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JOURNAL OF PUBLIC BUDGETING,
ACCOUNTING & FINANCIAL MANAGEMENT
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J. OF PUBLIC BUDGETING, ACCOUNTING & FINANCIAL MANAGEMENT
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JOURNAL OF
PUBLIC BUDGETING, ACCOUNTING & FINANCIAL MANAGEMENT
Volume 24, Number 3, Fall 2012
CONTENTS
Changing and/or Funding OPEB Promises: A Typology of
Local Government Responses to GASB 45 and the Realization
of OPEB Liabilities ………….......…...................................................... 369
J. E. Yusuf and T. Musumeci
Citizen Perceptions of General-Purpose and Special District
Governments: A Comparative Analysis .............…………………………. 397
L. J. Killian and K. Le
Two Accounting Standard Setters: Divergence Continues for
Nonprofit Organizations ..…......................................................…….. 429
M. Fischer and T. Marsh
The Sheriff of Nottingham's Favorite Tax: How Local Option
Sales Taxes Exacerbate Budgetary Inequalities between
Local Governments .…..…................................................................. 467
P. J. McHugh and G. J. Jolley
Debt and Budget Gimmickry Revisited: The Upfront Bond
Refinancing Savings Structure .…...….….…..…................................. 490
M. J. Luby
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J. OF PUBLIC BUDGETING, ACCOUNTING & FINANCIAL MANAGEMENT, 24 (3), 369-396
FALL 2012
CHANGING AND/OR FUNDING OPEB PROMISES: A TYPOLOGY OF
LOCAL GOVERNMENT RESPONSES TO GASB 45 AND THE
REALIZATION OF OPEB LIABILITIES
Juita Elena (Wie) Yusuf and Thomas Musumeci*
ABSTRACT. GASB Statement No. 45 addresses how governmental units
account for employees’ other post-employment benefits (OPEB), requiring
government employers to replace OPEB reporting on a pay-as-you-go basis
with an accounting of the cost of current and future benefits. This
requirement and the resulting OPEB liability may prompt government
employers to reconsider key questions regarding their OPEB provision. The
size of the OPEB liability depends on both the benefit promises made to
employees and the assets to fund these promises. We propose a typology
that defines four approaches for governments to respond to GASB 45 and
their OPEB liabilities. These approaches represent different combinations of
strategies involving OPEB promises and assets. We illustrate these
strategies and responses using selected counties and nine mid-Atlantic
cities.
INTRODUCTION
In June 2004, the Governmental Accounting Standards Board
(GASB) issued Statement No. 45 (GASB 45) Accounting and Financial
Reporting by Employers for Postemployment Benefits Other than
Pensions to require clear and transparent reporting of the current
---------------------------------------* Juita-Elena (Wie) Yusuf, Ph.D., and Thomas Musumeci are an Assistant
Professor, and a doctoral candidate, respectively, Department of Urban
Studies and Public Administration, Old Dominion University. Dr. Yusuf’s
research interests are in public budgeting and financial management, with a
particular interest in transportation finance, and transparency,
accountability and public participation. Musumeci’s research interests are in
local government budgeting and finance. He is the Deputy Treasurer for the
City of Virginia Beach, Virginia.
Copyright © 2012 by PrAcademics Press
370
YUSUF & MUSUMECI value of other post-employment benefits (OPEB) promises in state
and local government financial statements. These OPEB are defined
as non-pension benefits provided after an individual leaves
employment. They primarily include retiree healthcare, and often
dental, vision, and prescription drug plans, but possibly also life
insurance, disability, long-term care, and legal services if they are
provided separately from a defined benefit pension plan. Given that
health benefits are by far both the predominant and the most costly
OPEB for government employers, our research focuses primarily on
retiree health benefits.
OPEB have traditionally been reported and paid for on a pay-asyou-go (PAYGO) basis.
GASB 45, however, established new
accounting standards for state and local governments as employers,
requiring them to measure, recognize, and disclose the cost of their
OPEB in their financial reports. Compliance with GASB 45 reporting
guidelines provides employers with an understanding of their OPEB
actuarial liability exposure.
While intended solely as an accounting standard, GASB 45 may
significantly affect the funding, sponsorship, and design of OPEB.
This paper focuses on local government responses to GASB 45 and
the information it discloses regarding OPEB liability, and summarizes
decisions made by selected county and city governments in response
to the realization of the magnitude of their OPEB liabilities following
compliance with GASB 45. This focus on local governments is critical,
as of the over 89,000 local governments in the US, approximately 77
percent provide OPEB to their retirees (Bell, 2006).
We ask the following research question: How have local
governments in the U.S. responded to GASB 45 and the resulting
information about unfunded OPEB liabilities?
Answering this
research question is timely given the recent implementation of GASB
45. It is also relevant given the potential size of OPEB liabilities.
Coupled with the current fiscal crisis, OPEB liabilities may prompt
local governments to re-think the fundamental question of whether to
continue to provide OPEB. Our research examines the decisions
made by local governments regarding the continued sponsorship of
retiree healthcare benefits, prefunding of such benefits, and
subsequent benefit plan redesign and other cost cutting strategies to
accommodate continued sponsorship in the face of significant
liabilities and annual funding requirements. We illustrate, using a
CHANGING AND/OR FUNDING OTHER POST-EMPLOYMENT BENEFITS PROMISES
371 four-cell typology, how local governments have responded to the
informational content of GASB 45. We frame these responses in
terms of changing OPEB promises and/or building assets to fulfill
these promises.
We begin with a brief overview of GASB 45 and discuss the
potential impacts of GASB 45 on government employers. Against this
backdrop we introduce four possible categories of responses to GASB
45. These responses involve different combinations of prefunding
OPEB and maintaining benefit levels. We illustrate these responses
using a study of counties by the National Center for the Study of
Counties (NCSC) and examples of nine mid-Atlantic cities. We
highlight how some local governments’ responses to GASB 45 have
resulted in reduced OPEB.
BACKGROUND ON GASB 45
GASB 45 is the governmental equivalent to Financial Accounting
Standards Board Statement 106 (FAS 106) and International
Accounting Standards Board Statement 19 (IASB 19). GASB 45 was
partly motivated by economic and demographic factors, such as the
impending baby boomers’ retirement and escalating healthcare costs
that threaten to significantly increase the costs to government
employers for retiree benefits (Marlowe, 2008). The traditional
PAYGO approach to OPEB can result in inadequately prefunded
benefits that may in turn contribute to mounting deferred liabilities
and potentially adverse effects on the fiscal health of government
entities. The importance of GASB 45 was spurred by most subnational governments’ not reporting or disclosing in their financial
documents information pertaining to the amount of their OPEB
obligations, making it impossible for the public to determine the true
cost for government of providing these benefits.
OPEB costs have traditionally been accounted for and funded on
a PAYGO basis, with current year benefits and administrative costs
paid out of current revenue. In establishing Statement No. 45, GASB
(2004) noted that the PAYGO approach and its related reporting
failed to (1) recognize the cost of benefits when the exchange of
benefits and service takes place, (2) provide information about the
actuarial accrued liabilities for promised benefits and the extent to
which these benefits have been funded, and (3) provide information
needed to assess potential demands on future cash flows. In
372
YUSUF & MUSUMECI essence, the problem with the PAYGO approach is that it allows
governments to ignore future expenses associated with benefits
promised to retirees, and to underreport substantial accumulated
liabilities that have been incurred and will be incurred in the future.
GASB 45 was driven by two inter-related issues (Governmental
Accounting Standards Board, n.d.). First was the lack of reporting
and information about the nature and size of long-term OPEB
obligations and commitments, and second was the incomplete
information with which to assess the cost of government and to
analyze the financial position and long-run financial health of
government. GASB 45 addressed concerns that the PAYGO approach
was “not transparent and obscured the magnitude of government
employers’ financial obligation … [and] the funded status of postretirement obligations was not disclosed and was not recognized on
the financial statements” (Bell, 2006, p. 29).
OPEB are a form of deferred compensation and should be
recognized and recorded as the benefits are earned, rather than
recognized in the future when the benefits are paid (Mead, 2008).
GASB 45 establishes an amortization period so government
employers can account for the cost of OPEB over the active service
life of employees. From an informational perspective, GASB 45
dictates that employers offering defined benefit OPEB plans must
measure and disclose their long-term OPEB costs and the extent to
which the employers have contributed to meet those costs. In
summary, GASB 45 requires that government employers produce
statements for their OPEB using generally accepted accounting
principles that present the estimated actuarial accrued liabilities and
the annual required contributions necessary to cover the liabilities. In
much the same way as GASB Statement No. 43 changed how subnational governments report the liabilities associated with their
pension plans, GASB 45 changes how state and local governments
report the liabilities associated with their OPEB plans.
Informational Components of GASB 45
According to Wisniewski, “the new OPEB standards provide
information about whether and to what extent promised benefits
have been funded, as well as information about the potential impact
by such benefits on the employer’s future cash flow” (2005, p. 106).
GASB 45 can “[p]rovide information useful in assessing potential
373 demands
on
the
employer’s
future
cash
flows”
(http://www.gasb.org/st/summary/gstsm45.html). It requires the
measurement, recognition, and reporting of annual OPEB costs on an
accrual accounting basis, which allows for the systematic and rational
allocation of the present value of the OPEB over the working life of
employees.
The determination of the OPEB costs and liabilities begins with
calculating the annual required contribution (ARC). There are two
components to the ARC. The first is the employer’s normal costs or
the present value of providing one year of the OPEB to all qualifying
retirees. The second component of the ARC is the amortized costs of
the OPEB liability. These amortized costs represent “[t]he portion of
the actuarial present value allocated to prior years of employment
and thus not provided for by normal costs in the current or future
years” (Mead 2008, p. 290). The actuarial accrued liability (AAL) is
the total amount of the OPEB earned by employees up to the date
that GASB 45 is implemented and is amortized over thirty years. It
represents “the amount that the organization should have been
contributing in the periods prior to the implementation of the OPEB
standard” (Voorhees, 2005, p. 64).
Compliance with GASB 45 also involves determining the
unfunded actuarial accrued liability (UAAL) which is the amount by
which the actuarial value of the OPEB plan assets exceeds the AAL.
For governments using PAYGO, the UAAL will be equal to the AAL as
the OPEB plan will have no assets. The UAAL can also be defined as
the cumulative annual ARC short- falls.
The content of the information resulting from GASB 45 is
daunting. Given that many governments have traditionally relied on
the PAYGO approach to finance their OPEB, GASB 45 was expected to
result in reporting of significant, eye-opening, unfunded liabilities.
McKethan et al. (2006) reported that the AAL could amount to as
much as $1 trillion nationwide. Keating and Berman (2007) cited
estimates of OPEB liabilities in the $1 trillion (McTague, 2006) to
$1.5 trillion (Zion & Varshney, 2007) range. Estimates by the
Government Accountability Office (2007) showed an aggregate state
and local government unfunded liability of between $500 billion and
$1.6 trillion. Research by Credit Suisse estimated that the 25 largest
cities had unfunded OPEB liabilities of over $90 billion (Zion &
Varshney, 2007). OPEB liabilities for the City of Los Angeles alone
374
YUSUF & MUSUMECI were projected to be $93 billion, equivalent to $8,000 per resident
(Marlowe, 2008). More recently, Coggburn and Kearney (2010)
provided data on OPEB liabilities of individual states, which ranged
from effectively $0 to $68 billion. Fourteen states had OPEB
liabilities in excess of $10 billion.
Clearly these liabilities, and the resulting funding requirements,
can have serious consequences for governmental balance sheets,
just as the implication of FAS 106 discussed next had serious
consequences for the balance sheets of many private companies.
POSSIBLE RESPONSES TO GASB 45 AND THE SUBSEQUENST REALIZATION
OF OPEB LIABILITIES
GASB 45 brings public sector accounting practices in closer
alignment with the private sector pension accounting rules instituted
in response to several highly publicized private sector pension fund
collapses. Hurley et al. (2006) viewed GASB 45 as the public sector
equivalent of FAS 106, to which many attributed a steep decline in
private sector retiree healthcare benefits (Patterson, 2001).
Learning from the FAS 106 Experience
Pearson and Jerris (1995) argued that including liability reporting
for OPEB reduced healthcare and other benefits received by private
sector employees and retirees. FAS 106 became effective December
15, 1992, and statistics show that the private sector has since seen
decreasing retiree health benefits. In 1997, 22 percent of private
sector employers provided retiree health benefits, but by 2002, only
13 percent provided such benefits (Kilgour, 2009). Other studies
documented this positive relationship between reduction in benefits
and the implementation of FAS 106 (Mittelstaedt, Nichols, & Regier,
1995; Binnis & Riffe, 2000).
The private sector experience with FAS 106 suggests that despite
its intended role as simply an accounting and reporting standard that
requires government employers to recognize OPEB costs, GASB 45
could result in these government employers reducing or even
eliminating their OPEB. Kilgour suggested that “the major short run
impact of GASB 45 will be to pressure employers to reduce costs by
reducing retiree health and other benefits by curtailing access and
benefit levels and shifting more of their cost to retirees” (2009, p.
375 32). Therefore, while GASB 45 is an accounting standard and does
not mandate how a governmental entity conducts its operations,
“[c]onsideration of the information produced by the application of the
standard may encourage … governments to think about reducing
such benefit programs (and their associated liabilities) in the future”
(Wiesnewski, 2005, p. 115).
Coggburn and Kearney (2010) argued that while GASB 45 has
made OPEB costs more transparent, the resulting unfunded liabilities
have prompted a concern “over the sustainability of many
government benefit plans” (p. 106). Many of the questions being
addressed by government employers today are equivalent to those
resulting from FAS 106. These companies had to consider the
sustainability of continuing to provide retiree healthcare benefits in
their existing forms, and subsequently what types of plan design
changes or cost control measures could be instituted and how they
would be instituted. Companies also had to consider whether to
prefund their retiree healthcare plans and how much to prefund.
Both sets of questions are examined in this study. The former focuses
on whether to continue providing OPEB and if so, what types of
changes might be made to the OPEB plan. These questions are
important because they affect the assumptions underpinning the
OPEB actuarial valuation, which may result in “nontrivial differences”
in the OPEB liabilities (Marlowe, 2008, p. 216). The latter question of
prefunding deals with building the assets base for addressing future
liabilities. The responses to these questions are important because
they determine the extent of OPEB liability underfunding.
Changing OPEB Promises: Continuing OPEB Provision and At What
Levels?
As private sector employers dealt with FAS 106, some considered
discontinuing their retiree healthcare benefits or ending participation
for future retirees or new hires. Several companies implemented
changes to their OPEB plans, affecting benefit levels, eligibility, and
the cost sharing relationship. Some private employers began to tie
their retiree healthcare benefits to greater lengths of service with the
company or introduced graded vesting and accruing retiree
healthcare benefits over the employees’ working careers. Other
elements of plan design that came under scrutiny were the provision
of full benefits to spouses at no cost, the provision of full benefits at
younger retirement ages, and the level of benefits provided (Feldman
376
YUSUF & MUSUMECI & Haynes, 2007). To ameliorate the financial impact of FAS 106,
some companies capped the amount the employer would contribute
toward retiree healthcare benefits. Also to reduce their financial
burden, employers shifted away from a defined benefit (DB) plan to a
defined contribution (DC) plan. These approaches had the key
advantage of reducing both the employer’s liabilities and expenses
for such benefits. Similar actions are expected to be taken by
government employers as they deal with GASB 45.
In situations where government employers may be considering
plan redesign, the focus will typically be on preserving as much as
possible the expectations of present retirees, while allowing the
greatest changes to affect new future hires. While there is usually
much more flexibility to change retiree benefits for new employees,
public sector unions and the relevant labor laws may influence the
government employer’s ability to change its retiree benefits (Moran,
2010). The power of government employees and their unions in
particular has been shown to be an important factor influencing
governments’ decisions regarding retiree benefits (McKethan et al.,
2006). In some jurisdictions, unions are strong and can prevent
unilateral action by the government employer. Other jurisdictions
may be similarly constrained if their OPEB have constitutional,
statutory, or judicial status that precludes or limits what governments
can do, especially for retirees and incumbent employees.
Building the Assets Base: Should the Government Employer Prefund?
A key component of GASB 45 is the option of prefunding OPEB.
Doing so provides a vehicle for building an asset base to offset the
actuarial accrued liabilities and pay for the benefits as they come due
in the future. The growth of the assets, theoretically, provides greater
benefit security for retirees (Young, 2005) as more revenues into the
plan, over time, come from investment income. The new OPEB
reporting standards do not require that the OPEB be prefunded or
that funds be held in trust. However, prefunding and setting up an
irrevocable trust are recommended best practices for local
governments implementing GASB 45 (Coe & Rivenbank, 2010).
Government employers can choose to continue to address their
OPEB on a PAYGO basis. But there are long-term consequences of
doing so, in that the OPEB liability and net obligation for the employer
will continue to grow unchecked. With the PAYGO approach “the
377 expensing is only out of pocket so there is not assistance against the
accruing liability” (Bell, 2006, p. 34). However, there are significant
obstacles to OPEB prefunding. For most employers the ARC payment
is a large multiple of the PAYGO amount. Depending on the size of
the OPEB plan, advance funding under the GASB 45 rules may add
fiscal stress to the governmental entity (Young, 2005).1 Prefunding,
because it usually involves higher short-term costs compared with
PAYGO, may introduce additional financial obligations at an
inopportune time. This may prompt a reconsideration of OPEB levels
instead of prefunding existing levels of benefits (Wiesnewski, 2005).
A Four-cell Typology of Government Responses to GASB 45
GASB 45 provides government employers with an understanding
of their OPEB actuarial liability, which may raise the important issue
of how to manage that liability (Young, 2005). The UAAL depends
both on the promises to employees and the assets designed to fund
these promises. Governments can respond to GASB 45 by focusing
on both sides of the equation, by (1) changing benefits (i.e., the OPEB
promises made to employees) and/or (2) building the OPEB assets
needed to provide the benefits.
Government responses to addressing the OPEB liabilities that
result from compliance with GASB 45 can be organized into a fourcell typology. This typology categorizes government responses based
on two dimensions (see Figure 1). The first dimension is the OPEB
promise made to employees. Government employers can either
maintain the same OPEB promise as before implementation of GASB
45, or reduce or eliminate benefits.2 The second dimension pertains
to the assets and funding of OPEB. Here, governments also have two
options, either to continue funding OPEB on a PAYGO basis, or to
prefund OPEB. The four cells of the typology include a combination of
these two dimensions. First, governments could maintain the status
quo and make no changes to their OPEB benefits or to their PAYGO
approach to funding OPEB (cell 1). Alternatively, government
employers could prefund their OPEB and continue to provide the
same OPEB benefits (cell 2). The remaining two response options
both involve reductions in benefits, whether funding via PAYGO (cell
3) or by prefunding (cell 4). As the next section illustrates, local
governments’ response to GASB 45 are spread across these different
categories.
378
YUSUF & MUSUMECI FIGURE 1
Four-Cell Typology of Government Employers’ Responses to GASB 45
and Unfunded OPEB Liabilities
OPEB Assets
OPEB Promises
PAYGO
approach
Prefund
OPEB
Maintain same benefits
as pre-GASB 45
Reduce or eliminate
benefits
1. MAINTAIN STATUS
QUO
3. PAYGO WITH LOWER
BENEFITS
2. PREFUND WITH SAME
BENEFITS
4. PREFUND WITH
LOWER BENEFITS
HOW HAVE COUNTY GOVERNMENTS RESPONDED TO GASB 45 AND THE
REALIZATION OF THEIR OPEB LIABILITIES?
In 2007, the National Center for the Study of Counties (NCSC)
examined how counties across the country were responding to GASB
45 through case studies of 15 counties (Sanford, 2007). The study’s
findings indicate a range of responses, as shown in Appendix 1. Only
a few selected examples from the NCSC study will be highlighted here
to illustrate variations in how the responding counties addressed
GASB 45 and its associated OPEB liabilities.
Fairfax County, Virginia, had an unfunded OPEB liability of $143
million and an ARC of $15.2 million. The county did not make any
changes to its retiree healthcare plan, but instead focused solely on
funding the ARC and creating an OPEB trust. Montgomery County,
Maryland, followed a similar approach. The FY 2008 unfunded
liability was $2.6 billion and the ARC was $240 million. Partly
because 70 percent of its employees are unionized, the county
committed to full funding of the ARC over a 5 year period.
Sonoma County, California, on the other hand, adopted a twopronged strategy: (1) provide personal, professional, and political
recognition of healthcare costs and their importance, and (2) protect
health retirement benefits over the long term by making them
sustainable. This sustainability was defined as a benefit level where
the county could provide services to citizens yet also offer a fair
379 compensation package to employees who deliver those services
(Sanford, 2007). As a result, the county reduced its retiree
healthcare contribution to a more sustainable level.
Gwinnett County, Georgia, also made changes to its OPEB, but
only changed the insurance funding mechanism and not access to
healthcare (Sanford, 2007). County leaders, realizing that their OPEB
liabilities were not sustainable, created an OPEB trust fund to set
aside assets to cover the liabilities and changed from paying a
percentage of the retiree healthcare premium to paying a defined
monthly contribution. This strategy has allowed the county to
essentially lock in its OPEB liabilities at more manageable levels.
Finally, Chester County, Pennsylvania, had an unfunded OPEB
liability of about $4.4 million, which prompted significant changes to
its OPEB. To limit both exposure to such liabilities and the impact on
taxpayers, the county eliminated the healthcare benefit for
employees retiring after June 30, 2006.
HOW HAVE CITY GOVERNMENTS RESPONDED? EXAMPLES FROM NINE MIDATLANTIC CITIES
To provide a more comprehensive examination of how local
governments have responded to GASB, we supplemented the finding
of the NCSC study with examples of how cities have responded to the
information concerning their liabilities. By combining these examples
of nine Mid-Atlantic cities in Virginia, Maryland, and North Carolina
with the fifteen case studies of counties, we are able to better
represent the different types of local governments in the U.S.
Three cities were selected from each of the three states:
Baltimore, Gaithersburg, and Rockville in Maryland; Charlotte,
Fayetteville, and Winston-Salem in North Carolina; and Alexandria,
Richmond, and Virginia Beach in Virginia. These cities were selected
to provide variety in terms of number of retirees, budget size, OPEB
unfunded liability, and ARC. In addition we selected cities from both
right-to-strike (Maryland) and right-to-work (Virginia and North
Carolina) states. Table 1 summarizes the characteristics of the nine
cities including government net assets, population, per capita
income, UAAL and UAAL per capita. Appendix 2 provides a summary
of the cities’ responses to GASB 45. As can be seen from Table 1
and Appendix 2, the cities selected for case study vary widely not only
380
YUSUF & MUSUMECI in terms of government size and affluence, but also with regard to
OPEB-related characteristics such as the AAL, UAAL and UAAL per
capita, ARC, and number of government retirees. The examples from
the nine selected cities are discussed next.
TABLE 1
OPEB Characteristics of Selected Cities (2008)
Total Govt
Net Assets
(in
billions)
City
Richmond, VA
$2.489
Alexandria, VA
$0.373
Virginia Beach, VA
$3.093
Baltimore, MD
$4.834
Gaithersburg, MD
$0.165
Rockville, MD
$0.271
Charlotte, NC
$7.616
Fayetteville, NC
$1.058
Winston-Salem, NC
$1.413
Popula- Per Capita
tion
Income
200,123
141,000
434,072
637,455
59,912
63,170
695,995
181,453
224,889
UAAL
(million)
UAAL Per
Capita
$39,860
$76.0
$379.77
$65,141
$150.5 $1,067.38
$43,578
$127.7
$292.74
$32,445 $2,150.0 $3,161.01
$69,985
$18.0
$300.44
$53,754
$10.1
$160.46
$24,858
$229.7
$330.03
$34,245
$28.0
$149.33
$35,666
$79.0
$351.28
Analysis of the cities’ responses to GASB 45 and its informational
content was based on examination of their respective comprehensive
annual financial reports (FY 2006 through FY 2010) and other
government documents. Data from FY 2006 through FY 2008 were
used to determine how the cities responded to the implementation of
GASB 45. Follow-up information using data for FY 2009 and FY 2010
was used to update the cities’ responses. City finance and budget
directors were also surveyed to obtain information about compliance
with GASB 45 and its impact on OPEB provision.
Richmond, Virginia
Of all the cities studied, Richmond, Virginia, had adopted the
most proactive strategy to reduce its unfunded liability. The city’s
original UAAL was $194 million, which prompted the city to make
significant changes to its retiree healthcare program. This reduced
the liability by almost $120 million to $76 million. The most
381 significant change was to eliminate the Medicare subsidy provided to
its retirees. This was accomplished by enrolling retirees in the
Medicare Advantage program instead of keeping them on the OPEB
plan. Second, all employees hired after January 1, 1997, were
moved into a DC retiree healthcare plan (in the form of a HSA), and
those employees receive no retiree healthcare in the future. Finally,
for current retirees and employees hired prior to January 1, 1997, the
city froze its retiree healthcare contributions at the 2007 levels. By
aggressively redesigning the OPEB, Richmond was able to
significantly reduce and limit its OPEB liability. The city decided not to
set up a trust fund to prefund the remaining benefits promised to
their pre-1997 employees, but did set aside (in 2008) $650,000
towards future OPEB costs. In 2009 and 2010 the city set aside $1.4
million per year towards its OPEB liability. This amount was
significantly less than the ARC and is roughly equal to the normal cost
component of the ARC.
Alexandria, Virginia
The City of Alexandria, Virginia, decided to continue to provide
retiree healthcare and to prefund the liability. This was accomplished
by creating an OPEB trust fund and making an initial deposit of $5.6
million in 2008 as well as identifying an additional $10.7 million from
the ending General Fund balance from FY 2008 for deposit into the
trust fund. The city made several changes to its employee healthcare
plan, which affected retirees, as they participate in the employee
healthcare plan. The city’s monthly contribution is a fixed $260 per
person toward the healthcare premium and the remaining balance is
the responsibility of the retiree. Healthcare premiums were increased
by 3.3 percent in FY 2007, and this increase was borne solely by
retirees. In addition, retiree healthcare for employees hired after
September 30, 2007, will be prorated based on the length of service.
While not related to retiree healthcare, the city also decided that
employees hired after July 1, 2008 would not receive the retiree life
insurance benefit that had been previously provided. This had the
effect of lowering the overall OPEB liability for the city. The city’s most
recent actuarial valuation was on December 31, 2009 and at that
time the OPEB trust fund was valued at $8.2 million and the AAL was
$90.7 million (resulting in an UAAL of $82.5 million which is a funding
ratio of 9%). This was after the city made the full ARC payment for
both 2009 and 2010.
382
YUSUF & MUSUMECI Virginia Beach, Virginia
The City of Virginia Beach decided that it would continue to
provide retiree healthcare and that it would prefund the OPEB and
establish a trust fund. In 2007 the city created an Employee Benefits
Review Task Force, whose members represented City Council, city
employees, public safety employees, and citizens and business
owners. The Task Force developed an overall strategy of reducing the
unfunded retiree healthcare liability and, to the extent practical,
funding the ARC. Recommendations made by the task force became
effective in FY 2009. The city’s first ARC was made on June 30,
2008, in the amount of $10.3 million. The city has contributed 100
percent of the ARC into the trust fund for all fiscal years since
implementation of GASB 45.
Reducing the OPEB liability involved significant changes to the
OPEB promises. First, length of service necessary for retiree health
insurance eligibility was increased from 5 years to 25 years. Second,
the city shifted more costs to employees, in the form of reduced
employer subsidies and increased employee co-pays, deductibles,
and out-of-pocket maximums. The city eliminated the zero premium
(i.e., 100% employer subsidy) healthcare option for single subscriber
retirees, in addition to introducing a graduated subsidy plan capped
at 50 percent. In FY 2010 the city offered employees the option to
switch from the current DB plan to a DC plan with a HSA. However,
limited enrollment in the HSA option indicates that it is unlikely to
substantially reduce the unfunded liability.
Baltimore, Maryland
Baltimore has, by far, the largest liability of the cities included in
this study. Maryland is a right-to-strike state, and Baltimore has
union contracts that made it impossible for the city to consider
changing or eliminating its OPEB to reduce the liability. Given the size
of the UAAL ($2 billion for the city and its school system combined),
carrying an unfunded liability of that magnitude on the financial
disclosure and reporting documents could have a negative effect on
the city’s bond ratings. Therefore prefunding was the only option, and
in FY 2008 the city established an OPEB trust fund and contributed
$183.3 million. This represented $18.7 million more than the ARC
and was an increase of $78.6 million over the previous year’s PAYGO
amount. For FY 2009 the city contributed $142.3 million to the OPEB
383 trust fund ($37 million less than the ARC). For FY 2010 the city again
contributed $142.3 million to the OPEB trust fund (the ARC was
$203.7 million). Despite the prefunding strategy, as of June 30,
2010, the UAAL for the city of Baltimore was $2.6 billion, an increase
of $415 million since June 30, 2008.
Gaithersburg, Maryland
Gaithersburg, Maryland, adopted a proactive strategy,
implementing GASB 45 a year earlier than required. The city decided
to prefund its existing OPEB with no plan changes. The city pays
85percent of the retiree’s health and dental premiums as well as
100percent of the life insurance premiums. An employee must have
at least 15 years of service to qualify for the OPEB. In FY 2007, the
city established an OPEB trust fund with an initial deposit of $2.6
million (over two and a half times the ARC). However in subsequent
years (FY 2008 through FY 2010) the city’s contribution to the trust
fund was significantly below the ARC: 32 percent, 47percent, and
10percent of the ARC, respectively. According to the most recent
actuarial valuation of the OPEB plan (completed July 1, 2009), the
AAL was $24.9 million and the UAAL was $22.9 million.
Rockville, Maryland
The City of Rockville, Maryland, faced a very small OPEB liability,
primarily because in order to qualify for the benefit, retirees must be
at least 60 years old with ten years of service. This has had the effect
of minimizing the “window” within which the retiree will receive OPEB
before being eligible for Medicare at age 65. Because the benefits
were already minimal, the city decided to make no plan changes. In
2009 the city established a trust fund and made the full ARC
payment of $1.3 million. However, in the following year the city
funded only $237,000 of the $1.4 million ARC.
Charlotte, North Carolina
Prior to GASB 45, the City of Charlotte, North Carolina, offered a
modest OPEB in which retirees with at least 15 years of service were
eligible for the healthcare plan and the city subsidized 85 percent of
the premium. Employees who retired with at least ten but less than
15 years of service were allowed to participate in the plan but had to
pay the full premium. Those with less than ten years of service
384
YUSUF & MUSUMECI received no benefits. With the implementation of GASB 45, no
changes to those eligibility and participation requirements were
made. Instead, the city adopted an aggressive prefunding strategy
and focused on building the asset base needed to pay for future
benefits.
In FY 2008, the city established a trust fund and made a payment
of $28.4 million (166% of the ARC). For 2009 and 2010 the city
contributed 195 percent and 104 percent of the ARC payment,
respectively. The most recent actuarial valuation (as of July 1, 2009)
was $174 million, which suggests that the aggressive prefunding
strategy has been able to reduce the OPEB unfunded liability.
Fayetteville, North Carolina
The City of Fayetteville, North Carolina, decided to continue to
offer healthcare coverage to its retirees, but has made changes to the
healthcare plan in an effort to reduce OPEB liabilities. For employees
hired after February 1, 2008, eligibility to participate in the retiree
healthcare plan is based on 20 years of credible service. This is a
considerable increase from the previous requirement of only 5 years
of service. In addition, retirees will only be able to carry a dependent
on the plan if that dependent was on the plan for the consecutive five
years prior to retirement, and the dependent must pay the full
premium.
However, the city has not yet decided whether to prefund the
liability, and as of June 2010, the city was still using PAYGO. Despite
continuing with the PAYGO approach and not prefunding, the city has
seen a reduction in its UAAL, from $28 million in 2008 to $15 million
in 2009, which could be largely due to changes to the plan.
Winston-Salem, North Carolina
The City of Winston–Salem, North Carolina, also decided to
continue to provide retiree healthcare, while adopting an aggressive
prefunding strategy. In January 2008 the city established an OPEB
trust fund with $34.8 million (44.1% of the UAAL). In subsequent
years (FY 2009 and 2010) the city contributed 100 percent of the
ARC amount.
The city also made plan changes to reduce its liability. For
example, the city increased the required number of credible service
385 years to 15. Dependents will be allowed on the plan only if they pay
the full group rate premium. For those retirees who qualify for the
OPEB, the city limited its annual contribution to $2,400 per retiree,
with increases in premiums, co-pays, and deductibles beyond this
amount to be covered by the retiree. As of the most recent actuarial
valuation on January 1, 2010, the OPEB liability was almost halffunded (48.5%), as the AAL was $80.6 million, and plans assets were
valued at $39.1 million.
CONCLUSION AND IMPLICATIONS
The examples discussed in this paper show that local
governments have responded to GASB 45 using a combination of
strategies. The findings of the NCSC study of counties and the case
studies of nine mid-Atlantic cities indicate that local governments
have responded to GASB 45 and the knowledge of the magnitude of
their OPEB liabilities in four different ways (see Figure 2). Improving
the asset base appears to be a popular response to reducing the
unfunded liability with almost 70 percent of the cities and counties
included in this study taking steps to prefund their OPEB. However,
some local governments (43.5%) have also responded by reducing or
eliminating retiree healthcare.
As illustrated in this paper, coming to grips with the OPEB
unfunded liabilities has resulted in some local governments not only
reconsidering their OPEB plan designs, but also contemplating
eliminating their OPEB. While the severity of plan redesign and
possible discontinuation of OPEB plan offerings by government
employers will typically depend on the magnitude of the unfunded
liability, the current fiscal environment facing governments is such
that even those cities with smaller OPEB liabilities may consider
reducing or eliminating their OPEB as a way to reduce future liabilities
and outgoing cash flows.
Several authors and studies have suggested measures for
governments to manage their OPEB liabilities. For example, Russell
(2008) suggested several approaches to controlling OPEB liabilities,
including the following:
- Modifying the cost-sharing philosophy by requiring retirees to pay
an increased share.
386
YUSUF & MUSUMECI FIGURE 2
OPEB Liabilities in Four Different Ways
PAYGO approach
Prefund OPEB
OPEB Assets
OPEB Promises
Maintain same benefits as preGASB 45
Maintain Status Quo
Counties:
Mecklenburg, NC; Multnomah,
OR
Prefund with Same Benefits
Counties:
Clark, NV; Fairfax, VA;
Hillsborough, FL; Harris, TX;
Montgomery, MD; Oakland, MI
Cities:
Baltimore, MD; Charlotte, NC;
Gaithersburg, MD;
Rockville, MD
Reduce or eliminate benefits
PAYGO with Lower Benefits
Counties:
Chester, PA; Marathon, WI
Cities:
Fayetteville, NC; Richmond, VA
Prefund with Lower Benefits
Counties:
Gwinnet, GA; Shelby, TN; Sonoma,
CA
Cities:
Alexandria, VA; Virginia Beach, VA;
Winston-Salem, NC
Note: Tulsa, OK was included in the NCSC study of county responses but is
not included in this summary figure because the county does not offer a
DB OPEB plan. Bernalillo, NM was also not included because its retirees
participate in the state retiree health plan and the county has no
liability.
- Increasing eligibility requirements for receiving benefits or
reducing benefits if retirement occurs after a certain date.
- Limiting employer liability exposure by reducing duration of
coverage, capping employer annual claims costs per retiree, and
capping employer aggregate costs, or introducing DC plans.
- Modifying benefit designs such as changes to deductible, copayments, co-insurance, and out-of-pocket limits.
- Other cost management strategies such as switching retirees to
Medicare advantage and Medicare supplement plans.
Examples of how these approaches have been implemented by
counties and cities in this study are presented in Table 2.
387 TABLE 2
Strategies and Approaches for Reducing Benefits
Strategy/Approach
Example
Modifying the Cost-Sharing Philosophy
Winston-Salem: Dependents pay full premium.
 Different subsidies for
retirees vs. dependents
Charlotte: Employees with 15 years of service
 Linking retiree
contributions to years of are allowed to participate in the healthcare plan
and the city pays 85 percent of the premium.
service
Employees who retire with at least ten but less
than 15 years of service are allowed to
participate in the plan but must pay the full
premium.
Increasing Eligibility Requirements for Receiving Benefits or Reducing
Benefits If Retirement Occurs after a Certain Date
Fayettevile: 20 years of credible service
 Increasing eligibility
required for a retiree to participate in the
requirements for
healthcare plan.
receiving benefits
Chester County: Eliminate the healthcare
 Reducing benefits if
retirement occurs after a benefit for employees retiring after June 30,
2006
certain date
Limiting Employer Liability Exposure
 Limiting employer annual Winston-Salem: Limit the annual contribution to
$2,400 per retiree, with increases in premiums,
costs per retiree
co-pays and deductibles beyond this amount to
be covered by the retiree.
Richmond: For current retirees and employees
 Capping employer
hired prior to January 1, 1997, the city froze its
aggregate costs
contributions to retiree healthcare at the 2007
levels.
Virginia Beach: Provide employees the option of
 Introducing DC plans
switching from the current DB plan to a HSA (DC
plan).
– Changing deductibles, co- Virginia Beach: Increase retiree co-pays,
payments, co-insurance, deductibles and out-of-pocket maximums.
and/or out-of-pocket
limits
Richmond: Enroll retirees in Medicare
– Switching retirees to
Advantage program.
Medicare supplement
plans
388
YUSUF & MUSUMECI This study utilized a sample of 15 counties (from across the
country) and nine Mid-Atlantic cities as the basis of the analysis of
local government responses to GASB 45 and its informational
contents regarding OPEB liabilities. The counties and cities varied in
terms of size, measured as population, government net assets, and
government workforce and retirees. Furthermore, the cities and
counties represent both urban and rural areas, and right-to-work and
right-to-strike states. While the cities are all from the mid-Atlantic
region, there is no reason to believe that their responses to GASB 45
are driven by regional factors, particularly since many of their
responses are similar to those of the counties. This suggests that the
findings are, with some degree of confidence, generalizable to local
governments throughout the country.
Implications
The goal of this paper was to highlight the variety of ways that
local governments have responded to knowledge about their OPEB
liabilities, and to show that some of these measures have resulted in
reduced benefits for government employees. The next paragraphs
discuss the implications of these responses to GASB 45.
Clearly, the accounting and reporting standards of GASB 45
have serious implications for government employers. Clark (2008)
argued that GASB 45 serves as “an important tool for policymakers
and stakeholders in determining future compensation and
employment policies and tax policies” (p. 3). In complying with GASB
45, governments are able to generate information about OPEB that is
useful to policymakers, investors, and other stakeholders. While in
the beginning GASB 45 may introduce staggering liabilities to
government employers’ balance sheets, “in the longer term, it might
bring into sharper focus for both the electorate and elected officials
the fact that massive financial commitments have been made to
public employees that will be progressively more difficult to meet”
(Hurley et al., 2006, p. w203). Furthermore, information resulting
from compliance with GASB 45 may shed light on instances where
current and future funding of OPEB would strain a government’s
operations or where conditions are such that governments are unable
to fulfill their OPEB obligations (Bell, 2006).
In the recent ICMA Survey of Local Government Employee Health
Insurance Programs (ICMA, 2007), cities and counties were asked
389 the amount of their OPEB liabilities. Interestingly, 26 percent of
respondents were not sure of their estimated OPEB liabilities. Clearly,
the reporting requirements of GASB 45 are needed to ensure that
those cities and counties are aware of the future funding needed to
ensure that they can keep the promises made to their employees and
retirees. As McKethan et al. (2006) suggested, “GASB 45 is an
important and needed contribution to public accounting and oversight
that will help ensure that public officials will take the future costs of
such programs into account when setting retiree benefits and
premiums” (p. 1523). It can be argued that the costs associated with
reduced benefits are a reasonable tradeoff for the increased
confidence of knowing that the needed assets have been put aside to
deliver on those promises. For government employees, despite
possibly experiencing reductions in OPEB, there is greater security in
knowing that the retiree benefits retained will be more fully
accounted for and better funded.
It is also important to note that GASB 45 may not entirely be at
fault for the reduction in retiree healthcare benefits. Beyond
disclosing the liabilities and costs of governments’ OPEB, GASB 45
does not require governments to take any actions to manage their
OPEB liabilities. Therefore, the resulting changes in benefits should
not be blamed entirely on GASB 45. In many instances, the effect on
OPEB of GASB 45 cannot be differentiated from other economic and
fiscal factors.
Clark (2008) argued that most government OPEB plans are
regularly amended, as government employers periodically increase
premiums, raise deductibles, increase co-payments, restrict choices,
or raise eligibility criteria. Wiesnewski (2005, p. 118) suggested that
implementation of GASB 45 is “less likely to influence the employer’s
decision to continue to provide such benefits than other strong
economic factors such as significant continued healthcare cost
inflation and a continued deterioration in the active-to-retiree
workforce ratio in state government employment.” In the face of the
current fiscal crisis, it would not be surprising if more and more state
and local governments turn to benefit plan redesign as a means of
reducing their overall OPEB liabilities, not because of GASB 45 but
because of economic pressures. Therefore, when coupled with
factors such as the growth in medical and healthcare costs and the
decreasing ratio of active employees to retirees in the public sector,
390
YUSUF & MUSUMECI GASB 45 may result in local governments reducing their OPEB in
order to avoid additional liabilities.
Finally, GASB 45 may also have implications for how governments
think about their other unfunded liabilities. The Cobalt Community
Research survey (2009) asked respondents whether their GASB 45
and OPEB experiences had heightened their awareness of other longterm liabilities. A majority (59%) of respondents answered in the
affirmative; 27 percent indicated that GASB 45 has increased their
awareness of other similar liabilities and had prompted them to begin
planning for these liabilities. The other 32 percent, while being more
aware, were insufficiently concerned about the liabilities to begin
planning for them.
Even while government employers deal with issues arising from
the information provided through the implementation of GASB 45,
several other concerns must also be addressed. Surrounding the
overarching questions of whether to prefund (and the potential fiscal
impact of higher contributions associated with prefunding) and
whether the existing benefit structure will be maintained are key
issues such as (1) the extent to which any decreases in benefits
undercut government’s competitive ability to hire needed employees;
(2) the affordability of prefunding; (3) the political hazards associated
with addressing OPEB liabilities; (4) legal issues associated with
OPEB levels and the possible reductions in such levels; and (5) the
effect on bond ratings of decisions to address OPEB liabilities (Young,
2005). These questions were not addressed in this study. However,
as more local and state governments are forced to come to grips with
their OPEB plans and the associated liabilities, these issues will come
increasingly to the forefront of policy discussion. These issues
provide ample opportunity for continued future research on the
financial, human resources, and political implications of GASB 45 and
the recent realization by government employers of their OPEB
liabilities.
NOTES
1. It may have been the absence of both the equivalent standards
(to GASB 45) and the greater disclosure and transparency
resulting from such standards that precipitated the underlying
financial problems. However, the additional financial pressures
391 associated with making the ARC payments could contribute to
substantial additional stress.
2. While it is possible that another option would be to increase OPEB
benefit levels, existing concern over sustainability of OPEB
promises suggest that it is unlikely that government employers
will raise benefits.
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394
YUSUF & MUSUMECI APPENDIX 1
Summary Information for Counties in the NCSC Study(a)
Government Response to GASB 45 and
Employment Information About OPEB
AAL
ARC
Liabilities
County
($million) ($million)
FTE
 County participates in the
Bernalillo,
state retiree healthcare
NM
n/a
n/a
1,608
program and has no liability
 County already offered HSA,
so only have minimal liability
due to implicit rate subsidies
 Retirees have access to
county health plan but pay
100% of premiums
Tulsa, OK
1
n/a
n/a
 Eliminated healthcare
benefits for employees
retiring after June 30, 2006
Chester, PA
4
1
2,290
 County already offered HSA,
so only have minimal liability
Marathon,
due to implicit rate subsidies
WI
5
0.1
838
 Cost-allocate the ARC across
Hillsbothe department as part of the
rough, FL
100
8.2
10,429
cost of each FTE
Multnomah,
 PAYGO for 2008
OR
110
12.7
4,281
 No plan changes
 Switched from a DB plan to a
DC plan
 Created a locally controlled
Gwinnett,
OPEB trust and pension plan
GA
140
13.6
4,586
 No changes to benefits as the
county recognizes that OPEBs
are important
Mecklenrecruitment/retention tools
burg, NC
141
14.6
4,282
 Focus on funding the ARC
 Created OPEB trust fund
Fairfax, VA
143
15.2
10,999  No changes to health plans
 Significantly reduced retiree
benefits package for new
employees
 No changes for current
employees
Shelby, TN
267
28.2
6,277
 Partially funding ARC
Clark, NV
372
49.7
18,705  No changes to health plan
395 APPENDIX 1 (Continued)
Government Response to GASB 45 and
Employment Information About OPEB
AAL
ARC
Liabilities
County
($million) ($million)
FTE
 Reduced employer contribution to the healthcare
Sonoma, CA
382
37.2
4,154
premium
 Has been prefunding OPEB
since 1980s and full AAL is
advance funded
 Introduced HSA
Oakland, MI
830
60.2
4,536
 Significantly reduced retiree
benefits package for new
employees
 No changes for current
employees
Harris, TX
834
90.0
15,840
 Full funding of ARC
implemented over a five year
Montgomery,
period
MD
2,600
240.0
9,089
Notes: Information about the number of government retirees is not available.
Source: Research by the National Center for the Study of Counties (Sanford
2007).
APPENDIX 2
Summary Information for Selected Cities (2008)
Response to GASB 45
Govt
AAL
ARC
Govt
Employees and Information about
($million) ($million) Retirees
OPEB Liabilities
(FTE)
 Phasing out OPEB
through significant plan
Richmond,
changes
VA(a)
76.1
4.6
1,172
8,940
 Established OPEB Trust
Fund with initial deposit
of $5.5 million
 Increased employee
Alexandria,
premiums
VA(a)
88.1
17.9
1,015
4,472
Fund and made the ARC
payment
 Changed plan for
Virginia
retirees and employees
Beach, VA
84.7
10.3
574
6,762
City
396
YUSUF & MUSUMECI APPENDIX 2 (Continued)
Response to GASB 45
Govt
ARC
Govt
AAL
Employees and Information about
($million) ($million) Retirees
OPEB Liabilities
(FTE)
Fund with ARC plus
$18.7 million
Baltimore, 214,454
MD(a)
.0
164.6 21,017
28,171  No changes to plans
 Established OPEB trust
fund with an initial
deposit of 250% of ARC
Gaithers No changes to plan
burg, MD
9.7
0.9
27
363
 Established OPEB trust
fund with ARC payment
Rockville,
 No changes to plan
MD
8.8(b)
1.3
18
535
of 166% of the ARC
 No changes to health
Charlotte,
plans
NC
229.7
17.0
1,895
6,577
 Set aside less than $1
million towards liability
Fayetteville, NC
28.0
6.6
436
1,996  Made plan changes
of $34.8 million (44% of
UAAL)
WinstonSalem, NC
79.1
$6.98
1,056
2,660  Made plan changes
City
Notes: (a) Figures are for city government and school district
combined.
(b) As of January 1, 2009.
FALL 2012
CITIZEN PERCEPTIONS OF GENERAL-PURPOSE AND SPECIAL
DISTRICT GOVERNMENTS: A COMPARATIVE ANALYSIS
Larita J. Killian and Kimdy Le*
ABSTRACT. Special districts comprise over 40% of local governments,
prompting debate on the merits of general versus special entities. Previous
research focused on relative cost-efficiency and tended to ignore how
special districts impact government accountability. This study fills a critical
need by testing how type of government (general versus special) impacts
citizen awareness of and familiarity with government, a precondition for
accountability. Drawing from two theoretical perspectives (institutional
reform and public choice), we used survey research to assess familiarity with
the goals and performance and financial practices of local governments in
Indiana. Our study participants were more aware of and familiar with
general than special governments, which supports the institutional reform
perspective more than public choice. We conclude that efforts to improve
accountability should be expanded to include special districts.
INTRODUCTION
Special districts are the growth area of government. Between
1952 and 2007, the number of independent school districts in the
United States decreased by 81% and the number of general purpose
local governments increased by just 5% (all growth was among
municipalities), yet the number of special districts increased over
200%. Per census data, special districts now comprise nearly 42% of
all local governments (U.S. Census Bureau, 1992; 2007a).
The
remarkable proliferation of special districts has prompted scholars
-----------------------* Larita J. Killian, Ed.D, CPA, is an Assistant Professor, Division of Business,
Indiana University at Columbus. Her teaching and research interests are in
governmental accounting, special districts, and accounting pedagogy.
Kimdy Le, Ph.D., is an Assistant Professor of Psychology at Indiana
University at Columbus. His teaching and research interests are in
personality theory, statistics, and measurement.
398
KILLIAN & LE and policymakers to debate the relative merits of general-purpose
and special district governments. But a critical aspect of the debate,
the relationship between local government structure and democratic
accountability, suffers from a lack of empirical evidence. This study
addresses that problem by testing citizen familiarity with the generalpurpose and special district governments that serve them -- a
precondition for government accountability. Of course, the fact that
citizens are aware of and familiarity with the governments that serve
them does not guarantee accountability, but without such awareness
and familiarity, citizens cannot hold governments accountable.
This study uses the U.S. Census Bureau (2002a) definition of
special districts, which includes many entities with “authority” in their
titles. Several factors account for the growth of special districts,
including inflexible or unsuitable municipal annexation laws (Bollens,
1957; Foster, 1997); the desire to circumvent debt limitations or
personnel policies imposed on general-purpose governments
(Bollens, 1957; Smith, 1969; Advisory Commission on
Intergovernmental Relations (ACIR) 1987; Leigland, 1990; Axelrod,
1992); the desire to attract technical experts who prefer to avoid the
glare of partisan general elections (Smith, 1969); and federal
government policies that direct funds to special districts (Smith,
1969; Foster, 1997). Wood (1961) referred to tradition and political
style as factors behind the increase of special districts. For instance,
a growing community may face a critical decision on provision of
water services for a new housing development: the new development
can be annexed into the previous municipality, or a special water
district can be created. Whatever course is chosen sets a precedent
and becomes a learned response for future decisions. “As time goes
on, the alternative first adopted tends to become a governmental
tradition, a political style, and even may crystallize into law” (Wood,
1961, p. 66). Regardless of the explanations for the growth of
special districts, a democracy cannot afford to ignore the impact on
accountability.
Government accountability is a multi-faceted and evolving
concept. Most observers agree that accountability begins with
adequate financial reporting, and in recent years, the need for
performance reporting has gained acceptance (Harris, McKenzie &
Rentfro, 2011). Ingram and Copeland (1981) found that accounting
information is useful to voters in deciding whether to retain
CITIZEN PERCEPTIONS OF GENERAL-PURPOSE AND SPECIAL DISTRICT GOVERNMENTS
399 incumbents. Guo, Fink and Frank (2009) found that financial
reporting is a critical foundation of accountability and that the
contemporary political and economic environment requires a higher
quality of financial disclosure. They conclude, however, that the lack
of norms (such as trend data or comparisons with referent groups)
detracts from the ability of financial reports to enhance accountability
(Guo, Fink & Frank, 2009). Lowery (2001) found that for citizens to
exercise meaningful democratic control, they must have valid
information on what government is doing and how well it is doing it.
He asserted that a fragmented (versus consolidated) government
structure provides more opportunities for public officials to
manipulate reported information and thus weaken democratic
accountability (Lowery, 2001).
While adequate financial and performance reporting is necessary
for accountability, it is not sufficient.
Most definitions of
accountability involve a dynamic exchange of information between
government and citizens.
If the exchange is ineffective,
accountability is not achieved. The Governmental Accounting
Standards Board (GASB) included the notion of active discourse in its
definition of accountability: it includes the citizens’ “right to know”
and to receive facts about government costs and operations that may
“lead to public debate by the citizens and their elected
representatives” (GASB, 1987). Wells and Scheff (1992) identified
six measures of accountability, including “public accountability” which
is indicated by the level of citizen participation in government affairs.
Per Wells and Scheff, other measures of accountability include
market accountability, political accountability, bureaucratic
accountability, legal accountability, and professional accountability.
Chan and Rubin (1987) wrote that governmental accounting and
financial reporting stem from the normative theory of democracy
which commends citizens to be well-informed; further, per demand
models of government, public policies emerge from the direct and
active demands of citizens. Williams (2002) found that accountability
involves more than the provision of technical economic facts; it
implies a moral imperative and “permits making explicit who is
accountable to whom and for what” (2002, 5). Sen (1999)
acknowledged the dynamic nature of accountability when he wrote
that political participation is intrinsic to human well-being; to be
prevented from participation is a “major deprivation.” Further, Sen
(1999) found that public discussion and exchange of information are
400
KILLIAN & LE required for identifying and prioritizing economic needs and for
keeping democratic governments responsible and accountable.
From the above, we can identify key elements of government
accountability. It involves the exchange of information between a
government and its citizens; discussion or debate that serves to
identify and prioritize civic needs; and voter judgments regarding the
responsiveness of government officials. Government accountability is
a growing concern, especially in the current climate where budget
crises are forcing trade-offs and cutbacks in services, and where
states such as Indiana, New York, and Ohio are working to streamline
government and improve responsiveness.1 Efforts to assess or
improve accountability, however, have tended to focus on generalpurpose governments and to by-pass special districts (Killian, 2011).
Our research fills a critical need by extending the investigation of
accountability to special districts.
There are reasons to question the relative accountability of
special districts as compared to general-purpose governments. After
studying compliance with generally accepted accounting principles
(GAAP) among state and local governments, GASB (2008) estimated
that special districts have the lowest rate of financial reporting
compliance of all local governments. Special districts also have a
lower profile with regard to performance reporting. For instance, the
Association of Government Accountants (AGA) posts information
about performance reporting on its website, listing entities that have
recently earned certificates of excellence for Service Efforts and
Accomplishments (SEA) reporting and entities that have voluntarily
submitted citizen-centric reports; special districts are rarely found on
these lists. The U.S. Census Bureau reported that special districts
had the lowest response rate to the organization survey for the 2002
census of governments (U.S. Census Bureau, 2002a). In short, while
accountability is a concern for all types of government, citizens may
be even less familiar with the finances and performance of special
districts. This would magnify the “accountability deficit” for special
districts relative to general-purpose governments.
Most research on general versus special government has
addressed the relative cost-efficiency of providing a given service
through general or special government; questions of accountability
have been vigorously debated but generally ignored in research. This
situation obtains, in part, because it is more difficult to assess
401 accountability than to measure cost-efficiency (Lowery, 2001). We
agree with Lowery (2001) that direct measures of accountability are
difficult to obtain. We can contribute to the debate, however, by
measuring a precondition for accountability: citizen familiarity with
their governments. The key elements of accountability (information
exchange between citizens and government, discussion and debate
about priorities, voter judgments of officials) require citizen
awareness of and familiarity with the governments that serve them.
By comparing citizen familiarity with general-purpose and special
district governments, we can test whether the form of government
impacts this prerequisite for accountability.
THEORETICAL PERSPECTIVES AND RESEARCH QUESTIONS
Several theoretical perspectives have been applied to
comparisons of general-purpose and special district governments
(Foster, 1997). The “institutional reform” and “public choice”
perspectives are most relevant to our research. Both perspectives
compare general-purpose and special district governments along
three dimensions: economy and efficiency of operations, policy
alignment and allocation of resources, and democratic accountability.
While a thorough analysis of these competing perspectives is beyond
the scope of this paper, a brief summary is provided below.
The institutional reform perspective originated with scholars such
as Bolens (1957) and Smith (1969). It arose in response to the
increasing fragmentation and layering of government that became
apparent during the 1950’s and which continues, though at a
reduced pace. Institutional reformers believe that a complex,
fragmented government structure increases the total cost of
government through increased administrative and coordination costs.
Moreover, a fragmented structure confuses citizens and reduces their
ability to hold public officials accountable. Institutional reformers
often propose the consolidation of government entities to reduce
fragmentation and improve efficiency. This perspective enjoyed early
acceptance, though actual efforts to consolidate governments have
usually ended in failure (Faulk and Hicks 2009). In recent decades,
the public choice perspective has been ascendant. However,
scholars such as Barlow (1991) and Lowery (2001) kept the
institutional reform argument alive. Lowery (2001) identified an
emergent, “neoprogressive” perspective that is grounded in the
402
KILLIAN & LE institutional reform tradition but places greater reliance on social
science methods and empirical tools to combat the public choice
argument. Recent efforts at government consolidation, such as
proposals to consolidate or eliminate townships in Indiana (Indiana
Commission on Local Government Reform (ICLGR), 2007)
demonstrate that the institutional reform perspective retains
currency.
In contrast, public choice advocates believe that consolidation
and centralization lead to monopolistic government with the power to
force certain services upon citizens and require them to pay for the
services, even if the services do not correspond to citizen
preferences. The public choice argument stems from the famous
Tiebout hypothesis. Tiebout (1956) argued that there is a market in
governments, just as there is a market for commercial goods and
services. Citizens have the power to “vote with their feet” and move
to the community that offers the basket of government services they
prefer at a price (tax levy) they can afford. Building upon the Tiebout
hypothesis, public choice scholars such as Delorenzo (1981) and
Mehay (1984) argued that the proliferation of governments results in
the best value for consumer-citizens, if not always the lowest price.
For instance, citizens might choose to pay more for higher quality or
increased quantity of service. When institutional reformers claim that
consolidated governments can provide services at less cost due to
economies of scale, public choice scholars reply that small,
specialized governments can also achieve economies through jointcontracting or service agreements. Moreover, Bish and Ostram
(1973) found that some services, such as education and police
protection, are highly sensitive to local conditions and that
consolidation of these services on a large scale could lead to
diseconomies.
After decades of research, the argument between institutional
reform and public choice is inconclusive. Studies can be found to
support both perspectives; this is not surprising given the complexity
of the subject matter, varying local contexts, and variations in state
enabling laws for general and special governments (McCabe, 2000).
Foster (1997) conducted a meta-analysis and reported that the
preponderance of evidence supports the institutional reform
perspective. A continuing problem, however, is that prior research
has emphasized the cost-efficiency dimension while other
403 dimensions, such as the impact of government structure on
accountability, remained virtually unexamined.
Focus on Democratic Accountability
As shown in the introduction, accountability involves the
exchange of information between a government and its citizens;
discussion or debate to identify and prioritize needs; and voter
judgments regarding the responsiveness of government officials. At a
minimum, this requires citizen awareness of which government
entities are responsible for which services. Critics charge that the
proliferation of special districts confuses citizens and detracts from
democratic accountability. For instance, Bollens (1957) referred to
fragmented local government as a three-ring circus that sows
confusion and indifference among citizens, especially regarding
special districts. “Twice removed” from special district officials,
citizens are frequently unable to bring direct action against them
(Bollens, 1957). Axelrod (1992) wrote that special districts insulate
officials from voters; normal, democratic checks and balances do not
apply. Peddie (2007) found that special district elections do not
coincide with general elections, draw little voter interest, and are
usually uncontested. Spitzer (2007) concluded that many citizens
are simply unaware of the existence of special districts.
The opposing, public choice argument is offered by scholars such
as Wagner and Weber (1975), Mehay (1984), and the later ACIR
(1987).2 They conclude that citizens can monitor small, specialized
units of government more effectively than large, general
governments. Wagner and Weber (1975) noted that a fragmented
and overlapping government structure is preferable to having a
reduced number of general governments that can act as monopolistic
(and thus unresponsive) rather than competitive suppliers of services.
Mehay (1984) found that citizens may be less able to monitor
officials in general purpose entities because the (presumably) larger
bureaucracy associated with general governments is harder to
penetrate.
In 1987, ACIR took a nuanced and carefully stated
position: ACIR found that citizens can monitor a single, special district
government with ease, though the proliferation of special districts
exacerbates the accountability challenge.
In summary, institutional reformers and public choice advocates
agree that public awareness of service outcomes and costs, and the
404
KILLIAN & LE ability of voters to judge government officials, are essential to
democratic accountability. They disagree, however, on the optimal
government structure to achieve these ends. Our research addresses
this problem by comparing citizen familiarity with general-purpose
and special district governments.
Research Questions
In testing for comparative awareness and familiarity, we
distinguish between a government’s goals and performance and its
finances. GASB (1994) noted that citizens need information about
government performance as well as government finances. Sanders
(1994) agreed that citizens need both types of information, but noted
that due to “fiscal illusion” citizens are more likely to have
information about performance than finances. For instance, citizens
can often experience or observe the quantity and quality of services
provided, but they may lack information on the cost of those services.
The problem is exacerbated when several small, overlapping taxing
entities are consolidated onto a single county tax bill (Sanders,
1994).
Since there is no objective standard for adequate civic
information, we ask citizens to rate their own level of familiarity with
the governments that serve them.3 This is appropriate for our
research because the absolute level of familiarity is not the issue;
rather, we are concerned with the comparative levels of familiarity
regarding general-purpose and special district governments. We also
want to test whether citizens perceive they have enough information
about the governments that serve them, so we include questions on
the ideal level of familiarity for a given government. Finally, we want
to test whether the disparity between actual and ideal familiarity
differs between general-purpose and special district governments.
These goals lead to the following research questions:
Goals and performance:
Question 1: Do citizens differ in their familiarity with the goals and
performance of general-purpose versus special district
governments?
Question 2: Do citizens differ in their perceptions of ideally how
familiar they should be with the goals and performance of
general-purpose versus special district governments?
405 Question 3: Is the disparity between actual and ideal familiarity with
goals and performance different for general purpose versus
special district governments?
Finances:
Question 4: Do citizens differ in their familiarity with the financial
resources of general purpose versus special district
governments?
Question 5: Do citizens differ in their perceptions of ideally how
familiar they should be with the financial resources of general
purpose versus special district governments?
Question 6: Is the disparity between actual and ideal familiarity with
financial resources different for general purpose versus special
district governments?
METHODOLOGY
The distribution of special districts varies appreciably from state
to state, as do the powers granted to special districts in state
enabling laws (McCabe 2000; Foster, 1997).
This situation
constrains the potential for valid, cross-state research. For this pilot
study, we limited our sample to a single state, choosing the state of
Indiana. In recent years, there have been high-level studies on how to
streamline and improve Indiana government (ICLGR, 2007; Faulk and
Hicks, 2009), and proposals to restructure local government have
been repeatedly introduced into the state legislature. However, these
past studies and proposals usually focused on general-purpose
governments and bypassed special districts. A study that compares
how general and special governments impact a precondition for
accountability brings needed attention to this issue and contributes
to the ongoing policy debate. Further, we live and work in Indiana
and our university strongly encourages service to the region. By
focusing on special districts in Indiana for this initial study, we are
upholding an important institutional value.
Research Instrument
We designed an instrument to measure citizen awareness of the
goals and performance and financial resources of local governments,
shown in Appendix A. Our instrument is adapted from a survey that
406
KILLIAN & LE was commissioned by the Association of Government Accountants
(AGA) in 2008. (AGA has since repeated the survey). The AGA survey
addressed three levels of government (national, state, and local) but
did not differentiate among entities at the local level (AGA, 2008).
Our survey addresses local government exclusively and separates
general purpose from special district entities. Like the AGA survey,
our instrument uses a 10-point Likert-type response scale; this scale
provides ample flexibility to participants yet avoids neutral (numerical
middle) responses. We conducted a validity test of our instrument,
and it was reviewed by academic staff members of the Center for
Evaluation and Education Policy at Indiana University.
Our analysis includes two general-purpose and two special district
governments that serve every citizen of Indiana.4 The generalpurpose entities are counties and townships. Indiana is unique in
that every citizen is served by both county and township government.
Townships are distinct from cities and towns. All citizens are served
by counties and townships, and some are also served by cities or
towns. To minimize bias in research design (i.e., to avoid the more
obscure special districts) we included two of the most common
special districts in the state, solid waste management districts and
soil and water conservation districts. The boundaries of these special
districts coincide with county boundaries, though in a few cases
several adjacent counties are joined in a single, solid waste
management district. Indiana has 92 counties, 92 soil and water
conservation districts, and 68 solid waste management districts (U.S.
Census Bureau, 2007b). The counties, townships, and soil and water
conservation districts are governed by an elected board or council;
solid waste management districts have appointed boards comprised
of officials who were elected to other posts. For instance, one
member of the solid waste management board is appointed from
elected members of the county council.
For each government entity, the survey asks, Are you served by a
(entity)? Participants indicated Yes, No, or Uncertain. The Uncertain
option was included to prevent guessing and because the literature
suggests significant confusion among citizens regarding which
entities serve them (Axelrod, 1992; ICLGR, 2007; Spitzer, 2007; New
York State Commission on Local Government Efficiency and
Competitiveness (NYSCLGEC) 2008; Sanders, 1994).
Thus,
uncertainty is a legitimate response and a forced choice between Yes
407 and No would be invalid. When participants selected No or Uncertain
to being served by an entity, they were prompted to move on to the
next entity. When they selected “Yes” to being served, they were
asked to rate their familiarity with the goals and performance of the
entity and their familiarity with how the entity obtains and uses
financial resources (separate questions). Responses were captured
with a Likert-type response scale where 1 meant “Not at all familiar”
and 10 meant “Very familiar.” Using the same scale, participants
also indicated the ideal level of familiarity the average person should
have with the goals and performance and financial resources of the
given entity.
To ensure participants were not influenced by order effects, each
survey alternated presentation of general and special entities
(general, special, general, special). We also created three different
sequences (A, B, and C) of entity presentation. For both hard-copy
and internet surveys, the three sequences were judiciously
represented. The hard-copy surveys were collated so each sequence
was presented in turn (A, B, C, A, B, C, etc.) For internet data
collection, participants were randomly directed to one of the three
sequences; there were 71 responses for sequences A and B, and 69
responses for sequence C. The research instrument also collected
demographic data: gender and citizenship status were captured using
simple checklists; educational attainment and household income
were captured as interval data using checklists; and participants
entered their zip code and age.
The survey instrument was pretested on 40 diverse participants
to determine whether it was too long, whether it was clear, whether
participants would be willing to answer the questions honestly, and to
examine whether the questions asked were reliable and valid and
whether they correlated with each other in expected ways. Within
each entity, familiarity ratings for goals and performance and
financial resources were moderately to highly correlated, indicating
that people who were familiar with one aspect of a particular
government (goals and performance) were familiar with other aspects
(financial resources). However, there were low correlations between
government entities, indicating that knowledge of one government
did not relate highly to knowledge of other governments. Thus, the
pretest of the survey instrument yielded high internal consistency and
408
KILLIAN & LE some discriminant validity. We would not expect this pattern of
results if participants were answering randomly to the questionnaire.
Participants and Sample Size
We collected responses from voting-eligible residents of Indiana
using hard-copy and internet (electronic) surveys; both formats
contained identical questions. We used a convenience sampling
technique and gathered responses from several venues to obtain as
large and diverse a population as possible. Hard-copy data were
collected from volunteer participants at seven venues (an outdoor
farmers’ market, a bingo game at a fraternal organization, a seniorcitizen center, a large grocery store, a non-profit community services
center, a working-class shopping mall, and a college campus). For
the internet questionnaire, we invited participants to respond via links
in an online newspaper and via emails sent to a college alumni
mailing list. Hard-copy participants received modest food incentives
(snack bars); internet participants received no incentives. We strove
for balance in our data collection: hard-copy collection on a college
campus was balanced with hard-copy collection at a weekly bingo
game, a human services center, and a shopping mall in a workingclass neighborhood. The alumni mailing list from a small public
college (both graduates and drop-outs) was balanced with the mailing
list of a popular regional newspaper.
We collected responses from 444 participants (hard-copy and
internet combined). To limit the survey to voting-eligible residents of
Indiana, we excluded responses from six participants who were less
than 18-years of age; from 75 participants who were not United
States citizens or who provided no citizenship status; and from 16
participants who provided no zip code, provided a non-Indiana zip
code, or provided a zip code found in Marion County. (As explained in
Note 4, residents of Marion County were excluded from this study.)
Finally, we excluded responses from 12 participants whose
educational attainment was less than a high school diploma or
equivalent: due to their low number, they constituted outliers, and we
felt that excluding these outliers was appropriate even though it
exerted upward pressure on educational attainment of the sample.
The resulting data set contains responses from 335 participants, 190
hard-copy and 145 internet, drawn from 21 Indiana counties.
409 We tested for demographic differences between the hard-copy
and internet samples to see if, statistically, they were significantly
different from each other. We conducted an independent samples ttest to test for age differences and chi-square tests to test for
whether gender, educational attainment, and household income were
different for the two samples. The only statistically significant
difference occurred with age: the internet participants (Median age =
52) were a few years younger than the hard-copy participants
(Median age = 55). Generally, the two groups did not differ
demographically. Next, we tested to see whether the two samples
differed from each other on familiarity ratings. There were no
statistically significant differences in familiarity scores between the
hard-copy and internet participants, so we combined them into a
single sample for analysis.
Appendix B summarizes the demographic profile of our sample
and provides comparative data for registered and reported voters in
Indiana, where available. “Reported voters” are those who indicated
having voted in the 2008 general election when responding to the
U.S. Census Bureau’s November 2008 Current Population Survey.
Where Indiana-specific data are not available, we show comparative
data for all registered and reported voters in the United States. The
comparative data in Appendix B are from the U.S. Census Bureau
(2008). The median age of our sample (52.3) falls within the median
age range for registered and reported voters in Indiana (45-64).
Likewise, the gender distribution of our sample (54% female)
corresponds to the gender distribution of Indiana registered and
reported voters (52.8% and 53.2% female, respectively). We do not
have access to education and income data for Indiana voters, so
Appendix B shows education and income data for all registered and
reported U.S. voters. The median household incomes of our hardcopy and internet participants ($50,000-$74,999 and $75,000$99,999, respectively) correspond to the median household incomes
of registered and reported U.S. voters, respectively. The median
income of our total sample ($75,000-$99,999) corresponds to the
median income of all U.S. voters.
The U.S. Census Bureau (2009a) reports that median income for
all Indiana households, not just voters, is $45,000-$49,999. This is
below the median income for all U.S. households ($50,000-59,999),
so we conclude that our participants, whose incomes correspond to
410
KILLIAN & LE all U.S. voters, have incomes somewhat above all Indiana voters. The
educational attainment of our participants is above the educational
attainment for all U.S. registered and reported voters. Since
educational attainment in Indiana is slightly below the national
average (U.S. Census Bureau, 2009b) we conclude that the
educational attainment of our sample is above educational
attainment for all Indiana voters.
In summary, our survey participants correspond to all Indiana
voters in both age and gender distribution; they have household
incomes that correspond to U.S. voters but are somewhat above
household incomes for Indiana voters; and they are more highly
educated than the medians U.S. and Indiana voter. As explained in
the Discussion section, we believe the demographic profile of our
sample strengthens our conclusions.
RESULTS
Awareness of Government Entities
For every government entity on the survey, the initial screening
question is, Are you served by a (entity)? Results for this question are
shown in Tables 1 and 2. All participants included in the analysis are
served by all four entities. Yet as shown in Table 1, only 73
participants (22%) were aware of being served by all four entities.
Twenty-one participants (6.3%) were unaware of being served by any
of the entities, and about half (46%) were aware of being served by
only one or two of the entities.
TABLE 1
Positive (Yes) Responses on Being Served by One, Two, Three, or Four
Entities (Frequency and Percent)
N=
(%)
0 Entity
21
(6.3%)
1 Entity
59
(18%)
2 Entities
95
(28%)
3 Entities
87
(26%)
4 Entities
73
(22%)
Table 2 shows the Yes, No, and Uncertain responses for
individual entities. With a sample of 335 individuals and an analysis
that covers two general and two special governments, there were 670
opportunities for a Yes response on general governments and 670
411 opportunities for a Yes response on special district governments.
However, general entities received a total of 458 Yes responses and
special entities received a total of 344 Yes responses. In the
aggregate, citizens are more aware of being served by generalpurpose than by special district governments.
TABLE 2
Awareness of Being Served by Individual Entities (Frequency and
Percent)
County
N*
314
Township
314
Solid Waste
Management
Soil & Water
Conservation
307
309
YES
269
(85.7%)
189
(60.2%)
203
(66.1%)
141
(45.6%)
NO
22
(7%)
65
(20.7%)
43
(14%)
45
(14.6%)
UNCERTAIN
23
(7.3%)
60
(19.1%)
60
(19.5%)
123
(39.8%)
Note: * Number of valid responses varies because some participants
did not respond to prompts regarding every entity.
The aggregate pattern of awareness (i.e., citizens are more aware
of being served by general than special governments) does not apply
for each individual entity. Awareness of being served ranges from
85.7% for counties to 45.6% for soil and water conservation districts.
However, 60.2% of respondents were aware of being served by
townships while 66.1% were aware of being served by solid waste
management districts. Interestingly, the highest No response was for
townships, with 20.7% incorrectly saying they were not served by
townships. The Uncertain responses for townships and solid waste
management districts were comparable. Soil and water conservation
districts received the highest “Uncertain” response (39.8%).
Familiarity with Government
Participants who responded “Yes” to being served by a specific
entity were prompted to answer questions regarding their familiarity
with that entity. Table 3 shows mean familiarity scores aggregated by
412
KILLIAN & LE type of government (general versus special), and Table 4 shows mean
familiarity scores for individual entities. Since there is no objective
standard for the appropriate level of familiarity, a single familiarity
score lacks significance in isolation, but comparative scores allow us
to assess relative familiarity with general and special governments.
Tables 3 and 5, which show aggregate results, contain data from
citizens who recognized being served by at least one general and at
least one special entity. This ensures a robust comparative analysis
of familiarity by type of government.
As shown in Table 3, participants who recognize being served by
at least one form of general and at least one form of special
government are more familiar with general governments, and the
differences are statistically significant. On a 10-point scale, the mean
familiarity with the goals and performance of general governments is
4.84 while the mean for special district governments is 3.98. The
mean familiarity with how governments obtain and use financial
resources is 4.76 for general governments and 3.35 for special
district governments.
TABLE 3
Familiarity Ratings by Type of Government (General versus Special)
Familiarity with Goals and Performance of
Significance Test
(Entity Type)
N
Mean Std. Deviation
General 233
4.84
2.28
t(232) = 5.98, p < .05
Special
233
3.98
2.29
Familiarity with How (Entity Type) Obtains
Significance Test
and Uses Financial Resources
N
Mean
Std. Deviation
General 232
4.76
2.36
t(232) = 10.43, p < .05
Special
232
3.35
2.11
Note: To be included in Table 3 analysis, participants must have
responded “Yes” to at least one general entity and “Yes” to at
least one special district entity. Therefore, the N is smaller than
the total number of participants.
413 When individual entities are considered, in Table 4, the direction
of results is the same: for both goals and performance and financial
resources, citizens report more familiarity with general than with
special entities. Participants are most familiar with counties, which
received the highest, mean familiarity scores for both goals and
performance (5.30) and financial resources (5.25). The familiarity
scores for townships, on both goals and performance (4.36) and
financial resources (4.3) are lower than for counties. Still, for both
goals and performance and financial resources, participants are more
familiar with townships than with the special districts. These results
have face validity: counties score highest on awareness of being
served (Table 2) as well as familiarity (Table 4), while soil and water
conservation districts score lowest on awareness of being served and
on both familiarity measures.
TABLE 4
Familiarity Ratings for Individual Entities
Familiarity with Goals and Performance of (Entity)
N
Mean
Median
Std. Deviation
County
268
5.30
5
2.39
Township
188
4.36
5
2.63
Solid Waste Mgt. 202
4.31
5
2.63
Soil & Water
141
3.62
3
2.40
Familiarity with How (Entity) Obtains and Uses Financial Resources
N
Mean
Median
Std. Deviation
County
268
5.25
5
2.53
Township
189
4.3
4
2.59
Solid Waste Mgt. 202
3.55
3
2.55
Soil & Water
141
3.18
3
2.28
Tables 5 and 6 show results for the ideal level of familiarity “the
average person” should have with various governments. Per Table 5,
the mean ideal familiarity with goals and performance of general
governments is 7.50 while the mean for special district governments
is 6.85. The mean ideal familiarity with the financial resources of
general governments is 7.64 while the mean ideal for special district
governments is 6.87. These differences are statistically significant,
414
KILLIAN & LE yet they converge more than the aggregate scores for actual
familiarity.
TABLE 5
Ideal Familiarity Ratings by Type of Government (General versus
Special)
Ideal familiarity with Goals and Performance
of (Entity Type)
N
Mean Std. Deviation
General
233
7.50
1.92
Special
233
6.85
2.06
Ideal familiarity with How (Entity Type) Obtains
and Uses Financial Resources
General
232
7.64
1.90
Special
232
6.87
Significance Test
t(232) = 6.48,
p<.05
Significance Test
t(231) = 7.65,
p<.05
2.14
Note: To be included in Table 5 analysis, participants must have
responded “Yes” to at least one general entity and “Yes” to at
least one special district entity. Therefore, the N is smaller than
the total number of participants.
Table 6 shows the ideal familiarity ratings for individual entities.
In comparing the data in Tables 4 and 6, two important points should
be noted. First, whether the topic is goals and performance or
financial resources, and whether referring to general or special
entities, citizens believe the ideal level of familiarity is higher than
their actual level of familiarity. Second, the mean scores in Table 4
vary more than the mean scores in Table 6: there is more variation in
actual than in ideal familiarity. Participants tend to converge in their
perceptions of ideal levels of familiarity, but their actual scores are
more varied due to their lower familiarity with special districts.
Table 7 shows the results of gap analysis. The familiarity gap for
each entity is computed by subtracting the actual familiarity score
(Table 4) from the ideal familiarity score (Table 6). The familiarity
gaps are statistically significant. The smallest gap (2.36 on a 10point scale) pertains to goals and performance for counties. The
415 TABLE 6
Ideal Familiarity Ratings for Individual Entities
Ideal Familiarity with Goals and Performance of (Entity)
N
Mean
Median Std. Deviation
County
269
7.66
8
1.90
Township
188
7.53
8
2.04
Solid Waste Mgt.
202
7.05
7
2.12
Soil & Water
141
6.99
7
2.22
Ideal Familiarity with How (Entity) Obtains and Uses
Financial Resources
County
269
7.88
8
1.93
Township
188
7.65
8
2.11
Solid Waste Mgt.
202
6.90
7
2.30
Soil & Water
141
7.14
8
2.45
TABLE 7
Gap Analysis: Mean Familiarity minus Mean Ideal Familiarity
Gap Between Actual and Ideal Familiarity* (on 10-point scale)
Goals and Significance Test Financial Significance Test
Resources
Performance
County
2.36
Township
3.18
Solid Waste
Management
Soil & Water
2.74
3.38
t(267) = 15.77,
p < .05
t(186) = 15.06,
p < .05
t(200) = 14.61,
p < .05
t(140) = 15.32,
p < .05
2.63
3.36
3.35
3.97
t(267) = 16.33,
p < .05
t(187) = 15.46,
p < .05
t(201) = 17.22,
p < .05
t(140) = 16.22,
p < .05
Note: *Perceived information gaps are computed using data from
Tables 5 and 7.
largest gap (3.97) relates to how soil and water conservation districts
obtain and use financial resources. For goals and performance,
participants report a larger familiarity gap for townships than for solid
waste management districts (3.18 and 2.74, respectively), though
these entities have similar familiarity gaps on financial resources
(3.36 and 3.35, respectively).
416
KILLIAN & LE Table 7 reveals several important points. For every entity, the
familiarity gap related to financial resources is greater than the gap
for goals and performance. Further, the familiarity gaps for townships
resemble special districts as much as they resemble counties.
Finally, while participants place the “ideal” bar lower for special
districts than for general governments, they perceive significant
familiarity gaps for all entities in this analysis.
DISCUSSION
For citizens to hold their governments accountable, they must be
aware of and familiar with the governments that serve them.
Awareness and familiarity do not guarantee accountability, but where
they are absent, accountability cannot ensue. We compared citizen
familiarity with general purpose and special district governments in
Indiana. The participants in our sample correspond to Indiana voters
in both age and gender distribution; have incomes that correspond to
all U.S. voters but are above the median for Indiana voters; and have
educational attainment that is above the median for Indiana and U.S.
voters. Since participation in political processes, whether voting or
more active behavior, is positively associated with age, education,
and income (Lijphart, 1997, U.S. Census Bureau, 2004 and 2008),
the demographic profile of our participants strengthens the results.
On measures of familiarity with the governments that serve them, it is
reasonable to expect our participants to be as familiar as the general
population, if not more so.
We gathered responses using a pre-tested survey instrument.
Table 1 indicates that the level of confusion among citizens is high
and the awareness of being served by various local governments is
low. Only 22% of participants recognize being served by all four
entities, and less than half (48%) recognize being served by at least
three of the four entities. Confusion is associated with both general
and special governments, though Table 2 indicates that in the
aggregate, citizens are more aware of being served by generalpurpose than by special district governments. The aggregate results
do not apply to all individual entities; participants are more likely to
recognize being served by solid waste management districts than by
townships. The overall level of confusion is disconcerting, given that
the boards or councils of these entities are comprised of elected
officials, that three of the four entities can levy property taxes, and
417 that the fourth (soil and water conservation districts) can levy special
assessments.
In the aggregate (Table 3) participants who are aware of being
served by at least one general-purpose and at least one special
district government are more familiar with general-purpose
governments. This finding applies for both goals and performance
and financial resources, and the differences are statistically
significant. When individual governments are considered (Table 4)
the pattern holds: participants are more familiar with the goals and
performance and financial resources of general-purpose
governments. Tables 3 and 4 also support Sanders’ (1994) thesis on
“fiscal illusion,” discussed earlier. In the aggregate and for individual
entities, participants are less familiar with government finances than
with government goals and performance.
In terms of the ideal level of familiarity (Tables 5 and 6)
participants set the bar higher for general-purpose entities. Across
the board, however, participants want more information about the
governments that serve them. There is more convergence on ideal
than actual levels of familiarity. Ideally, participants want their
familiarity with special districts to more closely resemble their
familiarity with general-purpose governments.
Table 7 shows the comparative gaps between actual and ideal
familiarity. An important finding for government accountants and
financial managers is that for each entity in this study, the familiarity
gap on how the entity obtains and uses financial resources exceeds
the gap on goals and performance.
It is important to note that this study intentionally includes two of
the most prominent types of special districts in the state.5 Solid
waste management districts and soil and water conservation districts
serve every citizen in Indiana and have boundaries that correspond
with county boundaries. Thus, we expect them to be among the most
familiar of the 25 types of special districts in the state (U.S. Census
Bureau, 2002b). The recognition and familiarity levels for the special
districts in this study do not bode well for the more obscure special
districts.
This research has near-term, practical significance. Every year
from 2004 through 2011, bills were introduced into the Indiana
legislature to reform or eliminate townships. In turns, the draft
418
KILLIAN & LE legislation called for consolidation of smaller townships into larger
entities, or elimination of townships and transfer of their
responsibilities to counties (Indiana Township Association (ITA,
2011). The drive to consolidate or eliminate townships is motivated
by a desire to make government more visible and accountable and to
reduce operating costs (ICLGR, 2007; Faulk and Hicks, 2009).
Township defenders have managed to block reform efforts for eight
consecutive years, and the ITA and other associations maintain a
strong defense of township government. Yet only 60% of the
participants in this study, whose demographic profile places them
among the more politically active citizens, recognize being served by
townships. This suggests that townships may be unable to mobilize
sufficient public support to withstand reform efforts indefinitely.
CONCLUSIONS
The results of this study support the institutional reform
perspective more than the public choice perspective. Public choice
advocates assert that citizens can monitor smaller, specialized
governments more effectively than larger, generalized governments,
but our results contradict this claim. Participants were more familiar
with the goals and performance and financial resources of generalpurpose than special district governments. Since this study included
two of the most prominent special districts in the state, we expect the
results would be even more pronounced for less prominent special
districts. Further, institutional reformers assert that the proliferation
of special districts leads to confusion among citizens as to which
governments serve them, and we found this to be true in the
aggregate: participants were more likely to recognize being served by
the general-purpose than the special district governments. This was
not always true at the individual level: participants were more likely to
recognize being served by solid waste management districts than by
townships.
Citizens, public officials, and scholars who want to improve
government accountability should pay more attention to special
districts. At the very least, they should exert pressure on specialdistricts to publish financial reports that comply with GASB standards.
As noted earlier, special districts have the lowest compliance rate for
all local governments (GASB 2008). Of course, compliance needs to
be improved among all local governments. Efforts to increase
419 performance reporting and citizen-centric reporting, such as the
programs sponsored by the Association of Government Accountants
(AGA), should be expanded to include special districts. Since external
reports are of limited use without norms to support trend analysis and
comparisons with other entities (Guo, Fink and Frank, 2009),
scholars could make a significant contribution by developing norms,
or at least regional benchmarks, for special districts as well as
general governments. We note, however, that since accountability
requires a dynamic exchange between citizens and their governments
(discussed in the Introduction), good reporting is necessary but not
sufficient: it must be accompanied by dialog and participation.
We could add that civics education in public schools and other
voter education programs (such as programs sponsored by the
League of Women Voters) need to be more effective in promoting
awareness of and familiarity with various governments. Ultimately,
however, the problem may be structural. This study shows that it is
challenging for citizens to monitor (even be aware of) multiple local
governments, and that they are less familiar with special districts
than general-purpose governments. As citizens and public officials
consider structural changes to improve accountability and costefficiency, and as they weigh proposals to consolidate local
governments, they should examine all local governments. Thus far,
Indiana has devoted most of its time and energy to townships. It is
time to examine the role and impact of special districts.
Limitations
The participants in our sample resemble “all Indiana voters” in
age and gender and exceed “all Indiana voters” in income and
educational attainment. As discussed earlier, we believe this
strengthens our conclusions. To the extent that our participants are
unaware of or unfamiliar with local governments, we expect the
median Indiana voter to be even more so.
The legal, political, and economic contexts for local government
and the powers granted to general and special governments vary
from state to state (McCabe, 2000; Foster, 1997). This limits the
potential for cross-state conclusions and creates the need for local
and regional research. Our research has direct implications for
Indiana, and can inform and motivate research in other states. While
the results cannot be generalized to other states, our research
420
KILLIAN & LE instrument can be adapted to measure awareness of and familiarity
with local governments elsewhere.
NOTES
1. The Indiana Commission on Local Government Reform was
established in 2007, as was the New York State Commission on
Local Government Efficiency and Competitiveness.
Ohio
established its Commission on Local Government Reform and
Collaboration in 2008.
2. Throughout its existence, the U.S. Advisory Commission on
Intergovernmental
Relations
(ACIR)
adopted
differing
perspectives on special districts. In its 1987 report, ACIR
endorsed policies consistent with the public choice perspective.
3. No objective norms have been established for how much citizens
“should know” about government performance and finances,
though secondary education standards might be a start. Selfreported familiarity is adequate for our research goals. Citizen
perceptions would be inadequate for comparing actual costefficiencies of various governments.
4. Since 1970, the City of Indianapolis and Marion County have
been merged under Uni-Gov. Marion County is included in the
total count of Indiana counties (92), but due to Uni-Gov, Marion
County does not share the same characteristics as all other
Indiana counties. Therefore, residents of Marion County are
excluded from this study.
5. We asked the Associate Director of the Indiana Advisory
Commission on Intergovernmental Relations to help us select the
most common special districts to minimize inherent bias. She
suggested solid waste management districts, soil and water
conservation districts, and library districts (Palmer 2009).
Library districts were excluded from this analysis because they do
not serve every citizen, as do the other entities.
ACKNOWLEDGEMENTS
We are indebted to Howard Frank, Patricia Patrick, and to
anonymous reviewers for beneficial suggestions and for some
references in this paper.
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APPENDIX A
Research Instrument
Are you served by a
select your answer)
a.
b.
c.
(Entity) government?
(Circle the appropriate letter to
Yes (please answer the questions below)
No (skip to next page)
Uncertain (skip to next page)
1. How familiar are you with the goals and performance of your (entity)?
Not at all
Very
Somewhat Familiar
familiar
familiar
1
2
3
4
5
6
7
8
9
10
2. Ideally, how familiar should the average person be with the goals and
performance of your (entity)?
Not at all
Very
Somewhat Familiar
familiar
familiar
1
2
3
4
5
6
7
8
9
10
3. How familiar are you with how your (entity) obtains and uses financial
resources?
Not at all
familiar
1
2
Somewhat Familiar
3
4
5
6
7
8
9
4. Ideally, how familiar should the average person be with how
obtains and uses financial resources?
Not at all
Somewhat Familiar
familiar
1
2
3
4
5
6
7
8
9
Very
familiar
10
your (entity)
Very
familiar
10
426
KILLIAN & LE Demographic Data
This information will tell us about the citizens who complete the survey. If
you are not comfortable with providing any of the information, you may leave
it blank.
Are you male or female?
Male
Female
Please enter your Zip Code __________
What is your age in years? __________
What is your household income, per year? (Check appropriate box)
Less than $15,000
$15,000 to $24,999
$25,000 to $34,999
$35,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 or over
Prefer not to answer
Place a check next to your education level.
Less than high school
Some high school
High school diploma or equivalent (e.g., GED)
Some college, but no college degree
Associate's degree
Bachelor’s degree
Some graduate school, but no graduate degree
Graduate degree (e.g., M.S., M.D., and Ph.D.)
Prefer not to answer
What is your citizenship status?
Note: Identical questions were repeated for each type of government.
Demographic questions appeared at the end of the survey. For the
online survey, “skip logic” automatically progressed to the next entity if
the participant selected No or Uncertain to being served by the given
entity.
427 APPENDIX B*
Demographic Data for Survey Participants and Registered and Reported
Voters
Percent (%) Educational Attainment
High School or Some College Bachelor’s Advanced
Equivalent
or Associates Degree
Degree
15.8
35.3
25.8
23.2
6.2
16.5
42.8
34.5
11.6
27.2
33.1
28.1
Hard-Copy Sample
Internet Sample
Total Sample
U. S. Citizen
Permanent resident, but not citizen
Other
Indiana Registered
Indiana Voters
All U.S. Registered
28.6
All U.S. Voters
27.3
31.4
31.6
Median Household Income
Hard-Copy Sample
Internet Sample
Total Sample
Indiana Registered
Indiana Voters
All U.S. Registered
All U.S. Voters
$50,000-74,999
$75,000 - 99,999.
$75000-99,000
21.1
22.4
10.9
11.8
Gender (%)
M
F
42
58
51
49
46
54
47.2 52.8
46.8 53.2
Median
Age
55
52
52.3
45-64
45-64
$50,000-74,999
$75,000-99,999
*Descriptions for Appendix B Data Elements.
Indiana Voters and All U.S. Voters are those who reported voting in the 2008
general election in response to questions in the U.S. Census Bureau’s
November 2008 Current Population Survey (CPS).
Data for registered and reported voters in Indiana, and for all U.S. registered
and reported voters, were extrapolated from various tables in the U.S.
Census Bureau (2008), Voting and Registration in the Election of November
2008 - Detailed Tables. The specific tables are identified below. Where
Indiana-specific data are not available, we report all U.S. data.
Educational Attainment. Education attainment of our sample (shown for
hard-copy, internet, and total) can be compared to educational attainment of
all U.S. registered and reported voters. The “All U.S.” percentages are
calculated from Table 5: Reported Voting and Registration, by Age, Sex, and
Educational Attainment. We do not have access to data for education
attainment for registered and reported voters in Indiana.
428
KILLIAN & LE Household Income. Median household income of our sample (shown for
hard-copy, internet, and total) can be compared to median household
income for all U.S. registered and reported voters. The “All U.S.” income is
from Table 9. Reported Voting and Registration of Family Members, by Race,
Hispanic Origin and Family Income: November 2008.
Gender. Gender of our sample (shown for hard-copy, internet, and total) can
be compared to gender of registered and reported voters in Indiana. The
Indiana data is from Table 4b: Reported Voting and Registration of the
Voting-Age Population, by Sex, Race and Hispanic Origin, for States.
Age. Participants in our sample (shown for hard-copy, internet, and total)
entered their age in years into a blank box on the survey. The median age
for our sample can be compared to median age for registered and reported
voters in Indiana, which is provided as interval data in Table 4c: Reported
Voting and Registration of the Total Voting-Age Population, by Age, for States.
FALL 2012
TWO ACCOUNTING STANDARD SETTERS: DIVERGENCE CONTINUES
FOR NONPROFIT ORGANIZATIONS
Mary Fischer and Treba Marsh*
ABSTRACT: The ability of financial statement users, investors, donors and
academic researchers to compare financial information issued by nonprofit
universities, hospitals, fund-raising organizations and government agencies
is affected by their understanding of current accounting recognition and
reporting guidance. Public nonprofit organizations report different financial
results from private nonprofit organizations. This study looks at the events
that brought about the divergence in nonprofit financial accounting
recognition and reporting for higher education institutions, discusses specific
differences, and offers a look at additional changes in recognition and
reporting for the sector currently underway.
INTRODUCTION
Prior to the establishment of the Governmental Accounting
Standards Board (GASB), financial recognition and reporting of both
public and private not-for-profit organizations, i.e., colleges and
universities, hospitals, utilities and fundraising organizations
remained, similar in most respects (Fischer 1997). Since the mid1990s, much has been written about the divergence and growing
recognition and reporting differences created by having two standard
setters for the same industry (Van Daniker, 2009; Menditto, &
-----------------------* Mary Fischer, Ph.D., CGFM, is Professor of Accounting, College of
Business and Technology, The University of Texas at Tyler. Her research
interests include financial accounting, nonprofit and governmental
organizations, auditing and accounting education. Treba Marsh, DBA, CPA,
is Professor of Accounting and Director of Gerald W. Schlief School of
Accountancy, Stephen F. Austin State University. Her research interest
includes state and local public finance, financial accounting, internal
controls and public budgeting.
430
FISCHER & MARSH
Gordon, 2008; Brown, 2005; Goldstein & Menditto, 2005; Robert, &
Mohaghegh, 2004; Fischer et al., 2004; Nelson et al., 2003;
Crawford, 2003; Fischer, & Gordon, 2002; Engstrom, & Esmond-Kiger
1997; Smith et al., 1997; Fischer, 1997). Accounting standards and
guidance developed by the GASB and the Financial Accounting
Standards Board (FASB) create differences for the public and private
nonprofit sector accounting recognition and reporting. This paper
reviews some of the history of the recognition and reporting
divergence for the higher education nonprofit sector, identifies and
discusses specific differences, and presents comments on current
research agendas at the Boards that could lead to new divergence.
BACKGROUND
The American Institute of Certified Public Accountants’ (AICPA)
College and University Audit Guide (1973) gave post-secondary
institutions the fund-based reporting model. The model began
changing in the 1980s when the FASB began its not-for-profit agenda
that identified several projects. Those projects resulted in the
issuance of Statement of Financial Accounting Standard (SFAS) No.
93 that addresses depreciation (FASB, 1987), SFAS No. 116 that
provides contribution guidance (FASB, 1993a), SFAS No. 117 that
establishes the reporting model (FASB, 1993b), SFAS No. 124 that
directs investment recognition (FASB, 1995), SFAS No. 136 that
provides guidance to recognize funds held by others (FASB, 1999),
and SFAS No. 164 that provides guidance for not-for-profit
combination and merger reporting (FASB, 2009a).
The GASB was created in 1984 and soon after began issuing
accounting standards affecting public colleges and universities.
GASB Statement (GASBS) No. 8 (1988) addresses the recording and
reporting of depreciation and GASBS No. 9 (1989) concerns the
statement of cash flows. Both standards were reactions to standards
issued by the FASB. GASBS No. 35 (1999b) was a landmark event in
terms of higher education reporting and occurred as a consequence
of the GASB abandoning the effort to develop a separate reporting
model for higher education and electing to include public colleges
and universities in the GASBS No. 34 model. GASBS No. 34 (1999a)
identifies three options for reporting: business-type activities (BTA)
that charge a fee for their services, governmental, and governmental
TWO ACCOUNTING STANDARD SETTERS FOR NONPROFIT ORGANIZATIONS
431
with a BTA. Most colleges and universities report as a BTA because
(1) it is straightforward and (2) it matches well—though not perfectly—
the reporting display followed by private institutions. The differences
discussed in this paper are based on the GASB BTA reporting model.
Some differences identified are not necessarily specific FASB
action differences but result from actions by the AICPA addressing
FASB guidance. The AICPA proposes guidance; the FASB and/or
GASB review(s) the guidance and while they may not endorse the
proposition, unless they object, the guidance becomes GAAP. In that
situation, it is as if the FASB or GASB has issued the guidance. The
AICPA reacted to the issuance of SFAS Nos. 116 and 117 (FASB,
1993a; 1993b) that fundamentally changed financial reporting for
private higher education institutions, by issuing a new audit guide in
1996. The audit guide marked the official departure from the fundbased model and the introduction of an entity-based reporting model
for not-for-profits. The capitalization of software is an example of
AICPA (1997) action and non-action by the accounting boards that
resulted in the establishment of GAAP guidance. Although different
levels of GAAP exist, all guidance must be followed when preparing
financial statements in order to obtain an unqualified audit opinion.
With the adoption of the Sarbanes Oxley Act (2002), the role of
the AICPA in accounting guidance development has been significantly
reduced. The act created a five-member Public Company Accounting
Oversight Board (PCAOB) that has the authority to set and enforce
auditing, attestation, quality control and ethics guidance for public
companies. The act also directed the FASB to assume the
responsibility for issuing accounting guidance and the AICPA to no
longer issue authoritative statements of position.
PHILOSOPHY OF THE BOARDS
Examining the philosophical approaches the Boards have taken
may help to understand the various differences in standards issued
by the two Boards. These philosophical approaches can be found in
each Board’s respective concept statements. Concept statements
are not accounting standards to which preparers must adhere when
issuing financial statements. Instead, taken as a whole, concept
statements form the framework used by the Boards when developing
accounting standards.
432
FISCHER & MARSH
The overall focus of the FASB is decision utility, i.e., attempting to
provide the best information to influence decisions by investors,
creditors, and others interested in commercial and not-for-profit
activity. The FASB conceptual framework includes:
- Objectives of Financial Reporting by Business Enterprises,
- Qualitative Characteristics of Accounting Information,
- Objectives of Financial Reporting by Nonbusiness Organizations,
- Recognition and Measurement in Financial Statements of
Business Enterprises,
- Elements of Financial Statements, and
- Using Cash Flow Information and Present Value in Accounting
Measurement.
The GASB’s overall focus is accountability as opposed to decision
utility. This results from the heavy reliance on taxpayer support of
governmental entities. The GASB conceptual framework includes:
- Objectives of Financial Reporting,
- Service Efforts and Accomplishments Reporting,
- Communication Methods, and
- Elements of Financial Statements.
Future projects listed on the GASB agenda (www.gasb.org) continue
to address recognition and measurement.
The line between decision utility and accountability is blurred and
the Boards’ propensity toward one does not make it exclusive of the
other. Rather, it is a continuum on which the Boards operate. For
example, the FASB in issuing FASB Statement No. 136 (1999),
Transfers of Assets to a Not-for-Profit Organization or Charitable Trust
That Raises or Holds Contributions for Others, was focused just as
much on accountability as on decision utility. Similarly, the GASB’s
efforts on other postemployment benefits, which resulted in GASB
Statement No. 45 (2004), Accounting and Financial Reporting by
Employers for Postemployment Benefits Other Than Pensions, clearly
is focused as much on decision-making as it is accountability.
433
AREAS OF POTENTIAL DIFFERENCES
There are four major types of differences:
recognition,
measurement, display, and disclosure. Recognition differences deal
with whether or not an item appears in a financial statement. An
example is contributed services. SFAS No. 116 (1993a) addresses
contributed services while GASBS No. 33 (1998) does not.
Measurement differences refer to how items are included in the
financial statements—at what amount and based on which criteria.
For example, both the FASB and the GASB require recognition of
pension liabilities but they have established different methods for
measuring the amount to be recognized. An example of a display
difference is the GASB requirement for a classified balance sheet that
separates assets and liabilities into current and noncurrent
components. The FASB requires listing assets and liabilities in order
of liquidity, but does not require separating them into current and
noncurrent categories. The Boards have significantly different
requirements with respect to required note disclosures that are not
addressed in this paper.
EXHIBIT Ia
Sample State University
Statement Of Net Assets
June 30, 2010
ASSETS
Current Assets
Cash and equivalents
$
76,975
Short term investment
78,856
Accounts receivable
33,891
Notes receivable
Prepaid expenses
Total current assets
Noncurrent Assets
Investments - bond trustee
Endowment investments
Pledge receivable
2,589
4,515
196,826
47,032
158,621
2,152
434
FISCHER & MARSH
EXHIBIT Ia (Continued)
Notes receivable
Property and equipment
Other assets
Total noncurrent assets
TOTAL ASSETS
LIABILITIES
Current Liabilities
Accounts payable and accrued liabilities
Deposits and deferred revenue
Accrued benefits - current portion
Long-term debt - current portion
Total current liabilities
Noncurrent Liabilities
Life income agreements
Government loan advances
Accrued benefits
Long-term debt
Total noncurrent liabilities
TOTAL LIABILITIES
NET ASSETS
Invested in capital assets net of related debt
Restricted nonexpendable
Endowment – campus
Endowment - affiliated organizations
Restricted expendable
Endowment gains
Funds functioning as endowments
Life income and annuity contracts
Gift, grants and contracts
Loan funds
Affiliated organizations
Unrestricted net assets
TOTAL NET ASSETS
$
$
18,746
439,120
2,282
667,953
864,779
43,469
24,514
7,397
1,938
77,318
$
1,526
17,214
67,589
205,376
291,705
369,023
$
279,974
38,839
66,230
$
26,217
6,495
787
18,319
5,296
6,745
46,854
495,756
435
EXHIBIT Ib
Sample University
Statement Of Financial Position
June 30, 2010
(in Thousands)
ASSETS
Cash and equivalents
Short term investments
Accounts receivable
Note receivable
Pledge receivable
Investments
Investments held by others
Prepaid expenses
Property and equipment
Other assets
TOTAL ASSETS
LIABILITIES
Accounts payable
Deposits and deferred revenue
Compensated absences
OPEB and other benefits payable
Split-interest contracts
Notes and bonds payable
U.S. Government advance
TOTAL LIABILITIES
NET ASSETS
Unrestricted
Temporarily restricted
Permanently restricted
TOTAL NET ASSETS
$
$
$
$
82,158
120,705
33,891
21,335
15,810
87,789
70,832
4,515
439,120
2,282
878,437
43,469
24,514
13,534
61,452
1,526
207,314
17,214
369,023
$
326,828
67,517
115,069
$
509,414
436
FISCHER & MARSH
EXHIBIT IIa
Statement of Revenue, Expenses
and Changes To Net Assets
For Fiscal Year Ended June 30, 2010
(in Thousands)
Operating Revenue
Tuition and Fees
Discount Allowances
Net Tuition and Fees
Government Grants and Contracts
Private Grants and Contracts
Sale of Auxiliary Services
Other Operating Revenue
Total Operating Revenue
Operating Expenses
Salaries and Wages
Fringe Benefits
Supplies and Services
Utilities
Grant Subcontracts
Depreciation
Total Operating Expenses
Operating Loss
Non-Operating Revenue (Expense)
State Appropriations
Non-Capital Gifts
Investment Income
Interest Expense
Total Non-Operating Revenue
Net Income before Capital Items
Capital and Other Items
State Appropriations for Capital
Capital Asset Gifts
Endowment Gifts
Endowment Gains, (losses)
and Additions
Total Capital Deductions
Net Increase/Decrease in Net Assets
Net Assets - Beginning of Year
Net Assets - End of Year
$
$
193,491
-51,773
141,718
86,138
14,832
103,442
20,049
366,179
235,141
76,826
101,651
12,498
13,510
26,895
466,521
-100,342
79,134
11,989
16,494
-5,840
101,777
1,435
5,687
1,206
10,314
$
-26,922
-9,715
-8,280
504,036
495,756
437
EXHIBIT IIb
Sample University
Statement of Activity
(in Thousands)
Revenue
Tuition and Fees
Discount Allowances
Net Tuition and Fees
Government Grants and
Contracts
Private Grants and Contracts
Private Gifts
Other Investment
Income/Losses
Sale of Auxiliary Services
Other Operating Revenue
Total Revenue
Reclassifications
Net Revenue
Expenses
Salaries and Wages
Fringe Benefits
Supplies and Services
Utilities
Grant Subcontracts
Depreciation
Total Operating Expenses
Change in Net Assets
Net Assets - Beginning of Year
Net Assets - End of Year
Temporarily Permanently
Unrestricted Restricted Restricted
Net Assets Net Assets Net Assets
Combined
Total
$278,312
-31,773
246,539
$278,312
-31,773
246,539
66,138
66,138
11,989
$1,206
3,658
$20,314
13,195
23,972
11,621
-7,439
222
4,404
20,536
20,536
103,442
20,049
477,739
0
477,739
20,536
94,533
$115,069
235,141
76,826
107,491
12,498
13,510
26,895
472,361
5,378
504,036
$509,414
103,442
20,049
459,778
11,906
471,684
235,141
76,826
107,491
12,498
13,510
26,895
472,361
-677
327,505
$326,828
-2,575
-11,906
-14,481
-14,481
81,998
$67,517
438
FISCHER & MARSH
EXHIBIT IIIa
Statement Of Cash Flows
(in Thousands)
Cash Flows from Operating Activities
Tuition and fees
Grants and contracts
Sales of auxiliary services
Other operating revenue
Payments to employees
Payments for employee benefits
Payments to suppliers and vendors
Net cash flow from operating activities
Cash Flows from Noncapital Financing Activities
State appropriations
Noncapital gifts
Net cash flow from noncapital financing activities
Cash Flows from Capital Financing Activities
Capital gifts, grants and contracts
Endowment gifts
Capital assets acquired
Proceeds from sales of capital assets
New debt proceeds
Debt principal payments
Debt interest payments
Net cash flow from capital financing activities
Cash Flows from Investing Activities
Investment sales and maturities
Investment acquisitions
Investment income
Net cash flow from investing activities
Decrease in cash and cash equivalents
Beginning cash and cash equivalents
Ending cash and cash equivalents
$
143,178
95,714
104,614
20,406
-232,781
-72,121
-117,214
-58,204
79,134
9,313
88,447
3,885
1,206
10,314
-74,634
198
43,153
-46,447
-9,169
-71,494
$
100,771
-97,251
13,250
16,770
-24,481
101,456
76,975
439
EXHIBIT IIIa (Continued)
Reconciliation of Operating Loss to Net Cash Used by
Operating Activities
Operating loss
Depreciation
Changes in current assets and liabilities
Accounts receivable
Notes receivable
Prepaid expenses and other current assets
Deposits and deferred revenues
Accrued employee benefits
Net Cash Used in Operating Activities
$
$
-100,342
26,895
-7,715
276
320
12,791
4,866
4,705
-58,204
EXHIBIT IIIb
Sample University
Statement of Cash Flows
(in Thousands)
Cash Flows from Operating Activities
Change in net assets
Depreciation
Changes in current assets and liabilities
Accounts receivable
Notes receivable
Prepaid expenses and other current assets
Deposits and deferred revenues
Accrued employee benefits
Net cash flow from operating activities
Cash Flow from Investing Activities
Investment sales and maturities
Investment acquisitions
Capital assets acquired
Proceeds from sales of capital assets
Loans disbursed
Principal collected on loans
$
5,378
26,895
-7,715
276
320
12,791
4,866
4,705
47,516
$
85,588
-87,251
-74,634
198
12,183
-12,188
440
FISCHER & MARSH
EXHIBIT IIIb (Continued)
Net cash flow from investing activities
Cash Flow from Financing Activities
New debt proceeds
Principal payments
Endowment gifts
Net cash flow from financing activities
Decrease in cash and cash equivalents
Beginning cash and cash equivalents
Ending cash and cash equivalents
-76,104
$
$
43,153
-46,447
10,314
7,020
-21,568
103,726
82,158
The Balance Sheet (Exhibits Ia and Ib), Activity Statement
(Exhibits IIa and IIb), and Cash Flow (Exhibits IIIa and IIIb) illustrate
the differences in the financial statement recognition and display
following GASB and FASB guidance. All financial statements’ data are
presented in thousands of dollars. The Sample State University
statements follow GASB guidance while Sample University follows
FASB guidance.
Although the statements reflect the same
transactions that occurred during the fiscal year, the statements
reflect many differences in recognition (amounts), recording, and
presentation. References are made to items within the exhibits
throughout the paper to illustrate specific reporting differences.
SPECIFIC DIFFERENCES
Contributed Services
The FASB set forth specific criteria for private institutions to
identify and recognize contributed services. The GASB does not have
criteria for recognizing contributed services, however, there may be a
GASB project to address contributed services in the future. Currently,
private institutions recognize contributed services that meet certain
criteria established in SFAS No. 116 (1993a). The effect of this
difference is the amount of gift revenues and expenses recognized
and reported. In most cases, there is no impact on net revenues
because the contribution revenues usually are offset by an equal
expense. An exception occurs when the contributed services create
or enhance nonfinancial assets. In those cases, net assets increase
by the value of the services. Contributed services received by Sample
441
University are included in the gift revenue and the salary and wage
expense displayed in Exhibit IIb.
Restricted Cash Contributions
For FASB institutions, restricted cash contributions are recognized
as either temporarily or permanently restricted based on whether the
restriction can be met or not – see Sample University revenue display
in Exhibit IIb. For GASB institutions, time restricted cash contributions
are recognized as deferred revenue displayed in Exhibit Ia until the
restriction is met. This affects the amount of liabilities and gift
revenues reported and thereby impacts net assets for both the public
and private institutions.
Endowment Pledges
The difference in recognition of endowment pledges is quite
noticeable. Endowment pledges to give are recognized by private
organizations as a Pledge Receivable (Exhibit Ib) and as Permanently
Restricted Revenue (Exhibit IIb). A comparable endowment pledge will
not be recognized by a public institution. The FASB recognizes
endowment pledges (promise to give) as permanently restricted as
the endowment corpus cannot be spent. Rather, the income earned
on the investment of the endowment is used according to the donor’s
either restricted or unrestricted direction. The GASB prohibits
recognition of endowment pledges based on its conclusion that a
promise to give cannot satisfy the restriction because resources have
not been received. This difference affects the recognition of assets,
gift revenues, and net assets. Exhibit IIa illustrates that Sample State
University (GASB) would recognize only $10.3 million as endowment
gifts while Exhibit IIb for Sample University (FASB) recognized $20.3
million including an endowment pledge of $10 million. On the
Balance Sheet (Exhibit Ia), Sample State University reports the
endowment gift as a noncurrent investment and restricted
nonexpendable endowment net assets held for its fundraising
foundation affiliated organization ($66.2 million) while Exhibit Ib for
Sample University (FASB) reports the endowment gift as an
investment and permanently restricted net assets.
442
FISCHER & MARSH
Restricted Non-Endowment Pledges
The FASB recognizes restricted non-endowment pledges as
temporarily restricted revenue (see Exhibit IIb Statement of Activity).
The GASB prohibits recognition of pledges for future period use,
under the same concept as endowment pledges – one cannot
recognize the gift before it is available for use. This results in private
institutions recognizing and reporting larger amounts of assets, gift
revenues, and net assets than public institutions.
Discounting of Pledges
The FASB requires discounting if the pledge is collectible in
installments over multiple years. That is, the net present value of the
annuity is recognized when the installment gift is pledged and the
pledge receivable is adjusted each year of the promise to reflect the
time value of money as additional revenue is recognized. The GASB
permits discounting, but does not require it. The difference in
recognizing installment gifts affects assets, gift revenues and net
assets. In Exhibit Ia, Sample State University (GASB) reports the
noncurrent asset pledge receivable as $2.1 million while the Sample
University (FASB) (Exhibit Ib) reports a current asset pledge receivable
in the amount of $15.8 million.
The differences with regard to pledges do not preclude GASB
institutions from recognizing all pledges, only those that meet certain
criteria, i.e., the eligibility to be utilized upon receipt of the pledge.
The logic for the difference in discounting is APB Opinion 20 (AICPA
1971), which drives the recognition of discounts, and applies to
exchange transactions. By definition, pledges are nonexchange
transactions because the donor does not expect anything in return for
the gift. Therefore, the GASB does not require discounting.
Investment Income
GASBS No. 31 (1997) establishes prescriptive treatment for
investment income. Investment income and realized investment
gains/losses must be reported as a single net amount illustrated by
Exhibit IIa Sample State University reporting nonoperating investment
income of $16.4 million. In most public institutions’ financial
statements, investment income includes current yield and net
realized gains and losses in addition to the net unrealized gains and
443
losses. Net unrealized gains and losses can be displayed separately
from investment income by using a prescribed label: net increase
(decrease) in the fair value of investments.
Investment income cannot be reported as operating revenue by
public colleges and universities unless it results from loans to
students, which are classified as program loans. In fact, the only
governmental entities that can report investment income as
operating revenue are pooled-investment entities and fundraising
foundations whose mission includes investment activities.
The FASB does not have similar requirements related to
investment income display or classification as nonoperating. Thus as
displayed in Exhibit IIb, investment income and losses are combined
and displayed as revenue for the related net asset class –
unrestricted, temporarily restricted or permanently restricted.
Pell Grants
Funds received for Pell Grants are not reported as revenue by
FASB institutions. Because the resources are funds held for the
student, the funds are held in trust for the students in an agency
account and not recognized as institutional revenue. It is a balance
sheet cash and accounts payable to the student rather than an
activity statement transaction. For GASB institutions, Pell Grant
receipts are recognized as institutional revenue in accordance with
GASBS No. 24 (1994) that directs all grant receipts to be reported as
revenue.
Whether the revenue is considered operating or
nonoperating is somewhat controversial. The differing recognition
treatment affects grants and contracts revenue, which will be higher
for public institutions. Exhibit IIa indicates government grants and
contracts revenue in the amount of $86.1 million for public
universities versus $66.1 million for private institutions (Exhibit IIb).
As a result of this recognition difference, tuition revenue will be higher
for private institutions. Note that Exhibit IIb reports tuition and fee
revenue of $278.3 million for private universities but only $193.4
million for public universities in Exhibit IIa due to the different
recognition of Pell grant funds. In addition, liabilities and net assets
may often vary.
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Perkins Loan Program
For private (FASB) institutions, federal advances for Perkins loans
are reflected as liabilities on the balance sheet. Public (GASB)
institutions have an option to reflect Perkins loan advances as
liabilities on the balance sheet or revenues on the activities
statement. Both are acceptable under current accounting guidance.
The determination has to do with whether Perkins loan funds are
treated as a net asset or a liability. Some believe the advances are a
liability because the federal government can mandate their return.
Others believe this possibility is so remote that they should be
reported as revenues and net assets. National Association of College
and University Business Officers (NACUBO) raised the issue with the
GASB, suggesting that it is inappropriate to treat something as a net
asset when an external party can require it to be returned. The GASB
recognizes that different rules apply to different types of loans. Until
the GASB adds the issue to its agenda and resolves the question,
either approach is used. If public institutions reflect Perkins awards
on the activities statement, it results in differences from private
institutions for grants and contracts revenue, liabilities, and net
assets.
Both Sample State University and Sample University
recognize Perkins student loan advances as liabilities in Exhibits Ia
and Ib.
Funds Held in Trust by Others
Funds held in trust by others are recorded differently in terms of
both recognition and display. When the private institution is an
irrevocable beneficiary, the private (FASB) institution includes these
resources as assets. The Statement of Financial Position in Exhibit Ib
for Sample University reports investments held by others in the
amount of $70.8 million while there is no comparable account for the
Sample State University in Exhibit Ia. Public institutions do not treat
funds held in trust by others as an asset; rather, if material, they are
disclosed in the notes to the financial statements. However, under
GASBS No. 39 (2002), if the external entity meets specified criteria, it
is reported as an affiliated organization resource or component unit
using a discrete presentation. That is, the financial statements for
the affiliated organization will be included with those of the public
institution in the annual financial report.
445
Technically, public institutions can report blended component
units when the unit holds assets in the institution’s name. Those
assets would be included in the reported amounts but would not be
labeled funds held in trust by others. The effect of this difference is
that funds held in trust by others will appear on private institutions’
statements as a specific amount, but not on those of public
institutions (unless they qualify as component units). In addition,
private institutions display revenue/loss as a result of a change in the
value of the funds held in trust that results in a change in net assets.
Restriction Definition
The FASB’s definition of who can establish restrictions is much
narrower than the GASB. Under FASB, only donors can restrict
resources held by the entity whereas under the GASB any external
party – donors, creditors, legislation, contracts, and constitutional
provisions can impose restrictions. This stems from the GASB’s
philosophy toward accountability that if any restrictions are imposed,
the GASB wants them to be clearly identified. The effect of the
restriction is only on the categorization of revenues and net assets.
Unless donor directed, resources would be displayed as unrestricted
under the FASB guidance but would be displayed as restricted
expendable under GASB guidance. There is no difference for true
endowments, which are restricted nonexpendable for public
institutions and permanently restricted for private institutions. Exhibit
Ia shows the various restrictions for restricted expendable net assets
of Sample State University while Exhibit Ib for Sample University does
not give any details regarding the temporarily restricted net assets.
Use of Restricted Funds
The FASB’s guidance on the use of restricted funds is another
area of difference and is considered one of the most controversial
steps that the FASB has taken with respect to not-for-profit
organizations. The FASB mandates the first dollar release method.
Under first dollar release, restrictions are released if unrestricted
resources are used for a purpose for which restricted resources are
available. Although internal accounting and reporting may not be
affected, the application of first dollar release will convert previously
restricted resources into unrestricted resources simply because they
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FISCHER & MARSH
could have been expended. An amendment to SFAS No. 117 allows
the requirement to be optional.
The GASB considered the mandating position but concluded that
it should not be required in a governmental environment. Instead
they chose to recognize first dollar release as an acceptable method,
making it optional. The GASB requires note disclosure of the policy
applied in situations when both restricted and unrestricted resources
are available for the same purpose. Again, this affects the
categorization of net assets.
Other Postemployment Benefits (OPEB) and Pensions
The GASB uses the term OPEB when referring to other
postemployment benefits which consist primarily of health care for
retirees.
The comparable term in FASB literature is other
postretirement benefits.
While the GASB deliberated recognition and reporting of OPEB
and pensions, the Board concluded that similarities did exist between
private and public sectors. The Board could have adopted the FASB
guidance that was already in place but determined that significant
relevant differences existed between for-profits and governments
which warranted different guidance. For example, governmental
entities can be assumed to have a ‘perpetual’ existence unlike
businesses that can be liquidated. In addition, businesses’ prime
concern is net income resulting from revenues exceeding expenses
whereas governmental entities are concerned with compliance.
While the GASB and the FASB have different approaches to
calculating pension and other postemployment liabilities, they are
consistent within their own methodologies for calculating these types
of liabilities. This affects the measurement and recognition of those
liabilities which impacts expense, liability, and net assets. Both
Sample State University and Sample University display a liability for
benefits payable but with different amounts in Exhibits Ia and Ib.
Impairment
The FASB requires a cash flow approach for determining
impairment loss (loss based on measurement of expected cash
flows). Thus private institutions must recognize an impairment cost
447
and reduction of a capital asset’s value when its carrying value will
not be recovered by future cash flows. The GASB considered the
cash flow approach but opted instead for a service utility approach
when GASBS No. 42 (2003b) was issued. The impairment is
determined by calculating the decline in service (years) based on the
impairment event or change in circumstances. These events include
technological obsolescence, environmental changes, or changes in
the capital asset usage.
The different methods for measuring an
impairment loss also include (1) an estimate of the costs needed to
restore the utility of the assets and (2) deflating the depreciation to
reflect a replacement cost. Each of these approaches affects assets,
expenses, losses, and net assets. Neither Sample State University
nor Sample University reports an impairment expense.
Endowment Losses
The FASB requires that permanently restricted net assets remain
intact—insulated from reductions caused by the recognition of losses.
Therefore, SFAS No. 124 (1995) requires that endowment losses
reduce temporarily restricted net assets to the extent of unspent
appreciation. If losses exceed such amounts, the excess is reflected
as a reduction in the unrestricted net assets. If the loss is considered
temporary, a loss contra can be employed.
However, when the
Uniform Investment Act has been adopted in the state where the
private institution resides, the act’s guidance prevails.
The GASB has no similar requirement. Losses attributable to
restricted nonexpendable net assets reduce the restricted
nonexpendable net assets.
Both Sample State University and Sample University report
investment losses in Exhibits IIa and IIb. Sample State University
reports the loss as Other Items while Sample University reports
negative revenue in the temporarily restricted net asset class.
Fair Value
The SFAS No. 124 (1995) provides a definition of fair value and
guidance for estimating the fair market value of investment in debt
and equity securities. Private institutions report all debt and equity
securities at fair value except for those investments accounted for by
the equity method. Gains and losses, both realized and unrealized,
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FISCHER & MARSH
are recognized and reported in the statement of activities. This
guidance results in increased consistency and comparability in fair
value measurements. However, SFAS No. 157 (2006) and other
accounting codification updates (2009c, 2010) introduced
inconsistency as institutions sought to value investments other than
equities and debt at their fair value.
The GASB provides reporting and recognition guidance in its
GASBS No. 31 (1997) that requires public institutions to report
investment income (including changes in fair value) in the statement
of revenue, expenses and changes in net assets. Money market
investments with a maturity of less than one year may, however, be
reported at their amortized cost rather than market value.
Fair value recognition is reported by both Sample State University
and Sample University as part of investment gains/losses in the
Exhibits IIa and IIb.
Endowments Holding Real Estate
GASBS No. 52 (2007a) amended its earlier guidance to require
public institutions to report their endowment investments of land and
other real estate investment at fair value. In addition, it requires
governments to report the changes in fair value as investment
income and to disclose the methods and assumptions used to
determine fair value. This reporting enhances the users’ ability to
evaluate an entity’s investment decisions and performance.
SFAS No. 157 (2006) provides similar guidance for long-term
assets to be reported at fair value. Institutions typically use
comparable estimates to determine the reportable values rather than
relying on appraisals.
The result of this recognition difference is not transparent in the
financial statements. Rather, the financial statement user must rely
on financial statement note disclosures to discern any change of the
long-term asset value.
Risk Assessment and Deposit Disclosures
GASBS No. 40 (2003a) addresses various deposit and
investment risks such as credit risk, concentration of credit risk,
interest rate risk and foreign currency risk. It requires disclosure of
449
investments that have fair values that are highly sensitive to changes
in interest rates. In addition, it requires disclosure of policies related
to the various risks. The FASB has no similar requirement for private
institutions. There is a benefit for publics with respect to concerns
regarding financial transparency and risk assessment.
Regardless of the risks, the financial statement user must rely on
the financial statement note disclosures to identify any risk exposure.
Early Retirement Plans
Public institutions are obligated to report the financial obligations
associated with early retirement plans when the plan is announced
(GASB 2005). The obligations are allocated to the appropriate fiscal
years when the plan is in place. This recognition causes public
institution’s expenses and liabilities to be greater than a comparable
private institution that also has an early retirement plan because
there is no FASB reporting requirement for private institutions to
recognize early retirement costs. Instead, private institutions report
the early retirement related costs as they are incurred or expended.
Neither Sample State University nor Sample University display any
early retirement plan expenses or liability in Exhibits IIa or IIb.
Intangible Assets
Public institutions must report intangible assets, except goodwill,
acquired in a combination transaction, as a capital asset (GASB
2007b). This recognition requirement ensures that nonfinancial
assets without physical structure are displayed as noncurrent assets
in the statement of net assets. Private institutions have no display
restrictions but typically display intangible assets following the
property, plant and equipment assets.
Neither Sample State University nor Sample University report any
intangible assets in Exhibits Ia or Ib.
Collections
The GASB and FASB do not require, but encourage, capitalization
of collections (art, books, etc.) as long as the collections meet three
conditions which are the same - held for educational purposes, cared
for/protected, and proceeds used to add to the collection if items are
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sold. If the collectibles do not meet these conditions, they must be
capitalized. Exhaustible capitalized collectibles should be
depreciated. Both the GASB and FASB require recognition of
collectible contributions as revenue if the collectible is capitalized.
However, if collectible is not capitalized the GASB (1999a) requires a
charge to a program expense to offset any revenue. In contrast, the
FASB (1993b) does not allow recognition of revenue for items
contributed to noncapitalized collections. These differences can be
identified with the comparison of expenses, revenues and net assets.
Neither Sample State University nor Sample University capitalized
collection is their balance sheet displayed in Exhibits Ia or Ib.
Management Discussion and Analysis
The GASB prescribes the reporting of a management’s discussion
and analysis (MD&A) and outlines specific information that must be
presented (GASB 1999a ¶11). The MD&A must discuss the
relationships between each of the required financial statements as
well as capital projects, functional expenses, change in long-term
debt and the impact of known future events. The discussion should
be easy to read and understand but avoid “boilerplate” language
(GASB 1999a ¶11).
The FASB has no similar requirement for private institutions.
There is no substantive effect of this difference as private institutions
tend to include descriptive transmittal letters from the president and
financial leaders to convey the current state of the institution to the
financial statement reader. Given this, there is a benefit for publics
with respect to concerns regarding financial transparency.
Disaggregation (Columns on Statements)
The FASB allows line of business (e.g. academic, auxiliaries) or
net asset class (i.e., unrestricted, temporarily restricted, permanently
restricted) disaggregation. The GASB allows only line of business
disaggregation that includes nonexpendable restricted and
expendable restricted net assets. Unrestricted net asset class
disaggregation is prohibited (GASB 1999a, ¶37) but disaggregation
display is allowed as a note disclosure.
451
Both Sample State University and Sample University display
equity information by net asset class in Exhibits Ia and Ib. Only
Sample University displays revenue and expenses in Exhibit IIb by net
asset class.
Balance Sheet Display
The GASB (1999a) requires a classified balance sheet (i.e.,
current, noncurrent) and defines three net asset classes (capital
assets, net of related debt – [that is a part of unrestricted new assets
in FASB statements (1993b)], restricted and unrestricted). Exhibits Ia
and Ib detail the different displays. If an institution has permanent
endowments, it must classify restricted net assets as expendable or
nonexpendable. Restricted expendable is very similar to temporarily
restricted in FASB statements. It does not match exactly because the
GASB’s broader definition of restriction results in some net assets
being classified as restricted expendable by public institutions when
the same net assets would be classified as unrestricted by private
institutions.
Capital assets that are being or have been depreciated are
reported net of accumulated depreciation. When a government has a
significant amount of nondepreciable capital assets such as land or
infrastructure, the GASB requires that they be reported separately
from depreciable capital assets (GASB 1999a ¶20).
The FASB does not have a classification requirement. The FASB
net asset classes are unrestricted, temporarily restricted, and
permanently restricted. The FASB has no specific requirements
related to the display of capital assets, although they are considered
part of unrestricted net assets. Exhibits Ia and Ib display the different
formats for the public and private institutions.
Activities Statement
Reclassifications
The FASB (1993b) treats all expenses as unrestricted. To the
extent that temporarily restricted provisions have been met and the
resources are to be used to finance an expense, they must be
reclassified from temporarily restricted to unrestricted net assets.
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The GASB has no similar concept—expenses can be unrestricted,
restricted, operating, or nonoperating (See Exhibits IIa and IIb).
Operating Measure
The GASB (1999a) requires a somewhat prescriptive operating
measure. State appropriations, gifts, and investment income (except
interest on program loans) must be reported as nonoperating.
Institutions are allowed to decide how to treat other items. For
example, gains and losses resulting from the disposition of
capitalized equipment can be either operating or nonoperating. In
institutions where the disposal of capital equipment occurs
frequently, and is a routine part of doing business, it might be
classified as operating. If it occurs infrequently, it likely will be
reported as nonoperating.
There has been a great deal of discussion with regard to an
operating measure for private institutions. The FASB allows for a selfdefined operating measure and requires disclosure of the
methodology for determining the measure if it is not obvious. See
Fischer et al (2004) for a discussion of the variances found among
college and university financial statements that report an operating
measure, together with how the differences impact peer comparison
and benchmarking.
Exhibit IIb does not display an operating measure for Sample
University. A quasi measure Net Income before Capital Items of $1.4
million is reported for Sample State University in Exhibit IIa.
Expense Classification
The FASB (1993b) allows natural classification of expenses but
requires functional classification, either in the display or in the notes.
The GASB (1999a) allows natural or functional expense classification
display. NACUBO encourages a matrix reconciling functional and
natural expense classification to be included in the notes.
Both Sample State University and Sample University use natural
classifications to report their expenses in Exhibits IIa and IIb.
453
Specific Expenses
The FASB (1993b) requires allocation of certain functional
expenses, such as operations and maintenance of plant,
depreciation, and interest. The GASB (1999a) allows, but does not
require, allocation of depreciation. The GASB requires bad debts to
be offset against the corresponding revenue source. The exception to
this general rule is for bad debts resulting from loans because there
is no revenue source.
Since Sample University used natural classification to display
expenses in Exhibit IIb, no allocation was necessary.
Exception Items
The FASB defines extraordinary items as those that are unusual
and infrequent. The GASB has the same definition for extraordinary
items and goes on to specify an additional category—special items.
Special items are unusual or infrequent, and within management’s
control. For example, if a public institution elects to abandon a
software implementation in which significant dollars have been
invested (and capitalized based on NACUBO guidance), it would
report this as a special item because it is within management’s
control. A comparable private institution might feel that this
transaction is neither unusual nor infrequent and; therefore, record it
as part of operating expenses.
Cash Flow Statement
There are significant differences in the cash flow statement
display (see Exhibits IIIa and IIIb). The FASB (1993b) allows the
indirect method and specifies three categories for reporting cash
flows: operating, investing, and financing. Operating activities
display the cash flow in the revenue and expense activities adjusted
by the changes in the working capital accounts. The investing
activities detail the cash flow changes in the nonworking capital and
long-term asset accounts.
The financing activities display the
changes in the long-term liabilities and equity gifts for long-lived
assets and endowments.
In contrast, the GASB (1999a) mandates the direct method to
display cash flows from operating activities that requires operating
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cash flows (both revenue and expense) be reported by type. The
GASB also requires a reconciliation of the operating cash to operating
income as reported on the Statement of Revenues, Expenses, and
Changes in Net Assets (Exhibit IIa). The GASB specifies the use of four
categories for presenting cash flows: operating, investing, capital and
related financing, and noncapital financing. These categories are
different from those prescribed for private institutions and are based
on activities being performed rather than balance sheet components.
Exhibits IIIa and IIIb detail the different displays for Sample State
University and Sample University.
The GASB does not require the inclusion of the cash effects
associated with nonoperating revenues and expenses as cash flows
from operating activities. For example, cash paid for interest on
borrowings is included in cash flows from noncapital financing
activities or cash flows from capital and related financing activities
depending on the circumstances. In Exhibit IIIa, the debt interest
payment of $9.1 million made by Sample State University and
reported as Cash Flows from Capital Financing Activities is part of the
change in net assets within the Operating Activities reported by
Sample University in Exhibit IIIb. Cash received from interest and
dividends is displayed by Sample State University in the Cash Flows
from Investing Activities while Sample University includes the interest
income as part of their operating activities. Another major difference
is the GASB requirement that cash payments to acquire capital
assets be reported as Cash Flows from Capital Financing Activities
and not Cash Flows from Investing used by Sample University to
report the transaction. Exhibit IIIa displays Sample State University’s
$74.6 million payment to acquire capital assets as part of Cash Flows
from Capital Financing Activities while Sample University in Exhibit IIIb
reports the same transaction/amount in the Cash Flows from
Investing Activities. Additionally, cash received from the sale or
disposal of capital assets is reported by Sample State University as
cash flows from Capital Financing Activities while Sample University
reports the same transaction as an investing activity.
These are only a few of the differences between the FASB and
GASB statement of cash flow display guidance.
455
CURRENT GAAP REPORTING PROJECTS
Several research topics currently on the GASB’s action agenda
will expand the public versus private nonprofit recognition and
divergence. One research item is monitoring the effect of the
electronic media on information delivery and user needs to provide
the GASB with a basis for evaluating the need to develop standards
for electronic financial reporting. Another research item considers
whether any additional information is useful for assessing a
government’s economic condition and determining if it should be
required or encouraged for inclusion in the financial report. Other
research agenda items will re-examine current guidance pertaining to
fair value measurement, pension accounting (GASB 2009b), and the
reporting of component units (GASB 1991).
The GASB recently issued Statement No. 58 (2009a) to provide
accounting and financial reporting guidance for governments that
have been granted protection from creditors under Chapter 9 of the
United States Bankruptcy Code. It requires governments to
remeasure liabilities that are adjusted in bankruptcy when the
bankruptcy court confirms (approves) a new payment plan.
Governmental nonprofit entities are not excluded from the guidance.
Both the GASB and FASB had leases on their research agendas
but the GASB put their investigation on hold pending the work
currently underway at the FASB.
The FASB is working with the
International Accounting Standards Board (IASB) to reconcile lease
recognition and accounting. Once this work is completed, the GASB
will review the conclusion to determine whether to accept or develop
specific guidance for US governmental entities.
In addition to the joint project with IASB on leases, the FASB is
working on a revision of the financial statement presentation. This
project is considering a common approach to presenting information
in financial statements using the current cash flow statement
categories.
To date, nonprofit entities have been specifically
excluded from the deliberations.
A FASB project that did impact the nongovernment nonprofit
entities is the accounting standards codification (FASB 2009b). The
codification is a single, authoritative, comprehensive integrated
compilation of US accounting and financial reporting literature. It
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became GAAP in June 2009 as a fully functional, online, real-time
database with searching capability and retrieval.
The GASB maintains a codification for GASB guidance in hardcopy
paper format that can be purchased. For an annual fee, a
searchable, digitized format of the GASB codifications is available.
CONCLUSION
As evidenced by the discussion of the specific differences
between the financial recognition and reporting by public
(governmental/GASB) and private (nongovernmental/FASB), a
comparison between comparable institutions can lead to a very
different financial conclusion. Table 1 presents common ratio and
other analysis using financial information presented in Exhibits Ia, Ib,
IIa and IIb.
TABLE 1
Comparative Financial Statement Ratios
Sample
Sample
State
University
University
value
value
Liquidity
current ratio
current assets/current liabilities
2.546
3.483a
quick ratio
cash+ marketable security+ receivables/
current liabilities
2.454
3.483a
days of cash on
hand
cash+ short term marketable securities/
(total operating expenses+
depreciation/365)
129.376
166.219
6.623
6.292
55.111
58.011
1.243
1.074
Asset turnover
receivables
revenue-tuition revenue/accounts
receivable
average
365/receivable turnover
collection period
fixed asset
turnover
total unrestricted revenue/net fixed assets
457
TABLE 1 (Continued)
Sample
Sample
State
University
University
value
value
total asset
turnover
total unrestricted revenue/total assets
0.631
0.537
Leverage
debt ratio
debt to equity
Profitability
total long-term debt/total assets
total long-term debt/total net assets
0.337
0.588
0.343b
0.591b
-0.019
0.011
-0.01
0.006
-0.017
0.011
increase in net assets/total unrestricted
revenue and other support
Return on assets increase in net assets/total assets
return on net
increase in net assets/total net assets
assets
total margin
Notes: a. Without a classified balance sheet, this measure is an estimate that
assumes assets and liabilities are presented in order of liquidity.
b. Current portion of long-term debt may or may not be displayed in financial
statement notes.
Four categories of analysis are illustrated – liquidity, asset
turnover, leverage and profitability-all available to the average
financial statement user.
Given the different reporting and
recognition criteria used by Sample State University and Sample
University, Sample University will typically report better liquidity
measures because gift pledges at Sample State University cannot be
recognized before the institution is eligible (based on time or
purpose) to use the gift. Unless the current portion of long-term
liabilities or obligations is known, Sample University analysis should
yield better leverage values. With the immediate recognition of gift
revenues, regardless of whether the gift is given as cash or a pledge,
Sample University profitability analysis should exceed that of Sample
State University. Sample State University, however, should report
better turnover measures thanks to a lower amount of gift pledge
receivables. Sample University’s tuition revenue will exceed that of
Sample State University because Sample University will recognize the
Pell Grant awards as tuition revenue rather than contract and grant
revenue that Sample State recognizes. Without knowledge of why the
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FISCHER & MARSH
data differ, the financial statement user could make inappropriate
conclusions about the financial health of an institution.
Given current reporting and recognition guidance based on the
fact that the FASB and the GASB treat time restriction differently, a
comparable private institution will always report greater gift revenue
than its comparable public institution due to the private’s recognition
of pledged gifts. The time restriction treatment is the primary cause
for some of the more significant reporting and recognition
differences. Another significant difference is the requirement for
public institutions to report state appropriations as nonoperating
revenue that results in public institutions reporting a negative
operating income. When a beneficial trust is held by a third party, the
private institution will always report a larger amount of assets on the
balance sheet than does the public institution.
Thanks to the
requirement for public institutions to recognize Pell Grant funds as
revenue, comparable public institutions will always report less tuition
revenue than private institutions. And the list of differences in
reporting and recognition by nonprofit organizations goes on and on
as outlined in Table 2. The divergence in financial recognition and
reporting between private and public nonprofit institutions appears to
be increasing rather than decreasing.
TABLE 2
FASB GASB: Summary of Differences
Panel A
Financial
Statements
Governmental
Nonprofit Organization
Uses AICPA
Government Audit Guide (1999)
Nongovernment Notfor-profit Organization
Uses AICPA Not-forProfit Audit Guide (1996)
GASB 35/34 (1999a; 1999b)
MD&A (RSI)
Statement of Net Assets
Statement of Revenues,
Expenses and Change in Net Assets
Statement of Cash Flow
Notes
Other Required Supplemental
Information (RSI)
FASB 117 (1993b)
Statement of Financial
Position
Statement of Activities
Statement of Cash Flows
Notes
459
TABLE 2 (Continued)
Panel B
Governmental
Balance Sheet GASB 35/34 (1999a;1999b)
Classified per ARB 43
Current
Noncurrent
A = L + NA
A L NA (No totals)
Within classificationsassets and liabilities
presented in liquidity order
Investments (including
real estate) presented at
fair value
Funds held in trust by
others reported in notes if
significant
Capital Assets net of
related debt
Restricted Nonexpendable
Restricted Expendable
Unrestricted (designation
prohibited)
FASB (1993b)
Classification not
Required
A = L + NA
Assets and liabilities
presented in liquidity
order
Investments (real estate
optional) presented at
fair value
Funds held in trust by
others reported as assets
and Permanently Restricted
NA
Unrestricted Net Assets
Temporarily Restricted NA
Permanently Restricted NA
Panel C
Income
Statement
Governmental
Expenses display in appropriate net
asset class
Any external party can restrict
resources
Restriction met when
first $ spent - optional
All expenses displayed as
unrestricted
Only donors can restrict
Resources
Restriction met when
first $ spent - optional
Met restrictions are
reclassed into Unrestricted
Net Assets
Expenses displayed
functionally or by natural class
Expenses displayed
functionally or by natural
class
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FISCHER & MARSH
TABLE 2 (Continued)
Plant operation and
depreciation may be
presented as functional
designation
Revenues presented by type
Operating measure prescribed
Realized and unrealized
investment income
presented separately
reported as non-operating
revenue
Plant operation,
depreciation and interest must be
allocated (no
guidance provided)
Revenues presented by type
Operating measure-optional
Realized and unrealized
investment income may
be netted
Appropriations may be
reported as operating
revenue
Panel D
Cash Flow
Governmental
GASB 9 (1989)
Direct method mandated
Reconciliation required
(indirect method to report
operating activities)
Cash equivalents same as
cash if <90 days and original
investment maturity 90 days or
less
Four categories
Operating
Non-Capital Financing
Transfers
Subsidies
Contributions
Agency transactions
Capital Financing
All capital asset related
Capital contributions
New capital debt
Capital debt obligations
Sale of capital assets
Investing
All investing activities
Acquisitions
Sales
Interest earned
FASB 117 (1993b)
May use direct or indirect
method
Cash equivalents same as cash
if <90 days and original
investment maturity 90 days or
less
Three categories
Operating measureNet income +/- change
in working capital
accounts
Investing +/- changes
in long term assets
Financing +/- long term
liabilities
New endowment gifts
461
TABLE 2 (Continued)
MD&A
Notes
Required supplemental
reporting - contents prescribed
Required by various GASB
guidance
Not required
Required by various FASB
guidance
Legends: A = Assets; L = Liabilities; NA = Net Assets.
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FALL 2012
THE SHERIFF OF NOTTINGHAM'S FAVORITE TAX: HOW LOCAL OPTION
SALES TAXES EXACERBATE BUDGETARY INEQUALITIES BETWEEN
LOCAL GOVERNMENTS
Patrick J. McHugh and G. Jason Jolley*
ABSTRACT. This paper tests the theory that local option sales taxes (LOST)
work to the disadvantage of poorer localities, particularly rural areas, where
many residents commute to shop and work. We also hypothesize that LOST
systems hurt struggling communities more than they help prospering ones.
The LOST system is examined using multiple years of data from North
Carolina, a state whose tax structure favors such an analysis. The results
indicate that LOST systems exacerbate inequality between local
communities by actively moving revenue from poorer communities to more
wealthy ones. We find evidence that LOST systems cost poorer counties a
greater percentage of their total budgets than is gained by the wealthy
counties that attract retail activity.
INTRODUCTION
Local option sales taxes (LOST) came into vogue in the late
1970s and 1980s during the “property tax-revolt” and they now exist
in more than thirty states. Local option sales taxes were initially
proposed as an alternative revenue source that would allow local
governments to provide property tax relief. Another touted strength of
this policy is that each local government gets to decide for itself
--------------------------* Patrick J. McHugh, Ph.D., is a Senior Research Associate, International
Economic Development Council. His teaching and research interests include
public policy, public administration, economic development, political theory
and political communication. G. Jason Jolley, Ph.D., is the Senior Research
Director, Center for Competitive Economies, and Adjunct Assistant Professor
at the Kenan-Flagler Business School, University of North Carolina at Chapel
Hill. His teaching and research interests include public administration,
public policy, public finance, and economic development.
THE SHERIFF OF NOTTINGHAM'S FAVORITE TAX
467 whether to adopt the tax, so reform is not being heavy-handedly
imposed by state governments. While appealing for a number of
reasons, the performance of local option sales taxes in the real world
have been largely disappointing. First, evidence that LOST revenues
allow localities to reduce property taxes is mixed, at best (Zhao &
Jung, 2008; Sjoquist, Walker, & Wallace, 2005). In this paper, we
focus on a second concern; there is growing evidence that local
option sales taxes tend to shift revenue from poorer, often rural,
communities to more affluent ones, making LOST systems regressive
at both the individual and community levels.
There is considerable evidence that poorer taxpayers pay a larger
percentage of their income on sales taxes than do wealthier
taxpayers (Rostvold, 1966; Ghazanfar, 1978; Schweitzer & Taylor,
2008; Shoup 1983; Siegfried & Smith, 1997). An effort to replace
federal income taxes with a national sales tax in the 1990's never got
off the ground because congressional Democrats and President
Clinton saw the sales tax as a bad deal for the poor. Moreover, there
is little evidence that states systematically use exemptions for
particular goods to ease the regressive nature of sales taxation
(Fletcher & Murray, 2006).
We maintain that local option sales taxes tend to be regressive at
the community level as well, and this paper tests whether local option
sales taxes actively shift revenue from struggling communities to their
more wealthy neighbors. Because retail activity is increasingly
clustered in wealthier and more populous areas, we expect sales tax
revenue to flow from more impoverished rural areas to centers of
wealth and population that are capturing retail business. In a national
sales tax, poorer citizens pay a larger percentage of their resources,
but at least they are part of the population those funds serve. When
sales tax revenues flow from one county to the next, the citizens in
the losing county are actively paying for their more prosperous
neighbors' roads, schools, and social services.
How Local Option Taxes Work and Why they Reinforce Inequality
Most of the attention to the inequalities of local governmental
revenue has historically focused on property taxes. Imbalances in
education finance, produced by imbalances in property tax revenue,
have generated equal protection lawsuits in several states and
substantial media attention. While property taxes are important, there
468
MCHUGH & JOLLEY is good reason to also examine how local option sales tax systems
function and whether they reinforce inequalities between local
communities.
Sales tax policy is determined at the state level and most
revenues go to state governments. Local option sales taxes exist
where state governments give localities the option of levying an
additional tax on top of the statewide rate. In most cases, state
governments grant counties the authority to enact local sales taxes
that will stay with the county governments. From the perspective of
representation, this seems to be an equitable arrangement;
communities that favor increased sales taxes can do so without
forcing others go along for the ride. While LOST mechanisms may be
intuitively appealing, the way they work in the real world raises
serious concerns. Like property taxes, areas with more wealth
generate more LOST revenues for local governments. While
disparities based on wealth are to be expected, we contend that
market forces shift revenue from poorer communities to more
wealthy ones, making the final distribution even more uneven than
underlying differences in wealth.
Retailers follow rooftops, especially in wealthy populous areas.
Malls, outlet stores, boutique shops, restaurants, and other retailers
are all are drawn to communities that can afford their services. As a
result, poorer communities usually have fewer retail choices, forcing
residents to drive to the nearest retail centers. Particularly as big-box
retailers, super-centers, and regional malls have replaced local shops
and grocers, retail activity is more concentrated than it was several
decades ago (Artz & Stone, 2003). In many rural areas and innercities, local shops have been squeezed out of business when larger
retailers offering lower prices move into communities nearby. On top
of differences in retail choices, many residents of poorer communities
are forced to commute to find work. The sales tax revenues for
whatever purchasing commuters do near their places of employment
will stay where that shopping occurred. Whenever residents of one
locality commuting, travel to shop, or shop elsewhere because it is
near their work, they leave the LOST revenues behind. Because we
expect residents of poorer communities to have more cause to travel
to shop than their more affluent neighbors, we expect that LOST
revenues to flow in the same direction. Unlike property taxes, whose
variation across counties is purely an effect of differences in property
469 value, LOST revenues may be literally riding in wallets from poorer
areas to more prosperous ones.
While the inequities in LOST revenues have not been scrutinized
as much as property taxes, the existing work supports the theory
articulated here. Much of the existing work has focused on how LOST
inequalities impact levels of education funding, just as has been the
case for property taxes. Work on inequalities in education funding has
indicated that LOST systems tend to reinforce the differences in
revenue resulting from inequities in property tax base (Rubenstein
and Freeman 2003). One study claimed that LOST inequalities
violated the equal protection clause of Iowa's state constitution (Craft,
2002).
Disturbing evidence about LOST inequalities is not limited to
education funding. In a study of revenue inequalities between county
governments in Georgia, Zhao and Hou found that LOST revenues
were even more unevenly distributed than were property tax revenues
(Zhao and Hou 2008). A study of LOST revenues in Iowa estimated
that, over a ten year period, $800 million in LOST revenues would
move from “retail poor” to “retail rich” counties (Artz & Stone, 2003).
Another study in Tennessee found that when a rural county is in close
proximity to two newly-opened urban malls, their sales tax revenues
will fall an average of 16% (Chervin, Edmiston, & Murray, 2000).
In this paper, we examine whether LOST systems are regressive in
a variety of ways. Do local option sales taxes shift resources away
from counties with poorer populations? Do LOST systems move
revenue out of communities that are under more fiscal strain? Can
we find direct evidence that LOST revenues move with the flow of
traffic from poorer to more affluent communities? Finally, do poorer
communities lose a greater proportion of their overall budget than is
gained by their more affluent neighbors? For the first time, this paper
shows that LOST systems tend to hurt poorer communities more than
they help affluent ones, resulting in a net economic loss to the local
economy. We examine LOST systems from a variety of vantage points,
and find consistent evidence that the policy actively moves public
resources away from where they are needed most.
Outline of this Study
The methods section discusses why North Carolina's sales tax
policy makes it an appealing case. North Carolina's system is quite
470
MCHUGH & JOLLEY different from the traditional LOST setup, but these differences turn
out to be analytically advantageous for studying how point of sale
systems impact county budgets. We then describe the details of
projecting a per-capita allocation for each county in each year and, by
comparing that projection to the reported point of sale collections,
sorting counties who are advantaged under the point of sale system
from those that are disadvantaged by the point of sale system.
The first section of results examines whether point of sale
systems work against counties with less prosperous residents. In
other words, we are less interested in whether LOST systems
disadvantage “retail-poor” communities than whether they work
against communities that are broadly less affluent. This section
shows that the point of sale system tends to disadvantage counties
that are more rural, have populations with lower income, and higher
poverty rates.
The next section presents evidence that LOST systems tend to
undercut local governments that are under greater fiscal stress. We
show that counties who are disadvantaged by the point of sale
system have less cash on hand and have lower average credit scores
than counties who prosper under the point of sale system.
The next section tests the central theoretical argument outlined
above. Are retail tax dollars literally moving from poorer communities
to more affluent ones when sales tax revenues are realized on a point
of sale basis? More wealth obviously generates more sales taxes but,
if the theory outlined above is correct, LOST revenues should be
distributed even more unevenly than absolute wealth. We find that
out-commuting rates have a significant impact on sales tax revenue,
even controlling for county income. These results provide direct
evidence of the core theory driving this project. When county
residents drive elsewhere to work, their home county loses sales tax
revenue. When wealthier counties attract retail business, they have
even more to spend on their citizens.
The final section of results reports the ultimate consequences of
distributing sales tax dollars at the point of sale versus allocating
them according to county population. We show that moving from a
point of sale to a per capita system would help the governments that
are disadvantaged by the point of sale system more than it would hurt
counties that prosper under point of sale. Finally, we show that this
policy choice (per capita vs. point of sale) has a substantial aggregate
471 impact on where revenues are realized. Over a decade, the
differences between point of sale and per capita systems can run into
the billions.
METHODS
Why Study North Carolina?
North Carolina's sales tax system is actually unlike most
traditional LOST arrangements. Where other states give counties the
option of levying a sales tax on top of the statewide rate, North
Carolina's system was established and is run entirely at the state
level. All sales taxes are collected by the state government and then
part of those revenues are distributed back to the county
governments. North Carolina does not have the traditional local
option sales tax, but instead a statewide tax with revenue sharing
built into the system. While North Carolina's system is not true to the
original LOST idea, it is an advantageous case to study.
At the most basic level, North Carolina's system ensures that
differences in local sales-tax revenues are not due to differences in
how the tax is administered. The choices of which goods to tax, how
those revenues are collected, and how they are reported do not
change from one county to the next.1
At a deeper level, North Carolina's system ensures that
differences in retail activity between counties are not driven by
differences between local tax structures. Previous research has found
that differences in local sales tax rate affect the location of retail
outlets (Fisher, 1980). In more traditional systems, some counties
exercise the local sales tax option before others (Sjoquist et al.,
2007), which may influence where retailers choose to set up shop. In
addition, some jurisdictions may not enact the full allowable tax rate,
again producing incentives for retailers to go where taxation is
limited. Beyond influencing where retail outlets open, differences in
sales tax rate between adjacent jurisdictions (e.g. neighboring states)
have been shown to influence where consumers do their shopping
(Fox, 1986; Walsh & Jones, 1988).
Since the focus of this paper is on how market forces influence
LOST revenues, and not on how LOST systems change market
decisions, North Carolina's system removes a potential source of
endogeneity from our analysis. In a purely local option system, some
472
MCHUGH & JOLLEY counties adopt the levy years after it is first instituted by other
localities. During the period when some counties collect LOST
revenues and others do not, we would expect retailers to factor these
differences into where they choose to do business. As the market can
be skewed by the sequence of adoption, North Carolina is an
appealing case because these factors have not influenced where
retail outlets are located.
North Carolina also provides an example of how states can adjust
for inequalities produced by point of sale systems without going to a
purely per-capita alternative. Sales taxes revenue that is distributed
to North Carolina counties is broken up into four independent articles
enacted by the state legislature. Article 39 creates a 1% sales-tax
where the revenues are distributed on a point of sale basis. Articles
40 and 42 both create ½% sales taxes that are distributed according
to county population. Article 44 creates a final ½% sales tax with half
of these revenues being distributed on a per-capita basis and the
other half staying where sales occur. Articles 39, 40, and 42 apply to
food purchases of home consumption, while Article 44 does not.
Calculating LOST Revenues Distributed on Per-Capita vs. Point-of-Sale
Bases
The core of this paper is driven by a comparison between the
revenues that each county would realize under a purely point of sale
system, like those that exist in most states, and what each county
would receive if sales-tax revenues were distributed on a purely percapita basis. Because each article of the North Carolina sales tax is
reported independently, we can isolate the portion that is distributed
on a purely point of sale basis.
When we first began this project, the idea was to compare the
revenues counties receive under the two ideal components of North
Carolina's system (point of sale vs. per capita). It turns out that, at
least in North Carolina, per-capita does not really mean per-capita.
North Carolina law applies an “appropriate adjustment factor” to each
county's population-based share of sales tax revenue, increasing or
decreasing their actual allotment. These factors range from .81
(county would receive 81% of the share allotted to their population) to
1.49 (would receive 149% of per-capita share). To date, we have not
found any specific explanation of how these factors were produced.
While the “per-capita” component of the North Carolina tax is more
473 equitably distributed than the portion based on point of sale receipts,
these adjustment factors create inequalities that run in the same
direction. There is actually a positive correlation between county
wealth and its “adjustment factor," meaning that wealthier counties
are collecting more per-capita than are poorer counties. As a
consequence, we could not use the “per-capita” portion of North
Carolina's system to estimate what counties would receive if the
entire system were actually distributing sales tax revenues according
to population.
Therefore, we use the purely point of sale component of North
Carolina's system (Article 39), to calculate what each county would
receive under an actually per-capita system. For each year, we
summed the total revenues that all counties received from Article 39
and divided that by the statewide population. This produces the
statewide average sales tax revenue generated by each resident of
North Carolina. We then multiply this figure by each county's
population to find the share of the statewide sales tax pot that each
county would receive. With this in hand, we compare a county's
estimated per-capita share to what they actually received under the
point of sale system. Article 39 only constitutes 1% of the 2.5% of
sales taxes that are distributed to county governments, so the real
receipts and our estimate of per-capita share were both multiplied by
2.5 to produce an estimate of what each county government would
receive if the entire system were run on a point of sale or per-capita
basis. In the final section, we estimate the change in each county’s
overall budget that is produced by moving from a point of sale to a
per capita system under 1%, 2.5% and 5% sales tax rates.
This approach accomplishes a few critical things. First, it allows
us to separate who wins from who loses under these alternative
systems. We know what counties actually received under a point of
sale system, and now we can see whether they would have fared
better or worse if these revenues were distributed based on
population. This allows us to directly test whether the counties that
suffer under a point of sale system really are poorer, more rural, and
have more struggling populations. Second, we can directly estimate
what percentage of the overall budget picture is at play. We can
estimate how much each county would lose or gain if North Carolina
moved from a purely point of sale system to a per-capita one. This
allows us to test the claim that point of sale LOST systems cost
474
MCHUGH & JOLLEY poorer counties a larger percentage of their overall budget than
wealthy counties stand to gain.
RESULTS
Point-of-Sale Systems Disadvantage Poor and Rural Communities
Before anything else, it is important to look carefully at the profile
of counties that are advantaged by a point of sale system compared
to those that are disadvantaged by sales tax revenue being realized
at the point of sale. Is it true that traditional LOST systems work
against communities that are already under greater fiscal duress?
This section presents evidence that counties who suffer under a point
of sale LOST system are struggling rural communities. The next
section shows that the same disadvantaged communities have fewer
alternative sources to draw upon and are in greater fiscal distress.
Looking at county finances from both ends, it is clear that point of
sale systems hurt communities with greater needs and fewer
resources to serve those demands.
We argued at the outset that point of sale LOST systems
disadvantage less affluent, often rural, counties because their
residents' must travel elsewhere to work and shop. Table 1 supports
the concern at the heart of this project. The first column reports the
average population, median household income, and poverty rates for
counties that are advantaged by a point of sale system (counties that
collect more revenue on a point of sale basis than they would on a
per-capita distribution). The second column shows the same averages
for counties that disadvantaged by a point of sale allocation. These
data were taken 2008 county revenue summaries provided by the
North Carolina Treasurer (http://www.nctreasurer.com/lgc/units/
unitlistjs.htm). North Carolina has 100 counties, but 3 of these did
not supply all of their data for 2008, so Table 1 reflects the 97
counties that did report.
First off, it is clear that rural communities tend to be
disadvantaged by the point of sale system. On average, counties that
are disadvantaged when LOST revenues are based on where sales
take place are significantly smaller than counties that prosper under
a point of sale system. We suspect that a LOST system would also
disadvantage purely inner-city counties, but North Carolina does not
475 TABLE 1
Demographic Differences between Counties Advantaged and
Disadvantaged by the Point of Sale System (2008)
Counties
Counties Advantaged
Disadvantaged by Point
by Point of Sale
of Sale
Population
std err
Med House Inc
Poverty (all)
Poverty (under 18)
Number of Counties
131,737
39,854
$45,071
1,595
14.1%
0.69
20.4%
0.90
22
80,422
13,120
41,050**
863
17.6%**
0.55
24.8%**
0.80
75
Note: Counties Advantaged by Point-of-Sale are counties that collect more point of
sale revenues than they would on a per-capita basis; Counties Disadvantaged by
Point-of-Sale collect less point of sale revenues than they would on a per-capita
basis.
** Significant difference (.01 level) between counties advantaged by point of
sale sales tax allocation and those disadvantaged. The differences reported as
based on the entire population of North Carolina counties (excepting three
missing cases), so significance levels are not necessary for discussing North
Carolina's system. However, since we are interested in the theoretical behavior
of LOST systems generally, we report significance levels for differences of means
tests conducted on these data, effectively treating North Carolina as a sample of
the population of all county governments.
Source: Revenue and population data (North Carolina Treasurer 2011). Accessed at
http://www.nctreasurer.com/lgc/units/unitlistjs.htm. Poverty rates (U.S. Census
Bureau 2010). (Accessed at http://www.census.gov/cgi-bin/saipe/saipe.cgi).
have any counties that match that profile. What we see here is the
first evidence that residents of rural counties must travel to shop and,
in so doing, leave their tax revenues behind in more populous areas.
The claim that point of sale tax revenues flow from less prosperous
counties to more wealthy ones will be more explicitly tested later, but
these data do support the concern that LOST systems work against
rural communities with limited retail activity.
While it is important to know that point of sale systems work
against rural counties, there would be less cause for alarm if those
areas were prospering otherwise. However, many rural communities
476
MCHUGH & JOLLEY in North Carolina and throughout the county are struggling. If our
central claim is correct, and LOST systems reinforce economic
inequalities between local communities, average income should be
higher in counties that are advantaged by a point of sale revenue
allocation and poverty rates should be lower, which is precisely what
the data in Table 1 show.
TABLE 2
Per Capita Revenues for Counties Advantaged and Disadvantaged by
the Point of Sale System (2008)
Counties
Counties Advantaged
by Point of Sale
of Sale
Property Taxes
std err
Service Taxes
Other Taxes
Inter-Gov't Grants
Misc Revenue
All Non Sales Tax
Revenue
Number of Counties
$727
$46
$181
$33
$114
$28
$332
$75
$103
$13
$1,722
$507**
$13
$168**
$13
$45**
$3
$255**
$10
$68**
$4
$1192**
$173
$41
22
75
Note: Counties Advantaged by Point of Sale are counties that collect more point of
Point of Sale collect less point of sale revenues than they would on a per-capita
basis.
sale sales tax allocation and those disadvantaged.
Source: North Carolina Treasurer (2011); U.S. Census Bureau (2010).
Point-of-Sale Systems Disadvantage Counties that are Under Greater
Fiscal Stress
Having seen that a point of sale revenue system tends to work
against rural communities with lower income and more poverty, this
477 section examines whether these county governments are under
greater fiscal stress. This section first reviews revenue streams
generated by everything other than sales taxes, showing that counties
who are disadvantaged by LOST collect significantly less revenue per
resident from other funding sources than do counties who are
advantaged by a point of sale system. Second, this section shows
that counties who are disadvantaged by a point of sale system also
have less cash on hand and have lower average credit ratings, both
good indications that they are under greater fiscal stress.
Table 2 shows that LOST systems work against counties that
often face a more dismal revenue situation than the counties who are
advantaged by the system. In 2008, North Carolina counties that did
better when sales tax revenues were distributed on a point of sale
basis also collected more per resident in property taxes, more in
other taxes, more in service taxes, received more in intergovernmental grants, and collected more miscellaneous revenue. The
final row of Table 2 reports the average revenue per resident derived
from everything but sales taxes. In 2008, North Carolina counties that
were advantaged by the point of sale system collected, on average,
$530 more in revenue per resident than counties that were
disadvantaged by the point of sale system. If we treat North Carolina
counties as a sample, the difference in per-capita revenue between
counties advantaged by a point of sale system and those
disadvantaged by it is statistically significant at the .01 level.
Showing raw differences in revenue does not, in itself, prove that
LOST systems work against communities who are under greater fiscal
stress. Given that we have already seen that point of sale systems
work against rural communities, differences in county revenue could
simply be driven by differences in the cost of living. Rural
governments may need less revenue per citizen because the cost of
providing services and infrastructure is lower. To account for this
possibility, we examine two indicators of fiscal stress (bond ratings
and fund balances) to test whether counties who are disadvantaged
by point of sale systems are under greater fiscal stress than counties
who are advantaged by how LOST systems generally function.
Fund balances are one traditional measure of fiscal stress (Gold,
1986; Hendrick, 2004). Based on North Carolina Treasurer county
revenue summaries, we calculated the fund balance available per
resident for each North Carolina county in 2008. The first row of
478
MCHUGH & JOLLEY Table 3 shows that counties who were advantaged by a point of sale
system had roughly twice as much cash on hand than did
disadvantaged counties, a difference that almost certainly outstrips
differences in cost of living and providing governmental services.
TABLE 3
Per Capita Revenues for Counties Advantaged and Disadvantaged by
the Point of Sale System (2008)
Per-Capita Fund
Balance
Standard Error
Average S&P Rating
Obs for Fund Balance
Obs for S&P Rating
Counties Advantaged
by Point of Sale
Counties
Disadvantaged by
Point of Sale
$407
$217**
$51
5.94
0.44
22
16
$12
3.77**
0.25
75
49
Note: Counties Advantaged by Point of Sale are counties that collect more point of
Point of Sale collect less point of sale revenues than they would on a per-capita
basis.
sale sales tax allocation and those disadvantaged.
Source: North Carolina Treasurer (2011).
Bond ratings provide another test of whether point of sale LOST
systems work against counties that are under greater fiscal stress,
Bond ratings and changes in bond ratings are established measures
of fiscal stress (Jesse Marquette, R Marquette, and Hinckle 1982;
Grizzle 2010). Governmental bond ratings are designed to capture a
government's ability to repay its debt, so counties that are on a solid
fiscal footing receive higher bond ratings than do counties who are
closer to insolvency (for a description of S&P bond rating
methodology see http://www.standardandpoors.com/ratings/). The
lowest rating reported for North Carolina counties in these data was
BBB+ and the highest was AAA. We coded S&P ratings numerically in
the following way: BBB+=1, A-=2, A=3, A+=4, AA-=5, AA=6, AA+=7,
AAA-=8, AAA=9. Another coding was conducted, where +'s and -'s
479 were dropped and each major rating was placed on a scale from
BBB=1 to AAA=4, which produced very similar results.
The second row of Table 3 compares the average bond rating of
counties advantaged and disadvantaged by a point of sale LOST
system. Based on our coding, counties disadvantaged by a point of
sale system have an average bond rating between A and A+, while
counties advantaged by the system have an average rating AA, a
difference of almost one major S&P rating. According to Standard and
Poor's, an A rating mean “strong capacity to meet financial
commitments, but somewhat susceptible to adverse economic
conditions and changes in circumstances”. An AA rating means “Very
strong capacity to meet financial commitments” (Standard and
Poor's. Retrieved from http://www.standardandpoors.com/ratings/).
Clearly, based on the best models of fiscal strength available,
counties that are disadvantaged by a point of sale LOST system tend
to be on more tenuous financial footing. The difference is not
enormous but, given the variety of factors that feed into bond ratings,
it is telling that differences in sales-tax revenue are so clearly
correlated with measurable fiscal stress. It is worth noting that this
result is not unique to the recession that set in during 2008; we ran
this analysis on all years from 2003 to 2009 independently and the
results were extremely similar.
All told, there is substantial evidence that a point of sale LOST
system works against counties that are harder pressed to meet their
residents' needs. Counties that are disadvantaged by a point of sale
system collect less revenue from other sources, have less cash on
hand, and have lower bond ratings.
Do LOST Revenues Move with the Flow of Traffic?
To this point, we have focused on implications of the thesis
behind this paper, but we have not explicitly tested the mechanism at
the core of the theory. We argue that travel patterns reinforce
revenue differences produced by resident income alone. As retail
activity gravitates toward centers of spending power, residents of
poorer communities do more of their working and shopping away
from home. This section directly tests whether sales tax revenue
literally moves with the flow of traffic when revenues are realized at
the point of sale.
480
MCHUGH & JOLLEY TABLE 4
Predicting Per-Resident Revenue Each County Would Receive under
2.5% Point of Sale Tax
Med House Inc
($1,000's)
(Standard Error)
Predictor
Coefficients
4.51**
(.163)
5.04**
(1.53)
-2.67**
(.55)
18.08**
(1.99)
30.95**
(3.38)
16.38**
(5.69)
13.08
(8.81)
8.92
(10.50)
67.46
(46.50)
.41
Outcommuting Rate
2004 dummy*
2005 dummy
2006 dummy
2007 dummy
2008 dummy
Constant
r2
18.66**
(2.08)
31.92**
(3.44)
18.20**
(5.99)
15.63
(9.29)
12.9
(11.06)
-7.66
(53.42)
0.14
Note: Pooled linear regression model where the unit of analysis is the county
budgetary year, with each year from 2003 to 2008 counted as unique
observations. Standard errors are clustered on the county to account for
correlations in each county's errors over years. Dependent variable is the tax
revenue generated for each county under a 2.5% point of sale tax (Article
39*2.5), divided by the county's population in that year. Median houshold
income and sales tax revenue taken from county summaries provided by the
North Carolina Treasurer. Outcommuting rates for each county taken from 2000
U.S. Census (most recent year available).
Sources: North Carolina Treasurer (2011); U.S. Census Bureau (2000).
Table 4 reports the results of a pooled linear regression model
predicting the revenues that each county would receive if North
Carolina's sales tax system were distributed on a purely point of sale
basis. The model includes data for each county from 2003 to 2008
(except where data was not reported in the NC Treasurer files), which
are pooled. The dependent variable is the reported revenues from
Article 39, multiplied by 2.5, and then divided by the county's
481 population. Median income data is taken from the US Census Small
Income and Poverty Estimates (http://www.census.gov/cgibin/saipe/saipe.cgi). Outcommuting rates are taken from the 2000
census. Unfortunately, county outcommuting rates are not available
for each year, so we use the 2000 estimates for each year of data.2
Because we are using pooled data, year dummies are included to
account for differences in average sales tax revenues from year to
year (2003 is the omitted category). In addition, because there are
likely to be factors unique to each county's sales tax revenues, we
cluster standard errors to account for any correlated errors for
individual counties over years.
The first model only uses median household income to predict the
revenues each county would receive from point of sale taxes. As we
would expect, counties with more disposable wealth also generate
more sales tax revenues. The second model adds a county's
outcommuting rate as a predictor of point of sale tax revenues. If our
theory is correct, tax dollars should be moving with the flow of traffic.
While outcommuting rates is an imperfect proxy for inter-county
shopping, these data should capture travel patterns that influence
shopping patterns. As predicted, outcommuting is negatively
associated with sales tax revenues. When more of a county's
residents work outside the county, and presumably do shopping while
away from home, their home county collects less sales tax revenue
per citizen. Critically, this effect holds even controlling for average
income. This means that counties with high outcommuting rate
collect less point of sale tax revenues than their income would predict
and counties with low outcommuting rates collect more than they
should, based on wealth alone. On top of this, the second model is a
much better fit to the data (r2=.41 vs r2=.14). Even given that the
addition of an explanatory variable necessarily inflates r2, the addition
of outcommuting rates explains significantly more variance than the
base model. If we want to understand why some counties collect
more point of sale taxes per citizen than others, we must consider
dominant travel patterns that influence where people do their
shopping.
482
MCHUGH & JOLLEY Examining the Proportional and Aggregate Effect of Point of Sale
versus Per Capita Systems
This final section outlines what is at stake. Previous studies have
shown that local option sales tax revenues are biased toward
counties with more retail options. While one study did estimate the
total leakage of revenues from “retail-poor” to “retail-rich" counties
over a ten year span (Artz & Stone, 2003), no study has directly
estimated the percentage change in each county's budget. Thus, we
ask, how would county budgets change if North Carolina went from a
purely point of sale system to one where proceeds are distributed
according to population?
We have seen that, on average, counties that are disadvantaged
by a point of sale system are poorer, more rural, and generate less
revenue through alternative sources, and have lower credit ratings. As
a consequence, we hypothesize that the movements of revenue
found in the previous section have the most impact on counties that
lose retail activity. In other words, we expect LOST systems to reduce
poor counties' budgets by a greater extent than they increase the
budgets of wealthy communities. When residents of poorer counties
drive to neighboring communities to shop, the lost revenues comprise
a substantial portion of their home county's operating budget
because these counties have less property tax valuation, lower
incomes, and less economic activity to generate alternative sources
of revenue. On the other hand, counties that attract retail business
tend to already be much better off; that's why the retailers are keen
to set up shop in those communities in the first place. While some
counties would not do as well under a per-capita system as they do
under a point of sale system, these more affluent counties have less
at stake than do counties that are disadvantaged by the point of sale
system.
To test this hypothesis, we estimated the percentage change in
each county's total budget that would result from exchanging a
system where sales tax revenues stay where sales take place (point
of sale) to one where revenues are distributed according to county
population (per-capita). The equation used to accomplish this for
county i in year j is given by:
∆
483 Where
is the total estimated county budget if all sales tax
revenues were distributed according to county population and
is the estimated county budget under a purely point of
is the percent change county ′ total
sale system. Thus, ∆
budget, in year (positive or negative), that would be produced by
moving from a point of sale to a per-capita system.
Abandoning the local option sales tax, and replacing it with one
where revenues are distributed according to population, would help
struggling counties more than it would hurt their more affluent
neighbors. We already have seen that point of sale systems penalize
counties that can least afford it, and this exercise indicates that
poorer counties lose proportionally more than the wealthier counties
gain.
Table 5 reports the average change in budget for counties that
are advantaged by a point of sale system versus those that are
disadvantaged. As local option sales tax rate varies across states, we
provide three estimates depending on the allowable local tax rate.
The first line reports the average gains and losses attached to
changing from a point of sale to a per-capita system if the local rate is
1%. The second line reports the same estimates for states, like North
TABLE 5
Average Impact of Exchanging the Point of Sale System for a PerCapita System
Counties
Counties Advantaged
by Point of Sale
of Sale
Local Sales Tax Rate
1%
2.50%
5%
Obs
-1.73%
-3.81%
-6.43
179
+2.49%
+5.84%
+10.51
505
Note: Mean change in estimated county budgets that would result from moving to a
per-capita allocation of sales taxes. Unit of analysis is the individual county
budgetary year.
484
MCHUGH & JOLLEY Carolina, with a 2.5% local sales tax. The final line reports the change
that would occur in states where the local option tax rate is at 5%, as
it is in Louisiana, which is the highest rate allowed by any state
government.
Even under a 1% LOST tax, counties that are disadvantaged by
the point of sale system would see their budgets grow by 2.49%,
while counties that benefit from the point of sale system would see
their revenues shrink by 1.73%. Under a 2.5% local sales tax rate,
counties that are disadvantaged by the point of sale system would
see an average budgetary increase 5.84% while counties who do
better under a point of sale system would lose 3.81% in revenue. In
states that permit localities to tax sales up to 5%, shifting to a
statewide per-capita system would increase budgets in counties that
are disadvantaged under the existing system by an average of
10.51%, while counties that prosper under the current arrangement
would see their revenues fall by roughly 6.43%. This is direct evidence
that traditional LOST systems penalize the counties that can least
afford it. When sales tax revenues flow from struggling rural counties
to their more prosperous neighbors, the losses are felt more heavily
than the corresponding gains. The coffers of wealthy counties that
attract retail business are already being filled from a variety of larger
revenue streams, while the revenue lost by rural counties is being
taken out of much smaller sources.
Finally, it is useful to useful to understand the total amount of
revenue that hangs in the balance depending on whether sales tax
revenues stay at the point of sale or are distributed according to
population.
The central point of this exercise is to demonstrate that we are
talking about substantial amounts of revenue for local governments,
which is what Table 6 shows. For example, if North Carolina had
shifted from a 2.5% point of sale system to a 2.5% tax allocated
according to county population, counties that would have gained from
such a switch would have received an aggregate of $296,116,839
extra. Over the six year span captured in our data, the total revenue
that would depend on per capita versus point of sale, for a 5% sales
tax, would stack up to over $3 billion. All in all, it is clear that policy
choices about sales tax revenue allocation have a substantial impact
on local budgets.
485 TABLE 6
Total Revenue to Be Gained by Counties that Are Disadvantaged by
the Point of Sale System if Sales Tax Revenues were Allocated
According to Population
Year
1% Tax
2003
2008
2003-2008
$89,663,472
$118,446,735
$633,183,285
2.5% Tax
5% Tax
$224,158,681
$448,317,362
$269,116,839
$592,233,678
$1,582,958,213 $3,165,916,426
Note: Values reflect the total change in revenues depending on how sales taxes are
allocated. For a shift to the per capita system, away from the point of sale
system, the values represent the total revenues gained by counties who are
disadvantaged by the point of sale system.
DISCUSSION
There is growing evidence that local option sales taxes are a bad
deal for impoverished communities with struggling local governments.
Previous research has shown that LOST taxes are distributed more
unequally than property taxes (Zhao & Hou, 2008), that they tend to
flow from “retail poor” to "retail rich” counties (Artz and Stone 2003),
and that over time these transfers added up to substantial sums of
money. This paper reinforces all of the previous findings about local
sales taxes and rounds out our understanding of the policy in a
number of important ways.
First, we show that local option sales taxes undermine the
revenues of counties with struggling populations. Counties that are
disadvantaged by a point of sale system tend to have fewer residents,
lower average family incomes, and higher rates of poverty. We also
showed that counties who are disadvantaged by a point of sale
system generate less revenue per resident, have less cash on hand,
and have lower credit ratings, all indications that these counties are
under greater fiscal stress.
Second, we provide direct evidence that variation in LOST
revenue cannot be explained by differences in wealth alone. Counties
where more residents work outside of the county collect less point of
sale revenue than they we would expect, based on income and
counties where fewer residents commute, collect more than they
should, based on income. This is direct evidence that when counties
486
MCHUGH & JOLLEY attract business from their neighbors, they capture their neighbors'
sales tax revenues as well.
The final section demonstrates that local option sales taxes have
a substantial impact on counties' overall budgets. Previous studies
have shown that LOST revenues reinforce other inequalities in local
funding, but do not provide a concrete picture of how much poor
counties are losing and how much wealthy counties are gaining. One
of the purposes of this study was to test our suspicion that
proportional gains by counties that capture retail from their neighbors
were smaller than the proportional losses to communities that leak
retail. The evidence clearly shows that abandoning LOST systems and
replacing them with systems that distribute sales tax revenue
according to county population would help struggling communities
more than it would hurt their more affluent neighbors.
NOTES
1. There is a multiplicity of local option sales taxes that generate
both general and specific-purpose revenues. Some localities
exempt food purchases, housing expenditures, or transportation
spending from their local sales taxes.
2. We expect that time mismatches between outcommuting rate and
point of sale tax revenues should work to mute the relationship,
so any error should be conservative. To be even more confident
that this mismatch is not driving our results, we ran the model
using only 2003 data, the closest in time to the outcommuting
reading within these data, and the results were extremely similar.
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FALL 2012
DEBT AND BUDGET GIMMICKRY REVISITED: THE UPFRONT BOND
REFINANCING SAVINGS STRUCTURE
Martin J. Luby*
ABSTRACT. In recent years state governments have significantly increased
the use of debt to fund their capital and operating budgets. As the size of
government bond portfolios increased, the opportunities to refinance debt to
realize substantial operating budget savings grew. To relieve short-term
fiscal stress, some state governments have utilized debt refinancing
structures that provide near term benefits with the same negative long-term
budgetary impacts as other common “one-shot revenue” budget gimmicks.
This paper thoroughly describes the strategy and mechanics of one such
debt-related budget gimmick, the upfront bond refinancing savings structure,
and details its usage by state governments over the last decade. Through
descriptive research, this paper finds that states have only very modestly
used this budget gimmick, which has theoretical and policy implications
relating to principal-agent theory and the efficacy/necessity of debt
restrictions, respectively.
INTRODUCTION
State governments across the country continue to struggle with
sizable cyclical and structural budget deficits even as the Great
Recession was “officially” declared over in June 2009. In the current
2012 fiscal year that started on July 1, estimates show that 44 states
and the District of Columbia will report operating budget deficits
totaling $112 billion (Center on Budget and Policy Priorities, 2011).
This follows annual budget deficits of $110, $191 and $130 billion in
fiscal years 2009, 2010 and 2011 (estimated), respectively.
Moreover, state finances are only expected to slowly recover over the
------------------------* Martin J. Luby, Ph.D., is an assistant professor in the School of Public
Service at DePaul University. His teaching and research interests are in
state and local government capital markets, public financial management,
and organizational behavior.
490
LUBY
next few years as evidenced by a preliminary aggregate state budget
deficit of $75 billion in fiscal year 2013 (Center on Budget and Policy
Priorities, 2011).
While the upcoming year constitutes one of the most fiscally
challenging budget years on record, states have been regularly
struggling with their finances for many years even before the Great
Recession. For example, as a result of the last recession in 2001,
state budget deficits totaled $40, $75, $80 and $45 billion in fiscal
years 2002, 2003, 2004 and 2005, respectively. Unlike the federal
government which has the ability to cover deficits with borrowing,
states are constitutionally or statutorily restricted from running
operating budget deficits. While the strictness of this restriction
varies by state, states generally aim for balance, at least “on paper”
(Briffault, 1996). The traditional measures used to address these
budget gaps reside on both the revenue and expense sides of the
operating budget and include such measures as implementing new or
raising existing taxes, creating new or increasing existing user fees or
other revenues, cutting program expenditures, reducing service
levels, and consolidating programs and departments.
Such
measures were used extensively in the last two recessions. For
example, during the Great Recession, 46 states reduced services to
its residents and 30 states increased taxes with some of these
increases quite substantial (Center on Budget and Policy Priorities,
2011).
However, it has also been well documented that states have
relied on other less traditional, and many argue more fiscally
reckless, measures to achieve budgetary balance (Briffault, 1996;
Petersen, 2003; Mikesell 2009). A common one of these measures
involves the refinancing or restructuring of a government’s
outstanding debt. The focus of this study is on one specific type of
debt-related budget gimmick not extensively explored in the
literature, the upfront bond refinancing savings structure. This
budget gimmick involves a government structuring its bond
refinancing so that the interest cost savings occur in the first year or
in the first couple years after the refinancing with all subsequent
years receiving minimal or zero savings. By taking all the savings
upfront, the government is, in effect, employing a “one-shot revenue”
to lessen the fiscal strain on its operating budget. The use of one-
DEBT AND BUDGET GIMMICKRY REVISITED: THE UPFRONT BOND REFINANCING SAVINGS
491 shot revenues has generally been discouraged by public finance
experts as it can lead to or exacerbate structural budget deficits.
In order to shed greater light on this budgetary technique, this
paper specifically describes the technique, details its usage by state
governments and describes the implications of such usage level for
public financial management theory (agency theory) and practice
(efficacy of debt restrictions). More specifically, the paper proceeds
as follows. First, the paper details how this analysis fits into the
broader public finance literature on budget gimmickry and public
administration literature using principal-agent theory to understand
management behavior.
Second, the paper details the rising
importance of debt finance in recent decades and how this has
provided an opportunity to use bond refinancing to help achieve
short-term budgetary balance. This section will also provide a
thorough description of the budget gimmick technique under study,
the upfront bond refinancing structure. Third, the paper describes
the methodology used in calculating the overall usage of upfront bond
refinancing structures and then proceeds to detail the actual
utilization level of this budget gimmick by state governments over the
last decade. The final section describes the implications of such
usage level for theory and practice.
LITERATURE REVIEW
This paper contributes to two different strands of applied
empirical literature and one body of theoretical literature. First, this
paper adds to the empirical budget gimmickry literature. This
literature has generally been relatively descriptive in nature detailing
the various budget gimmicks that subnational governments employ to
achieve budgetary balance. Mikesell (2009) describes several
budgetary gimmicks often employed by subnational governments
including overestimation of revenues, asset sales, capitalization of
unrecognized assets, interfund manipulations and borrowing,
acceleration of revenues and delays in spending, capitalization of
current costs and borrowing to cover them, and anticipated future
savings. Briffault (1996) concurs with Mikesell and outlines a similar
list of budgetary gimmicks in the context of the desirability of a
federal balanced budget rule including the use of overly optimistic
revenue forecasts, manipulation of fiscal periods, payment deferrals,
pension fund reductions based on overly optimistic return yields,
492
LUBY
asset sales, special fund transfers, and bond refinancing. Petersen
(2003) focuses on what he calls “more exotic, interesting and more
damaging budget gimmick methods” including sophisticated debt
refinancings that amount to the “liquidation of an unrecognized
asset.” The budgetary gimmick that is the focus of this paper, upfront
refinancing savings structure, is included in the list of debt-related
budget gimmicks briefly detailed in Petersen (2003).
Second, this paper attempts to contribute to the empirical
literature on bond refinancing of municipal debt, which, to date, is not
very robust. Most of this literature has been prescriptive in nature
detailing the optimal timing and structure of subnational bond
refinancings (Dyl and Joehnk 1976; Babad and Speer 1978; Kalotay
and May 1998; Kalotay, Yang and Fabozzi 2007; Zhang and Li 2004).
There have also been a couple studies on the impact of bond
refinancings and some of the factors associated with the refinancing
decision (Luby 2011; Vijayakumar 1995). This paper details the
actual technique and budgetary impact of a specific bond refinancing
strategy.
Third, this paper will also aim to add to the public management
theoretical literature that utilizes economic models and, more
specifically, agency theory as a means of understanding public
financial management decision-making. There are several research
studies that have at least tangentially utilized agency theory to
explain public financial management decision-making as it relates to
the use of financial advisors, bond method of sale, debt policies, and
debt management networks (Bhagat and Frost 1986; Miller 1993;
Leonard 1996; Simonsen and Kittredge 1997; Simonsen and
Robbins 1996; Robbins and Dungan 2001; Peng and Brucato 2003;
and Kriz 2003). A 2006 symposium in the Journal of Public
Budgeting, Accounting and Financial Management included studies
that seemed to refute the use of rational choice theories such as
principal-agent theory in explaining public financial management
behavior. The symposium presented four studies that offered
alternative theoretical explanations on the connection between
individual motives, organizational structures and financial results
whereby public financial managers were found to be "satisficers" not
entirely influenced by individual self-interest but by other factors
including politics, professional norms and individual values (Carroll
493 and Marlowe 2006; Burke 2006; Rivenbark 2006; Robbins and Miller
2006; Stalebrink and Sacco 2006).
Simonsen and Hill (1998) is the most prominent research study
to date that has attempted to explicitly use agency theory to
understand public sector debt management decisions. Their study
utilizes a survey of city and county government finance officers in
trying to determine whether there is evidence of a principal-agent
problem in the issuance of municipal bonds. Based on the results of
their survey instrument, Simonsen and Hill concluded that there is
evidence of a significant principal-agent problem (Simonsen and Hill,
1998). This paper attempts to extend Simonsen and Hill’s study in
drawing inferences from debt management decisions, not from
survey responses. That is, rather than relying on survey research in
determining whether agency problems plague debt management
decisions, this paper looks at the actual behavior of public sector
financial managers (i.e., whether to use an upfront refinancing
savings structure) to observe evidence of the existence of a principalagent problem.
BOND REFINANCING SAVINGS STRUCTURE DESCRIPTION
The first part of this paper’s analysis entails describing the
budgetary gimmick under study, the upfront bond refinancing savings
structure. However, to provide broader context to the research study
at hand, it is first important to briefly describe some recent
subnational government bond finance trends in order to establish
saliency of the issue. In recent years, state and local governments
have significantly expanded their debt finance activities as a means
of increasing and optimizing their capital and, sometimes, operating
budget funding. In general, however, state and local government
debt is mainly employed to finance capital activities such as the
construction of roads, schools, and bridges. This is known as “new
money” debt. As the size of their outstanding new money bond
portfolios increase (which increases the interest cost component of
the operating budget), the opportunities for state and local
governments to refinance debt (depending on interest rate
conditions) to realize substantial operating budget savings grows.
Refinancing bonds are known as “refunding” debt. The actual
acceleration in bond issuance is illustrated in Graph 1 which details
the growth in bond volume by purpose, new money or refunding, for
494
LUBY
GRAPH 1
State and Local Government Annual Aggregate Bond Issuance
Par Amount by Purpose (New Money or Refunding)
Source: The Bond Buyer.
state and local governments between 1990 and 2010. In 1990,
state and local governments sold $120 billion in new money bonds,
$20 billion in refunding bonds and $5 billion in combined new money
and refunding bonds. Twenty years later, in 2010, state and local
governments sold $279 billion in new money bonds, $98 billion in
refunding bonds and $55 billion in combined new money and
refunding bonds. While this comparison only examines two discrete
points in time, the graph clearly shows the significant upward growth
trend over time in both new money and refunding bonds and, thus,
the import of both new money and refunding debt to state and local
governments.
495 As mentioned above, the most likely reason that a state or local
government would decide to refinance all or a portion of its
outstanding debt portfolio is due to changes in interest rates that
make the refinancing economically beneficial on an interest cost
savings basis. Under this type of refinancing, the state and local
government issues new bonds and uses the proceeds to retire
outstanding bonds that have higher interest costs. This exchange of
new debt for old debt has the effect of replacing higher interest rate
debt (outstanding bonds) with lower interest rate debt (new bonds).
This is known as an economic refinancing/refunding and is congruent
with an individual’s decision to refinance his home due to a reduction
in interest rates from the time he originally obtained his mortgage
resulting in monthly mortgage payment savings.
In the case of a municipal bond economic refunding, the interest
cost savings provide operating budget relief to the state or local
government in the form of lower annual interest payments since
these interest costs are considered a current expense and paid out of
the operating budget. In the last twenty years, the increased use of
debt finance combined with steadily declining interest rates has
presented significant opportunities for state and local governments to
refinance their debt to achieve interest cost savings. Graph 2 plots
interest rates and refunding bond volume detailing the relationship
between annual state and local government bond refunding volume
and the level of interest rates as proxied by the annual average of the
Bond Buyer’s 20 GO Index. As expected, a visual inspection of this
chart illustrates a strong inverse relationship between refunding
volume and the overall level of interest rates. This is further
evidenced by the correlation coefficient of .583 between these two
variables.
Similar to an individual’s refinancing of his/her home mortgage,
state and local government refinancings can be structured to produce
equal annual interest cost savings to the government. In an equal
annual savings structure, the subnational government receives the
same interest cost savings each year over the course of the life of the
bond refinancing. However, state and local governments are
generally not required to structure the refinancing bonds to achieve
equal annual interest cost savings. That is, many government entities
can structure the refinancing such that the interest savings occur in a
496
LUBY
GRAPH 2
State and Local Government Annual Average Refunding Bond
Issuance Compared to Average Annual Interest Rate
Source: The Bond Buyer.
targeted year or period of years. For example, the refinancing can be
structured so that the savings all occur in the first year or first few
years after the refinancing bonds are issued with the subsequent
years realizing little or no debt service savings. This type of
refinancing structure is known as an “upfront savings structure” or, in
the parlance of home mortgage finance, a “cash-out refinancing.”
Compared to an upfront savings structure, an equal annual
interest cost savings structure provides greater long-term budget
relief and is more efficient from a present value savings perspective.
An upfront savings structure offers enhanced budgetary flexibility in
the short-term, thus making an upfront savings structure attractive to
the often short-range budgetary perspective of politicians, and is
often less efficient compared to an equal annual savings structure.
497 Upfront refinancing savings structures usually entail refunding nearterm principal maturities with these bonds known as “structuring
bonds” in a refinancing. Utilizing these “structuring bonds” in a
refinancing usually results in an efficiency loss represented by lower
present value savings compared to an equal annual savings
structure. The efficiency loss vis-à-vis an equal annual savings
structure is due to two factors: 1) the refunding bonds are amortized
slower with longer maturities generally carrying higher interest rates
than shorter maturities and/or 2) bonds that would normally not be
refinanced based on interest savings target thresholds are included
in the refunding. Table 1 provides a hypothetical example of the
difference in annual principal and interest payment savings under the
equal annual savings and upfront savings structures. Graph 3
visually illustrates this comparison between bond refinancing
structures.
TABLE 1
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Total
$10,000
$10,000
$10,000
$10,000
$10,000
$10,000
$10,000
$10,000
$10,000
$10,000
$100,000
$9,500
$9,500
$9,500
$9,500
$9,500
$9,500
$9,500
$9,500
$9,500
$9,500
$95,000
$8,500
$8,500
$8,500
$10,000
$10,000
$10,000
$10,000
$10,000
$10,000
$10,000
$95,500
$500
$500
$500
$500
$500
$500
$500
$500
$500
$500
$5,000
Annual Savings
(Upfront Savings
Structure)
Annual Savings
(Equal Annual
Savings Structure)
Refinancing Bonds
P&I (Upfront
Savings Structure)
Refinancing Bonds
P&I (Equal Annual
Savings Structure)
Year
Refinanced Bonds
P&I
Hypothetical Savings Structure Analysis; Annual Principal and Interest
Savings by Refinancing Bond Structure (In $1,000)
$1,500
$1,500
$1,500
$0
$0
$0
$0
$0
$0
$0
$4,500
498
LUBY
GRAPH 3
Bond Refinancing Saving Structure Comparison
As shown in Table 1 and Graph 3, compared to the equal annual
savings structure, the state or local government receives greater
savings in each of the first three years under the upfront savings
structure ($1,500,000 compared to $500,000) but realizes lower
savings in each of the subsequent years ($0 compared to $500,000).
Moreover, the total savings over the course of the bond issue is less
for the upfront savings structure ($4,500,000) than the equal annual
savings structure ($5,000,000), which reflects the greater bond
structuring efficiency of the equal annual savings structure.
Efficiency considerations aside, the major budgetary problem with the
upfront savings structure relates to structural budget deficits and the
use of one-time revenue sources. By taking all of the refinancing
savings upfront (or over the first couple years), the state or local
government is effectively utilizing a one-time (or short-term) revenue
“shot” to fund its budget. In this example, after year 3, the
government entity will either have to replace the $1,500,000 in
savings with some other revenue source or cut such amount from its
499 annual operating budget going forward since there will be no annual
principal and interest savings associated with the refinancing starting
in year 4. That is, the interest costs on the refinancing bonds will
revert back to the debt service levels prior to the refinancing. In
austere budget times, this use of the short-term budget shot may put
further strain on the government’s operating budget when the annual
savings disappear in year 4. Even in the presence of strong revenue
growth and a balanced budget, the use of such a short-term revenue
shot provides the perception that the government entity has greater
resources than it actually does (at least on a longer-term basis) which
provides an artificial incentive to increase spending from its operating
budget in the short term.
Analyzing an actual bond refinancing that utilized an upfront bond
refinancing structure will further illustrate the issues described above.
Table 2 details the interest cost savings analysis for the
$225,655,000 Cook County, Illinois, General Obligation Refunding
Bonds, Series 2004A issued in March 2004. These bonds were sold
to refund a portion of Cook County’s 1993A, 1993B, 1999A, and
2001A bonds achieving $16.5 million in total interest cost savings
throughout the term of the refinancing bonds. The refinancing
produced savings of $5.11 million in fiscal year 2004, $10.18 million
in fiscal year 2005, and $991,910 in fiscal year 2006. Savings in
fiscal years 2007 through 2023 was no more than $50,000 with
some years having negative savings and several years with zero
savings. Due to an artifact associated with the time of year that the
refinancing was executed, Cook County achieved significant savings
in fiscal year 2004 as a result of the interest on the 2004 bonds
being calculated over only a seven month period (end of March 2004
through November 30, 2004) whereas the refunded bonds interest
was calculated over 12 months (November 30, 2003 through
November 2004). The fiscal year 2005 savings was accomplished by
refunding $9.225 million principal amount of the 1993B bonds
scheduled to mature in fiscal year 2005 while not amortizing any of
the 2004 bonds during this fiscal period. As described above, the
$9.225 million in bonds represents the use of “structuring bonds” to
achieve near-term budgetary relief. In essence, through the use of
this bond refinancing structuring technique, Cook County was able to
monetize most of the total interest cost benefits associated with the
refinancing into the first three years.
500
LUBY
TABLE 2
Refinancing Analysis
General Obligation Refunding Bonds, Series 2004A,
The County of Cook, Illinois
Refunded Bonds Annual Principal and Interest
FY
2004A P&I
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Total
6,931,352
11,090,163
15,515,163
15,713,163
18,481,163
10,685,763
21,778,888
10,125,138
10,131,438
10,131,525
22,505,500
33,955,500
33,921,250
43,681,750
27,469,250
27,454,750
13,819,250
13,836,000
13,853,500
13,865,250
374,945,752
1993A P&I 1993B P&I 1999A P&I 2001A P&I
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
3,998,500
13,783,500
13,794,250
13,810,000
13,819,250
13,836,000
13,853,500
13,865,250
148,742,250
Annual
Savings
1,362,860
2,986,038
3,700,150
5,116,196
10,587,860
2,986,038
3,700,150 10,182,385
5,822,385
2,986,038
3,700,150
991,910
5,051,025
2,986,038
3,700,150
22,550
7,847,030
2,986,038
3,700,150
50,555
0
2,986,038
3,700,150
-1,075
0 14,076,038
3,700,150
-4,200
0
2,431,538
3,700,150
5,050
0
2,431,538
3,700,150
-1,250
0
2,431,538
3,700,150
-1,338
0
4,756,538 13,765,150
14,688
0 16,229,475 13,759,156
31,631
0 16,228,675 13,729,406
35,331
0 16,229,550 13,710,631
41,931
0
0 13,700,681
25,681
0
0 13,672,406
27,656
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
30,671,160 92,731,113 119,338,931 16,537,702
DATA AND BOND REFINANCING SAVINGS STRUCTURE OPERATIONALIZATION
The second part of this paper examines the usage of upfront
refinancing savings structures in state government bond refundings.
This section of the paper describes the data and methodology used in
calculating the degree of upfront refinancing structure for a sample of
refunding bond issues. The data consist of a random sample of all
state government refinancing bond issues (both revenue and general
obligation bond types) sold between January 1, 2002 through
December 31, 2009, a period that covers two recessions and one
period of economic expansion thus allowing for some variability in the
fiscal environments of the states. The universe of state government
refinancing bond issues was compiled through the Thomson Reuters
SDC database. The sample was generated through the random
number function in the computer spreadsheet program Microsoft
Excel where each bond issue was assigned a number with the
computer selecting the bond issues used in the sample. Refinancing
501 bond issues whose final maturity was more than 2 years after the
final maturity of the refunded bonds were classified as “restructuring”
bonds and were not included in the universe from which the sample
was drawn since these refinancing transactions were not executed
primarily on the basis of producing economic savings but more likely
to explicitly provide short-term operating budgetary relief through the
extension of debt maturities. Nine bond issues were excluded on this
basis. In this study, the number of bond issues in the sample totaled
113 from a total population of 389.1
The information necessary for determining the degree of upfront
refinancings savings variable was found in each bond issue’s official
statement or through its escrow agreement. The official statement is
a document prepared for a new municipal bond issue by or for the
issuer of the debt. This document describes the issue, financial
details about the issuer and other relevant facts and is the municipal
bond market’s equivalent to the stock prospectus used in the equity
markets. The official statement also provides information on the
details, nature and purpose of the bond refinancing including
information related to the bonds being refunded under the
refinancing. The escrow agreement provides additional details
regarding the refunding including information on the specific bonds
being refunded. The official statements and escrow agreements were
acquired through EMMA, the Municipal Securities Rulemaking
Board’s (MSRB) market data repository website.
The degree of upfront refinancing savings structure calculation is
quite novel and somewhat technical. Specifically, this study has
operationalized the variable as continuous in nature and calculated
as the difference between the amortization (i.e., the gradual payment
of bond principal) of the first three years of refunded bond principal
as a percentage of entire bond issue principal minus the amortization
of the first three years of refunding bond principal as a percentage of
entire bond issue principal. This operationalization aims to capture
whether the state is retiring the bond principal on its refinancing
bonds as quickly or quicker as its refunded bonds or whether it is
employing a structure to delay bond repayment on its refunding
bonds as a means of pushing the refinancing savings into the near
term. A three year amortization period was chosen based on the
notion that elected officials will generally try to implement budget
strategies that will provide them maximum financial flexibility in the
502
LUBY
short-term often just long enough until the next election. A three year
window for bond refinancing savings will usually satisfy this strategy
since most administrative elected officials are elected for a four-year
term. Under this operationalization, the greater the value of the
variable, the more the savings is structured on an upfront basis.
Conversely, the lower the value of the variable, the less the savings is
structured on an upfront refinancing savings basis.
Since this type of analysis has never been performed to date, the
operationalization of the variable is novel to the municipal finance
literature.
However, it is justified based on basic
mathematical/financial principles that underlie it, which is best
illustrated through the use of an example. Table 3 details the
calculation of the degree of upfront refinancing saving structure for
the 2004 County of Cook, Illinois refinancing described in the
TABLE 3
Refunding Analysis
General Obligation Refunding Bonds, Series 2004A
The County of Cook, Illinois (In $1,000)
Refunding Bonds
Refunded Bonds
3rd year Bonds Cumulative
3rd year Bonds Cumulative
Amortization: $4,425
Amortization: $14,155
% of Bonds Amortized in First 3 years: % of Bonds Amortized in First 3 years:
1.96%
6.10%
Cumulative
Cumulative
Maturity
Maturity
Amortization
Date
Par
Date
Amortization
Par
Amount
Amount
3/1/2004
11/15/2004
0
11/15/2004
0
11/15/2005
0
11/15/2005
9,225
9,225
11/15/2006
4,425
4,425
11/15/2006
4,930
14,155
11/15/2007
4,800
9,225
11/15/2007
4,415
18,570
11/15/2008
7,760
16,985
11/15/2008
7,445
26,015
11/15/2009
275
17,260
11/15/2009
26,015
11/15/2010
11,375
28,635
11/15/2010
11,090
37,105
11/15/2011
290
28,925
11/15/2011
37,105
2012-2023 196,730 225,655
2012-2023 195,125
232,230
4.13% % Difference Between Refunded Bonds First 3 Years
Amortization and Refunding Bonds First 3 Years Amortization
503 previous section of this paper. The table lists the maturity dates and
principal amounts for the refunding bonds and the refunded bonds
showing the cumulative amortization (in dollars) at any point in time
as well as the percentage and dollar amount of bonds amortized in
the first three years for the refunding and refunded bonds. The
bottom of the table shows the percentage point difference between
the cumulative three year amortization structures between the
refunded and refunding bonds.
By the end of the third fiscal year after the refinancing (i.e.,
2006), the county had amortized 1.96% of its refunding bonds
whereas the refunded bonds principal would have been 6.10%
amortized if the refinancing did not occur. This produces a 4.13
percentage point difference between the amortization of the first
three years of refunded bond principal as a percentage of entire bond
issue principal and the amortization of the first three years of
refunding bond principal as a percentage of entire bond issue
principal.
In dollar terms, the refunded bonds cumulative
amortization by the end of fiscal year 2006 was $14,155,000
whereas the cumulative amortization of the refunding bonds was
$4,425,000. This slower amortization of the refunding bonds vis-àvis the refunded bonds allowed the County of Cook, Illinois to delay
approximately $9,730,000 in bond principal payments to provide
short-term operating budget relief from FY 2004 through FY 2006 (in
addition to the interest cost savings from the refinancing accruing in
this period). Thus, this calculation comports well with Table 2 which
clearly showed that the County of Cook, Illinois used an upfront
savings structure on its 2004 refinancing.
USE OF UPFRONT BOND REFINANCING SAVINGS STRUCTURES BY THE
STATES
This section of the paper proceeds to detail the actual utilization
level of upfront bond refinancing savings structures by state
governments over the last decade. As a means of establishing
generalizability, the analysis must show that the sample is
representative of the universe of state refinancing bond issues as it
relates to various bond issue and issuer characteristics such as bond
sale method type, bond size, use of a financial advisor, bond type,
credit rating, and total state representation. Table 4 shows the
summary statistics for the various characteristics of the bonds in the
504
LUBY
TABLE 4
Summary Statistics: Upfront Refinancing Savings Structure (Random
Sample of State Refinancing Bond Issues Sold Between 01/01/2002
– 12/31/2009)
Variable
REFSAVSTRUC
(Degree of upfront
refinancing savings1)
BONDSIZE (in millions)
SALEMETH
(Obs. are number of
negotiated sale bond issues)
RATAAA
(Obs. are number of bond
issues from states rated AAA
at time of refinancing)
RATAA
issues from states rated AA
RATA
issues from states rated A at
time of refinancing)
RATBAA
issues from states rated BAA
FINADV
(obs. are number of bond
issues that used a financial
advisor)
BONDTYPE
(Obs. are number of revenue
bond issues)
Note:
Obs.
Mean
Std. Dev. Min.
113 2.306283 7.73956 -6.68
Max.
45.54
113 330.1338 277.0992 6.365 1074.89
71 .6283186 .4854065 0
1
29
.2566372 .438723
0
1
79
.699115 .4606857
0
1
4
.0353982 .1856073
0
1
1
.0088496 .0940721
0
1
93
.8230088 .3833613
0
1
20
.1150442 .3204966
0
1
1 Continuous variable that represents the difference between the
amortization of the first three years of refunded bond principal as a
percentage of entire bond issue principal minus the amortization of the
first three years of refunding bond principal as a percentage of entire
bond issue principal).
505 sample. For the sample, 71 (or 63%) were sold on a negotiated
basis, 93 (or 82%) used an independent financial advisor, 20 (or
18%) were revenue bonds, and 79 (or 70%) were sold by states rated
in the AA credit rating category. The mean size of bond issues was
$330 million reflecting a relatively large average size with bond issue
sizes ranging from the tiniest issue of $6.365 million to the largest at
$1.074 billion. Refinancing bond issues from 35 different states
were utilized in the sample. For the entire universe of state
government refinancing bond issues sold between January 1, 2002
and December 31, 2009, 246 (or 66%) were sold on a negotiated
basis, 293 (or 78%) used an independent financial advisor, 97 (or
26%) were revenue bonds, and 311 (or 83%) were sold by states
rated in the AA credit rating category. The mean size of bond issues
was $259 million with bond issue sizes ranging from the tiniest issue
of $1.975 million to the largest at $1.5 billion. This comparison
demonstrates that the sample serves as a relatively good match with
the universe as a whole along these issuer and issue characteristics
(although revenue bonds and AA rated states may be slightly under
sampled).
Most importantly for the purposes of this study, Table 5 shows the
descriptive breakdown of bond issues by degree of upfront savings
structure. The greater the number for degree of upfront refinancing
savings structure, the more the savings was structured on an upfront
basis. 48 bond issues (42% of the sample) employed savings
structures where the degree of upfront savings was actually negative
(i.e., the states were amortizing the refinancing bonds faster than the
original bonds amortization schedule). 71 bond issues (63% of the
sample) utilized savings structures where the degree of upfront
refinancing savings was 1% or lower (ranging from 1% to -6.68%).
This signifies that 63% of the sample of bond issues utilized a bond
structure that produced very little or no degree of upfront refinancing
savings. Another seven bond issues (6% of the sample) utilized
savings structures where the degree of upfront refinancing savings
was between 1% and 2%. If we set a threshold whereby savings
structures between 1% and 2% represent a relative modest amount
of upfront refinancing savings, 69% of the sample employed savings
structures that produced relatively modest or no upfront refinancing
savings. 35 bond issues (31% of the sample) utilized savings
structures where the degree of upfront refinancing savings was 2% or
506
LUBY
TABLE 5
Upfront Refinancing Savings Structure Analysis
Random Sample of State Refinancing Bond Issues Sold Between
01/01/2002 – 12/31/2009: Degree of Upfront Refinancing Savings
>-1% -1% to 0% to 1% to 2% to 3% to 4% to 5%>
0%
1%
2%
3%
4%
5%
Number of Bond
Issues with this
Savings
Structure
24
24
23
7
14
Percentage of
Bond Issues with
this Savings
Structure
21.2
%
21.2
%
20.4
%
6.2%
12.4
%
5.3% 1.8% 11.5
%
Cumulative
Percentage of
Bond Issues
21.2
%
42.4
%
62.8
%
69%
81.4
%
86.7
%
6
2
13
88.5 100%
%
Note: * Categories represent the amount of bond issues where the difference
between the amortization of the first three years of refunded bond principal as a
percentage of entire bond issue principal minus the amortization of the first
three years of refunding bond principal as a percentage of entire bond issue
principal is in the stated range. The greater the number, the more the savings
were structured on an upfront basis.
greater (ranging from 2% to 45.54%). If we set a threshold whereby
savings structures greater than 2% represent more considerable
upfront refinancing savings, 31% of the sample employed savings
structures that produced substantial upfront refinancing savings.
In sum, a clear majority of the bond issues employed little or no
upfront savings structure. However, some issuers did utilize this type
of debt-related budgetary gimmick. While it is beyond the scope of
this paper, future research should explore why these issuers chose an
upfront refinancing bond savings structure. Nevertheless, even
though the descriptive results represent “negative findings” in the
sense that most states did not utilize this debt-related budgetary
gimmick, the results do serve as a contribution to the public finance
literature. Petersen (2003) suggested that the use of upfront bond
refinancing savings structures was one way that states use fiscal
alchemy to balance their books. The results on this paper did not
507 indicate that such type of budget gimmickry is pervasively employed
by the states thus providing a quantitative estimate to the relative
usage size and scope of the strategy Petersen described in previous
research.
In addition, the empirical findings have significant
theoretical and policy implications. The next section of the paper
examines such implications.
THEORETICAL AND POLICY IMPLICATIONS
The third part of this paper involves the application of the
empirical findings to theory and practice. These findings have both
theoretical and policy implications relating to principal-agent theory
and the efficacy/necessity of debt restrictions, respectively.
Generally-speaking, principal-agent theory revolves around conflicts
of interest between two parties, a principal and an agent, whereby the
principal purchases goods or services from an agent whose interests
may not be congruent with the goals of the principal. The principalagent model used in this paper relies on the general agency theory
framework and assumptions utilized in the debt management
literature (Simonsen and Hill, 1998). From an agency theory
perspective, in the case bond refinancing, the public is the principal
and elected officials working through their financial managers are the
agent. In general, the public favors efficiency in government finance
activities and does not prefer debt management decisions that
produce short-term benefits at long-term costs as current taxpayers
do not want themselves or the future taxpaying public (which may
include their children and grandchildren) to be burdened by shortterm reckless debt management decisions made by the prior
generation’s elected officials and financial managers. Thus, the
public’s goal is the long-term cost efficient management of state
debt.2
The elected official, who ultimately oversees the state’s bond
practices (usually the governor or state treasurer), is the agent to the
public. The interests of the elected official are generally short-term
and primarily consist of electoral self-preservation which by its very
nature entails reelection. Reelection is achieved by keeping taxes low
(i.e., maintaining or decreasing tax rates) while raising or maintaining
government service levels, both of which can be facilitated by certain
debt refinancing practices. The elected official’s interests are
accomplished through the debt refinancing decisions made by his
508
LUBY
financial manager who acts as an agent on behalf of his principal, the
elected official. However, the bond issuance process is quite
technical and the decisions made by elected officials working through
their financial managers are often not transparent and depending on
a state’s debt disclosure requirements may not easily be known or
understood by the public. Thus, there is a strong information
asymmetry between the principal (the public) and its agents (elected
officials and financial managers) as it relates to the nuances of bond
refinancing decision-making. Figure 1 details the principal-agent
relationship between the parties in the municipal bond refinancing
process as well each party’s goals and interests.
Theoretically, principal-agent problems are said to exist when
management activities involve delegated bureaucratic decisionmaking and are plagued by information asymmetry, and thus, allow
for the prospect of moral hazard. The decision on how to structure
refinancing bond savings, a subtle but important public financial
management choice, meets these requirements. More specifically
and as described earlier, many state and local governments allow
public financial managers to capture the timing of refinancing bond
savings in any permutation: upfront, equal in every year, proportional,
back-loaded, etc. (i.e., there exists bureaucratic delegation).
Moreover, the refinancing savings structure decision is not readily
transparent to the principal since many states do not proactively
FIGURE 1
Municipal Bond Refinancing Process
Participants and their Goals and Interests
509 provide nuanced information about their bond sales to the public (i.e.,
information asymmetry is present). Finally, the temptation to
structure refinancing savings upfront may be strong for public
financial managers since it provides elected officials the ability to
increase spending, cut taxes, or avoid painful spending cuts in the
near term. However, the cash infusion from upfront refinancing
savings effectively serves as one-time (or short-term) revenue
infusion, which combined with any of the aforementioned budget
decisions, will only exacerbate or help cause a structural budget
deficit (i.e., prospect of moral hazard). Thus, the use of an upfront
refinancing savings structure offers evidence of a classic principalagent problem in public financial management. In this policy
environment, the elected official chooses an alternative policy option
(debt refinancings with upfront savings structures) to meet his
interests (i.e., lower principal and interest payments in the short-term
so as to avoid the possible electoral wrath of the public often
associated with tax increases or spending cuts) at the expense of his
principal’s interests (i.e., lower principal and interest payments over
the long-term). Figure 2 details in visual form how the use of upfront
refinancing savings structures provides evidence of an agency
problem.
The results of the empirical analysis carry some interesting
implications as it relates to the agency theory and the necessity of
debt restrictions as applied in this context. First, the finding of only
very moderate use of upfront refinancing savings structures (i.e., only
31% of all state government bond refinancings used savings
structures where the three year amortization structure difference
FIGURE 2
Agency Theory and Upfront Refinancing Bond Structures
510
LUBY
between the refunded and refunding bonds was 2% or greater)
questions the explanatory power of agency theory in understanding
decision-making by public financial managers. That is, the use of
upfront refinancing savings structures in bond refinancings provides
agents (elected officials and debt managers) a perfect opportunity to
make decisions that provide a short-term benefit to the agent at a
long-term cost to the principal (the public) in the administrative
management context where information asymmetry is present and
delegated bureaucratic decision-making is available. Thus, a priori,
agency theory would predict that upfront refinancing savings
structures would be used extensively by state governments in this
seemingly unending era of fiscal austerity. Since it has been shown
that most state governments did not capitalize on such opportunity
(i.e., they did not generally use an upfront refinancing savings
structure), it seems that agency theory does not provide an adequate
theoretical explanation for the decision-making behavior of most of
these state governments. Thus, this finding does not provide support
for prior research that directly addressed the issue of principal-agent
problems in the municipal bond process finding that a substantial
agency problem existed (Simonsen and Hill, 1998).
As such, an alternative theoretical framework that stresses
influences beyond individual self-interest may offer a better
explanation for the behavior of these state governments. For
example, based on this finding, one might hypothesize that state level
public financial managers are generally motivated and influenced by
their understanding of prudent debt policy as developed in their
education and professional training in making bond refinancing
decisions. As described in this study’s literature review, recent
research that described public financial managers influenced by
factors beyond self-interest such as professional norms and
individual values may offer a better explanatory theoretical
framework for understanding this type of public financial
management decision-making behavior (Carroll and Marlowe 2006;
Burke 2006; Rivenbark 2006; Robbins and Miller 2006; Stalebrink
and Sacco 2006). However, further systematic research is needed in
analyzing the use of upfront refinancing savings structures in local
government refinancing transactions in order to definitively determine
the extent of this debt management technique by all subnational
governments.
511 Second, this finding related to principal-agent theory has direct
policy implications as well. In recent years, several states have
placed greater restrictions on their debt management practices due
to the perceived existence of agency problems plaguing this area of
financial management. That is, some observers in the municipal
finance arena speculate that the interests of public financial
managers (i.e., agent) acting on behalf of elected officials may not be
aligned properly with the debt management goals of the public (i.e.,
principal). Therefore, statutory debt restrictions are needed to better
ensure that a public financial manager’s actions reflect the desires
and policy goals of the public, which are assumed to be the long-term
cost efficient and effective management of state debt. However,
reducing managerial autonomy is not costless and, thus,
governments need to be sure such restrictions are truly necessary in
order to determine their overall efficacy (Luby, 2009).
Practically-speaking, the finding of very moderate use of upfront
refinancing savings structures casts doubt on the wisdom of applying
blanket restrictive managerial control mechanisms on all states’ debt
managers as a means of controlling opportunistic managerial
behavior and, thus, mitigating agency problems. That said, based on
the fact that some states did, in fact, engage in some opportunistic
behavior as it relates to bond refinancing, statutory restrictions may
be appropriate in some states but certainly not in all. However, even
in these states, more formalized/stricter debt policy guidance and
greater disclosure requirements may accomplish the same goal as
statutory restrictions without the costs associated with limiting
financial managerial autonomy.
CONCLUSION
The escalating use of debt finance combined with steadily
declining interest rates over the last decade have provided state and
local governments ample bond refinancing opportunities that have
the potential to substantially reduce the interest cost component of
their operating budgets. However, the ever-present fiscal stress
experienced during this time period has incented subnational
governments to contemplate refinancing savings structures, including
the upfront refinancing savings structure explored in this paper, that
emphasize short-term budget relief at the expense of maximizing
aggregate present value interest cost savings. These structures also
512
LUBY
exacerbate or help create structural budget deficits as they act like
other “one-shot” revenue techniques such as asset sales and
payment deferrals.
Thus, these debt refinancing structures
effectively serve as a budget gimmick that state and local
governments can use to achieve “short-term” budget balance. The
first part of this paper offers substantial detail on the mechanics and
impact of the upfront refinancing bond savings structure as a means
of better understanding this type of fiscal alchemy.
This paper’s empirical analysis of state government utilization of
upfront bond refinancing savings structures attempts to shed light on
managerial decision-making in an area of public financial
management that generally lacks transparency yet offers
bureaucratic autonomy and, thus, investigates a policy area where, at
least theoretically, agency problems are most likely to be common
and pervasive if they do, in fact, exist. However, the results of this
study demonstrate that most state governments did not employ
upfront refinancing savings structures in their bond refinancings.
This finding provides evidence that a pervasive agency problem may
not be present in the management of state debt. Thus, these results
seem to question the grand use of agency theory in helping to
understand this area of public financial management. In addition,
from a policy perspective, this finding offers empirical support for
generally minimizing statutory debt restrictions on public financial
managers as this paper’s analyses seem to demonstrate that these
managers usually make prudent financial decisions as it relates to
bond refinancing. That said, some states did utilize an upfront
refinancing savings structure and the wisdom of applying statutory
debt management restrictions to these states is clearly still
debatable.
The states that did utilize upfront refinancing savings structures
provide a fertile area of future research. That is, from a policy
perspective, it would be instructive to determine the various factors
that impact the refinancings savings structure decision as a means of
better understanding decision-making in this area of public financial
management and to offer some specific policy and management
recommendations that could serve to mitigate the agency problem to
the extent it does exist. For example, does the existence of formal or
informal debt policies reduce the likelihood of utilizing upfront
refinancing savings structures? Does the use of an independent
513 financial advisor impact decision-making in this area? Another area
of inquiry may be whether the use of these structures is contingent on
the level of fiscal stress or financial condition of the state
government. Research of this type and scope would be very valuable
in understanding the impact of various bond issue and issuer
characteristics on the decision-making of public financial managers
with an “eye” towards developing practices that encourage long-term
fiscally prudent actions as it relates to debt management.
NOTES
1. A sample was used in this study due to the significant time it
takes to construct the dependent variable in this analysis. The
data for the dependent variable comes from two source
documents comparing the refunded and refunding bonds
amortization. In addition to the substantial time it takes to
acquire all the information on the refunded bonds from the
source documents, the dependent variable for each bond issue
needs to be constructed comparing and calculating the difference
in amortization schedules between the refunded and refunding
bonds, which also is time consuming. As stated elsewhere in the
paper, the sample is relatively large (30% of the universe) and
represents a good match of the universe as shown in Table 4,
thus enhancing the external validity of the study.
2. One could argue that the public’s goal is not long-term,
sustainable budgeting practices via the use of debt but rather to
prefer debt management practices that allow for taxes not to be
raised or services not to be cut in the short-term (e.g., using
upfront refinancing structures) at the expense of long-term
finances. However, the lack of the citizenry’s general knowledge
of the tradeoffs associated with various debt refinancing
structures makes it difficult to ascertain the public’s general
preference.
Thus, this paper’s model assumes citizen’s
preferences for long-term prudent debt management activities.
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