SOCIAL ENTERPRISE: INNOVATION OR MISSION DISTRACTION?

REBECCA TEKULA, PH.D. Pace University Helene and Grant Wilson Center for Social Entrepreneurship 163 William Street, 21st Floor New York, NY 10038 Tel: (212) 346-1028 Fax: (914) 989-8038

I am particularly grateful to Professor Dr. Marco Meneguzzo, Dean Dr. Brian Nickerson, and Professor Alex Murdock for their guidance and advice on this work; the participants and discussants of the ProDoc session of the 2009 Swiss Public Administration Network conference for their useful feedback; Monica Bommarito for her support during my time at the University of Lugano; Wilson Center graduate student aid Anna-Kay Sinclair for her research assistance; and Keywan Rasekhschaffe for his useful insights, keen intuition, and invaluable support. All errors are my own.

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ABSTRACT

This study examines the relationship between unrelated business income (UBI) and program-related expenditure of human service nonprofit organizations based in New York County. The results of my analysis do not indicate a positive relationship between unrelated business income and programmatic expenditure. These findings are in accordance with crosssubsidy theories of diversification in which internal budgeting allocates funds to divisions with few investment opportunities (ailing enterprises of nonprofits) while failing to channel funds to those with ample investment opportunities (effective, efficient programs that attract public and private funding).

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INTRODUCTION

“Increased resources bring added outputs, but at the cost of the distraction of the nonprofit from its declared mission.” Burton Weisbrod, 1988

In 1988, when Burton Weisbrod hypothesized that as nonprofits branch out from their central mission the quality of their principal tax-exempt activities would decline, the terms “social entrepreneurship” and “social enterprise” were not part of the popular discourse. Since then, the work of Bill Drayton (2002), Charles Leadbeater (1997), David Bornstein (2004), and Gregory Dees (1998) have further shaped the way academics and practitioners think about social entrepreneurship, social enterprise and sustainable income in nonprofit organizations. The central argument of many of their theories is that charitable or socially beneficial activities will be longer lasting and have a more penetrating effect when these activities are either married with or fully integrated into a model generating earned income. The Drayton-Leadbeater-Bornstein-Dees paradigm has significant impact in a growing sector of the global economy. The nonprofit sector plays an increasingly important role in the provision of vital services in fields such as healthcare, social service, and education. The size of the U.S. nonprofit sector has increased rapidly from approximately 12,000 registered organizations in 1940 to over 1.5 million today, and the aggregate book value of assets, as reported by nonprofit organizations which filed IRS information returns for tax year 2008, was over $4 trillion, or 8.9% of U.S. GDP (Urban Institute, 2009).

Background of Enterprising Behaviors of Nonprofits

Tekula: Page 4 Researchers have noted that by the mid-1970s, data on the revenue sources of nonprofits clearly indicated a substantial dependence on non-donated revenues, that is, income from either membership dues or some form of sales. Burton Weisbrod (1991) notes that as early as 1908, the Metropolitan Museum of Art operated a sales shop. In 1982 the Girl Scouts sold 125 million boxes of cookies for gross revenue of over $200 million (Weisbrod, 1991). Through the 1980s researches noted that this earned income behavior was increasing sharply. There is general agreement amongst theoreticians that we can trace this growing engagement in profit-generating activities to cutbacks in federal funding in the 1980s both in the U.S. and across Europe (Adams & Perlmutter, 1991). As early as 1983, sector analysts were reporting the growth of nonprofit enterprise. According to a text published that year, “sixty-nine percent of the organizations we surveyed have given birth to new [profit-oriented] enterprise within the past twelve years” (Crimmins and Keil, 1983).

Mission Distraction Just five years after Crimmins and Keil noted the proliferation of profit-oriented enterprises, in 1988 Burton Weisbrod hypothesized that unrelated business activities might divert nonprofits from their charitable purpose (Weisbrod, 1988). This most important dilemma, that business activities may distract charities from their mission, may be due to the pressure to perform profitably in the competitive marketplace, which can divert resources and energy from the organization’s principal social purpose even while total resources are being expanded. This behavior can be likened to the inefficient cross-subsidies theory of corporate diversification. Diversification discounts have been calculated by various researchers in the field of corporate

Tekula: Page 5 finance. Findings estimate that the subsidization of poorly performing segments contributes to value losses between 13 percent and 15 percent (Berger & Ofek, 1995).

Human Service Nonprofits Amongst all public charities, human service organizations can be considered the closest to the traditional definition of charity, in that they provide essential services, especially for those who are least able to help themselves (USDHHS, 2009). Human service is an area considered inappropriate for profit making (Groenbjerg, 2001; Guo, 2006). Yet following with overall trends in the nonprofit sector in recent decades, human service nonprofit organizations have notably increased their earned income behaviors, tripling this type of income in the years 1995 to 2005 (IRS BMF, 2007) Nonprofit charitable organizations are generally exempt from paying state and local taxes on property used “primarily” for the organization’s exempt purpose; and nonprofits are exempt from federal and state corporate income taxes on income from activities that, even if commercial, are deemed to be substantially related to the organization’s primary exempt purpose (Cordes & Weisbrod, 1998). However, in addition to this exempt income, a growing number of tax-exempt organizations have begun to earn an increasing amount of “unrelated business income” (UBI) from commercial and other activities that are not substantially related to their tax-exempt missions and is thus subject to Federal taxation. Income is defined as UBI if it is produced from an activity that is conducted on a regular basis and is not directly related to an organization’s taxexempt mission: the fact that the income may be used for furthering an organization’s exempt purposes does not alter the definition and therefore any profits from these activities are taxed at regular corporate or trust income tax rates (Riley, 2002). Current theoreticians of social

Tekula: Page 6 enterprise and social entrepreneurship would term this type of revenue generation by a nonprofit an “external” model of social enterprise (Alter, 2007). Until now the possible consequences of social enterprise on programmatic activities has remained speculative; hard evidence from large sample empirical studies does not exist. Previous authors have conjectured that an increase in financial dependence on market sales relative to donations will diminish the contribution of some nonprofits to social welfare (Weisbrod, 1988). Still, myriad philanthropists and private foundations, as well as government agencies, purport the benefits of “sustainable” earned income for nonprofit organizations without the benefit of an indepth analysis of the effects of earned income on programmatic output. Closer study of the impact of enterprising activities on program activities is necessary and long-overdue. Unanswered questions which I hope to address with the present study include: What is the relationship between unrelated business income (external social enterprise) and program expenditure? What is the relationship between financial distress factors of organizations and their enterprising behavior? In other words, do financially weak organizations become more enterprising, and vice versa? I also attempt to address the issue of causality by relating future changes in enterprising behavior and program expenditure to lagged explanatory factors.

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LITERATURE REVIEW

Globally, there is growing attention placed on the enterprising activities of nonprofit organizations, much of which is theoretical analysis of this activity. Kim Alter (2007) offers a spectrum-like typology of social enterprise the motivation for which she describes with the following: The growing practice of social enterprise is fueled by nonprofit organizations’ quest for sustainability, particularly in current times when support from traditional, philanthropic, and government sources is declining and competition for available funds is increasing. Social enterprise enables nonprofits to expand vital services to their constituents while moving the organization toward selfsufficiency. Nonprofit organization leaders understand that only by establishing an independent means of financing can they become a going concern. Alter’s typology ranges from a fully “integrated” model of social enterprise, in which the income-generating activity is in fact part of the mission of the organization to an “external” model in which the enterprise in unrelated to the mission. Many researchers and theoreticians look to enterprising behavior as a beacon of light for a nonprofit sector rife with struggling organizations. Lasprogata and Cotton (2003) offer an analysis of the business and legal challenges of social entrepreneurship and conclude that “Traditional revenue sources are rapidly dwindling…Social service nonprofit organizations that adopt an entrepreneurial approach to sustaining social mission may have the solution” (p. 110). Stefan Toepler (2006) reviews the underpinnings of the current commercialization debate in the nonprofit sector with an analysis of the Metropolitan Museum of Art and finds that current conceptual frameworks of this phenomenon are adequate in explaining the motivations behind the Museum’s commercial activities. However, Toepler argues that the changing rationale and

Tekula: Page 8 the economic fortunes of these enterprising activities highlights the need for a better understanding of the effects and consequences of commercial activity by nonprofit organizations which is increased by the push for growth of enterprising behavior by these organizations. Foster and Bradach (2005) argue that the enthusiasm for business which reached a height during the 1990’s has had a profound impact on nonprofits. Yet they hypothesize that launching and running enterprising ventures consumes scarce management resources and dilutes an organization’s focus on its social programs and caution that executives of nonprofit organizations should not be encouraged to “search for a holy grail of earned income in the marketplace” for fear of harming “society itself, which depends for its well-being on a vibrant and mission-driven nonprofit sector (p. 100). J. Gregory Dees (2004) cautions that we must not consider nonprofit business ventures as a panacea: “Nonprofit leaders should not jump on this bandwagon without understanding and addressing the challenges, costs, and risks of taking the ride…In some cases, the financial benefits will not be worth the hidden costs to the organization” (p. 4). Several studies have endeavored to uncover the impact of such behavior on the missionrelated output of nonprofit organizations. For example, in the face of commercialism, blood transfusion services deteriorated (Titmuss, 1971), and nonprofit organizations that were successful in their enterprising activities shifted their emphasis toward a more affluent client base (Adams & Perlmutter, 1991; Weisbrod, 2004). Salamon (1995) examined the impact of income source on client focus and found that revenue from fees are negatively correlated with poverty focus. More recently, Baorong Guo (2006) conducted an analysis of self-reported survey data of 67 nonprofits which considered themselves to be “venturing” (from a larger sample of 519).

Tekula: Page 9 Guo found that as commercial revenue increases in human service nonprofits, donative revenues decrease. More relevant to my analysis, Guo finds that commercial revenues “do not make a significant contribution” on the organizations mission and service delivery. Pierre-Emmanuel LY (2006) analyzed data on 74 UK-based international NGOs to determine if NGOs treat donated and earned income as perfect substitutes. LY found that while donated and earned income have a positive and significant effect on charitable expenditure, the effect of earned income is significantly less than that of donations. Outside of the literature on social enterprising behavior and nonprofit earned income, we can also look to the finance literature for information on the allocations of resources between divisions of a diversified firm. In fact, Rajan, Servaes and Zingales (2000) were able to find evidence consistent with their hypothesis that when diversity in resources and opportunities increases in a firm, resources can flow toward the most inefficient division, leading to more inefficient investment and less valuable firms. Overall, there have been very mixed reviews and theories of the impact of enterprising behaviors on the programmatic output of nonprofit organizations. While early work to explore the impact of enterprising behavior on nonprofits did uncover evidence of a mission shift to less necessary services, a large focus in the literature has been on touting the strengths of earned income as a sustainability strategy for nonprofit organizations. Still, many researchers have concluded that there is a distinct and growing need for a better understanding of the effects and consequences of commercial activity by nonprofits organizations. But until now, empirical analysis with a large random sample of nonprofit organizations does not exist in the literature. Learning from the work of Rajan, et. al., the current analysis endeavors to uncover possible

Tekula: Page 10 similar inefficient investment or cross-subsidy in the allocations of resources in nonprofit organizations.

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METHODOLOGY

My analysis focuses on addressing the following questions: (1) What is the relationship between unrelated business income (external social enterprise) and program expenditure? (2) What is the relationship between financial distress factors of organizations and their enterprising behavior?

Specification 1:

PE  1UBI _ RATIO   2TR   My main regression is Specification 1. This regression directly relates the variable programmatic expenditure as a proportion of total expenditure (PE) to the unrelated business income as a proportion of total income (UBI_RATIO) and organization size as proxied by total revenue. The motivation for this model is to explore the relationship between unrelated business activities, as a percentage of total income, to the contemporaneous and future programmatic focus. The program expenditure to total expenditure ratio is a commonly used indication of the potential return on investment for a funder. This ratio represents the amount of a dollar invested (donated) that will be spent on the programmatic mission of the organization. Total revenue is introduced in this specification as a control variable.

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Specification 2

PE  1UBI _ RATIO   2TR   Specification 2 introduces the dependent variable of change in the ratio of program expenditure to total expenditure and size as proxied by total revenue. While it is often difficult to relate or predict changes in a variable (here, change in programmatic spending as a proportion of total spending), with this specification I attempt to draw out the relationship between changes in unrelated business activity and the change in program focus.

Specification 3

UBI _ RATIO  1LIAB _ RATIO   2TR   Specification 3 introduces contemporaneous proportion of unrelated business income as the dependent variable, as related to the value of liabilities-to-assets ratio (LIAB_RATIO) for the previous organizational year. The motivation for this specification is to uncover the relationship between organizational distress (LIAB_RATIO) and unrelated business income. Total revenue is again introduced as a control variable.

Sample and Data I consider unrelated business income as the sum of Lines 104b and 104d of the IRS Form 990. The lines represent, respectively, taxable unrelated business income and income taxexcluded by sections 512, 513, and 514 of the tax code. This data, as with the data for each of my variables, is collected from the IRS Business Master Files and the IRS Statistics of Income and assumed to be an accurate proxy for the unrelated business activities of the given

Tekula: Page 13 organizations. I further consider the programmatic expenditure of these organizations to be an accurate proxy for the relative level of their programmatic activity. Of course we cannot look at market value of nonprofits, but the output of social goods can be proxied by the expenditure on social goods (program expenditure). I test my hypothesis empirically using a sample of nonprofit human service organizations operating within New York County, which has the same boundaries as the Borough of Manhattan and is reported in the IRS Business Masters Files as those organizations with the fivedigit Federal Information Processing Standard (FIPS) code 36061. In order to ensure a high level of homogeneity, I focus on a relatively specific yet large population of organization: human service nonprofits operating in Manhattan. In addition to offering a homogeneous sample, human service organizations are often considered the most closely related to the idea of charity, and are addressing the most visceral needs of the neediest groups of people. My data are from IRS Form 990 samples drawn by the Statistics of Income (SOI) Division of the United States Internal Revenue Service, for the six years 2000 to 2005, inclusive. The Form 990 includes detailed data on each registered nonprofit organization’s revenue, expenses, assets and liabilities. The SOI samples include all nonprofits that are exempt from taxation under section 510 ( c ) (3) of the Internal Revenue Code (donations to these organizations are tax-deductible on personal income tax returns) and that have assets of at least $10 million, as well as a smaller sample of small organizations. While the number of registered nonprofits organizations in the U.S with assets of over $10 million represents only 5% of all nonprofit organizations filing form 990 US Tax Returns (including 990EZ and 990PF), this group represents 81.5% of total reported revenues and 89.5% of total reported assets for the sector. From these samples, I drew upon only those in the Human Services division of the

Tekula: Page 14 industry: those classified as within the National Taxonomy of Exempt Organizations (NTEE) classification system Major Group code “HU”. The final sample represents 700 organizational years, and covers 2000 to 2005, inclusive.

Characteristics of Sample Nonprofits Table 1 displays distributions for the characteristics of the sample, including all explanatory variables used in the regression analysis. The values listed are means of values for each organization, computed using sums for all years that the organization appears in the sample. Total expenses values are derived from the value listed as such on the tax return for each organizational year, for each organization. Program service expenses are also listed as such on the tax return. Program spending ratio is the proportion of program service expenses to total expenses. Total revenue includes direct and indirect contributions, government support, revenue from program services, membership dues, investment revenue, and both related and unrelated business income. Unrelated business income the sum of Lines 104b and 104d of the IRS Form 990. The lines represent, respectively, taxable unrelated business income and income taxexcluded by sections 512, 513, and 514 of the tax code. Total assets include cash, savings, receivables (accounts, pledges, grants, loans, and notes), inventories, prepaid expenses, deferred charges, investments, land, buildings and equipment. Total liabilities include accounts payable, accrued expenses, grants payable, deferred revenue, loans, tax-exempt bond liabilities, mortgages and notes payable.

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Tekula: Page 16 The average expenses for these organizations is $19,176,503. Program services make up an average of 82.2% of total expenses, at an average $16,647,579. Mean total revenue is $20,306,188, with an average of $1,325,121 in unrelated business income. The assets of these organizations are substantial, averaging $42,402,251, with mean liabilities of $19,342,615.

Pearson Correlation Coefficients Table 2 reports mean cross-sectional correlations for the period 2000 through 2005 (inclusive). Reported correlations are average correlation coefficients across the six years in the sample. Pearson correlations are presented in the table with corresponding p-values in italics below.

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Not surprisingly, the proxy for size (total revenue) is positively correlated with program spending ratio. Clearly economies of scale would contribute to this finding. Also noteworthy is the result that total revenue and unrelated business income ratio are strongly correlated, which indicates that larger organizations are more likely to earn a high proportion of unrelated income.

Regression Analysis I follow the methodology first proposed by Fama and Macbeth (1973), which continues to be considered an appropriate and fairly simple approach to analyzing panel data. For each year, and for each specification of my three models, I conduct cross-sectional regressions and record the slopes (coefficients). The final coefficients are the time series averages for each of the cross-sectional slopes. The t-statistic is computed using the time series standard deviation. Intuitively, it is natural to judge the accuracy of a coefficient by its variation. This approach very directly uses the time series variation to assess the significance of coefficients. The method was devised for asset pricing tests, but in this case we face a similar problem of correlated errors in the cross-sectional dimension.

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RESULTS

Regression Analysis The next few tables report the results of estimating each of my three specifications for the six cross-sectional regressions for the years 2000 to 2005, inclusive. Mean coefficients are means of the six estimates. The t-statistics are computed in the manner of Fama and Macbeth (1973). The indicated “t-statistic” value in each of the following tables represents the results from the test on whether or not the coefficients are statistically different from zero. Generally, a coefficient with a t-stat of ≥1.96 or ≤-1.96 (95% confidence level) indicates that the coefficient is significantly different from zero. In other words, at ±1.96, there is a 5% chance that the coefficient is not different from zero. Table 3 presents the main result of my analysis, Specification 1. In this table, PE represents the program expenditure to total expenditure ratio. UBI_Ratio is the unrelated business income as a proportion of total income. TR is Total Revenue. Specification 1:

PE  1UBI _ RATIO   2TR  

Table 3: Specification 1 coefficient tstat

1

2

-0.173 (-7.24)

0.064 (5.68)

adjr2 0.047

The proportion of unrelated business income (“external” enterprising behavior) is significantly negatively related to program expenditure ratio. As hypothesized, the internal capital markets of

Tekula: Page 20 nonprofit firms seem to follow that of for-profit firms in that diversification leads to value loss as proxied by programmatic expenditure. What can be inferred from my findings is that this particular type of external enterprising behavior is associated with less value in the programmatic output of human service nonprofits. Table 4 presents my next model, Specification 2. ∆PE represents a ratio of the current PE to the previous period’s PE. UBI is the unrelated business income as a proportion of total income. ∆UBI_RATIO is the logarithmic change in the proportion of current UBI to the previous period’s proportion of UBI. TR is total revenue. Specification 2:

PE  1UBI _ RATIO   2TR  

Table 4: Specification 2 coefficient tstat

1

2

-0.13 (-1.19)

0.485 (0.823)

adjr2 0.0065

Here, when considering change in program spending ratio, unrelated business income remains negatively, but insignificantly associated. Table 5 details my third and final model, in which UBI _RATIO is the unrelated business income as a proportion of total income. LIAB_RATIO is the ratio of liabilities to assets. TR is the total revenue.

Tekula: Page 21 Specification 3:

UBI _ RATIO  1LIAB _ RATIO   2TR  

Table 5: Specification 3 coefficient tstat

1

2

-0.146 (-23.08)

-0.001 (-6.30)

adjr2 0.11

Results from this model suggest that UBI is significantly and negatively related to organizational distress as proxied by liability-to-asset ratio. This serves as evidence that nonprofit organizations follow for-profit firms in their diversification behaviors in that financially stronger (weaker) nonprofits are more likely to have a higher (lower) proportion of unrelated earned income. In other words, it appears that larger firms are more likely to source diversified revenues in the form of unrelated business income.

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CONCLUSION

Until now the possible consequences of social enterprise on the programmatic activities of nonprofit organizations has remained speculative; hard evidence from large sample empirical studies did not exist. Previous authors have conjectured that an increase in financial dependence on market sales will diminish the contribution of some nonprofits to social welfare (Weisbrod, 1998). Still, myriad philanthropists, associations and now federal and local governments are supporting the social enterprise movement with growing fervor, and without the benefit of an indepth analysis on the relationship between earned income and programmatic output: closer study of the impact of enterprising activities on program activities has been necessary and longoverdue. My findings are in accordance with cross-subsidy theories of diversification in which internal budgeting allocates funds to divisions with few investment opportunities (ailing enterprises of nonprofits) while failing to channel funds to those with ample investment opportunities (effective, efficient programs). While this research is a first step toward identifying the factors associated with earned income behavior in nonprofit organizations, there is much work to be done in this area. My analysis focused clearly on unrelated business income, which social enterprise scholars and practitioners would consider an “external” funding model in which the source of funds is not related to the exempt mission of the organization. A largesample empirical analysis of the relationship between proportion of programmatic expenditure and related or “internal” earned income would also be beneficial to the current body of literature. It also would be useful to identify failures of unrelated business ventures in order to identify

Tekula: Page 23 potential risk factors and begin to understand potential indicators of future success (failure) of these activities. Furthermore, in order to create a clear distinction between “charitable” and “business” activities, I identified human service organizations as the target of my analysis. Much work could be done in areas of the arts, healthcare, and education which have also experienced growth in the area of earned income. Clearly more thought and research must be invested in this area and caution must be given in popularizing and glorifying the unproven benefits of unrelated or external enterprising activities on the very organizations that have become important service providers for society’s neediest individuals. From a broad perspective, this works has an overarching motivation: myriad philanthropists, associations and now federal and local governments support with a growing fervor the social enterprise movement and the use of business practices and measures in the nonprofit sector, but without the benefit of much analysis on the appropriateness or the success of these practices and the programmatic output of these vital public service providers. Continuing exploration and critique of the applicability of business practices in the nonprofit sector is unarguably important not only for health of the nonprofit sector, but for the well-being of the general public which has come to rely so heavily on these organizations for human and social services.

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REFERENCES

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Tekula: Page 25 Dees, J. G. 2004. Putting nonprofit business ventures in perspective. In S. Oster, C. Massarsky, & S. Beinhacker (Eds.), Generating and sustaining nonprofit earned income: A guide to successful enterprise strategies: 1-18. San Francisco, CA: Jossey-Bass. Drayton, W. 2002. The citizen sector: becoming as entrepreneurial and competitive as business. California Management Review, 44(3): 122-132. Fama, E. F. & Macbeth, J. D. 1973. Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3): 607-636. Fama. E. F. & Jensen, M. C. 1983. Agency problems and the theory of the firm. Journal of Political Economy, 88(2), 327-350. Foster, W. & Bradach, J. 2005. Should nonprofits seek profits? Harvard Business Review, 83(2): 92-100. Frumkin, P. & Kim, M. T. 2001. Strategic positioning and the financing of nonprofit organizations: Is efficiency rewarded in the contributions marketplace? Public Administration Review, 61(3): 266-275. Groenbjerg, K. A. 2001. The U.S. nonprofit human service sector: A creeping revolution. Nonprofit and Voluntary Sector Quarterly, 30(2): 276-297. Hansmann, H.B. 1980. The role of nonprofit enterprise. The Yale Law Journal, 89: 835-98. Hansmann, H. B. 1989. Unfair competition and the unrelated business income tax. Virginia Law Review, 75: 605-35.

Tekula: Page 26 Independent Sector. http://www.independentsector.org/PDFs/npemployment.pdf; Retrieved on June 1, 2009. Internal Revenue Service. 2004. Testimony: Charitable giving problems and best practices. IR2004-81, June 22, 2004. James, E. & Rose-Ackerman, S. 1986. The nonprofit enterprise in market economies. New York: Harwood Press. Lasprogata, G. A. & Cotton, M. N. 2003. Contemplating “enterprise”: The business and legal challenges of social entrepreneurship. American Business Law Journal, 41(1): 68-112. Leadbeater, C. 1996. The rise of the social entrepreneur, London, UK: Demos. Luksetich, W. 2008. Government funding and nonprofit organizations. Nonprofit and Voluntary Sector Quarterly, 37: 434-442. Milgrom, P. & Roberts, J. 1992. Economics, organization and management. United States: Prentice Hall National Center for Charitable Statistics. www.nccs.urban.org; Retrieved on June 3, 2009. Oster, S. 1995. Strategic management for nonprofit organizations. New York: Oxford University Press. Riley, M. 1995. Exempt Organization Business Income Tax Returns, 1991. Internal Revenue Service Statistics of Income Bulletin, 14(4): 38-63.

Tekula: Page 27 Riley, M. 2002. Unrelated business income tax returns, 1998. Internal Revenue Service Statistics of Income Bulletin, 21(4): 187-215. Salamon, L. M. 1995. Partners in public service: Government-nonprofit relations in the modern welfare state. Baltimore, MD: Johns Hopkins University Press. Schiff, J. & Weisbrod, B. 1993. Competition between for-profit and non-profit organizations in commercial markets. In A. Ben-Ner & B. Gui (Eds.), The nonprofit sector in the mixed economy 127-148. Ann Arbor, MI: University of Michigan Press. Simon, J. G. 1987. The tax treatment of nonprofit organizations: A review of federal and state policies. In Walter W. Powell (Ed.) The nonprofit sector: A research handbook. 67-98. New Haven, CT: Yale University Press. Smith, S.R., 2003. Social services. In L. Salaman (Ed.), The state of nonprofit America. Washington, D.C.: Brookings Institution Press and Aspen Institute Press. Titmuss, R. M. 1971. The gift relationship: From human blood to social policy. New York, NY: Pantheon. Toepler, S. 2006. Caveat venditor? Museum merchandising, nonprofit commercialization, and the case of the Metropolitan Museum in New York. Voluntas, 17: 99-113. United States Department of Health and Human Services. HHS.gov; http://www.hhs.gov/about/; Retrieved on May, 13, 2009. Urban Institute; The National Center for Charitable Statistics; http://nccsdataweb.urban.org/; Retrieved on April 2, 2009.

Tekula: Page 28 Weisbrod B.A. & Schlesinger, M. 1986. Public, private, nonprofit ownership and the response to asymmetric information: The case of nursing homes. In S. Rose-Ackerman (Ed.) The Economics of Nonprofit Institutions: Studies in Structure and Policy, 133-151. Oxford: Oxford University Press. Weisbrod, B. A. 1988. The nonprofit economy. Cambridge, MA and London: Harvard University Press. Weisbrod, B. A. 2004. The pitfalls of profits. Stanford Social Innovation Review, 2(3): 40-47. Weisbrod, B. A. (Ed.). 1998. To profit or not to profit: The commercial transformation of the nonprofit sector. New York: Cambridge University Press. Weitzman, M. S. & Lampkin, L. M. 2002. The new nonprofit almanac and Desk Reference. New York: Jossey-Bass, Table 1.1. at 4-5.

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BIOGRAPHICAL SKETCH

Rebecca Tekula, PhD, MPA, MBA Rebecca Tekula, PhD, is the Executive Director of the Helene and Grant Wilson Center for Social Entrepreneurship, an institute of Pace University aiming to serve students and nonprofit organizations towards the goal of more effective and efficient nonprofit management practices. Dr. Tekula completed her PhD in Economics at the University of Lugano, Switzerland. She earned her BA at Vassar College, her MPA from Pace University, and her MBA from the University of Oxford. She has an extensive background in New York City philanthropy and across the nonprofit sector.