Spatial Industrial Dynamics - An Empirical Test of the Lead-Lag Model

One fundamental hypothesis within the field of spatial industrial dynamics is the idea that in most countries it is possible to identify a limited number of leading urban regions. They keep their lead by continuously initiating, imitating and developing activities that over time to a substantial degree tend to diffuse to other locations in a hierarchy of functional urban regions. There are a number of forces that might propel diffusion processes of this kind. One force often mentioned in the literature is the maturing of products and industries that makes them less dependent upon the external economies offered by the large urban regions. Another force is the change in the type and the organisation of production taking place over time in the non-leading regions, which, for example, produce an increased demand for producer services. A third force worth mentioning is the secular rise in the real incomes in non-leading regions which give rise to an increased demand for various consumer services due to an income elas-ticity of demand greater than one. Given the above hypothesis a number of questions may be formulated: Is it possible to docu-ment these kinds of decentralisation processes? If so, what are their characteristics? How rapid are they? What differences are there between different products, different industries, different technologies, and so on? Are the follower regions catching up over time? The purpose of this paper is to analyse the spatial behaviour of a specific aggregate of private industries, namely urban growth industries, in Sweden during the period 1993-1998. Urban growth industries are defined in this paper as private industries in which the leading urban region in Sweden - the Stockholm region - specialise and that exhibit rapid growth in the rest of the country. The choice to analyse this group of industries are motivated by the hypothesis that it is this group of industries that has the largest potential for decentralisation of produc-tion and employment in the near future.

Spatial ICT Clusters in Sweden ? An Empirical Method to Identify a Necessary Condition for Existence

The tendency of information and communication technology (ICT) industries to cluster spatially is well documented in the international literature. Sweden has been characterised of a rapid growth of most ICT industries during the 1990s. In this paper we examine the spatial clustering of ICT industries in Swedish functional regions and changes in the patterns of clustering during the period 1990-2001. To be defined as a region with an ICT cluster a region must exhibit a significant overrepresentation of both ICT plants and ICT employment given its size in terms of population. By using this method it is possible to identify macro, meso and micro clusters. We examine the life cycles of these clusters during the period 1990-2001 in terms of births, growth, decline and disappearance as well similarities and differences between the different clusters in terms of, for example, industrial composition and regional factor endowments. We also compare the development of the ICT sector in regions with ICT clusters with the development of the ICT sector in regions specialised in large scale ICT production and in regions specialised in small scale ICT entrepreneurship. Based upon the results we also formulate recommendations for ICT policies in different types of regions.

The role of accessibility for regional innovation systems

The link between proximity and innovation has been dwelled upon extensively in the literature. A regional economic milieu characterized by proximity between relevant actors is maintained to be suitable for establishing and maintaining successful regional innovation system. In this paper it is proposed that the relevant link to be studied is rather that between accessibility and innovation. Although accessibility is a key factor in facilitating the processes stressed to be important for innovations, the relationship between accessibility and innovation is surprisingly unexploited. Scrutinization of the relationship between accessibility and innovation is necessary in order to fully comprehend regional innovative capacity. Furthermore, such scrutinization will shed further light in the issue of the importance of knolwedge spillovers.

Company R&D and University R&D - How Are They Related?

At the same time as we can observe strong tendencies of a globalisation of R&D, we also can observe a strong spatial clustering of R&D and related innovative activities. The standard explanation in the literature of the clustering of innovative activities is that such clusters offer external knowledge economies to innovative companies, since they are dependent upon knowledge flows and that knowledge flows are spatially bounded. Obviously, location is crucial in understanding knowledge flows and knowledge production, since knowledge sources have been found to be geographically concentrated. There are two major performers of R&D: industry and universities. It seems rather straight-forward to assume that industrial R&D might be attracted to locate near research universities doing R&D in fields relevant to industry. Already as far back as in the 1960s a number of case studies confirmed the important roles played by Stanford University and MIT for commercial innovation and entrepreneurship. During the years a large number of formal studies have presented evidences of a positive impact of university R&D on firm performance. The question is, does it also work the other way around? Does industrial R&D function as an attractor for university R&D? We may actually think of several reasons why university R&D may grow close to industry R&D. First of all political decision-makers may decide to start or expand university R&D at locations where industry already is doing R&D. Secondly, we can imagine that industry doing R&D in a region might use part of their R&D funds to finance university R&D. Thirdly, universities in regions with industrial R&D might find it easier to attract R&D funds from national and international sources due to co-operation with industry. Obviously, not all types of university R&D attract industrial R&D. There are reasons to believe that, in particular, university R&D in natural, technical and medical sciences attracts industrial R&D but that there are also strong reasons to believe that there are variations between different sectors of industry regarding how dependent their R&D is to be located close to university R&D. The above implies that there are behavioural relationships between industrial R&D and university R&D and vice versa. However, the litrature contains few studies dealing with this problem. Most studies have concentrated on the one-directional effect from university R&D to industrial R&D and the outputs of industrial R&D in most cases measured in terms of the number of patents and neglected the possible mutual interaction. However, if there is a mutual interaction between university and industry R&D, and if there are knowledge externalities involved, then we can develop a dynamic explanation to the clustering of innovative activities based on positive feedback loops. This would imply strong tendencies to path dependency and that policy initiatives to transfer non-innovative regions to innovative regions would have small chances to succeed. The fact that knowledge flows seem to be spatially bounded implies that proximity matters. Most contributions analysing spatial knowledge flows have used very crude measures of proximity. However, there are some authors that have argued that proximity could be measured using accessibility measures. Accessibility measures can be used to model interaction opportunities at different spatial scales: local, intra-regional and inter-regional. The purpose of this paper is to analyse the locational relationship between industry R&D and university R&D in Sweden using a simultaneous equation approach and to analyse existing differences between different science areas and different industry sectors.

Spatial ICT Clusters in Sweden - An Empirical Method to Identify a Necessary Condition for Existence

The tendency of information and communication technology (ICT) industries to cluster spatially is well documented in the international literature. Sweden has been characterised of a rapid growth of most ICT industries during the 1990s. In this paper we examine the spatial clustering of ICT industries in Swedish functional regions and changes in the patterns of clustering during the period 1990-2001. To be defined as a region with an ICT cluster a region must exhibit a significant overrepresentation of both ICT plants and ICT employment given its size in terms of population. By using this method it is possible to identify macro, meso and micro clusters. We examine the life cycles of these clusters during the period 1990-2001 in terms of births, growth, decline and disappearance as well similarities and differences between the different clusters in terms of, for example, industrial composition and regional factor endowments. We also compare the development of the ICT sector in regions with ICT clusters with the development of the ICT sector in regions specialised in large scale ICT production and in regions specialised in small scale ICT entrepreneurship. Based upon the results we also formulate recommendations for ICT policies in different types of regions

Regional Growth and Access to Knowledge and Dense Markets -An Empirical Study of the Performance in Sweden.

Access to knowledge and local service markets can be assumed to explain regional growth performance. The supply of services and knowledge with respect to regional development are stressed in the seminal papers by for example Rivera-Batiz (1988) and Knowledge referens. In this paper we make an empirical analyse using panel data for Swedish regions. The purpose is to analyse the relationship between regional growth and access to knowledge. We also acknowledge the size of the regional economy and access to the local labour market. We estimate first a cross-section model by using OLS. Second we employ a panel data model, using time distance access to population and the share local labour force with high education as explanatory variables. In the analysis we compare the results from the different models and our own results from the Swedish economy with other studies in this field. We find that local externalities for increasing returns are very important in the Swedish economy. Our estimated models yields a high level of goodness of fit, and the results indicates significant elasticity for high education and population density in the Swedish economy with respect to performance of regional gross domestic product.

Spatial Industrial Dynamics - An Empirical Test of the Lead-Lag Model

One fundamental hypothesis within the field of spatial industrial dynamics is the idea that in most countries it is possible to identify a limited number of leading urban regions. They keep their lead by continuously initiating, imitating and developing activities that over time to a substantial degree tend to diffuse to other locations in a hierarchy of functional urban regions. There are a number of forces that might propel diffusion processes of this kind. One force often mentioned in the literature is the maturing of products and industries that makes them less dependent upon the external economies offered by the large urban regions. Another force is the change in the type and the organisation of production taking place over time in the non-leading regions, which, for example, produce an increased demand for producer services. A third force worth mentioning is the secular rise in the real incomes in non-leading regions which give rise to an increased demand for various consumer services due to an income elas-ticity of demand greater than one. Given the above hypothesis a number of questions may be formulated: Is it possible to docu-ment these kinds of decentralisation processes? If so, what are their characteristics? How rapid are they? What differences are there between different products, different industries, different technologies, and so on? Are the follower regions catching up over time? The purpose of this paper is to analyse the spatial behaviour of a specific aggregate of private industries, namely urban growth industries, in Sweden during the period 1993-1998. Urban growth industries are defined in this paper as private industries in which the leading urban region in Sweden - the Stockholm region - specialise and that exhibit rapid growth in the rest of the country. The choice to analyse this group of industries are motivated by the hypothesis that it is this group of industries that has the largest potential for decentralisation of produc-tion and employment in the near future

Knowledge Accessibility and Regional Economic Growth

This paper analyzes the role of knowledge accessibility in re¬gional economic growth. The research question is the following: can the variation in knowledge accessibility between regions in a given period explain the variation in their growth performance in subsequent periods? As knowledge measures, we use company R&D, university R&D and patents. A main assumption in the paper is that knowledge accessibilities as a measure of knowledge potentials transform into potential knowledge flows. Our regression results indicate that the intra-municipal and intra-regional knowledge accessibilities of municipalities are significant and capable of ex¬plaining a significant share of the variation in growth of value added per employee between Swedish municipalities. However, the inter-regional knowledge accessibility of municipalities turned out to be insignificant. This is interpreted as a clear indication of spatial dependence in the sense that the knowledge resources in a given municipality tend to have a positive effect on the growth of another municipality, conditional on that the municipalities belongs to the same functional region. Thus, the results of the analysis indicate that knowledge flows transcend municipal borders, but that they tend to be bounded within functional regions. Also, the analysis shows that there is no remaining spatial correlation among the residuals of the spatial units (municipalities) when using accessibility measures in the model, which confirms that the spatial dependence is captured by the accessibility variables.