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Journal of Gambling Studies

, Volume 35, Issue 4, pp 1147–1162 | Cite as

A Quantification of the Net Consumer Surplus from Gambling Participation

  • Matthew J. RockloffEmail author
  • Matthew Browne
  • Alex Myles Thomas Russell
  • Stephanie S. Merkouris
  • Nicki A. Dowling
Original Paper

Abstract

Gambling exposes people to risk for harm, but also has recreational benefits. The present study aimed to measure gambling harm and gambling benefits on similar scales using two novel methods adapted from the Burden of Disease approach (McCormack et al. in Psychol Med 18(4):1007–1019, 1988; Torrance et al. in Health Serv Res 7(2):118–133, 1972) to find whether gambling either adds or subtracts from quality of life. A Tasmanian population-representative survey of 5000 adults (2534 female) from random digit dialling (RDD) of landline telephones in Tasmania (50%), as well as pre-screened Tasmanian RDD mobiles (17%) and listed mobile numbers (33%), measured gambling benefits and harms amongst gamblers (59.2%) and a non-exclusive set of people who were “affected” by someone else’s gambling (4.5%). The majority of gamblers indicated no change to their quality of life from gambling (82.5% or 72.6% based on direct elicitation or time trade off methods, respectively). Nevertheless, a weighted average of all the positive and negative influences on quality of life, inclusive of gamblers and affected others, revealed that the quality of life change from gambling is either a very modest + 0.05% or a more concerning − 1.9% per capita. Gambling generates only small or negative net consumer surpluses for Tasmanians.

Keywords

Burden of Disease (BoD) Years of life lost (YLL) Disability adjusted life year (DALY) Quality adjusted life year (QALY) 

Notes

Funding

This research was funded by the Tasmanian Department of Treasury and Finance by way of successful tender for The Fourth Social and Economic Impact Study of Gambling in Tasmania (2017).

Compliance with Ethical Standards

Conflict of interest

All authors have received funding from multiple sources, including government departments or agencies that are funded primarily by government departments (some through hypothecated taxes from gambling revenue). ND and SM have been the Victorian state representatives (unpaid) on the NAGS Executive Committee (which derives its funding from member fees conference proceeds and includes representatives from all stakeholder groups). AR has received industry funding from Echo/Star Entertainment to evaluate gambling and problem gambling amongst their casino employees. The remaining authors (MR, MB, NAD, SM) have not knowingly received research funding from the gambling industry or any industry-sponsored organization. The authors have no conflicts of interest to declare in relation to this paper.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of Deakin University’s Human Ethics Panel; the Australian Code for the Responsible Conduct of Research (2007); and the National Statement on Ethical Conduct in Human Research (2007).

References

  1. ACIL Allen Consulting Pty. (2017). 2017 Tasmanian prevalence study. Retrieved from https://www.treasury.tas.gov.au/liquor-and-gaming/gambling/reduce-harm-from-gambling/social-and-economic-impact-studies. 20 October.
  2. American Association for Public Opinion Research. (2016). Standard definitions: Final dispositions of case codes and outcome rates for surveys. Retrieved October 9, 2018 from https://www.aapor.org/AAPOR_Main/media/publications/Standard-Definitions20169theditionfinal.pdf.
  3. Browne, M., Greer, N., Rawat, V., & Rockloff, M. (2017a). A population-level metric for gambling-related harm. International Gambling Studies, 17(2), 163–175.CrossRefGoogle Scholar
  4. Browne, M., Langham, E., Rawat, V., Greer, N., Li, E., Rose, J., et al. (2016). Assessing gambling-related harm in Victoria: A public health perspective. Melbourne: Victorian Responsible Gambling Foundation.Google Scholar
  5. Browne, M., Rawat, V., Greer, N., Langham, E., Rockloff, M., & Hanley, C. (2017b). What is the harm? Applying a public health methodology to measure the impact of gambling problems and harm on quality of life. Journal of Gambling Issues.  https://doi.org/10.4309/jgi.2017.36.2.CrossRefGoogle Scholar
  6. Chhabra, D. (2007). Estimating benefits and costs of casino gambling in Iowa, United States. Journal of Travel Research, 46(2), 173–182.CrossRefGoogle Scholar
  7. Cho, D. J., Kim, H. T., Lee, J., & Park, S. H. (2018). Economic cost–benefit analysis of the addictive digital game industry. Applied Economics Letters, 25(9), 638–642.CrossRefGoogle Scholar
  8. Clayton, W. A., Wright, M., & Sarver, W. S. (1993). Benefit cost analysis of riverboat gambling. Mathematical and Computer Modelling, 17(4), 187–194.CrossRefGoogle Scholar
  9. Collins, D., & Lapsley, H. (2003). The social costs and benefits of gambling: An introduction to the economic issues. Journal of Gambling Studies/Co-Sponsored by the National Council on Problem Gambling and Institute for the Study of Gambling and Commercial Gaming, 19(2), 123–148.Google Scholar
  10. Diener, E., & Seligman, M. E. P. (2004). Beyond money: Toward an economy of well-being. Psychological Science in the Public Interest: A Journal of the American Psychological Society, 5(1), 1–31.CrossRefGoogle Scholar
  11. Dowling, N. A., Youssef, G. J., Jackson, A. C., Pennay, D. W., Francis, K. L., Pennay, A., et al. (2016). National estimates of Australian gambling prevalence: Findings from a dual-frame omnibus survey. Addiction, 111(3), 420–435.CrossRefGoogle Scholar
  12. Goodwin, B. C., Browne, M., Rockloff, M., & Rose, J. (2017). A typical problem gambler affects six others. International Gambling Studies, 17(2), 276–289.CrossRefGoogle Scholar
  13. Grinols, E. L. (2004). Gambling in America: Costs and benefits. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  14. Grinols, E. L., & Omorov, J. D. (1996). Development or dreamfield delusions: Assessing casino gambling’s costs and benefits. Journal of Law and Commerce, 16, 49.Google Scholar
  15. Jackson, A. C., Pennay, D., Dowling, N. A., Coles-Janess, B., & Christensen, D. R. (2014). Improving gambling survey research using dual-frame sampling of landline and mobile phone numbers. Journal of Gambling Studies/Co-Sponsored by the National Council on Problem Gambling and Institute for the Study of Gambling and Commercial Gaming, 30(2), 291–307.Google Scholar
  16. Jiménez-Murcia, S., Granero Pérez, R., Fernández-Aranda, F., Álvarez Moya, E., Aymamí, M. N., Gómez-Peña, M., et al. (2009). Comorbidity of pathological gambling: Clinical variables, personality and response to treatment. Revista de Psiquiatria Y Salud Mental, 2(4), 178–189.CrossRefGoogle Scholar
  17. Li, E., Browne, M., Rawat, V., Langham, E., & Rockloff, M. (2016). Breaking bad: Comparing gambling harms among gamblers and affected others. Journal of Gambling Studies/Co-Sponsored by the National Council on Problem Gambling and Institute for the Study of Gambling and Commercial Gaming, 33, 223–248.  https://doi.org/10.1007/s10899-016-9632-8.CrossRefGoogle Scholar
  18. Lorains, F. K., Cowlishaw, S., & Thomas, S. A. (2011). Prevalence of comorbid disorders in problem and pathological gambling: Systematic review and meta-analysis of population surveys. Addiction, 106(3), 490–498.CrossRefGoogle Scholar
  19. McCormack, H. M., Horne, D. J., & Sheather, S. (1988). Clinical applications of visual analogue scales: A critical review. Psychological Medicine, 18(4), 1007–1019.CrossRefGoogle Scholar
  20. Productivity Commission. (2010). Gambling: Report No. 50. Canberra: Commonwealth of Australia.Google Scholar
  21. Rodriguez-Monguio, R., Errea, M., & Volberg, R. (2017). Comorbid pathological gambling, mental health, and substance use disorders: Health-care services provision by clinician specialty. Journal of Behavioral Addictions, 6(3), 406–415.CrossRefGoogle Scholar
  22. Sproston, K., Hing, N., & Palankay, C. (2012). Prevalence of gambling and problem gambling in New South Wales. Sydney: NSW Office of Liquor, Gaming and Racing. Retrieved October 9, 2018 from https://www.researchgate.net/profile/Nerilee_Hing/publication/260419175_Prevalence_of_gambling_and_problem_gambling_in_New_South_Wales/links/00b495311616e20702000000/Prevalence-of-gambling-and-problem-gambling-in-New-South-Wales.pdf.
  23. Tackett, J. L., Krieger, H., Neighbors, C., Rinker, D., Rodriguez, L., & Edward, G. (2017). Comorbidity of alcohol and gambling problems in emerging adults: A bifactor model conceptualization. Journal of Gambling Studies/Co-Sponsored by the National Council on Problem Gambling and Institute for the Study of Gambling and Commercial Gaming, 33(1), 131–147.Google Scholar
  24. Torrance, G. W., Thomas, W. H., & Sackett, D. L. (1972). A utility maximization model for evaluation of health care programs. Health Services Research, 7(2), 118–133.PubMedPubMedCentralGoogle Scholar
  25. Walker, D. M. (2007). Problems in quantifying the social costs and benefits of gambling. American Journal of Economics and Sociology, 66(3), 609–645.CrossRefGoogle Scholar
  26. Wardle, H., Reith, G., Best, D., McDaid, D., & Platt, S. (2018). Measuring gambling-related harms: A framework for action. Retrieved October 9, 2018 from http://www.gamblingcommission.gov.uk/PDF/Measuring-gambling-related-harms.pdf.
  27. Williams, R. J., Belanger, Y. D., & Arthur, J. N. (2011). Gambling in Alberta: History, current status and socioeconomic impacts. Alberta Gaming Research Institute. Retrieved October 9, 2018 from https://prism.ucalgary.ca/handle/1880/48495.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Experimental Gambling Research LaboratoryCentral Queensland UniversityBundabergAustralia
  2. 2.School of PsychologyDeakin UniversityGeelongAustralia
  3. 3.Melbourne Graduate School of EducationUniversity of MelbourneParkvilleAustralia

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