Trajectories are clustered using Ward’s (1963) hierarchical agglomerative algorithm (cf. Quintini and Manfredi, 2009). A number of seven different clusters per data source is imposed, resulting from a trade-off between the greatest possible homogeneity of trajectories within the cluster and the desired differentiability between clusters. Clustered trajectories are matched with information on individual and household characteristics used for the analyses.