(4) effects of gaap regulation and bond market interaction on local government disclosure

Journal of Accounting and Public Policy 23 (2004) 23-52

www.elsevier.com/locate/jaccpubpol

The efects of GAAP regulation and bond market interaction on

local government disclosure A

ngela

K.

Gore

*

Department of Accounting, Lundquist College of Business, University of Oregon, Room 1208,

Eugene, OR 97403, USA

Abstract

This study examines the efects of disclosure regulation on municipal managersÕ

incentives to disclose financial report information to the bond market. I compare disclosure levels of municipal governments in Michigan, which requires GAAP, with those in Pennsylvania, which has unregulated disclosure. In the absence of disclosure regulation I find that managers have bond market-induced incentives to disclose information. Controlling for other incentives to disclose, the evidence implies that regulation induces additional disclosures for low-debt governments, and is not binding for highdebt governments. Ó 2003 Elsevier Inc. All rights reserved.

Keywords: Regulation; Disclosure; Bond market; Local governments

1. Introduction

Although financial reporting and disclosure have been regulated for over 60 years, relatively few studies have evaluated the efects of these regulations. The lack of research critically evaluating the efects of disclosure regulation is surprising given the impact that this regulation has had on the accounting

* Tel.: +1-541-346-3329; fax: +1-541-346-3341. E-mail address: [email protected] (A.K. Gore).

24 A.K. Gore / Journal of Accounting and Public Policy 23 (2004) 23-52

profession (Healy and Palepu, 2001). Disclosure regulation research is especially critical in light of recent calls for increased regulation due to the corporate accounting scandals. Regulation proponents assert that market failures necessitate mandatory disclosure, and that in the absence of regulation, organizations lack incentives to voluntarily disclose adequate levels of information. Critics argue that market forces produce optimal levels of disclosure, and provide arguments against the efcacy of market failures. 1 Empirical evidence on disclosure regulation is extremely limited, however, primarily due to data constraints (Healy and Palepu, 2001).

The purpose of my paper is to provide further empirical evidence about the efects of disclosure regulation on information production. I do so in the context of the municipal bond market, for two reasons. First, governmental GAAP is being made mandatory in many states at substantial cost. Second, because not all states require GAAP, municipalities allow an examination of disclosure regulation in a relatively controlled experiment.

I first examine disclosure in an unregulated case, and hypothesize that bond market incentives are sufcient to induce disclosure. I next examine the influence of regulation on disclosure and hypothesize that for any given level of regulation, mandated disclosure induces information production for low-debt municipalities, and is non-binding for the rest. My empirical tests compare municipal disclosure levels in a state that requires GAAP (Michigan) with those in a state with unregulated disclosure (Pennsylva- nia). 2

My analysis indicates two main results. First, in the unregulated state, I find a significant positive association between disclosure levels and proxies for bond market interaction. This evidence suggests that in the absence of regulation, municipal managers disclose financial information in response to bond market incentives. This result is interesting because prior studies have had conflicting results about the relation between disclosure and proxies for debt. For example, studies such as Robbins and Austin (1986) and Evans and Patton (1987) find positive relations, while others such as Evans and Patton (1983), Ingram and DeJong (1987) and Copley (1991) find either no statistically significant relation or report mixed results. It is also interesting because it shows municipal managers act rationally in response to capital market incentives, opening an avenue to future disclosure regulation research with implications that extend beyond the municipal sector.

1 For summaries of the arguments for and against disclosure regulation, see Easterbrook and Fischel (1991), Watts and Zimmerman (1986), and Leftwich (1980).

2 I define ''regulated'' disclosure as requiring GAAP regulations, and ''unregulated'' disclosure as requiring neither GAAP nor other, state-mandated disclosure regulations.

A.K. Gore / Journal of Accounting and Public Policy 23 (2004) 23-52 25

Second, I find that GAAP disclosure levels are significantly higher in the regulated state than in the unregulated state. The diference in disclosure levels is significantly smaller among those governments with higher debt, however, which implies two things. First, this evidence suggests that regulation is not binding for governments with high debt levels. 3 In other words, regulated governments with high debt levels are required to disclose GAAP information that they would have voluntarily disclosed in the absence of regulation. Sec- ond, it implies that regulation induces the production of information, or is binding, for governments with low debt levels, indicating that these governments may incur costs by being forced to disclose more information than the market requires. These results are interesting given that prior governmental research (e.g., Ingram and DeJong, 1987; Copley, 1991) does not find a significant diference in disclosure level between states that require GAAP and states with unregulated disclosure.

The evidence presented in this paper is relevant for evaluating the implications of the recent trend of increasing GAAP disclosure requirements (Barth and Murphy, 1994). For example, the GASB recently enacted a new disclosure standard for governments that expands the level of required disclosures (GASB Statement No. 34). Opposition has been strong, due to the costs of implementing and monitoring this standard, and due to questions about whether there is demand for the information (Copley et al., 1997). My results suggest there is an economic basis for governmentsÕ choice to voluntarily provide financial information. Mandating more information imposes costs on governments with lower bond market interaction, and ultimately the taxpayers, while conferring benefits to public accountants by increasing monitoring costs.

One caveat needs to be considered when interpreting my results, however. My analysis focuses on disclosure incentives in the context of bond markets. Therefore, I do not consider alternative perspectives addressed in prior studies, such as disclosure incentives derived from political markets (Baber, 1990). However, as discussed later in the paper, there is a growing body of evidence that indicates capital market participants are the primary users of the financial reports, while voters rarely use them. In addition, while I do not focus on political incentives to disclose, I do use control variables to represent them in the empirical analysis.

The remainder of the paper is organized as follows. In Section 2, I discuss the governmental accounting environment, and in Section 3, the theory and hypothesis development. Section 4 describes the research design, Section 5 discusses the results, while Section 6 concludes.

3 The term ''binding'' refers to a binding constraint, applying the standard definition found in most microeconomic theory texts.


2. Governmental accounting environment

2.1. Governmental accounting regulatory environment

In this paper, the term ''GAAP'' refers to standards issued by the Gov- ernmental Accounting Standards Board (GASB), the governmental equivalent of the Financial Accounting Standards Board (FASB). The GASB prescribes the minimum GAAP requirement for financial reports as a set of general purpose financial statements, which are comprised of combined financial statements and footnote disclosures. Some governments choose to prepare a more comprehensive report known as the comprehensive annual financial report (CAFR), however. In addition, I use the term ''non-GAAP'' disclosure to refer to financial report disclosures that are not required under GAAP or state- specific regulations. 4

Although the GASB issues GAAP standards, the level of disclosure required of local governments is regulated by the states in which they are located. States may require that local governmentsÕ financial report disclosures follow GAAP, state-specific regulations, or may be unregulated. Approximately 27 states require that local governments follow GAAP, 14 have state-specific disclosure regulations, and the remaining nine have unregulated disclosure (NASACT, 1996). 5

2.2. The primary user group--the bond market

The remainder of my paper examines the costs and benefits of disclosing financial report information. The determination of whether the disclosure of information is a net cost or benefit depends in part upon which financial statement userÕs perspective is adopted (Beaver, 1998). Although the GASB identifies three potential user groups, which are voters, regulators, and the bond market, I take the position that the primary users of local government financial reports are members of the bond market. This position is supported by both focus groups commissioned by the GASB (AAA, 1996), and by prior literature (Gafney, 1986; Jones et al., 1985; Copley et al., 1997).

4 The traditional term for disclosure outside of the set of GAAP disclosures is ''voluntary disclosure'' (see Core, 2001). However, because all disclosure is voluntary in Pennsylvania, it renders the term ''voluntary'' confusing in my study.

5 The State of Michigan adopted GAAP in 1968. An examination of news articles from this time period did not reveal the reasons why State ofcials decided to adopt GAAP. However, discussions with State of Michigan Treasury Department ofcials indicate that GAAP was most likely adopted because Michigan had recently re-convened the state constitutional convention, and at that time enacted mandatory audit requirements. When new GAAP and auditing regulations came out in 1968, they were automatically adopted because it was in the state constitution.


In the GASB focus group sessions, user groups representing voters and regulators indicate that the two primary sources of financial information are the budget; and conversations with individuals employed by the government. The majority of these user groups do not use the annual financial reports.

Evidence in the literature also supports the proposition that bond market participants commonly use the annual financial reports, while voters and regulators do not. Empirical research, discussed in detail in Ingram and Robbins (1987), shows that bond market representatives use governmental financial reports to assess default risk. Other studies such as Zimmerman (1977), Gafney (1986), Jones et al. (1985), and Copley et al. (1997) suggest that citizens rarely use governmental reports.

Although a growing body of evidence indicates that bond market participants use financial reports, the literature has had inconsistent results about the relation between debt proxies and disclosure levels. Some studies such as Robbins and Austin (1986) and Evans and Patton (1987) find positive relations, while others such as Evans and Patton (1983), Ingram and DeJong (1987) and Copley (1991) find either an insignificant relation or report mixed results. However, these studies confine their analyses to large municipalities, do not distinguish between GAAP and non-GAAP disclosures, and most do not consider diferences in statesÕ regulatory environments.

2.3. Disclosure regulation

While theory supports the proposition that disclosure regulation results in higher disclosure levels, municipal disclosure studies have not found such a relation. For example, Ingram and DeJong (1987) examine whether the presence of a state requirement mandating GAAP compliance afects citiesÕ disclosure levels, and find no significant diference in disclosure levels between GAAP-regulated and unregulated disclosure states. Two issues potentially af- fect a straightforward interpretation of their evidence, however. First, their sample is drawn from across all states without controlling for diferences in regulatory environments that potentially afect the role of financial information in the bond market. For example, Colorado only permits the issuance of revenue bonds, which require covenants. In contrast, Massachusetts only permits general obligation bonds, which are backed by the full faith and credit of the governments issuing them. Creditors in Colorado may therefore have relatively greater incentives to monitor local governments through financial reporting. 6

Second, Ingram and DeJong only study large cities, with a mean population of 143,000. Gore et al. (2004) finds that large cities tend to disclose more

6 For example, FSA, a municipal bond insurer, states on their website that revenue bonds typically require more analysis than do general obligation bonds.


information because they are more likely to access the bond market. Therefore, the finding of no diference in disclosure between large cities in GAAP-regulated and unregulated disclosure states is not surprising.

In another study, Copley (1991) uses a dummy variable to control for whether municipalities are in GAAP-regulated states, and finds this variable is insignificant. However, CopleyÕs measure of disclosure includes both GAAP and non-GAAP disclosures. The inclusion of non-GAAP disclosures could cause the lack of significance because municipalities can voluntarily disclose information regardless of whether the state requires GAAP. In addition, their analysis is again restricted to large cities, with a mean population of 177,000.

In contrast to these studies, I employ a research design that restricts the sample to two states in order to minimize the potentially confounding efects of state-specific regulations, and also include smaller municipalities. In addition, my disclosure measures distinguish between GAAP and non-GAAP disclosures.

3. Theory and hypothesis development

3.1. Basic theoretical framework of municipal disclosure

My focus is on the relation between disclosure and the bond market. In so doing, I expand ZimmermanÕs (1977) positive theory analysis, which focuses on political incentives for disclosure, to explicitly consider the efects of regulation and bond market incentives on disclosure. In order to develop the theory, I need two assumptions. First, I assume that municipal managersÕ primary motivation for financial disclosure is in response to bond market incentives, and that municipal managers have incentives to lower municipal debt costs. For example, ceteris paribus, if lower debt costs lead to lower property taxes, which translate into more votes for municipal ofcials, then municipal ofcials will want to lower borrowing costs. Second, I assume the bond market is competitive, which implies that bond issuers fully bear transaction and information costs in the form of higher debt costs.

Given asymmetric information whereby investors are unable to fully determine the default risk characteristics of issuers, managers use increased disclosure to reduce the cost of capital in two ways. First, to reduce the costs associated with the information asymmetry component of the cost of capital, such as those due to transaction costs. Managers issuing debt therefore have incentives to voluntarily disclose information to reduce the information asymmetry problem, thus reducing the cost of financing (Myers and Majluf, 1984). Second, managers use disclosure to reduce costs associated with investorsÕ information risk. Barry and Brown (1985) argue that when disclosure is not


perfect, investors bear risks in forecasting their investmentsÕ future payof. 7 If this risk is not diversifiable, investors will demand an incremental return for bearing the information risk. Managers therefore have incentives to voluntarily disclose information to reduce investorsÕ information risk, and hence lower their cost of capital. The results of empirical studies are consistent with theory, showing that public financial disclosure reduces bond yields for both corporate and government issuers (see Sengupta, 1998; Benson et al., 1991, respectively).

Municipalities that have a high level of bond market interaction stand to gain relatively more benefits by disclosing information. This leads to the following hypothesis:

H1: Ceteris paribus, within a state that has unregulated disclosure, there is a positive association between disclosure level and debt.

3.2. Disclosure regulation

When disclosure is mandated by regulation, it creates a minimum level of disclosure. Assuming there is a positive association between disclosure and debt, municipalities can have three general forms of disclosure equilibrium levels (see Fig. 1). For some governments, the mandated disclosure level is set above the municipalitiesÕ optimal level in the unregulated environment, and is therefore binding (see Region 1 of Fig. 1). 8 This level of regulation unam- biguously induces the production of information, imposing additional non- productive costs on municipalities and their taxpayers.

For other governments, the equilibrium level is equal to the level set by regulation, and so includes the set of required GAAP disclosures. This second scenario is not likely because it is unlikely that regulators can determine an optimum level of disclosure for all governments. Because GAAP is designed to fit all state and local governments, including 35,000 counties, cities, towns, and villages ranging in population from less than 1,000 to several million, it is unlikely to be optimal for many of them.

7 One may conjecture that investors merely need to examine bond ratings in order to assess risk. In the case of municipal bonds, however, many issues are not rated by ratings agencies, and for these unrated issues, public disclosure is especially important to help resolve information asymmetry. Empirical research such as Fairchild and Koch (1998) finds the decrease in debt costs from public disclosure is greater for unrated issues. Even when bonds are rated, however, the ratings alone are not sufcient for investors to forecast risk. Bond ratings only represent a range for the probability of default, not the probability of recovery, and the ratings agencies do not assess the liquidity of the underlying assets.

8 The term ''optimal'' refers to optimal disclosure for the municipal government, rather than financial statement users. As such, I implicitly assume that the level of state regulation is exogenous. I acknowledge that there may be additional cost-benefit concerns involved with statesÕ decisions to mandate GAAP, however, I consider them outside the scope of this study.


Fig. 1. Hypothesized relation between total disclosure and bond market interaction. Note: This figure shows the relation between disclosure and debt, and does not consider other incentives for disclosure. ''GAAP'' represents the level of disclosure required under GAAP regulations. ''Regulated GovernmentsÕ Disclosure'' represents the relation between debt and disclosure for governments required to comply with GAAP. Note that Regulated Governments in Region 1 (low debt) disclose at levels required by GAAP; while Regulated Governments in Region 2 (high debt) voluntarily disclose above the levels required under GAAP. ''Unregulated GovernmentsÕ Disclosure'' represents the relation between debt and disclosure for governments that do not have to comply with disclosure regulations.

Still other governments have equilibrium levels of disclosure above the required level (see Region 2 of Fig. 1). In this case, the mandated disclosure level is below that which is optimal for governments, and is not binding.

Assuming municipalities are faced with varying demands for and quantities of debt capital, then the benefits of information production will vary across governments. Absent regulation, governments with little bond market interaction lack incentives to disclose information. In a GAAP-regulated state, however, governments with low bond market interaction are required to disclose more information than they would in the absence of regulation. There- fore, consistent with Fig. 1, for the subset of governments with low debt, the level of GAAP disclosures will be higher in the GAAP-regulated state than it is in the unregulated disclosure state. In other words, regulation will be binding for low-debt governments, which leads to the following hypothesis:

H2A: Ceteris paribus, for the subset of governments with low debt, the level of GAAP disclosures is higher in a state that requires GAAP than it is for governments in a state that has unregulated disclosure.


Governments with a relatively higher level of bond market interaction will voluntarily comply with GAAP if compliance results in lower borrowing costs, as suggested by some of the literature discussed previously. In this case, the level of GAAP disclosures should be the same regardless of whether the state requires GAAP. In other words, for high-debt governments, regulation will not be binding. This leads to the following hypothesis:

H2B: Ceteris paribus, for the subset of governments with high debt, the level of GAAP disclosures is the same in a state that requires GAAP as it is for governments in a state that has unregulated disclosure.

The combination of H2A and H2B represents a joint test of the efects of regulation and bond market interaction on information production. Theoret- ically, there should be a large diference in GAAP disclosure between regulated and unregulated disclosure states for low-debt governments, and a relatively smaller, or no diference between the two states for the high-debt governments, consistent with Fig. 1. In addition, note that I confine my analysis of H2 to GAAP disclosure because a priori, it is unknown how GAAP regulation afects non-GAAP disclosure.

4. Research design and tests of hypotheses

4.1. Sample selection

I employ data from Michigan, which requires GAAP, and Pennsylvania, which has unregulated disclosure (NASACT, 1996). 9 Michigan is chosen because it is a state that both requires and enforces the use of GAAP. 10 I confine my analysis to two states to ensure that the municipalities in the sample are as much alike as possible, with respect to non-disclosure regulatory and legal constraints. Michigan and Pennsylvania are chosen because they closely match each other in many ways other than the level of disclosure regulation. This is important because my analysis relies on the assumption that, absent the requirement of GAAP disclosure, governments in the regulated state would disclose information at a level similar to those in the unregulated state.

9 An alternative research design would encompass the examination of governments in one state, before and after the enactment of GAAP disclosure requirements. This is not feasible in part due to the lack of data availability.

10 Discussions with State of Michigan regulators reveal that they routinely test GAAP compliance by examining a sample of municipal financial reports in detail. If they find that a financial report is not in compliance with GAAP, then the municipality must re-submit revised reports within a specified time frame.


However, because there are only nine states that have unregulated disclosure, I control for the diferences that are most likely to afect the level of financial report disclosure.

Michigan and Pennsylvania are similar in the following respects. Both states have city and township governments that do not have overlapping boundaries, to ensure that the financial reporting relation is clear. This criteria ensures that municipalities only record transactions (such as debt) for that specific municipality, rather than for other entities as well (for example, school districts). 11 The states are also similar with regards to the types of bonded debt allowed, both general obligation and revenue bonds, as well as the restrictions on the amount of debt, in that both allow cities to issue debt directly. I use these requirements because regulations afecting incentives to issue debt can indi- rectly cause variation in disclosure. 12 Finally, both states require local governments to be audited, however, Pennsylvania allows the choice of either an external or an internal auditor. 13 I use this last requirement because mandated audits potentially influence the level of GAAP disclosures.

Table 1, Panel A describes the selection criteria for the Michigan sample. Similar to Zimmerman (1977), I select those governments with populations greater than 10,000, for a total of 166 observations. Note that the use of this restriction efectively biases against finding results because smaller governments are less likely to have interaction with the capital markets (Gore et al., 2004). From these, I collected financial reports for 88 municipalities from the Mich- igan Department of Treasury for 1995. 14 I limit the analysis to one year because disclosure policies appear to remain relatively constant over time (Botosan, 1997), and due to the availability of data.

Financial report data for the Pennsylvania municipalities are obtained in a similar manner. I randomly selected 92 financial reports from those governments with populations greater than 10,000, roughly equivalent to the number gathered from Michigan (see Table 1, Panel B). I collected a total of 87 reports,

11 Note that this does not refer to component units, but rather, organizations that are not normally considered component units, such as school districts.

12 I hypothesize that there is a positive relation between debt and disclosure. If a state restricts the amount of debt issued, then it is possible that I could find no relation between debt and disclosure, which efectively biases against finding results.

13 Internal auditors are defined as auditors that agree to perform one municipal audit per year, and may or may not be Certified Public Accountants. The audits performed by internal auditors are in accordance with GAAP standards. However, I am unable to assess the impact the use of internal auditors may have on audit quality.

14 Local governments are required to submit two copies of their financial reports to the Michigan Department of Treasury on an annual basis. The Department of Treasury contributed the ''second copy'' of the financial reports to this study for approximately one half of the cities and townships with populations in excess of 10,000. This sample cannot be construed as random, however, there is no known bias in the selection of individual financial reports.


Table 1 Summary of financial report selection procedures

Panel A: Michigan sample

Total local governments in Michigan Less governments with population <10,000 and

governments other than cities and townships Total Michigan cities and townships with populations

>10,000 Financial reports randomly eliminated Final sample, collected from Michigan Department

of Treasury

Panel B: Pennsylvania sample

Total local governments in Pennsylvania Less governments with population <10,000 and

governments other than cities and townships Total Pennsylvania cities and townships with

populations >10,000 Randomly selected Financial reports collected directly from municipalities Financial reports collected from Pennsylvania Depart-

ment of Community and Economic Development Financial reports not available Total financial reports Final sample

Panel C: Total sample Cities Townships Total

1,800 1;634

166

78 88

2,498 2;288

201

92 65 22

05 90 87

Michigan

44 44 88

Pennsylvania

21 66 87

Total

65 110 175

through a combination of requests to the municipalities and the Department of Community and Economic Development in Pennsylvania. The sample selection procedures yield a total sample of 175 governments (see Table 1, Panel C).

4.2. Tests of hypotheses

4.2.1. Regression specification for H1

I use the following regression specification to test my first hypothesis:

DISCLOSUREit ¼ ai þ b1iPOPit þ b2i

CITYit þ b3iAUDITSit

þ b4iDEBTit þ eit

ð1Þ

where

DISCLOSUREit is the value of the GAAP, non-GAAP, or TOTAL disclosure index in year t for government i,

34

A.K. Gore / Journal of Accounting and Public Policy 23 (2004) 23-52

AUDITSit is the number of municipal audits performed in year t by government iÕs auditor, POPit is the log of total population in year t for government i, CITYit is a dummy variable where 1 indicates the city form of government and 0 indicates the township form of government, DEBTit is total debt/population in year t for government i.

The dependent variable is measured alternately using GAAP, non-GAAP, or TOTAL (the sum of the two) disclosure indices, described in detail below. Each disclosure index measures the number of items satisfied by the financial report. H1 examines whether DEBT is positive and significant within Penn- sylvania, the unregulated disclosure state.

4.2.1.1. Disclosure indices. I measure disclosure with two disclosure indices, one measuring the extent of GAAP disclosure, and the other measuring the extent of non-GAAP disclosure. The GAAP index is comprised of GAAP disclosures identified on a checklist provided by the Michigan Department of Treasury, the entity that oversees local governments in Michigan. The checklist, which only contains GAAP disclosures, is used to determine whether municipalitiesÕ financial reports are in compliance with GAAP. When compiling the GAAP index, I retain all disclosures on the checklist that apply to all municipalities. 15 Otherwise, the index could proxy for complexity, as larger and more complex governments would tend to score higher. 16 The non-GAAP disclosure index includes those disclosures identified through the prior literature and through Standard & PoorÕs (1986) as useful to bond market representatives.

I compile the two indices from disclosures contained within the annual financial reports. The GAAP disclosures are drawn from elements contained within the basic financial statements, as well as from the footnotes. Non-GAAP disclosures are from the basic financial statements, footnotes, and supplementary statistical information. Each disclosure is counted as part of the disclosure index if it is present, and for the GAAP index, appears to be substantially in compli-

15 For example, commitments and contingencies are required to be disclosed under GAAP, and this disclosure is listed on the checklist. However, many municipalities do not have contingencies. I therefore exclude this disclosure, since it is likely to proxy for complexity.

16 Prior studies vary as to disclosure index construction. Some studies such as Robbins and Austin (1986) use indices comprised of disclosures found useful to the bond market. The use of such an index would be biased against finding evidence consistent with my hypotheses if some of the disclosures required by GAAP are not useful to creditors. Rather than using one of these indices, I use the checklist because it is a broad measure of GAAP, is somewhat more objective than those used in prior studies, and also because it references recent disclosures. For example, studies such as Copley (1991), Ingram and DeJong (1987), and Ingram (1984) use disclosures available in the mid- 1980s, and so do not include recent GASB pronouncements such as the investment disclosure.


ance with GAAP requirements. No attempt is made to assess the quality of particular disclosures. The GAAP index contains 18 disclosure elements that are required by GAAP (see Appendix A), while the non-GAAP disclosure index is comprised of thirteen disclosures that are not required by GAAP (see Appendix B). Equal-weighted index scores can therefore range between 0 and 18 for the GAAP index, and between 0 and 13 for the non-GAAP disclosure index. 17

4.2.1.2. Debt. The debt variable represents current and future incentives to reduce the costs of issuing debt. For current debt, the disclosure of information reduces the enforcement and monitoring costs of existing contracts. It also reduces the costs of future forays into the debt market. The bond market incentives should increase as the amount of debt, and therefore, the level of interaction with the bond market, increases, and as such is expected to be positively associated with disclosure. I use the total debt per capita as the proxy for the debt level. 18 Total debt is comprised of all debt, including general obligation bonds, revenue bonds, and other debt such as bank notes payable. I use this ratio to be consistent with prior studies such as Ingram and DeJong (1987) and Copley (1991).

4.2.1.3. Control variables. I include three control variables found significant in prior studies, audit quality, population, and government type, in the empirical tests that follow. 19 Audit quality is postulated to be associated with disclosure level in part because auditors often prepare the financial statements and footnotes for their clients. One measure of audit quality is that of industry specialization. OÕKeefe et al. (1994) find that the auditorÕs level of industry knowledge is positively associated with audit quality, and Gore et al. (2004) finds it is positively associated with GAAP disclosure. The proxy used for a given observation is the number of governmental audits performed by the CPA firm or auditor who audited that government. Population is included because

17

18 The use of an equally-weighted index is supported by Robbins and Austin (1986). In Michigan, debt issued on behalf of local governments at the county or state level, called

overlapping debt, is recognized on the local governmentsÕ financial statements. In Pennsylvania, local governments are required to include overlapping debt in calculations of the borrowing base, which makes it likely that they include it in their financial reports. It is also likely to be included because their financial reports are audited. However, because disclosure is not regulated in Pennsylvania, it is also possible that they do not include it. Therefore, the debt variable may understate the bond market incentives in Pennsylvania, which efectively biases against finding results for my first hypothesis.

19 An additional variable commonly used in disclosure studies is a proxy for funding sources, the ratio of intergovernmental revenues to total revenues. In this study, part of the sample is drawn from the state of Michigan, where most of the intergovernmental revenue is comprised of state- shared revenue allocated based upon population. I therefore do not include this variable because it does not adequately represent a governmentÕs reliance on non-capital market sources of revenue.


prior studies such as Robbins and Austin (1986), Evans and Patton (1983), and Copley (1991) find it positively associated with disclosure.

Government type is included as a control because Gore et al. (2004) finds that for a sample of Michigan governments, the township government type is negatively associated with the level of GAAP disclosure compliance. 20 The negative relation is potentially attributable to restrictions in debt issuance imposed by the state of Michigan, or because townships in general have fewer incentives to comply with GAAP. 21 Alternatively, this could be due to the more fundamental issue of why a government chooses to operate as a city versus a township. Because the efect of government type on financial report disclosure is unclear, this variable is included as a control. A dummy variable is used to indicate the city government type.

With the exception of the audit quality and population variables, all data are obtained directly from the financial reports. Data for the audit quality variables are hand-collected from the Michigan Department of Treasury and the Pennsylvania Department of Community and Economic Development. I verify the accuracy of the lists by comparing auditors on the lists with those in a random sample of financial reports. Population data are from the 1990 census.

4.2.2. Regression specification for H2

My second hypothesis examines whether there is a significant diference in disclosure levels for governments with low bond market interaction, and a relatively lower (or insignificant) diference in disclosure levels for governments with high bond market interaction. I therefore partition the sample into three groups based upon the level of debt, with the top, middle, and bottom third of the sample designated as high, medium, and low debt, respectively. This test utilizes the total sample of Pennsylvania and Michigan municipalities, and dummy variables to indicate the state (MI or PA) and the debt level (HIGHDEBT, MEDDEBT, or LOWDEBT). I use the following regression specification to test H2:

20 It is also common for disclosure studies to include a dummy variable indicating the city manager form of government. Prior studies show that the presence of the city manager form of government is positively associated with citiesÕ disclosure level. Studies such as Zimmerman (1977) commonly describe this variable in terms of reducing agency costs that exist between city councils and appointed city managers. However, in this study, both townships and cities are included in the sample, and a control variable is included to measure diferences in disclosure due to government type. Because this variable is highly correlated with the city manager dummy variable, the latter is not included in the regression. When I include the city manager variable, however, the results remain consistent with those presented.

21 The State of Michigan does not allow townships to directly issue debt for bond issues greater than $1,000,000. Instead, the county in which the township resides issues the debt, which the township in turn must repay to the County. This may reduce townshipsÕ incentives to issue debt relative to cities. However, anecdotal evidence reveals that townships respond by issuing several small issues, each under $1,000,000, in order to circumvent this regulation.

A.K. Gore / Journal of Accounting and Public Policy 23 (2004) 23-52

GAAPit ¼ ai þ b1iPOPit þ b2i

CITYit þ b3iAUDITSit

þ b4iHIGHDEBT; MIit þ b5i

HIGHDEBT; PAit

þ b6iMEDDEBT; MIit þ b7i

MEDDEBT; PAit

þ b8iLOWDEBT; MIit þ eit

37

ð2Þ

where HIGHDEBT,MI, MEDDEBT,MI and LOWDEBT,MI indicates the

top, middle, and bottom 1/3 of the sample for Michigan municipalities, and HIGHDEBT,PA and MEDDEBT,PA indicates the top and middle 1/3 of the sample for Pennsylvania municipalities, ranked by debt per capita. The low- debt partition for Pennsylvania is represented by the intercept term, and the remaining variables are as described above. H2A tests whether LOWDEBT,MI is positive and significant, while H2B tests whether (HIGHDEBT, MI ) HIGHDEBT,PA) is not significantly diferent from zero. I use ordinary least squares to facilitate comparison with previous studies. However, I also use multinomial logit (not reported) in the sensitivity analysis due to the discrete nature of the dependent variables, with the results qualitatively similar to those reported.

5. Results

5.1. Descriptive statistics

Table 2 describes the total sample (Panel A), the subset of Pennsylvania and Michigan governments (Panel B), and partitions based upon the level of debt (Panel C). I assess the reasonableness of comparing Michigan and Pennsyl- vania municipalities through non-parametric statistical tests in Table 2, Panel B. These comparisons indicate there are no significant diferences in population or debt, however, diferences between CITY and AUDITS are statistically significant at the 0.01 level. Half of the Michigan sample is comprised of cities, while only 24% of the Pennsylvania sample consists of cities. Also, Michigan auditors perform a significantly higher number of governmental audits on average than do Pennsylvania auditors (median 57 for Michigan versus median 4 for Pennsylvania). The diference in the number of audits performed is probably due to PennsylvaniaÕs use of internal auditors, who are restricted by law to one municipal audit per year. I do not consider this a problem that will impact the hypothesis tests because the two variables are control variables in the multivariate specifications.

Panel B of Table 2 reveals that Michigan municipalitiesÕ median score for GAAP is 17 out of a possible 18, indicating that there is not full compliance with GAAP. This efectively biases against finding results for H2, however. In addition, the non-parametric tests in Panel B show a significant diference


Table 2 Descriptive statistics and tests of significance from non-parametric tests of diferences between Michigan and Pennsylvania

Variable Mean Median Std. dev.

Panel A: Total sample (n ¼ 175)

POP CITY AUDITS DEBT STATE GAAP NONGAAP

3.065 0.371

30.503 578.979

0.503 14.006

2.935

2.90 0.00 9.00

393.68 1.00

15.00 1.00

0.701 0.485

38.700 757.501

0.501 4.390 3.888

Pennsylvania (n ¼ 87) Michigan (n ¼ 88) Mann- Whitney

Mean

Median Std. dev. Mean Median Std. dev. p-values*

Panel B: Subset of Pennsylvania and Michigan governments

POP 3.095 2.90 0.772 3.035 2.895 0.627 0.542 CITY 0.241 0.00 0.430 0.500 0.000 0.503 0.003 AUDITS 7.149 4.00 6.681 53.591 57.000 43.205 0.000 DEBT 584.337 324.54 715.237 573.683 408.158 801.170 0.833 GAAP 11.552 13.00 4.810 16.432 17.000 1.923 0.000 NONGAAP 2.756 2.00 3.226 3.102 1.000 4.428 0.238

Low debt (n ¼ 58)a High debt (n ¼ 58)b

Mean Median Std. dev. Mean Median Std. dev.

Panel C: Subset of governments partitioned by debt

POP 2.858 2.73 0.450 3.258 2.924 0.909 CITY 0.259 0.00 0.442 0.517 1.000 0.504 AUDITS 25.086 8.50 35.968 33.707 9.000 41.267 DEBT 108.469 118.48 66.159 1252.437 956.247 1003.721 STATE 0.517 1.00 0.504 0.500 0.500 0.504 GAAP 12.328 14.00 4.673 15.793 17.000 3.259 NONGAAP 1.618 1.00 2.423 4.193 2.000 4.756

*Indicates the two-sided statistical significance levels for a test of diferences between Pennsylvania

and Michigan. This table presents descriptive statistics for the total sample (Panel A), and the subset of Michigan and Pennsylvania governments (Panel B). Panel C shows the total sample partitioned into three groups based on the total debt per capita, with the top and bottom third of the total sample

designated as high debt and low debt. Variable descriptions are as follows: POP it is the log of population in year t for government i; CITYit is a dummy variable where 1 indicates the city form of government and 0 indicates the township form of government; AUDITS it is the number of municipal audits performed in year t by government iÕs auditor; DEBTit is the total debt per capita in year t for government i; STATE is a dummy variable where 1 indicates Michigan (GAAP disclosure state) and 0 indicates Pennsylvania (unregulated disclosure state); GAAPit is an index of GAAP disclosures in year t for government i; and NONGAAPit is an index of voluntary disclosures in year t for government i.

a n ¼ 30 Michigan, 28 Pennsylvania. b n ¼ 29 Michigan, 29 Pennsylvania.


between the two states for GAAP disclosure, but no significant diference in non-GAAP disclosure. The latter indicates that it is appropriate to compare the two states, because in the absence of disclosure regulation, municipalities voluntarily disclose information at similar levels.

Table 3 reports correlation matrices for the total sample (Panel A), the subset of Pennsylvania governments (Panel B), and for partitions based on the level of debt (Panels C and D). For the total sample and some of the partitions, the correlation between STATE and variables such as AUDITS is high (0.54). I therefore test for multicollinearity by computing condition indices following the procedure outlined in Belsley et al. (1980). In each case the condition index is below 10, which indicates that multicollinearity is not severe.

Table 3 Correlation matrices

POP CITY AUDITS DEBT STATE

Panel A: Total sample (n ¼ 175)

POP 1.000 CITY 0.238* 1.000

AUDITS )0.009 0.154* 1.000 DEBT 0.212** 0.290** 0.057 1.000

STATE )0.046 0.270** 0.540** 0.016 1.000

Panel B: Subset of Pennsylvania governments (n ¼ 87)

POP 1.000 CITY 0.242* 1.000

AUDITS )0.037 )0.158 1.000 DEBT 0.347* 0.287** )0.090 1.000

Panel C: Subset of high debt governments (n ¼ 58)

POP 1.000 CITY 0.299* 1.000

AUDITS )0.145 0.189 1.000 DEBT 0.072 0.381** )0.106 1.000 STATE )0.160 0.207 0.710** )0.077 1.000

Panel D: Subset of low debt governments (n ¼ 58)

POP 1.000 CITY 0.279* 1.000

AUDITS )0.076 0.264* 1.000 DEBT 0.118 0.201 0.000 1.000 STATE 0.016 0.255* 0.450** 0.064 1.000

*Significant at p < 0:05.

**Significant at p < 0:01. Note: see Table 2 for variable definitions. This table shows the Spearman rank correlation matrices for the total sample in Panel A, and for the subset of Pennsylvania governments in Panel B. The total sample is also partitioned into three groups based on the total debt per capita, with the top and bottom third of the total sample designated as high debt (Panel C) and low debt (Panel D), respectively.


5.2. Tests of hypotheses

I first perform a Wald test to determine whether it is appropriate to pool the cities and townships into one sample. 22 The results of this test indicate that the Wald statistic has a value of 0.93, which is significantly close to zero, thus allowing the cities and townships to be pooled into one sample.

Table 4 reports results for tests of my first hypothesis using Pennsylvania governments, and presents evidence of the relation between bond market interaction and disclosure. Disclosure is represented by the GAAP, non- GAAP, and Total disclosure indices, with the latter being the sum of the two. DEBT is positive and significant for all three models, consistent with H1, and shows that in the absence of disclosure regulation, municipal managers have incentives to disclose information to the bond market. Interestingly, AUDIT is positive and significant for GAAP disclosure, but not significant for non- GAAP disclosure, consistent with practitionersÕ conjecture that auditors pre- paring financial information for their clients are more focused on GAAP compliance.

Prior to testing my second hypothesis, I first examine whether there is a significant diference in disclosure between municipalities in GAAP-regulated and unregulated disclosure states, similar to Ingram and DeJong (1987). The results of this test, presented in Table 5, indicate that STATE is positive and significant (p < 0:01). I include an interaction term, DEBT Ã STATE, because I expect there to be an interaction between the state and the level of debt. The findings reveal that the level of GAAP disclosure is significantly higher in the regulated state, in contrast to the insignificant diference found by Ingram and DeJong (1987). 23

22 The Wald test is used because it does not rely on the assumption of constant variances across samples, as does the Chow test. Preliminary analysis of the data indicated that the variances of the cities could be diferent from the variances of the townships. The test statistic used is found in Greene (1993), and is as follows:

W ¼ ðh1 À h2Þ0ðV1 þ V2ÞÀ1ðh1 À h2Þ

where h1, and h2 are two normally distributed estimators of a parameter based upon independent samples (cities and townships), with variances V1 and V2. The variance estimates are obtained from separate OLS regressions of the cities and townships. The Wald statistic has a chi-squared distri- bution with K degrees of freedom, and tests whether the diferences between the parameters are significantly close to zero.

23 Interpretations of my results need to allow for the possibility that fundamental diferences between the states could lead to diferences in disclosure regulation. For example, there could be diferences in the underlying incentives to borrow that lead to why Michigan requires GAAP, while Pennsylvania does not. However, analyses in Poterba and Rueben (1997) show that the fiscal institutions (e.g. the level of debt restrictions, balanced budget and spending limits) of the two states are very similar. I consider any remaining diferences outside the scope of this study.


Table 4 OLS results for a test of the relation between disclosure level and debt in Pennsylvania, the

unregulated disclosure state (H1)

Model: DISCLOSUREit ¼ ai þ b1iPOPit þ b2i

CITYit þ b3iAUDITSit þ b4i

DEBTit þ eit

V

aria

ble

Expected

sign

Dependent variable:

GAAPa (n ¼ 87) Non-GAAPa

(n ¼ 87) Totala (n ¼ 87)

Coef- t-statistic Coef- t-statistic Coef- t-statistic

cient cient cient

Intercept 3.194 1.46 )0.850 )0.55 1.832 0.60 POP + 1.841 2.37** 0.712 1.31 2.740 2.53**

CITY + 1.011 0.90 )1.199 )1.55 )0.145 0.09 AUDITS + 0.198 3.00** 0.060 1.25 0.247 2.68** DEBT + 0.002 2.01* 0.000 3.53** 0.004 3.11** Adjusted 0.30 0.27 0.36

R2

F -statistic 10.20 8.45 13.2 (p-value) (<0.0001) (<0.0001) (<0.0001)

*Significant at p < 0:05; based on two-tailed tests.

**Significant at p < 0:01; based on two-tailed tests. Note: Variable descriptions are as follows: POPit is the log of population in year t for government i; CITYit is a dummy variable where 1 indicates the city form of government and 0 indicates the township form of government; AUDITSit is the number of municipal audits performed in year t by government iÕs auditor; DEBTit is the total debt per capita in year t for government i; GAAPit is an index of GAAP disclosures in year t for government i, described in Appendix A; and Non-GAAPit

is an index of voluntary disclosures in year t for government i, described in Appendix B; and Total is the sum of the GAAP and Non-GAAP disclosure indices.

a WhiteÕs t-statistics. All regression results have been checked for the presence of influential data points using CookÕs D statistic; no influential data points were detected. All models have also been estimated using multinomial logit with the results generally consistent with those presented here.

Table 6 reports results for my second hypotheses (H2A and H2B). Results for H2A show that the diference in disclosure between low-debt governments in Michigan and Pennsylvania is significant (p < 0:01), represented by the variable LOWDEBT,MI. Consistent with H2A and Fig. 1, for the subset of low- debt governments, the level of GAAP disclosures is significantly higher in the regulated state. This result is consistent with regulation inducing the disclosure of information for governments with little bond market interaction.

H2B tests whether the diference in disclosure between high-debt governments in Michigan and Pennsylvania are not significantly diferent from zero, or ðb4i

À b5iÞ is not significant. I find that high-debt municipalities in Michigan

disclose significantly more information, inconsistent with H2B. However, this result appears to be sensitive to my selection of the debt proxy, because when I use alternate debt proxies (see sensitivity analysis below), I consistently find no significant diference in disclosure among the high-debt governments.


Table 5 OLS results for a test of the relation between the GAAP disclosure level and the state



DEBTit þ b5iDEBTit Ã STATEit

þ b6iSTATEit þ eit

V

ariable

Intercept POP CITY AUDITS DEBT DEBT Ã STATE STATE Adjusted R2

Expected sign

++++

)+

Total sample (n ¼ 175)

Coefcient

6.714

1.072 1.018 0.014 0.002

)0.002 4.957

0.47

t-statistica

5.63**

2.72** 3.06** 2.42* 2.89**

)2.21* 7.38**

*Significant at p < 0:05; based on two-tailed tests, two-tailed otherwise.

**Significant at p < 0:01; based on two-tailed tests, two-tailed otherwise.

Note: Variable descriptions are as follows: POPit is the log of population in year t for government i; CITYit is a dummy variable where 1 indicates the city form of government and 0 indicates the township form of government; AUDITSit is the number of municipal audits performed in year t by government iÕs auditor; DEBTit is the total debt per capita in year t for government i; STATE is a dummy variable where 1 indicates Michigan (GAAP disclosure state) and 0 indicates Pennsylvania (unregulated disclosure state); and GAAPit is an index of GAAP disclosures in year t for government i, described in Appendix A.

a WhiteÕs t-statistics. All regression results have been checked for the presence of influential data points using CookÕs D statistic; no influential data points were detected. All models have also been estimated using multinomial logit with the results generally consistent with those presented here.

I also test whether the diference in disclosure between the low-debt governments is significantly greater than the diference in disclosure between high-

debt governments, or b8i À ðb4i

À b5iÞ > 0, consistent with Fig. 1. The results of

this test, reported in Table 6, show that the diference is significant (p ¼ 0:003). The results of this test are consistent with regulation being binding for low-debt governments, and not binding for high-debt governments.

5.3. Sensitivity analysis

Sensitivity analysis establishes that my results are robust to alternative specifications and measures of debt. First, I assess the sensitivity of the results to model specification by estimating an alternate regression specification using multinomial logit and ordered probit because of the discrete nature of the dependent variables. The results of these specifications, not reported in the tables, do not difer significantly from those reported.

Second, I use three alternative measures of debt because the use of debt per capita may not accurately reflect the current level of bond market


Table 6 OLS results for tests of the relation between regulation and disclosure (H2)a



HIGHDEBT; MIit

þ b5iHIGHDEBT; PAit þ b6i

MEDDEBT; MIit þ b7iMEDDEBT; PAit

þ b8iLOWDEBT; MIit þ eit

Variable Expected Total Sample (n ¼ 175)

sign Coefcient t-statisticb

Intercept 4.764 4.11**

POP + 1.357 4.53** CITY + 1.007 2.40* AUDITS + 0.013 2.76** HIGHDEBT,MI + 6.909 7.74** HIGHDEBT,PA + 4.406 4.22** MEDDEBT,MI + 6.184 6.78** MEDDEBT,PA + 2.278 2.09* LOWDEBT,MI + 6.003 7.22** Adjusted R2 0.51

Test of equality of coefcients

F -statistic for diference in coefcients:

HIGHDEBT,MI ) HIGHDEBT,PAc 7.04 (p-value)

LOWDEBT,MI ) (HIGHDEBT,MI ) HIGHDEBT,PA)

(p-value)

*Significant at p < 0:05; based on two-tailed tests, two-tailed otherwise.

**Significant at p < 0:01; based on two-tailed tests, two-tailed otherwise. Note: See Table 2 for variable definitions.

(0.0088) 9.00

(0.0031)

a The total sample is ranked by the total debt per capita, with the bottom third designated as low debt (LOWDEBT) governments, the top third designated as high debt (HIGHDEBT) governments, and the middle third as medium debt (MEDDEBT) governments. MI designates Michigan governments, and PA denotes Pennsylvania governments.

b WhiteÕs t-statistics. All regression results have been checked for the presence of influential data points using CookÕs D statistic; no influential data points were detected. The model has also been estimated using multinomial logit with the results generally consistent with those presented here.

c The p-value of this test is insignificant (p ¼ 0:19) when multinomial logit is used.

interaction. Therefore, I also use the log of total debt, the ratio of total debt/ total revenue, and the number of new bond issues in the last five years, to measure debt. The latter variable represents the frequency of recent forays into the bond market. The results from these analyses are consistent with my tests of H1. However, for my test of H2B, I now find that for the alternate measures of debt, there is no significant diference in disclosure level among high-debt governments, or ðb4i

À b5iÞ is not significant, consistent with H2B.

Because my original specification with debt per capita as the debt proxy includes population as a deflator and again as a separate control variable, it is possible that this caused an econometric problem. This is plausible because


when total revenue is used as an alternate size deflator (in the ratio of total debt/total revenue), I find no significant diference in disclosure between highdebt municipalities in Pennsylvania and Michigan. In addition, when I use multinomial logit for the specification that includes debt per capita, I again find that there is no significant diference in disclosure between high-debt governments.

Third, I assess the sensitivity of the results to the disclosure index measure by using two alternative disclosure indices, the first based on Copley (1991) and the second on Ingram and DeJong (1987). I chose these two indices because both purport to represent measures of GAAP disclosure. A comparison of the content of these alternate indices with the current studyÕs is provided in Appendices A and B. Although I separate the GAAP and non-GAAP com- ponents into two separate indices in the appendices to facilitate comparison, for the purpose of this sensitivity test, I combine the indices in the same manner as that used by the two aforementioned studies. The results of this specification do not difer significantly from those reported, and as such, my results are not likely due to index design.

Fourth, I assess the efect of the point of sample partition in the test of H2B, which uses the upper and lower third of the total sample to represent high and low debt, by instead using the upper and lower quarter of the total sample. The results from this analysis are again consistent with those presented. In particular, when I use this alternative partition point, the coefcient estimates for the low-debt subset are slightly larger, and for the high-debt subset slightly smaller, than the partition that divides the sample into thirdÕs.

6. Conclusion

The purpose of this paper is to examine the efects of disclosure regulation and bond market interaction on information production, using data from the governmental sector. I compare disclosure in Michigan, a state that requires GAAP, with that of Pennsylvania, a state with unregulated disclosure.

My analysis indicates two main results. First, within the unregulated disclosure state, I find a significant positive association between disclosure level and proxies for the level of bond market interaction. This result suggests that in the absence of regulation, municipal managers disclose financial report information because they have bond market-induced incentives to do so.

Second, I find that the level of GAAP disclosure is significantly higher in the regulated state than in the unregulated state. The diference in disclosure levels between states is significantly smaller among those governments with higher debt, however, which implies two things. First, although somewhat mixed, this evidence suggests that regulation is not binding for governments with high


debt levels. In other words, regulated governments with high debt levels are required to disclose GAAP information that they would have voluntarily disclosed in the absence of regulation. Second, it implies that regulation induces the production of information, or is binding, for governments with low debt levels. The latter result suggests that mandating GAAP information imposes costs on governments with lower bond market interaction, and ultimately the taxpayers, while conferring benefits to public accountants through monitoring costs.

My study examines disclosure levels for the governmental sector for one year. This focus enables a more precise analysis of some of the consequences of accounting regulation. However, it also means the results may not be gen- eralized to the corporate sector and/or other time periods. This issue could be addressed in future studies by applying a similar methodology to research areas where corporate disclosure is diferentially regulated, for example, in interna- tional research.

Another limitation is that because some of the tests examine whether the diference in disclosure between the two states is not significantly diferent from zero, it is possible that the insignificance is due to model misspecification. A final limitation of this study is that it necessarily restricts the examination of disclosure to a bond market perspective. However, as discussed previously, both focus groups commissioned by the GASB as well as prior academic research indicate that bond market participants are the primary users of municipal financial reports. An additional benefit of the bond market focus is that it allows analysis of non-political incentives to disclose, an area of the governmental literature not extensively explored.

Acknowledgements

I would like to thank my dissertation committee, Bob Hagerman, Susan Hamlen, Mike Rozef, and P.K. Sen, for their guidance and support. This paper has also benefited from the comments and suggestions of Bill Baber, Ray King, Steve Matsunaga, Wayne Mikkelson, Dale Morse, Terry OÕKeefe, Megan Partch, Kevin Sachs, Mike Stein, two anonymous reviewers, and by the workshop participants at the American Accounting Association 2001 annual meeting, Boston University, the University of Oregon, SUNY at Bufalo, and the joint conference of the Universities of British Columbia, Oregon, and Washington (UBCOW). I would also like to thank Dick Balderman and the Michigan Department of Treasury Local Audit staf, as well as Ken Johnson and the Pennsylvania Department of Community and Economic Development staf, for the use of their financial reports. Financial support from the AAA government and non-profit section is appreciated.

Appendix A. A GAAP disclosure index

This table presents the GAAP disclosure index used in regressions. The index is compiled directly from disclosures contained within the governmentsÕ annual financial reports, and is drawn from both the basic financial statements and the footnotes. The GAAP index contains 18 disclosure elements that are required by GAAP. Thus, governments can attain an equally-weighted index score of between 0 and 18. The frequency of occurrence columns indicate the total number of times each individual item is disclosed, and is shown for the total sample partitioned by state and debt per capita. High denotes a high debt level, whereas Low denotes a low debt level

N

o

.

Copley (1991)

Ingram and DeJong

Disclosure practice Frequency of occurrence

Total sample partitioned by

(1987) State Debt

MI PA High Low (n ¼ 88) (n ¼ 87) (n ¼ 58) (n ¼ 58)

Basic financial statements 1 A3 Combined balance sheet 88 72 58 49 2

A2, B1 Combined statement of revenues, expendi- 88 70 57 48 tures, and changes in fund balance--all governmental fund types and expendable trust funds

3 A1 1, 7 Combined statement of revenues, expendi- 76 56 53 36 tures, and changes in fund balance--budget and actual--all governmental fund types and expendable trust funds

4 A8 Combined statement of revenues, expenses, 82 54 50 40 and changes in retained earnings--all proprietary fund types and similar trust funds

4A

.K. G

ore / Journal of Accounting and P

ublic Policy 23 (2004) 23-52

5 A7 Combined statement of cash flows--all pro- 82 51 55 36 prietary fund types and similar trust funds

Footnotes

6 A10 8 Basis of accounting--governmental funds 88 59 52 46 use modified accrual

7 8 Basis of accounting--expendable trust, 88 43 51 40 agency funds use modified accrual

8 8 Basis of accounting--non-expendable trust, 88 50 52 38 pension, proprietary funds use accrual

9 B5 Budgetary basis of accounting, budgetary 86 75 57 51 policies

10 B6 Basis of accounting--revenue and expense 88 74 57 50 recognition

11 Property tax calendar: lien, levy, and due 58 35 38 24 dates

12 Cash deposits with financial institutions: 75 57 47 40 carrying amount of total deposits, and total bank balance classified into three risk categories

13 Investments: investments classified into three 65 37 38 32 risk categories; disclosed carrying amount and market value in total and for each investment type; and briefly describe types of investments authorized by legal or contractual provisions

14 B4 2 Fixed assets: statement of changes in general 78 47 49 35 fixed assets; and method of recording general fixed assets

A.K

. Gore / Journal of A

ccounting and Public P

olicy 23 (2004) 23-52 47

Appendix A (continued)

N

o

.

Copley (1991)

Ingram and DeJong



(1987)

State

MI PA

Debt

High Low

(n ¼ 88) (n ¼ 87) (n ¼ 58) (n ¼ 58)

15 A6 10 Accrued sick and vacation pay (compensated 72 57 49 39 absences) recorded in F/S or footnote

16 All 4 Long-term debt: debt service requirements 75 56 50 36 to maturity; and changes in general long-term debt

17 B7 Interfund receivables/payables footnote 83 35 45 37 18 B2 5 Amount of pension expenditure pursuant 86 76 56 53

to an actuarial determination B3 9 Commitments and contingencies are

discloseda

A5 Unfunded pension liabilitiesa

A9 Lease and purchase commitmentsa

a Items proxy for the level of complexity, as only those that have this particular activity are required to disclose it.

48 A

.K. G


ublic Policy 23 (2004) 23-52

Appendix B. Non-GAAP disclosure index

This table presents the non-GAAP disclosure index, comprised of seven disclosure elements that are not required by GAAP. Thus, governments can attain a non-GAAP index score of between 0 and 7. The non-GAAP disclosure elements are drawn from the basic financial statements, footnotes, and supplementary statistical information. The frequency of occurrence columns indicate the total number of times each individual item was disclosed for the total sample partitioned by state

N

o

.

Copley (1991)

Ingram and DeJong



1

2345

6789

10

A12 A13 B9 B10

B11 B12

(1987)

General governmental expenditures by source and function Percentage of property taxes collected Legal tax limits Assessed value of taxable property Legal debt limits and unused debt margins Property tax rates Schedule of direct and overlapping debt Principal taxpayers Demographic statistics--population (10-year trends) Demographic statistics--per capita income (10-year trends)

State

MI

(n ¼ 88)

22

24 11 40 22

43 21 22 17

11

PA (n ¼ 87)

17

30 11 41 15

56 16 17 6

7

Debt

High

(n ¼ 58)

19

24 10 32 20

35 19 20 15

14

Low (n ¼ 58)

4

10 420 3

30 442

2

A.K

. Gore / Journal of A

ccounting and Public P

olicy 23 (2004) 23-52 49

Appendix B (continued)

N

o

.

Copley (1991)

Ingram and DeJong



(1987) State Debt

MI PA High Low (n ¼ 88) (n ¼ 87) (n ¼ 58) (n ¼ 58)

11 Demographic statistics--unemploy- 15 4 11 2ment rate (10-year trends)

12 Demographic statistics--school enroll- 16 5 13 2ment (10-year trends)

13 Demographic statistics--median age 10 1 7 1(10-year trends)

3 Current liabilities are reported separate from long-term liabilities

6 Encumbrances are reported as a reserve of fund balance at year-end

B8 Disclosure that legal bond requirements have been met

A4 Revenues and expenditures by source and function

50 A

.K. G


ublic Policy 23 (2004) 23-52


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(4) effects of gaap regulation and bond market interaction on local government disclosure

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