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
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collaborative management of complex policy
problems. In 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, ed pro-
bit models analyze effects of IGM models on
perceptions, with coefficients reported. Diag-
nostic tests indicated no assumptions of ed
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 ed 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.
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