J. OF PUBLIC BUDGETING, ACCOUNTING & FINANCIAL MANAGEMENT, 26 (3), 494-526
FALL 2014
SMART CUTS?: STRATEGIC PLANNING, PERFORMANCE
MANAGEMENT AND BUDGET CUTTING IN U.S. CITIES
DURING THE GREAT RECESSION
Benedict S. Jimenez*
ABSTRACT. Periods of fiscal decline present an opportunity for city officials to
transform their local government into a leaner and more effective
organization by targeting cuts to non-essential programs and services.
However, the political nature of the fiscal retrenchment process means that
such opportunity is often squandered. Could the application of strategic
planning and performance management in cutback management lead to a
more focused and targeted budget cutting? Advocates of rational
management believe that information gathering, analysis and use in
decision-making can help local governments adapt to a fiscal crisis by
facilitating targeted cuts in expenditures that preserve administrative
capacity, and avoiding across-the-board cuts that trim both the
organization’s muscle and fat. The results of this research show that rational
analytic techniques do matter in budget cutting.
INTRODUCTION
Cities face a two-fold challenge in navigating the Great Recession.
In the short-term, city governments must shrink by matching their
service responsibilities with declining resources. In doing so however,
cities must ensure that they have the administrative capacity to
function effectively in the long term (Behn, 1980; Levine, 1985;
Levine, Rubin & Wolohojian, 1981). The first task involves
--------------------------------------* Benedict S. Jimenez, PhD, is an Assistant Professor, Department of
Political Science, Northeastern University. His research examines how subnational governments finance, manage and provide local public goods.
Copyright © 2014 by PrAcademics Press
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
495 immediately cutting controllable expenditures. The second requires
implementing cuts strategically, without regard for the distribution of
losses (Levine, 1978, 1985).
The allocation of cuts inevitably “involves the tradeoff between
equity and efficiency” (Levine, 1978, p. 320). Equity means
distributing the pain across the organization by cutting across the
board, regardless of whether both the fat and meat are trimmed.
Efficiency requires cutting strategically or targeting cuts to
departments, programs or services that are not central to the
achievement of the organization’s mission and capacity to maintain
or improve performance in the future (Levine, 1978, 1979, 1985;
Behn 1980).
Prioritizing equity over efficiency by implementing across-theboard cuts is generally viewed negatively in the literature, and
considered a symptom of decision paralysis (Levine, 1985). An
immediate result of such cuts is a deterioration in service quality as,
for example, when a smaller staff is expected to meet unchanged if
not increasing demand for services (Levine, Rubin & Wolohojian,
1981). Levine (1978) notes that even-percentage-cuts produce
different effects on government units. Those with sufficient slack
resources can easily absorb cuts, while other smaller and specialized
units become immobilized with the elimination of just “one or two
positions” (Levine, 1978, p. 322). Behn (1980, p. 619) offers a
similar argument noting that equal cuts assume that “each
component contributes equally to the organization’s overall purpose”,
and can thus cripple both priority and non-priority programs. In the
long-term, these problems accumulate, creating a government that is
weaker and less capable of responding to citizens’ needs and
demands (Levine, 1985; Behn, 1980).
The preference for across-the-board cuts has been explained in
terms of the need to minimize political conflict during the fiscal
retrenchment process. Such cuts promote a sense of fairness and
equity among budgetary claimants, minimizing conflict in the
retrenchment process (Wildavsky, 1988; Behn, 1980; Levine, 1978;
Wolman & Davis, 1980). Targeting cuts, thus, requires political will –
a willingness to inflict pain on specific groups when necessary.
Beyond expenditure of political capital, targeting cuts also requires
analytical and planning capacity (Levine, Rubin & Wolohojian, 1981;
Behn, 1980; Levine, 1978, 1985). The organization must know what
496
JIMENEZ its priorities and needs are, as well as the weak links in its production
processes. Additionally, the capacity to gather and analyze feedback
information is also crucial to gauge the effectiveness of cuts.
The comprehensive case studies of fiscal retrenchment in the
1980s focused on the politics of retrenchment specifically the
reaction of interest groups and decisions of elected officials (see
Levine, Rubin & Wolohojian, 1981; Clark & Ferguson, 1983), and only
briefly touched on the management requirements for successfully
implementing cutbacks. Much has changed since that period. Many
local governments have adopted rational management techniques to
improve decision-making in the public sector through collection and
analysis of information, and the implementation of multi-year
planning (see surveys by Melkers & Willoughby, 2005; Poister &
Streib, 2005). This research examines the contributions of strategic
planning and performance management in the fiscal retrenchment
process. Specifically, have these management techniques enabled
cities to focus on creating a leaner but better-run organization by
implementing targeted budget cuts?
LITERATURE ON CUTBACK MANAGEMENT
Fiscal retrenchment “involves turning the organization into one
that is smaller, doing less, consuming fewer resources, but still doing
something and doing it well” (Behn, 1980). It is similar to cutback
management which is “organizational change towards lower levels of
resource consumption and organizational activity” (Levine, 1979, p.
182), although cutback management is a response, not only to
economic or fiscal deterioration, but also to political or policy-related
decline (Levine, 1978). Research on fiscal retrenchment and cutback
management in local governments gained momentum in the 1980s
with the now classic works of Levine (1978, 1979, 1985), Wolman
and Davis (1980), Schick (1980), Behn (1980), Levine, Rubin and
Wolohojian (1981), Clark and Ferguson (1983) and Downs and Rocke
(1984), among others. Research on the topic appeared sporadically
in the next two decades (see Morgan & Pammer, 1988; Schick,
1988; Lewis, 1988; Pammer, 1990; Bartle, 1996; Maher & Deller,
2007), but interest has increased in recent years as scholars and
policymakers ponder the consequences of the Great Recession on
the fiscal health of local governments across the country (see
Hendrick, 2011; Jimenez, 2012).
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
497 A number of major inter-related themes have emerged from the
literature on fiscal retrenchment. One theme focused on whether the
retrenchment process was systematic or unstructured. Those arguing
that the process was structured pointed to the importance of the level
of fiscal stress in determining the administrative responses of local
governments, with delaying tactics implemented in the early stages of
decline, and cutting and smoothing responses (which include highly
disruptive and conflictive strategies) adopted when the fiscal
hemorrhage is severe and prolonged (Levine, Rubin & Wolohojian,
1981; see also Wolman and Davis [1980]; for a more recent
treatment, see Hendrick [2011]).
A different group of studies pointed out that how cities coped with
fiscal stress was unpredictable. Morgan and Pammer (1988),
Pammer (1990) and Bartle (1996) argued that cities followed a
garbage can process of decision-making in which the choice of fiscal
retrenchment strategies was largely determined by chance. More
recently, Maher and Deller’s (2007) empirical analysis did not find
any consistent explanation for how municipal governments
responded to fiscal stress.
Another theme is the role of politics in the retrenchment process
and focuses, among others, on the question of how cuts are
implemented. Schick (1988, p. 524) introduced the term
decrementalism which is incrementalism in reverse: In good times,
“incremental budgeting searches for opportunities to expand
programs”, but in bad times “the decremental variant searches for
opportunities to contract them.” Decremental strategies include
cutting across the board to minimize political conflict among budget
claimants (Schick, 1978; Levine, 1985).
Others contend that groups with considerable political influence,
such as firefighters and police officers, are protected from cuts
(Bartle, 1996; Lewis, 1988). However, Downs and Rocke’s (1984, p.
343) analysis of two cities arrives at a different conclusion,
specifically that budget cutting was not done across-the-board, nor
did police and fire protection services remain sacrosanct and
protected from cuts. There is general agreement in the literature
however, that across-the-board cut is an initial response to fiscal
difficulties, while prolonged fiscal decline forces local governments to
implement selective or targeted cuts (see Wolman & Davis, 1980;
Levine, Rubin & Wolohojian, 1981).
498
JIMENEZ Yet another theme is the importance of government
professionalization and rational management approaches. Levine,
Rubin and Wolohojian (1981) argued that reformed city governments
were more capable of implementing an orderly retrenchment process.
Other scholars point to specific management practices such as
strategic planning. Behn (1980, p. 617) made a case for a corporate
strategy, while Levine advocated (1985) for a strategic management
perspective. Both concepts refer to the need for organizations to
clarify their mission, prioritize services, and match resources with
critical responsibilities. Levine, Rubin and Wolohojian (1981, p. 210)
pointed to the importance of a “multiyear strategy for targeting cuts
and smoothing out impacts [so that] a locality can retain its long-term
administrative capacity and capital plant even if its short-run
existence is dismal”. Others were skeptical of the ability of
organizations to sustain rational management approaches during
periods of severe scarcity (see Schick, 1980). Most of these works
were theoretical or case study-based, and large-n empirical evidence
to date is thin.
This study builds on the previous research on fiscal retrenchment
and cutback management, and uses a large sample of city
governments to examine if rational management approaches, such
as strategic planning and performance management, increase the
probability that city governments will adopt targeted cuts to
expenditures. It also connects the different themes in the fiscal
retrenchment literature by assessing whether fiscal condition,
interest group politics, and government professionalization mediate
the relationship between rational management and budget cutting.
THEORETICAL EXPECTATIONS:
RATIONAL MANAGEMENT AND BUDGET CUTTING
Effects of Strategic Planning and Performance Management
Strategic planning represents a “disciplined effort to produce
fundamental decisions and actions that shape and guide what an
organization (or other entity) is, what it does, and why it does it”
(Bryson, 2004, p. 6). Strategic planning involves scanning
environmental threats and opportunities, analyzing organizational
strengths and weaknesses, clarifying organizational vision and
mission, translating general goals to specific objectives, and
developing strategies and action plans to match internal capabilities
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
499 with external threats and opportunities (Poister & Streib, 2005;
Bryson, 2004; Hendrick, 2003; Berry & Wechsler, 1995).
Performance management, on the other hand involves the regular
collection of information regarding various aspects of organizational
performance, and the use of such information in organizational
decision-making (Moynihan, 2008; Poister, 2010) and in reporting to
citizens (Halachmi & Holzer, 2010).
Scholars have emphasized the interdependence between
strategic planning and performance management (Hendrick, 2003;
Poister & Streib, 2005; Poister, 2010; Bryson, Berry, & Yang, 2010).
Strategic planning is “forward looking” and aims to shape the future
of an organization while performance management is “backward
looking” as it aims to influence organizational decision-making by
examining past results (Rubin & Willoughby, 2011, p. 21). Hildreth
(2000, p. 68) defines the linkage between the two processes:
“Performance is the contextual antecedent: It triggers changes in
strategic momentum”. Others have argued for a comprehensive
management process linking planning, measurement, budgeting and
operations, pointing out that this approach produces better outcomes
for public organizations (Steiss, 1985; Hendrick, 2003; Poister &
Streib, 2005; Moynihan, 2008; Poister, Pitts & Edwards, 2010).
Strategic planning and performance management are rational
approaches to organizational decision-making.1 Rational analytical
techniques matter for organizations’ capacity to target cuts. As Levine
(1978, p. 320) argued, “efficiency cuts involve costly triage analysis
because the distribution of pain and inconvenience requires that the
values of people and subunits to the organization have to be weighed
in terms of their expected future contributions.”
Specifically, a planning process would enable cities to clarify their
mission and goals and prioritize among services (Berry & Wechsler,
1995; Poister & Streib, 2005). Environmental scanning allows
organizations to anticipate environmental shocks and prepare
accordingly (Bryson, 2004; Hendrick, 2003). Behn (1980, p. 615)
argued that “[p]reparing for cutback management requires analysis:
uncovering, recognizing and understanding the fundamental shifts in
demographic patterns, economic behavior, social attitudes, or
political power that will, sometime in the future, force retrenchment”.
External assessment allows city governments to gather input from
external stakeholders about possible ways to prepare for changes in
500
JIMENEZ the environment that may affect the organization. For example, by
involving citizens and other stakeholders in the process, local
governments can identify which services are more important to the
local community (Miller & Svara, 2009). Assessment of the internal
environment permits decision-makers to examine which services the
local government can produce cost-effectively, and may lead to a
decision to terminate costly services, or experiment with alternative
production processes (Levine, 1985; Bryson, 2004). Linking plans to
budget and operations enables organizations to channel resources to
the organization’s core service responsibilities (Boyne & GouldWilliams, 2003; Berry & Wechsler, 1995). As Levine (1985, p. 691)
argued, the reexamination required by strategic planning “may call for
a significant reallocation and reconfiguration of resources and work
force activity”.
Performance management supports strategic planning. It is
through the performance measurement system that organizations
gather and analyze information that is used in the planning process
(Bryson, 2004). Levine, Rubin and Wolohojian (1981, p. 212), for
example, emphasized the need for feedback information, arguing that
“[s]low and vague feedback, therefore, can leave a government or
agency groping around in a cost-cutting program without any clear
idea about its effectiveness or what options are likely to succeed or
fail if further retrenchment is necessary.” LeRoux and Wright (2010)
found, at least in the case of non-profit organizations, that use of
performance data improved strategic decision-making.
Beyond planning, use of performance information in budgeting
can help organizations allocate resources on the basis of program
effectiveness and efficiency (see Gilmour & Lewis, 2006; Moynihan
2008).2 Reporting government performance to citizens may also help
generate support among citizens about the need to cut ineffective or
non-essential services. Finally, performance information use in
personnel management can help city governments identify instances
of overstaffing and can lead to decisions to target cuts in personnel
(see Ammons & Rivenbark, 2008). It is hypothesized that:
H1a-H1b: Strategic planning (performance management) is associated
with a higher probability of adopting targeted cuts to
expenditures.
The review of related literature showed that the effect of planning
and performance management on the decision to implement targeted
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
501 cuts to expenditures is likely to be contingent on a number of factors
including the level of fiscal decline, presence of interest groups, and
government professionalization. These possible interaction effects
are explored below.
Conditioning Effects of Fiscal Decline
Schick (1981) argued that the level of scarcity as determined by
the presence/absence of slack budgetary resources affects the
quality of the planning and budgeting practices in organizations.
Planning and program evaluation deteriorate as organizations
transition from periods of chronic scarcity through acute scarcity, until
unrealistic planning and repetitive budgeting become the norm in
total scarcity. Empirical studies have provided support for Schick’s
(1981) argument. In the case of strategic planning, research has
shown that slack resources are important for adoption of planning
practices (Berry, 1994), the quality of planning documents (Boyne,
Gould-Williams, Law, & Walker. 2004), and the effectiveness of the
planning process itself (Wheeland, 1993). Planning requires
additional staff, time, and technology (Berry, 1994; Boyne et al.
2004), and without sufficient slack resources, the capacity of the
organization to search for and analyze information will be
constrained. Similarly, studies have also found that performance
management tends to be underemphasized or deteriorate in periods
of acute fiscal distress (see Hou, Lunsford, Sides, & Jones, 2011). It
is expected that fiscal condition mediates the relationship between
rational management approaches and budget cutting strategies.
Specifically:
H2a-H2b: Strategic planning (performance management) is associated
with a higher probability of adopting targeted cuts to expenditures
in moderate fiscal stress, but this probability decreases under
very severe fiscal stress.
Conditioning Effects of Interest Groups
Periods of accelerated revenue decline activate different interest
groups within and outside of government (Levine, Rubin &
Wolohojian, 1981; Clark & Ferguson, 1983). Public sector unions,
service recipients, ethnic groups, business and neighborhood groups
resist strategies that target cuts to expenditures and services
benefiting their members. Behn (1980, p. 619) argued that a
502
JIMENEZ decision-maker must take into account the “potential for political
destruction possessed by those who they mark for the most severe
cutbacks”. Not surprisingly, Wolman and Davis (1980, p. 244)
concluded, “to the maximum extent possible, conflict avoidance is
likely to characterize 1ocal official expenditure cutback behavior”.
This implies that rational management approaches would be
underemphasized when a city government is faced with numerous
interest groups, and political expediency, specifically the need to
minimize conflict, would dictate the approach to budget cutting. It is
expected that there is an interactive effect between the presence of
interest groups and rational management approaches. Specifically:
H3a-H3b: Strategic planning (performance management) is associated
with a higher probability of adopting targeted cuts to expenditures
when potential interest group influence is weak, but this
probability decreases when interest group influence intensifies.
Conditioning Effects of Government Professionalization
Professional government matters in budget cutting because it
implies managerial capacity to effectively implement fiscal
retrenchment. Studies have concluded that reformed governments
are more likely to support rational decision-making approaches
(Poister & Streib, 1989). According to Hendrick (2011), more
professional governments are exposed to accepted standards and
best practices in financial management. These standards and
practices function as decision aids during budget cutting, serving as
“anchors to guide development or search for solutions to financial
problems” (Hendrick, 2011, p. 62).
Professional government also implies sufficient political insulation
to implement high-conflict retrenchment strategies. Less professional
governments tend to emphasize a political process of decisionmaking (Hendrick, 2011). Levine, Rubin and Wolohojian (1981, p.
215) suggested that “jurisdictions with strong elected executives…
are likely to be more open to ethnic, neighborhood and other
pressure groups and have no history of sound budgeting”. Such
openness may make it difficult for cities to impose targeted cuts
because of the concern for imposing losses on political supporters
and organized interest groups. In other words, while rational
management provides the analytical basis for targeting cuts, the
political will to execute such cuts is simply not there. It is expected
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
503 that the relationship between rational management approaches and
the cutting strategy is contingent on the level of government
professionalization. Specifically:
H4a-H4b: Strategic planning (performance management) is associated
with a higher probability of adopting targeted cuts to expenditures
in more professional governments, but this probability is lower in
less professional governments.
MODEL, MEASURES AND DATA SOURCE
Outcome and Main Independent Variables
The outcome and main independent variables are constructed
using results of the International City/County Manager Association’s
(ICMA) 2009 State of the Profession survey which targeted city-like
and county governments and had a response rate of 26%.3
Respondents included city and county managers and chief
administrative officers. This research uses the data for 1921 city-like
governments (municipal and township governments). Other data
sources include the 2002 and 2007 Census of Governments, the
2000 decennial census, and the 2005-2009 American Community
Survey.
The outcome variable—implementation of targeted cuts—is
measured using a dummy variable with “1” indicating that cuts were
targeted, and “0” otherwise. The 2009 ICMA survey showed that 884
(or 46% of 1921 cities with usable answers) reported implementing
targeted cuts in expenditures. The ICMA survey also examined
strategic planning and performance management practices in city
governments. The survey showed that 1120 (or 63% of 1778 cities
with usable answers) indicated that they had a strategic or long range
plan, of which 74% reported that plans were linked to budgets,
whereas 72% reported that plans guided operations. Among cities
with strategic plans, 47% reported revising their plans in response to
the 2007 economic recession, of which 48% allowed internal
stakeholders such as elected officials and employees to participate in
the revision, and 23% involved external stakeholders such as private
businesses, the local chamber of commerce, and organized and
unorganized citizens. Some 749 (or 45% of 1164 cities with usable
answers) reported that they engaged in performance measurement
activities. Of these cities, 80% reported that they used performance
504
JIMENEZ information in the budgeting process, 52% in reporting to citizens,
57% in evaluating employees, and 51% in strategic planning.
The survey items were reduced using factor analysis. Because the
specific strategic planning and performance management practices
were operationalized as dichotomous measures (“1” indicating yes,
and “0” otherwise), the factor analysis was run on the matrix of
tetrachoric correlations instead of Pearson correlations to avoid
producing spurious factors. Dichotomous variables are likely to have
similar distributions and will load into the same factor regardless of
whether they tap into the latent concept represented by the factor.
Tetrachoric correlations address this issue by assuming that the
dichotomous variables are proxies for unobserved, continuous, and
normally distributed variables (Panter, Swygert, Dahlstrom, & Tanaka,
1997).
Table 1 shows the results of the tetrachoric factor analysis with
varimax rotation. Two factors have Eigenvalues greater than 1, and
explain 85% of the variation in the items. Two indices representing
comprehensive strategic planning and comprehensive performance
management are constructed using the factor scores. The Cronbach’s
alpha is .81 for the strategic planning index, and .87 for the
performance management index, suggesting that the items
comprising each index have relatively high internal consistency.
To test hypotheses 2-4, the strategic planning and performance
management indices are interacted with measures of government
fiscal condition, government professionalization, and interest group
influence. Perception-based and objective measures of fiscal
condition are used based on Schick’s (1980, p. 114) argument that
conditions of scarcity “are defined as much by the aspirations and
perspectives of budget makers as by the objective condition of the
budget.” The first measure is based on the ICMA survey item: “How
does the anticipated shortfall compare to cuts made in the FY 2009
budget?” Responses ranged from “Less”, “Same” or “Greater”. The
second measure is the change in the ratio of operational
expenditures to own-source revenues from 2002 to 2007, with higher
values indicating that expenditures have been growing faster than
revenues.
Proxies for interest group influence include percentage of workers
employed in local public administration and an ethnic fragmentation
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
505 TABLE 1
Undertake performance measurement activities
Used performance information in reporting to
citizens
Used performance information in personnel
management
Used performance information in budgeting
Used performance information in planning
Has strategic plan
Revised plan in response to 2007 economic
recession
Involved internal stakeholders in planning
Involved external stakeholders in planning
Linked plan to budget
Linked plan to operations
Eigenvalues
Variance explained (cumulative)
Factor 2
Comprehensive
Performance
Management
Survey Items
Factor 1
Comprehensive
Strategic
Planning
Factor Loadings
0.11
0.99
0.15
0.89
0.02
0.84
0.18
0.38
0.98
0.94
0.84
0.16
0.96
0.11
0.96
0.87
0.84
0.82
6.44
0.39
0.13
0.05
0.29
0.29
3.02
0.86
index. Public employees are likely to resist targeted cutting that may
lead to layoffs or reductions in salaries and benefits. Different ethnic
groups demand particularistic goods (Alesina, Baquir & Easterley,
1999), and city officials are forced to adopt even-percentage-cuts to
reduce conflict among these groups and minimize loss of political
support.
An indicator variable for mayor-council form is included to
measure government professionalization. However, studies have
shown that there has been some cross-fertilization between mayorcouncil and council-manager cities, such as the appointment of a
professional chief administrative officer (CAO) to assist the mayor in
politicized jurisdictions (Frederickson, Johnson & Wood, 2004). To
address this issue, a manager empowerment index is constructed
using responses to the ICMA survey question regarding the extent of
506
JIMENEZ responsibility of city managers or CAOs over budget, policy and
personnel management. Another proxy measure is percentage
employed in professional or management positions. Hendrick (2006)
argued that this variable measures voters’ preference for a more
efficient, responsive and professional local governance.
Other Control Variables
Following the socio-economic decline model, certain community
characteristics influence the fiscal retrenchment strategy adopted by
city officials (Pammer, 1990; Maher & Deller, 2007). Cities with
higher median income might be able to avoid resorting to targeted
cuts in expenditure, while central cities, which have a more
dependent population (Ladd & Yinger, 1989), might have limited
choice and resort to dramatic service cuts.
Increase in population indicates an improving local economy,
enabling the city government to resort to delaying strategies. Another
measure of local economic condition is based on the ICMA survey
question: “To what extent is your local government affected by the
financial crisis in the U.S. economy?” Responses ranged from “Not at
all’ to “Severely”.
The models include measures of city government size and
revenue sources. In general, bigger governments – those with bigger
population, offer more services and have higher per capita
expenditures –have more slack resources (Hendrick, 2006). Such
cities have more leeway to implement across-the-board cuts in
response to fiscal decline. Alternatively, a bigger government can
exacerbate fiscal decline given higher costs for employee salaries,
benefits, and even pensions (see Neiman & Krimm, 2009), forcing
cities to implement drastic targeted expenditure cuts. Finally, cities
that are dependent on grants requiring local matching might be less
willing to adopt across-the-board cuts as such cuts affect all services
including grant-funded ones, leading to loss of federal or state
revenues (Wolman and Davis, 1980). Appendix Table A shows the
variable definitions, expected effects on the dependent variable, data
sources and basic descriptive statistics.
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
507 RESULTS
Because the outcome variable is binary, logistic regression is
used to estimate the models. The models are run with and without
state dummies. A state dummy is a dichotomous variable indicating
that a specific city is located in a particular state (e.g. “1” indicating
that a city is located in Ohio, and “0” otherwise). State dummies
control for state-specific effects or factors at the state level that
cannot be readily observed but can affect how cities undertake
budgeting cutting. Examples of such state-specific effects include
state fiscal institutions (e.g. balanced budget rules and tax and
expenditure limits), historical factors (e.g. whether cities traditionally
enjoy home rule powers), and even cultural factors (e.g. conservative
versus liberal political cultures).
All models employ Huber-White sandwich estimators that produce
heteroskedasticity-robust standard errors. To avoid multi-collinearity,
variables in the interaction terms are mean-centered. The correlation
matrix for independent variables (see Appendix Table B) shows that
the control variables are largely distinct, with the exception of
household income and percentage employed in professional and
management positions which are moderately correlated. Exclusion of
one of these variables did not affect the results.
Results for Strategic Planning and Performance Management
Tables 2 and 3 show the results of the logistic regressions.
Models 1 and 2 in table 2 are the base models for targeted cuts
(there are no interaction terms). Only model 2 has state dummies. In
both models, strategic planning is highly significant and positively
associated with higher probability of adopting targeted cuts,
corroborating hypothesis 1a. The coefficient for performance
management is also positive but fails to reach conventional levels of
statistical significance, providing limited evidence for hypothesis 1b.
Because logit coefficients have no straightforward interpretation,
predicted probabilities are calculated using the final results in model
2 to better understand the relationships among the variables of
interest.4 Model 2 was chosen because the state dummies ensure
that unobserved factors that influence the variation in the outcome
variable are controlled for. Probabilities are calculated at the lowest
and highest values of the variable of interest, holding constant the
effects of other controls. Table 4 shows the predicted probabilities for
508
JIMENEZ significant variables only. Cities with comprehensive strategic
planning have a 14-percentage-point-higher probability of targeting
cuts compared with cities that have the least comprehensive
planning process. Specifically, comprehensive planning is associated
with a 64%-probability of implementing targeted cuts, whereas least
comprehensive planning process is associated with a 49%-probability
of selective cutting.
TABLE 2
Basic Logistic Regressions
(Dependent Variable: Targeted Cuts)
Model 1
Model 2
Coef.
(S.E).
Coef.
(S.E.)
Strategic planning (SP) index
0.511*** 0.164 0.454*** 0.172
Performance management (PM) index
0.170 0.153 0.227 0.164
Mayor-Council form
-0.522*** 0.159 -0.609*** 0.185
Manager empowerment index
0.283 0.222 0.323 0.246
% employed in professional/
0.034 0.021 0.027 0.024
management position
2002-07 change in spending/revenue
0.081 0.477 -0.090 0.508
ratio
Budget shortfall
0.260*** 0.105 0.267** 0.114
% employed in public administration
-0.039* 0.020 -0.029 0.022
Ethnic fragmentation
-0.684 0.416 -0.602 0.523
Spending per capita (2007) log
0.398*** 0.211 0.490** 0.246
2009 population (log)
0.219** 0.086 0.180* 0.095
Service index
0.060** 0.026 0.062** 0.028
Median household income
0.000 0.000 0.000 0.000
2000-09 population change (log)
0.806 0.735 0.828 0.809
Financial crisis severity
0.391*** 0.088 0.442*** 0.097
Central city
-0.014 0.278 0.139 0.304
Dependence on IGR (2007) (log)
0.101 0.071 0.127 0.102
State dummies
No
Yes
Number of obs
1052
1039
Wald chi sq. / Prob > chi sq
127.650
173.130 / 0.000
Pseudo R sq
0.106
0.150
Note: *** significant at 1%, ** at 5%, * at 10%; two-tailed tests. All models
use heteroskedasticity-robust standard errors (S.E.). The base state in
all models is Colorado. Natural logs of some variables are used because
of the long tails in their distribution.
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
509 Results for Control Variables
As for the control variables, the results are similar in both models
1 and 2 with the exception of percentage employed in local public
administration which is no longer statistically significant once state
effects are controlled for. The negative sign for this variable is as
expected, and means that cities with a bigger local public sector
employment have a lower probability of implementing selective cuts.
Mayor-council governments are also less likely to implement targeted
cuts, providing support to Levine, Rubin and Wolohojian’s (1981)
observation more than three decades ago. Bigger governments as
measured by higher number of services, per capita expenditures and
population size, and cities severely affected by the 2007 financial
crisis and have higher budget deficits in 2010 compared to 2009, are
likely to target cuts in expenditures.
Examining the predicted probabilities for model 2, councilmanager cities have a 14-percentage point-higher probability of
targeting cuts compared with mayor-council cities. Government size
exerts a considerable influence on the probability of selective cutting.
Cities that offer the most number of services are 28-percentage
points more likely to target cuts compared with cities that offer the
least number of services. The highest spending city also targets cuts
more – approximately 23-percentage point-higher likelihood –
compared with the thriftiest city. In terms of population size, the
biggest jurisdiction is more likely to cut selectively by 13 points
compared with the smallest city. Finally, cities reporting that the
recession severely affected them are 13-percentage points more
likely to adopt targeted cuts compared with cities least affected by
the 2007 financial crisis.
The positive and statistically significant effect of budget shortfall
lends support to the observation in the literature that targeted cuts
are implemented when fiscal condition deteriorates further.
Specifically, cities reporting higher deficits in 2010 have a 59%
probability of targeting cuts compared with only 46% for cities with
less severe deficits. This is an important finding because it addresses
concerns that selective cuts reported by cities in the ICMA survey
could have focused on less politically contentious expenditure items
such as infrastructure maintenance. Although such cuts are viewed
negatively in the literature because they eventually lead to the
deterioration of the quality of public fixed assets (Jimenez & Pagano,
510
JIMENEZ 2012), research has shown that targeting cuts to less politically
visible items is a delaying strategy and is employed only in the initial
stages of a fiscal stress (Hendrick, 2011). That targeted cutting is
occurring in more severe fiscal stress suggests that local
governments are being forced to make the hard decisions, that is,
cutting more politically visible items including services and personnel
(see Wolman & Davis, 1980; Hendrick, 2011).
Results for Interaction Terms
Models 3 and 4 in Table 3 show the results for the interaction
terms. Only model 4 has state dummies. The relationship between
planning and targeted cuts remains positive and statistically
significant. However, none of the interaction terms for planning and
measures of government professionalization and fiscal condition are
significant. Additionally, when measures of planning and performance
management and interest group influence are interacted, no
systematic relationships are observed. It is possible that the proxy
measures did not adequately capture the degree of interest group
influence. Future research will need to develop and use more direct
measures of interest group involvement in fiscal retrenchment.5
These results do not provide evidence for hypotheses 2a, 3a 4a, and
4b.
Models 3 and 4 also show that the effects of performance
management are largely random. However, there are interesting
results for the interaction terms. In both models, the interaction term
for performance management and budget shortfall is marginally
significant and the sign of the coefficient is positive. This means that
in cities with worsening budget deficits, performance management is
associated with higher probability of implementing targeted cuts
which is contrary to hypothesis 2b.
The interaction term for performance management and mayorcouncil form is positive and weakly significant in models 3 and 4. A
comprehensive performance management system is associated with
increased likelihood of implementing selective cuts in mayor-council
cities compared to council-manager cities, which is contrary to
hypothesis 3b.
Predicted probabilities for the interaction terms are calculated
using the final results in model 4 which has state dummies. To
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
511 interpret the results for significant interaction terms, the value of the
conditioning variable is changed, that is, probabilities for the outcome
variable are calculated at the minimum and maximum values of the
conditioning variable. For example, the probability of targeting cuts for
cities with comprehensive performance management is calculated
when the budget deficit is severe, and when the deficit becomes
smaller.1
TABLE 3
Logistic Regressions with Interaction Terms
(Dependent Variable: Targeted Cuts)
Strategic planning (SP) index
Performance management (PM) index
Mayor-Council form
Manager empowerment index
% employed in professional/
management position
SP*Manager
SP*Professional/management
SP*Mayor-Council
PM*Manager empowerment
PM*Professional
PM*Mayor-Council
2002-07 change in spending/revenue
ratio
Budget shortfall
SP*Budget shortfall
SP*Spending/revenue ratio
PM*Budget shortfall
PM*Spending/revenue ratio
% employed in public administration
Ethnic fragmentation
SP*Public administration
SP*Ethnic fragmentation
PM*Public administration
PM*Ethnic fragmentation
Spending per capita (2007) log
2009 population (log)
Service index
Median household income
Model 3
Model 4
Coef.
(S.E.)
Coef.
(S.E.)
0.490** 0.205 0.421* 0.219
0.020 0.191 0.035 0.201
-0.485*** 0.164 -0.552*** 0.189
0.275 0.228 0.290 0.249
0.030
0.021
0.026
0.024
-0.155
-0.038
0.164
0.341
-0.017
0.648*
0.568
0.037
0.390
0.488
0.034
0.345
-0.286
-0.031
0.186
0.373
-0.025
0.664*
0.608
0.040
0.425
0.506
0.036
0.372
0.163
0.518
-0.088
0.558
0.253**
0.013
-0.389
0.408*
1.116
-0.044**
-0.636
0.068
-0.150
0.051
-0.053
0.389*
0.243
0.052*
0.000
0.106 0.258** 0.115
0.247 0.057 0.270
1.204 -0.840 1.268
0.218 0.403* 0.235
1.041 1.130 1.087
0.021 -0.033 0.023
0.425 -0.560 0.529
0.052 0.039 0.053
0.906 0.002 0.948
0.044 0.018 0.046
0.827 -0.139 0.865
0.212 0.474* 0.248
0.088 0.206** 0.096
0.027 0.055* 0.029
0.000 0.000 0.000
512
JIMENEZ TABLE 3 (Continued)
2000-09 population change (log)
Financial crisis severity
Central city
Dependence on IGR (2007) (log)
State dummies
Number of obs.
Wald chi sq. / Prob > chi sq.
Pseudo R sq
Model 3
Model 4
Coef.
(S.E.)
Coef.
(S.E.)
0.848 0.740 0.868 0.814
0.393*** 0.090 0.449*** 0.099
0.005 0.275 0.159 0.302
0.092 0.072 0.120 0.106
No
Yes
1052
1039
134.370 / 0.000 180.100 / 0.000
0.115
0.157
Note: *** significant at 1%, ** at 5%, * at 10%; two-tailed tests. All models
use heteroskedasticity-robust standard errors (S.E.). The base state in
all models is Colorado. Natural logs of some variables are used because
of the long tails in their distribution.
Table 4 shows that comprehensive performance management in
cities with more severe deficits in 2010 (in comparison to 2009) is
associated with an 88%-greater likelihood of targeting cuts,
compared to 78% in cities reporting smaller budget shortfalls in
2010, or a 10-percentage point-difference. In terms of the
conditioning effects of government form, Table 4 shows that
comprehensive performance management in mayor-council cities is
associated with a 79% probability of selective cutting, compared to
67% in council-manager cities, or a difference of approximately 12
percentage points.
DISCUSSION
That comprehensive strategic planning is important for local
governments’ capacity to target cuts is certainly good news for cities
that have invested in building their capacities to undertake planning.
There is a rich literature debating the merits of strategic planning with
some arguing that planning improves various aspects of
organizational performance (see, for example, Bryson, 2004:
Hendrick, 2003; Poster & Streib, 2005; Boyne, 2001), and others
pointing to the difficulties of undertaking planning in the public sector
(see among others, Rabin, Miller & Hildreth, 2000). The result here
provides strong empirical support to those advocating for strategic
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
513 TABLE 4
Predicted Probabilities of Implementing Targeted Cuts
Model 2
Model 4
Std.
Prob.
Err.
-----------
Variables
Prob.
Std. Err.
Least comprehensive
Most comprehensive
Difference
Council-manager
Government form
Mayor-council
Difference
2010 deficit less than
2009's
Budget shortfall
2010 deficit greater
than 2009's
Difference
Minimum expenditure
Spending per capita Maximum expenditure
Difference
Minimum population
Population size
Maximum population
Difference
Offers minimum number
of services
Service index
Offers maximum number
of services
Difference
Not at all
Financial crisis
Severely
severity
Difference
Council-Manager
Results for most
comprehensive PM Mayor-Council
when varying
Difference
government form
2010 deficit less than
Results for most
2009's
comprehensive PM
2010 deficit greater
when varying value
than 2009's
of budget shortfall
Difference
0.49
0.64
0.14
0.68
0.54
-0.14
0.03
0.04
0.46
0.04
--
--
0.59
0.02
--
--
Strategic planning
0.13
0.62
0.85
0.23
0.80
0.93
0.13
0.04
0.05
0.09
0.07
0.09
0.06
--------
----
0.42
0.09
--
--
0.70
0.07
--
--
0.28
0.82
0.96
0.13
----
0.12
0.03
---
--0.14
0.12
0.12
--
--
--
--
--
----0.67
0.79
0.78
0.14
0.88
0.14
0.10
Note: Probabilities are simulated using models 2 and 4. When calculating
probabilities for a specific variable: a) all other independent variables are held
constant at their means; b) interaction terms are held constant by first getting
the means of the component variables prior to the interaction (see Long and
Freeze 2006). Probabilities are simulated using Tomz, Wittenberg and King’s
(2003) Clarify software in Stata.
514
JIMENEZ planning as a tool in cutback management (Behn, 1980; Levine,
1985; Levine, Rubin & Wolohojian, 1981). Nevertheless, while it is
tempting to recommend that city governments should undertake
strategic planning in response to fiscal stress, such counsel may not
be practical. Planning requires resources that are of limited supply
during periods of fiscal decline. Cities in this study were engaged in
planning before the local crisis became severe, and were able to
revise existing plans in response to the 2007 recession.
An unexpected result is that performance management is
associated with a higher probability of implementing targeted cuts
during severe fiscal stress. It is a common observation in the
literature that performance management systems are crippled during
periods of fiscal crisis. For example, in the case of performancebased budgeting at the state level, Hou et al. (2011, p. 370)
concluded that “PBB is used more by the states during strong
economic times as opposed to during economic downturns”. What
explains the empirical result?
Targeting cuts is never easy, and such decisions can cost city
managers or elected officials their jobs (Rubin, 1980; Levine, Rubin &
Wolohojian, 1981). While performance management is often thought
of as a rational and objective approach to organizational decisionmaking, it is not difficult to see that it can be used for political
purposes, specifically as a tool to control opposition during periods of
severe fiscal stress when organizations need to cut back and
immediately control expenditures (see Radin, 2006 on performance
management’s negative agenda). This explanation also provides a
sound basis for the finding that performance management is
associated with a higher likelihood of implementing selective cuts in
expenditures in mayor-council governments. While mayor-council
cities are likely to be more politicized, performance information could
have provided elected officials the instrument they needed to justify
targeting cuts to certain departments or units, minimizing political
opposition from affected units whose performance have been
measured but was found wanting.
The finding on the conditioning effects of government form also
suggests that care must be taken when concluding that mayorcouncil forms automatically have compromised capacity to undertake
systematic cutback management. Levine, Rubin and Wolohojian
(1981) arrived at this conclusion, but their case studies were done
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
515 more than three decades ago when very few city governments, if any,
had performance management systems. Today, more and more
governments are undertaking performance measurement and
management activities, although the quality of the process is likely to
be highly uneven. Nevertheless, this finding certainly provides
empirical support for advocates of performance management in local
governments.2
It is important to clarify that it is very unlikely that a performance
management system would have been associated with targeted cuts
if such a system is relatively new. A new system is unlikely to have
sufficient credibility to provide political cover for decisions to target
cuts. Additionally, a newer system is more likely to be abandoned
when the government’s fiscal condition worsens. On the other hand,
one would expect that early adopters of performance management
have had sufficient time to become familiar with technologies used in
measuring, analyzing and reporting performance, and are more likely
to have set up permanent performance management structures and
processes, compared to late adopters. Even if the system itself is not
relied upon extensively for decision-making during a fiscal crisis,
results of past performance evaluations stored in a database system
can be pulled out anytime by an enterprising city official eager to find
a justification for a proposed budget cut.
CONCLUSION
Periods of fiscal decline represent an opportunity for city officials
– elected and appointed alike – to transform their local government
into a leaner but more effective organization by targeting cuts to nonessential programs and services. However, the nature of the fiscal
retrenchment process itself—disappearing slack resources that
makes innovation impossible (Schick, 1980), vehement opposition
from those affected by cuts (Behn, 1980), the political pressure to
satisfy demands of organized and unorganized interests (Levine,
Rubin & Wolohojian, 1981)—means that such an opportunity is often
squandered (Hildreth, 2000).
Advocates of rational decision-making believe that information
gathering, analysis and use in decision-making will lead to superior
organizational performance (Boyne, 2001), even in times of fiscal
distress (Behn, 1980; Levine, 1985). To Levine (1978, p. 322),
appeals for using rational techniques in budget-cutting “assumes
516
JIMENEZ organizations are fully rational actors”, which to him was “an
assumption easily dismissed.” He adds that “[m]ore likely, cuts will be
distributed by a mix of analysis and political bargaining”. The results
of this research show that rational analytic techniques can help local
governments target cuts to expenditures. Whether selective cutting
will ultimately lead to a more focused and stronger local government
is a question that can be answered only by tracking the retrenchment
process across time, which is beyond the scope of this research. The
results also suggest that rational analysis and politics are not
necessarily mutually exclusive. Analysis can be used as a tool to
minimize political opposition, as when performance information is
used to justify targeted cuts.
A critical point raised in this research is the need for city
governments to invest early in developing their capacities to
undertake rational approaches to management. The lesson is clear:
There are no shortcuts to enable any organization to effectively adjust
and adapt to fiscal crises. Stronger organizations—those that have
developed processes and structures to support rational management,
in other words, organizations that are already well run even before a
fiscal crisis hits—are in a better position to implement constructive
approaches to fiscal retrenchment.
Some limitations of this research should be noted. First, the
cross-sectional nature of the ICMA data means that causality cannot
be established. Further validation is required using multi-year data.
Second, future studies can focus on assessing how the quality of the
strategic planning process and performance management systems
influences the choice of budget cutting approach. A combination of
qualitative case studies, and large-n quantitative analysis will provide
a better picture of how the quality of public management processes
matters in fiscal retrenchment in local governments.
NOTES
1. A more sobering view of strategic planning, specifically the
difficulties of undertaking planning in public organizations, is
found in Rabin, Miller and Hildreth (2000). On the other hand, see
Radin (2006) for an analysis of problems and unexpected
consequences of performance management, mostly, in the
federal government.
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
517 2. For a contrary view, see among others, Melkers and Willoughby
(2005), and more recently, Heinrich (2012)
3. An analysis of the distribution of municipal governments in the
sample – based on population, tax authority, census region and
government form – vis-à-vis all municipal governments in the U.S.
shows that the survey under-sampled cities with a population less
than 10,000, and included more mid-sized and bigger cities. This
means that cities from Region 4, where there is a higher
concentration of bigger cities with council-manager governments,
are also overrepresented. More cities in the sample also used the
sales tax in comparison to the general population of municipal
governments. Considering the issues with the representativeness
of the sample, care must be taken when claiming generalizability
of the findings in this research.
4. The calculation of the probabilities was implemented via the
Clarify program in Stata (see Tomz, Wittenberg & King, 2003)
5. However, Clark and Ferguson’s (1984) research showed that
measures of interest group size, rather than their political
activities, significantly affected local fiscal outcomes.
6. Given a simplified multiplicative interaction model:
yi = ß1Xi + ß2Zi + ß3Zi*Xi + ui
where y is the probability of implementing targeted cuts, X is
strategic planning (or performance management) and Z is the
conditioning variable (e.g. budget deficit). The total effect of
strategic planning on y is represented by ß1 + ß3Zi. This means
that for city i, the effect of strategic planning on the probability of
implementing targeted cuts depends on the value of the budget
deficit. The probabilities are calculated based on the total effect
ß1 + ß3Zi.
7. An important caveat is that given the marginal significance of the
interaction terms, one cannot rule out the possibility that the
results are nothing more but statistical artifact.
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APPENDICES
TABLE A
Variable Definition, Data Sources, and Descriptive Statistics
Std.
Expected Data
Mean
Dev.
Sign Source
Variable
Dependent Variables
Implemented targeted cuts to expendiutres (1 – yes,
0 – otherwise)
Main Independent Variables
Strategic planning index – factor scores from
variables measuring if city has strategic plan and
revised it in response to 2007 economic recession,
involved internal and external stakeholders in
planning, and linked plan to budget and operations.
Alpha=0.81
+
ICMA
2009
0.46 0.50
Same
0.33 0.40
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
523 TABLE A (Continued)
Variable
Performance management index – factor
scores from variables measuring if city
undertakes performance measurement
activities and uses performance information in
reporting to citizens, in personnel management
and budgeting. Alpha=0.87
Measures of Government Professionalization
% of workers employed in professional/
management position
Mayor-Council form of government (1 – yes, 0
– otherwise)
Manager empowerment index – Additive index
composed of variables measuring if city
manager or chief administrative officer has
responsibility over developing and
implementing policies, preparing and
presenting the budget, and appointing and
supervising key personnel. (Ranges from 0-1
with higher values indicating more empowered
managers). Alpha=0.60
Measures of Fiscal Condition
Perceived severity of anticipated 2010 general
fund shortfall compared to cuts made in the
FY2009 budget (1-less, 2-same, 3-greater)
2002 to 2007 change in operating
expenditures as % of own-source revenues
(Measure of past fiscal condition, with positive
value signifying worsening fiscal condition)
Measures of Interest Group Influence
% of workers employed in local public
administration
Ethnic fragmentation = 1 – ∑(Race)2, where
Race i denotes the share of population
identified as of race i including White, Black,
Hispanic, Asian and Pacific Islander, and
American Indian. (Ranges from 0-1, with higher
values signifying more fragmentation)
City Size
Expected Data
Mean
Sign
Source
+
Same
0.39
0.47
+
Same
8.99
4.52
–
Same
0.32
0.47
+
Same
0.78
0.39
+
Same
2.43
0.66
+
2002,
2007
CoG
-0.04
0.27
–
20052009
ACS
4.78
3.44
–
Same
0.41
0.29
2007 per capita expenditure (in 1000)
+/–
2009 estimated population
+/–
Std.
Dev.
2007
1.27
1.04
CoG
ICMA
30025 112921
2009
STRATEGIC PLANNING, PERFORMANCE MANAGEMENT AND BUDGET CUTTING
525 TABLE A (Continued)
Variable
Service index (Total number of services
provided by city. Ranges from 0-19)
Socio-Economic and Other Controls
Median household income (2005-2009
average)
Population change (% change from 2000 to
2009)
Financial crisis severity (“To what extent is your
local government affected by the financial
crisis in the U.S. economy? 1. Not at all, 2.
Minimally, 3. Moderately, 4. Significantly, 5.
Severely”)
Central city status (1 – yes, 0 – otherwise)
Dependence on IGR (2007 federal and state
revenues as % of city own-source revenues)
Expected Data
Mean
Sign
Source
+/–
–
–
+
+
+
Same
10.01
Std.
Dev.
3.08
20052009 53134 23977
ACS
2000
DC,
0.11
0.26
ICMA
2009
ICMA
2009
Same
2007
CoG
3.23
0.83
0.09
0.28
18.16
23.02
Note: ICMA – International City/County Management Association’s 2009 State of the
Profession Survey; CoG – 2002 and 2007 Census of Governments; DC – 2000
Decennial Census; ACS – average 2005-09 American Community Survey.
TABLE B
a
b
c
d
e
f
G
H
I
j
k
l
m
n
o
p
q
a
1.00
b -0.04 1.00
c
-0.08 -0.09 1.00
d
0.07 0.08 -0.37 1.00
e
0.03 0.16 -0.14 0.10 1.00
f
0.10 0.32 -0.25 0.17 0.32 1.00
g
0.05 0.11 0.03 0.07 0.12 0.20 1.00
h
0.06 0.02 -0.02 0.02 -0.05 -0.06 0.00 1.00
i
0.06 0.08 -0.10 0.03 0.05 0.24 0.05 -0.05 1.00
j
0.02 0.02 -0.07 0.02 0.04 0.10 0.03 -0.04 0.29 1.00
k -0.01 0.23 -0.11 0.04 0.06 0.57 -0.01 -0.02 0.14 0.08 1.00
l
0.01 0.04 -0.01 -0.03 -0.09 -0.05 0.00 -0.01 -0.04 0.00 0.01 1.00
m 0.08 0.22 -0.24 0.12 0.15 0.47 0.08 -0.05 0.15 0.11 0.29 0.18 1.00
n
0.11 0.16 -0.03 0.05 -0.03 0.24 -0.02 0.03 0.01 0.05 0.20 0.03 0.12
1.00
o
0.04 0.08 -0.09 0.06 -0.05 0.00 -0.19 0.23 0.06 0.03 0.16 0.00 0.08
0.22 1.00
p
0.02 0.07 -0.04 0.08 0.64 0.13 0.21 0.01 0.00 -0.02 -0.12 -0.12 -0.05
-0.10 -0.13 1.00
q -0.11 0.00 0.04 -0.02 -0.11 -0.03 -0.16 0.00 0.10 0.05 0.04 0.01 -0.13
-0.12 -0.04 -0.09
1.00
Legends: a. Strategic planning (SP) index; b. Performance management (PM) index; c. Mayor-Council form; d. Manager empowerment index;
e. management positions; f. 2009 population (log); g. 2000-09 population change (log); h. 2002-07 change in spending/revenue ratio; i.
Financial crisis severity, j. Budget shortfall; k. Central city; l. % employed in public administration; m. Ethnic fragmentation. N. Service
index; o. Spending per capita (2007) log; p. Median household income (2005-09); q. Dependence on IGR.
Correlation Matrix for Independent Variables
526
JIMENEZ