Properties of Accounting Earnings in Not-For-Profit Organizations By Charles A. Barragato Long Island University - C.W. Post Campus School of Professional Accountancy Northern Blvd. Brookville, NY 11548 516-299-3279
[email protected] and Sudipta Basu Goizueta Business School Emory University 1300 Clifton Rd. Atlanta, GA 30322-2710 404-727-6475
[email protected] October 2004
We thank Lin Nan, Shiva Rajgopal, Stephen Ryan, Lakshmanan Shivakumar, Greg Waymire and seminar participants at the 2002 Southeastern Summer Accounting Research Colloquium, 2002 American Accounting Association Annual Meeting, London Business School and University of Washington for helpful comments.
Properties of Accounting Earnings in Not-For-Profit Organizations
Abstract We examine the properties of nonprofit earnings, where earnings denotes the nonprofit periodic accounting performance measure, change in net assets. We find that nonprofit earnings display a slight mean reverting tendency, and that they exhibit asymmetric persistence, similar to for-profit earnings. However, nonprofit’s operating cash flows possess properties very similar to their earnings, suggesting that operating accruals play a smaller role in determining nonprofit earnings. We also find considerable variation in these properties across nonprofits operating in different sectors. Since financial accounting rules for nonprofit firms are almost identical to those of for-profit firms, these differences suggest that accounting standards are not the sole determinants of the properties of reported earnings. By comparing financial accounting in nonprofit and for-profit organizational structures, our study complements existing for-profit research that examines variations in accounting properties between countries or sectors. Keywords: Charities, Conservatism, Regulation, Financial Reporting Data Availability: Data used in this study can be obtained from the public sources identified in the paper.
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1.
Introduction Nonprofit organizations are increasingly important in modern economies. Over 819,000
charities were registered with Internal Revenue Service in 2000, up two-thirds over the past ten years (The Chronicle of Philanthropy, 2001). The nonprofit sectors of many countries grew at more than three times the rate of their overall economies from 1990 to 1995.1 Despite the nonprofit sector’s economic significance and rapid growth, its accounting and reporting practices have not been examined extensively. Over the last forty years, U.S. financial accounting rules for nonprofit enterprises have gradually converged to those of for-profit firms, and are now virtually identical. However, nonprofit and for-profit enterprises differ on several dimensions including the types of contracting relations that comprise these organizations, the different economic sectors that they specialize in, and the extent and types of regulation they undergo. We examine whether the properties of summary accounting numbers reported by nonprofit firms are similar to those of their for-profit counterparts. More specifically, we investigate the time-series properties of nonprofit accounting earnings, where earnings denotes summary accounting performance measures for fiscal periods. If accounting standards primarily determine the properties of accounting earnings, then we would expect earnings reported by nonprofits to resemble those of for-profit firms. Contrarily, if contracting and informational motivations drive accounting practice, then we would expect different properties for accounting earnings of nonprofit enterprises relative to for-profit firms. We examine the time-series properties of nonprofit organizations' current change in net assets (their equivalent of for-profit net income, since nonprofit organizations do not pay
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According to the Johns Hopkins Center for Civil Society Studies, 28% of the populations of 22 countries, on average, donate their time to nonprofit organizations. The 22 countries comprised 13 from Europe, 5 from Latin America, and Australia, Israel, Japan and the United States.
dividends).2 We compare these time-series properties to those previously documented for earnings of for-profit enterprises. Ball & Watts (1972) and others report that annual income approximates a random walk, although there is a slight mean-reverting tendency. Subsequently, Brooks & Buckmaster (1976) and others document that income changes have asymmetric persistence, i.e., positive earnings changes tend to be permanent, whereas negative earnings changes tend to reverse. Basu (1995) shows that cash flows are less asymmetrically persistent than earnings, consistent with the income asymmetry being caused partially by accrual adjustments to cash flows. We find that nonprofit earnings have a slight mean-reverting tendency, and that they display asymmetric persistence, similar to prior results for profit-seeking enterprises. However, we find that operating cash flows for nonprofits have very similar properties to their earnings. This consistency between accrual-basis (change in net assets) and cash-basis (cash flow from operations) earnings, suggests that relative to for-profit enterprises, operating accruals play a smaller role in determining the properties of nonprofit accrual earnings. We also find considerable variation in these properties across nonprofits operating in different sectors. Our paper is related to Ball, Robin & Wu (2003), who show that earnings properties in East Asian countries differ systematically from those in Anglo-American countries despite similar accounting standards; Ball & Shivakumar (2004) who show that earnings properties of private UK firms differ from those of public UK firms, although they follow identical accounting standards; and Basu, Hwang & Jan (2001) who compare the earnings properties of U.S. firms audited by Big Eight and non-Big Eight auditors. These studies suggest that the informational needs of contracting parties determine the properties of reported accounting numbers rather than 2
Change in net assets is the bottom line on the nonprofit income statement and the top line on the nonprofit statement of cash flows under the indirect method. Net assets is defined as total assets less total liabilities, and
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the accounting standards alone. Thus, imposing uniform accounting standards within countries, or working for harmonization of accounting standards across countries, does not necessarily lead to comparable accounting numbers, although this is what policymakers often assume. However, the prior research focuses on comparisons within for-profit firms, whereas we compare different organizational structures. Section 2 describes the institutional background of nonprofits and nonprofit accounting. Section 3 develops hypotheses and Section 4 reviews the data. Section 5 describes the research design and reports the empirical results and sensitivity tests, while Section 6 concludes.
2.
Institutional Background of Nonprofits
2.1
What are nonprofits? The nonprofit sector comprises many diverse organizations and activities. The term
“nonprofit institution” denotes nongovernmental organizations that are legally subject to a “nondistribution constraint,” which means that residual earnings cannot be distributed to individuals who control the organization, such as officers, members or directors (Hansmann, 1987). The emergence of nonprofits in addition to for-profits firms has been the subject of much debate. Some believe that nonprofits fill a gap in supplementing public services provided by government agencies, while others believe that nonprofits exist in response to information imperfections where trust and altruistic motives are important. Nonprofit status conveys two important benefits - tax exemption on income from mission-driven endeavors and the ability to solicit tax-deductible contributions, but a cost is that they cannot use equity financing. Unlike government entities, nonprofits cannot rely on taxation for resources, but likely have greater flexibility in how they pursue their organizational missions. We focus, as does most nonprofit following the balance sheet equation, corresponds to book value of equity in for-profit enterprises.
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research, on U.S. organizations that are tax-exempt under Section 501(c)(3) of the Internal Revenue Code (IRC).3 Nonprofits dominate three types of market settings; (a) provision of nonrival and nonexcludable “public” goods, such as scientific research; (b) excludable goods where the intended consumers cannot afford to pay, such as housing for the homeless; and (c) markets where nonprofits have competitive advantages over for-profit entities for various reasons (Weisbrod 1977; Hansmann, 1980). Nonprofits comprise 100% of organizations classified as religious, foundations or social/fraternal, and overwhelmingly dominate museums/zoos and family services (Tuckman, 1998).
2.2
Regulation and external monitoring of nonprofits in the U.S. Today, most states allow nonprofits to organize under the Model Nonprofit Corporation
Act (33 states had adopted it by 1993). This act governs many aspects of nonprofit operations, including board meetings, rights and procedures to amend articles of incorporation, voting quorum, election and removal of officers, mergers and consolidations with other nonprofit organizations, record management, and dissolution. Charitable organizations report financial information to the Internal Revenue Service (IRS) annually on Form 990. Many states also require nonprofits to file annual information reports with the Secretary of State. Several private oversight agencies also monitor nonprofit
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In addition to the non-distribution constraint, 501(c)(3) organizations cannot engage in political activity. Many other tax-exempt (under different IRC sections) organizations cannot receive tax-deductible contributions. These organizations include homeowners’ associations, civic clubs, fraternal societies and farmers’ cooperatives. However, some non-501(c)(3) organizations such as cemetery companies and veterans’ organizations can solicit taxdeductible contributions. Nonprofits are generally exempt from property taxes in addition to the corporate income tax, although in recent year, municipalities have required “voluntary” payments in lieu of tax (PILOT).
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organizations, and serve as information intermediaries to donors (Baber, Daniel & Roberts, 2002). 4
2.3
Contracting parties in nonprofits Nonprofit financial accounting must meet the diverse informational needs of many users.
Current and potential users that are especially interested in nonprofit financial information include resource providers, service beneficiaries, governing oversight bodies and managers (SFAC No. 4, FASB 1980c, par. 29). These users have a common interest in nonprofit services, but also likely demand user-specific information. Our discussion focuses on financial data, although nonprofit constituents likely also use a variety of nonfinancial information (e.g. Buchheit & Parsons, 2003). Resource providers (typically contributors, members, lenders and employees) are interested in an organization's future viability, how well it has met its objectives, and whether to provide it with ongoing support. Several studies empirically document that more efficient nonprofits receive more charitable contributions (e.g. Weisbrod and Dominguez, 1986; Posnett and Sandler, 1989; Tinkelman, 1999).5 In a few sectors such as social welfare, hospitals and nursing, the government dominates resource provision (e.g. Rose-Ackerman, 1996). Service beneficiaries generally have no direct connection to an organization.6 They are merely user/recipients of nonprofit programs and focus mainly on information about program eligibility and effectiveness. 4
The IRS and other state authorities have the power to subpoena the books and records of nonprofits and may impose penalties and other sanctions (including the revocation of tax exempt status) to ensure compliance with formation and reporting guidelines. 5 These studies find that service “price” is negatively associated with the level of contributions received by charitable organizations, where “price” is defined as the after-tax-cost to a donor to purchase one dollar (or other monetary unit) of output to beneficiaries 6 In certain instances, service beneficiaries include resource providers, i.e., members who pay dues.
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Governing and oversight bodies utilize accounting information chiefly to evaluate whether managers have carried out their policy mandates and to assess the efficacy of existing guidelines. These governing and oversight bodies include the nonprofit's board of directors/trustees, government agencies (Internal Revenue Service and state regulators) and private oversight agencies.7 Managers focus primarily on information that assists them in fulfilling their stewardship responsibilities. These responsibilities include ensuring that resources are used for their intended purposes, adhering to budgetary guidelines (including donor-imposed restrictions) and planning and controlling program activities (SFAC No. 4, FASB 1980c, par. 32). Managers are often evaluated and sometimes compensated based on operating efficiency computed from their financial statements.
2.4
Role of financial accounting in nonprofit organizations Coase (1937) argues that firms exist because the price mechanism is more costly to
operate in certain situations. Nonprofit organizations are Coasian firms, operating in an environment that lacks marketable ownership interests. They function as intermediaries, brokering between service consumers and resource providers, and adding value by mitigating information asymmetries regarding product quality (Arrow, 1963). From an agency perspective, the absence of residual claims mitigates any donor-residual claimant agency problem; however, the incentive for internal agents to expropriate donations still remains (Fama and Jensen, 1983). Williamson (1983) argues that monitoring is more costly for nonprofit organizations because “ownership” interests are not marketable, making it difficult to assess performance based upon a 7
Private oversight agencies, such as the Philanthropic Advisory Service of the Council of Better Business Bureaus, issue publicly available reports about nonprofits' compliance with standards promulgated by the agency. These
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periodic valued-added measure. Thus, financial accounting practices, including the concepts promulgated under generally accepted accounting principles (GAAP), can be viewed as components of an efficient institutional answer to a contracting-cost problem (Ball, 1989). With respect to nonprofit GAAP, the FASB says, “it is not necessary to develop an independent conceptual framework for any particular category of entities (e.g., nonbusiness organizations or business enterprises). Rather its (the Board’s) goal is to develop an integrated conceptual framework that has relevance to all entities” (SFAC No. 4, 1980c, par.1). The FASB issued several standards subsequently to reduce the divergence between for-profit and nonprofit accounting. Standards for external financial reporting for nonprofits are now very similar to those for-profits. The Appendix reviews the history of nonprofit entities and their financial accounting regulation in more detail. The paper examines whether having similar accounting standards for the two types of organizations suffices for similar properties in reported earnings. Anthony (1989) argues that nonprofits do not have incentives to maximize earnings, and aim for a zero or slightly positive surplus each period. However, Chang & Tuckman (1990) find that a large majority of nonprofits earned surpluses in 1983, very few nonprofits had surpluses close to the zero level, and that the size of a nonprofit’s surplus was related to its equity and asset holdings.8 This evidence suggests that nonprofit managers may have similar incentives to nonprofit managers in terms of maximizing earnings, even though the organizations avow that they do not seek to earn profits.
reports typically cite charities' program expense ratio as a performance indicator (Baber et al., 2002). 8 The prior theoretical arguments for zero surplus accumulation are reviewed in Chang & Tuckman (1990). They also posit several different incentives for nonprofit managers to accumulate surpluses. These include (1) a source of subsidy to those unable to afford program services, (2) a facilitator of allocations to the future, (3) a hedge against risk and uncertainty, (4) a means to increase independence from the marketplace and (5) a measure of financial success.
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3.
Hypotheses
3.1
Prior research on accounting earnings properties in business enterprises Most capital markets studies use equity prices, returns and/or trading volume to infer the
decision usefulness and other properties of accounting information in for-profit enterprises. Since nonprofits have no marketable equity interests, we cannot use this approach. Similarly, we cannot use analysts’ forecasts to infer the properties of nonprofit earnings. Instead, we examine the time-series properties of nonprofit earnings. Ball & Watts (1972) report that annual earnings approximately follows a random walk, with a slight mean-reverting tendency; and several subsequent studies find that the random walk model predicts subsequent annual earnings as well as other Box-Jenkins models (see Brown, 1993, for a review). However, accounting researchers do not have a good economic theory to explain why annual net income follows a random walk (Kothari, 2001, pp. 145-6). Brooks & Buckmaster (1976) and several others document mild mean reversion in earnings, especially for extreme earnings.9 Subsequently, Elgers & Lo (1994) and others find that this mean reversion is asymmetric, i.e., negative earnings changes tend to reverse more than positive earnings changes. Kothari (2001) lists several economic reasons that have been posited for these findings. First, competition in product markets implies that above-normal profitability is not sustainable (e.g. Beaver & Morse, 1978), suggesting mean reversion in earnings. Second, firms incurring losses have the option to liquidate if the shareholders do not expect recovery (Hayn, 1995). Thus, surviving firms are likely those that were expected to recover, and hence, the abandonment option along with survival bias suggest that earnings will exhibit reversals.
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In-sample estimates of autocorrelation coefficients are biased downwards because of the small sample bias that equals –1/(T-1), where T is the number of time-series observations (e.g. Kendall, 1954). Bias-adjusted first-order serial correlation coefficients for annual earnings changes are close to zero (Dechow, Kothari & Watts, 1998, Table 5).
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Third, accounting conservatism results in economic bad news being recognized more quickly than good news (Basu, 1997). Finally, agency theory suggests that managers have incentives (e.g. compensation contracts and CEO turnover) to take “big baths” in earnings (Healy, 1985). The last three explanations are consistent with both mean reversion in earnings and asymmetric mean reversion. A third set of prior research findings is that the time-series properties of earnings and cash flows differ systematically, reflecting the properties of accounting accruals. Dechow (1994) reports that both operating cash flows and operating accruals are strongly mean-reverting, and argues that they are negatively correlated contemporaneously, because accruals tend to ‘smooth’ or undo the mean-reverting properties of underlying cash flows. Thus, earnings changes tend to reverse less than operating cash flow changes. Basu (1995) shows that cash flows are less asymmetrically persistent than earnings, and explains that asset writedowns typically only affect accruals, not cash flows. He argues that this result demonstrates that accounting conservatism has an effect that is incremental to the economics-based arguments for earnings mean reversion, which predict similar properties for cash flows and earnings.10 However, these results are also consistent with the “big bath” arguments.
3.2
Hypotheses on accounting properties of nonprofit earnings We now discuss whether we would expect to find similar or different effects in the
properties of nonprofit earnings. Since accounting rules are virtually the same for nonprofits and for-profit enterprises, ceteris paribus, we would expect similar properties in the outputs or summary measures produced by their accounting processes. In this section, we discuss how the
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Basu, Hwang & Jan (2001) and Ball, Robin & Wu (2002) conduct similar tests in examining differences in conservatism between Big Eight and non-Big Eight auditees, and across four East Asian countries.
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contracting differences between for-profit and nonprofit enterprises could affect the properties of accrual- and cash-basis earnings. As Kothari (2001) notes, there is no good economic explanation for why earnings approximates a random walk. Hence, in the absence of any compelling theory, we predict that change in net assets, i.e., nonprofit accrual earnings, will also approximate a random walk. Beaver & Morse (1978), Fama & French (2000) and others posit competition as a reason for mean reversion in for-profit earnings. It is difficult to assess the degree of competition in nonprofits, but clearly it is intense in some sectors, especially where nonprofits compete with for-profit and/or governmental organizations (e.g. healthcare). A second argument pertains to the liquidation option of controlling parties. We do not know of any systematic studies of nonprofit bankruptcy or liquidation frequencies, but some nonprofits do close when unsuccessful. Based on these economic arguments, we expect to find mean reversion in both cash flows and earnings for nonprofits. However, operating cash flows should have a greater mean-reverting tendency because accruals tend to ‘smooth’ mean-reversion in underlying cash flows (Dechow, 1994).
HYPOTHESIS 1: Change in net assets tends to reverse slightly, and reverses less than operating cash flows.
The liquidation option argument also predicts asymmetric mean reversion in cash- and accrual-basis earnings. In other words, decreases in change in net assets and operating cash flows should be more likely to reverse than their corresponding increases.
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HYPOTHESIS 2: Decreases in change in net assets (operating cash flows) reverse more than increases in change in net assets (operating cash flows).
The conservatism and “big bath” explanations predict differences in the asymmetric mean reversion properties of earnings and cash flows. Basu (1997) and Holthausen & Watts (2001) find that variation in auditor liability exposure is correlated with changes in conservatism in the U.S. across time. Similar inferences are drawn from comparisons of conservatism across countries (e.g. Ball, Kothari & Robin, 2000) and across auditor types (Basu, Hwang & Jan, 2001). However, nonprofits do not issue tradable equity securities, exposing them and their auditors to considerably less litigation risk than publicly traded firms (which face class-action shareholder lawsuits under the Securities Acts of 1933 and 1934).11 Thus, auditors have less incentive to require conservative estimates by nonprofit clients than their for-profit clients. For-profit CEOs have incentives to undertake “big baths” because of the presence of “floors” in their bonus plans (Healy, 1985). Unfortunately, we do not have much systematic evidence on the managerial compensation contracts in nonprofits. Haber (1995) suggests that nonprofit managers are less likely to receive bonus compensation than their for-profit counterparts, but may be more likely to receive salary increases as rewards for accounting performance. Baber et al. (2002) document a positive association between charity CEOs’ compensation changes and program spending changes, consistent with managers being rewarded for mission-related spending.12 Additionally, if CEO turnover in nonprofits is related to poor 11
However, nonprofits may issue debt securities, for instance, to finance construction. Nonprofits are generally exempt from registration of securities and the Uniform Securities Act. However, some states do not exempt the securities of nonprofits from registration, and many states impose conditions on the exemption. A few states require nonprofits that “issue” their own securities to be registered as issuers or issuer-dealers. 12 Without more systematic evidence on how salary increases are determined in nonprofits, we do not know if they have similar pay-related incentives to take “big baths” as for-profit firms. To the extent that salary decreases are rare, salary changes implicitly have a “floor” of zero similar to the floor in bonus compensation plans.
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accounting performance, and new CEOs have incentives to take “big baths” to improve future accounting performance, we might still expect differential asymmetric persistence between accrual and cash earnings. However, to the extent that high-level professionals accept lower pay levels in nonprofits than in equivalent for-profits in exchange for non-pecuniary benefits such as the ability to make a lasting social contribution (e.g. Preston, 1989; Cornell, 2004), compensation related incentives are likely to be a smaller factor than in for-profit organizations. In summary, both the liability and compensation structure differences suggest little difference in asymmetric persistence between earnings and operating cash flows within nonprofits, but potentially large differences in asymmetric persistence between nonprofit and forprofit earnings.
HYPOTHESIS 3: The asymmetric mean-reversion in change in net assets is greater than that for operating cash flows.
4.
Sample Selection and Data Description
4.1
Sample Selection We obtain data through the National Center for Charitable Statistics (NCCS). NCCS
compiles data from the annual Form 990 tax return filed with the IRS by tax-exempt organizations. These tax returns have been used to study a broad array of nonprofit issues, including financial vulnerability and debt management (Tuckman and Chang, 1991, 1993), sources and uses of funds (Chang and Tuckman, 1990) and economic performance (Chang and Tuckman, 1990). We utilize the IRS Statistics on Income (SOI) files. The SOI division of the IRS creates an annual file based on information included in the annual Form 990 Return
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Transaction File (RTF).13 SOI files include all 501(c)(3) entities with assets in excess of $10 million and a random sample of smaller organizations. Thus each annual file contains between 10,000 and 13,000 organizations and includes information for over 300 financial and other variables. Financial variables were extracted from IRS SOI files covering the period 1988 through 1997. We exclude organizations functioning merely as conduits, i.e., those with revenues equal to expenses. Since the Form 990 tax return does not require the disclosure of cash flow information, we compute operating cash flows indirectly using balance sheet and income statement amounts. Our computation of operating cash flow incorporates all of the major balance sheet items that typically affect nonprofits' computation of working capital.14 To further partition the data, SOI files were merged with NCCS National Taxonomy of Exempt Entities (NTEE) data files. The NTEE classification system was developed in the 1980's by the NCCS, in collaboration with major nonprofit organizations, to classify all forms of nonprofit organizations (Stevenson, 1997). It is a mixed notation system comprised of the following ten major categories: Category
Illustrative Organization
Arts Education Environment and Animals
Cultural Center for the Arts Julliard School New York Botanical Garden
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The SOI division staff review SOI data prior to their internal use, making them more reliable than the RTF data. Froehlich and Knoepfle (1996) find Form 990 tax return data to be a generally reliable source of information. They find a greater correlation between tax filings and financial statements for larger organizations (annual revenues greater than $1.3 million). Froehlich, Knoepfle and Pollak (2000) conclude that the SOI files provide reliable information for analyzing balance sheet and income statement items. Gordon, Greenlee and Nitterhouse (1999) recommend that researchers interested in the major nonprofit organizations (those with assets in excess of $10 million) use the SOI files. 14 Determining cash flows indirectly introduces measurement error, which can bias reported associations (Dechow, 1994; Collins and Hribar, 2002). Measurement error is also a concern in the nonprofit setting, particularly to the extent that revenues and/or program commitments span more than one fiscal year. Anecdotal evidence (Barragato, 2002a) suggests that most nonprofits used the cash basis to report multi-year promises to give before December, 1994, when SFAS No. 116 (FASB, 1993a) became effective.
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Health Human Services International Public, Societal Benefit Religious Related Mutual Membership Unknown
American Diabetes Foundation Boy Scouts of America Plan International USA United Way International Bible Society Actors Fund of America
The NTEE system is further sub-divided into 26 major groups and 645 centile levels. In this study, we limit our descriptive data analysis to the ten major NTEE categories.
4.2
Data and descriptive statistics Table 1 reports descriptive summary statistics for our nonprofit sample. Panel A reports
statistics on our unscaled primary variables. Panels B and C report scaled univariate statistics and correlations, respectively, for our regression variables. The first section of Table 1 Panel A reports sample descriptive statistics in $000's. Average beginning of year total assets is about $60 million with a median of $18 million. The latter statistic indicates that more than half our sample is composed of large nonprofits, with assets of $10 million or more as per the IRS SOI definition. The distribution is highly rightskewed with a maximum of $24.3 billion, and a standard deviation of $258 million. The average total revenue is $39.2 million with a median of $9.2 million. The distribution is again rightskewed with a maximum of $11.1 billion, and a standard deviation of $141.7 million. We have 233 observations with negative total revenues (minimum of -$47 million), which results from the reporting of certain revenue items net of related expenses in the revenue section of Form 990. The average change in net assets is $4 million with a median of $0.6 million. The maximum is $10 billion and the minimum -$2.6 billion. Given that the standard deviation is only $45 million, this indicates a very leptokurtic distribution. The average operating cash flow is about $6.2
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million, with a median of $1.3 million. The minimum is -$2.2 billion and the maximum $10.3 billion, again reflecting high kurtosis. Implicitly, our working capital accruals measure has a mean of $2.2 million, i.e., the difference between the means of change in net assets and operating cash flow. Average investment in securities is $18.7 million, which represents just over 31% of organizations' average total assets. This distribution is also highly right-skewed, with a median of $4 million and a standard deviation of $173 million.15 The second section of Table 1 Panel A reports statistics on three key financial ratios (in percentages) that are typically used to assess nonprofit operating performance and financial vulnerability (Tuckman and Chang, 1991). The first ratio, surplus margin, has an average of 6.5% and a median of 6.1%. The surplus margin ratio measures the degree of slack (operating revenues less operating expenses) generated by an organization. Nonprofits with high surplus margin are less likely to reduce services in order to maintain financial viability. The next measure, administrative cost ratio, has an average value of 15.4% and a median of 10.5%. Nonprofits with very low administrative cost ratios are more prone to reduce their services when faced with a financial hardship. This is because nonprofits that dedicate a higher proportion of their revenues to administration will likely have more flexibility in reducing discretionary administrative costs before reducing services.16 The last measure, program expense ratio, has an average of 79.7%, with a median of 85.1%. The program expense ratio is used to assess an
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Three observations report negative investment in securities. These negative values likely result from reclassifications within the Form 990 tax return or from data entry errors in the SOI files. However, all three observations report positive total assets and total revenues. 16 Kähler & Sargeant (2002) find that the administrative cost ratio is inversely related to nonprofit size, which potentially reflects economies of scale.
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organization's efficiency in fulfilling its programs and related charitable objectives. High program expense ratios suggest greater operating efficiency.17 To mitigate the effects of the highly right-skewed and leptokurtic distributions on our regressions, we deflate by two-year lagged total revenues, to control for size/scale effects (Christie, 1987).18 We also exclude observations in the top and bottom 1% of scaled change in net assets or cash flow in each year. Panel B reports statistics on these deflated variables, which appear to be better behaved. The scaled change in net assets is 31.1% with a median of 6.0%. Scaled operating cash flow is on average 44.5% with a median of 11.9%. Implicitly, the mean accrual is negative at –13.4% (31.1% - 44.5%), consistent with results in for-profit enterprises, and mainly attributable to depreciation expense. The standard deviation for scaled changes in net assets is less than for operating cash flows, consistent with accruals tending to ‘smooth’ cash flows to improve matching (Dechow, 1994; Dechow, Kothari & Watts, 1998). A similar inference can be drawn from comparisons of the extreme values of these variables. Panel C reports pooled Pearson (below diagonal) and Spearman rank (above diagonal) correlations among the scaled variables. All correlations are positive and statistically significant, and the magnitudes of the Pearson and Spearman correlation coefficients are similar, consistent with little non-linearity in the data. Table 2 reports mean and medians for our variables by year and NTEE classification. Panel A reports that we have between 9,000 and 11,000 observations in each year, except in 1988 where we have 12,600. The average assets and revenues increase almost monotonically 17
Krishnan, Yetman & Yetman (2002) report that nonprofit organizations appear to shift expenses from administrative to program categories to improve their reported efficiency statistics, and that this manipulative tendency is more pronounced in smaller nonprofits that are more reliant on donations. 18 We scale our variables by total revenue at time t-2 to mitigate simultaneity concerns. We choose total revenue as our deflator over total assets because total revenue has a more stable coefficient of variation from 1988 through 1997. In unreported analyses, the coefficient of variation for total assets increases by approximately 20% during this
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over the years, and similar (but less monotonic) increases are also apparent in the median values. Average change in net assets and average operating cash flows more than double over the sample years. There is some evidence that the last recession had an impact on nonprofit institutions, with markedly lower change in net assets, cash flows and investment in securities in 1990, and steep increases in these variables in 1995 after the start of the recent bull market.19 The median surplus margin ratio hovers between 5% to 6% from 1988 to 1994, and then increases by approximately 1% per year to 9.2% in 1997. There is a gradual decrease in the median administrative cost ratio from 10.9% in 1988 to 9.8% in 1997. The median program expense ratio remains relatively stable (ranging between 84.2% and 85.6%) over the sample period. Panel B reports means and medians by NTEE classifications. The Education, Health, and Human Services groups have the most observations, and between them comprise about 80% of the sample. Educational organizations have the largest assets on average, followed by Health, International and Mutual Membership organizations. Organizations with the largest average total revenues are from the Health, Education and International categories, respectively. Education, Health and Public, Societal Benefit organizations have on average the highest change in net assets and cash flow. Mutual Membership organizations maintain the largest average investment in securities, followed by organizations in the Education and Public, Societal Benefit groups. The median surplus margin ratio is quite erratic, ranging from a high 33% for Mutual Membership organizations to a low of 1.8% for unclassified organizations. Organizations in the Arts category have the highest median administrative cost ratio (14.8%). The Mutual Membership group
period. Therefore, use of total assets as deflator could bias our untabulated annual regressions results, which we run to ensure that our pooled t-statistics are not overstated due to residual correlation (Brown, Lo and Lys, 1999). 19 The increase in change in net assets around 1995 may also have been impacted by SFAS No. 116, which generally became effective for fiscal years beginning after December 15, 1994. In the pronouncement's dissenting discussion, Chairman Beresford posited that many adopters would likely report large increases in net assets as a result of recording previously unrecognized unconditional promises.
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appears to operate the leanest, generating a median administrative cost ratio of 2%. All ten NTEE groups plowed more than two thirds of their total expenditures into programs, with Mutual Membership and Arts at the extremes (median program expense ratios of 95.8% and 74.1%, respectively).20 5.
Research Design and Empirical Results
5.1
Research design We utilize a research design adapted from Basu (1997) to examine the time-series
properties of nonprofit firms' change in net assets. More specifically, we examine the persistence of change in net assets, denoted X, to examine if nonprofit earnings follow a random walk or are mean-reverting. We also examine this persistence as a function of the sign of the past-period change. If nonprofit accounting is conservative, we expect negative changes to have a greater tendency to reverse in the next period than positive changes. We test these predictions using a pooled cross-section and time-series regression model: ∆Xt = α0 + α1D + β0∆Xt-1 + β1D*∆Xt-1 + εt
(1)
∆Xt in this piecewise linear specification is the period t change in earnings, and a dummy variable, D, indicates whether the prior period earnings change is negative. Since earnings is essentially comprised of two components; (1) a moving average of current and prior economic gains, and (2) a transitory loss component; specifying the model in first differences rather than in levels is more appropriate (Ball and Shivakumar, 2004).21 The predictions are that β0 is zero (random walk) or slightly negative (mean reverting) for earnings and cash flows; that β0 is more 20
Harvey & McCrohan (1988) report that a 60% program service ratio appears to be a critical threshold, with organizations exceeding this benchmark receiving significantly higher donation levels.
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negative for cash flows (accrual smoothing of cash flows); that β1 is negative (asymmetric persistence) for earnings and cash flows; and finally that β1 is more negative for earnings than cash flows (conservatism-induced asymmetric persistence). We report tests for a sample of over 100,000 nonprofit-year observations from 1988 to 1997.
5.2
Full sample results on asymmetric persistence Tables 3 report results of our hypotheses on the time-series properties of earnings and
cash flow. Panel A reports results of estimating equation 1 for earnings. The first regression reports that the slope coefficient, β0, is –0.218, and significant, consistent with Hypothesis 1 and evidence in Ball & Watts (1972) and Basu (1997) for profit-seeking firms. The explanatory power of the regression is low with an adjusted R2 of 2.9%. The second regression introduces intercept and slope dummies for observations with earnings decreases. The adjusted R2 increases slightly to 3.2%. The coefficient on prior earnings increases is significantly negative at -0.188. The difference in slope coefficients, β1, is -0.236, and significantly negative, which is consistent with our second hypothesis. These results are also consistent with prior evidence in Brooks & Buckmaster (1976), Elgers & Lo (1994), Basu (1997) and Fama & French (2000) for profitseeking firms. Panel B of Table 3 reports parallel results for operating cash flows. Similar to Panel A, we find a mean reverting tendency in operating cash flow changes, with a significant and negative slope coefficient, β1, of -0.226, and a low adjusted R2 of 3.1%. The slope coefficient is slightly more negative than the corresponding coefficient for change in net assets, which is also consistent with Hypothesis 1, and suggests that accruals tend to ‘smooth’ cash flows very 21
The choice of specification also depends on the stationarity of the earnings (change in net assets in our case) timeseries (Finger, 1994). We do not have long enough time-series data for individual organizations to conduct
19
slightly. As in Panel A, the adjusted R2 increases slightly to 3.4% when we introduce dummies for negative prior period performance. The difference in slope coefficients, β1, is significantly negative at –0.297, and greater than that in the corresponding accrual earnings regression. This result is inconsistent with our third hypothesis.
5.3
Relation between operating cash flow changes and lagged earnings changes Researchers find that earnings changes lead operating cash flow changes, consistent with
operating accruals incorporating information about expected future operating cash flows (e.g. Finger, 1994; Dechow, 1994; Dechow, et al., 1998). More recently, Ball & Shivakumar (2004) argue that the more timely recognition of unrealized losses than unrealized gains (Basu, 1997) should result in negative earnings changes being less highly associated with next period operating cash flow changes. To evaluate whether transitory negative changes in net assets contain more timely economic information, we estimate (following Ball & Shivakumar, 2004): CFt+1 = α0 + α1D + β0 ∆Xt + β1D*∆Xt + β 2 *Xt-1 + εt+1
(2)
where CFt+1 equals operating cash flows in year t+1; ∆Xt represents the difference in change in net assets from year t-1 to year t; Xt-1 equals change in net assets in year t-1; and D represents a dummy variable set equal to 1 for all earnings decrease firms in year t. To the extent that both year t negative and positive ∆X contain information about future cash flows, we expect β0 to be positive and β1 to be negative, but smaller in absolute value than β0.
stationarity tests.
20
The results from estimating regression equation 2 are reported in Table 4. The first specification, which excludes intercept and slope dummies, produces positive and significant slope coefficients for β0 and β2, which suggest that Xt-1 and ∆Xt provide information about future cash flows. The second regression reports results for the full specification. The estimates of β0 and β1 are 1.016 and -0.838, respectively, and are significant. These results are consistent with our prediction that current period accrual earnings changes contain economic information about future cash flows, with positive changes being more persistent than negative changes. This evidence is also consistent with hypothesis two in that negative and positive working capital accruals have different properties.
5.4
Additional analyses
5.4.1 Year-by-year estimation The results presented thus far are based on a pooling of observations across organizations and across time. To ensure that our reported t-statistics are not unduly overstated due to timeseries correlation, we re-estimate the regressions by year. The signs and significance of the (unreported) annual slope coefficients remain consistent with those of the pooled results. We also replicated these tests using t-statistics based on the distribution of the annual cross-sectional coefficients following Fama & MacBeth (1973) and Fama & French (2000). The statistical significance is greatly reduced (see Tables 3 and 4), because we have only 9 annual crosssections from which to calculate standard errors for the estimates, but our inferences remain unchanged.
21
5.4.2
Investments in Securities Endowments represent a substantial portion of the net assets for many nonprofit
organizations. To the extent that our sample nonprofits maintain endowment funds in securities investments and recognize both unrealized gains and losses from changes in their carrying values, we are likely to find less asymmetric persistence for heavily endowed nonprofits. We partition our sample into those that (do not) report investments in securities and re-estimate our Table 3 regressions to examine how SFAS 115 affects our inferences. In untabulated tests, we find that nonprofits with securities investments exhibit a slightly greater mean reverting tendency for earnings, as well as much greater asymmetric persistence. Nonprofits without securities investments have a greater mean-reverting tendency for cash flows than earnings, similar to for-profit firms, but the reverse is true for nonprofits with securities investments. The asymmetric persistence tests are inconsistent with our third hypothesis in that earnings is less asymmetrically persistent than operating cash flows for both groups. To summarize, our inferences (1) on mean-reversion in accruals are sensitive to the investments in securities, (2) remain consistent with an asymmetric persistence related to economic causes, (2) but are inconsistent with any incremental effects of accounting conservatism through operating/working capital accruals.
5.4.3
Changes in total revenues Some nonprofits accumulate or conserve funds for later spending on special projects or
other major endeavors. In these instances, the revenues and expenditures associated with such projects/endeavors fall in different accounting periods. Thus, it is possible that our tests are capturing some portion of this transitory phenomenon rather than an asymmetry related to
22
conservatism. To address this issue, we partition our sample firms based on extreme changes in total revenues. For purposes of our analysis, we define an extreme change as one where there has been a more than ten percent increase or decrease in an organization's total revenues over the preceding year.22 Untabulated results suggest that despite large revenue swings, our inferences remain unchanged and are consistent with economic-related mean reversion and asymmetric persistence, with little incremental contribution from operating accruals.
5.4.4
Non-articulation of balance sheet and income statement items As discussed previously in Section 4, we utilize a balance sheet approach to compute our
operating cash flow variable since cash flow information is not a required disclosure on the Form 990 tax return. Drtina and Largay (1985) and Collins and Hribar (2002) demonstrate that using a balance sheet approach in for-profit research can lead to significant measurement errors if a firm has participated in a merger, acquisition or divestiture. Unfortunately, the SOI files do not include information on M&A activity. To examine the sensitivity of our results to such measurement errors, we re-estimate our Table 3 regressions excluding all organizations that have a more than 10% difference between period t-1 ending total assets and period t beginning total assets. Dropping these organizations from our analysis would likely capture any entity that was involved in a merger, divestiture or the acquisition of a for-profit operation. Of course, it is likely that employing such a filter will exclude some firms that were not involved in any of these transactions, e.g., organizations that reclassified non-working capital items on their tax return balance sheet to conform to the current year's presentation. However, we have no way of identifying such firms in the SOI data set. Our untabulated results for 61,479 nonprofit-year observations (28,867 decrease firms; 32,612 increase firms) remain qualitatively unchanged. 22
This should also help control for size changes due to mergers between nonprofits.
23
5.5
Cross-industry variation Due to the diversity that characterizes the nonprofit sector, it is likely that the time-series
properties of nonprofit earnings will vary by industry group. We repeat our tests for each of the ten NTEE categories. Table 5 presents results by NTEE major group for both the change in net assets and cash flows specifications. Not surprisingly, the time-series properties vary considerably across NTEE groups. First, change in net assets is mean-reverting in all groups except Religious Related, and operating cash flows are mean-reverting in all groups except International. Change in net assets is less mean-reverting in 6 out of 10 groups, but some of these differences are very small. Hence, there seems to be no systematic difference in the mean-reverting tendency of change in net assets and operating cash flows across all 10 groups. This suggests that litigation and compensation related incentives have less effect on income determination in nonprofit enterprises than previously documented in for-profit enterprises. Asymmetric persistence varies substantially across each category. For the change in net assets specification, Religious-related, Arts and International organizations exhibit the greatest asymmetric mean-reverting tendency, as evidenced by the incremental slope coefficient for prior decrease observations, β1, or -0.93, -0.45 and –1.26, respectively. Only five of the ten groups have significantly negative β1 slope coefficients. As for the cash flow specification, the International, Religious-Related and Education groups evidence greater asymmetric mean reversion, with the incremental slopes for prior decrease observations, β1, of -1.11, -0.620 and -0.517, respectively. Again, only five of ten groups have significantly negative β1 slope coefficients. Side by side comparisons of the change in assets and cash flows specifications
24
reveal that only two of the ten categories have results consistent with hypothesis 3 (Arts and Religious-Related). Overall, despite the wide variation by NTEE major group, the evidence is consistent with mean reversion and asymmetric persistence in both change in net assets and operating cash flows, but no incremental asymmetric persistence due to operating accruals.
5.6
Other robustness checks We conduct three sensitivity checks based on regression equation 1 which do not affect
our inferences: (1) controlling for nonprofits’ size using opening total assets and total revenues as partitioning variables, (2) segregating our sample into pre (1989-1994) and post (1995-1997) regulation periods to assess the impact of SFAS Nos. 116 and 117 (FASB, 1993a, 1993b), 23 and (3) re-defining nonprofit earnings by substituting surplus margin (which excludes unrealized gains and losses on investment securities and other items typically recognized under GAAP but not on the tax return) for change in net assets.
6.
Direct Comparison to Publicly Traded For-Profit Enterprises A potential reason we find different results for nonprofit enterprises is that they are
engaged in fundamentally different economic activities than for-profit enterprises. To explore this possibility, we compare the asymmetric persistence of earnings for nonprofit and for-profit firms that are classified under the same North American Industrial Classification System (NAICS) codes.24 For ease of comparison, we group these into firms into five “sectors”: Media,
23
SFAS Nos. 116 and 117 affect nonprofit revenue recognition and financial reporting, respectively, and generally became effective for fiscal years beginning after December 15, 1994. 24 Bhojraj et al. (2003) and Krishnan & Press (2003) describe the NAICS system and evaluate its effectiveness in classifying firms.
25
Financial, Educational, Healthcare and Leisure. We collect data on publicly traded for-profit firms from Compustat. As in previous tables, we drop the extreme 1% observations within each subsample. Table 6 reports results from this comparison. We have 8,540 for-profit firm-years and 37,333 nonprofit firm-years in this subsample. Within these groups, the representation of nonprofit and for-profit firms differs widely, with Media being dominated by for-profit firms, and Educational and Healthcare being dominated by nonprofits. The pooled coefficients for the nonprofit subsample are similar in magnitude to those reported for our full nonprofit sample in Table 3 Panel A. However, the for-profit results indicate no asymmetric persistence, contrary to the strong asymmetric persistence reported in prior research. This suggests that the common NAICS industries are more representative of nonprofit industries than for-profit industries. The preliminary results indicate that we find asymmetric persistence, i.e. a negative β1 coefficient, only when the sample size is large, for either for-profit or nonprofit sectors. While this is consistent with competition amongst firms with similar organization structures causing asymmetric persistence, it is also possible that sampling error reduces our ability to detect this effect in smaller subsamples. The Financial sector is the only one where we find no evidence of asymmetric persistence in either the for-profit or nonprofit sample, consistent with mark-tomarket accounting for financial assets or industry-specific regulation dominating any asymmetric loss recognition for nonfinancial assets.
7.
Conclusion Because of their different organizational structure, nonprofit enterprises provide an
interesting setting for comparing the effects of accounting standards versus contracting structures
26
on the properties of financial accounting performance measures. We examine over 100,000 nonprofit-years from 1988-1997 to investigate the time-series properties of nonprofit earnings. Our tests indicate that the change in net assets, the nonprofit equivalent of earnings, tends to reverse and is asymmetrically persistent, which is similar to results documented in for-profit research. We find similar evidence of mean reversion and asymmetric persistence for nonprofit operating cash flows. These main results are consistent with the effects of economic mean reversion in profitability due to competition that have been advanced in for-profit research (Beaver & Morse, 1978; Fama and French, 2000). However, there appears to be little systematic difference in the properties of earnings and cash flows, unlike the case in for-profit research. This suggests that operating accruals play a different or smaller role in nonprofits than for-profit enterprises. The lack of difference in asymmetric persistence between change in net assets and operating cash flows is consistent with auditor liability concerns being less important in the nonprofit sector than for publicly traded firms. It is also consistent with nonprofit auditors not having easy access to a signal of value decline that publicly-traded firms have, i.e., negative stock return. It is also consistent with managers having less compensation or job security related reasons to undertake “big baths” than their for-profit counterparts. In other words, differences in the time-series properties of earnings in nonprofit and for-profit organizations are consistent with systematic differences in their contracting structures playing an important role, even though the FASB has “harmonized” their accounting standards. There is considerable variation in these earnings time-series properties across different nonprofit sectors. Although this variation is probably related to different competitive and/or regulatory environments, we leave a systematic investigation of these possibilities to future
27
research. A preliminary comparison of for-profit and nonprofit firms classified in the same NAICS industries indicates greater asymmetry for nonprofit firms than for-profit firms in the pooled samples, inconsistent with our expectations. However, larger industries are associated with greater asymmetric persistence, consistent with competitive pressures inducing economic mean reversion. Future research could also explore variation in these earnings properties across time. We believe that empirical research on the large nonprofit sector can increase our knowledge about fundamental accounting issues, and complements research that compares differences in for-profit accounting between countries or industries.
28
Appendix A.1
A brief history of nonprofits The U. S. concept of the non-religious, non-sectarian nonprofit organization can be traced
back to sixteenth century England.25 It was during this period, when government support of civilian needs was limited, that private philanthropies developed to provide funding for a variety of societal necessities. This relationship helped shape the nonprofit’s distinct organizational characteristics (Hall, 1987). As the nonprofit concept continued to evolve, tax policy issues surfaced. Ultimately, nonprofits were distinguished from other tax paying entities as part of the British Statute on Charitable Uses of 1601. Though the American colonies were influenced by the British concept of the nonprofit, few nonprofit corporations existed in the colonies prior to 1780. This was in part because their status was not firmly established in the law. For example, Harvard College, the oldest corporation in colonial New England, was organized by charter (making it technically private). However, Boards consisting of state and state-established church officials governed it. Harvard received endowments from private benefactors, but it also received funding from public allocations. At the time, Harvard was considered a public institution. It was only after the colonies declared independence that a more formal legal concept for nonprofits developed (Hall, 1987). Nonprofits ultimately emerged as either charitable trusts or private corporations and were creatures of state law. From the end of the U.S. Civil War to the turn of the 19th century, nonprofit organizations became increasingly instrumental in furthering cultural, educational and scientific endeavors. This was a period of rapid economic growth, which together with the emergence of large
25
Private charitable foundations can be traced back to Roman times, and have existed in one form or another in most civilizations (Margo, 1992).
29
corporations and well-developed financial markets, resulted in a sharp increase in the number of personal fortunes. This Progressive Era was also one characterized by an increased concern for social welfare. By the start of the twentieth century, nonprofits had become more economically significant and carried influential social implications. They were viewed as an independent sector, i.e., an alternative to government and a supplement to big business. The Great Depression altered the relationship between government and the nonprofit sector, causing the nonprofit sector to become increasingly reliant on federal funds. After World War II, the steady growth in the number and size of nonprofit organizations drew the attention of Congress. Beginning in the early 1950’s and continuing on through the early 1980’s, a number of committees and commissions were formed to evaluate the role and scope of the nonprofit sector. These deliberations led to stricter oversight and reporting requirements, particularly of private foundations. However, nonprofits retained the two primary benefits of nonprofit status tax exemption and the ability to solicit tax-deductible contributions.
A.2
Development of nonprofit financial accounting Fiscal control is emphasized throughout the development of the nonprofit accounting and
reporting practices. Fiscal control was emphasized in the Venetian method of double entry bookkeeping. Early double-entry bookkeeping systems were ostensibly “customized” to meet the needs of merchants and clergy based on existing business practices, such as controlling inventories of wine and other staples (Peragallo, 1971). Business contributions to charity were recorded in the ledgers under “God’s account” (e.g. D’Epiro & Pinkowish, 2001, pp. 110,150). These Italian accounting methods came to America via Britain.
30
In the early 1900’s, the Institute for Government Research (presently the Brookings Institution) commissioned Francis Oakey to report on the principles of government accounting and reporting. The Oakey Report (1921) laid the foundations for governmental fund accounting. Many of Oakey’s comments and suggestions were adopted by the nonprofit sector, particularly those related to fund accounting and to fiscal control. The AICPA and American Accounting Association (AAA) extended Oakey’s work and issued guidance on the application of fund accounting by nonprofits. However, it was unclear if generally accepted accounting principles (GAAP), in their entirety, applied to nonprofit entities. Accounting Research Bulletin No. 43, Chapter 1, par. 5 (Committee on Accounting Procedures, 1953) discusses the applicability of GAAP to business and nonprofit organizations: The committee has not directed its attention to the accounting problems or procedures of religious, charitable, scientific, educational, and similar nonprofit institutions, municipalities, professional firms and the like. Accordingly, except where there is a specific statement of a different intent by the committee, its opinions and recommendations are directed primarily to business enterprises organized for profit. In 1966, the AAA issued A Statement of Basic Accounting Theory, which started narrowing the accounting theory gap between for-profit and nonprofit enterprises. In 1971, the AAA issued a comprehensive follow-up report, which assessed the merits of existing accounting practices and made suggestions on the form and content of nonprofit reporting practices. The AAA recommended that the full accrual basis be considered a generally accepted accounting principle for the preparation of nonprofit financial statements. Second, although fund accounting provides a methodology for the maintenance of fiscal controls of individual funds, the AAA recommended that more attention be paid to providing information on the composite nonprofit operating entity taken as a whole in the financial statements.
31
The Filer Commission’s report (Commission on Private Philanthropy and Private Needs, 1977) criticized accounting methods used by eleemosynary organizations. In response, the AICPA issued SOP 78-10, Accounting Principles and Reporting Practices for Certain Nonprofit Organizations (AICPA, 1978), as well as two Audit Guides directed at colleges, universities and voluntary health and welfare organizations (AICPA 1973, 1974). These publications took the first steps in unifying nonprofit accounting principles. However, numerous inconsistencies still remained, particularly among specialized industry groups. During the late 1970's and early 1980’s, the FASB issued six Statements of Financial Accounting Concepts (SFAC). SFAC No. 4 (FASB, 1980c) specifically addressed the objectives of general purpose external financial reporting by nonbusiness organizations. SFAC No. 4, par.1, claims, “It is not necessary to develop an independent conceptual framework for any particular category of entities e.g. nonbusiness organizations or business enterprises.” Instead, FASB clearly indicates that nonprofit financial reporting objectives should be grounded in the fundamental notion of decision usefulness, consistent with SFAC No. 1 (FASB, 1978). This reasoning later prompted the issuance SFAC No. 6 (FASB, 1985), which superseded SFAC No. 3 (FASB, 1980b), and expanded its scope to include nonprofit organizations as well. Though several issues were addressed on a conceptual level, inconsistencies in accounting and reporting practices remained unresolved. In March 1986, the FASB added three items to its nonprofit project agenda: (1) accounting for depreciation, (2) accounting for contributions and (3) the display of information in financial statements. These items were addressed in SFAS No. 93 (FASB, 1987), SFAS No. 116 (FASB, 1993a), and SFAS No. 117 (FASB, 1993b), respectively.26
26
The FASB issued SFAS 136 in 1999 on accounting for donations to certain charitable trusts. Currently, the FASB has an agenda item on accounting for nonprofit combinations, with the intent of developing a purchase accounting
32
To better align its position with that of the FASB, the AICPA issued audit guidance (AICPA, 2001a, 2001b) that integrated many of the changes initiated by SFAS Nos. 93, 116, and 117. These audit guides recommend that not-for-profit organizations follow the effective provisions of ARB, APB and FASB statements and interpretations unless otherwise specifically exempted. To sum up, nonprofit financial accounting has rapidly converged to for-profit financial accounting since the mid-1980s, and they are now essentially identical.
model for nonprofits, so that SFAS Nos. 141 and 142 (FASB, 2001a, 2001b) can be applied when two nonprofits merge.
33
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TABLE 1 Descriptive Statistics
Panel A:
Selected Variables Used in the Analysis – Years 1988 through 1997
N=101,364
Mean
Median
Standard Deviation
Total assets
59,826
18,011
257,996
0
24,340,526
Total revenues
39,180
9,199
141,698
-46,877a
11,129,011
Change in net assets
4,032
599
45,069
-2,627,264
10,125,942
Operating Cash flows
6,192
1,298
51,080
-2,243,278
10,300,607
18,716
351
173,149
-2,098b
33,254,000c
6.5
6.1
1329.7
Administrative cost ratio
15.4
10.5
129.9
Program expense ratio
79.7
85.1
21.0
Variable
Minimum
Maximum
(in $000's)
Investment in securities (in %'s) Surplus margin ratio
a
There are 233 observations with negative total revenues. Negative total revenues result from the reporting of certain revenue items (net of related expenses) in the revenue section of the Form 990 tax return e.g. rents, gains and losses from the sale of assets, special events and inventory sales. b
There are 3 observations with negative investment in securities. A negative value for this variable likely results from (1) reclassifications within the Form 990 balance sheet and/or (2) data entry errors. All three of these observations report positive total assets and total revenues. c
There is 1 observation with investment in securities greater than the maximum value for total assets.
41
TABLE 1 (continued) Descriptive Statistics
Panel B:
Variables Used in the Analysis - Scaled by Total Revenuest-2 Years 1989 through 1997
Mean
Median
Standard Deviation
Minimum
Maximum
Total assets
5.992
1.660
28.600
0
2,423
Change in net assets
0.311
0.060
1.441
-23.769
50.995
Operating Cash flows
0.445
0.119
2.001
-34.504
70.690
Variable N=75,108
Observations falling in the top or bottom 1% of change in scaled net assets or operating cash flows are excluded
Panel C:
Correlations Among Variables Used in the Analysis - Scaled by Total Revenuest-2 Years 1989 through 1997
N=75,108 Total Assets Change in Net Assets Operating Cash Flows
Total Assets
Change in Net Assets
Op. Cash Flows
-
0.446 ** -
0.547 ** 0.798 ** -
0.478 ** 0.567 **
0.790 **
Pearson correlation coefficients below the diagonal, Spearman correlation coefficients above the diagonal. Observations falling in the top or bottom 1% of change in scaled net assets or operating cash flows are excluded.
**p-value
