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Voluntary taxation and the arts


The arts in the USA receive little federal support relative to other developed nations. Because culture and the arts are often viewed as a nonessential role of government, public officials have proposed eliminating public funding for the arts. We examine support for public arts funding using a real-donation experiment (Eckel and Grossman in Games Econ Behav 16(2):181–191, 1996). Real-donation experiments combine elements of a controlled laboratory experiment with the context of a field experiment. In this “giving to the government” experiment, each participant allocates money between herself and a charitable organization supporting either cancer research, education, or the arts. There are two charities within each function: one is a private organization and the other a government agency. Not only do participants donate significant amounts to support the arts generally, we observe significant donations to a government agency that funds the arts. We find similar donation rates to cancer research and education as Li et al. (J Publ Econ 95(9–10):1190–1201, 2011), which provides a measure of external validity. Participants donate less to the arts than to cancer research or education and consistently give less to government organizations than to private charities. However, observing voluntary taxation to support the arts stands in striking contrast to current public policy. Significant predictors of giving include the perceived importance, efficiency, and trust of the organization, as well as gender. Our evidence suggests that current public funding for the arts may be less than optimal.

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Fig. 1


  1. The FY18 appropriation to the National Endowment for the Arts was less than 0.004 percent of total federal outlays (National Endowment for the Arts n.d.).

  2. See the review by Kirchberg for an example of research on private arts donations (2003).

  3. If any participant would have declined to act as monitor, the process would repeat until a monitor was selected. However, none declined the option to act as monitor.

  4. Li et al. (2011) also vary the organizations by “level” from local, state, and national.

  5. This was a different experimenter than the one tasked with reading instructions or who placed earnings in payment envelopes.

  6. One could equally conjecture that participants believe they are expected to confirm economic theories such as free-riding, so perhaps participants feel compelled to give nothing.

  7. See also Kessler and Vesterlund (2015).

  8. Survey questions: How much do you trust the following organizations in providing [service]? To what extent do you agree or disagree that to provide [service] is the responsibility of the following organizations? How confident are you that donations to the following [service] organizations will be used efficiently?

  9. In Session 2, participants could donate in honor or memory of someone. This option is not provided in Session 1. We find no significant difference in giving between sessions. Regression models include a treatment indicator for Session 2.

  10. Cancer versus education: t = 3.37, p > 0.01; Wilcoxon signed-rank test, z = 3.20, p > 0.01. Education versus arts: t = 9.45, p > 0.01; z = 6.72, p > 0.01. All comparisons of importance remain statistically significant after Bonferroni corrections.

  11. We cannot distinguish between those who give $0 and would not take from those who give $0 only because taking is prohibited. For evidence of taking in dictator allocations, see List (2007); for evidence of taking in real-donation experiments, see Luccasen and Grossman (2019).

  12. In real donation experiments with a charity as the recipient, females tend to be more charitable than males (Mesch et al. 2011).

  13. We also estimate random effects probit models to investigate the likelihood of giving. Giving is more likely if the mission is important, the organization is trusted, or if the participant is female. Results and data are available upon request.

  14. Minimal crowd-out may be a lower bound on the effect. Public funding may act as seed-money that may signal the organization is worthy of support. Public funding may then “crowd-in” additional private donations (see List and Lucking-Reiley (2002).


  • Americans for the Arts. (2018). Americans speak out about the arts in 2018: An in-depth look at perceptions and attitudes about the arts in America.

  • Borgonovi, F., & O’Hare, M. (2004). The impact of the National Endowment for the Arts in the United States: Institutional and sectoral effects on private funding. Journal of Cultural Economics, 28(1), 21–36.

    Article  Google Scholar 

  • Brooks, A. C. (2001). Who opposes government arts funding? Public Choice, 108(3/4), 355–367.

    Article  Google Scholar 

  • Camerer, C. F. (2015). The promise and success of lab–field generalizability in experimental economics: A critical reply to Levitt and List. In G. R. Fréchette & A. Schotter (Eds.), Handbook of experimental economic methodology. Oxford: Oxford University Press.

    Google Scholar 

  • de Quidt, J., Vesterlund, L., & Wilson, A. (2019). Experimenter demand effects. In A. Schram & A. Ule (Eds.), Handbook of research methods and applications in experimental economics. Cheltenham: Edward Elgar Publishing.

    Google Scholar 

  • Eckel, C. C., & Grossman, P. J. (1996). Altruism in anonymous dictator games. Games and Economic Behavior, 16(2), 181–191.

    Article  Google Scholar 

  • Eckel, C. C., Grossman, P. J., & Johnston, R. M. (2005). An experimental test of the crowding out hypothesis. Journal of Public Economics, 89(8), 1543–1560.

    Article  Google Scholar 

  • Ho, J., Tumkaya, T., Aryal, S., Choi, H., & Claridge-Chang, A. (2018). Moving beyond P values: Everyday data analysis with estimation plots.

  • Jones, K. (2017). Government or charity? Preferences for welfare provision by ethnicity. Journal of Behavioral and Experimental Economics., 66, 72–77.

    Article  Google Scholar 

  • Kessler, J., & Vesterlund, L. (2015). The external validity of laboratory experiments: The misleading emphasis on quantitative effects. In G. R. Fréchette & A. Schotter (Eds.), Handbook of experimental economic methodology. Oxford: Oxford University Press.

    Google Scholar 

  • Kirchberg, V. (2003). Corporate arts sponsorship. In R. Towse (Ed.), A handbook of cultural economics. Northampton: Edward Elgar.

    Google Scholar 

  • Levitt, S., & List, J. A. (2007). What do laboratory experiments measuring social preferences reveal about the real world. Journal of Economic Perspectives, 21(2), 153–174.

    Article  Google Scholar 

  • Lewis, G. B., & Brooks, A. C. (2005). A question of morality: Artists’ values and public funding for the arts. Public Administration Review, 65(1), 8–17.

    Article  Google Scholar 

  • Li, S. X., Eckel, C. C., Grossman, P. J., & Brown, T. L. (2011). Giving to government: Voluntary taxation in the lab. Journal of Public Economics, 95(9–10), 1190–1201.

    Article  Google Scholar 

  • Li, S. X., Eckel, C. C., Grossman, P. J., & Brown, T. L. (2015). Directed giving enhances voluntary giving to government: Implications for tax policy. Economics Letters, 133, 51–54.

    Article  Google Scholar 

  • List, J. (2007). On the interpretation of giving in dictator games. Journal of Political Economy, 115(3), 482–493.

    Article  Google Scholar 

  • List, J., & Lucking-Reiley, D. (2002). The effects of seed money and refunds on charitable giving: Experimental evidence from a university capital campaign. Journal of Political Economy, 110(1), 215–233.

    Article  Google Scholar 

  • Luccasen III, R. A. & Grossman, P. J. (2019). Taking aversion with earned endowments and tangible money. Monash University, Working paper.

  • Massey, C., & Thaler, R. (2013). The loser’s curse: Decision making and market efficiency in the National Football League draft. Management Science, 59(7), 1479–1495.

    Article  Google Scholar 

  • McGlone, P. (February 12, 2018). Trump’s budget eliminates NEA, public TV and other cultural agencies. Again. The Washington Post. Accessed 15 July 2018.

  • Mesch, D. J., Brown, M. S., Moore, Z. I., & Hayat, A. D. (2011). Gender differences in charitable giving. International Journal of Nonprofit and Voluntary Sector Marketing, 16, 342–355.

    Article  Google Scholar 

  • National Endowment for the Arts. (2000). International data on government spending on the arts. Research Division. Note #74. Retrived July 15, 2018.

  • National Endowment for the Arts. (n.d.). Quick facts. Accessed 13 Jan 2020.

  • Newport, F. (2017). Americans’ confidence in institutions edges up. Accessed July 15, 2018.

  • Vesterlund, L. (2016). Using experimental methods to understand why and how we give to charity. In J. Kagel & A. Roth (Eds.), The handbook of experimental economics (Vol. 2). Princeton: Princeton University Press.

    Google Scholar 

  • Zizzo, D. J. (2013). Experimenter demand effects in economic experiments. Experimental Economics, 13(1), 75–98.

    Article  Google Scholar 

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We wish to thank Mississippi University for Women for financial support of this project.

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Correspondence to M. Kathleen Thomas.

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Luccasen, R.A., Thomas, M.K. Voluntary taxation and the arts. J Cult Econ 44, 589–604 (2020).

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  • Charitable giving
  • Taxation
  • Laboratory experiment
  • Real donation
  • Philanthropy
  • The arts

JEL Classification

  • C91
  • D64
  • H2
  • Z1