Building Nonprofit Financial Capacity

Abstract

Building on the impressive body of research on issues of nonprofit revenue choice and mix, this research empirically tests Foster and Fine’s claim that revenue concentration contributes to the growth of nonprofit organizations. Using National Center for Charitable Statistics (NCCS) digitized data (1998-2003), the authors test whether revenue concentration is a viable revenue-generating strategy that can help bolster a nonprofit’s financial capacity. Overall, study findings refute the mythology of revenue diversification; the authors find that implementing a revenue concentration strategy generates a positive growth in one’s financial capacity—in particular, a growth in one’s total revenue, over time. Contrary to the prevalent charges laid at the door of high administrative and fundraising efforts by some, the authors find that in order to support financial capacity growth, nonprofits must make positive investments in favor of administrative and fundraising support but not in the form of high executive salaries.

Keywords

revenue concentration financial capacity nonprofit growth revenue structure overhead diversification

Introduction

In their inventory of the progress of research on nonprofit revenue sources and revenue diversification, Chang and Tuckman (2010) observed that this impressive body of research has been primarily centered on explaining revenue choices, the rewards and risks associated with revenue diversification, and the association between revenue diversification and nonprofit financial stability. The authors’ proposed agenda for future research continues to be directed at only one of two dimensions of financial health (Bowman, 2011)—achieving financial stability, which is a type of organizational survival generated from reduced volatility in revenue streams (Carroll & Stater, 2009; Tuckman & Chang, 1991; Yan, Denison, & Butler, 2009). This continued focus is no surprise, as it reflects a widespread negligence toward the second dimension of nonprofit financial health—financial capacity (Miller, 2001, 2003), that is, the “resources that give an organization the wherewithal to seize opportunities and react to unexpected threats” (Bowman, 2011, p. 38). Focusing on this second dimension, this research investigates whether revenue concentration is a strategy for building financial capacity.

A lot of attention has been on the potency of the revenue diversification strategy. This research however, examines whether the inverse of that—revenue concentration—has some utility in bolstering nonprofits’ financial capacity, as suggested by Foster and Fine. In their study of 144 nonprofits that had reached US$50 million in annual revenue between 1970 and 2003, the authors attributed the growth in revenue of 110 of these nonprofits to the organizations’ decision to “raise the bulk of their money from a single type of funder such as corporations or governments—and not . . ., by going after diverse sources of funding” (p. 46). Of these 110 nonprofits, 90% demonstrated reliance on “a single dominant funding stream such as government, individual donations, or corporate gifts” (Foster & Fine, 2007, p. 49), with almost 90% of the organizations’ total revenue being generated from a single dominant funding stream.

Although limited, the focus on the efficacy of the revenue concentration strategy is not new. For instance, Gronbjerg (1992) observed that nonprofits may sometimes opt to develop and rely on one to a few stable sources of funding in order to establish program and funding continuity. However, to our knowledge, until Foster and Fine’s (2007) research, no connection had been drawn between revenue concentration, as a revenue-generating strategy, for the specific purpose of growing one’s financial capacity. In fact, Foster and Fine claim that revenue concentration is the strategy of choice if nonprofit organizations want to grow and achieve sustainability or longevity. Along these lines, Faulk’s (2010) preliminary analysis of 3,642 U.S. nonprofit theatres also found evidence giving some credence of the potency of revenue concentration in bolstering one’s financial capacity.

In addition, prior literature also finds that organizations that appear relatively inefficient (i.e., a higher proportion of total spending allocated to administrative expenses, and/or fundraising expenses, resulting in a lower program expense ratio) receive less donor support (Greenlee & Brown, 1999; Jacobs & Marudas, 2009; Szper & Prakash, 2011; Tinkelman & Mankaney, 2007). On the other hand, administrative expenses can provide organizations with resource flexibility necessary to take advantage of capacity-building opportunities. In this research, we also consider whether investing in administrative and fundraising activities is associated with financial capacity building.

To this end, we rely on the 1998 to 2003¹ digitized data from the National Center for Charitable Statistics (NCCS). These data were drawn from the annual Form 990 filings submitted to the Internal Revenue Service by nonprofit organizations with revenues exceeding US$25,000 annually. The digitized data set has the advantage of differentiating government grants from private contributions, in addition to further distinguishing between direct and indirect private contributions. Such nuances allow us to construct different measures of revenue concentration. This data set also contains additional variables that would not be found in the NCCS core files, one of which is instrumental in the construction of one of our measures of financial capacity—total unrestricted end-of-year fund balance (Line 67 on the IRS 990 Form). There are, however, inherent weaknesses to this data set as has been adequately documented in the literature (see, Gordon, Greenlee, & Nitterhouse, 1999; Keating & Frumkin, 2003).

Nonprofit Financial Capacity

The current economic crisis has resulted in financial distress for social service nonprofit organizations due to declines in charitable donations and as their state and local government clients continue to scale back in response to their own fiscal challenges (Bridgeland & Reed, 2009). To add insult to injury, the demand for social services continues to rise. For instance, more than 70% of nonprofits in Michigan have seen an increase in service demand, with the state of Arizona seeing a more than 100% rise in the number of people seeking social services between 2007 and 2008 alone (Bridgeland & Reed, 2009). For these reasons, nonprofits are even more compelled to reevaluate their financial capacity along with devising revenue-generating strategies geared toward strengthening their financial capacity and, in the long term, bolster their financial sustainability. As noted in the literature, financially vulnerable nonprofits are likely to cut back on their services offerings (Greenlee & Trussel, 2000; Tuckman & Chang, 1991) or, in some cases, close altogether.

As noted earlier, financial capacity can be described as consisting of “resources that give an organization the wherewithal to seize opportunities and react to unexpected threats” (Bowman, 2011, p. 38). Financial capacity has also been conceptualized as organizational slack,² a view held prevalent in the private sector (e.g., Antle & Eppen, 1985; Bourgeois, 1981; Cyert & March, 1963). In the nonprofit context, Bowman views organizational slack in terms of returns on or percentage change in net assets (or total fund balance). In light of these two depictions and consistent with Foster and Fine (2007), as well as prior literature (e.g., Saxton & Guo, 2011), we first measure financial capacity in terms of total revenue (a measure of organizational size). Following Bowman’s conceptualization of capacity as organizational slack, we also include total fund balance as a measure of financial capacity. Due to the fact that fund balances may be restricted (and thus not available as a general organization resource) we further measure financial capacity as the total unrestricted fund balance.

The Role of Revenue Diversification

Donor preferences and priorities change, and government support waxes and wanes (Hager, 2001). As a result, revenue diversification has been offered as a strategy for maximizing one’s resource independence (Chang & Tuckman, 1994; Pfeffer & Salancik, 2003). A long-held belief is that nonprofits that reduce the volatility of their revenue streams with revenue stability resulting from a diversified revenue portfolio increase their organizations’ chances at survival (Carroll & Stater, 2009; Jegers, 1997; Kingma, 1993; White, 1983; Markowitz, 1952). As a result, various theoretical models of nonprofit financial health (e.g., Chang & Tuckman, 1994; Frumklin & Keating, 2002; Greenlee & Bukovnsky, 1998; Greenlee & Trussel, 2000; Greenlee & Tuckman, 2006; Trussel, 2002; Tuckman & Chang, 1991) consider revenue diversification as one of the key indicators of financial stability and of an organization’s agility in recovering from financial shocks.

In spite of this overwhelming endorsement of revenue diversification as an effective strategy for bolstering nonprofit organizations’ stability, others also extend alternative explanations for having diversified revenue streams. For instance, revenue diversification has also been positively associated with community buy-in and organizational legitimacy (Bielefeld, 1992; Galaskiewicz, 1990; Galaskiewicz & Bielefeld, 1998), whereby nonprofits consciously seek to widely diversify their funding sources in order to establish more relationships in the community. Such social networking signals the organization’s dependence on community support.

Furthermore, recognizing the influence of the variant nature of the services nonprofits provide, Young suggests that the extent to which a nonprofit’s revenue streams are diversified/concentrated may actually be a function of the nature of services it provides, that is, the types of benefits the services confer to a particular collection of beneficiaries. For example, although public benefits emanate from collective goods that exude a nonexcludability quality to them, and therefore accrue to society in general (e.g., educated youth, an inoculated population), private benefits accrue specifically to only those individual consumers who signal by their willingness to pay for the services provided (see Young, 2006). As a result, particular service fields are predisposed toward particular revenue mixes (see Fischer, Wilsker, & Young, 2010).

Without discrediting the importance of revenue diversification or of investing in secondary funding sources, Foster and Fine also remind us that there has to be a natural congruence of missions and beneficiaries with the primary funding source. In addition, concentrating one’s funding sources can also result in lower overhead costs as well as stimulate capacity growth (Foster & Fine, 2007). Overall, this finding suggests that the decision to diversify/concentrate one’s revenue streams can be a product of conscious strategizing on the one hand and a product of path dependence on the other, one that is driven by the nature of benefits (services) a nonprofit confers through its activities.

The Role of Overhead Costs

In addition to evaluating the impact of revenue concentration on nonprofit growth, we also examine the relationship between organizational efficiency—an arena that is currently being championed by nonprofit watchdogs of the likes of Charity Navigator and the Better Business Bureau—and financial capacity growth. Generally, nonprofit watchdogs view high overhead costs and nonprogrammatic expenses as indicators of inefficiency and waste. Such inefficiencies have been linked to reductions in donor confidence and support (Greenlee & Brown, 1999; Jacobs & Marudas, 2009; Tinkelman & Mankaney, 2007), which in turn reduce an organization’s overall financial capacity. For instance, investing in fundraising efforts has been observed to yield increases in financial capacity in the short run; however, when donors perceived prior fundraising expenses to have been too high, negative lagged effects resulted (Weisbrod & Dominguez, 1986).

Yet others contend that having access to high administrative costs provides organizations with some financial flexibility it can use as leverage in turbulent economic times (Tuckman & Chang, 1991). However, organizational capacity is reduced when nonprofits limit their fundraising and administrative oversight expenses (Bowman, 2006; Silvergleid, 2003). Furthermore, relying on more concentrated revenue bases may actually result in lower administrative and fundraising costs (e.g., Foster & Fine, 2007; Frumkin & Keating, 2002). In a nutshell, whether overhead costs are associated with higher or lower rates of financial capacity building remains an important empirical question, in addition to evaluating the effects of the revenue concentration strategy.

Data and Methods

Using the NCCS digitized data from 1998 to 2003, we empirically test whether revenue concentration leads to nonprofit growth (measured as financial capacity growth). These data allow us to capture a 5-year revenue growth period. Bowman (2011) classifies a 12-month period as a short-term period, one that reflects on an organization’s “resilience to occasional economic shocks while making progress toward meeting its long-term objective” (p. 42). Although not explicit, a long-term period can be considered anything beyond 12 months.

To that effect, unlike Foster and Fine (2007), who focus on a much longer growth period of 33 years (1970 to 2003) and rely on a much smaller sample (n = 144), this research focuses on a 5-year growth period. And unlike their case study approach, we employ ordinary least squares (OLS)³ analysis using a very rich multiple-year data set containing a national sample of nonprofit organizations (n ranging from 50,000 to 108,000). In addition, we also employ multiple measures of financial capacity growth (measured as 5-year percentage growths in total revenues, end-of-year total fund balances, and unrestricted end-of-year fund balances), instead of relying on merely “having more revenue” as an indicator of nonprofit growth. Finally, we also employ multiple measures of revenue concentration (following Calabrese, 2011; Carroll & Stater, 2009; Yan et al., 2009).

Dependent Variables: Financial Capacity Growth

When nonprofits raise surplus revenue, they contribute to building their growth potential for service expansion and other organizational investments (Carroll & Stater, 2009; James, 1983; Miller, 2001, 2003; Tuckman & Chang, 1991). Surplus revenues provide nonprofits “the wherewithal to seize opportunities and react to unexpected threats” (Bowman, 2011, p. 38). We therefore model financial capacity in the following three ways:

Percentage growth in total revenue

This measure is consistent with Foster and Fine’s and Yan et al.’s (2009) measures of nonprofit growth, measured in total revenue and the log of total revenue, respectively. We model nonprofit growth as the log of 5-year percentage growth in total revenues (Line 12 on the IRS 990 Form). Although total revenue as a “metric of growth” is limited, revenue remains a “central constraint that prevents many nonprofits from growing” (Foster & Fine, 2007, p. 49).

And consistent with Bowman’s (2011) conceptualizing nonprofit financial capacity as organizational slack, we also model financial capacity in terms of percentage growths in Total End-of-Year Net Assets or Fund Balances and Total End-of-Year Unrestricted Fund Balances as follows:

Percentage growth in total fund balance or accumulated surplus

Here we calculated the log of 5-year percentage growth in the end-of-year total fund balance (Line 73 on the IRS 990 Form). This includes unrestricted, temporarily, and permanently restricted funds, which, based on the 990 Form, includes excess income (Line 18), the beginning-of-year net fund balances (Line 19), and other changes in net assets (e.g., foreign gains, actuarial gains on annuity obligations, interest and dividends on gift annuity investments, increases in trust held by third party).

Percentage growth in total unrestricted fund balance or accumulated surplus

The richness of our data set also allowed us to model nonprofit growth in terms of unrestricted net assets calculated as the log of 5-year percentage growth in the end-of-year total unrestricted fund balance (Line 67 on the IRS 990 Form). Unlike the total fund balances, unrestricted net assets or fund balances capture only the funds available to nonprofits without restrictions (excludes restricted gifts and grants) and are within the control of the nonprofits. Unrestricted fund balances are an important source of a nonprofit’s internal financing (Bowman, Tuckman, & Young, 2011; Calabrese, 2011).

Independent Variables

Revenue concentration

Revenue concentration (or its inverse) has also been measured in several ways. Depending on the nature of the 990 data used, researchers often relied on three revenue streams—contributions, government grants, and program revenue (e.g., Carroll & Stater, 2009), whereas others expanded the revenue streams into four major categories—government grants, contributions, program revenue, and investment income (e.g., Yan et al., 2009). Using the Herfindahl–Hirschman Index (HHI),⁴ we therefore model revenue concentration in three ways: as measured by Carroll and Stater⁵ (HHI_C-S) and by Yan et al.⁶ (HHI_Yan), and similar to Calabrese (2011), we also include a comprehensive and finer measure⁷ (HHI_Comp) that takes advantage of the richness of the digitized data. The HHI ranges from “0” (which denotes perfect diversification) to “1” (which denotes perfect concentration).

Overhead costs

We measure the resources allocated to overhead costs (i.e., organizational efficiency) in two ways, as administrative efficiency—modeled as a ratio of administrative costs to total expenses (Line 14 divided by total expenses in Line 17 on the IRS 990 Form), and as fundraising efficiency—modeled as a ratio of fundraising expenses to total expenses (Line 15 divided by total expenses in Line 17 on the IRS 990 Form).

Control Variables

Our control variables reflect findings from previous research. In explaining nonprofit capital structure, previous research has also controlled for executive compensation as an important variable (Yan et al., 2009). The rationale is higher-paid executives are likely to have more professional training (Yan et al., 2009), they may possess skill sets, expertise, and innovative revenue-generating strategies and other ideas that can be implemented to improve their organizations’ financial capacity. On the other hand, similar to the negative lagged effect noted with fundraising costs (Weisbrod & Dominguez, 1986), high executive compensation could also be viewed as wasteful and inefficient, which may result in similar negative effects on a nonprofit’s financial capacity. We measure executive compensation as a percentage of total expenses (Line 25a as a percentage of total expenses in Line 17 on the IRS 990 Form).

Finally, following previous research on nonprofit financial health (e.g., Carroll & Stater, 2009; Chang & Tuckman, 1994; Faulk, 2010; Fischer et al., 2010; Greenlee & Trussel, 2000; Hager, 2001; Keating, Fischer, Gordon, & Greenlee, 2005; Tuckman & Chang, 1991; Yan et al., 2009), we also control for organizational demographics such as industry type (National Taxonomy of Exempt Entities [NTEE]), location (state), and organizational size (measured as a natural log of total revenues, total fund balance, or total unrestricted fund balance).

Table 1 below shows the descriptive statistics for the variables included in our models. Note here that the median revenue growth over the 5-year period was relatively tame (15%). The median total fund balance increased by 22% over the 5-year period, and the median unrestricted fund balance declined by 9% for the sample. A review of our three measures of revenue concentration reveals a consistently high concentration of revenue on average for the sample. Our most comprehensive measure (HHI_Comp) shows the lowest average concentration index (0.71), whereas the Carroll and Stater’s (2009) measure (HHI_C-S) has the highest average concentration index (0.82). The sample also reports an average administrative expense ratio of 14%, average fundraising expense ratio of 3%, and average compensation ratio of 5%. The size of the sample organizations is quite skewed toward larger organizations; therefore we log the dependent variable and size controls in this analysis.

Table 1.

Descriptive Statistics.

Variables	M	Median	SD	Min.	Max.	N
Dependent variables
5-year total revenue growth	7.61	0.15	185.28	–1	39,208	200,658
5-year fund balance growth	115.12	0.22	14,034	–1	4,573,157	198,965
5-year unrestricted fund balance growth	29.19	–0.09	2,893	–1	849,790	106,587
Independent variables
Revenue concentration (1998)
HHI_Comp	0.71	0.73	0.24	0.12	1	190,948
HHI_C-S	0.82	0.91	0.19	0.33	1	200,338
HHI_Yan	0.79	0.85	0.21	0.25	1	190,918
Administrative expenses ratio (1998)	0.14	0.07	0.20	0	21.77	199,683
Fundraising expenses ratio (1998)	0.03	0.00	0.10	0	13.55	199,683
Compensation ratio (1998)	0.05	0.00	0.16	0	51.88	199,683
Total revenue (1998) in millions	3.3	0.173	4.55	0	12,400	200,976
Total fund balance (1998) in millions	3.65	0.133	74.3	0	15,900	200,976
Total unrestricted fund balance (1998) in millions	2.44	0.011	49.7	0	13,400	200,976

Results and Analysis

In what follows, we present our regression results for the three dependent variables: log of 5-year total revenue growth, log of 5-year fund balance growth, and log of 5-year unrestricted fund balance growth. Shown in Table 2 are summary regression results for the Carroll and Stater’s (2009) measure of revenue concentration (HHI_C-S); the Yan et al.’s (2009) absolute measure of revenue concentration (HHI_Yan); and the comprehensive revenue concentration index (HHI_Comp; see Tables 3A, 3B, and 3C in the Appendices for detailed regression results for each of these models).

Table 2.

Summary Key Regression Results—Determinants of Growth in Nonprofit Financial Capacity.

	(1) Log of 5-year total revenue growth		(2) Log of 5-year fund balance growth		(3) Log of 5-year unrestricted fund balance growth
Across all three models	Full sample	Excluding hospitals	Full sample	Excluding hospitals	Full sample	Excluding hospitals
HHI_C-S (1998)	0.24^c (0.03)	0.14^c (0.03)	–0.43^c (0.03)	–0.63^c (0.03)	–0.16^c (0.04)	–0.39^c (0.05)
HHI_Yan (1998)	0.27^c (0.03)	0.22^c (0.03)	–0.17^c (0.03)	–.034^c (0.03)	0.17^c (0.04)	0.03 (0.04)
HHI_Comp (1998)	0.51^c (0.02)	0.50^c (0.03)	0.17^c (0.03)	–0.00 (0.03)	0.37^c (0.04)	0.23^c (0.04)
In the HHIC-S model
Administrative expenses ratio (1998)	0.09^c (0.02)	0.10^c (0.03)	0.06^c (0.03)	0.09^c (0.03)	0.06^b (0.03)	0.08^c (0.03)
Fundraising expenses ratio (1998)	0.22^c (0.05)	0.20^c (0.07)	0.55^c (0.06)	0.52^c (0.07)	0.76^c (0.08)	0.80^c (0.10)
Compensation expense ratio (1998)	–0.06^b (0.03)	–0.04^c (0.02)	–0.03 (0.05)	–0.04 (0.05)	–0.10 (0.07)	–0.15^c (0.08)
In the HHIY_an model
Administrative expenses ratio (1998)	0.13^c (0.02)	0.15^c (0.03)	0.07^c (0.03)	0.10^c (0.03)	0.07^b (0.03)	0.09^c (0.03)
Fundraising expenses ratio (1998)	0.30^c (0.05)	0.23^c (0.08)	0.60^c (0.06)	0.56^c (0.07)	0.79^c (0.08)	0.83^c (0.10)
Compensation expense ratio (1998)	–0.05^b (0.02)	–0.04^b (0.02)	–0.01 (0.05)	–0.03 (0.05)	–0.09 (0.07)	–0.14^a (0.08)
In the HHI_Comp model
Administrative expenses ratio (1998)	0.16^c (0.02)	0.16^c (0.03)	0.08^c (0.03)	0.11^c (0.03)	0.10^c (0.03)	0.11^c (0.04)
Fundraising expenses ratio (1998)	0.37^c (0.05)	0.24^c (0.09)	0.61^c (0.06)	0.56^c (0.07)	0.83^c (0.08)	0.84^c (0.10)
Compensation expense ratio (1998)	–0.06^b (0.02)	–0.04^b (0.02)	–0.00 (0.05)	–0.03 (0.05)	–0.07 (0.07)	–0.13^a (0.08)

Note: Standard errors are in parentheses.

Significant at 10%.

Significant at 5%.

Significant at 1%.

Our first key finding is consistent with Fine and Foster (2007). Table 2 shows that the more concentrated a nonprofit’s revenue streams are, the higher its 5-year growth in total revenue, across all three models (24%, 27%, and 51% growths, respectively). These results are statistically significant at the 1% level, and this relationship also remains consistent and statistically significant when we exclude hospitals from the analysis (showing 14%, 22%, and 50% growths in total revenue over a 5-year period, respectively).

However, when financial capacity is measured in terms of restricted and unrestricted fund balances, the results tell a more nuanced story, across all three models (see Table 2 and Tables 3A, 3B, and 3C in the Appendices). The regressions show mixed results with respect to the retention of increased levels of restricted and unrestricted fund balances over time. However, at close observation, the levels of fund balances retained appear to increase as the comprehensiveness of the revenue concentration index increases. As the revenue concentration index becomes more concentrated (Table 3A to Table 3B to Table 3C) the results yield an increasingly positive change in the levels of restricted (–43%, –17%, and 17% changes) and unrestricted fund balances (–16%, 17%, and 37% changes).

The second key finding in this research is that whereas charity watchdogs recommend expending less resources on administrative support and fundraising as an indication of organizational legitimacy, our results show a positive and statistically significant association between growth in nonprofit financial capacity (whether measures as total revenue or restricted or unrestricted fund balances) and administrative support and fundraising expenses. Spending more on administrative support is associated with an expected 13% growth in total revenue over a 5-year period (15% when we exclude hospitals) and an expected 7% growth in both restricted and unrestricted net assets over the 5-year period.

Even in the face of alleged gross underreporting of fundraising expenses among some nonprofits (Hager, 2003; Hager, Rooney, & Pollak, 2002), our results show that spending more on fundraising is associated with even larger dividends for nonprofits’ financial capacity. This result is consistent with prior research on the impact fundraising has on increasing donations (see Sloan, 2009). The coefficients ranged from an expected 20% to 84% growth in financial capacity (statistically significant at the 1% level), with higher dividends for unrestricted fund balances.

Although high executive salaries have been regarded as indicative of investments in professional and highly trained personnel—an investment that could yield positive dividends for a nonprofit organization (Yan, Denison, & Butler, 2009), our findings suggest otherwise when it comes to building one’s financial capacity. Although the magnitude of the change is low, these results suggest that high compensation ratios actually limit an organization’s potential for financial capacity growth. Spending more on executive compensation reduced nonprofits’ total revenue growth by approximately 4% to 6% and unrestricted net assets by 15%, 14%, and 13%, respectively (when we exclude hospitals). These results are also statistically significant.

Whereas these results suggest that revenue concentration can be expected to increase nonprofits’ financial capacity, our results also indicate that increasingly becoming more concentrated over time may be unwise. For example, the change in the revenue concentration index between 1998 and 2003 was negatively associated with financial growth, and this remained consistent and statistically significant at the 1% level across the first two models. As shown in Table 3A and Table 3B, as an organization’s revenue streams became more concentrated over time (1998-2003), we observe declines in total revenues, total net assets, and unrestricted net assets over the 5-year period. This suggests that revenue concentration is more effective at generating financial growth when deployed as a one-time strategy.

However, like the previously discussed results pertaining to the revenue concentration measure, the change in the most comprehensive revenue concentration measure model (see Table 3C) shows a positive association with revenue growth (24%). In addition, the change in revenue concentration is associated with a smaller cut to the growth in the total net assets. Overall, the findings on revenue concentration suggest that the more comprehensive the measure of revenue concentration, the relatively more positive the association between revenue concentration and capacity growth. This calls for further inquiry into the measurement and sensitivity of revenue concentration indices.

Finally, recall that this analysis is limited to a 5-year growth rate due to data constraints. Although many nonprofits might consider 5 years as long term in their planning, some nonprofits might have a longer- (or shorter-) term horizon. To assess whether our results hold over different time frames, we also extracted the NCCS core data for the years 1998 to 2008. The limitations in the core data however hampered this sensitivity test in a number of ways. First, we were limited to one measure of revenue concentration—the Carroll and Stater (2009) measure (HHI_C-S). Second, we could not control for administrative expenses, and finally, we could not assess the growth in unrestricted fund balances.

With these caveats in mind, in running robust regressions (available upon request), our results remained qualitatively similar (in terms of direction and statistical significance) to those reported in Table 3A for our revenue concentration measure. The results also remained similar when we consider the 5-year growth period from 2003 to 2008. And finally, replicating these regressions over a 2-year period (2001 to 2003), utilizing the digitized data, also yielded qualitatively similar results to those reported in Table 2.

Discussion and Conclusions

The nonprofit literature exhibits overwhelming endorsement of revenue diversification as a key strategy for achieving financial stability and reducing a nonprofit’s vulnerability to financial shocks (e.g., Chang & Tuckman, 1994; Frumklin & Keating, 2002; Greenlee & Bukovnsky, 1998; Greenlee & Trussel, 2000; Greenlee & Tuckman, 2006; Tuckman & Chang, 1991). However, shifting the focus to financial capacity building, this research provides robust empirical evidence in support of the hypothesis (see Faulk, 2010; Foster & Fine, 2007) that the inverse of revenue diversification—revenue concentration—has some utility in advancing an organizations’ financial capacity, apart from minimizing administrative burdens associated with revenue diversification (Frumkin & Keating, 2002).

Overall, there are four noteworthy observations across all three of our models. First, revenue concentration is positively associated with a growth in nonprofits’ financial capacity, particularly when capacity is measured as total revenues. Conditioned on the number of funding streams measured, certain caveats apply. For instance, one key pattern that stands out is that the number of funding streams an organization has, and therefore included in the measurement of the revenue concentration indices, appears to influence the degree to which this variable effectively contributes toward growing one’s restricted and unrestricted net assets over time. Specifically, the more comprehensive the revenue concentration index, the larger the size of the coefficients gets. This pattern raises questions about the sensitivity of the revenue concentration indices and their measurement implications, on the direction and magnitude of their effects on the dependent variable as well as other variables. Overall, the more comprehensive the revenue concentration index is, the more likely it is to positively influence financial capacity growth across all measures. Such a finding warrants further investigation.

Second, when financial capacity is measured in terms of net assets, we find mixed results. A plausible explanation for the mixed effects of revenue concentration on the growth of nonprofits’ restricted and unrestricted fund balances may have to do with the meaning and symbolic value of retained earnings, as types of rainy-day funds. The public administration and public budgeting literature has tended to view fund balances as a type of rainy-day fund (e.g., Douglas & Gaddie, 1996; Knight & Levinson, 1999; Pollock & Suyderhoud, 1986; Wagner & Elder, 2007). Viewed in this light, it makes sense that revenue concentration would negatively affect nonprofits’ net fund balances. As is consistent with prior research (e.g., Carroll & Stater, 2009; Jegers, 1997; Kingma, 1993; White, 1983), being less concentrated increases organizational financial stability.

Third, though not surprising with fundraising, our results are divergent from the prevalent debate on achieving organizational efficiency by minimizing expenditures on administration and executive compensation. Whereas past research (e.g., Tuckman & Chang, 1991) hailed the availability of the option to shed off administrative support as a sign of financial health, our results suggest that nonprofit organizations may not be able to grow their financial capacity without making some investment in administrative capacity.

And finally, others contend that in order to attract and retain the best and the brightest, nonprofits need to offer competitive executive salaries (e.g., Pallotta, 2008) when trying to build their financial capacity. Our findings show that nonprofits can certainly do without making huge resource allocations toward executive salaries. Large expenditures or investments toward this line item negatively affect nonprofits’ potential for financial growth, especially if organizations want to enlarge their total revenues and, to some degree, grow their unrestricted net assets over time. This result is not surprising since it has been documented that organizations with a lot of slack or unrestricted funding tend to pay their executive staff more (Bowman, Keating, & Hager, 2006). Naturally, this can hinder an organization’s ability to retain more net assets over time. However, this result in no way implies that professional executives do not add value to their organizations in other qualitative ways, such as strengthening relationships with communities, articulating the strategic vision in meaningful and practical ways, and advancing their organizations’ missions, among other innovative contributions. And to Pallotta’s point, the challenge remains of devising compensation levels that enable nonprofits to attract and retain talented leaders.

Overall, for those nonprofits trying to build their financial capacity, directors and managers should find these results informative as they consider their resource allocations decisions. It is also equally important that nonprofit directors and managers recognize the two-dimensional nature of financial health—as distinguished between financial capacity (having more resources to further the organizational mission) and financial stability (being able to weather any fluctuations in revenue streams in order to continue to exist). Such an understanding will enlighten their judgment about which revenue-generating strategies are appropriate for which of these purposes.

Also equally important is the consideration that a nonprofit’s revenue-generating strategy, even for financial growth purposes, may be influenced by other contextual factors such as organizational mission and services. The application of Young’s (2006) benefits-based theory of nonprofit finance by Fischer et al. (2010) alerts us to the fact that a nonprofit organization’s revenue mix can be fueled in part by its mission or the nature of the services it provides, thus minimizing its desire to concentrate its revenue along a single funding stream.

Inferring from Young’s (2006) benefits-based theory, therefore, it can be concluded that an organization’s ‘natural’ revenue mix—the revenue streams that emanate as a result of the nature of the benefits conferred—and the revenue concentration strategy addressed here do not necessarily have to be at odds. Nonprofits’ understanding of the benefits their services confer, and hence, why they are able to attract particular funding sources, may serve as an important precursor. That is, having achieved a revenue mix that is congruent with its mission and the services it provides, a nonprofit can then adopt a revenue concentration strategy from this mix, for financial capacity–building purposes.

However, if the desire is to enhance one’s financial stability, then a revenue diversification strategy may be implemented instead. In some respects, this ties in with Foster and Fine’s (2007) second hypothesis, first concentrating one’s resources (e.g., relying on government funding) and then diversifying within the limited funding sources (e.g., by obtaining funding from different levels of government), a strategy that is predicted to reduce the transactions costs associated with managing and accounting for multiple funding sources. With more nuanced data, future research should investigate into this type of “within-source” diversification.

Footnotes

Appendix

Table 3C.

Robust Regression Results—Determinants of Growth in Nonprofit Financial Capacity.

	(1)	(2)	(3)
	Log of 5-year total revenue growth	Log of 5-year fund balance growth	Log of 5-year unrestricted fund balance growth
Revenue concentration (1998; HHI_Comp)	0.51^c	0.17^c	0.37^c
Revenue concentration (1998; HHI_Comp)	(0.02)	(0.03)	(0.04)
Change in revenue concentration_{_Comp} (1998-2003)	0.24^c	–0.40^c	0.03
Change in revenue concentration_{_Comp} (1998-2003)	(0.02)	(0.03)	(0.04)
Log of total revenue (1998)	–0.31^c	—	—
	(0.00)
Log of fund balance (1998)	—	–0.45^c	—
		(0.00)
Log on unrestricted fund balance (1998)	—	—	–0.41^c
Log on unrestricted fund balance (1998)			(0.00)
Administrative expenses ratio (1998)	0.16^c	0.08^c	0.10^c
Administrative expenses ratio (1998)	(0.02)	(0.03)	(0.03)
Fundraising expenses ratio (1998)	0.37^c	0.61^c	0.83^c
	(0.05)	(0.06)	(0.08)
Compensation expense ratio (1998)	–0.06^b	–0.00	–0.07
Compensation expense ratio (1998)	(0.02)	(0.05)	(0.07)
State	Yes	Yes	Yes
Sector	Yes	Yes	Yes
Observations	105,276	107,470	49,590
R ²	12%	29%	25%

Note: Standard errors are in parentheses.

Significant at 10%.

Significant at 5%.

Significant at 1%.

Acknowledgements

We gratefully acknowledge the feedback received at the 2011 ARNOVA conference, as well as comments from Dr. Deborah A. Carroll (UGA), and Dr. Robert Purtell (University at Albany). In addition, we acknowledge the National Center for Charitable Statistics, which provided the data used for this project.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Grace L. Chikoto is an assistant professor at the University of Wisconsin–Milwaukee. Her research specializes in the implications of funding on nonprofit organizations, state–INGO relations, and nonprofit disaster management.

Daniel Gordon Neely is an assistant professor at the University of Wisconsin–Milwaukee. His research specializes in the role of financial information in governmental and nonprofit organizations.

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