How important are plant and regional characteristics for labor demand? Plant-level evidence for Germany - Michaela Fuchs; Udo Brixy (European Regional Science Association (ERSA), 2010)
Empirical research on agglomeration and regional economic growth puts high emphasis on the impact of specialization, diversity, and competition on regional employment dynamics (Glaeser et al. 1992, Henderson et al. 1995, Blien et al. 2006, Fuchs 2009). However, Beugelsdijk (2006) and Raspe/van Oort (2008) argue that this relationship should most profoundly hold at the micro or firm level. This paper centres on the labour demand of individual plants and assesses the influence of regional features in direct contrast to plant-specific characteristics as well as conventional labour-demand determinants. Hence, it contributes to the sparse literature on the importance of regional character-istics for firm performance and additionally integrates research from industrial as well as labour economics. The analysis is based on the IAB Establishment Panel, a comprehensive data set on German plants. For the years from 2004 to 2008 it encompasses observations on roughly 8,000 plants. The regional variables are added on the NUTS3-level. First econometric results confirm the basic hypotheses derived from labour-demand theory: wages exert a significantly negative and output a positive influence on the number of employees. Among the plant-specific characteristics, it is mainly plant size, exporting behaviour and R&D / innovation activities that foster employment. There are also distinctive differences regarding the single sectors. Last but not least, the regional environment plays a decisive role for plant-level labour demand. The size of the region the plant is located in, the degree of sectoral concentration as well as of competition within a sector have a positive and highly significant impact. By contrast, accessibility to highways, specialization, and diversity seem to be of minor relevance
Keywords: J23; L25; R10; 330; firms; labor demand; agglomeration externalities; panel data methods