agency Constraints
0.438***
(0.084)
4.208***
(0.574)
-6.054***
(0.572)
-8.430***
(1.295)
-0.064
(0.596)
-0.098
(0.068)
-0.720*
(0.301)
-0.116*
(0.052)
2.178***
(0.364)
-0.098
(0.092)
0.091***
(0.013)
-0.001
(0.002)
0.455
(0.310)
-9.354***
(1.178)
Yes
0.38
346
Divided Government
Margin of Control
Divided Govt x Margin
Chamber Distance
NOMINATE Distance
Environmental Groups
Significant Law
Statutory Fragmentation
Floor-President Distance
Democratic President
Congress
Total EPA Legislating
Floor-DC Circuit Distance
Intercept
Policy Fixed Effects
R2
Total Observations
∗∗∗
p < .001,∗∗ p < .01,∗ p < .05
45
Yes
1
.8
.6
.4
.2
0
Agency Curbing by Congress
Agency Curbing and Citizen Suit Delegations
No
Citizen Suits Provided
Yes
Consistent with expectations, when Congress has empowered private litigants to sue, legislators
need not provide as much ongoing monitoring and punishment of agencies. Or perhaps
alternatively, the threat of citizen suit litigation effectively motivates the agency to be compliant.
46