Profiling Excluders from German Casinos using Municipality Level Data

Abstract

Gambling is not a totally undisputed way to spend leisure time. While most people pursue their play instinct only from time to time, some happen to lose control over their urge and develop a problematic or even pathological gambling behavior. Getting excluded can be a way to regain control and minimize harm for affected gamblers. In comparison to the majority of other work dealing with this topic, not individual level information was used, but higher aggregated municipality level data. The goal of this paper was to analyze in what way sociodemographic factors and proximity measures can be used to explain the variation in the number of excluded gamblers across German communities. For that purpose, a unique dataset with 3,091 observations containing information about the number of excluders as well as census data and spatial information has been created. The method used for estimation of the effects was OLS. The results of the study suggested that excluders are more likely to be male, between 30 and 39 years old and less likely to be single. Due to flaws in the data, the other sociodemographic factors did not yield significant associations. Additionally, the number of exclusions increases with close proximity to gambling establishments. The distance to the closest casino has a negative impact on exclusions. This is backed up by the finding that there are relatively more exclusions in communities where casinos are directly located.