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A measure for identifying substantial geographic concentrations
Abstract and Figures
en Regional industrial policy emphasizes the notion of building on existing concentrations of competitive firms. A range of measures to identify such concentrations has been put forward in the literature. These measures, however, do not identify substantial concentrations which have the best potential for further development, tend to concentrate on scale measured by employment, and are applied using data for pre‐specified administrative boundaries. This paper presents a new concentration index that identifies substantial concentrations and utilizes information on both the number and size of plants. It also proposes a method for generating relevant industry‐specific spatial units.
Resumen
es La política industrial regional hace hincapié en la noción de construir sobre las concentraciones existentes de empresas competitivas. En la literatura se ha presentado una serie de medidas para identificar tales concentraciones. Estas medidas, sin embargo, no identifican las concentraciones sustanciales que tienen el mejor potencial para un mayor desarrollo, tienden a concentrarse en la escala (medida por el empleo), y se aplican utilizando datos para límites administrativos especificados de antemano. Este artículo presenta un nuevo índice de concentración que identifica concentraciones sustanciales y utiliza información sobre el número y el tamaño de las plantas industriales. También propone un método para generar unidades espaciales relevantes específicas para la industria.
抄録
ja 地域の産業政策は、競争力のある既存の企業の集積を拡大する意図を強調している。この集積を同定する様々な方法が論文で提唱されている。しかしながら、これらの方法は将来発展する可能性が最も高い大きな集積を識別せず、従業員数で測る規模に注目しており、予め設定された行政区域のデータを使用するときに適用できる。本稿では、大きな集積を識別し工場の数と規模の両方の情報を利用する新しい集積指数を提案する。また、重要な産業に特異的な空間単位を作り出す方法も提案する。
Figures - available via license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
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... More precisely, S3 implies regional economic diversification, including diversified specialization (Asheim, Grillitsch, and Trippl 2016) and smart diversification (Balland et al. 2019). Lack of demarcation between specialization and diversification leads to confusion (Hassink and Gong 2019), as well as a lack of delimitation between specialization (cluster, smart, regional) and spatial concentration (Bickenbach, Eckhardt, and Krieger-Boden 2013;Dragan and Isaic-Maniu 2017;Van Egeraat et al. 2018). As such an approach intrinsically increases the dynamics of the regional industrial development (regardless of the specificity of a socio-spatial setting), attending to the domains of (industrial) specialization and spatial concentration (of industry) in the transitional context of the WB seems particularly important, as highlighted in the following subsection and elaborated in the central part of the paper. ...
... The issue of spatial concentration has rarely been associated with regional industrial development, except in literature on geographic distribution that presents industrial concentration in some areas (Ellison and Glaeser 1999;Maurel and Sedillot 1999;Marcon and Puech 2010;Lehocký and Rusnák 2016;Van Egeraat et al. 2018;Stellian and Danna-Buitrago 2019). The analysis of spatial concentration is mainly based on locational and industrial specialization indices. ...
... All these indices have various strengths and weaknesses; however, they are rarely applied in regional industrial development and planning. In this paper, industrial concentration and regional specialization were measured using a new concentration index (a modified Herfindahl-Hirschman index, according to Van Egeraat et al. 2018), and location coefficients. ...
This paper analyzes post-socialist industrial development and policy in the Western Balkans through the lens of its regional specialization and spatial concentration. Against a conceptual framework revolving around place-based industrial policy, and using the Concentration index (modified Herfindahl-Hirschman index) and location coefficients (Balassa index), a comparative analysis over three decades (1990–2020) highlights weak regional diversification and intra-regional integration of industrial activity. The findings offer a new industrial policy that transcends regional specialization and spatial concentration to address regional development, planning and governance. The concluding remarks reveal some basic paths toward effective and pro-European regional industrial policy in the Western Balkans.
... These shortcomings were recently addressed by van Egeraat et al. (2016). Their Concentration Index (CI index) can be used to identify substantial industrial concentrations. ...
... The pharmaceutical industry in Ireland can serve to illustrate some of these ideas. The spatial configuration of the industry is characterised by a high level of concentration, involving three substantial concentrations (in Cork, Dublin and Waterford), although pharmaceutical plants are operating in several other locations in the country (van Egeraat et al., 2016). Detailed qualitative research on the Cork pharmaceutical concentration (van Egeraat & Curran, 2013) showed that companies within that concentration utilised very few raw material input suppliers, even at the national level. ...
... To take another example, the spatial configuration of the financial services sector is characterised by a single substantial concentration in Dublin (van Egeraat et al., 2016). The initial cause for this level of concentration was related to government policy, making fiscal incentives to financial companies conditional on their location in the demarcated International Financial Services Centre (IFSC). ...
For almost thirty years the cluster concept and cluster policy have retained strong traction across both academic and policymaking circles. In this paper we select issues of current relevance, particularly for policymaking, from contexts of the evolution of understanding of the concept, the experience of implementing policy and on-going
research.
The next section sets out key features of the cluster concept from its roots in Porter’s work (1990, 1998) and in well-worn considerations relating to agglomeration and innovation. Cluster policy experience is examined in the following section, in relation both to the Irish case and to international, mainly European, approaches and experience.
For Ireland, a lack of an agreed, consistent or clear definition of cluster is revealed across policy documents and practice. The importance of amplifying connectivity between cluster members is considered fundamental to future cluster performance across regional
and sectoral boundaries. This is increasingly important for innovation imperatives.
The next section argues that to close the gap between government commitment to revising Irish cluster policy on the one hand and its implementation on the other, a number of issues must be addressed in terms of cluster policies, strategies and actions. Key to delivering impactful cluster policy are coordination and integration of approaches across relevant government departments and related agencies. In addition, we highlight a number of issues relevant for growing the evidence base on underlying structures and scales of relevance for an appropriately developed and targeted cluster policy for Ireland. These issues cover methods for identifying clusters, their relevant geographical scale and the applicability of cluster policy for different areas in Ireland. The final section sets out our concluding comments.
... However global data sets at the sub-national level such as clusters are typically lacking. Even if sub-national administrative divisions are available, these may show a poor overlap with actual inventive activity (Alcácer and Zhao 2016;Van Egeraat et al. 2018). Furthermore, the spatial scale of sub-divisions can vary greatly from country to country, making international sub-national comparisons difficult. ...
... The organic approach is especially advantageous in international research because it overcomes the challenge of using differing statistical boundary sizes for different countries. The approach also avoids potential dilution or distortions due to the use of inappropriate boundaries (Alcácer and Zhao 2016;Van Egeraat et al. 2018). ...
In this paper a methodology for identifying and delineating spatial technology clusters based on patenting concentration is developed. The methodology involves the automated geocoding of patent inventor addresses, the application of a home bias correction factor and a sensitivity analysis to determine the optimal parameters of the kernel density estimation interpolation distance and the minimum concentration threshold to identify clusters. The methodology’s performance is compared to a number of other cluster identification methods and it is validated across 18 individual sectors, including mature broad-based high-technology sectors and emerging niche sustainable energy technology sectors. The results suggest that the performance of the methodology exceed that of alternative cluster identification methods, although there is some variation in performance between different sectors. This demonstrates that the methodology provides researchers, practitioners and policy makers with a useful tool to gain insight into the spatial distribution of sectoral innovation activity at a global scale and sub-national regional level and to monitor changes over time, thereby supplementing more readily available global statistical data which is available at the national level.
... , i refers to MSA i in 2007. Also yij, 2007 is MSA i 's industry j employment level, y i,2007 is total employment in MSA i, y Nj,2007 is total industry j employment in all MSAs, and y N,2007 is total employment in all MSAs.The Krugman index D i,2007 , measuring industrial structure dissimilarity, ranges from zero to two, with zero indicating that MSA i's industrial structure is identical to the national industrial structure and two indicating maximum dissimilarity(Van Egeraat et al., 2016;Goschin et al., 2009). The Herfindal index Her i,2007 measures concentration in a particular industry. ...
... The Herfindal index Her i,2007 measures concentration in a particular industry. The higher the index, the more specialised is an MSA(Van Egeraat et al., 2016). ...
In this paper, we show that the economic crisis commencing in 2007 had different impacts across US Metropolitan Statistical Areas, and seek to understand why differences occurred. The hypothesis of interest is that differences in industrial structure are a cause of variations in response to the crisis. Our approach uses a state-of-the art dynamic spatial panel model to obtain counterfactual predictions of Metropolitan Statistical Area employment levels from 2008 to 2014. The counterfactual employment series are compared with actual employment paths in order to obtain Metropolitan Statistical Area-specific measures of crisis impact, which then are analysed with a view to testing the hypothesis that resilience to the crisis was dependent on Metropolitan Statistical Area industrial structure.
... There is a clear contribution to the decision-making process on the location of future facilities, diversification of the national electricity matrix, and increase of energy security and efficiency in the country. When analyzing industrial concentration, its identification is frequently based on geographic concentration and industrial-specific indices [34]. Despite the importance of sugarcane bagasse bioelectricity, no studies were found on the allocation of productive resources (e.g., funding, specialized labor), which could lead to higher productive efficiency, sustainable local development, and generate jobs and income [35]. ...
Bioelectricity generation from sugarcane is significant across Brazil and is related to regional market structure characteristics where the mills are located. To understand the distribution and conjuncture of this sector, this study analyzes the pattern of location, concentration and clustering of the bioelectricity supply from sugarcane bagasse in Brazil, for 2017 and 2022. The data were obtained from the Brazilian National Electric Energy Agency, and the methodology was based on concentration indices and scan statistics. The results showed that the Southeast region presented the most thermoelectric power plants and installed capacity. The Southeast and Midwest regions were highly concentrated in terms of quantity and sugarcane bioelectricity installed capacity. Five clusters were identified for the number of power plants in 2017; for 2022, there were eight clusters. Regarding installed potential, there were 14 clusters in 2017 and 23 clusters in 2022, all statistically significant. The existence of clusters provides information on the competitive advantages in the national market, which can drive new investments in more densified areas or in the neighborhood. Identification of the location and concentration pattern showed that facilities in the state of São Paulo and the Northeast coast were responsible for the most important share of supply. These results indicate to investors the impact of electricity generation on the sector and the most relevant location for installing new thermoelectric plants.
... There are various indices of spatial concentration of economic diversity. One of the most commonly used is the HHI (van Egeraat et al. 2018). The simplicity of the calculation necessary for its determination and the small amount of data required for the calculation are the main advantages of this index. ...
The creative sector is one of the most rapidly growing sectors of the global economy. This sector can alsoplay an important role in providing economic benefits for developing countries. Promoting the creative economyneeds a better understanding of the underlying factors that account for its spatial distribution. One of the most impor-tant factors that may influence the development of creative industries is tolerance. This paper focuses on the spatialdistribution of the creative economy across cities in Indonesia and examines its relationship with tolerance. The maindata sources of this paper are the unique data produced by the Central Bureau of Statistics (Badan Pusat Statistik or BPS)and the Indonesian Agency for Creative Economy (Badan Ekonomi Kreatif or BEKRAF), in addition to the City ToleranceIndex provided by the SETARA Institute. The study finds that the creative economy in Indonesia does not tend to havea high spatial concentration, indicating that cities in Indonesia have an opportunity to develop the creative economy.The analysis confirms that tolerance matters for the creation of the creative economy in Indonesia. Three components ofthe City Tolerance Index that influence the creative economy are the Mid-Term Regional Development Plan, discrim-inatory regional rules and incidents of abuses against the freedom of religion or belief. The size of the population, theHuman Development Index, and the status of a city as the provincial capital play a significant role in explaining thedistribution of creative economies across the cities in Indonesia.
... One such process, for example, is that of agglomeration. Industrial clustering has long been recognised as a key process shaping regional economic character, and this is often intentional in cases where states enact policies conducive to attracting industries in regional agglomerations (van Egeraat et al., 2016). These processes can become autopoeitic or self-reproducing in conducive circumstances (Alhadeff- Jones, 2008). ...
In a context of mistrust in public health institutions and practices, anti-COVID/vaccination protests and the storming of Congress have illustrated that conspiracy theories are real and immanent threat to health and wellbeing, democracy, and public understanding of science. One manifestation of this is the suggested correlation of COVID-19 with 5G mobile technology. Throughout 2020, this alleged correlation was promoted and distributed widely on social media, often in the form of maps overlaying the distribution of COVID-19 cases with the instillation of 5G towers. These conspiracy theories are not fringe phenomena, and they form part of a growing repertoire for conspiracist activist groups with capacities for organised violence. In this paper, we outline how spatial data have been co-opted, and spatial correlations asserted by conspiracy theorists. We consider the basis of their claims of causal association with reference to three key areas of geographical explanation: (1) how social properties are constituted and how they exert complex causal forces, (2) the pitfalls of correlation with spatial and ecological data, and (3) the challenges of specifying and interpreting causal effects with spatial data. For each, we consider the unique theoretical and technical challenges involved in specifying meaningful correlation, and how their discarding facilitates conspiracist attribution. In doing so, we offer a basis both to interrogate conspiracists’ uses and interpretation of data from elementary principles and offer some cautionary notes on the potential for their future misuse in an age of data democratization. Finally, this paper contributes to work on the basis of conspiracy theories in general, by asserting how – absent an appreciation of these key methodological principles – spatial health data may be especially prone to co-option by conspiracist groups.
... The Herfindahl index measures concentration in a particular industry. A higher value indicates higher industrial concentration in a region, while a lower value indicates a lower level of industrial concentration in the region (van Egeraat et al., 2018). ...
Automation is expected to have strong implications for labour-saving technologies. We calculate the proportion of jobs at high risk of automation across European regions using data from the 2018 Labour Force Survey (LFS). We examine the relationship between regional vulnerability to job automation, specialization, related (and unrelated) variety and agglomeration. The results indicate that regions at low vulnerability to job automation benefit from unrelated variety and high population density. Regions with higher proportions of clerical support workers, craft and related trade workers, and plant and machine operators and assemblers are likely to face greater disruption.
... Relating to industrial concentration research, this study highlights: Chalvatzis and Ioannidis [10], Charumbira and Sunde [11], Coelho Junior [12], [13], Coelho Junior et al. [14]- [20], Mohammed et al. [21], Nawrocki and Carter [22], Selvatti et al. [23], and Van Egeraat et al. [24]. Regarding special conglomerate analyses, we emphasize: Arroyo et al. [25], Lieu et al. [26], Nigatu et al. [27], Randolph [28], and Yih et al. [29]. ...
This study analyzes the concentration and conglomerate spatial distribution of forest-based thermoelectric plants in Brazil, in 2018. Herein, we spatially identified thermoelectric plants in different Brazilian regions and states, and measured the state concentrations (levels 1 and 2 of forest) using various indicators, including the concentration ratio (
CR
(
k
)), the Herfindahl-Hirschman index (
HHI
), Theil’s entropy (
E
), and the Gini coefficient (
G
). Meanwhile, each state’s conglomerates were evaluated using the Scan statistic. We found that there are 98 forest-base thermoelectric plants in Brazil, most of which are located in the south-central portion of the country where there is rapid forest growth. The southern region contains 32.65% of the identified plants as a result of the presence of level 2 forest resources (black liquor and forest waste). Regarding the state’s concentration (forest level 1),
CR
(
k
) revealed a moderate concentration, the
HHI
and
E
indices demonstrated low concentrations, and
G
suggested null to weak inequality. Of these Brazilian forest bioelectricity plants (level 1), 4 clusters were identified, but only one was statistically significant, located in the southern region. Concerning level 2 sources, the only statistically significant conglomerate regarding charcoal was centered in Açailândia (Maranhão). These findings will provide information to assist industry decision-making processes and help guide public policies for forest bioelectricity development in Brazil that favor energy security and improve resource utilization.
... What should be considered side by side with concentration and specialization is the importance, or rather, the relative degree of concentration. Therefore, for policy considerations, the indices should be considered within their context (Van Egeraat et al. 2018). ...
This paper introduces two indicators for innovation, showing the allocation of innovation and its inherent diversity. Both indicators can give insights for regional innovation policy conception. The first indicator measures the share of patents in research and development expenditure, proposing a locational innovation output indicator. It can show that innovation in Europe differs strongly among NUTS2-level regions, which points to regionally specific, place-based policies as a result of a strong dispersion in European innovation activity. The second measure, the innovation diversity indicator, shows the diversification of innovation in a region and is built upon Krugman's loca-tional Gini coefficients. Here, the share of patents belonging to a particular IPC class is related to the dispersion of all patents in a region. Possible implications for policy are the construction of place-based, technology-specific programs, on either national or subnational (NUTS2-) level, where each country or region has to be considered carefully. Analyses underline that innovation in Europe is a highly regionally and technically diversified concept.
... Geometric representation of business with circles (also called overlapping labour fields) of different size appeared recently inVan Egeraat et al. (2018). They try to use unions (overlaps) of circles in their CI index, but use the Herfindahl approach with cut-offs and define "the labour fields" on the basis of the average travel to work distance, but without referring to firms' size. ...
Paper develops a Spatial Agglomeration Index (SPAG) of the economic activity for the point geo‐localisations of firms. It includes the effects of location, the distance between firms and the overlapping impact of the firms' size. The SPAG builds a new class of measures of the spatial density of the economic activity inside the region, based on the geometrical representation of firms with circles, without referring to the commonly used Ripley's K function. The SPAG measures the degree of divergence from the benchmark distribution, what detects different spatial distributions as clusters or borderline dispersion. We test SPAG with real point data.
... When applying the KDE method decisions must be made about two important variables: the interpolation range and the concentration threshold for recognizing an area as being of high concentration. The interpolation range can be decided based on several criteria, for example Van Egeraat et al. (2018) uses commuting distance while Alcácer and Zhao (2016) uses 20 mi (32.2 km), with no justification given. Acs et al. (2002) notes that within a 50 mi (80.5 km) distance from the boundaries of a metropolitan statistical area, there is still some positive innovation effect. ...
A methodology for identifying high R&D city-regions worldwide using patent data is presented. A heat map (kernel density estimation) approach is used which allows city-regions to be identified in areas with a high patenting intensity, a proxy for high R&D expenditure. The methodology is independent of any pre-existing administrative boundaries and it can therefore be applied to identify sub-national concentrations of R&D expenditure worldwide. This is an important advantage compared to other statistical data which is often only available at the national level. The results provide insight into the changing worldwide spatial distribution of R&D expenditure between 1997 and 2011, including the rapid rise of Asian R&D city-regions as well as less dramatic shifts among European and North American city-regions. The results also highlight some challenges of identifying high R&D city-regions and estimating R&D expenditure using patent data, and the existence of very large high R&D city-regions which encompass multiple cities. Some suggestions for improvement and further research are also proposed.
... 4. It is important to mention that the overall limitations of RCAs as an indicator of industrial concentration are becoming increasingly well known throughout economic geography. In their recent contribution, Van Egeraat, Morgenroth, Kroes, Curran, and Gleeson (2018) highlight a number of these shortcomings and propose an alternative measure of specialis- ation based on a Concentration Index (CI). This index takes into consideration a number of features including share of activity, employment, number of firms and the size distribution of concentrations to name but a few and is therefore better able to identify areas of substantial industrial concentrations. ...
This paper advances a measure of knowledge complexity to analyse for Ireland whether more complex knowledge is generated by local or foreign firms. Information on assignees, technological structure and global ownership contained within a recently developed Irish patent database forms the basis for distinguishing between technologies developed by local and nonlocal firms. Thereafter, our knowledge complexity index uses a modified bipartite network to link these technologies to their country of origin, i.e. local or nonlocal. Our results indicate that the most complex technologies tend to be produced in a few diverse regions. Furthermore, the majority of complex knowledge is generated in technology classes where the share of foreign activity is greater than local firms. © 2019
... The LQ is not without its drawbacks (Woodward & Guimarães, 2009) as, for example, it does not take into account the number of plants within a region and may be hampered by the predetermined definition of appropriate spatial units. Research on Germany (Scholl & Brenner, 2016) and Ireland (Van Egeraat, Morgenroth, Kroes, Curran, & Gleeson, 2015) address these issues using geocoded plant data for two-and three-digit industrial classifications. 16. ...
Motivated by ongoing research into the cluster concept that considers dynamic features of economic development and the cluster life cycle, differences between traded clusters and local activity across different spatial scales are examined for Ireland. Using recent cluster definitions for Europe, this paper presents clustering patterns within the Irish economy from 2008 to 2012. We report on data requirements when applying the benchmark cluster definitions to Irish data. Integrating small, open economy features with life-cycle concerns, we focus on specific clusters in Ireland, along with their export performance, noting that appropriate cluster boundaries are neither regional nor national. Analyses indicate that while Ireland hosts a number of internationally competitive clusters, foreign-owned firms remain substantially more productive than indigenous enterprises. We identify the geographical location of these prominent clusters at the NUTS-3 regional level and highlight the role of regional features for differences in adaptive cycles of clusters. We identify a substantial portion (60%) of Irish regional wage variation relates to the different cluster mixes across regions.
A methodology for detection of spatially distributed trade clusters across the territory was developed based on the kernel density function used in GIS technologies. To determine the optimal parameters for the placement of trade enterprises, interpolation distance for density assessment of point objects and a minimum concentration threshold are applied, allowing for the identification of various types of trade clusters in the Republic of Crimea. The aim of the article is to identify evidence of the existence of spatially distributed trade clusters of different types in the region, determine their concentration, economic role, and possible functioning prospects. In the paper spatial modeling methods using GIS technologies were used. It is shown that trade facilities can be of various morphological types, such as marshal, nodal, satellite, and sectoral ones. A classification of trade clusters in the Republic of Crimea was made, and the potential weight of each cluster type was calculated. Heat maps of population density distribution were created to assess potential zones for trade development. Using the kernel density function, spatially distributed trade clusters of different types were identified in the area under analysis. This approach is applied to detect hotspots based on extrapolated estimates of the number of stores and their distribution across the regions. Cartography was carried out using the ArcGIS software tool. The analysis confirms the existence of spatially distributed trade clusters with varying morphology on the peninsula and emphasizes their advantages and disadvantages. The role of these clusters in regional development is shown. The results of the article may be used in development of regional strategies that contribute to various forms of trade relations in the region.
The article identifies the current problems of the modern Russian labor market. To study them more closely and provide solutions, the paper proposes a methodological toolkit for assessing the use and impact of labor resources on the development of an industrial region in the conditions of digital transformation. The testing was carried out in the regions of the Volga Federal District of the Russian Federation (hereinafter the Volga Federal District), where a quarter of the country’s industrial production is concentrated. According to the testing results, the demographic factor was recognized as the most significant for the development and effective functioning of the labor market among numerous factors affecting the regional labor market amid digital transformation of industry. The analysis revealed the problems in the structure of available labor resources in the Volga Federal District, including the growing deficit of labor resources associated with the decline in the number of people below working age and the decline in the output of middle-level specialists (technical specialties). The results of the study confirm that the implemented set of state support measures is not fully efficient, so it is necessary to develop and introduce new tools and mechanisms that regulate the sustainable development of labor potential and meet the conditions of the transformational economy in the country’s industrial regions.
Purpose
This paper analyses how firm births and deaths are influenced by previous firm births and deaths in related and unrelated sectors. Competition and multiplier effects are used as the theoretical lens for this analysis.
Design/methodology/approach
This paper uses 2008–2016 Irish business demography data pertaining to 568 NACE 4-digit sectors within 20 NACE 1-digit industries across 34 Irish county and sub-county regions within 8 NUTS3 regions. A three-stage least squares (3SLS) estimation is used to analyse the impact of past firm deaths (births) on future firm births (deaths). The effect of relatedness on firm interrelationships is explicitly modelled and captured.
Findings
Findings indicate that the multiplier effect operates mostly through related sectors, while the competition effect operates mostly through unrelated sectors.
Research limitations/implications
This paper's findings show that firm interrelationships are significantly influenced by the degree of relatedness between firms. The raw data used to calculate firm birth and death rates in this analysis are count data. Each new firm is measured the same as another regardless of differing features like size. Some research has shown that smaller firms have a greater propensity to create entrepreneurs (Parker, 2009). Thus, it is possible that the death of differently sized firms may contribute differently to multiplier effects where births induce further births. Future research could seek to examine this.
Practical implications
These findings have implications for policy initiatives concerned with increasing entrepreneurship. Some express concerns that public investment into entrepreneurship can lead to “crowding out” effects (Cumming and Johan, 2019), meaning that public investment into entrepreneurship could displace or reduce private investment into entrepreneurship (Audretsch and Fiedler, 2023; Zikou et al ., 2017). This study’s findings indicate that using public investment to increase firm births could increase future firm births in related and unrelated sectors. However, more negative “crowding out” effects may also occur in unrelated sectors, meaning that public investment which stimulates firm births in a certain sector could induce firm deaths and crowd out entrepreneurship in unrelated sectors.
Originality/value
This paper is the first in the literature to explicitly account for the role of relatedness in firm interrelationships.
Territorial inequalities have long been a subject of study and concern in Canada. In the face of large structural changes such as industrial shifts and the decarbonization of our economies, there is an urgency to understand such inequalities and design effective policy interventions for those places facing persistent economic decline. This paper shares a novel composite index that measures economic disparity across Canadian Census Subdivisions (CSDs) using Census data from 2001 through 2016 and the 2011 National Household Survey. Named the “Index of Economic Disparity,” it is comprised of an equally weighted average of four sub‐indices that assign percentile rankings for all CSDs based on whether they experience persistent and substantial decline in key economic areas: population, labour force outcomes, working‐age share of population, and industrial diversity. The variation of outcomes across geographies—urban and rural—highlights the importance of place‐based policies .
Bu çalışmanın amacı, işletme kümelerini belirlemek için kullanılan yöntemlere ilişkin bir literatür incelemesi sunmak ve yöntemlerin ürettiği enformasyonu ve kısıtlarını kümelerin kavramsal nitelikleri kapsamında değerlendirmektir. Literatürde yer alan tüm yöntemlerin kendilerine özgü sınırlılıklara sahip olduğu görülmektedir. Bununla birlikte karma yaklaşımların, nicel yöntemlerden yararlanan yukarıdan aşağı yaklaşımlar ve nitel yöntemlerden yararlanan aşağıdan yukarı yaklaşımların tek başına benimsenmesinin neden olduğu sınırlılıkları ortadan kaldırabildiği görülmektedir. Kümelerin en temel niteliği olan etkileşim/bağlantısallık düzeyinin tespit edilmesinde ise sosyal ağ analizinden yararlanılabilir. İşletme kümelerinin ekonomik sistemler içinde belirlenebilmesi kümelere özgü politika önerilerinin geliştirilebilmesi için önem taşımaktadır.
The aim of this paper is to analyse co-location patterns of manufactures and service industries at a microgeographic level using Spanish data from the Mercantile Register. Our approach allows us to analyse joint-location and co-location patterns of firms in different industries, and to overcome previous technical constraints in this type of analyses, partially thanks to using homogeneous cells instead of administrative units. This paper contributes to the empirical literature on industry location by developing a multisectorial co-location index computed by comparing differences between observed data about firms’ location and randomly generated data. Multisectorial relationships are analyzed by transposing bilateral relations onto an n-dimensional space. Our results show that dispersed industries tend to locate jointly and that industries with lower joint-location patterns have spatial structures similar to those obtained through input–output relationships, suggesting weak role of co-location patterns as interindustry linkages are not the main location determinants.
This exchange urges economic geographers working within several major extant schools of thought to pay greater attention to uneven economic development in general and the dark side of the economic geographies in particular.
The City Region is becoming the spatial focus for economic development policy across many parts of the European continent. But these functional regions have taken on a new impetus in the UK with the introduction of ‘city deals’ aimed at improving network and coordination of actors in local authorities. One of the goals of city regions is to improve industrial policy particularly lacking since the abolition of many of the Regional Development Agencies across the UK. However, city regions in developing policy appear to be following in an unquestioning manner the industrial priorities of earlier institutions, and nowhere is this more obvious than in the case of the identification of priority industry development sectors. Too often the selection of industries and clusters for special support has been undertaken in an unquestioning manner. In this paper we focus on the case of the Cardiff Capital Region. We review approaches to identify priority sectors in this case and the problems associated with this policy approach.
Paper develops a measure of spatial agglomeration of economic activity based on geo-localizations of firms. Proposed here Spatial Agglomeration Index (SPAG) includes the effects of location, distance between firms and overlapping impact resulting from the size and number of companies in given sector. SPAG builds a new class of measures of spatial density of economic activity inside the region, basing on geometrical representation of firms with circles, without referring to often used Ripley's K function. SPAG detects different spatial distributions of economic activity, including clusters. We provide also the Monte Carlo significance test of SPAG, based on theoretical distribution for spatially uniform locations of business.
JEL Code: R12, R32, C43, D30
Using extensive empirical analysis of the changes of regional specialization over a period of two decades, observing its causes and consequences the authors show economic integration as a relocation of resources across sectors and space. The authors argue that the resulting challenge to both regional and social cohesion in the enlarged European Union may require a reorientation of cohesion policy at European, national and local levels. Disaggregated national data sets with respect to both the sectoral and spatial levels are combined with an analysis of both regional structural change and the role of foreign direct investment in this process. This book will be of great interest to post graduate students and researchers interested in international trade and regional economics as well as policy makers engaged with regional and structural changes at both a European and national level.
The process of knowledge production exhibits a very distinctive geography. This article argues that this geography is fundamental, not incidental, to the innovation process itself: that one simply cannot understand innovation properly if one does not appreciate the central role of spatial proximity and concentration in this process. The goal of this article is to demonstrate why this is true, and to examine how innovation systems at the subnational scale play a key part in producing and reproducing this uneven geography over time. This article addresses four key issues. First, it looks at the reason why location matters when it comes to innovative activity. Second, it turns to examine regional innovation systems, and the role played by them in generating and circulating new knowledge leading to innovation. Third, the article considers the relationship between regional systems of innovation and institutional frameworks at the national level. Finally, the relationship between local and global knowledge flows is examined.
Conceptual innovation with respect to the enclave concept has been virtually absent compared with industry agglomerations. This is despite the fact that some varieties of agglomeration distinguished in the literature appear to come close to what previously were regarded as industrial enclaves and despite frequent allusions to the enclave nature of economic spaces produced by contemporary processes of globalization. Bringing the literature on agglomeration and enclaves into dialogue, we revisit the concept of the enclave—a concept that has been largely neglected since it enjoyed a popularity in connection with the study of particular (notably extractive) industries and particular (notably dependencia) theories of national economic development during the 1960s and 1970s. Much has changed since this time, which suggests that the concept of the enclave ought to be ripe for reevaluation. In this article we take an initial step in this direction, identifying analytical dimensions to the enclave and illustrating different manifestations of enclaves in the mining industry, drawing on the case of Chile. We conclude by advocating the renewed study of industry enclaves within contemporary economic geographic analysis.
Abstract This paper investigates how, if at all, inward foreign investment can instigate a clustering process when,such investment is initially attracted to a region as a result of targeted public policy rather than the existence of local sectoral capabilities. The case of the medical technology cluster in Galway on the west coast of Ireland is used to examine if FDI (foreign direct investment) can create a clustering effect in FDI-generated agglomerations. The study incorporates the collection of quantitative data from a postal questionnaire survey of the cluster member,firms and qualitative data from semi-structured interviews with a sample of both indigenous and foreign-owned,firms in the cluster. The empirical evidence shows that the presence of large foreign-owned,MNCs (multinational corporations) results in local knowledge transfers and regional reputation effects, which together give rise to a clustering process. The research contests the view that there are generally limited local spillovers in FDI-generated clusters (De Propris and Driffield 2006) and contrary to other perspectives (Phelps 2008), it shows that external economies can be captured locally from FDI in such clusters. Keywords: Regional industrial clusters, Foreign Direct Investment, Medical Technology 2
There is increasing recognition that the existence of clusters can only be understood when studying their dynamics over time (Audretsch and Feldman 1996; Pouder and St. John 1996; Swann et al. 1998; Maggioni 2002; Brenner 2004; Iammarino and McCann 2006; Menzel and Fornahl 2010; Ter Wal and Boschma 2011). In fact, clusters may be best understood as products of a path-dependent process (Martin and Sunley 2006). In that context, scholars have described the main features of cluster development over time, and have explored the driving forces behind their evolution. In their seminal contribution, Menzel and Fornahl (2010) proposed a cluster life cycle model in which firms enter and exit the cluster, capabilities of cluster firms develop and interact (and might converge), and inter-organizational linkages within and beyond the cluster are established and dissolved along the cluster life cycle.
Disambiguates theories of industrial clusters by providing a framework of three ideal-typical forms of clustering: the classic model of pure agglomeration, the industrial-complex model, and the social network or club model. The first two of these models come from classical and neoclassical economic tradition. The third comes from sociology. An analytic definition of these models and a discussion of their implications are provided. The economic models are also contrasted with the sociological model. The analysis examines how the theories might be empirically tested using actual data from the London area, and discusses the significance of the distinction between these models for policymakers. The model of pure agglomeration arises from Marshall and Hoover. Marshall theorized that firms localize in a given geographic area due to the development of a local pool of specialized labor, the increased local provision of non-traded input specific to an industry, and the maximum flow of information and ideas. Hoover classifies the sources of agglomeration advantages into three groups: internal returns to scale, localization economies, and urbanization economies. Industrial complexes are characterized by sets of identifiable and stable relations among firms which are in part manifested in their spatial behavior. Traditionally, the focus of the analysis under this model is how location affects transaction costs. The social network model sees the creation of organizations is a rational response to the transaction cost problems caused by bounded rationality and opportunism in a pure market-contracting economy. Because such a system requires interpersonal trust, proximity has often be a prerequisite for the development of social networks. (CAR)
The notion of ‘resilience’ has recently risen to prominence in several disciplines, and has also entered policy discourse.
Yet, the meaning and relevance of the concept are far from settled matters. This article develops the idea of resilience and
examines its usefulness as an aid to understanding the reaction of regional economies to major recessionary shocks. But in
so doing, it is also argued that the notion of resilience can usefully be combined with that of hysteresis in order to more
fully capture the possible reactions of regional economies to major recessions. These ideas are then used as the basis for
a preliminary empirical analysis of the UK regions.
The article presents a regional innovation policy model, based on the idea of constructing regional advantage. This policy model brings together concepts like related variety, knowledge bases and policy platforms. Related variety attaches great importance to knowledge spillovers across complementary sectors, possibly in a region. Then, the paper categorises knowledge into ‘analytical’ (science based), ‘synthetic’ (engineering based) and ‘symbolic’ (artistic based) in nature, with different ‘virtual’ and real proximity mixes. Finally, the implications of this are traced for evolving ‘platform policies’ that facilitate economic development within and between regions in action lines appropriate to related variety and differentiated knowledge bases.
. Economists have recently devoted an increasing attention to the issue of spatial concentration of economic activities. However,
surprisingly enough, most of the empirical work is still based on the computation of very basic statistical measures in which
the geographical characteristics of data play no role. By making use of a series of empirical examples we show that spatial
concentration consists of two different features that are rarely kept as separate in the statistical analysis: an a-spatial
concept of variability which is invariant to permutations, and the concept of polarization that refers to the geographical
position of observations.
Empirical studies on the evolution of concentration, specialization or localization of economic activity have provided ambiguous results that strongly depend on the researcher's choice of the reference. This paper develops a decomposition method for Theil indices of localization that clarifies where this ambiguity originates from. The method allows expressing the difference between absolute and relative Theil indices of localization in terms of Theil indices that are subject to straightforward interpretation. Illustrations show that the divergence of absolute from relative localization in the EU-15 and in UK manufacturing is largely a statistical artifact inherited from the peculiarities of the industry classifications.
Los estudios empíricos sobre la evolución de la concentración, la especialización o la localización de la actividad económica han proporcionado hasta la fecha resultados ambiguos que dependen fuertemente de la elección de la referencia por parte del investigador. Este artículo desarrolla un método de desagregación para índices de Theil de localización que aclara el origen de esta ambigüedad. El método permite expresar la diferencia entre los índices de Theil de localización absolutos y relativos, en términos de índices de Theil que están sujetos a una interpretación directa. Los ejemplos muestran que la divergencia de localización absoluta a relativa en la UE-15 y en el sector de manufacturas del Reino Unido es en gran parte un artefacto estadístico heredado de las peculiaridades de las clasificaciones de los sectores industriales.
In economic theory, one can distinguish between variety as a source of regional knowledge spillovers, called Jacobs externalities, and variety as a portfolio protecting a region from external shocks. We argue that Jacobs externalities are best measured by related variety (within sectors), while the portfolio argument is better captured by unrelated variety (between sectors). We introduce a methodology based on entropy measures to compute related variety and unrelated variety. Using data at the NUTS-3 level in the Netherlands for the period 1996-2002 we find that Jacobs externalities enhance employment growth, while unrelated variety dampens unemployment growth. Productivity growth can be explained by traditional determinants including investments and R&D expenditures. Implications for regional policy follow
O'Donoghue D. and Gleave B. (2004) A note on methods for measuring industrial agglomeration, Reg. Studies 38, 419- 427. A range of quantitative techniques have been employed by researchers in economic geography and other social science disciplines for the purpose of measuring and spatially delimiting agglomerations of industrial activity. However, these techniques appear to have been applied with little consistency within the literature, particularly with regard to the use of arbitrary cut-off values for determining what level of industrial specialization defines an agglomeration. This paper proposes a new measure, the 'standardized location quotient', which recognizes agglomerations as being comprised of locations with statistically significant (rather then arbitrarily defined) location quotient values for the industry/activity under analysis. The use of the measure in delimiting spatial agglomerations within the UK business services sector, using recent employment and workplace data, is demonstrated.
Only a few research papers have analysed the spatial distribution of
economic activity in Ireland. There are a number of reasons for this, not least the fact
that comprehensive data on the location of economic activity by sector across all
sectors has not been available at the highly disaggregated spatial level. This paper
firstly establishes the geographic distribution of employment at the 2 digit NACE
level, using a novel approach that utilises a special tabulation from the CSO 2006
Census of Population Place of Work Anonymised Records (POWCAR). It then
analyses the spatial patterns of this distribution using maps and more formal methods
such measures of spatial concentration and tests for spatial autocorrelation. The paper
considers the locational preferences of individual sectors, the degree to which specific
sectors agglomerate and co-agglomerate, and thus will uncover urbanisation effects
and differences across urban and rural areas regarding economic activity.
'The empirical data and analysis is rich and well-written and so is the policy section. . . the book provides a valuable addition to the literature of regional clusters and should be included as a must-read for those involved not only in research, but also in policy-making on regional clusters.'- Jukka Teräs, Regional Studies. © Dirk Fornahl, Sebastian Henn and Max-Peter Menzel 2010. All rights reserved.
Although a growing number of studies emphasize the advantages small firms gain by co-locating in space, there is little empirical work that directly examines clustering trends by firm size. This paper presents an empirical analysis of the isolated effects of size on clustering patterns of producers in a major manufacturing state in the southeast United States. Recent developments in point process modeling allow us to control for the critical fact that economic activity is, in general, concentrated in space. Our findings suggest that the relationship between establishment size and clustering in North Carolina is roughly characterized by an inverted u-shape, that is, clustering increases up to some size threshold and then decreases again.
Identifies and discusses three different types of small firms, considering the ways of discriminating among them and their relationships to scale economies. Regional variation in small firm distribution is assessed, and finally considers the case of small firms in industrial districts in detail, including the significance of local government. -T.Hoare
This chapter presents a survey of factors associated with the crafting of new innovative high-technology clusters. The evidence strongly supports the view that there are strong agglomeration forces in high-technology sectors, mainly related to the concentration of scientific knowledge. Adequate incentive structures and entrepreneurial activity are also important, as are spin-offs from highly capable universities and research centres. Thus, the emergence of clusters is not a purely random phenomenon. Initial conditions and 'endowments' play a crucial role in defining the geography of innovation. However, these do not suffice to account either for the genesis of clusters, neither for the failures. The literature forcefully points to the observation that processes are the essence of what clusters are made of.
This paper examines the micro foundations of geographical concentration of Chinese manufacturing industries in China at very disaggregated levels using the most recent economic census data. The empirical results indicate that natural advantages, agglomeration economies and institutional changes together influence industrial location in China. Overall, industries bearing higher transportation costs and difficulty to ship are largely dispersed. Resource-based industries follow the pattern of natural advantages and show less agglomeration but metal mineral consuming industries are agglomerated. Trading establishments and foreign enterprises are heavily concentrated, confirming the importance of globalization effects. However, local protectionism has indeed discouraged industrial agglomeration, but provincial governments are more likely to succeed in exercising local protectionism policies and imitation strategy compared to the county governments. Agglomeration economies have done a better job in driving the geographical concentration of Chinese industries at the county level than at the province level. Proxies for knowledge spillovers are highly significant at the county level. The findings suggest that the spatial scale matters in understanding industrial clustering, and economic transition and its consequence are also critical in explaining the spatial pattern of Chinese industries.
This article briefly discusses the previous literature on differences across sectors in innovation and then puts forward the concept of sectoral systems of innovation. It also discusses the basic building blocks of sectoral systems: knowledge, technological domains, and sectoral boundaries; actors, relationships, and networks; and institutions. Furthermore, this article examines the dynamics and transformation of sectoral systems. Finally, it discusses some policy implications and the challenges ahead. This article looks at a large number of sectors that are highly innovative and technologically advanced and have strong links with science, which nevertheless organize innovation very differently: computers, semiconductors, telecommunication equipment and services, software, chemicals, pharmaceuticals and biotechnology, and machine tools. The role of innovation in the dynamics and transformation of these sectors is highly diverse.
This paper investigates whether the geographic distribution of manufacturing activities depends on the size of plants. Using Italian data we find, as in Kim (1995) and Holmes and Stevens (2002, 2004), that large plants are more concentrated than small plants. However, considering distance-based patterns via spatial auto-correlation, we find that small establishments actually exhibit a greater tendency to be located in adjacent areas. These apparently contradictory findings raise a measurement issue regarding co-location externalities, and suggest that large plants are more likely to cluster within narrow geographical units (concentration), while small establishments would rather co-locate within wider distance-based clusters (agglomeration). This picture is consistent with different size plants engaging in different transport-intensive activities.
With the publication of his best-selling books "Competitive Strategy (1980) and "Competitive Advantage (1985), Michael E. Porter of the Harvard Business School established himself as the world's leading authority on competitive advantage. Now, at a time when economic performance rather than military might will be the index of national strength, Porter builds on the seminal ideas of his earlier works to explore what makes a nation's firms and industries competitive in global markets and propels a whole nation's economy. In so doing, he presents a brilliant new paradigm which, in addition to its practical applications, may well supplant the 200-year-old concept of "comparative advantage" in economic analysis of international competitiveness. To write this important new work, Porter and his associates conducted in-country research in ten leading nations, closely studying the patterns of industry success as well as the company strategies and national policies that achieved it. The nations are Britain, Denmark, Germany, Italy, Japan, Korea, Singapore, Sweden, Switzerland, and the United States. The three leading industrial powers are included, as well as other nations intentionally varied in size, government policy toward industry, social philosophy, and geography. Porter's research identifies the fundamental determinants of national competitive advantage in an industry, and how they work together as a system. He explains the important phenomenon of "clustering," in which related groups of successful firms and industries emerge in one nation to gain leading positions in the world market. Among the over 100 industries examined are the German chemical and printing industries, Swisstextile equipment and pharmaceuticals, Swedish mining equipment and truck manufacturing, Italian fabric and home appliances, and American computer software and movies. Building on his theory of national advantage in industries and clusters, Porter identifies the stages of competitive development through which entire national economies advance and decline. Porter's finding are rich in implications for both firms and governments. He describes how a company can tap and extend its nation's advantages in international competition. He provides a blueprint for government policy to enhance national competitive advantage and also outlines the agendas in the years ahead for the nations studied. This is a work which will become the standard for all further discussions of global competition and the sources of the new wealth of nations.
This paper explores the idea that spatial planning-triggered satellite industrial platform-type concentrations may, over time, automatically gain the capacity to generate substantial agglomeration economies and ultimately transform into entities capable of stimulating self-perpetuating growth. Applying the lexicon of agglomeration theory, the idea is explored in the context of the spatial dynamics of the pharmaceutical industry in Ireland. Spatial concentration indices indicate a particularly high level of spatial concentration in one of the industry's sub-sectors, namely, drug substance production. Based on interview data and secondary sources, a detailed investigation of the spatial dynamics of the Irish concentrations suggests that, while some agglomeration advantages have emerged, they remain relatively limited and have played only a minor role in shaping local industrial concentration. They are mainly of the urbanisation type, relating particularly to the pooled market for workers. The evidence serves to show that the kind of spatial planning-triggered satellite industrial platforms in late-developing economies do not automatically start generating substantial agglomeration economies and crucial technological spillovers, not even after, as in the case of the Cork pharmaceuticals concentration, nearly 40 years of existence.
For geographers and economists, urban agglomeration remains an enduring feature of the industrial landscape and a perennial source of theoretical and empirical interest. Curiously, despite this long-standing interest, there has been a remarkable tendency to explain agglomeration with reference to Alfred Marshall's trinity of external economies and industrial district model. In this paper, we seek to draw some contrasts in the form and causes of agglomeration. Our discussion proceeds by developing a simple and highly schematic taxonomy of what could be considered the emblematic forms of agglomeration in proto-industrial, industrial and post-industrial urban contexts. Highly simplified though they are, such contrasts highlight the changes in the spatial extent of agglomeration, the contribution of particular industrial sectors and types of external economy and of exports to the process of agglomeration over time. As such, there is an urgent need to reconcile the perspectives of economists and geographers in a renewal of the theory of agglomeration.
The main argument advanced in this paper is that proximity matters. Product innovations, new forms of organization or new skills are arrived at in interactive processes within industrial systems. Such systems are embedded in a broader cultural and institutional context. Everything else being equal, interactive collaboration will be less costly and more smooth, the shorter the distance between the participants. The benefits of proximity can be translated into a force of spatial agglomeration in relation to firms engaged in interactive learning. Thus, agglomerations of related economic activity are not just reminiscents of previously cost efficient spatial configurations, but are currently being recreated as a result of an increasing demand for rapid knowledge transfer between firms. In this finding, we argue, lies the foundation for explaining the observed durability in otherwise incomprehensible patterns of specialization and competitiveness between countries and regions.
Over the past few years, a new 'geographical' economics has emerged, focused on the spatial agglomeration of industry and the long-run convergence of regional incomes. Several leading names are associated with this 'geographical turn', including Paul Krugman, Michael Porter, Robert Barro and W. Brian Arthur. This 'new economic geography', it is argued here, is neither that new, nor is it geography. Instead, it is a reworking (or re-invention)-using recent developments in formal (mathematical) mainstream economics-of traditional location theory and regional science. As such it is quite opposed to, and difficult to reconcile with, the work on regional development and industrial agglomeration being carried out in economic geography proper.
Fundamental problems exist with the classical characterisation of agglomeration economies, since such definitions do not reflect the various cost issues on which firms may wish to economise. A lack of understanding of the relationship between the notions of market hierarchies and locational behaviour leads to confusion not only in applied economic interpretation, but more fundamentally in the construction of theoretical location models. In particular, neo-classical location theory can be shown to be crucially flawed as a basis for spatial analysis. This paper therefore attempts to provide an alternative definition of the various types of agglomeration economies such that the various strands of economic theory might be used in a more rigorous manner in the discussion of spatial increasing returns.
The concept of external/agglomeration economies has held a central place within geographical accounts of the spatial concentration of economic activity since Weber's discussion of agglomeration. The use of the concept within the geographical literature has not been without its problems. After a brief estrangement from mainstream industrial geography, the concept is once again the centre-piece of influential accounts of the spatial organisation of production. This paper examines the internal consistency of the 'flexible accumulation' thesis. It examines the microeconomic logic to agglomeration within accounts of a new regime of accumulation. One influential account of the agglomeration of production is examined in the light of a brief review of the use of the concept of external/agglomeration economies within the geographical literature. The paper identifies several shortcomings of contemporary explanations of agglomeration.
Although a growing number of studies emphasize the advantages small firms gain by co-locating in space, there is little empirical work that directly examines clustering trends by firm size. This paper presents an empirical analysis of the isolated effects of size on clustering patterns of producers in a major manufacturing state in the southeast United States. Recent developments in point process modeling allow us to control for the critical fact that economic activity is, in general, concentrated in space. Our findings suggest that the relationship between establishment size and clustering in North Carolina is roughly characterized by an inverted u-shape, that is, clustering increases up to some size threshold and then decreases again.
Identifies and assesses three types of industrial districts that exist as alternatives to the "new industrial district" model, to remark on the limits of a locally targeted development strategy. Industrial districts are defined as sizable and spatially delimited areas of trade-oriented economic activity with a distinct specialization. "Sticky places" are industrial districts with the ability to both attract and keep capital and labor, despite globalizing tendencies. Especially in advanced capitalist countries, corporations are faced with the problem of maintaining income-generating activities rather than outsourcing labor to developing countries. This analysis rejects the "new industrial district" (NID) traditionally offered as a solution - that is, the proposed "flexibly specialized" scenario of small, innovative firms in a successful system of industrial governance. Metropolitan growth since 1970 was studied for four countries - the United States, Japan, Korea, and Brazil -and include one case in each country that conformed to the NID, as well as three to five others that did not. Utilizing interviews and examination of documents, three alternative models emerged -- the hub-and-spoke district, the satellite industrial platform, and the state-centered district. These models reject the NID emphasis on small firms, instead demonstrating the power of the state and/or multinational corporations. As opposed to the NID internal emphasis, the proposed models are exogenously driven and allow increased networking across districts. Districts emerge as a result of multiple forces, including industry structures, cororate strategies and public policies. The study of industrial districts needs to move away from the NID model, encompassing a greater variety of firms, and analyzing more closely their links to the larger industry and global economy from which they emerge. (CJC)
Advocacy of the advantages accruing to business clusters in developing economies has followed that in developed economies. With doubts emerging about the evidence for these in developed economies, it is therefore appropriate to review the experience in the developing world. A model of cluster emergence and growth has guided accounts of developing country clusters. Drawing on experience from Indonesia, doubts are raised about that model's prediction of the emergence of successful joint action in maintaining cluster advantages. Any advantages from clustering are insufficient to face development challenges arising from the globalisation of economic activity. The significance of business clusters in low income economies needs to be reviewed in the light of actual experience and the reappraisal emerging in developed or high income countries.
This paper investigates whether the geographic distribution of manufacturing activities depends on the size of plants. Using Italian data, we find, as in Kim [Kim, S., 1995. Expansion of markets and the geographic concentration of economic activities: the trends in U.S. regional manufacturing structure, 1860–1987, Quarterly Journal of Economics 110 (4), 881–908.], Holmes and Stevens [Holmes, T.J., and Stevens, J.J., 2002. Geographic concentration and establishment scale, Review of Economics and Statistics 84, 682–690.], and Holmes and Stevens [Holmes, T.J. and Stevens, J.J., 2004. Spatial distribution of economic activities in North America, in: J.V. Henderson and J.F. Thisse, eds., Handbook of Regional and Urban Economics, Vol.4, (Elsevier-North Holland, Amsterdam).], that large plants are more concentrated than small plants. However,
considering distance-based patterns via spatial auto-correlation, we find that small establishments actually
exhibit a greater tendency to be located in adjacent areas. These apparently contradictory findings raise a measurement issue regarding co-location externalities and suggest that large plants are more likely to cluster within narrow geographical units (concentration), while small establishments would rather co-locate within wider distance-based clusters (agglomeration). This picture is consistent with different size plants engaging in different transport-intensive activities.
The purpose of this paper is to offer an empirical investigation of the geographic concentration of French industries. The index of concentration is derived from a location model in the line of Ellison and Glaeser (1994, 1997) and can be interpreted as the correlation between the location decisions of two business units in the same industry. Along with extractive and traditional industries, some high technology industries are highly localized, which supports the view that technological spillovers may be important. Besides, the identification of the most and least localized industries reveals similar patterns in France and in the U.S.
Over the past decade, there has been growing interest in local industrial agglomeration and specialization, not only by economic geographers but also by economists and by policy-makers. Of the many ideas and concepts to have emerged from this new-found focus, Michael Porter's work on clusters has proved by far the most influential. His cluster theory has become the standard concept in the field, and policy-makers the world over have seized upon Porter's cluster model as a tool for promoting national, regional, and local competitiveness, innovation and growth. But the mere popularity of a construct is by no means a guarantee of its profundity. Seductive though the cluster concept is, there is much about it that is problematic, and the rush to employ cluster ideas has run ahead of many fundamental conceptual, theoretical and empirical questions. Our aim is to deconstruct the cluster concept in order to reveal and highlight these issues. Our concerns relate to the definition of the cluster concept, its theorization, its empirics, the claims made for its benefits and advantages, and its use in policy-making. Whilst we do not wish to debunk the cluster idea outright, we do argue for a much more cautious and circumspect use of the notion, especially within a policy context: the cluster concept should carry a public policy health warning.
Incl. bibliographical notes and references, index, biographical note on the author
While the geographical clustering of economic activities remains an enduring feature of the industrial landscape and a perennial source of theoretical and empirical interest, the geographical scale at which external economies and agglomerative effects are now claimed to operate is on the increase. Such changes in the spatial form and potential causes of agglomeration over time pose important questions. How should we analyse changes in the spatial extent of external economies and agglomerative effects? Ought we to pay more attention to the sorts of banal economic spaces thrown up as part of increasingly diffuse forms of agglomeration? To answer the first of these questions, it is noted how economists and geographers have explained agglomerations often in the rather singular and invariant categories of pecuniary and Marshallian externalities respectively. This paper considers the relevance of neo-Marshallian analysis and the concept of 'borrowed size'—as variations on these classical principles—to an analysis of the mobility and fixity of external economies and contemporary diffuse forms of agglomeration. Whilst reflecting important changes in the spatial extent of industrial agglomerations, they are insufficiently sensitive to the interaction of different types of external economies with different scale-dependencies. In answering the second question, it is noted that part of the value of analysing the economic basis of largely overlooked 'banal' intermediate places lies in what they may reveal about the functioning of diffuse forms of agglomeration.
This paper discusses the prevalence of Silicon Valley-style localizations of individual manufacturing industries in the United States. A model in which localized industry-specific spillovers, natural advantages, and random chance contribute to geographic concentration motivates new indices of geographic concentration and coagglomeration. The indices contain controls that facilitate cross-industry and cross-country comparisons. The authors find almost all industries to be more concentrated than a random dart-throwing model predicts but the degree of localization is often slight. They also discuss which industries are concentrated, the geographic scope of localization, coagglomeration patterns, and other topics. Copyright 1997 by the University of Chicago.
Lever W. F. (1972) Industrial movement, spatial association and functional linkage. Reg. Studies 6, 371--384. Much of the Government's distribution of industry policy depends upon the availability of mobile industry which can be diverted from the congested South East and Midlands to the regions of high unemployment. Recent work has suggested that external economies, particularly those associated with access to suppliers of inputs and customers, may be more important than regional planners assume. The paper uses correlation coefficients to measure the degree of spatial association between pairs of industries and input-output tables to measure the importance of functional linkages between pairs of industries. Functional linkages are found to have a strong locational effect even upon such modern expanding industries as engineering, metal goods industries and motor vehicle manufacture. The paper concludes that there is an important distinction to be drawn for regional employment policies between the expanding metal and engineering industries of the West Midlands and the expanding science-based industries of the London Metropolitan region.
De Propris, L. (2005) Mapping local production systems in the UK: methodology and application, Regional Studies 39 , 197-211. The paper outlines a possible methodology to map and study local production systems. The three-level diagnostic methodology enables researchers to map, classify and analyse in depth firms' agglomerations in regions or countries where there is little information about the presence and location of local production systems. The spatial diagnostic procedure is applied to the UK to map local production systems.
In this paper, we respond to Steven Brand's criticisms of our FLQ formula for adjusting national input-output tables to take account of interregional trade. We argue that the FLQ's cross-industry foundations are theoretically appropriate and that our approach provides a rigorous basis for testing the traditional assumption of identical regional and national technology. We provide a more detailed rationale for the role of regional size in the FLQ formula and also present a revised version of this formula. Notwithstanding Brand's criticisms, we aim to demonstrate that the FLQ remains a very useful addition to the regional analyst's tool box.
The concept of agglomeration economies, first considered in a systematic (though rather restrictive) manner by Weber, has proven to be an important feature in the analysis of industrial location, whether this is of a theoretical or empirical nature. In either case considerable reliance has been placed on the categories of agglomeration economy proposed by Ohlin. These were termed by Hoover scale economies, localisation economies and urbanisation economies, and were later discussed in some detail by Isard. Leaving aside the reasonable concerns of McCann, who argued that attention should be concentrated on the cost issues underlying agglomeration economies, such as tripartite classification is incomplete in several respects, and therefore represents at best a partial summary. It has recently been argued that the agglomeration economies enjoyed by a firm can be divided into those based on internal economies and those based on external economies, and also that each kind of economy can be considered in terms of scale, scope or complexity. A classification organised around these distinctions subsumes the Ohlin-Hoover classification, and also permits a sharpening of his categories. The concern here is to explore certain implications of this classification, and to examine a number of issues that have probably not received adequate attention. These issues include: the residual nature of agglomeration economies; the possibility of agglomeration without agglomeration economies; and the spatial context of agglomeration economies. It will be argued that such issues need to be addressed if the concept of agglomeration is to be employed effectively in the analysis of industrial location.