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Nonprofit executive incentive pay

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Abstract

We utilize information only recently disclosed on Form 990 to examine the use, and consequences of, incentive pay at nonprofit organizations. Bonuses are common in nonprofits, as we observe that approximately 45% of the 44,000 organization-year observations in our sample reported paying CEO bonuses. We find that the bonuses are positively associated with profitability, competition from other nonprofits, firm size, available cash, and use of compensation consultants and committees, while negatively related to board oversight, donations, and grants. Our results also suggest that donors look unfavorably at the payment of bonuses; that is, bonuses are associated with lower future donations. Nonetheless, we find evidence consistent with the payment of bonuses incentivizing nonprofit executives, as despite reduced fundraising, future profitability and program services are positively associated with current bonus compensation.

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Notes

  1. While nonprofits do not have or report “profits” in the traditional sense, we measure profitability as the excess of revenues over expenses in a given fiscal year.

  2. Incentives can also arise from increases in base salary. However, in addition to increasing fixed costs, it is unclear whether a potential raise in base pay provides the same incentives as a bonus (Kahn and Sherer 1990).

  3. This latter finding that higher donations and government grants are associated with lower bonuses seems counterintuitive; i.e., it appears the CEO is penalized for fundraising. We note that we are merely showing an association, not establishing causation, and that this result is consistent with charitable organizations (those more reliant on funding from donations) paying lower bonuses. Consistent with this explanation, in additional untabulated analyses, we find that this association only holds in two of our six industry classifications, religion and “other,” i.e., the more charitable industries.

  4. Not all nonprofits are required to provide this additional information. For example, only nonprofits with at least one executive earning more than $150,000 would generally be required to file Schedule J.

  5. While papers using publicly disclosed data were subject to this limitation, others, such as Ballou and Weisbrod (2003) and Erus and Weisbrod (2003), which rely on survey data, were not. However, those papers are more concerned with compensation differences between for-profit and nonprofit hospitals, and then within different types of nonprofit hospitals, and less concerned with the relationship between pay and performance. For example, Ballou and Weisbrod (2003) find that the amount of bonus is positively associated with a hospital disclosing that it considered financial performance in its determination, but do not investigate the metric used, nor the relationship between the metric and bonus.

  6. The IRS defines reasonable compensation as: “the value that would ordinarily be paid for like services by like enterprises under like circumstances. Reasonableness is determined based on all the facts and circumstances.” (http://www.irs.gov/Charities-%26-Non-Profits/Exempt-Organization-Annual-Reporting-Requirements:-Meaning-of-Reasonable-Compensation).

  7. The IRS does not prohibit the payment of bonuses, i.e., prohibitions against the use of incentive pay systems were removed in 1980 (IRS Counsel Memorandum 38,283, Revenue Ruling 8,122,068). However, payments of large bonuses could be deemed excessive pay by the IRS.

  8. These percentages are consistent with Chang and Tuckman (1990), who find that the majority of organizations in their sample reported surpluses, and very few had surpluses close to zero. They are also consistent with Yetman (Yetman 2001, p. 298), who documents that nonprofits report “aggregate profits of over $50 billion on their tax-exempt activities.”

  9. We do, however, control for for-profit competition in our empirical analyses.

  10. The use of a log transformation is common in the compensation literature to mitigate skewness. See for example Guojin et al. (2011).

  11. In our additional analysis we get closer to measuring the competition for executive services by using the actual incentive compensation paid by competing organizations. However, because of the ensuing reduction in sample size, e.g., not all competing organizations file schedule J, we do not use that variable in our primary analysis.

  12. This measure is a refinement of that used by Deng and Gao (2013). To identify competing nonprofit organizations, we use the NCCS CORE file that includes a comprehensive cross-section of 501(c)(3) organizations. To identify for-profit organizations we use the NCCS NTEE/NAICS/SIC crosswalk compiled by the National Center for Charitable Statistics, which we obtained from http://nccsdataweb.urban.org/kbfiles/786/xwalka.pdf on October 20, 2014.

  13. A counter argument, however, is that contingent compensation is only effective if the principal, in this case the board, can monitor the performance metrics and how they are being measured.

  14. Our results are robust to using OLS.

  15. Automatic extensions of six months are available.

  16. By definition, this standardization does not affect the t-statistics of the individual variables, nor the R2 of the model.

  17. See http://nccsweb.urban.org/. Advantages of using information prepared and provided by the NCCS, rather than data available from the IRS, are 1) additional classification information, such as Metropolitan Statistical Area codes (used for our competition variables); 2) separate files for 501(c)(3), non-501(c)(3), 990-EZ, and 990-PF filers (our sample focuses on 501(c)(3) filers as these are the only organizations required to file schedule J from which our bonus data is collected); and 3) data can be extracted and downloaded into user friendly format. See Feng et al. (2014) for a detailed discussion of data availability and differences between data provided by the NCCS and the IRS.

  18. The NCCS is in the process of digitizing more recent years at this time.

  19. Our results are robust to including observations with compensation less than $150,000. However, given that firms are not required to complete Schedule J below this threshold, and that voluntary disclosers may differ from those required to disclose, we limit our analysis to organizations that are required to disclose this information.

  20. Our industry classification follows that of Frumkin and Keating (2010).

  21. We emphasize that restricted assets need not be cash, i.e., there may be restrictions on other investments or property, plant, and equipment. However, in the absence of a way to identify the actual restricted assets, we use the most conservative approach and assume that the restrictions are on the use of cash. As a reference point, the mean of cash plus savings and temporary cash investments is $4 million; investments in publicly traded securities $39 million; investments in other securities $49 million; and land, buildings, and equipment $57 million;for nonprofits in our sample. So the average nonprofit has unrestricted assets in excess of $100 million.

  22. As an alternative formulation, in an untabulated analysis, we jointly model the decision to pay a bonus and the amount of the bonus. In this two-stage model, the first stage models the choice to pay a bonus, while the second models the amount of the bonus, incorporating the inverse Mills ratio (IMR) to control for selection bias. Our results are robust to this alternative specification.

  23. As our inferences are consistent across panels, for brevity we only discuss panel A.

  24. One possible explanation for this result is the lack of for-profit competition for our sample organizations; that is, we find only 36% of sample organizations face competition from for-profit organizations in the same industry and size quartile.

  25. To further probe this finding, in an untabulated analysis, we replace Log Salary with Excess Salary and continue to find a positive and significant association with the likelihood, amount, and change in bonus. The finding that bonus in excess of that explained by the other economic and monitoring variables is positively associated with excess salary is not proof, but nonetheless is consistent with, managerial power theory.

  26. Y = (Total Assetst – Permanently Restricted Net Assetst-1) / (Total Expensest-1 – Fundraising Expensest-1)

  27. We find similar results for ROA and Operating Margin but do not tabulate for brevity.

  28. We note that these findings are stronger than those of Balsam and Harris (2014), who fail to find an association between total compensation and subsequent donations for their overall sample; they only find their result for nonprofits whose compensation is disclosed in the media and nonprofits with sophisticated donors. While we cannot definitively reconcile these differing results, we note that the sample selection criteria in the two studies differ substantially. That is, this project focuses on organizations reporting total compensation in excess of $150,000 that are required to file schedule J, while Balsam and Harris (2014) incorporate firms of all size. Our samples are also drawn from different time periods, as Balsam and Harris (2014) examine 2002 through 2008, while we study 2008 through 2012.

  29. In untabulated analysis we also find consistent negative relationships when we specify our dependent and control variables in change form, with the level of bonus pay (as well as alternative bonus specifications) as our test variables.

  30. The coefficient on net income in column II of Table 10 is positive, but not significantly different from zero.

  31. The coefficient on Log Program Service Revenues in column I of Table 10 is negative, but not significantly different from zero.

  32. While we do not tabulate for brevity, we find similar results for the alternative metrics of bonus used in Table 9, i.e., Bonus/Total Compensation, Bonus/Salary, Bonus Squared, and Excess Bonus.

  33. Our results are robust to including the lagged dependent variable, i.e., time t profitability, as an additional control variable in the model.

  34. Our results are robust to including concurrent, instead of lagged, control variables in the model.

  35. While others, such as Bruynseels and Cardinaels (2014) and Balsam et al. (2017), use lagged dependent variables as instruments, Larcker and Rusticus (2010) argue that lagged variables are not proper instruments.

  36. These results are robust to using lagged independent variables. However, this reduces are sample size even further.

  37. Control variables are included in our industry-specific models but not tabulated for brevity.

  38. Once again, these results are robust to using lagged independent variables. However, once again, this would further reduce our sample size.

  39. As reported in footnote 11 we do not use this measure in our primary analysis due to the ensuing reduction in sample size.

  40. We exclude these variables from our main analysis because relatively few entities report taxable revenues (about 16% of our sample) and mean taxable revenues are relatively low (about $417,000).

  41. This analysis is limited by the fact that Schedule J reporting is only required for employees earning $150,000 or more. Therefore, we may be missing bonus pay provided to employees with total compensation below this threshold.

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Acknowledgements

We would like to thank the following individuals for their helpful comments: Sudipta Basu, Larry Brown, Lucy Chen, Mark Defond, Ivo Jansen, Daniel Neeley, Christine Petrovits, and Andrea Roberts as well as workshop participants at Baruch College, Drexel University, Rutgers University – Camden, Temple University’s Conference on the Convergence of Managerial and Financial Accounting Research, the University of North Carolina at Charlotte, Villanova University, West Virginia University, and the 2014 American Accounting Associations’ Annual and Mid-Atlantic Midyear meetings.

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  1. Fox School of Business, Temple University, 1801 Liacouras Walk, Philadelphia, PA, 19122, USA

    Steven Balsam

  2. Villanova School of Business, Villanova University, 800 East Lancaster Avenue, Villanova, PA, 19085, USA

    Erica E. Harris

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Correspondence to Steven Balsam.

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Balsam, S., Harris, E.E. Nonprofit executive incentive pay. Rev Account Stud 23, 1665–1714 (2018). https://doi.org/10.1007/s11142-018-9473-z

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