case Study

General Interest

Local Managerial Perceptions of Intergovernmental Management

Luke Fowler 1

Abstract Interjurisdictional policy problems have facilitated both interlocal cooperation and opportunities for self-interested behavior from local governments. However, intergovernmental management (IGM) approaches shape how local governments interact with each other and how much influence local managerial efforts have on policy outcomes. After identifying three IGM models used to manage air quality, analyses of local managerial perceptions indicate that some approaches facilitate more cooperation and organizational efficacy than others through structuring responsibilities in Clean Air Act policy implementation. Conclusions suggest that approaches to IGM are important in shaping how managers perceive efforts to manage complex policy problems.

Keywords cooperation, managerial perceptions, air quality

Over the past several decades, interjurisdic-

tional policy problems have facilitated both

interlocal cooperation and opportunities for

self-interested behavior from local govern-

ments (Conlan 2006; McGuire 2006; Feiock

and Scholtz 2009). However, intergovernmen-

tal management (IGM) approaches shape how

local governments interact with each other and

how much influence local managerial efforts

have on policy outcomes. While different

approaches to IGM likely lead to different local

managerial perceptions of interlocal interac-

tions and organizational efficacy (i.e., agency

effectiveness), there are few examples of alter-

native approaches being used for the same pol-

icy. However, the U.S. Clean Air Act (CAA)

provides a unique case of a complex policy

problem that includes multiple IGM models:

(1) delegated-authority, in which local govern-

ments are delegated power to adapt programs to

local needs; (2) top-down, in which local

governments serve as administrative subunits

of the state; and (3) uncentralized, in which

local governments manage complex policy

problems outside of state-led efforts. Depend-

ing on local managers’ place in state-led CAA

implementation strategies, some approaches

facilitate more cooperation and organizational

efficacy than others through structuring respon-

sibilities in policy implementation. As such,

certain IGM approaches may create a better

platform for engaging local managers in

1 School of Public Service, Boise State University, Boise, ID,

USA

Corresponding Author:

Luke Fowler, School of Public Service, Boise State University,

1910 University Dr., MS 1935, Boise, ID 83725, USA.

Email: [email protected]

State and Local Government Review 2018, Vol. 50(1) 6-14 ª The Author(s) 2018 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0160323X18769974 journals.sagepub.com/home/slg

collaborative management of complex policy

problems. In order to examine these issues, this

article proceeds with a discussion of IGM mod-

els used in U.S. CAA implementation, fol-

lowed by an examination of managerial

perceptions of interlocal cooperation and orga-

nizational efficacy using data from local air

agencies. Finally, conclusions suggest that

approaches to IGM are important in shaping

how managers perceive efforts to manage

complex policy problems.

IGM and CAA Implementation

Federal and state administrative structures and

rules create institutional barriers to local gov-

ernment efforts by fragmenting authority and

formalizing intergovernmental interactions

(Chen and Thurmaier 2009; Feiock and Scholtz

2009; Kwon and Feiock 2010). As framed

under the CAA, air quality governance relies

on a federal–state partnership. The U.S. Envi-

ronmental Protection Agency (EPA) sets the

National Ambient Air Quality Standards

(NAAQS). States develop State Implementa-

tion Plans (SIPs) to maintain those standards

based on control strategies and regulations

approved by the EPA (Belden 2001). However,

some states have both the political will and the

institutional capacity to manage CAA pro-

grams, and others have neither of those advan-

tages (Wood 1992; Potoski and Woods 2002;

Emison and Morris 2010; Konisky and Woods

2010; Fowler 2013). Despite state-centralized

power, federal, state, and local agencies, as

well as nongovernmental organizations

(NGOs), are involved in air quality manage-

ment (Ringquist 1993a, 1993b; Lester 1995;

Emison and Morris 2010). Additionally, local

context constrains what is feasible in practice,

leading to both interlocal cooperation and com-

petition (Woods and Potoski 2010; Gofen 2013;

Reed 2014; Fowler 2016, 2018).

As such, state SIPs can be divided into three

general types. First, top-down states centralize

power at the state level. Local governments are

treated as administrative subunits of the state,

with managers focused on compliance manage-

ment. Second, delegated-authority states create

implementation partners by delegating regula-

tory and enforcement powers to local agencies.

Local governments develop programs and

negotiate partnerships with other local agencies

as necessary. Finally, uncentralized states nei-

ther preempt nor delegate authority to the local

level in their SIPs. In response, local agencies

strategically interact with other organizations

but face barriers to forming partnerships and

managing air quality outcomes. Consequently,

SIPs have important implications for local gov-

ernments and their roles in IGM. For instance,

by delegating authority, states encourage local

governments to adapt programs to local needs,

which may include interlocal partnerships. On

the other hand, by using local governments as

implementation agents, states rely on hierarch-

ical relationships rather than cooperation.

Alternatively, by leaving local governments out

of implementation plans, states limit responsi-

bilities and opportunities for local governments

to work toward shared goals. Consequently,

how federal and state governments shape local

government roles affects local agencies’ ability

to both cooperate with each other and impact

complex policy problems.

Delegated-authority IGM

The most sophisticated IGM approach provides

local governments with discretion and flexibil-

ity, by delegating authorities. Consequently,

local governments find new, innovative ways

to manage programs to satisfy both local needs

and national standards (Waterman and Meier

1998; Agranoff and McGuire 2001). Addition-

ally, they voluntarily interact with state,

federal, or other local agencies that are part of

the implementation plan in the process of

managing shared goals (Scicchitano and

Hedge 1993; Agranoff and McGuire 2001;

Allik and Realo 2004). As a result, there is an

inherent bargaining process in which resource

exchanges, program requirements, and respon-

sibilities are negotiated. As such, delegated-

authority arrangements seem like partnerships,

in which local managers are semiequal partici-

pants with bargaining power. Furthermore,

local managers are able to adjust state or

Fowler 7

federal plans to improve local policy outcomes

(Agranoff and McGuire 2001). Consequently,

they see specific local outcomes as a result of

their efforts rather than the result of federal or

state decisions. In this way, managers connect

local outcomes to their efficacy and credit

themselves for policy outcomes. As such, with

power to negotiate, local managers in delegated-

authority states will perceive more interlocal

cooperation and organizational efficacy than

managers in other states.

Top-down IGM

More traditional IGM arrangements (i.e., top-

down models) allow the federal government

to manage programs by using state and local

governments as implementing agents (Wright

1988; Agranoff 2001; Agranoff and McGuire

2001; O’Toole and Christensen 2012). State

and local managers function as compliance

managers, with external mandates requiring

considerable resources to implement and pro-

viding few opportunities to match programs

with local needs (Agranoff and McGuire

2001; Lipsky 2010). Consequently, local auton-

omy is reduced, and central decision-making is

disconnected from street-level implementation

(Waterman and Meier 1998; Agranoff and

McGuire 2001). Since cooperation relies on

voluntary engagement, overseeing federal or

state requirements may seem more coercive

than cooperative, even when local governments

work together (Scicchitano and Hedge 1993;

Allik and Realo 2004). Additionally, similar

to other principal–agent relationships, local

governments (agents) place credit or blame for

outcomes on states (principals) that make

decisions and coordinate implementation

(Waterman and Meier 1998). As such, with

coerced participation, local managers in top-

down states will perceive less interlocal

cooperation and organizational efficacy than

managers in delegated-authority states.

Uncentralized IGM

Local governments are not always included

in federal or SIPs. Interestingly, these local

governments still choose to manage complex

policy problems from outside state-led efforts.

However, they find cooperation difficult, which

leads to more self-interested, opportunistic

behavior. If their roles are not clear, local

managers may obtain resources and power

through nonconventional interactions (i.e.,

outside federal and state management struc-

tures). Consequently, local managers strategi-

cally build ties to multiple partners, which

results in varied interactions (Agranoff and

McGuire 1998, 2001). In a practical sense,

resources are sought from federal, state, and

local governments, as well as NGOs, which

“allows any and all actors to play an impor-

tant, irreplaceable role in local governance”

(Agranoff and McGuire 2001, 675).

Additionally, there are numerous barriers to

cooperation when an agency is not part of the

official implementation strategy. Most impor-

tantly, local government programs are not

defined by national policies, so they may not

share goals with other local, state, or federal

agencies. Consequently, interactions are more

likely to be based on resource exchange and

strategic benefits than shared goals, which cre-

ates the impression of a transaction rather than

of cooperation (Agranoff and McGuire 2001;

Graddy and Chen 2006; Provan and Lemaire

2012). Furthermore, since state or federal

implementation plans are the primary means

of managing policy problems in the uncentra-

lized approach to IGM, local managers may not

be aware of specific impacts their efforts are

making. That is, they may not be able to distin-

guish which impacts result from state or federal

efforts and which result from their own local

efforts. With no official role, local managers

in uncentralized states will perceive less inter-

local cooperation and organizational efficacy

than managers in both delegated-authority and

top-down states.

Method

Data Collection

Survey data were collected from local managers

who are members of the National Association

8 State and Local Government Review 50(1)

of Clean Air Agencies (NACAA 2017). Previ-

ous research suggests NACAA membership is

the most accurate list representing a discrete

population of local air agencies, has a dedicated

mission to air quality and is implementing

initiatives for air quality improvement, and is

engaged in intergovernmental air governance

(Lester and Lombard 1998; Woods and Potoski

2010; Fowler 2016, 2018). Of the 118 total

members listed and contacted, seventy-eight

(66.1 percent) completed enough of the survey

to be usable for this analysis. Of these seventy-

eight members, twenty-six (33.3 percent)

responded via mail and fifty-two (66.7 percent)

via online survey. No systematic differences

were found between survey respondents and

nonrespondents. The data sample is of a unique

local agency population. As such, it may not be

representative of all local agencies (especially

those with different missions or functions), lim-

iting generalizability. Further survey details are

available in the Online Supplemental Text 1.

Dependent Variables and Data Analysis

Dependent variables were modeled as ordinal

variables of local air agency managerial per-

ceptions of their partnerships with other local

agencies and efficacy of their agency. Two sur-

vey items were used to measure perceptions:

(1) “My office actively cooperates or partners

with local agencies working on air quality

issues in my area” (cooperation) and (2) “My

local office has a direct impact on air quality

in my area” (efficacy). A five-point Likert scale

was used that ranged from 1 (strongly disagree)

to 5 (strongly agree). Accordingly, ordered pro-

bit models analyze effects of IGM models on

perceptions, with coefficients reported. Diag-

nostic tests indicated no assumptions of ordered

probit were violated (Menard 2002). Online

Supplemental Table 1 provides descriptions of

dependent and predictor variables.

IGM Models

States were classified into three IGM models

using a four-step methodology. First, previous

scholarship (e.g., Lester and Lombard 1998;

Woods and Potoski 2010) and the NACAA

Web site were consulted to narrow down differ-

ences in state-level management approaches

and identify states with local air agencies

(twenty-six such states were identified). Sec-

ond, survey data revealed local governments

with delegated powers for setting air pollutant

standards, enforcing state and/or federal stan-

dards, performing air quality monitoring, and

operating pollution prevention programs. Miss-

ing survey data for four states reduced the num-

ber of states in this analysis to twenty-two.

Local responses were aggregated to the state

level, and trends in local agency authorities

were identified. Trends were then confirmed

by reviewing SIPs.

Third, states were classified according to

IGM type based on their decision-making rules

(as reflected in their SIPs). Delegated-authority

states delegate powers to local agencies for set-

ting and enforcing standards (six states).

Uncentralized states do not delegate powers

Table 1. Ordered Probit Models.

Coefficients Cooperation*** Efficacy***

Delegated- authority

1.254 (0.469)** 1.278 (0.490)**

Top-downa 0.317 (0.476) 0.125 (0.566) Local

government per capita

�0.519 (0.171)** �0.164 (0.211)

Metropolitan percentage

0.875 (0.249)*** 0.790 (0.293)**

Metropolitan population

0.631 (0.286)* 1.200 (0.457)**

Air quality 0.024 (0.010)* 0.002 (0.013)

Cut point 1 �1.564 �1.341 Cut point 2 �0.942 �0.470 Cut point 3 �0.436 0.472 Cut point 4 1.042 — Pseudo R

2 0.109 0.139

Log likelihood �67.598 �54.483 N 68 69

Note: Standard errors are clustered at the state level. Asterisks signify results of t-tests and F-tests at the follow- ing levels: *<.05, **<.01, ***<.001. For efficacy, missing cut points result from respondents not selecting all available categories. a Coefficients comparing delegated-authority to top-down

are as follows: .938* for cooperation and 1.153* for efficacy.

Fowler 9

to the local level (eight states). Top-down states

create local-level administrative subunits that

require delegating authorities for enforcement,

air quality monitoring, and/or pollution preven-

tion programs to the local level but not author-

ities for setting standards (eight states). Finally,

SIPs were rereviewed to further confirm survey

data, assumptions, and state classifications.

Based on the classifications of state IGM models

for air quality, local managers were identified as

operating within top-down, delegated-authority,

or uncentralized states. Of the seventy-eight

local manager respondents, twenty (25.6 per-

cent) were found to operate in top-down states,

thirty-seven (47.4 percent) in delegated-

authority states, and twenty-one (26.9 percent)

in uncentralized states. Finally, dummy vari-

ables compared local managers in top-down and

delegated-authority states to those in uncentra-

lized states.

Other Predictor Variables

Additionally, predictor variables control for

size of local governments, relative jurisdic-

tional sizes of air agencies, area population, and

air quality. Per capita personal income from

local governments in the metropolitan area con-

trols for variance in area local government

size. 1

Size of local governments correlates with

competition in local areas. If local governments

increase in size, then local managers will be

likely to perceive more competition from other

local agencies and feel less cooperative. Addi-

tionally, as managers perceive more competi-

tion, their perceptions of their own efficacy

will decrease as they feel more pressure for per-

formance. Therefore, it is hypothesized that as

local government capacity increases, coopera-

tion and efficacy will decrease.

Percentage of metropolitan population

within air agency jurisdiction controls for rela-

tive jurisdictional sizes of local air agencies. In

comparison to larger agencies, smaller agencies

are both less capable of affecting and less active

in governing regional air quality (Fowler 2016,

2018). If relative jurisdictions of local air agen-

cies increase, then managers will perceive

themselves as more central to air governance,

which will lead to perceptions of stronger coop-

erative ties and more efficacy.

Metropolitan population is controlled for as

well. Size of metropolitan area affects both air

quality conditions and state–local relations

(Woods and Potoski 2010; Fowler 2016,

2018). If population increases, then local man-

agers again will perceive themselves as more

central to governance and perceive stronger

cooperative ties and organizational efficacy.

Thus, it is hypothesized that as jurisdiction size

and population increase, cooperation and effi-

cacy will increase. U.S. Bureau of Economic

Analysis provided data on local economies and

populations.

Finally, air quality index (AQI) controls for

differences in environmental conditions. AQI

creates a standardized measure of air quality for

pollutants regulated under the NAAQS (on a

scale from 0 to 500) for air quality monitoring

regions (U.S. EPA 2017b). If there are poor

environmental conditions, then local agencies

will be in more need of cooperative ties to other

local agencies to effectively achieve their mis-

sion. Additionally, if environmental conditions

are poor, then local agencies are unlikely to

perceive organizations as having impacts on

policy outcomes. Thus, it is hypothesized that

as AQI increases, perceptions of cooperation

and efficacy will increase. EPA provided AQI

data (U.S. EPA 2017a).

Results

Online Supplemental Table 2 provides compar-

ison of means tests and Cramer’s V for local

manager perceptions of cooperation and effi-

cacy by IGM model. These initial findings indi-

cate local managers in uncentralized states have

much lower perceived levels of cooperative

relationships with other local agencies and

organizational efficacy than respondents in

delegated-authority and top-down states. Addi-

tionally, managers in delegated-authority states

have higher perceived levels of cooperative

relationships and organizational efficacy than

respondents in top-down states.

Table 1 displays ordered probit results for

cooperation and efficacy. Dummy variables

10 State and Local Government Review 50(1)

compare responses from delegated-authority

and top-down states to uncentralized states.

Findings indicate local managers in both top-

down and delegated-authority states perceive

levels of cooperation and efficacy to be higher

than those in uncentralized states, and percep-

tion levels in delegated-authority states are

higher than those in top-down states. However,

top-down states are not significantly different

from uncentralized states for either cooperation

or efficacy. With other variables at the means,

probability of managers in delegated-authority

states responding strongly agree to cooperation

increased by 45.5 percent and 35.9 percent

compared to uncentralized and top-down states,

respectively. Additionally, probability of man-

agers in delegated-authority states responding

strongly agree to efficacy increased by 43.0 per-

cent and 38.0 percent compared to uncentra-

lized and top-down states, respectively.

Online Supplemental Table 3 provides

findings for IGM models tested as ordinal

rather than nominal variables and indicates

similar trends. Furthermore, findings indicate

that local government per capita, local air

agency jurisdictions, populations, and AQI

are positively correlated with cooperation

and efficacy. Also, findings for local govern-

ment per capita and efficacy are negatively

correlated and not statistically significant.

Finally, pseudo R 2

statistics indicate models

are weak to moderate predictors of coopera-

tion and efficacy.

Discussion

Based on findings, there is sufficient support

for the following hypotheses: (1) Managers in

delegated-authority states perceive more coop-

eration and efficacy than managers in other

states, (2) managers in top-down states perceive

less cooperation and efficacy than managers in

delegated-authority states, and (3) managers in

uncentralized states perceive less cooperation

and efficacy than managers in other states. In

general, findings suggest local air managers in

delegated-authority states perceive more inter-

local cooperation and organizational efficacy

than do their counterparts in other states. While

local air agencies play a crucial, central role in

all states, agencies in delegated-authority states

are treated as partners. On the other hand, those

in top-down states are limited in autonomy, and

those in uncentralized states are not included in

SIPs. As a result, local air managers perceive

interagency cooperation and individual effi-

cacy in different ways.

Findings for control variables also indicate

that size and capacity of local agencies affect

local managerial perceptions. As local agencies

grow, perceptions of cooperation and efficacy

increase. This suggests managers in larger local

agencies have different perceptions than those

in smaller agencies. Additionally, findings on

air quality suggest that as a policy problem

worsens, managers are likely to perceive higher

levels of interlocal cooperation. This finding

likely stems from actual cooperation needs for

complex policy problems. Interestingly,

though, there is not a relationship between air

quality and perceptions of organizational effi-

cacy. Although not the central focus here, the

impacts of local capacity and resources on

managerial perceptions are an important aspect

of interlocal cooperation and organizational

efficacy and should be considered further.

Nevertheless, there are limitations to these

findings. First, analyses rely on data from a

group of agencies engaged in a specific mis-

sion. Because cooperative relationships are

affected by policy arena, future research should

apply this framework to other policies, employ

alternative measurements of these concepts,

and consider perceptions of NGOs as well

(Lundin 2007; Andrews and Entwistle 2010).

Second, analyses do not consider actual levels

of cooperation or efficacy of agencies and rely

only on perceptions. Variances in perceptions

could result from variances in actual coopera-

tive relationships and efficacy of agencies. If

so, it would suggest IGM is still having an

important impact on governance. Finally,

although predictor variables are connected to

dependent variables, they do not take into

account how specific managers may perceive

concepts such as capacity or specific forms of

cooperation (e.g., contracting).

Fowler 11

Conclusions

State management strategies are important in

shaping interlocal interactions and, in turn,

managerial perceptions of those interactions

and agency efficacy. Findings suggest two

important implications for public-sector coop-

eration. First, IGM affects how managers per-

ceive management strategies. By delegating

powers and creating bargaining opportunities,

local agencies are treated as partners who are

voluntarily engaged. Local air managers in

delegated-authority models have perceptions

of cooperative relationships with other organi-

zations and more efficacy for their agency.

On the other hand, leaving local managers out

of implementation strategies (i.e., uncentra-

lized) makes interorganizational ties difficult

to initiate. As a result, interactions are more

likely to be viewed as primarily for strategic

purposes rather than for cooperation. Addition-

ally, when managers lack autonomy and inde-

pendence (i.e., under the top-down IGM

approach), they perceive ties to other organiza-

tions as less cooperative and view themselves

as having less efficacy (at least compared

to managers working under the delegated-

authority IGM model).

Furthermore, although interagency interac-

tions may be objectively cooperative, they may

not always seem cooperative to participants.

When interagency interactions result from

coercion, managers may perceive themselves

as doing as mandated rather than cooperating.

In these cases, managers are likely less dedi-

cated, less invested, and more willing to take

advantage of partners, leading to less produc-

tive interactions. As such, local air manager

experiences are much different, and therefore,

managers ascribe different value to IGM pro-

cesses. In turn, those differences likely contrib-

ute to levels of willingness to participate in the

management of complex policy problems that

require cooperation. Nevertheless, further

research is necessary to examine mandated

interorganizational ties in cooperative environ-

ments. Additionally, research should better

incorporate social psychology into understand-

ing how to facilitate perceptions of cooperation

at the individual level. As networks are socially

based, it is important that social aspects inher-

ent to interagency cooperation are not over-

looked (Provan and Lemaire 2012).

Second, these findings add another dimen-

sion to understanding interlocal relations.

Clearly, some local air managers view relation-

ships with other local agencies as more coop-

erative and beneficial than do others, which

impacts broader interlocal relationships. Con-

sequently, IGM mechanisms may impact local

collaboration efforts (or at least perceptions of

them) and be a potential source of interlocal

conflict. However, air quality is a unique policy

area. It relies on national coordination and dis-

tinct roles for public agencies and NGOs,

which likely leads to a different perspective

on how IGM connects local agencies. As such,

further research should assess perceptional dif-

ferences in interlocal relations and their effects

on working relationships between local manag-

ers in other policy areas with complex prob-

lems. Interlocal relationships are increasingly

important in public service delivery, especially

for complex policy problems. As such, impor-

tant insights can be obtained from understand-

ing how different managerial approaches to

the same problems affect the character of

these relationships.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest

with respect to the research, authorship, and/or

publication of this article.

Funding

The author received no financial support for the

research, authorship, and/or publication of this

article.

Supplemental Material

Supplementary material for this article is available

online.

Note

1. We tested alternative measures such as environ-

mental expenditures. Findings are similar to those

reported. However, alternative measures had at

least two important flaws: (1) Most alternatives

12 State and Local Government Review 50(1)

cannot be disaggregated to local areas and (2)

focusing only on environmental efforts overlooks

other interagency partnerships (survey data indi-

cate cooperation with transportation and health

agencies too). On the other hand, per capita

income is consistently and comparably measured

in local areas, and model comparison statistics

indicate that it is a better fit than alternatives. In

cases where data were reported for state and local

combined, but not both individual levels, we took

the difference between aggregated and individual

levels to determine missing values.

References

Agranoff, Robert. 2001. Managing within the

matrix: Do collaborative intergovernmental rela-

tives exist? Publius 31:31–56.

Agranoff, Robert, and Michael McGuire. 1998. A

Jurisdiction-based model of intergovernmental

management in U.S. Cities. Publius 28:1–20.

Agranoff, Robert, and Michael McGuire. 2001.

American federalism and the search for models

of management. Public Administration Review

61:671–81.

Allik, Juri, and Anu Realo. 2004. Individualism-

collectivism and social capital. Journal of

Cross-Cultural Psychology 35:29–49.

Andrews, Rhys, and Tom Entwistle. 2010. Does

cross-sectoral partnership deliver? An empirical

exploration of public service effectiveness, effi-

ciency, and equity. Journal of Public Administra-

tion Research & Theory 20:679–701.

Belden, Roy S. 2001. The Clean Air Act. Chicago,

IL: American Bar Association, Section on Envi-

ronmental, Energy, and Resources.

Chen, Yu-Chen, and Kurt Thurmaier. 2009. Interlo-

cal agreements as collaborations: An empirical

investigation of impetuses, norms, and success.

American Review of Public Administration 39:

536–52.

Conlan, Tim. 2006. From cooperative to opportunis-

tic federalism: Reflections on the half-century

anniversary of the commission on intergovern-

mental relations. Public Administration Review

66:663–76.

Emison, Gerald, and John Morris. 2010. Speaking

green with a southern accent. Lanham, MD:

Lexington.

Feiock, Richard C., and John T. Scholtz 2009. Self-

organizing governance of institutional collective

action dilemmas: An overview. In Self-

organizing federalism: Collective mechanisms

to mitigate institutional collective action dilem-

mas, ed. R. C. Feiock, and J. T. Scholtz, 3–32.

New York: Cambridge University Press.

Fowler, Luke. 2013. Measuring organization: Per-

formance in environmental agencies. Interna-

tional Journal of Organizational Theory &

Behavior 16:324–58.

Fowler, Luke. 2016. Local governments: The

“Hidden Partners” of air quality management.

State & Local Government Review 48:175–88.

Fowler, Luke. 2018. When need meets opportunity:

Expanding local air networks. American Review

of Public Administration 48:219–31.

Gofen, Anat. 2013. Mind the gap: Dimensions and

influence of street-level divergence. Journal of

Public Administration Research & Theory 24:

473–93.

Graddy, Elizabeth A., and Bin Chen. 2006. Influ-

ences on the size and scope of networks for social

service delivery. Journal of Public Administra-

tion Research & Theory 16:533–52.

Konisky, David M., and Neal D. Woods. 2010.

Exporting air pollution? Regulatory enforcement

and environmental free riding in the US. Political

Research Quarterly 63:771–83.

Kwon, Sung-Wook, and Richard C. Feiock. 2010.

Overcoming the barriers to cooperation: Intergo-

vernmental service agreements. Public Adminis-

tration Review 70:876–84.

Lester, James P. 1995. Environmental policy and

politics: Theories and evidence, 2nd ed. Durham,

NC: Duke University Press.

Lester, J. P., and Emmett N. Lombard. 1998. Envi-

ronmental regulation and state-local relations.

In Governing partners: State-local relations in

the United States, ed. R. L. Hansen, 139–60.

Boulder, CO: Westview Press.

Lipsky, Michael. 2010. Street-level bureaucracy.

New York: Russell Sage Foundation.

Lundin, Martin. 2007. When does cooperation

improve public policy implementation? Policy

Studies Journal 35:629–52.

McGuire, Michael. 2006. Intergovernmental man-

agement: A view from the bottom. Public Admin-

istration Review 66:677–79.

Fowler 13

Menard, S. 2002. Applied logistic regression analy-

sis, 2nd ed. Thousand Oaks, CA: Sage.

National Association of Clean Air Agencies. 2017.

Find a state or local agency. http://www.4clea

nair.org/agencies (accessed February 1, 2017).

O’Toole, Laurence J., and Robert K. Christensen.

2012. American intergovernmental relations:

Foundations, perspectives, and issues, 5th ed.

Thousand Oaks, CA: CQ Press.

Potoski, Matthew, and Neal D. Woods. 2002.

Dimensions of state environmental polices: Air

pollution regulation in the United States. Policy

Studies Journal 30:208–27.

Provan, Keith G., and Robin H. Lemaire. 2012. Core

concepts and key ideas for understanding public

sector organizational networks: Using research

to inform scholarship and practice. Public

Administration Review 72:638–48.

Reed, Douglas S. 2014. Building the federal school-

house. New York: Oxford University Press.

Ringquist, Evan J. 1993a. Does regulation matter?

Evaluating the effects of state air pollution con-

trol programs. Journal of Politics 55:1022–45.

Ringquist, Evan J. 1993b. Environmental protection

at the state level. Armonk, NY: M. E. Sharpe.

Scicchitano, Michael J., and David M. Hedge. 1993.

From coercion to partnership in federal partial

preemption: SMCRA, RCRA, and OSH Act.

Publius 23:107–121.

U.S. Environmental Protection Agency. 2017a. Air

Data. http://www3.epa.gov/airdata/ (accessed

February 1, 2017).

U.S. Environmental Protection Agency. 2017b. Air

Quality Index (AQI) basics. http://airnow.gov/

index.cfm?action¼aqibasics.aqi (accessed Feb- ruary 1, 2017).

Waterman, Richard W., and Kenneth J. Meier. 1998.

Principal-agent models: An expansion? Journal

of Public Administration Research & Theory 8:

173–202.

Wood, B. Dan. 1992. Modeling federal implementa-

tion as a system: The clean air case. American

Journal of Political Science 36:40–67.

Woods, Neal D., and Matthew Potoski. 2010. Envi-

ronmental federalism revisited: Second-order

devolution in air quality regulation. Review of

Policy Research 27:721–39.

Wright, Deil. 1988. Understanding Intergovernmen-

tal Relations, 3rd ed. Belmont, CA: Wadsworth.

Author Biography

Luke Fowler is an assistant professor and director of

the Masters of Public Administration program in the

School of Public Service at Boise State University.

His research interests include environmental and

energy policy; state and local government; public

budgeting and finance; and administrative and policy

theory. His related work has been published in State

& Local Government Review, American Review of

Public Administration, Environmental Politics, and

Journal of Environmental Assessment Policy and

Management.

14 State and Local Government Review 50(1)