Modelling reallocation processes in long-term labour market projections - Tobias Maier; Caroline Neuber-Pohl; Anke Mönnig; Gerd Zik; Michael Kalinowski (Journal for Labour Market Research, 2017)
Long-term labour market projections are a popular tool for assessing future skill needs and the possibility of skill shortages. It is often noted that reallocation processes in the German labour market are hindered due to its strong standardization and occupational segmentation. However, it is possible that persons leave the occupation for which they have been trained for. Disregarding such reallocations and their dynamics in the projection model is likely to distort the results and lead to inaccurate practical advice. In this article, we describe for the first time, how reallocations in the labour market can be modelled using occupational flexibility matrices and wage dynamics. Here, it is shown that employers react to labour scarcity by increasing wages to attract workers who to some extent can adjust their mobility behaviour accordingly. We analyse the aggregate impact of this implementation of a reallocation process of labour supply on the projection results by the means of scenario comparisons. Our results suggest that considering reallocations but also additionally their dynamics has substantial effects on the projection outcomes. They help draw an insightful picture of the future labour market and prevent over- or understating the potential for labour shortages in several occupations. We conclude that the assumptions about how reallocations differ by occupation and to what extent they can be realized by wage impulses is essential for projection results and their interpretation. Furthermore, we find that in the German labour market, wage adjustments cannot balance the labour demand and supply for occupations completely. – – Wir entwickeln eine neue Methode zur Identifizierung verheirateter Paare in administrativen Daten. Mittels Adressdaten und Nachnamen der Gesamtheit der Beschäftigungsmeldungen in Deutschland, identifizieren wir ca. 3,3 Millionen Paare von Personen die an der gleichen Adresse wohnen, deren Nachnamen übereinstimmen, und einen Altersabstand von weniger als 15 Jahren haben. Wir zeigen mittels verschiedener Konsistenzchecks, dass ca. 89 bis 94 Prozent dieser Paare tatsächlich verheiratete Paare sind. Anhand von Informationen des Mikrozensus, zeigen wir, dass unsere Methode etwa 17 Prozent aller verheirateten Paar in Deutschland identifiziert und ca. 35 Prozent aller Paare bei denen beide Partner in sozialversicherungspflichtiger Beschäftigung oder arbeitslos sind. Der Paarindikator wird der Forschungsgemeinschaft und Nutzern der IAB Daten zur Verfügung gestellt. Unsere Methode eröffnet damit neue Forschungsmöglichkeiten für Haushaltsanalysen die von der Präzision und großen Beobachtungszahlen von administrativen Daten profitieren.
Keywords: I25; J20; J21; J22; J23; J24; O11; O15; 330; Labour market; Projections; Germany; Occupational mobility; Education; Wage development