Income-related inequality in gambling: evidence from Italy
Background: In line with a global trend, in the last decade there has been an expansion of gambling market in Italy, through a series of reforms that have considerably liberalised the gaming opportunities in both physical and virtual environments. Exceeded € 95 billion in 2016, the Italian gambling revenues represent, by far, the largest European gambling market. The continuous increase of the offer and variety of gambling products has been also associated with the increase in prevalence of problematic gambling observed (from 0.33 in 2007, to 1.04 in 2017 in the general population aged 15-64).
Purpose: This paper investigates the associations between the ranking based upon the person’s socioeconomic position and the choice of different type of games by means of income-related inequality measures. This allows investigating the socio-economic drivers of the engagement into the different gambling products, thereby allowing to identify pro-rich and pro-poor games.
Methods: Income-related inequality indices (Erreygers, 2009) are estimated for three macro-categories of games (traditional lotteries, betting, and new generation games). Our analysis is based on 13,121 individuals (n= 7,348 in 2014; 5,773 in 2017) participating in the 2014-2017 waves of the Italian Population Survey on Alcohol and other Drugs (IPSAD®) which is a national representative general population survey that also includes information on income and personal preferences for the different games of chance.
Results: 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 (males play more and have higher income), age (older people choose traditional games and are more well-off), and working condition (working people play more to traditional games and they have with higher income). Conversely, higher components of the pro-poor inequality observed in betting and new generation games come from income (low income people choose these games) and age (new games and betting games are more spread among younger people). These evidences remain substantially unchanged over the years (in 2014 and in 2017).
Conclusions: Since the pro-poor games are also the major contributors of the growth in gambling turnover and the increase in gambling disorders, our results suggest 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. These evidences could support effective public policies aimed at tackling the spread of pathological gambling through more targeted prevention programmes and treatment services and the growing inequality in health.