Self-employment career patterns in the Netherlands:exploring individual and regional differences
Although the self-employed represent 16.7% of the Dutch labor force (OECD 2020), their internal heterogeneity in profiles regarding motivations, characteristics and career trajectories remains unclear. Yet, understanding self-employment profiles and their spatial distribution may help understand differences in career progression of the self-employed. This study identifies and describes patterns in long-term career trajectories of the Dutch self-employed, and it explores spatial differences along the urban hierarchy. The study uses a life-course approach and register data of the whole populatio... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2023 |
Reihe/Periodikum: | Bay , F & Koster , S 2023 , ' Self-employment career patterns in the Netherlands : exploring individual and regional differences ' , The Annals of Regional Science , vol. 71 , pp. 601–625 . https://doi.org/10.1007/s00168-022-01139-5 |
Schlagwörter: | self-employment / Career patterns / SEQUENCE-ANALYSIS |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28778940 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://hdl.handle.net/11370/6af431d8-108c-427d-bbf7-2d54fb54ef1f |
Although the self-employed represent 16.7% of the Dutch labor force (OECD 2020), their internal heterogeneity in profiles regarding motivations, characteristics and career trajectories remains unclear. Yet, understanding self-employment profiles and their spatial distribution may help understand differences in career progression of the self-employed. This study identifies and describes patterns in long-term career trajectories of the Dutch self-employed, and it explores spatial differences along the urban hierarchy. The study uses a life-course approach and register data of the whole population to find common patterns of careers among a sample of Dutch self-employed (N = 42,028) and their spatial distribution. We investigated careers through sequence and cluster analysis of individuals’ socio-economic statuses between 2003–2018. The analysis identifies 7 career clusters that collapse into three main career profiles: Mixed self-employment careers that combine self-employment with wage-employment, stable self-employment, and precarious self-employment. The clusters differ importantly in terms of the individual characteristics of the self-employed including age, gender, educational level and income. In terms of spatial distribution, the study shows that self-employment career profiles follow the urban hierarchy. Urban regions give way to all types of self-employment, while rural regions mainly exhibit stable self-employment. Precarious self-employment presents differently in urban and rural areas; in urban labor markets, we find self-employed individuals vulnerable to economic shocks, losing their jobs as a consequence of the financial crisis in 2007/08. In rural regions, formerly inactive workers become self-employed following the crisis.