Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/158593
Authors: 
Haas, Anette
Rothe, Thomas
Year of Publication: 
2005
Citation: 
[Journal:] Zeitschrift für ArbeitsmarktForschung – Journal for Labour Market Research [ISSN:] 2510-5027 [Volume:] 38 [Year:] 2005 [Issue:] 1 [Pages:] 49-67
Abstract (Translated): 
In recent years analyses based on flow quantities have become more significant both in research and in policy advice. This paper presents the multiple accounts model, designed by us, which depicts regional transition processes in all employment offices in matrix form, and can therefore also be interpreted as a regionalised population and labour force account. For the data basis, official individual data about employees, the unemployed and participants in employment and training schemes are combined with aggregate data containing information about school pupils, the self-employed and the retired. In order to estimate missing transition information, the new algorithm ADETON is used, which has the advantage over other entropy optimisation methods that it is also possible to work with inexact boundary conditions. The advantages and possible applications of the multiple accounts model are shown using three examples. The general aims of the multiple accounts model are to record the dynamics of the local labour market, to facilitate comparisons between the regions and to create a basis for the future strategic orientation of active labour market policy. On the one hand it is an instrument that can be used flexibly for scientific analyses of regional labour markets in Germany, and on the other hand it can be used by the respective employment offices for diverse questions.
Subjects: 
regionaler Arbeitsmarkt
Stromgrößenanalyse
Arbeitskräftegesamtrechnung
amtliche Statistik
Arbeitslosigkeit - Zu- und Abgänge
sozialversicherungspflichtige Arbeitnehmer - Zu- und Abgänge
sektorale Verteilung
Berufsausbildung
Ausbildungsabsolventen
Berufseinmündung
Ingolstadt
Bayern
Bundesrepublik Deutschland
Document Type: 
Article

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