Abstract
The so-called Shift-Share-Regression is used to analyse the development of employment. This does not imply a deterministic decomposition such as in classical Shift-Share-Analysis (Dunn 1960; Loveridge and Selting 1998). Instead, Shift-Share-Regression is a powerful and flexible econometric tool, which is especially suitable for testing theory-based hypotheses. In a basic version it was introduced by Patterson (1991) as a method for analysing and testing regional industrial developments. In contrary to the deterministic Shift-Share-Analysis employment development was examined in a linear model. In Patterson’s analysis the industrial sector structure was used as the sole determining factor alongside the location effects and the national trend, parallel to those of the deterministic analysis. Möller and Tassinopoulos (2000) extended Patterson’s approach by an additional variable for regional concentration. Further theory-based influences were then integrated in various IAB analyses (Blien and Wolf 2002). Some results of these studies are presented below, following an overview of the method.
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Notes
- 1.
The analyses of the federal states were published in 2006 in issues 11 and 12 of the journal “Sozialer Fortschritt” (volume 55). A special analysis was dedicated to Bavaria which could be regarded as a brief predecessor (with a shorter data base from 1993 to 2001) of the analysis presented here (Eigenhüller 2006; see also Böhme and Eigenhüller 2005).
- 2.
The sectoral classification is based on the NACE classification (revision 1.1), with the exception of Group KA at the level of double letters, which remained almost identical to other industrial classifications (WZ93 and WZ03 in Germany). Additionally, a distinction is made between simple, scientific (or higher valued) corporate services and temporary work in the KA group, due to their heterogeneous structure.
- 3.
The positive effect may indicate that not only low-skilled employees are in this category, but also persons from all qualification levels, including highly qualified. This assumption is confirmed by analyses that examine the occupations of those whose “qualifications are unknown”. This not only includes unskilled labour.
- 4.
In forming the class categories, the starting point was the mean value for all West German districts, and a half and one standard deviation was added or subtracted to each.
- 5.
Buch et al. (2010) demonstrate, for example, that Munich shows the most positive migration balance for highly qualified employees among large German cities with more than 500,000 inhabitants. The migration balance for this qualification group is also positive for Nuremberg, but to a much smaller degree than for Munich.
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Annex
Annex
Employment development 1993–2008 (annual average growth rate in %)
Influence of the sectoral determinant in Bavarian districts
Influence of the establishment size determinant in Bavarian districts
Influence of the qualification determinant in Bavarian districts
Influence of the location determinant in Bavarian districts
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Blien, U., Eigenhüller, L., Promberger, M., Schanne, N. (2014). The Shift-Share Regression: An Application to Regional Employment Development in Bavaria. In: Kourtit, K., Nijkamp, P., Stimson, R. (eds) Applied Regional Growth and Innovation Models. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37819-5_6
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