This study examines differences in benefit receipt using an intersectional approach. Intersectionality theory highlights the importance of the interplay of multiple social dimensions. Therefore, this article examines how different combinations of three demographic variables plus education buffer or amplify benefit receipt and thereby create relatively advantaged and disadvantaged groups. Administrative data were used, sourced from Dutch registers, which provide accurate and detailed information about benefit receipt on the entire Dutch population, including segments that are small and harder to reach. Multilevel Analyses of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) are performed to assess which intersectional groups are relatively advantaged or disadvantaged with respect to benefit receipt. Intersectional group differences are more pronounced for social assistance than for unemployment insurance. Complex combinations of education, gender, age and migration background are required to better understand differences in benefit receipt, especially for unemployment insurance.

No abstract