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The social value of gambling: surplus estimates by gambling types for France

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Abstract

We estimate the social surplus of gambling in France by adding three components: consumer surplus, producer surplus and taxation revenue. To estimate consumer surplus, we use the rational benchmark approach, which attributes a loss of welfare (i.e. a negative surplus) to problem gamblers depending on their level of excess spending compared with recreational gamblers. Using data for the year 2019 and considering only legal gambling, we find that the consumer surplus is negative for the gambling activity as a whole. When we add the producer surplus and the taxation revenue to the consumer surplus, we find that the social surplus is more likely to be negative, ranging from − 45 billion euros in the pessimistic scenario to + 6 billion euros in the optimistic scenario. There are, however, important differences between gambling types. The social surplus is negative in all scenarios for poker and sports betting. Conversely, it is positive in all scenarios for draw lotteries and scratch cards.

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Data availability statement

Data available on request from the authors.

Notes

  1. The concepts of price and quantity are a bit peculiar in the gambling sector. We will explain in more detail what they mean and how we measure them in "Gambling spending and revenue at the aggregate level".

  2. The price uniqueness implicitly requires that the expected loss rate is identical for all gamblers and homogeneous within each gambling type, which is a simplifying working assumption.

  3. See Soullier et al. [12] for a presentation of the Health Barometer.

  4. This issue substantially reflects the distinct nature of a public health approach and a clinical one. The matter is rather complex, and the overview is quite schematic. See Delfabbro and King [21] and Browne and Rockloff [16] on the relevance of the prevention paradox for gambling, and Browne and Rockloff [22] and Delfabbro and King [23], on the difference between gambling-related harms and gambling disorders.

  5. The measure of problem gambler surplus (Eq. 6) is non-linear. Thus, the measurement obtained in a group with a PGSI score of 3–27 is different from that obtained by summing the surplus of subgroups with a PGSI score of 3–7 and 8–27. It then seems reasonable to separate the two groups in the calculation to preserve their characteristics rather than assigning them those of an aggregate group.

  6. This way of defining gambling spending is equivalent to that of the GGR (which removes winnings from bets). The issues of proper understanding of the question and reliability of self-reported data are addressed in the discussion.

  7. Note that this method is not usable for slot machines, poker, and other table games because of the small number of regular recreational gamblers. As pointed out by the Productivity Commission ([1], vol. 3, p. C19) for the casino table game category: “even ‘enthusiastic’ recreational players, appear not to play weekly”. We then use the median spending of all recreational gamblers rather than regular recreational gamblers for these games.

  8. The Française des Jeux (FDJ) has a monopoly on offline and online lottery games and offline sports betting. The Pari Mutuel Urbain (PMU) has a monopoly on offline horse racing betting. Slot machines and table games are authorized only in land-based casinos, which are subject to an operating licence from the Ministry of the Interior. Online sports and horse racing betting and poker are the only games officially open to competition.

  9. See Tirole ([26], p. 66 et seq.) on monopoly pricing behaviour.

  10. I.e. an approach where the producer surplus is measured as: \(PS = NGR - VC = \Pi + FC\), where \(VC\) is the variable costs, \(\Pi\) is the economic profit, and \(FC\) is the fixed costs. To our knowledge, there is no other available estimate of producer surplus in the literature.

  11. See Table 12 in the Appendix for details of the correspondence.

  12. Details of gains and losses for each category of problem gamblers are provided in the Appendix (Table 13). The loss on excess spending exceeds the gain on recreational spending for each category of problem gamblers and each type of gambling. As a result, the surplus is negative for each type of gambling and each category of problem gamblers.

  13. The shift in the threshold trivially changes the categories of recreational and problem gamblers. It also modifies the median spending of recreational gamblers (regular or not) and the share of recreational spending for problem gamblers. Note further that we compute the surpluses of problem gamblers with PGSI scores of 1–2, 3–7, and 8–27 separately before adding them when the threshold is set at 1 + .

  14. Note that the loss in consumer surplus exceeds the GGR for the gambling type with a negative social surplus in the baseline scenario Table 6. It follows that the estimate of producer surplus does not impact the sign of the social surplus in the baseline scenario since the taxation revenue plus the producer surplus is necessarily inferior to the GGR.

References

  1. Productivity Commission. Australia’s Gambling Industries (Inquiry Report No. 10). (1999). https://www.pc.gov.au/inquiries/completed/gambling/report

  2. Bernheim, B.D., Rangel, A.: Addiction and cue-triggered decision processes. Am. Econ. Rev. 94(5), 1558–1590 (2004)

    Article  PubMed  Google Scholar 

  3. Gruber, J., Köszegi, B.: Is addiction “rational”? Theory and evidence. Q. J. Econ. 116(4), 1261–1303 (2001)

    Article  Google Scholar 

  4. Lesieur, H. R., Anderson, C.: Results of a survey of gamblers Anonymous members in Illinois. Illinois Council on Problem and Compulsive Gambling. Mimeographed (1995)

  5. Thompson, W.N., Gazel, R., Rickman, D.: The social costs of gambling in Wisconsin. Wisconsin Policy Res. Inst. Rep. 9(6), 1–44 (1996)

    Google Scholar 

  6. Gerstein, D., Murphy, S., Toce, M., Hoffman, J., Palmer, A., Johnson, R., Larison, C., Chuchro, L., Buie, T., Engelman, L., Hill, M.A.: Gambling impact and behavior study: report to the National Gambling Impact Study Commission. National Opinion Research Center (1999)

    Google Scholar 

  7. Thorley, C., Stirling, A., Huynh, E.: Cards on the table: the cost to government associated with people who are problem gamblers in Britain. Institute for Public Policy Research, London (2016)

    Google Scholar 

  8. Fiedler, I.: Glücksspiele: Eine verhaltens- und gesundheitsökonomische Analyse mit rechtspolitischen Empfehlungen. Peter Lang, Frankfurt am Main (2016)

    Book  Google Scholar 

  9. Massin, S., Miéra, M.: Measuring consumer surplus in the case of addiction: a re-examination of the rational benchmark algebra. Econ. Bull. 40(4), 3171–3181 (2020)

    Google Scholar 

  10. Gruber, J.: Smoking’s internalities. Regulation 25(4), 52–58 (2002)

    Google Scholar 

  11. Ferris, J., Wynne, H.: The Canadian problem gambling index. Canadian Centre on Substance Abuse, Ottawa, ON (2001)

    Google Scholar 

  12. Soullier, N., Richard, J-B., Gautier, A.: Baromètre santé 2019. Méthode d'enquête. Objectifs, contexte de mise en place et protocole. Santé publique France (2021)

  13. Currie, S.R., Hodgins, D.C., Casey, D.M.: Validity of the problem gambling severity index interpretive categories. J. Gambl. Stud. 29(2), 311–327 (2013)

    Article  PubMed  Google Scholar 

  14. Stone, C.A., Romild, U., Abbott, M., Yeung, K., Billi, R., Volberg, R.: Effects of different screening and scoring thresholds on PGSI gambling risk segments. Int. J. Ment. Heal. Addict. 13(1), 82–102 (2015)

    Article  Google Scholar 

  15. Browne, M., Rawat, V., Greer, N., Langham, E., Rockloff, M., Hanley, C.: What is the harm? Applying a public health methodology to measure the impact of gambling problems and harm on quality of life. J. Gambl. Issues 36, 28–50 (2017)

    Google Scholar 

  16. Browne, M., Rockloff, M.J.: Prevalence of gambling-related harm provides evidence for the prevention paradox. J. Behav. Addict. 7(2), 410–422 (2018)

    Article  PubMed  PubMed Central  Google Scholar 

  17. Li, E., Browne, M., Rawat, V., Langham, E., Rockloff, M.: Breaking bad: comparing gambling harms among gamblers and affected others. J. Gambl. Stud. 33(1), 223–248 (2017)

    Article  PubMed  Google Scholar 

  18. Ladouceur, R., Jacques, C., Chevalier, S., Sevigny, S., Hamel, D.: Prevalence of pathological gambling in Quebec in 2002. Can. J. Psychiatry 50(8), 451–456 (2005)

    Article  PubMed  Google Scholar 

  19. Samuelsson, E., Wennberg, P., Sundqvist, K.: Gamblers’(mis-) interpretations of Problem Gambling Severity Index items: ambiguities in qualitative accounts from the Swedish Longitudinal Gambling Study. Nordic Stud. Alcohol Drugs 36(2), 140–160 (2019)

    Article  Google Scholar 

  20. Williams, R.J., Volberg, R.A.: The classification accuracy of four problem gambling assessment instruments in population research. Int. Gambl. Stud. 14(1), 15–28 (2014)

    Article  Google Scholar 

  21. Delfabbro, P., King, D.: Prevention paradox logic and problem gambling: Does low-risk gambling impose a greater burden of harm than high-risk gambling? J. Behav. Addict. 6(2), 163–167 (2017)

    Article  PubMed  PubMed Central  Google Scholar 

  22. Browne, M., Rockloff, M.J.: The dangers of conflating gambling-related harm with disordered gambling: Commentary on: Prevention paradox logic and problem gambling (Delfabbro & King, 2017). J. Behav. Addict. 6(3), 317–320 (2017)

    Article  PubMed  PubMed Central  Google Scholar 

  23. Delfabbro, P., King, D.L.: Don’t say the ‘P’Word: problem gambling is more than harm. Int. J. Ment. Heal. Addict. 18(3), 835–843 (2020)

    Article  Google Scholar 

  24. Currie, S.R., Miller, N., Hodgins, D.C., Wang, J.: Defining a threshold of harm from gambling for population health surveillance research. Int. Gambl. Stud. 9(1), 19–38 (2009)

    Article  Google Scholar 

  25. Gallet, C.: Gambling demand: a meta-analysis of the price elasticity. J. Gambl. Bus. Econ. 9(1), 13–22 (2015)

    Article  Google Scholar 

  26. Tirole, J.: The theory of industrial organization. MIT Press (1988)

    Google Scholar 

  27. Allen consulting group. Social and economic impact study of gambling in Tasmania. Volume 1: Gambling industry and economic impacts. Prepared for the Tasmanian Government Department of Treasury and finance (2011)

  28. Chambers, K.G.: Gambling for profit. University of Toronto Press (2017)

    Google Scholar 

  29. Fiedler, I., Kairouz, S., Costes, J.M., Weißmüller, K.S.: Gambling spending and its concentration on problem gamblers. J. Bus. Res. 98, 82–91 (2019)

    Article  Google Scholar 

  30. Slutske, W.S.: Longitudinal studies of gambling behavior. In: Smith, G., Hodgins, D.C., Williams, R.J. (eds.) Research and measurement issues in gambling studies, pp. 127–154. Academic Press, Burlington, MA (2007)

    Google Scholar 

  31. Toce-Gerstein, M., Gerstein, D.R., Volberg, R.A.: A hierarchy of gambling disorders in the community. Addiction 98, 1661–1672 (2003)

    Article  PubMed  Google Scholar 

  32. Wood, R.T., Williams, R.J.: ‘How much money do you spend on gambling?’ The comparative validity of question wordings used to assess gambling expenditure. Int. J. Soc. Res. Methodol. 10(1), 63–77 (2007)

    Article  Google Scholar 

  33. Heirene, R.M., Wang, A., Gainsbury, S.M.: Accuracy of self-reported gambling frequency and outcomes: comparisons with account data. Psychol. Addict. Behav. 36(4), 333–346 (2022)

    Article  PubMed  Google Scholar 

  34. Auer, M., Griffiths, M.D.: Self-reported losses versus actual losses in online gambling: an empirical study. J. Gambl. Stud. 33(3), 795–806 (2017)

    Article  PubMed  Google Scholar 

  35. Braverman, J., Tom, M.A., Shaffer, H.J.: Accuracy of self-reported versus actual online gambling wins and losses. Psychol. Assess. 26(3), 865–877 (2014)

    Article  PubMed  Google Scholar 

  36. Productivity Commission. Gambling (Inquiry Report No. 50). (2010). https://www.pc.gov.au/inquiries/completed/gambling-2010/report

    Google Scholar 

  37. James, R.J., O’Malley, C., Tunney, R.J.: Why are some games more addictive than others: the effects of timing and payoff on perseverance in a slot machine game. Front. Psychol. 7, 46 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We are very grateful to Jean-Michel Costes for his help to access the primary data. We also would like to thank the two anonymous reviewers for their very constructive comments that helped improve this manuscript.

Funding

This research received funding from the French Monitoring Centre for Gambling. This institution had no role in the study design, writing of the report or in the decision to submit the article for publication.

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Correspondence to Sophie Massin.

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Appendix

Appendix

See Tables 11, 12 and 13.

Table 11 Available estimates for the price elasticity of demand (international meta-analysis [25])
Table 12 Calibration of the price elasticity of supply using data at the sector level (amounts in million €; year 2019)
Table 13 Components of surplus for problem gamblers (amounts in million €; year 2019)

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Miéra, M., Massin, S. & Eroukmanoff, V. The social value of gambling: surplus estimates by gambling types for France. Eur J Health Econ 24, 1531–1543 (2023). https://doi.org/10.1007/s10198-022-01560-9

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