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Review of Regional Research

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01.02.2013 | Original Paper

The impact of regional location factors on job creation, job destruction and employment growth in manufacturing

verfasst von: Raimund Krumm, Harald Strotmann

Erschienen in: Review of Regional Research | Ausgabe 1/2013

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Abstract

Regions are exposed to intensive competition to provide the most attractive location conditions for firms and their employees. Therefore, regional employment development depends to a decisive degree on the attractiveness of regional location factors. Based upon the creation of establishment-level panel data from Official Statistics for manufacturing in Baden-Wuerttemberg, Germany, from 1980 to 1999 this paper gives an empirical analysis of the impact of regional location conditions on regional manufacturing employment growth. In particular, the paper examines whether the impact of regional location conditions on regional net employment growth is driven by the underlying gross components job creation and/or job destruction.

The results indicate that lower regional costs of production and a better regional endowment with skilled labour and R&D promote manufacturing employment growth. Thereby, lower costs of production as measured by a lower wage level stimulate employment growth by decreasing gross job destruction, while a better human capital endowment and a higher regional R&D intensity enhance employment growth by higher rates of gross job creation. Regions characterised by a smaller average firm size in manufacturing experienced higher manufacturing employment growth both by higher rates of job creation and lower rates of job destruction. On the other hand population density stimulates job creation as well as job destruction which lead to a zero effect on the scale of net employment change—indicating a compensation effect “behind the scenes”. Otherwise, the analysis reveals the tendency for regional location factors to influence either only gross job creation or only gross job destruction, but seldom both sides at the same time.

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For a small selection of the respective empirical papers covering various regional location factors, see Grek et al. (2011), Gauselmann et al. (2011), Arent and Steinbrecher (2010), Arauzo-Carod (2005), Audretsch and Dohse (2007), Devereux and Griffith (1998), or Hoogstra and van Dijk (2004). Referring to a decision-making support for the regional economic policy based on empirical analyses on regional location factors, see Goebel and Hamm (2010) for instance.

This was currently again confirmed by the empirical analysis of Fukao et al. (2011) who stress the importance of land prices and wage rates for the location choice of firms.

As discussed later, regional wages also have a demand-side aspect, but the net effect of the wage costs on regional manufacturing employment can usually be expected to be negative because the cost impact usually dominates the purchasing power impact. For current papers referring to this topic, see e.g. Suedekum and Blien (2007), Pierluigi and Roma (2008).

See the model of Alonso (1960), for instance, that deals with the relevance of land prices for location choices of firms.

See Kohlhase and Ju (2007) for the impact of property taxes on location decisions of firms. However, one must not neglect the fact that regional or local taxes can be used to finance public goods such as traffic infrastructure. See Gabe and Bell (2004), who show that a high provision of local public goods that goes along with high local tax rates possibly attracts more firms than in the case when both parameters are low.

Cheng (2006) analyses the relative role of human capital and wages and argues that high quality of human capital over-compensates for the significance of high wages.

Therefore, R&D policy may foster regional employment growth. In this context, Koo and Kim (2009) emphasise that such a policy only works if it does not neglect the specific regional environment, such as the regional industry structure. In addition, a R&D policy aimed at regional employment growth should distinguish between different types of subsidised R&D activities, as Koski (2008) points out. A discussion of the connection between location and innovation can also be found in a survey article of Feldmann (2000).

See, e.g., Coughlin and Segev (2000), De Vor and de Groot (2009), or Jiwattanakulpaisarn et al. (2008), each of the latter analyse the significance of highway infrastructure for regional employment growth. The effect of traffic congestion on employment growth is analysed by Hymel (2009).

Redding (2010) gives an overview about the empirics of the New Economic Geography in addition to the broad theoretical literature to this approach.

This is line with an overview of Feldmann (2000) who cites studies both for urbanisation economies and others for urbanisation diseconomies.

Strotmann (2007) analyses the impact of regional agglomeration on new-firm survival in German manufacturing and shows that the risk of failure of start-ups in agglomerated regions is about 30 % higher than the corresponding risk in rural areas.

According to Glaeser et al. (1992) localisation economies are also called Marshall-Arrow-Romer (MAR) externalities (in contrast to Jacobs externalities which stands for urbanisation economies, see Feldmann 2000). For localisation economies, see, among others, the empirical study by Hoogstra and van Dijk (2004). For aspects with regard to localisation economies calculated using direct measures of physical distances between pairs of firms rather than with respect to pre-specified geographical units, see, e.g., Cainelli and Lupi (2011).

See Almeida (2007) for selected aspects referring to economic structure and regional development, and Drucker (2009) for associations between industrial concentration and regional employment growth.

In some studies aspects of the industry structure are included by a shift-share analysis, see for instance Möller and Tassinopoulos (2000) and Suedekum et al. (2006).

Schettkat and Yocarini (2006) provide a review of the literature referring to the employment shift from the manufacturing to the service sector. This includes aspects of outsourcing as well as inter-industry shifts in final demand.

Baden-Wuerttemberg is one of the largest German states (Bundeslaender). In 2010, it accounted for more than 13 % of the German population, 14.5 % of German GDP, and 16.0 % of German exports. In addition, the state is host to the headquarters of a variety of global players like the Daimler AG or Robert Bosch GmbH for instance. Its GDP is larger than that of countries such as Sweden, Denmark, or Austria. The manufacturing sector which is analysed in this paper, is of above-average importance in Baden-Wuerttemberg, accounting for 31.4 % of total employment (Germany: 24.4 %) and 36 % of gross value added (Germany: 27.9 %, see Regional Accounts VGRdL 2011).

Handcraft firms with fewer than twenty employees are not included in German official statistics for manufacturing.

Data for small establishments with less than 20 employees are no longer available in Official German Statistics since the beginning of the 2000s. Therefore, the time period for the analyses in this paper has been limited to the time period from 1980 to 1999.

For descriptive statistical analysis referring to net employment changes and the underlying gross job creation and gross job destruction, see Wagner (1995) and Essletzbichler (2004) who analyse the situation in Germany and the United States, respectively.

In contrast to our analysis of location factors on the county-level, i.e., the regional scale, the approach of Arauzo-Carod (2005) is geared to the local scale.

Because unit labour cost data were not available, we could not consider potential interregional differences in labour productivity. With regard to the aspect of labour productivity as a determining factor of unit labour costs and to its impact on employment changes see Suedekum et al. (2006) for instance. There you can find a two-step procedure to overcome the problem of missing productivity data.

The significance of human capital for the economic success and the employment development of firms is also shown by the Human Capital Externalities Theory. According to the HCE approach additional skilled employees can contribute not only directly to their firm’s productivity but also indirectly by increasing the productivity of other employees through informal learning. With regard to HCE approach see for instance Heuermann et al. (2010, p. 756).

We would prefer to take R&D investments instead of R&D employment, but such data are not available on a yearly basis.

Referring to business cycle aspects of regional job creation and job destruction, see Böckermann et al. (2004).

The effects of various local supply- and demand-side conditions on employment growth in the producer service sector rather than in the manufacturing sector are analysed by Di Giacinto and Micucci (2007).

In 1989 a substantial number of firms have been added to the data due to corrections of the basic population and there were substantial changes in the basic population from 1994 to 1995 due to changes in the classification of industries. We therefore exclude the net employment change and the corresponding gross job flows for periods 1998/89 and 1994/95 from our analyses.

As for some of the variables data are not available for the early 1980s the number of total observations partly varies between variables considered.

Results for the tests are available upon request.

Referring to this local tax on profit and real capital, see Zimmermann (1999: 183).

This can even hold within a single study. Brixy and Fuchs (2010) for instance find that population density does not influence labour demand in Western Germany. On the other side there is a significant impact in Eastern Germany—but with different signs depending on whether there is a short- or a long-run framework.

Referring to newer studies especially to Germany testing localisation economies as determinants of regional or local employment changes, see Fuchs (2011), Illy et al. (2011) and Blien et al. (2006) for instance.

As the indicators of job creation and job destruction are defined such that they cannot be negative we alternatively estimated regression models with the natural logarithm of job creation and job destruction rates as the dependent variables. As the results are stable we only present estimations for original job creation and job destruction rates.

From a theoretical point of view one would expect that high tax rates correlate with high job destruction. This is why the respective tax base included (until 1996) not only profits but also real capital. Therefore, firms had to pay taxes even in times they suffered losses, periods which often coincide with times of job destruction. But in the analysis at hand the impact of the tax rates on job destruction does not reach a significant level.

This is in line with the concept of Florida (2002) who points out the importance of the so-called “creative class” for the economic success of firms. According to Florida the firms do not only consider traditional location factors but also “soft” environmental conditions that are preferred by creative class members. This implies that local and regional economic policy should try to supply such soft location conditions in order to attract people of the creative class, and therefore firms. The significance of the creative class for regional productivity and per capita income in German regions is shown in Gottschalk et al. (2011).

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Titel: The impact of regional location factors on job creation, job destruction and employment growth in manufacturing
verfasst von: Raimund Krumm
Harald Strotmann
Publikationsdatum: 01.02.2013
Verlag: Springer-Verlag
Erschienen in: Review of Regional Research / Ausgabe 1/2013
Print ISSN: 0173-7600
Elektronische ISSN: 1613-9836
DOI: https://doi.org/10.1007/s10037-012-0069-y

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