state agency discretion in a delegated federal program ...investment (brehm and gates 1997; moe...
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State Agency Discretion in a DelegatedFederal Program: Evidence from DrinkingWater Investment
Dorothy M. Daley*, Megan Mulliny andMeghan E. Rubadoy
*University of Kansas; [email protected] University
This article examines the use of discretion by state agencies in the context of multilevel policy.
Research on agency discretion assumes that discretion represents a departure from legislative
intent. However, Congress may delegate authority to promote policy innovation. Using data on
investment in drinking water infrastructure from 2000 to 2008, we examine the relationship
between agency discretion and functional expertise in implementing the Drinking Water State
Revolving Fund program.We focus on two areas where states can exercise discretion: (i) projects
not related to compliance with federal law and (ii) support to small water systems. Our results
indicate that agency expertise influences investment, but problem severity reduces differences
across agencies. Initial choices over agency design affect how states adapt federal programs to
meet state needs.
Fragmentation and multilevel governance remain enduring characteristics in
American government. Across a range of policy areas, devolution of authority has
created networked governance where different levels of government and multiple
agencies share responsibility for policy implementation (Agranoff 2007; Agranoff
and McGuire 2003; Mullin and Daley 2010; Gerber and Teske 2000; Meyers,
Riccucci, and Lurie 2001; O’Toole 1996; Potoski 2001; Scholz and Wei 1986;
Whitford 2007; Woods 2006; Woods and Potoski 2010). Typically, Congress and
the federal bureaucracy set broad policy goals and delegate authority to state
governments to achieve those goals. States then develop rules that transfer
significant responsibility for implementation to bureaucratic agencies.
State agencies play a critical role in the execution of federal public policy, but
our understanding of their behavior remains underdeveloped. Part of the problem
lies in the literature’s inconsistent treatment of state agency discretion in the
context of multilevel governance. On the one hand, scholars of fiscal federalism
treat devolution as an opportunity for states to craft policies that better match the
nature of their problems and the preferences of state populations (Oates 1972).
Publius:TheJournal of Federalism, pp.1^23doi:10.1093/publius/pjt033� TheAuthor 2013. Published by Oxford University Press on behalf of CSFAssociates: Publius, Inc.All rights reserved. For permissions, please email: [email protected]
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Devolution can be a mechanism to enhance the efficient provision of public goods,
particularly when faced with a diverse citizenry (Kincaid 1998; Whitaker and Time
2001). It also promotes policy experimentation, which can have benefits for the
entire federal system (Bednar 2011). On the other hand, theoretical work on agency
discretion and empirical research on state bureaucratic decision making typically
depicts the exercise of discretion as a departure from legislative intent and,
therefore, a lapse in democratic representation with unelected civil servants
wielding considerable authority. Factors that contribute to variable outcomes, such
as information asymmetry based on agency expertise, are represented as forces
countering federal control, rather than conditions that ought to influence
implementation of a devolved federal policy (Gailmard and Patty 2007, 2012;
Huber and McCarty 2004).
In this article, we examine the use of discretion by agencies with different types
of functional expertise in the context of a multilevel policy designed to promote
state flexibility and responsiveness to state-level problems. Our analysis capitalizes
on differences across institutional environments as well as problem conditions to
better understand what factors promote or inhibit agency discretion. In the 1996
amendments to the Safe Drinking Water Act (SDWA), Congress established the
Drinking Water State Revolving Fund (DWSRF) program to promote capital
investment in drinking water. Modeled after the Clean Water State Revolving Fund
(SRF) established nine years earlier, the DWSRF creates a system of shared
responsibility for water infrastructure investment. Under the DWSRF program, the
Environmental Protection Agency (EPA) awards capitalization grants to states,
which use these funds to provide low- or no-interest loans to local communities to
invest in drinking water infrastructure. Repayment by loan recipients ensures the
long-term integrity of the funds, allowing future investment in other communities.
Since 1997, DWSRF programs have provided more than $16.2 billion in low
interest loans to maintain, improve, and protect the nation’s drinking water
infrastructure (U.S. EPA 2010). Although the EPA retains authority to set and
enforce drinking water standards, it is up to local actors to design infrastructure
improvements that comply with federal law, and state officials are responsible for
prioritizing among deserving projects.
This type of decentralization can foster innovation and experimentation by
enabling states to design DWSRF programs that meet local needs. However,
resource and information constraints might prevent state agencies from fully taking
advantage of the discretion available to them. The DWSRF program offers a unique
opportunity to systematically examine the interplay between institutional expertise
and agency discretion. There is considerable variation in the functional focus of
agencies administering DWSRF programs, with implementation responsibility
falling under the authority of an environmental, public health, or financial agency,
or some combination of the three.
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Previous research indicates that institutional structure and administrative
procedures can influence agency decision making and output (Brehm and Gates
1997; Gerber and Gibson 2009; Hammond and Thomas 1989; Moe 1989; Morris
1997; Potoski 2002; Whitford 2002). We expect that an agency’s functional focus,
meaning an environmental, public health or financial focus in agency staffing and
mission, influences how state bureaucrats capitalize on the discretion available to
them in a multilevel program intended to promote state flexibility. Using data on
patterns of drinking water infrastructure investment from 2000 through 2008, we
analyze how these institutional differences influence responsiveness to problem
conditions in a state. We focus on two areas where states have considerable
opportunity to tailor water infrastructure investments: (i) projects not directly
related to compliance with federal law and (ii) support to small water systems that
face significant challenges in providing safe drinking water. We find evidence
indicating that an agency’s functional focus influences investment patterns, but
problem severity reduces differences across agency types.
Federalism and State Decision Making
Much of the literature on agency discretion assumes that discretion represents a
departure from program designers’ intent. For some scholars, conflict between
political principals and bureaucratic agents is intrinsic to the concept of discretion;
Calvert, McCubbins, and Weingast (1989) define discretion as ‘‘the departure of
agency decisions from the positions agreed upon by the executive and legislature at
the time of delegation and appointment’’ (589). A large literature on political
control of the bureaucracy examines the tools that elected officials use to increase
their leverage over agency behavior (Hammond and Knott 1996; McCubbins, Noll,
and Weingast 1987; Moe 1989, 1990; Whitford 2005; Wood 1990; Wood and
Waterman 1991, 1994). Other scholars who focus on the role of street-level
bureaucrats in delivering public services similarly treat bureaucrats’ use of
discretion in applying rules to particular cases as shifting policy outcomes away
from those defined in law (Jones et al. 1978; Lipsky 1980; Maynard-Moody and
Musheno 2003).
If delegation necessarily involves agency drift, the problem should be particularly
acute for complex, multilevel programs (Pressman and Wildavsky 1973). Indeed,
empirical studies of state implementation of federal policies reveal considerable
variation in state-level outcomes (Atlas 2007; Barrilleaux and Miller 1988; Gerber
and Teske 2000; Konisky 2007, 2009; Konisky and Woods 2010; Sigman 2003;
Potoski 2001; Whitford 2007). In some policy contexts, however, exercising
political control over state bureaucracies may not be the primary goal of federal
policy makers. Devolution instead can be an intentional effort to encourage
innovation and responsiveness to state problems and needs.
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For example, in creating the Temporary Aid to Needy Families (TANF)
program, the federal government allowed states to set welfare eligibility
requirements and benefit levels with the explicit intent to foster states’ creativity
in designing effective welfare systems. Studies of TANF programs reveal important
interstate differences in implementation, but unlike the case with the DWSRF
program, these differences are the product of political negotiations in state
legislative and executive branches (Soss et al. 2001; Fellowes and Rowe 2004). The
TANF experience demonstrates that state lawmakers will respond to a variety of
factors including political and economic conditions, demographics, problem
severity, and the policies of neighboring states when they pass legislation to
implement federal law, just as they do when enacting laws autonomously (Berry
and Berry 1999; Boushey and Luedtke 2011; Daley and Garand 2005; Gerber and
Teske 2000; Moreland-Russell et al. 2013; Ringquist 1993; 1994; Shipan and Volden
2006, 2008; Volden 2006). We know less about how state agencies use discretion
that may be granted under federal law.
Our research focuses on multilevel policies where the federal government seeks
to promote state flexibility. States implementing these policies have some discretion
to design programs to meet state needs and political demands, but they are far
more constrained than in the settings for most state policy adoption research. The
multilevel context not only limits the autonomy of state decision makers, but it
also complicates questions about political control of the bureaucracy by creating
two sets of principals delegating authority to state agencies. State agencies receiving
competing signals from federal and state political actors might seek to minimize
conflict by hewing closely to federal standards and other states’ policies. Another
factor that may reduce variation in state policies are the information demands
associated with state-level policy making. State bureaucrats might not have the
time, expertise, or data necessary to craft policies that address specific state needs,
and therefore rely instead on professional norms and agency expertise in making
implementation decisions.
We look specifically at the relationship between agency expertise and the exercise
of discretion, and examine how expertise interacts with state-level problem
conditions. An agency’s functional focus may help agencies navigate the two
challenges to exercising discretion outlined above. Bureaucrats facing competing
signals from multiple principals have an incentive to acquire further policy
expertise (Gailmard and Patty 2007). They will then utilize this expertise to
overcome information constraints in decision making. Implementation research
points to the critical role of organizational characteristics, including agency
mission, culture, and professionalism in predicting agency behavior (Bardach 1998;
Brehm and Gates 1997; Downs 1964; Kaufman 2006; Soss, Fording, and Schram
2011; Thomas 2003; Wilson 1989; Whitford 2010). If reliance on mission and
professional norms is a mechanism that agencies use to navigate complex decision
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making, we should expect agencies with different functional responsibilities, such as
environmental protection or financial management, to focus on different aspects of
drinking water infrastructure investment.
State Discretion in PrioritizingWater Infrastructure Spending
Congress created the DWSRF program to assist community water systems in
meeting rising federal standards for drinking water protection. By design, the
DWSRF program is meant to give state and local governments considerable latitude
in managing investments in water infrastructure. However, federal DWSRF policy
creates incentive for state agencies to pursue multiple, competing goals: to foster
innovative environmental investment and to maintain the fiscal integrity of the
loan funds. Implementing agents are responsible to political principals at both the
state and federal levels, but they may lack essential data about drinking water
problems and needs. In this complex policy environment, the functional focus of
an agency is likely to direct attention to some problems and issues over others, and
bureaucrats will rely on their expertise and preferences in directing drinking water
investment (Brehm and Gates 1997; Moe 1990; Watkins-Hayes 2011; Wilson 1989;
Whitford 2008). For example, DWSRF agency staff may have different levels of
knowledge about issues such as ecosystem health and source water protection, the
integration of drinking water with stormwater and wastewater management, or
loan portfolio analysis and cash flow modeling.
Drinking water protection is a goal clearly shared by environmental and public
health professionals. However, the longstanding organizational separation between
environmental and public health professionals has resulted in disengagement
between the fields and little mutual understanding (Gordon 1995; Kotchian 1997).
Previous work has reported that public health professionals have a tendency to
ignore environmental data and that pressures from interest groups and the political
environment contribute to environmental agencies focusing on their regulatory
responsibilities over their role in public health protection (Black 2000; Kotchian
1997). Financial agencies bring an entirely different set of tools to program
management. These agencies are staffed with individuals who have been trained to
promote fiscal responsibility and understand financial risk. The organizational
culture and expertise of staff working in financial agencies lends itself more to the
fund management aspects of DWSRF implementation than to the policy’s
substantive goals.
Substantial differences in agency mission and staff expertise exist between the
three types of agencies involved in DWSRF decision making. Past research
highlights the critical nature of organizational factors in shaping agency discretion
(Brehm and Gates 1997; Soss, Fording, and Schram 2011; Wilson 1989). Even when
public health and environmental agencies diversify by hiring financial professionals
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as agency staff, these financial experts are likely to be profoundly influenced by
established organizational norms (Soss, Fording, and Schram 2011; Watkins-Hayes
2011) and they face considerable hurdles in changing agency culture (Bardach 1998;
Kaufman 2006; Wilson 1989). Our research examines the relationship between
agency focus and outcomes for a program operated by different agency types.
In many states DWSRF programs are operated jointly by more than one agency.
Thirty-nine states have relied upon environmental agencies to manage the revolving
funds alongside other environmental programs. In twenty-two states, health
agencies have provided substantive policy leadership for the state funds, typically in
place of the environmental agency or occasionally in cooperation. In thirty-one
states, some type of financial agency has played a role in DWSRF decision making.
While these implementation arrangements are complex, they allow us to examine
how agency expertise influences investment decisions, and we expect the functional
focus of agencies to influence the allocation of funds even in cases of shared agency
authority.
Analyzing the relationship between the functional focus of an agency tasked with
implementation and programmatic outcomes begs the question of whether the
choice of an implementing agency is exogenous to the outcome of interest. We find
no evidence that states designate lead substantive agencies for the DWSRF program
in order to pursue a certain type of outcome. Delegation to the substantive agency
is dictated by primacy, or the agency that has primary enforcement responsibility
over public water systems in the state. In every state where either an environmental
or public health agency has at least partial responsibility for the revolving fund,
program management corresponds to the agency (or to at least one of the agencies,
in states where primacy is shared) for SDWA implementation. In the majority of
states, designation of SDWA enforcement authority was granted prior to 1980,
nearly two decades prior to establishment of the DWSRF program (U.S. EPA
1994). Moreover, recent work by Sinclair and Whitford (2012) suggests that
organizational structure, at least with respect to state environmental and health
agencies, may be better explained by historical factors than contemporary political
conditions.
Endogeneity is a bigger concern for finance agency involvement in DWSRF
implementation. In most cases, states delegate fund management to a financial
agency if the agency already manages the Clean Water SRF or some other
infrastructure financing program. Of the thirty-one states where finance agencies
have had at least partial responsibility over the DWSRF program, in all but three
states the agency already had established a role with the state’s Clean Water fund.
Financial agency involvement also might be an indication that the state intends to
issue leveraging bonds: finance agencies play a role in program management in
seventeen of the twenty-one (81 percent) leveraged states but in only thirty-one
states overall (62 percent). In general, the evidence suggests that assignment of
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DWSRF program responsibility to one or more agencies is largely a function of
historical responsibilities over water policy and choices about whether to leverage
federal funds. Case studies of SRF programs in three Southern states (Morris 2010)
indicate that interagency competition and administrative capacity also contributed
to state decisions about the location of program authority. Because the factors
contributing to agency assignment are complex and may be state-specific, we have
some confidence that the relationships we observe between an agency’s functional
expertise and loan allocation decisions are not spurious. Without strict exogeneity
in agency assignment, we cannot assert causal relationships, yet our results reveal
important patterns in how problem conditions shape the relationship between an
agency’s functional authority and decision outcomes.
Hypotheses, Models, and Data
We focus on two areas of spending in which states have some discretion: assistance
for projects not related to compliance with federal water quality law and assistance
for small water systems. In the EPA DWSRF spending data we use, states report the
amount of loan assistance they provide that helps currently noncompliant systems
meet compliance, the amount that helps compliant systems maintain compliance,
the amount that aids compliant systems to meet anticipated future standards, and
the amount not related to compliance. It is among the latter projects where state
agencies exercise discretion to provide assistance based on their own criteria,
including factors related to infrastructure improvement, affordability, the
applicant’s financial health, population served, and green projects. Our review of
the formulas states use to prioritize among projects reveals that the most influential
of these criteria is infrastructure improvement; these projects often take a broader
approach to water infrastructure development, aiming to advance green
infrastructure, promote watershed management and source water protection,
improve flow, or minimize service disruptions rather than address some particular
contaminant.
Given their expertise, environmental agencies should be most supportive of this
broad view of infrastructure development and therefore to dedicate a greater
portion of loan funds to projects not directly related to compliance [H1].
Professionals in these agencies have more background in the relationship between
water supply and ecosystem health. However, we expect that the severity of water
quality challenges within a state will moderate this response. High rates of water
quality violations will focus the attention of environmental agencies on compliance
goals, minimizing the influence of agency functional focus [H2].
The second area of spending we examine is assistance for small water systems.
Providing support for public water systems serving 10,000 or fewer people is an
important priority for the U.S. EPA. The 1996 SDWA Amendments placed
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emphasis on improving the technical, managerial, and financial capacity of small
systems and created several mechanisms for helping small systems comply with
drinking water regulations, including an optional set-aside fund that states may
establish within their DWSRFs. DWSRF officials can exercise discretion and invest
in small water systems. However, small systems entail substantial financial risk;
most small water systems have no credit history and remain vulnerable to local
economic conditions (Copeland 2010). States face competing pressures to design
DWSRF programs that both respond to their particular water quality challenges
and at the same time emphasize the fiscal health of applicant communities to
ensure the long-term integrity of the fund. The SRF approach creates a powerful
incentive for fiscal discipline. Enacting legislation for the state loan programs
envisioned that they would operate without ongoing federal support after initial
appropriations to capitalize the funds.1 The potential consequences for taking on
financial risk are substantial: without sound management of its loan programs, a
state may drain its funds and prevent its localities from accessing financial
assistance for infrastructure projects for the long term.
We hypothesize that DWSRF programs located in financial agencies will
emphasize the long-term fiscal integrity of loan funds, and therefore be more
cautious in assisting small water systems [H3]. As with noncompliance spending,
however, we expect that problem factors, such as the number of small systems
within a state, will outweigh the influence of agency type. Therefore the
relationship between institutional design and outcomes will be smaller in states that
are more reliant on small water systems [H4]. Furthermore, given their expertise
and training in financial management, we predict that financial agencies will be
more responsive than other management structures to the financial health of the
fund in deciding whether to award loans to small systems [H5].
Models and Data
Data on revolving fund spending patterns come from the DWSRF National
Information Management Systems (DWNIMS), compiled by the EPA for
accountability purposes. Our panel begins in 2000, by which time all states had
begun providing DWSRF loan assistance, and runs through 2008.2 We merged the
DWNIMS data with data from a variety of secondary sources to estimate the
influence of political and problem factors on state discretion in the implementation
of a multilevel policy program, and to assess how agency expertise conditions
responsiveness to problem conditions.
Our dependent variables are percentages of total loan funds awarded. Spending
on noncompliance-related projects is a percentage of spending across all
compliance categories (loans that help currently noncompliant systems meet
compliance, loans that help compliant systems maintain compliance, loans that aids
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compliant systems to meet anticipated future standards, and loans not related to
compliance), and assistance for small systems is the percentage of spending
dedicated to systems serving 10,000 or fewer people. We estimate expenditures
using Tobit, with censoring at 0 and 100.3 The premise of the Tobit model is that a
latent dependent variable is equal to the observed dependent variable within some
range, but censoring creates inequality between the latent and observed values
outside of that range. It is an appropriate estimation strategy for percentages that
are only observed between 0 and 100.
Coding of agency type comes from an EPA report to Congress reporting agency
leadership as of 2001 and information from DWNIMS about agency leadership as
of 2010. Where agency leadership changed, we identified the date of change using
state program reports and news articles. The SRF implementation environment is
complex. In 68 percent of state-years, program management is shared among two
or more agencies. Consequently, our agency variables measure whether an
environmental or financial agency has any formal decision making authority in
program management. Both are treated as dichotomous variables, because agency
type categories are not mutually exclusive in cases with shared program
management. Appendix 1, available as supplementary data at Publius online,
reports DWSRF agency leadership by state for the last year in our analysis, 2008.
To test how problem conditions might moderate the influence of an agency’s
functional focus, we interact agency type with problem condition variables
appropriate for our two models: (i) water quality violations to examine discretion
in supporting projects not related to SDWA compliance; and (ii) the percentage of
small systems and fiscal integrity of the loan fund to examine discretion in
supporting small water systems. To measure compliance, we used data from the
Safe Drinking Water Information System (SDWIS) on the percentage of water
systems in a state reporting water quality violations. This variable is lagged by one
year to give a realistic portrayal of when program officials might learn about their
state’s performance in compliance. Data on system size also come from the SDWIS.
To measure a loan fund’s fiscal status, we calculated the fund’s cumulative balance
using data and a formula from DWNIMS.
Drinking water infrastructure investments are likely shaped by a range of factors
in addition to the functional expertise of implementing agencies and problem
severity. Therefore, we include a number of control variables in our models. State
demographic characteristics may help direct infrastructure investment.
Infrastructure spending may be partially predicated on population density and
community wealth. Our analysis includes controls for population size, per capita
income, and percentage urban. Drinking water infrastructure investments tend
to be relatively low profile and low salience decisions. But, political factors
may influence investment patterns (McCubbins, Noll, and Weingast 1987; Wood
1990). Therefore we control for state political composition by including two
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variables: party control of the governor and the legislature and public opinion
liberalism. Given the sheer need for widespread investment in water infrastructure
(U.S. EPA 2002) and the human capital needed to oversee this investment, we
include a measure to control for bureaucratic capacity: number of state employees
per 1,000 residents. Similarly, infrastructure investment is likely to be controlled by
overall financial constraints. Therefore, we include a measure indicating the total
level of assistance awarded by a DWSRF each year and the cumulative funds
available.4 Because the agency variables that interest us vary little over time, we
omit state fixed effects but include fixed effects for year and Census region and
calculate standard errors with observations clustered by state.
Results and Discussion
Table 1 presents results of the two Tobit models predicting state discretion in SRF
programs. Summary statistics for all variables are given in Appendix 2 available as
supplementary data at Publius online. Omitted from the analysis are two state-years
with no DWSRF spending and, in the compliance model, six observations with
missing data.
Investment Outside of SDWA Compliance
Our first model examines the exercise of discretion when states invest in water
infrastructure that does not specifically advance SDWA compliance. This type of
investment can include projects that advance green planning, protect source water,
integrate technological innovations in drinking water systems, and improve
drinking water flow. We predicted that environmental agencies responsible for SRF
programs would invest more in noncompliance-related projects because these
professionals are in the best position to view the broad environmental and public
health benefits from targeting green infrastructure and technological innovation,
the type of projects that would typically fall into the noncompliance category (H1).
We also predicted that differences between agency types would be smaller where
water quality problems are more severe (H2). Model I in table 1 displays estimates
from our Tobit models.
To interpret the interaction between an agency’s functional focus and problem
conditions, we used the Tobit estimates to calculate average predicted differences in
DWSRF loan allocations between agencies of different types. Holding all other
variables at their actual values, we generated predicted loan allocations for each
observation with the agency variable set either to 0 (in this case indicating no
environmental agency management) or to 1 (in this case indicating environmental
agency management), accounting for censoring of the dependent variable.
Calculating the difference between these probabilities and averaging across all
observations produces the average predicted difference based on agency type.
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Testing the first hypothesis, we estimate that environmental agencies dedicate 2.03
percentage points more of their loan funds to noncompliance-related projects, but
this difference is not significant.5
We find more support for the hypothesis that differences between agency types
will vary across problem conditions (H2). The left panel of figure 1 depicts the
average predicted values of funding for projects not compliance related by agency
type across the range of values of compliance. The right panel shows the average
predicted difference between agency types. As seen in the right panel,
environmental agency management has a positive and significant relationship
Table 1 State discretion in DWSRF spending, 2000–08
I: Loans for projects
not compliance related
II: Loans for
small systems
Functional focus
Environment agency 57.425** (24.028) –
Finance agency – –414.942*** (131.017)
Problem conditions
Percent systems in violation, lagged 3.203 (1.980) 1.273** (0.523)
Percent small systems 1.589 (0.978) –0.175 (0.710)
Ln(funds available) –3.561 (15.912) 7.142 (6.763)
Functional focus * Problem conditions
Environment * percent systems in
violation, lagged
–4.987*** (1.834) –
Finance * percent small systems – 2.025*** (0.786)
Finance * Ln(funds available) – 12.415** (4.879)
Control variables
State employees per 1,000 population 2.781 (2.010) –1.330*** (0.446)
Governor party, lagged 3.694 (4.634) 2.224 (1.947)
Legislature party, lagged –0.477 (8.338) –4.918 (4.228)
Opinion liberalism 0.216 (1.147) 1.210*** (0.409)
Ln(population) 12.850 (13.722) –0.729 (5.766)
Ln(per capita income) 25.820 (23.250) –9.124 (11.893)
Percent urban –0.421 (0.695) –0.453** (0.214)
Ln(DWSRF assistance) 2.212 (3.441) –24.446*** (2.262)
Constant –568.477 (407.552) 509.055*** (185.577)
N 442 448
Pseudo R2 0.036 0.064
Note. Models estimated using Tobit with censoring at 0 and 100. Year and census region fixed
effects not shown. Standard errors clustered by state.
***p5.01, **p5.05, *p5.10 (two-tailed).
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(p5.05) with the percentage of loans dedicated to projects that are not compliance
related where compliance rates are high overall. Where just 1 percent of a state’s
water systems are in violation of drinking water quality laws, environmental
agencies award 13 percentage points more in noncompliance-related funding.
Environmental agencies scale back and behave more like other agency types when
violation rates are more severe.6 When levels of noncompliance are high, we detect
no difference between agency types.7
The model explains little of the overall variation in support for projects not
related to SDWA compliance. Political control does not predict patterns of SRF
spending; the estimated effects of the party of the governor and the legislature are
small and insignificant. Given the relatively low salience of drinking water
infrastructure investment, it is not surprising that political variables have no
consistent influence in our model. The only control variable that has a nearly
significant relationship with investment in projects that are not compliance related
is the percentage of water systems serving 10,000 or fewer customers (p¼ .101).
Both state and federal officials charged with drinking water protection have
particular concern about small water systems, which often lack the resources
Figure 1 Agency type and loans for projects not compliance-related, by violations
Note. Estimates calculated from Tobit coefficients shown in table 1. Estimates are expected values,
accounting for censoring. Shaded area shows a 95 percent confidence interval.
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necessary to maintain complex infrastructure and comply with water quality
regulations. Consequently, a number of states give funding priority to projects that
might not address specific compliance problems but instead consolidate small
systems or help small systems improve their operating capacity.
Investment in Small Water Systems
Loans to small water systems support the EPA’s goal of improving the performance
of these systems, but they are higher risk investments that offer no greater reward
than loans to larger, more financially sound water systems. We predicted that loan
funds managed in part by financial agencies would give greater attention to a
fund’s risk profile (H3). The pattern that emerges in this analysis is similar to that
in noncompliance-related spending: agency type does not have a direct relationship
with patterns of DWSRF investment when examined across the full range of
observations, but it appears to shape how program administrators respond to
problem conditions and fund status.
Using average predicted differences to interpret the interaction depicted in
Model II of table 1, DWSRFs managed by financial agencies do not dedicate a
significantly smaller percentage of their loan awards to small systems on average.
However, we find a significant difference between agency types in states where
small water systems are less prevalent (H4). Figure 2 shows model predictions
across the range of values of small system prevalence. The majority of community
water systems—92 percent in 2008—serve fewer than 10,000 people, although these
small systems serve just 18 percent of the total population receiving water from
community water systems (U.S. EPA 2011). As figure 2 demonstrates, in states with
a low relative percentage of small systems, DWSRFs managed by financial agencies
provide a significantly lower percentage of total funds to these small systems than
funds managed without financial agency involvement. The difference is as much as
32 percentage points at the lowest rate of small systems (69 percent). As the
percentage of small systems in a state rises, financial agencies appear to respond to
their need and commit significantly more funds to them. Thus the differences
across agency types dissipate with a higher percentage of small systems.
Results of the analysis of fund availability appear in figure 3. For all SRFs, the
proportion of funds made available to small systems rises as the overall SRF fund
balance rises. Consistent with H5, this relationship is stronger among financial
agencies than among other agency types and only significant among financial
agencies. By our measure of funds’ fiscal integrity—calculated using an EPA
formula—financial agencies appear to be more responsive than other agency types
to fund scarcity when making loan decisions. The result is that financial agencies
are more generous than other agency types to small systems where the status of
their funds is healthy, a finding that we had not anticipated. However, it may be
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that financial agencies are in a better position to evaluate the fiscal health and
potential financial risk of small systems compared to their public health or
environmental counterparts. This expertise may foster investment while public
health and environmental officials may adopt a conservative investment approach,
even as their fund balance increases, to avoid jeopardizing infrastructure investment
over the long term.
Several control variables are related to small system assistance. States with a large
percentage urban area dedicate significantly less funding to small systems; urban
states have a lower percentage of small systems, and loans to large urban water
utilities can easily crowd out other SRF loan activity. Holding constant fund
availability, the amount of assistance an SRF awards in the current year also has a
negative relationship with small system support, likely for the same reason that
large loans can dominate fund activity. Moreover, our measure of state capacity,
the number of state employees per 1,000 residents, is associated with lower rates of
small system funding. As further evidence that DWSRFs are responding to state
need, assistance for small systems is positively related to compliance with the
SDWA, with a one-point increase in the percentage of systems in violation yielding
Figure 2 Agency type and loans for small systems, by small systems
Note. Estimates calculated from Tobit coefficients shown in table 1. Estimates are expected values,
accounting for censoring. Shaded area shows a 95 percent confidence interval.
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a 0.98-point increase in percentage of funds to small systems. Considering that the
vast majority of SDWA violations occur in small systems (92 percent in our
dataset), increasing support for small systems is a sensible policy response to
noncompliance. The only political variable showing any association with SRF
funding patterns in either of our analyses is citizen ideology. Here, a shift from the
most conservative to the most liberal state is associated with a 34-point increase in
the percentage of funds going to small systems.
Conclusion
The devolution of policy authority to the states sometimes involves explicit
delegation of decision making responsibility with the hope that states will design
programs that are responsive to state-level conditions. However, the exercise of
discretion by state agencies implementing devolved policies typically is treated in
the literature as a departure from policy makers’ goals. We begin our analysis from
a different perspective: recognizing that states might be asked to exercise discretion
in policy implementation and to produce variable outcomes, but that state
Figure 3 Agency type and loans for small systems, by fund level
Note. Estimates calculated from Tobit coefficients shown in table 1. Estimates are expected values,
accounting for censoring. Shaded area shows a 95 percent confidence interval.
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bureaucrats operate in a murky environment with multiple political principals and
information constraints that can limit their ability to direct program implemen-
tation toward addressing their own state’s needs. Our goal was to explore the extent
to which states utilize their discretion in a multilevel program designed to foster
divergent approaches and to examine how the functional focus of an agency affects
responsiveness to problem conditions.
We predicted that initial decisions over allocating program responsibility to an
agency might have long-term effects on program implementation. State revolving
funds provide a rare opportunity to examine bureaucratic discretion and agency
expertise, because the same program is managed in different states by agencies with
distinct professional expertise and organizational norms. Looking across eight years
of data and two areas of water infrastructure expenditure, we find no direct
relationship between agency type and the exercise of state discretion. However, our
analysis indicates that agencies do use their discretion to respond to problem
conditions in their state, and that patterns of responsiveness vary across agency
types.
We find evidence that agencies’ functional expertise is associated with decision
making in areas where the state does not face a pressing problem, but that problem
severity diminishes differences between agency types. This is a particularly
interesting finding that highlights how problem conditions constrain agency
discretion. While some scholars equate discretion with agency drift, our results
emphasize the interplay of agency discretion and problem conditions. When
problems are severe, state agencies—regardless of their functional expertise—focus
their attention toward the problems in their state. For example, where a state has
high levels of compliance with drinking water quality regulations, environmental
agencies that manage DWSRF funds are more likely to engage in innovative
investment, that is, investment that is not directly aimed toward specific drinking
water contaminants. Differences between environmental and other agencies in
compliance-related spending disappear where a higher percentage of water systems
are in violation of water quality laws. Similarly, financial agencies demonstrate less
support for the EPA priority of funding small systems in states with relatively fewer
small systems, but where small systems are more prevalent, their support level rises
and they behave more like other agency types. Financial agencies also dedicate a
smaller percentage of loans to small systems where state fund balances are low,
behaving more like other agency types. Consistent with research by Mullin (2009),
we find that problem conditions moderate the relationship between institutional
design and outcomes, such that institutional factors have less influence where
problems are more severe. For federalism scholars, our findings lend support to one
of the underlying tenants of decentralization: subnational governments are in a
strong position to identify and respond to local problem conditions, regardless of
specific details of agency and program design.
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These results also reinforce the lessons from public administration research
highlighting the importance of organizational identity (Bardach 1998; Wilson
1989). Although locating an SRF program in a particular type of agency does not
directly produce a certain outcome, our results suggest that institutional location
influences how implementing officials perceive and respond to problem conditions
within a state. This creates opportunity for state political actors to exert ex ante
political control over a multilevel program by situating the program in an agency
that will be most sympathetic to the problems or goals the politician cares about
(McCubbins, Noll, and Weingast 1987; Moe 1989).
Ultimately, our research highlights the importance of considering the intent
behind devolution, delegation, and political control. State agency behavior in the
context of multilevel programs, even while those programs become increasingly
common, remains understudied. Our results suggest that state agencies exercise
discretion when substantive problems are not severe. Federal actors cede
responsibility to subnational units for a multitude of reasons and create complex
multilevel governance networks where state agencies must operate. Yet, research to
date tends to treat delegation as a necessary evil that will result in bureaucratic drift
with agencies deliberately pursuing their own goals. Given the near constant
drumbeat of devolution across multiple substantive areas, it is important to
consider devolution and delegation that is designed to promote state discretion and
determine the ways in which that discretion operates.
Supplementary Data
Supplementary data can be found at www.publius.oxfordjournals.org.
Notes
This project was supported by a Faculty Senate Seed Money Grant from Temple
University. The authors thank Heather Bosak and Arnold Kim for their help with
data collection.
1. The original goal was for SRFs to become self-sustaining, but implementation problems
combined with ongoing needs have led to continued annual Congressional appropriations.
The magnitude of federal appropriations for both Clean Water and Drinking Water SRFs
has declined over time, until the 2009 American Recovery and Reinvestment Act (ARRA)
dedicated $6 billion in emergency appropriations for SRF funds. Detailed information on
capitalization grants is available at: http://water.epa.gov/grants_funding/dwsrf/dwnims.cfm
2. We end our analysis in 2008 because new rules under the ARRA affected SRF decision
rules in many states even for non-ARRA spending.
3. Because states may report negative spending for accounting purposes, a total of nine
observations across the two analyses have values either less than 0 or greater than 100.
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Results are robust to estimating the models using ordinary least squares or to omitting
the outlying observations, and both strategies narrow the confidence intervals in the
tails. We present the more conservative estimates here acknowledging the censoring that
applies for most observations.
4. All variables but one are annual data or, in the case of the urban variable, linearly
interpolated from decennial Census data. The exception is the measure of public opinion
liberalism, a time-invariant indicator calculated by Erikson, Wright, and McIver from
public opinion polls conducted from 1976 to 2003. The authors have demonstrated that
state-level ideology has shown considerable stability over several decades (Erikson,
Wright, and McIver 2006).
5. Because we interact agency type with variables measuring problem conditions, the
coefficient in table 1 for environment agency indicates the difference in spending on
loans for projects that are not compliance related where the lagged percentage of systems
in violation is 0. As shown in the right panel of figure 1, environmental agencies do
spending significantly more on noncompliance-related spending in these high
compliance states, but the difference associated with agency type is not significant
when analyzed across the full range of observations at all levels of compliance.
6. These results are even stronger when we restrict our analysis to focus on cases where a
single agency implements the state’s DWSRF program. Under these conditions, an
agency’s functional focus should have a stronger influence on investment decisions
compared to situations where implementation is shared among agencies. When
environmental agencies implement DWSRF programs on their own, they dedicate a far
greater percentage of their funds to projects not related to compliance (endeavors like
source water protection, ecosystem management, and green infrastructure). The
functional focus of an agency has a greater impact where agencies act alone then where
they operate in cooperation with other agencies. The interaction with compliance is also
stronger among single agencies, so that agency type becomes insignificant where problem
severity is high.
7. Similarly, we find that agency type has no relationship with loan allocations that should
allow less agency discretion. In a placebo test, we regressed agency type on the
percentage of loan funds dedicated to projects for noncompliant systems to meet
compliance (rather than projects for maintaining compliance or meeting future
standards, or those not compliance-related). Helping systems that are in violation to
meet current regulatory standards should be the top priority for any funding program,
and indeed we find no difference between agency types regardless of statewide
compliance rates.
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