Perceptions of Local Government Fiscal Health and Fiscal Stress: Evidence From Quantile Regressions With Michigan Municipalities and Counties

• Author: Charles Kargman,Shu Wang,Stephanie Leiser
• Date: 01 December 2021
• DOI: 10.1177/0160323X211038356
• Published date: 01 December 2021
• Subject Matter: Research Articles

Perceptions of Local

Government Fiscal Health and

Fiscal Stress: Evidence From

Quantile Regressions With

Michigan Municipalities and

Counties

Stephanie Leiser

1

, Shu Wang

2

,

and Charles Kargman

1

Abstract

This study applies insights from open systems theory to explore how the perceptions of local offi-

cials can enhance our understanding of local government fiscal health—in particular, to understand

differences between healthy and distressed jurisdictions. With a sample of local governments in

Michigan from 2013 to 2019, we use quantile regression to investigate associations between subjec-

tive financial condition measures and objective indicators. The results show that these relationships

are often more muted for lower-stress governments and more pronounced for higher-stress gov-

ernments, a pattern that is not accounted for by traditional methods of measuring financial condi-

tion. The findings demonstrate the utility of open systems theory and quantile regression

techniques to improve understanding of the financial condition and suggest that in order to avoid

overlooking cases of fiscal distress, policymakers and analysts should incorporate these approaches

into methods for diagnosing local fiscal health.

Keywords

fiscal health, local governments, open systems theory

Financial condition, defined as a government’s

ability to meet financial and service obligations

(Jacob and Hendrick, 2013), affects all aspects

of government operations and public service

delivery. For example, credit ratings that

affect governments’costs of debt financing

are heavily driven by financial conditions

(Marlowe 2011). State governments also

design and implement early warning systems

based on local financial conditions to signal

inadequate service delivery in the future

(Kloha, Weissert and Kleine 2005). Financial

condition goes beyond financial management

of a government, for it encompasses the

1

Gerald R. Ford School of Public Policy, University of

Michigan, Ann Arbor, USA

2

Department of Political Science, Eastern Michigan

University, Ypsilanti, USA

Corresponding Author:

Shu Wang, Department of Political Science, Eastern

Michigan University, 601 Pray-Harrold, Ypsilanti, USA.

Email: Swang18@emich.edu

Original Research General Interest Article

State and Local Government Review

2021, Vol. 53(4) 317-336

© The Author(s) 2021

Article reuse guidelines:

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DOI: 10.1177/0160323X211038356

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government’s overall capacity for the provision

of services that are directly related to local res-

idents’wellbeing and quality of life. One only

needs to look at the Flint water crisis to under-

stand that financial struggles can have dramatic

implications in the lives of citizens. As such,

understanding financial condition is an integral

part of government transparency and account-

ability with great policy implications.

Despite abundant research on local govern-

ment fiscal condition, however, little consensus

has been formed regarding a set of indicators for

its measurement, a problem for both researchers

and practitioners charged with monitoring and

promoting local government fiscal health.

Popular methods include the Financial Trend

Monitoring System developed by the

International City/County Management

Association, Brown’s (1989) Ten-Point Scale,

and Kloha, Weissert and Kleine (2005)

method, which uses composite scores and peer

benchmarking. However, as Gorina, Maher

and Joffe (2018) note, the research on local

fiscal health has not converged on a preferred

methodology or set of indicators. Scholars and

practitioners have agreed, however, that fiscal

condition is a complex multi-dimensional con-

struct that is best characterized as an open

system (Hendrick 2004) and that the context

in which fiscal condition analysis is conducted

affects which set of indicators should be used

and how the indicators should be interpreted

(Bird and Slack 2015).

In this article, we attempt to advance the goal

of accurate diagnosis of the local fiscal condi-

tion in two ways by drawing on insights from

open systems theory. First, we place local offi-

cial perceptions at the center of the analysis

and investigate how those perceptions are

related to the traditional, objective measures

of financial ratios. Instead of viewing local offi-

cials as passive facilitators of the mission and

strategies of local governments, open systems

theory emphasizes that the beliefs and expecta-

tions of actors within a system are essential to

understanding the system itself (Scott and

Davis 2006), and interactions between organi-

zational decision-makers and the environment

are critical inputs to the functioning of the

system (Scott 2003). For example, local offi-

cials may have varying beliefs about the appro-

priate size of fund balances, leading them to

make different policy decisions and in turn

affecting the fiscal condition.

We also draw upon a concept from open

systems theory that has been under-developed

in the context of local fiscal health research:

homeostasis, which describes how “healthy”

organizations constantly adapt to their environ-

ment to maintain an internal steady-state while

“unhealthy”or “distressed”organizations strug-

gle to do so. Therefore, because healthy and

unhealthy organizations function differently,

they may not react in the same way to the

same stimuli. We argue that it is helpful to

make a similar distinction between (perceived)

fiscal health and distress, and hypothesize that

healthy and distressed governments are differ-

ent in how they respond to changing internal

and external conditions, as measured by fiscal

indicators. If local officials perceive their gov-

ernment to be healthy, for example, their per-

ception may be relatively unchanged in the

face of a minor adverse change in conditions,

while a more stressed government might react

more strongly.

To understand how this hypothesis relates to

the practical context of diagnosing fiscal health,

consider an analyst trying to understand how

the poverty rate is related to subjective fiscal

health using local government data. Assume

that when stress is low, correlation is very

weak (i.e. homeostasis is maintained), but

when stress is high, the correlation becomes

much stronger (i.e. homeostasis is disrupted).

If high-stress governments are a small enough

portion of the data sample, an analyst might

find that there is no statistically significant cor-

relation between poverty and stress and errone-

ously conclude that poverty rates are

unimportant. As a result, the analyst might fail

to diagnose a higher-stress local government

because they fail to understand the important

role of poverty.

To examine these patterns, we need a new

empirical approach that allows us to examine

how the relationships between indicators and

fiscal health may be different depending on

318 State and Local Government Review 53(4)