Capital Investment Analytical Techniques in Higher Education: A Factor in the Cost Growth?
Universities' investments in fixed assets, primarily bricks and mortar, could contribute to both increased debt burdens and cash flow pressures if the investment decisions were made incorrectly. For reasons discussed below, it is suspected that universities might be evaluating their investment alternatives using less than rigorous financial analysis. This paper is organized in four parts: (i) exposition of benefits, and predominance within the for-profit financial community of the evaluation of investment alternatives using a present value analysis based on the weighted average cost of capital (WACC), (ii) evidence as to the types of investment analysis likely to be conducted by not-for-profit institutions in general, (iii) results of a survey of senior financial officers of representative U.S. public and private four-year colleges and universities, and (iv) recommendations as to how WACC analysis should be implemented within the context of higher education.
CAPITAL INVESTMENT ANALYSIS FOR FOR-PROFIT ORGANIZATIONS
The capital budgeting process for corporations is well established with net present value modeling (NPV) being the accepted approach presented in MBA level finance textbooks (Brealey et al., 2011; Brigham and Ehrhardt, 2014; Ross et al., 2013). A 2013 survey of 434 senior finance practitioners, across various industries and organization structure, show that 85% use discounted cash flow techniques incorporating an institution's cost of capital to evaluate projects and investments, where the cost of capital reflects a combination of the entity's cost of equity and debt, and that 90% of publicly traded company respondents use this technique (Association for Financial Professionals, 2013). Using this approach, the discounted present value of all future cash flows are compared to the initial investment amount, with net positive results indicating that a project should be accepted.
The choice of discount rate is crucial for the NPV analysis, and this rate should reflect the risk of the investment alternative. The appropriate discount rate is the weighted average cost of capital for the firm (WACC) derived from the market-weighted average of the firm's after-tax debt and equity costs.
The cost of debt for a firm generally is observable by examining the after-tax cost of the trading level of a firm's outstanding borrowings or the quoted rate for new borrowing. The most common approach used to calculate the firm's cost of equity is the capital asset pricing model (CAPM), which frames the cost as a combination of a risk free rate and a risk premium. Since equity risks are always greater than debt risks, the WACC is always greater than the firm's cost of debt.
It is important to note that the discount rate is independent of the actual financing source for a specific project. Therefore, even if a particular project is financed solely with bank borrowing, the discount rate needs to reflect the average cost of financing for the entire firm. Otherwise, projects financed with debt might be incorrectly accepted while projects financed with internal funds, a form of equity, or new equity issuance might be incorrectly rejected. However, if the project financing is going to materially impact the entity's capital structure, then the WACC should be adjusted accordingly.
Since the discount rate should reflect the risk of the project, the rate needs to be adjusted if the risk of the project is different than the average risk of the firm. Guidance in making the risk adjustment can come from looking at the WACC of firms representative of the risk level of the considered project, after adjusting for any capital structure differences.
The internal rate of return (IRR) is another capital budgeting method and it is calculated by finding the discount rate that sets the NPV of the cash flows to zero. The attractiveness of this measure is the ability to easily compare the IRR to the firm's WACC, or hurdle rate. However, as discussed in the cited textbooks, the IRR has a number of shortcomings that reduces the attractiveness of this measure as a decision tool. These shortcomings include lack of scale, assumptions on reinvestment, and problems with changing cash flow signs.
The payback period is another capital budgeting method that calculates the number of years required to recoup the initial investment amount. This approach is considered inferior as it does not take into account the time value of money nor the cash flows beyond the breakeven period.
CAPITAL INVESTMENT ANALYSIS FOR NON-PROFITS
There are recognized difficulties in reconciling the decision-making benefits of financial benchmarks and methodology with the differing goals and mission of nonprofits relative to for-profit organizations (Bhayat et al., 2015; Brooks, 2005; Deily et al., 2000; University of Michigan, 2012; Steinberg, 2006). There are specific challenges in budgeting and cost analysis for non-profits (Brinkman and Morgan, 2010; Harris and Goldrick-Rab, 2010; Swift, 2012; Vonasek, 2011).
For capital budgeting, the primary distinction between for-profit and non-profit institutions is that investors own the former and the shareholder equity has a value based on the difference between the value of the assets and liabilities that can be determined by market factors. A non-profit is formed to achieve a purpose or mission, and the difference between the value of the assets and liabilities, or net assets, is retained and used to support such mission. This raises the question of whether non-profits should use a WACC for project analysis and, if so, what is the appropriate cost of net assets. Of the surveyed MBA textbooks, only Brigham and Ehrhardt (2014) address the topic with a web chapter on non-profit finance that concludes that the proper cost of net assets is the cost of equity of a comparable for-profit company.
Prior research has found that non-profits should recognize that the net assets have a cost that should be reflected in the cost of capital (Copeland and Jacobs, 1981; Michalski, 2011; Wheeler and Smith, 1988), and that the cost of net assets for non-profits may be as high as a comparable for-profit organization (Duggal and Budden, 2010; Heshmat, 1992; Reinhardt, 2000). However, a few have suggested that the cost of net assets may be as low as zero arguing that donors require no financial return (Jegers and Verschueren, 2006), or no higher than the cost of debt (Wedig et al., 1989).
Public institutions comprise a sub-set of non-profits. Conceptually, the process for choosing a discount rate for project analysis should follow that of a private non-profit, with a rate chosen similar to that of a for-profit enterprise, adjusted for tax differences. However, there is considerable disagreement on the choice of the discount rate for the use of government project analysis, particularly when evaluating long-term projects. This rate, often referred to as the social or societal discount rate, has been argued to be anywhere from a comparable for-profit rate at the high end, down to a rate well below the government borrowing rate for long-term analysis that span multiple generations (e.g., climate change analysis) (Quirk and Terasawa, 1987; Warusawitharana, 2014; Zerbe et al., 2002; Zhuang et al., 2007).
The finance curriculum in general MBA programs emphasizes the teaching of quantitative capital investment analytical techniques and the benefits of using the WACC. In order to determine whether future finance professionals in the non-profit sector were receiving similar training, a review was conducted of the available online syllabi of the financial management courses for 17 of the first 21 of the US News and World Reports 2013 list of the top non-profit management programs (generally MPA degrees). The textbooks used were: Finkler et al. (2013) (eight courses); Zietlow et al., (2007) (four courses); Bowman (2011) (four courses); and Shim and Siegel (1997) (two courses). Some textbooks were used in a single course: Young (2007); Blazek (1996); Bryce (1987); Krug and Weinberg (2004); McLaughlin (2009); Paulsen and Smart (2001); Weikart et al. (2012); and Young (2007).
Most of these textbooks advocate the use of present value analysis, but the majority suggest using the cost of borrowing as the discount rate (Finklereia/., 2013; McLaughlin 2009; Shim and Siegel, 1997; Weikart et al., 2012; Young, 2007; Zietlow et al., 2007). Some textbooks do not discuss present value concepts or are silent on the methodology for finding a discount rate (Blazek, 1996; Bowman, 2011; Bryce, 1987; Krug and Weinberg, 2004; Paulson and Smart, 2001). Finally, only a few texts discuss matching the discount rate with the project risk, and none offer a methodology (Bryce, 1987; Finkler et al., 2013, Shim and Siegel, 1997). In conclusion, it appears that most master's students oriented towards careers in the non-profit sector arrive without the same finance knowledge and skills as students oriented towards careers in the for-profit sector.
A simple illustration shows how improperly evaluating projects can lead to flawed economic decisions and harm to an institution. Assume a non-profit institution has a specific $700,000 perpetual expense. Also, assume the institution earns 7% on its endowment and that return is used as a proxy for its WACC. Besides tuition, the school has several alternatives to fund the expense: (a) a donor could make annual grants of $700,000; (b) a donor could make a grant of $10,000,000 to the endowment, and the endowment will generate $700,000 in annual income; or (c) the school could use the $10,000,000 grant to purchase a perpetual asset that eliminates the $700,000 expense (e.g., a machine reducing a labor cost).
All three of these choices are economically equivalent and eliminate the $700,000 expense. But, if the school uses a discount rate below 7%, then it will accept investments that cost more than $10,000,000. In this example, a discount rate of 4% would result in the school accepting a $17,500,000 purchase to eliminate the $700,000 expense (i.e., $700,000/0.04 = $17,500,000). The result is that economic value is destroyed as $17,500,000 is being deployed when only $10,000,000 is justified.
Some may argue that an acceptable solution would be to borrow at a rate of 4% to fund the purchase and, therefore, a $17,500,000 purchase is acceptable (i.e., $17,500,000 x 4% = $700,000, exactly the offset of the $700,000 expense). But, this argument requires that an economic actor can borrow 100% of its funding needs now and forever without regard to any underlying net reserves or equity, clearly an unsustainable assumption. It is the equivalent of an individual being able to infinitely borrow 100% of his investment needs.
Equally important is the failure to attempt to use proper financial analysis. For example, an institution may decide to provide free room and board for commuter students and will construct housing for such purpose. Since there are no cash flows associated with the project it might be argued that there is no role for financial analysis. But, by putting a value on the granted yearly room and board, an analysis of the investment can be completed and evaluated against alternatives such as providing vouchers for a nearby hotel or other forms of off-campus housing. Even if the objective of the institution is to bring more commuter students on campus, a proper analysis will better frame the cost of such a program and allow it to be ranked against other potential mission programs.
ANALYTICAL TECHNIQUES USED BY NON-PROFIT ENTITIES
Prior research on financial techniques used by various types of non-profit entities indicated that few use more sophisticated techniques. Zietlow (2010) reported that 36% of chief financial officers of faith-based organizations he surveyed said their primary financial objective is simply to break even financially. In his earlier survey of 47 faith-based organizations on capital budgeting techniques he found 45% used the payback method while only 11% used NPV or IRR (Zietlow, 1989). White (1997) surveyed 43 agricultural co-operatives and found that over 50% sometimes or always utilized NPV or IRR. Kamath and Elmer (1989) surveyed 120 hospitals, primarily non-profit, and found that 34% primarily used NPV analysis, with only 14 out of 44 respondents accounting for risk by adjusting the discount rate. Mukherjee etal. (2016) synthesized 11 published surveys of financial officers of healthcare organizations and found that more recent surveys indicate a growing percentage of respondents use discounted cash flow analysis, though many decision-makers still use payback period. Kee and Robbins (1991) surveyed 169 municipal and county administers and found that NPV or IRR was cited as the primary technique by 4% and the secondary technique by 16%.
ANALYTICAL TECHNIQUES CURRENTLY USED IN HIGHER EDUCATION
In order to assess the techniques currently used by finance professionals in higher education, a sampling frame was created composed of U.S. four-year colleges and universities by systematically selecting institutions from the Carnegie Classification of Institutions of Higher Education 2010 listing. The frame was constructed to include similar numbers of private (n = 413) and public (n = 372) institutions that varied with respect to size, as measured by enrollment, and the extent to which they were residential and non-residential. For each selected institution, the institution's website was accessed to identify an individual with a title indicating a senior officer with responsibility for finance or investment (e.g., chief financial officer, vice president finance) and then obtained their physical address to which was mailed a pre-advice indicating that a survey was being conducted to "improve the knowledge of how academic institutions, public, private and for-profit, use various financial analytical tools in making capital budgeting decisions" and that they would receive an email with an invitation and link to an online survey. The email was sent shortly afterward.
Although 130 individuals logged onto the survey, useable information was provided for only 69 individuals representing a 9% response rate. Fifty-four individuals indicated the type of institution for which they worked: 23 public and 31 private. Institutions varied with respect to enrollment (28% had fewer than 3,000 students, 50% had between 3,000 and 19,999, 22% had more than 20,000), asset size (24% were less than $100 million, 57% were $100 to $999 million, 19% were greater than $1 billion), and residential status (26% were primarily non-residential, 34% were primarily residential, 40% were highly residential).
Participants were asked to indicate how useful would each of payback period, NPV, and IRR be in their analyzing a proposal to construct a new classroom building with a six-point Likert-type response options (1 = Not at all useful, 2 = Somewhat useful, 3 = Fairly useful, 4 = Useful, 5 = Moderately useful, 6 = Very usefid). Participants were then asked for details on methods they said they would use. Participants who used payback period were asked about their breakeven period. Participants who used NPV or IRR were asked details about how they determined their hurdles rates (such as whether they used a debt rate and, if so, which debt rate, and whether they used a combination of debt and net reserves/equity, etc.).
Individuals who did not use NPV or IRR were asked why not with four response options: difficulty projecting cash flows, difficulty determining the discount rate, difficulty incorporating qualitative aspects, other (with a request to specify).
Participants were asked if there would be differences in their approach if they were evaluating an investment which would either generate a revenue stream or expense reduction associated with it (such as dormitory, parking garage, or cogeneration plant). Participants who responded affirmatively were asked to rate the usefulness of payback period, NPV, and IRR for evaluating that type of investment using the above six-point Likert-response scale and the option of an open-ended explanation of how and why the type of investment would influence their evaluation approach.
The survey then stated "many finance professionals who work for publicly-traded corporations analyze capital projects using an NPV with a hurdle rate determined by their weighted cost of debt and net assets (or net reserves, shareholder's equity, etc.). This rate is commonly referred to as the weighted average cost of capital ("WACC") and asked participants to indicate how useful they thought such a technique would be for six types of institutions: publicly-traded for-profit (non-educational), privately owned for profit (non-educational), publicly-traded for-profit college, privately-owned for-profit college, private not-for-profit college, public college.
Participants who thought WACC would be less appropriate for their institutions were asked to indicate the reasons: difficulty determining or estimating the debt rate, difficulty determining or estimating the net assets rate, difficulty determining the appropriate weighting between debt and net assets, difficulty projecting cash flows, difficulty incorporating qualitative aspects, other (with a request to specify).
Participants were asked for a variety of institutional demographics (i.e., type of institution, enrollment and net assets, proportion of residential students, endowment size and earning, rates, rating and conditions of debt issuance (if any), and individual demographics (title, academic and professional credentials, years of experience).
RESULTS AND DISCUSSION
The means of all participants with respect to the three different analytical techniques were similar and showed that payback period, net present value, and internal rate of return were all considered to be useful: payback period, n = 69, m = 3.91, sd = 1.89; net present value, n = 68, m = 3.69, sd = 1.93; internal rate of return, n = 68, m = 3.63, sd = 1.88. T-tests were performed to compare the ratings of participants who worked for public institutions and those who worked for privates (a breakdown of frequency of responses and statistics are shown in Table 1). In addition to establishing that the differences were statistically significant, the standardized mean difference (d) were also calculated as a measure of the magnitude of the difference. Those ds should be evaluated against the benchmarks commonly used in the social sciences: small, 0.2; medium, 0.50, and large, 0.80. There were statistically significant differences as private participants reported the more rigorous techniques of net present value and internal rate of return as being more useful. The greater use of NPV and IRR by privates could reflect differences in governance between public and private institutions.
There were no significant differences between privates and publics with respect to usefulness of payback period. However, there were marked differences with respect to payback period as average reported payback period for publics was 17 years versus 9 years for privates. The continued use of the payback methodology is worrisome as an institution using a payback benchmark of ten years likely is at risk of making a poor economic decision. For example, ten years of equal cash flows summing to an initial investment amount has an economic value of only 70% of the initial investment amount using a discount rate of 7%, the average expected return for an endowment. It would take 18 years of these equal payments to produce a positive PV. On the other hand, institutions who use a shorter payback period may be more likely to reject investment options that should be made.
As shown in Table 2, both one-third of publics and privates cited difficulty in incorporating qualitative aspects as reasons for not using NPV or IRR techniques. But, 17 percent of publics versus only 3 percent of privates cited difficulty in determining the discount rate as a reason not to use these techniques.
Many participants rated all three analytical techniques as more useful in the evaluation of capital expenditures that had direct associated revenue enhancement or expense reduction benefits, perhaps reflecting the unwillingness/inability to quantify the benefits of non-direct revenue projects. For participants who indicated they would analyze such projects differently the mean usefulness of each technique was calculated for the revenue/expense linked project, tested for statistical significance with the mean ratings for the general education project, and calculated the d: payback period, n = 47, m = 4.40, sd = 1.62 vs. m = 3.62, 1.84, t = 2.77, p < 0.01, d = 0.45; net present value, n = 43, m = 4.00, sd = 1.62 vs. m = 3.60, sd = 1.90, t = 1.83, p = 0.07, d = 0.23; and internal rate of return, n = 45, m = 4.07, sd = 1.64 vs. m = 3.62, sd = 1.89, t = 1.99, p = 0.05, d = 0.25.
The open-ended comments provide greater insights into the concerns of these finance professionals.
On decision-making, respondents generally express an understanding of the value of financial analysis but believe its importance is secondary to the use of qualitative analysis. Part of the reason is the difficulty in securing the information required for a financial analysis and part is the belief that non-profit's mission outweighs financial considerations.
"Would love for our decision-making to be driven by financial returns. But mission trumps return (rightly so), and the endowment helps cover shortfalls in payback."
"We make capital investments that make "business sense," with the realization that our business is the development and dissemination of knowledge, which cannot be reduced to a simple metric such as return on net assets or shareholder value."
"The biggest challenge is to secure broad buy-in to such analytical approaches. Many times investment decisions are made to show the students a "wow factor" each September."
"Competitiveness of facilities is very important in recruiting students; many projects required by code; even the best projects probably would not be approved in a for-profit situation."
"This is an emerging issue in higher education finance. Board members have an expectation that CFOs are using these tools to assess the viability of projects, however in higher education other factors often drive the project such as the strategic plan, emerging fields/disciplines, donor opportunities, and even politics. These more qualitative factors as well as other factors that make a pure financial analysis extremely difficult, usually lead the financial officers to ignore the financial computations. For example, how do you weigh the cost/benefit of a new research facility, when the facility may generate breaking new discoveries that reap significant financial benefits well into the future, or may not generate financial returns, but instead provides social benefits to humankind."
On using NPV or IRR analytical techniques for evaluating a new classroom building, respondents again point to both a lack of the information required to do such analysis, as well as the perspective that these techniques, or any financial techniques, are not relevant in deciding how to further the institution's mission:
"If we need a new classroom building, we base the decision to construct the building on the need, not the financing scheme."
"Not a relevant concept at a public institution for the vast majority of projects. The financial analysis for construction projects focuses on debt coverage for the duration of the debt."
"Decisions are based on whether we need them."
"Often the decisions to fund a facility are less about financial calculations such as WACC and more about donors, program need, strategic plan, politics, etc."
"Need to understand it better."
"Irrelevant if you need the building to accommodate growth."
"We would be much more likely to apply these techniques to projects for which the revenue stream (or cost savings) are clearer. An example would be a dormitory, for which the financial benefit (from adding bed revenue) is easier to see than adding classrooms."
While relatively few participants attempted to use WACC in their analysis, both public and private recognized its usefulness for organizations outside of higher education as both private and public participants reported the mean usefulness of WACC analysis for private non-educational organizations as 4.5.
A greater understanding of the type of analysis performed can be obtained by examining the detailed responses as to the discount or hurdle rates. As shown in Table 3, there were marked differences in the discount or hurdle rates used by those private and public institutions which said they performed NPV or IRR. None of the publics reported they attempted to apply a WACC analysis versus almost half of the privates. Most revealing, three-quarters of the publics and almost half of the privates used a debt rate. The return on endowment is considered to correspond to an estimate of cost of capital and note that 14% of the publics use that. Fourteen percent of publics use a cost of net assets, which should correspond to a cost of equity, but likely is estimated by many non-profits as having a cost no higher than a cost of debt.
Participants were asked to indicate the actual hurdle rate they would use. As would be expected given the above, the mean hurdle rate of public participants was 4.2% with a range of 3%-6% and a standard deviation of 1.0%, whereas the mean for private participants was 4.8% with a range of 3%-7.5% and a standard deviation of 1.3%. To put these numbers in perspective, a reasonable WACC for an S&P 500 company during the period in which the data was collected would have been around 7%, as equity returns would have been on the order of 10% with debt rates on the order of 3-4%, depending on their tax status, and the average equity/debt breakdown is roughly two to one (Bloomberg, 2016; Damodaran, 2016; Goldberg, 2015). Further, a rate of approximately 7% is consistent with projected endowment returns as endowments typically target a 60/40 mix of equities and bonds. Since for many institutions, the endowment represents a significant portion of the institution's assets, it is reasonable to proxy the WACC with the expected endowment return.
It is thus understandable that the average hurdle rate is closer to a debt rate than a WACC, reflecting, at least in part, a low assessment of the cost of equity/reserves. As expected, respondents that use the cost of debt reported a lower hurdle rate, 4.3%, than those that use the WACC or return on endowment, 4.9%. It seems, then, that even the private institutions, who are more likely to attempt to take into account a cost of equity concept are still likely to have a lower hurdle rate than larger for-profit companies and would accordingly be more likely to approve capital investment proposals that, arguably, should be rejected.
The average expected endowment rate was 7.2%, well above the reported project hurdle rate but, as shown above, consistent with a standard endowment of 60% stocks and 40% bonds. One-third of respondents have expected rates of 8% or higher increasing the likelihood that endowment revenue may fall below target. Combined with the low average hurdle rate of 4.7%, many projects will not produce a return expected for the endowment, resulting in a diminishment of institutional economic value. For example, a 20-year annuity project that meets a 4.7% hurdle has an upfront economic loss of 17% when evaluated at the more appropriate 7% discount rate.
Any study has its limitations and the low response rate needs to be addressed. The number of participants, of course, reduces statistical power and, of course, raises the question of whether the individuals who decided to participate were representative of those who did not. Given the differences between public and private participants with respect to enrollment, assets, and residentialness, it could not be determined whether such variables related to analytical approach after controlling for institutional type. More crucial, it is expected that individuals who decided to provide information likely differed from individuals who did not log onto the online survey or chose not to participate after they viewed the first series of items asking about their use of quantitative analytical techniques. It is possible that finance professionals, who knew the types of quantitative analytical techniques that are available to evaluate capital investment proposals might not wish to participate in a study where they thought they would be asked to indicate their analytical approach. As a matter of self-preservation, financial professionals who did not use analytical techniques might have been less likely to participate than those who did. In other words, the limited sample indicates relatively few institutions attempt to use more rigorous analytical techniques to their capital investment analysis, the proportion in the general population may be even lower.
Information provided by the respondents suggest that capital investment decisions made in higher education are not subjected to the type of analytical techniques commonly used in the for-profit sector. Indeed, most of the participants in this study acknowledged the usefulness of weighted average cost of capital and other analytical techniques for such organizations. The information provided by participants suggests that decision-makers in higher education may approve capital investment proposals that would be rejected by the decision-makers in publicly-traded for-profit organizations. The challenges which they report in applying rigorous analytical techniques are real. Certainly, it is valid to say that some investments, such as new science building or performing arts center are simply required to stay in business or "wow" prospective students, and certainly it may be difficult to estimate the incremental revenue associated with such projects. Such circumstances are often confronted by for-profit organizations faced by decisions with respect to construction of new corporate headquarters or a new distribution center which can be evaluated only as a small part of the large network. While it is possible that an institution "must" replace an outdated science building, it is still left to decide whether it should spend $50 or $100 million on the new facility.
More important, non-profits face unique circumstances with donors that may have specific preferences as to what he or she wants to support, with the result that negative NPV "Wow" projects may attract funding that may not be found for financially acceptable projects. Donors contribute to institutions for a variety of reasons, but financial return is not one of them. Therefore, it is up to the institution to ensure proper financial management of the funds, and to understand that there is a cost for investing in projects that do not earn what can at least be earned by placing the funds in the endowment, which is a proxy for a school's cost of capital. Before accepting such donations and embarking on these negative projects, proper analysis would provide the blueprint for attempting to convince donors to fund more worthwhile projects or at least to reconstitute the projects into ones that are more financially viable.
Failing to address these challenges may tend to contribute to the cost and indebtedness problems of higher education. Simply put, using less rigorous analytical techniques than NPV analysis and not properly accounting for an institution's weighted average cost of capital would tend to lead to over-investment in capital assets as well as a misallocation of resources within a capital investment budget, potentially robbing the institution of the means to continue to fund its mission. Greater emphasis on these techniques in public administration programs appears warranted.
Association for Financial Professionals. 2013. "2013 AFP Estimating and Applying Cost of Capital, Report of Survey Results." www.AFPonline.org, October 2013.
Bhayat, I., I. Manuguerra, and C. Baldock. 2015. "A Decision Support Model and Tool to Assist Financial Decision-Making in Universities." Journal of Higher Education Policy and Management 3: 69-82.
Blazek, J. 1996. Financial Planning for Nonprofit Organizations. Hoboken, NJ: Wiley.
Bloomberg, L. P. 2016. Debt Rates for Corporations. Retrieved Jan. 6, 2016 from Bloomberg database.
Bowman, W. 2011. Finance Fundamentals for Nonprofits. Hoboken, NJ: Wiley.
Brealey, R. A., S. C. Meyers, and F. Allen. 2011. Principles of Corporate Finance. New York, NY: McGraw-Hill.
Brigham, E. F., and M. C. Ehrhardt. 2014. Financial Management: Theory and Practice. Mason, OH: Cengage Learning.
Brinkman, P. T., and A. W. Morgan. 2010. "Financial Planning--Strategies and Lessons Learned." Society for College and University Planning (SCUP) April-June: 5-14.
Brooks, A. 2005. "What do Nonprofit Organizations Seek? And Why Should Policymakers Care?" Journal of Policy Analysis and Management 24: 543-558.
Bryce, H. J. 1987. Financial & Strategic Management for Nonprofit Organizations. Englewood Cliffs, NJ: Prentice-Hall.
Copeland, R., and P. Jacobs. 1981. "Cost of Capital, Target Rate of Return, and Investment Decision Making." Health Services Research 16: 335-341.
Craig, J. D., and S. R. Raisanen. 2014. "Institutional Determinants of American Undergraduate Student Debt." Journal of Higher Education Policy and Management 36: 661-673.
Damodaran, A. 2016. Damodaran Online, http://pages.stern.nyu.edu/~adamodar/ New_Home_Page/datacurrent.html. January 2016
Deily, M., N. McKay, and F. Dorner. 2000. "Exit and Inefficiency: The Effects of Ownership Type." The Journal of Human Resources 35: 734-747.
Denneen, J., and T. Dretler. 2012. The Financially Sustainable University. Sterling Partners and Bain & Company.
Duggal, R., and M. C. Budden. 2010. "Assuring Not-for-Profit Hospital Competitiveness through Proper Accounting for the True Cost of Capital." Journal of Business & Economic Research 8: 1-6.
Finkler, S. A., R. M. Purtell, T. D. Calabrese, and D. L. Smith. 2013. Financial Management for Public, Health, and Not-for-Profit Organizations. New York, NY: Pearson.
Goldberg, R. S. 2015. "A Methodology for Computing and Comparing Implied Equity and Corporate-Debt Sharpe Ratios." Review of Quantitative Finance and Accounting 4: 733-754.
Harris, D. N., and S. Goldrick-Rab. 2010. "The Unproductivity of American Higher Education: from "Cost Disease" to Cost Effectiveness." Working Papers Series 2010023. University of Wisconsin-Madison.
Heshmat, S. 1992. "Estimating the Cost of Capital for Nonprofit Hospitals. "Journal of Health and Human Resources Administration 14: 465-473.
Jegers, M., and I. Verschueren. 2006. "On the Capital Structure of Non-Profit Organizations: An Empirical Study for Californian Organizations." Financial Accountability & Management 22: 309-329.
Kamath, R. R., and J. Elmer. 1989. "Capital Investment Decisions in Hospitals: Survey Results." Health Care Management Review 14: 45-56.
Kee, R., and W. Robbins. 1991. "Capital Budgeting in the Public Sector: A Comparative Analysis." Journal of Managerial Issues 3: 288-302
Krug, K., and C. B. Weinberg. 2004. "Mission, Money, and Merit: Strategic Decision Making by Nonprofit Managers." Nonprofit Management and leadership 14: 325-342.
Martin, A. 2012. "Building a Showcase Campus, Using an I.O.U." New York Times. New York, NY. December 13, 2012.
McLaughlin, T. A. 2009. Streetsmart Financial Basics for Nonprofit Managers. Hoboken, N f: Wiley.
Michalski, G. 2011. "Influence of the Post-Crisis Situation on Cost of Capital and Intrinsic Liquidity Value in Non-Profit Organizations." International Journal of Management & Social Sciences 1: 67-78,
Mitchell, M., and M. Leachman. 2015. "Years of Cuts Threaten to Put College Out of Reach for More Students." Center on Budget and Policy Priorities, Washington, DC. May 13, 2015. http://www.cbpp.org/sites/default/files/atoms/files/5-13-15sfp.pdf
Moody's Investor Services. 2013. "Moody's: 2013 Outlook for Entire US Higher Education Sector Changed to Negative." Global Credit Research 16 Jan 2013. New York, NY: Moody's Investor Service.
Mukherjee, T., N. Al Rahahleh, W. Lane, and J. Dunn. 2016. "The Capital Budgeting Process of Healthcare Organizations: A Review of Surveys." Journal of Healthcare Management 61: 58-77.
Paulsen, M. B., and J. C. Smart. 2001. The Finance of Higher Education: Theory, Research, Policy and Practice. Flemington, NJ: Agathon Press.
Quirk, J. P., and K. L. Terasawa. 1987. The Choice of Discount Rate Applicable to Government Resource Use. Rand Corporation.
Reinhardt, U. E. 2000. "The Economics of For-Profit and Not-for-Profit Hospitals." Health Affairs 19: 178-186.
Ross, S. A., R. W. Westerfield, and J. F. Jaffe. 2013. Corporate Finance. New York, NY: McGraw-Hill.
Shim, J. K., and J. G. Siegel. 1997. Financial Management for Nonprofits. New York, NY: McGraw-Hill.
Steinberg, R. 2006. The Nonprofit Sector. New Haven, CT: Yale University Press.
Swift, L. 2012. "Assessing the Financial Viability of Academic Programmes." Journal of Higher Education Policy and Management 34: 259-272.
University of Michigan. 2012. Cost Containment Efforts. Ann Arbor, MI: University of Minnesota Press.
US News and World Report. 2013. "Top 25 Schools for Nonprofit Management." US News and World Report.
Vonasek, J. 2011. "Implementing Responsibility Centre Budgeting." Journal of Higher Education Policy and Management 33: 497-508.
Warusawitharana, M. 2014. "The Social Discount Rate in Developing Countries FEDS Notes." Federal Reserve Bank, October.
Wedig, G. J., M. Hassan, and F. A. Sloan. 1989. "Hospital Investment Decisions and the Cost of Capital." The Journal of Business 62: 517-537.
Weikart, L. A., G. G. Chen, and E. Sermier. 2012. "Budgeting & Financial Management for Nonprofit Organizations." Thousand Oaks, CA: CQ Press.
Wheeler, J. R. C., and D. G. Smith. 1988. "The Discount Rate for Capital Expenditure Analysis in Health Care." Health Care Management Review Spring: 43-51.
White, J. B. 1997. "An Exploratory Study into the Adoption of Capital Budgeting Techniques by Agricultural Co-operatives." British Food Journal 99: 128-132.
Young, D. R. 2007. Financing Nonprofits: Putting Theory into Practice. Lanham, MD: Altamira Press.
Zerbejr., R. O., X. Han, D. Layton, and T. Leshine. 2002. "A History of Discount Rates and their Use by Government Agencies." Evans School of Public Affairs, University of Washington, Unpublished. 2002.
Zhuang, J., Z. Liang, T. Lin, and F. De Guzman. 2007. "Theory and Practice in the Choice of Social Discount Rate for Cost-Benefit Analysis: A Survey." ERB Working Paper Series No. 94. Asian Development Bank
Zietlow, J. 2010. "Nonprofit Financial Objectives and Financial Responses to a Tough Economy. "Journal of Corporate Treasury Management 3: 238-48.
--. 1989. "Capital and Operating Budgeting Practices in Pure Nonprofit Organizations." Financial Accountability & Management 5: 219-232.
--, J. A. Hankin, and A. G. Seidner. 2007. Financial Management for Nonprofit Organizations. Hoboken, NJ: Wiley.
Robert S. Goldberg
Clinical Assistant Professor
David J. Prottas
Table 1 Perceived Usefulness of Different Analytical Techniques for General Investments Payback Period NPV Public Private Public Private n=23 N=31 N=23 n=30 Not Useful 30% 16% 35% 23% Somewhat/Fairly Useful 9% 29% 26% 13% Useful/Moderately Useful 43% 32% 26% 30% Very Useful 17% 23% 13% 33% mean 3.48 3.58 2.91 3.87 Standard deviation 1.97 1.97 1.83 2.06 t statistic 0.19 1.75 P value 0.85, two-tailed 0.09, two-tailed Standardized mean difference 0.05 0.49 IRR Public Private n=23 n=30 Not Useful 39% 13% Somewhat/Fairly Useful 26% 13% Useful/Moderately Useful 22% 43% Very Useful 13% 30% mean 2.74 4.13 Standard deviation 1.86 1.76 t statistic 2.79 P value <0.01, two-tailed Standardized mean difference 0.77 Table 2 Obstacles to Using IRR or NPV Analysis Public Private N = 22 N = 27 Difficulty Projecting Cash Flows 13% 17% Difficulty Determining Discount Rate 17% 3% Difficulty Incorporating Qualitative Aspects 30% 33% Table 3 Type of Discount Rate Used by those who use IRR or NPV Public Private (n=14) (n=29) Cost of Debt 72% 48% Cost of Net Assets 14% 0% Weighted Average Cost of Capital 0% 45% Return on Endowment 14% 7%
|Printer friendly Cite/link Email Feedback|
|Author:||Goldberg, Robert S.; Prottas, David J.|
|Publication:||Journal of Managerial Issues|
|Date:||Dec 8, 2017|
|Previous Article:||A Gendered Emotional Display Perspective on Workplace Touch and Perceived Supervisor Support.|
|Next Article:||Implementing Interfunctionally-Coordinated Market Orientation in Industrial SMEs: Lessons Learned in Commodity Markets.|