In Germany, gambling research has primarily focused on the broader population in prevalence studies, neglecting the importance and influence of the local socioeconomic context in the development and maintenance of gambling disorders. To analyze the interplay between contextual and compositional factors in the market for electronic gambling machines (EGMs) in Germany, we assessed the EGM densities and socioeconomic deprivation in 244 local communities within Baden-Wuerttemberg. Our results suggest that EGM density is statistically associated with 3 socioeconomic determinants: The shares of migrants, unemployed, and high-school-educated people in the communities are statistically significant variables in our linear regression model, whereas younger age, male gender, and marital status exhibit no statistical associations with EGM density. The share of unemployed people is the only variable of statistical and practical significance. Our analysis advocates area-based policy measures to minimize gambling-related harm. By decreasing EGM densities in communities with high levels of unemployment, we expect to protect at-risk population strata that are most vulnerable to gambling exposure.

Decision‐makers in the agricultural sector operate in a volatile and risky environment. The statistical assessment of agricultural commodity prices is necessary to deduce the stylised facts of agricultural markets and guide the action of market participants. This article examines the kurtosis values of 60 agricultural commodities and presents evidence that the distributions of their returns are fat‐tailed. We use power‐law distributions to model the tail returns and the possible time‐varying extreme event risks in commodity markets. Our results suggest that the usefulness of the value at risk and expected shortfall as risk management tools is questionable.

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