Modern Location Factors in Dynamic Regions

Abstract

Globalization has had an enormous impact on traditional industrial structures. It almost seems that everything is everywhere the same. And yet, in reality, some regions in a single industrialized country enjoy rapid economic growth while others are downsizing or stagnating. Thus there must be some remaining regional competitive advantages—even in the “Age of Globalization”. This paper engages in a quest to discover what these modern location factors might be and how and why they are necessary in creating dynamics and regional growth. In doing so, we link the driving forces behind these modern location factors with regional performance and eventually arrive at a concept of a regional lifecycle and its key dynamics. Using data that paint a comprehensive picture of industry and regional development in Germany we try to find empirical evidence for our approach.

Acknowledgements

The authors are indebted to Gerhard Kleinhenz, as well as to the participants of a workshop at the Entrepreneurship, Growth, and Public Policy Group at the Max Plank Institute for Economics in Jena, Germany, for comments on an earlier version of this paper. The authors also gratefully acknowledge comments and suggestions by three anonymous referees that have led to considerable improvement.

Notes

“Lean production is ‘lean’ because it uses less of everything compared to mass production—half the human effort in the factory, half the manufacturing space, half the investment in tools, half the engineering hours to develop a new product in half of the time. Also, it requires keeping far less than half the needed inventory on side, results in many fewer defects, and produces a greater and ever growing variety of products” (Womack et al., 1990, p. 13).

For a critical view on Porter's cluster approach and its recent promotion as a powerful analytical concept and policy tool, see Martin and Sunley (2003).

Krugman (1991, 14ff) provides a simple model of geographic concentration based on the interaction of increasing returns, transportation costs, and demand that leads to comparative cost advantages.

In contrast, information such as an exchange rate or a mathematical formula is codified and thus can be transferred.

Porter's cluster approach is also based on the idea of competitive advantage. He presents a diamond model that maps inter- and intra-firm relations as well as supporting institutions within a cluster. Based on this model, Porter derives strategic implications for the competitive advantage of nations (Porter, 1990) and also of regions (Porter, 1998).

For a more detailed discussion, see, e.g. Glaeser et al. (1992), Desrochers (2001), and Audretsch and Feldman (2004).

Audretsch and Fritsch (1994) discuss different methods of measuring entry rates.

We restrict the analysis to West Germany as information on East Germany, the former socialist GDR, is only available from 1992 onward, i.e. for a much shorter time period. Furthermore, empirical analyses have shown that economic conditions in East Germany in the 1990s were mainly driven by the transformation process to a market economy (cf. Fritsch, 2004).

We decided not to do an equal split of two periods of 7 years as patent data are available only from 1995 to 2000.

For a detailed discussion of the cluster analysis, see Lorr (1983).

The difference here from the results of Gort and Klepper (1982), who find a decrease in net entry for the lifecycle's fourth phase, might be attributed to the consideration of outsourcing.

The principal component analysis dates back to seminal papers by Pearson (1901) and Hotelling (1933). For a modern application-oriented approach, see Jackson (1991).