Are Donations Bigger in Texas? Analyzing the Impact of a Policy to Match Donations to Texas’ Emerging Research Universities

Abstract

We examine the impact of the Texas Research Incentive Program (TRIP), a state policy that offers matching funds to incentivize private-sector donations to certain public universities. We use a national dataset and employ a generalized difference-in-differences approach with matching procedures to estimate the treatment effect of TRIP on revenues at eligible institutions. Results show that TRIP is associated with increases in revenue from private gifts and state grants/contracts, which suggests that policymakers can leverage public investment to incentivize private donations. We do not detect a statistically significant relationship between TRIP and endowments, so donations are likely used for short-term funding and do not create long-term dividends. We consider potential social consequences of selecting certain universities to benefit from incentive policies.

Keywords

financial incentive institutional revenue principal-agent framework private donation state policy

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References

Allison

(2009). Fixed effects regression models: Quantitative applications in the social sciences. Sage. https://doi.org/10.4135/9781412993869

Andreoni

Payne

A. A.

(2003). Do government grants to private charities crowd out giving or fund-raising? American Economic Review, 93(3), 792–812. https://doi.org/10.1257/000282803322157098

Angrist

J. D.

Pischke

J. S.

(2009). Mostly harmless econometrics: An empiricist’s companion. Princeton University Press. https://doi.org/10.1515/9781400829828

Association of American Universities. (n.d.). AAU member universities. https://www.aau.edu/sites/default/files/AAU-Files/Who-We-Are/AAU-Member-Universities–Admission-Year.pdf

Bekkers

Wiepking

(2011). A literature review of empirical studies of philanthropy. Nonprofit and Voluntary Sector Quarterly, 40(5), 924–973. https://doi.org/10.1177/0899764010380927

Belasco

A. S.

Rosinger

K. O.

Hearn

J. C.

(2015). The test-optional movement at America’s selective liberal arts colleges: A boon for equity or something else? Educational Evaluation and Policy Analysis, 37(2), 206–223. https://doi.org/10.3102/0162373714537350

Bertrand

Duflo

Mullainathan

(2004). How much should we trust differences-in-differences estimates? Quarterly Journal of Economics, 119(1), 249–275. https://doi.org/10.1162/003355304772839588

Blackwell

Iacus

King

Porro

(2009). CEM: Coarsened exact matching in Stata. Stata Journal, 9(4), 524–546. https://doi.org/10.1177/1536867X0900900402

Blume-Kohout

M. E.

Kumar

K. B.

Sood

(2009). Federal life sciences funding and university R&D (Working Paper No. 15146). National Bureau of Economic Research. https://doi.org/10.3386/w15146

10.

Blume-Kohout

M. E.

Kumar

K. B.

Sood

(2014). University R&D funding strategies in a changing federal funding environment. Science and Public Policy, 42(3), 355–368. https://doi.org/10.1093/scipol/scu054

11.

Boelscher

Snyder

(2019). Driving better outcomes: Fiscal year 2019 state status & typology update. HCM Strategies. http://hcmstrategists.com/promising-policy/wp-content/uploads/2019/01/HCM_2019_DBO_Final.pdf

12.

Burrough

(2009). The big rich: The rise and fall of the greatest Texas oil fortunes. Penguin Books.

13.

Cantwell

Taylor

B. J.

(2013). Global status, intra-institutional stratification and organizational segmentation: A time-dynamic Tobit analysis of ARWU position among US universities. Minerva, 51(2), 195–223. https://doi.org/10.1007/s11024-013-9228-8

14.

Cerulli

(2015). Econometric evaluation of socio-economic programs: Theory and applications. Springer. https://doi.org/10.1007/978-3-662-46405-2

15.

Cheslock

J. J.

Gianneschi

(2008). Replacing state appropriations with alternative revenue sources: The case of voluntary support. Journal of Higher Education, 79(2), 208–229. https://doi.org/10.1353/jhe.2008.0012

16.

Cohen

(1988). Statistical power analysis for the behavioral sciences (2nd ed.). Erlbaum.

17.

Connolly

L. S.

(1997). Does external funding of academic research crowd out institutional support? Journal of Public Economics, 64(3), 389–406. https://doi.org/10.1016/S0047-2727(96)01626-X

18.

Cook

T. D.

Shadish

W. R.

Wong

V. C.

(2008). Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons. Journal of Policy Analysis and Management, 27(4), 724–750. https://doi.org/10.1002/pam.20375

19.

Daun-Barnett

St. John

E. P.

(2012). Constrained curriculum in high schools: The changing math standards and student achievement, high school graduation and college continuation. Education Policy Analysis Archives, 20(5), 1–25. https://doi.org/10.14507/epaa.v20n5.2012

20.

Eisenhardt

K. M.

(1989). Agency theory: An assessment and review. Academy of Management Review, 14(1), 57–74. https://doi.org/10.5465/amr.1989.4279003

21.

Y.-C.

(2017). Does the Project of World Class University (phase I) spur scientific productivity in STEM fields? A study of policy impact in Taiwan [Unpublished doctoral dissertation]. Pennsylvania State University.

22.

Y.-C.

Baker

D. P.

Zhang

(2020). Engineering a world class university? The impact of Taiwan’s World Class University Project on scientific productivity. Higher Education Policy, 33(3), 555–570. https://doi.org/10.1057/s41307-018-0110-z

23.

Furquim

Corral

Hillman

(2020). A primer for interpreting and designing difference-in-differences studies in higher education research. In Perna

L. W.

(Ed.), Higher education: Handbook of theory and research (Vol. 35, pp. 1–58). Springer. https://doi.org/10.1007/978-3-030-11743-6_5-1

24.

Gándara

Rutherford

(2018). Mitigating unintended impacts? The effects of premiums for underserved populations in performance-funding policies for higher education. Research in Higher Education, 59(6), 681–703. https://doi.org/10.1007/s11162-017-9483-x

25.

Gibbons

M. T.

(2018). Higher education R&D expenditures increased 4.7%, exceeded $75 billion in FY 2017 (NCSES InfoBrief No. 19-302). National Science Foundation. https://www.nsf.gov/statistics/2019/nsf19302/nsf19302.pdf

26.

Goodman-Bacon

(2018). Difference-in-differences with variation in treatment timing (Working Paper No. 25018). National Bureau of Economic Research. https://doi.org/10.3386/w25018

27.

Gottfried

M. A.

(2008). College crowd-in: How private donations positively affect alumni giving. International Journal of Educational Advancement, 8(2), 51–70. https://doi.org/10.1057/ijea.2008.8

28.

Halffman

Leydesdorff

(2010). Is inequality among universities increasing? Gini coefficients and the elusive rise of elite universities. Minerva, 48(1), 55–72. https://doi.org/10.1007/s11024-010-9141-3

29.

Hillman

N. W.

Tandberg

D. A.

Fryar

A. H.

(2015). Evaluating the impacts of “new” performance funding in higher education. Educational Evaluation and Policy Analysis, 37(4), 501–519. https://doi.org/10.3102/0162373714560224

30.

Hillman

N. W.

Tandberg

D. A.

Gross

J. P.

(2014). Performance funding in higher education: Do financial incentives impact college completions? Journal of Higher Education, 85(6), 826–857. https://doi.org/10.1353/jhe.2014.0031

31.

D. E.

Imai

King

Stuart

E. A.

(2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15(3), 199–236. https://doi.org/10.1093/pan/mpl013

32.

Villarreal

(2019). Public tuition on the rise: Estimating the effects of Louisiana’s performance-based funding policy on institutional tuition levels. Research in Higher Education, 60(5), 636–669. https://doi.org/10.1007/s11162-018-9526-y

33.

Hunt

J. M.

Tandberg

D. A.

Park

T. J.

(2019). Presidential compensation and institutional revenues: Testing the return on investment for public university presidents. Review of Higher Education, 42(2), 619–640. https://doi.org/10.1353/rhe.2019.0009

34.

Husted

T. A.

Kenney

L. W.

(2018). The effect of reduced support from state government on research in state universities. Journal of Education Finance, 44(2), 164–174. https://www.muse.jhu.edu/article/721604

35.

Iacus

S. M.

King

Porro

(2009). Causal inference without balance checking: Coarsened exact matching. Institute for Quantitative Social Science, Harvard University.

36.

Jaquette

Parra

E. E.

(2014). Using IPEDS data for panel analyses: Core concepts, data challenges, and empirical applications. In Paulsen

M. B.

(Ed.), Higher education: Handbook of theory and research (Vol. 29, pp. 467–533). Springer. https://doi.org/10.1007/978-94-017-8005-6_11

37.

Kennedy

P. E.

(1981). Estimation with correctly interpreted dummy variables in semilogarithmic equations. American Economic Review, 71(4), 801.

38.

King

Nielsen

(2019). Why propensity scores should not be used for matching. Political Analysis, 27(4), 435–454. https://doi.org/10.1017/pan.2019.11

39.

Kingma

B. R.

(1989). An accurate measurement of the crowd-out effect, income effect, and price effect for charitable contributions. Journal of Political Economy, 97(5), 1197–1207. https://doi.org/10.1086/261649

40.

Kivistö

(2008). An assessment of agency theory as a framework for the government– university relationship. Journal of Higher Education Policy and Management, 30(4), 339–350. https://doi.org/10.1080/13600800802383018

41.

Kleer

(2010). Government R&D subsidies as a signal for private investors. Research Policy, 39(10), 1361–1374. https://doi.org/10.1016/j.respol.2010.08.001

42.

Kramer

D. A.

Ortagus

J. C.

Lacy

T. A.

(2018). Tuition-setting authority and broad-based merit aid: The effect of policy intersection on pricing strategies. Research in Higher Education, 59(4), 489–518. https://doi.org/10.1007/s11162-017-9475-x

43.

Leydesdorff

(2018). Synergy in knowledge-based innovation systems at national and regional levels: The Triple-Helix model and the Fourth industrial revolution. Journal of Open Innovation, 4(2), Article 16. https://doi.org/10.3390/joitmc4020016

44.

Leydesdorff

Meyer

(2006). Triple helix indicators of knowledge-based innovation systems: Introduction to the special issue. Research Policy, 35(10), 1441–1449. https://doi.org/10.1016/j.respol.2006.09.016

45.

Merton

R. K.

(1968). The Matthew effect in science: The reward and communication systems of science are considered. Science, 159(3810), 56–63. https://doi.org/10.1126/science.159.3810.56

46.

Merton

R. K.

(1988). The Matthew effect in science, II: Cumulative advantage and the symbolism of intellectual property. Isis, 79(4), 606–623. https://doi.org/10.1086/354848

47.

Mettler

(2016). The policyscape and the challenges of contemporary politics to policy maintenance. Perspectives on Politics, 14(2), 369–390. https://doi.org/10.1017/S1537592716000074

48.

Meyer

B. D.

(1995). Natural and quasi-experiments in economics. Journal of Business & Economic Statistics, 13(2), 151–161. https://doi.org/10.1080/07350015.1995.10524589

49.

Mincer

(1974). Schooling, experience, and earnings. Columbia University Press.

50.

Moe

T. M.

(1984). The new economics of organization. American Journal of Political Science, 28(4), 739–777. https://doi.org/10.2307/2110997

51.

Morphew

C. C.

Baker

B. D.

(2004). The cost of prestige: Do new Research I universities incur higher administrative costs? Review of Higher Education, 27(3), 365–384. https://doi.org/10.1353/rhe.2004.0005

52.

National Center for Education Statistics. (2017). Endowment funds of the 120 degree-granting postsecondary institutions with the largest endowments, by rank order: Fiscal year 2015 (Table 333.90). Institute of Education Sciences, U.S. Department of Education. https://nces.ed.gov/programs/digest/d16/tables/dt16_333.90.asp

53.

National Center for Education Statistics. (2018). Number of educational institutions, by level and control of institution: Selected years, 1980-81 through 2015-16 (Table 105.50). Institute of Education Sciences, U.S. Department of Education. https://nces.ed.gov/programs/digest/d17/tables/dt17_105.50.asp

54.

O’Meara

(2007). Striving for what? Exploring the pursuit of prestige. In Smart

J. C.

(Ed.), Higher education: Handbook of theory and research (pp. 121–179). Springer. https://doi.org/10.1007/978-1-4020-5666-6_3

55.

Ortagus

J. C.

(2019). The price of mission complexity: A national study of the impact of community college baccalaureate adoption on tuition and fees. Educational Researcher, 48(8), 504–520. https://doi.org/10.3102/0013189X19872494

56.

Oster

S. M.

(2001). The effect of university endowment growth on giving: Is there evidence of crowding out? (Working Paper No. 10). Yale School of Management.

57.

Payne

A. A.

(2001). Measuring the effect of federal research funding on private donations at research universities: Is federal research funding more than a substitute for private donations? International Tax and Public Finance, 8(5–6), 731–751. https://doi.org/10.1023/A:1012843227003

58.

Perna

L. W.

Finney

J. E.

(2014). The attainment agenda: State policy leadership in higher education. JHU Press.

59.

Pfeffer

Salancik

(1978). The external control of organizations: A resource dependence perspective. Harper & Row.

60.

Posselt

J. R.

Jaquette

Bielby

Bastedo

M. N.

(2012). Access without equity: Longitudinal analyses of institutional stratification by race and ethnicity, 1972–2004. American Educational Research Journal, 49(6), 1074–1111. https://doi.org/10.3102/0002831212439456

61.

Richardson

S. R.

(2005). Oil, power, and universities: Political struggle and academic advancement at the University of Texas and Texas A&M, 1876-1965 (UMI No. 3261919) [Doctoral dissertation]. ProQuest Dissertations and Theses.

62.

Rosenbaum

P. R.

(2002). Observational studies (2nd ed.). Springer. https://doi.org/10.1007/978-1-4757-3692-2

63.

Rosenbaum

P. R.

Rubin

D. B.

(1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387), 516–524. https://doi.org/10.1080/01621459.1984.10478078

64.

Rosinger

K. O.

Belasco

A. S.

Hearn

J. C.

(2019). A boost for the middle class: An evaluation of no-loan policies and elite private college enrollment. Journal of Higher Education, 90(1), 27–55. https://doi.org/10.1080/00221546.2018.1484222

65.

Rubin

D. B.

(1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688–701. https://doi.org/10.1037/h0037350

66.

Santos

J. L.

(2007). Resource allocation in public research universities. Review of Higher Education, 30(2), 125–144. https://doi.org/10.1353/rhe.2006.0077

67.

Seong

Popper

S. W.

Goldman

C. A.

Evans

D. K.

Grammich

C. A.

(2008). Brain Korea 21 phase II: A new evaluation model. RAND Corporation. https://www.rand.org/content/dam/rand/pubs/monographs/2008/RAND_MG711.pdf

68.

Shavit

Arum

Gamoran

(2007). Stratification in higher education: A comparative study. Stanford University Press.

69.

Sherlock

M. F.

Gravelle

J. G.

Crandall-Hollick

M. L.

Hughes

J. S.

(2018). College and university endowments: Overview and tax policy options. Congressional Research Service. https://fas.org/sgp/crs/misc/R44293.pdf

70.

Shin

J. C.

(2009). Building world-class research university: The Brain Korea 21 project. Higher Education, 58(5), 669–688. https://doi.org/10.1007/s10734-009-9219-8

71.

Slaughter

Leslie

L. L.

(1997). Academic capitalism: Politics, policies, and the entrepreneurial university. Johns Hopkins University Press.

72.

Stephan

J. L.

Rosenbaum

J. E.

Person

A. E.

(2009). Stratification in college entry and completion. Social Science Research, 38(3), 572–593. https://doi.org/10.1016/j.ssresearch.2009.02.001

73.

Texas Higher Education Coordinating Board. (n.d.). National Research University Fund (NRUF). https://www.highered.texas.gov/institutional-resources-programs/public-universities-health-related-institutions/research-funding-in-texas/national-research-university-fund-nruf/

74.

Texas Higher Education Coordinating Board. (2009). Overview: HB 51, 81st Texas Legislature. http://www.thecb.state.tx.us/reports/PDF/1842.PDF

75.

Texas Higher Education Coordinating Board. (2010). A study of research expenditure definitions and terms for use by Research University Development Fund. http://www.thecb.state.tx.us/reports/PDF/2100.PDF

76.

Texas Higher Education Coordinating Board. (2018a). National Research University Fund eligibility September 1, 2016 – August 31, 2017. http://www.thecb.state.tx.us/reports/pdf/10614.pdf

77.

Texas Higher Education Coordinating Board. (2018b). Research funding in Texas: Overview. http://www.thecb.state.tx.us/reports/PDF/1525.PDF

78.

Texas Higher Education Coordinating Board. (2019). TRIP status report. http://www.thecb.state.tx.us/reports/DocFetch.cfm?Docid=10787&Format=XLS

79.

Umbricht

M. R.

Fernandez

Ortagus

J. C.

(2017). An examination of the (un)intended consequences of performance funding in higher education. Educational Policy, 31(5), 643–673. https://doi.org/10.1177/0895904815614398

80.

The University of Texas System. (2018). Texas Research Incentive Program (TRIP). https://www.utsystem.edu/sites/default/files/offices/governmental-relations/TRIP-2018.pdf

81.

Van Looy

Ranga

Callaert

Debackere

Zimmermann

. (2004). Combining entrepreneurial and scientific performance in academia: Towards a compounded and reciprocal Matthew-effect? Research Policy, 33(3), 425–441. https://doi.org/10.1016/j.respol.2003.09.004

82.

Zhang

Patton

Kenney

(2013). Building global-class universities: Assessing the impact of the 985 Project. Research Policy, 42(3), 765–775. https://doi.org/10.1016/j.respol.2012.10.003

83.

Zhang

Bao

Sun

(2016). Resources and research production in higher education: A longitudinal analysis of Chinese universities, 2000–2010. Research in Higher Education, 57(7), 869–891. https://doi.org/10.1007/s11162-016-9410-6

84.

Zhang

Sun

Bao

(2017). The rise of higher education and science in China. In Powell

J. J. W.

Baker

D. P.

Fernandez

(Eds.), The century of science: The global triumph of the research university (pp. 141–172). Emerald. https://doi.org/10.1108/S1479-367920170000033008

85.

Zhao

(2019). State disinvestment in higher education: the impact on public research universities’ patent applications (Working Paper No. 19-2). The Federal Reserve Bank. https://doi.org/10.29412/res.wp.2019.02

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