Socioeconomic correlates of the lottery rollover effect in Toronto, Canada

In a lottery with a progressive jackpot, the rollover effect refers to an increase in revenue or engagement with an accumulating jackpot size. Using an ecological dataset of lottery ticket sales aggregated by postcode, we test two corollaries of the rollover effect. First, how does the rollover effect change in neighborhoods with higher or lower socioeconomic status? Second, how do fluctuations on a progressive-prize lottery affect the consumption of fixed-prize lottery tickets in the same neighborhoods, in line with economic notions of ‘substitution’ versus ‘complementarity’? We used time-series data on ticket sales from 2012-2015 from 3 progressive-prize lotteries (Lotto 649, Lotto Max, and Lottario) in Toronto, Canada, aggregated for 95 forward-sortation area (FSA) postcodes. Regression models controlled for other cyclical fluctuations including day of week, month of year, and common paydays. Jackpot size positively predicted lottery ticket sales in all models, with a large effect size. There was a significant interaction between jackpot size and neighborhood SES, such that lottery sales in higher SES neighborhoods were more sensitive to jackpot size, although the effect sizes were negligible. Sales of fixed-prize lotteries were positively related to sales of progressive-prize lotteries, supporting complementarity. We observed a significant interaction between SES and progressive-prize sales, in which fixed-prize sales were more affected by progressive-prize sales in higher SES neighborhoods. Both the effect of larger jackpots on ticket sales, and the effects of progressive-prize sales on a second lottery type, are attenuated within more disadvantaged (i.e. lower SES) neighborhoods.</p

Overview of the Ultimatum Game (a) and the relationship of PA and NA with rejection behaviour (b).

<p>(<b>a</b>) On each of 20 trials participants attend to a fixation cross for 10 s, view a picture of the proposer or the computer for 10 s, the offer is presented for 10 s, and the participant then decides to accept or reject the offer. Feedback is presented for 10 s. (<b>b</b>) Relationship of PA and NA to the proportion of unfair offers that are rejected. As PA increases, participants reject more unfair offers. As NA increases, participants reject fewer unfair offers.</p

Summary of key study variables.

<p>Anger rated on a scale from 0 (not at all) to 100 (extremely).</p

Relationships between Ultimatum Game rejection rates, trait emotionality, and retrospective anger ratings.

<p>Rejection rates are percentages of each offer type refused. Proposals  =  mean offers made to other players. Anger unfair  =  average retrospective anger ratings of human and computer unfair offers. Relationships are assessed using Pearson's correlation co-efficient. *  =  significant at P<.05. **  =  significant at P<.01.</p

Relationships between individual PANAS items and rejection rates on the Ultimatum Game.

<p>Relationships are assessed using Pearson's correlation co-efficient. +  =  trend significant at P<.10; *  =  significant at P<.05; **  =  significant at P<.01.</p

Cognitive distortions and gambling near-misses in Internet Gaming Disorder: A preliminary study

The raw data from the slot machine tas

Subjective ratings in the slot machine task.

<p>(A) Liking ratings for wins, near-misses and full-misses; (B) Motivational ratings for wins, near-misses and full-misses; (C) Liking ratings for near-miss before, near-miss after and full-misses; (D) Motivational ratings for near-miss before, near-miss after and full-misses.</p

Demographic and behavioral characteristics of individuals with IGD and healthy control subjects. Mean (SD).

<p>Demographic and behavioral characteristics of individuals with IGD and healthy control subjects. Mean (SD).</p

Group differences on the GRCS, mean (SD).

<p>Group differences on the GRCS, mean (SD).</p

Time course of the slot machine task.

<p>Time course of the slot machine task.</p