Review of Economics of the Household

, Volume 17, Issue 4, pp 1107–1131 | Cite as

Income-related inequality in gambling: evidence from Italy

  • Giuliano Resce
  • Raffaele Lagravinese
  • Elisa Benedetti
  • Sabrina MolinaroEmail author


In this paper we document the income-related inequality in gambling. We employ a novel database from 2014–2017 waves of the Italian Population Survey on Alcohol and other Drugs (IPSAD) which also include information on the preferences for games of chance. Following the Erryegers Index, our findings suggest that traditional lotteries are concentrated among the richest individuals, while betting and new generation games tend to be pro-poor games. The decomposition of income-related inequalities reveals that pro-rich inequality observed in traditional games is mainly driven by gender, age, and working condition. Higher components of the pro-poor inequality observed in betting and new generation games come instead from income and age. Since the pro-poor games are also the major contributors of the growth in gambling turnover and the increase in gambling disorders, our results indicate that a relevant part of increasing social costs associated to gambling are more likely to be paid by the less-well off, and potentially most vulnerable members of the society.


Income Gambling Inequality Italy 

JEL classifications

I12 I14 



The authors wish to thank Vincenzo Carrieri, Owen O’Donnell, Paul Makdissi and Paolo Liberati for their useful suggestions. Furthermore, the authors are in debt with the participants of the Winter School 2019, HEALTH, OPPORTUNITIES AND REDISTRIBUTION held at Canazei 6–10 January 2019.

Compliance with ethical standards

Conflict of interests

The authors declare that they have no conflict of interest.


  1. Ariyabuddhiphongs, V. (2011). Lottery gambling: a review. Journal of Gambling Studies, 27, 15–33.CrossRefGoogle Scholar
  2. Bastiani, L., Gori, M., Colasante, E., Siciliano, V., Capitanucci, D., Jarre, P., & Molinaro, S. (2013). Complex factors and behaviors in the gambling population of Italy. Journal of Gambling Studies, 29(1), 1–13.CrossRefGoogle Scholar
  3. Beckert, J., & Lutter, M. (2009). The inequality of fair play: lottery gambling and social stratification in Germany. European Sociological Review, 25(4), 475–488.CrossRefGoogle Scholar
  4. Beckert, J., & Lutter, M. (2013). Why the poor play the lottery: sociological approaches to explaining class-based lottery play. Sociology, 47(6), 1152–1170.CrossRefGoogle Scholar
  5. Buth, S., Wurst, F. M., Thon, N., Lahusen, H., & Kalke, J. (2017). Comparative analysis of potential risk factors for at-risk gambling, problem gambling and gambling disorder among current gamblers—results of the austrian representative survey 2015. Frontiers in psychology, 8, 2188.CrossRefGoogle Scholar
  6. Carrieri, V., Di Novi, C., & Orso, C. E. (2017). Home sweet home? Public financing and inequalities in the use of home care services in Europe. Fiscal Studies, 38(3), 445–468.CrossRefGoogle Scholar
  7. Carrieri, V., & Jones, A. M. (2016). Smoking for the poor and vaping for the rich? Distributional concerns for novel nicotine delivery systems. Economics Letters, 149, 71–74.CrossRefGoogle Scholar
  8. Carrieri, V., & Wübker, A. (2013). Assessing inequalities in preventive care use in Europe. Health policy, 113(3), 247–257.CrossRefGoogle Scholar
  9. Cavalera, C., Bastiani, L., Gusmeroli, P., Fiocchi, A., Pagnini, F., Molinari, E., & Molinaro, S. (2018). Italian adult gambling behavior: at risk and problem gambler profiles. Journal of gambling studies, 34(3), 647–657.CrossRefGoogle Scholar
  10. Cerrai, S., Resce, G., & Molinaro S. (2018). Consumi d’azzardo 2017 - Rapporto di Ricerca sulla diffusione del gioco d’azzardo fra gli italiani attraverso gli studi IPSAD® ed ESPAD® Italia, (a cura di) Cnr Edizioni, ISBN 978 88 8080 301 0.Google Scholar
  11. Clotfelter, C. T. (1979). On the regressivity of state-operated ‘numbers’ games. National Tax Journal, 32(4), 543–548.Google Scholar
  12. Clotfelter, C. T., & Cook, P. J. (1987). Implicit taxation in lottery finance. National Tax Journal, 40(4), 533–546.Google Scholar
  13. Clotfelter, C.T., & Cook, P.J. (1989). Selling hope. Cambridge, MA: Harvard University Press.Google Scholar
  14. Colasante, E., Gori, M., Bastiani, L., Siciliano, V., Giordani, P., Grassi, M., & Molinaro, S. (2013). An assessment of the psychometric properties of Italian version of CPGI. Journal of Gambling Studies, 29(4), 765–774.CrossRefGoogle Scholar
  15. Combs, K. L., Kim, J., & Spry, J. A. (2008). The relative regressivity of seven lottery games. Applied Economics, 40(1), 35–39.CrossRefGoogle Scholar
  16. Costa-Font, J., Hernández-Quevedo, C., & Jiménez-Rubio, D. (2014). Income inequalities in unhealthy life styles in England and Spain. Economics & Human Biology, 13, 66–75.CrossRefGoogle Scholar
  17. Coughlin, C. C., & Garrett, T. A. (2009). Income and lottery sales: transfers trump income from work and wealth. Public Finance Review, 37(4), 447–469.CrossRefGoogle Scholar
  18. Crowley, F., Eakins, J., & Jordan, D. (2012). Participation, expenditure and regressivity in the irish lottery: evidence from Irish household budget survey 2004/2005. The Economic and Social Review, 43(2), 199–225.Google Scholar
  19. Deans, E. G., Thomas, S. L., Daube, M., & Derevensky, J. (2016). “I can sit on the beach and punt through my mobile phone”: the influence of physical and online environments on the gambling risk behaviours of young men. Social Science & Medicine, 166, 110–119.CrossRefGoogle Scholar
  20. Di Bella, E., Gandullia, L., & Leporatti, L. (2015). The impact of gambling on government budget: a european comparison with a focus on Italy. International Economics, 68(2), 187–212.Google Scholar
  21. Doorslaer, E. V., Koolman, X., & Jones, A. M. (2004). Explaining income‐related inequalities in doctor utilisation in Europe. Health Economics, 13(7), 629–647.CrossRefGoogle Scholar
  22. D’Orazio, M. (2017). Statistical matching and imputation of survey data with StatMatch. R package version 1.2.5.
  23. Erreygers, G. (2009). Correcting the concentration index. Journal of Health Economics, 28(2), 504–515.CrossRefGoogle Scholar
  24. Farrell, L., & Walker, I. (1999). The welfare effects of lotto: evidence from the UK. Journal of Public Economics, 72(1), 99–120.CrossRefGoogle Scholar
  25. Ferris, J. A., & Wynne, H. J. (2001). The Canadian problem gambling index (pp. 1–59). Ottawa, ON: Canadian Centre on Substance Abuse.Google Scholar
  26. Friehe, T., & Mechtel, M. (2017). Gambling to leapfrog in status? Review of Economics of the Household, 15(4), 1291–1319.CrossRefGoogle Scholar
  27. Gandullia, L., & Leporatti, L. (2018). The demand for gambling in Italian regions and its distributional consequences. Papers in Regional Science, 97(4), 1203–1225.CrossRefGoogle Scholar
  28. Garrett, T. A., & Coughlin, C. C. (2009). Inter-temporal differences in the income elasticity of demand for lottery tickets. National Tax Journal, 62, 77–99.CrossRefGoogle Scholar
  29. Ghent, L. S., & Grant, A. P. (2010). The demand for lottery products and their distributional consequences. National Tax Journal, 63(2), 253.CrossRefGoogle Scholar
  30. Greco, S., Ishizaka, A., Matarazzo, B., & Torrisi, G. (2018). Stochastic multi-attribute acceptability analysis (SMAA): an application to the ranking of Italian regions. Regional Studies, 52(4), 585–600.CrossRefGoogle Scholar
  31. Grote, K. R., & Matheson, V. (2012). The economics of lotteries: a review of the literature. In L. V. Williams & D. Siegel (Eds), Oxford handbook on the economics of gambling. London: Oxford University Press.Google Scholar
  32. Guiso, L. (2016). Attenti a quei soldi: difendere le proprie finanze dagli altri e da sé stessi. EGEA spa.Google Scholar
  33. Haisley, E., Mostafa, R., & Loewenstein, G. (2008). Subjective relative income and lottery ticket purchases. Journal of Behavioral Decision Making, 21, 283–295.CrossRefGoogle Scholar
  34. Hansen, A. (1995). The tax incidence of the Colorado state lottery instant game. Public Finance Quarterly, 23, 385–398.CrossRefGoogle Scholar
  35. ISTAT (2018). Indagine su reddito e condizioni di vita (EU-SILC). RomaGoogle Scholar
  36. Kearney, M. S. (2005). State lotteries and consumer behavior. Journal of Public Economics, 89(11–12), 2269–2299.CrossRefGoogle Scholar
  37. Khaled, M. A., Makdissi, P., Tabri, R. V., & Yazbeck, M. (2018). A framework for testing the equality between the health concentration curve and the 45‐degree line. Health economics, 27(5), 887–896.CrossRefGoogle Scholar
  38. Kjellsson, G., & Gerdtham, U. G. (2013). On correcting the concentration index for binary variables. Journal of Health Economics, 32(3), 659–670.CrossRefGoogle Scholar
  39. Korn, D. A. (2000). Expansion of gambling in Canada: implications for health and social policy. Canadian Medical Association Journal, 163(1), 61–64.Google Scholar
  40. Lagravinese, R., Liberati, P., & Resce, G. (2019). Exploring health outcomes by stochastic multicriteria acceptability analysis: an application to Italian regions. European Journal of Operational Research, 274(3), 1168–1179.CrossRefGoogle Scholar
  41. Laitner, J. (1999). Means-tested public assistance and the demand for state lottery tickets. Economic Dynamics, 2(1), 273–290.CrossRefGoogle Scholar
  42. Layton, A., & Worthington, A. (1999). The impact of socio-economic factors on gambling expenditure. International Journal of Social Economics, 26(1-2-3), 430–440.CrossRefGoogle Scholar
  43. Liberati, P. (2003). Fiscal federalism and national health standards in Italy: implications for redistribution. I sistemi di welfare tra decentramento regionale e integrazione europea. Franco Angeli, 241–273.Google Scholar
  44. Ljungvall, Å., & Gerdtham, U. G. (2010). More equal but heavier: a longitudinal analysis of income-related obesity inequalities in an adult Swedish cohort. Social Science & Medicine, 70(2), 221–231.CrossRefGoogle Scholar
  45. Madhusudhan, R. G. (1996). Betting on casino revenues: lessons from state experiences. National Tax Journal, 49, 401–412.Google Scholar
  46. Markham, F., Doran, B., & Young, M. (2016). The relationship between electronic gaming machine accessibility and police-recorded domestic violence: a spatio-temporal analysis of 654 postcodes in Victoria, Australia, 2005–2014. Social Science & Medicine, 162, 106–114.CrossRefGoogle Scholar
  47. Molinaro, S., Benedetti, E., Scalese, M., Bastiani, L., Fortunato, L., Cerrai, S., … & Fotiou, A. (2018). Prevalence of youth gambling and potential influence of substance use and other risk factors throughout 33 European countries: first results from the 2015 ESPAD study. Addiction, 113(10), 1862–1873.Google Scholar
  48. Olason, D. T., Kristjansdottir, E., Einarsdottir, H., Haraldsson, H., Bjarnason, G., & Derevensky, J. L. (2011). Internet gambling and problem gambling among 13 to 18 year old adolescents in Iceland. International Journal of Mental Health and Addiction, 9(3), 257–263.CrossRefGoogle Scholar
  49. O’Donnell, O., Van Doorslaer, E., Wagstaff, A., & Lindelow, M. (2007). Analyzing health equity using household survey data: a guide to techniques and their implementation. The World Bank, Washington, DC.Google Scholar
  50. Paton, D., Siegel, D. S., & Vaughan Williams, L. (2009). The growth of gambling and prediction markets: economic and financial implications. Economica, 76(302), 219–224.CrossRefGoogle Scholar
  51. Perez, L., & Humphreys, B. R. (2011). The income elasticity of lottery: new evidence from micro data. Public Finance Review, 39, 551–570.CrossRefGoogle Scholar
  52. Pickernell, D., Brown, K., Worthington, A., & Crawford, M. (2004). Gambling as a base for hypothecated taxation: the UK’s national lottery and electronic gaming machines in Australia. Public Money & Management, 24(3), 167–174.CrossRefGoogle Scholar
  53. Quiggin, J. (1991). On the optimal design of lotteries. Economica, 59(229), 1–16.CrossRefGoogle Scholar
  54. Rivenbark, W. C., & Rounsaville, B. B. (1996). The incidence of casino gambling taxes in Mississippi: setting the stage. Public Administration Quarterly, 20(2), 129–142.Google Scholar
  55. Sarti, S., & Triventi, M. (2012). Gambling: the iniquity of a voluntary tax. The relationship between socio-economic position and propensity of gambling. Stato e mercato, Società editrice il Mulino. 3, 503–534.Google Scholar
  56. Scalese, M., Bastiani, L., Salvadori, S., Gori, M., Lewis, I., Jarre, P., & Molinaro, S. (2016). Association of problem gambling with type of gambling among Italian general population. Journal of Gambling Studies, 32(3), 1017–1026.CrossRefGoogle Scholar
  57. Scott, F., & Garen, John (1994). Probability of purchase, amount of purchase, and the demographic incidence of the lottery tax. Journal of Public Economics, 54, 121–143.CrossRefGoogle Scholar
  58. Smith, J. (2000). Gambling taxation: public equity in the gambling business. The Australian Economic Review, 33, 120–144.CrossRefGoogle Scholar
  59. Suits, D. B. (1977). Gambling taxes: regressivity and revenue potential. National Tax Journal, 30(1), 19–35.Google Scholar
  60. Szakmary, A., & Szakmary, C. M. (1995). State lotteries as a source of revenue: a reexamination. Southern Economic Journal, 61, 1167–1181.CrossRefGoogle Scholar
  61. UPB (Parliamentary Budget Office). (2018) La fiscalità nel settore dei giochi. Focus tematico n. 6/3 maggio 2018. Rome.Google Scholar
  62. Wagstaff, A., Paci, P., & Van Doorslaer, E. (1991). On the measurement of inequalities in health. Social Science Medicine, 33(5), 545–557.CrossRefGoogle Scholar
  63. Worthington, A. C. (2001). Implicit finance in gambling expenditures: Australian evidence on socioeconomic and demographic tax incidence. Public Finance Review, 29, 326–342.CrossRefGoogle Scholar
  64. Worthington, A., Brown, K., Crawford, M., & Pickernell, D. (2007). Gambling participation in Australia: findings from the national household expenditure survey. Review of Economics of the Household, 5(2), 209–221.CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Institute of Clinical Physiology (IFC)Italian National Research Council (CNR)RomeItaly
  2. 2.Department of Economics and FinanceUniversità di Bari “A.Moro”BariItaly

Personalised recommendations