The new economy in Spain: a regional analysis

There is no enough evidence about the effects of the new information and communication technologies (ICT) in Spain and how these ICT cause differences between regions. So, the aim of this work is to analyze the regional disparities relative to the new economy in Spain. In the first part of this work, we will review the literature about the concept and measure of the new economy and the problems derived from the high number of definitions about it that difficult an homogeneous analysis. Despite of the several definitions, new economy refers, basically, to an economic development based in Internet and the technologic knowledge as the main inputs. Secondly, we review the empirical evidence about the location factors associated with the new economy. As we highlight in this section, the main conclusion is the complexity of the location dynamic related with the new economy because the results of the empirical studies range from the spatial concentration to the spatial dispersion. In the third section, we analyze the methodology and the empirical results. We collect regional indicators of the new economy in Spain trying to establish if the growth of the new economy in Spain has generated a high spatial concentration. But measuring the new economy at the regional level is even more difficult than it is at the national level because many of the most useful data tend to be nationally oriented. Therefore, it will be used a statistical database with the 28 regional indicators. The 28 indicators in this database are divided into 4 categories about the new economy: ICT industry, ICT services, the knowledge society and the information society. Firstly, we analyse the spatial concentration of the new economy variables in the Spanish territory with the aim of comparing the spatial concentration of the new economy with the spatial concentration of the economic activity. Next, we will construct a composite indicator that will give us the information about the relative position of a region in the new economy in order to find a variable that reflects the regional development of the new economy. Also, to compare the new economy indicator with the conventional economy it will be used the GDP per capita. As a preliminary result we find that the regional disparities in economic growth are more reduced than the regional disparities in the development of the new economy. So, the spatial concentration of the new economy is higher than the spatial concentration of the conventional economic activity. Also, a second preliminary conclusion is the relationship between a high economic development and a high level of the new economy. Finally, we conclude with an exposition of the main conclusions highlighting that the Internet and the ICT are an important progress instruments but can generate a growing of the regional disparities. Therefore, the role of the public sector promoting the introduction and development of the information and knowledge society, specially, in the regions with a low position in the new economy characteristics is essential.

The determinants of regional specialisation in business services: agglomeration economies, vertical linkages and innovation

The article accounts for the determinants of sectoral specialisation in business services (BS) across the EU-27 regions as determined by: (i) agglomeration economies (ii) the region-specific structure of intermediate linkages (iii) technological innovation and knowledge intensity and (iv) the presence of these factors in neighbouring regions. The empirical analysis draws upon the REGIO panel database over the period 1999–2003. By estimating a Spatial Durbin Model, we find significant spatial effects in explaining regional specialisation in BS. Our findings show that, besides urbanisation economies, the spatial structure of intermediate sectoral linkages and innovation, in particular Information and Communication Technologies (ICTs), are important determinants of specialisation in BS. The article contributes to the debate on the global versus local determinants of regional specialisation in BS by restating the importance of the regional sectoral structure besides that of urbanisation. We draw policy implications by rejecting the ‘footloose hypothesis’ for BS

An assessment of EU Cohesion Policy in the UK regions: direct effects and the dividend of targeting. LEQS Discussion Paper No. 135/2018 June 2018

With the prospective exit of the UK from the European Union, a crucial question is whether EU Structural Funds have been beneficial for the country and which aspects of Cohesion Policy should be maintained if EU funds are to be replaced. This paper addresses this question through a twofold investigation, assessing not only whether but also how EU funds have contributed to regional growth in the UK over three programming periods from 1994 to 2013. We document a significant and robust effect of Cohesion Policy in the UK, with higher proportions of Structural Funds associated to higher economic growth both on the whole and particularly in the less developed regions of the country. In addition, we show that the strategic orientation of investments also plays a distinct role for regional growth. While concentration of investments on specific pillars seems to have no direct growth effects, unless regions can rely on pre-existing competitive advantages in key development areas, we unveil clear evidence that targeting investments on specific areas of relative regional need has a significant and autonomous effect on growth. These findings have important implications for the design of regional policy interventions in Britain after Brexit

Spatial patterns of knowledge-intensive business services in cities of various sizes, morphologies and economies

We compare intra-urban localization patterns of advertising and IT companies in three large Czech cities. The main aim of our analysis is an empirically-based contribution to the question to what extent do knowledge bases affect the spatial distribution of various knowledge-intensive business industries. The central research question is: To what extent is the localization of these two industries influenced by different modes of innovation/knowledge bases (symbolic vs. synthetic) and to what extent by contextual factors, such as urban size, morphology, position in the urban hierarchy and economic profile of the given city. We found that the urban contexts shape the localization patterns of advertising and IT companies more than differences in knowledge bases-both industries cluster primarily in the inner cities and urban cores. Formation of more suburban IT "scientific neighborhoods" is limited.Web of Science125art. no. 184

Methods for detecting spatial clustering of economic activities using micro-geographic data

This PhD thesis consists of three self-contained but related essays on the topic of empirical assessment of spatial clusters of economic activities within a micro-geographic framework. The tendency of economic activities to be concentrated in a specific territory is well recognized, starting at least from the seminal studies by Alfred Marshall (Marshall, 1920). This spatial behaviour is not fortuitous; by concentrating in some areas firms enjoy a number of advantages, which then have implications for local economic growth and regional disparities and, as a consequence, are object of study in the fields of economics, geography and policy making. It has been recognized, however, that a major obstacle to further comprehension of the agglomeration phenomena of firms is the lack of a method to properly measure their spatial concentration. The most traditional measures employed by economists, indeed, are not completely reliable. Their most relevant methodological limit lies in the use of regional aggregates, which are built by referring to arbitrary definitions of the spatial units (such as provinces, regions or municipalities) and hence introduce a statistical bias arising from the chosen notion of space. This methodological problem can be tackled by using a continuous approach to space, where data are collected at the maximum level of spatial disaggregation, i.e. each firm is identified by its geographic coordinates, say (x, y), and spatial concentration is detected by referring to the distribution of distances amongst economic activities. The main purpose of the dissertation is to contribute to the development of this kind of continuous space-based measures of spatial clustering. The scientific context and motivation are outlined in depth in the first three chapters. Then the first essay introduces the space–time K-function empirical tool, proposed in spatial statistical literature, into economic literature in order to detect the geographic concentration of industries while controlling for the temporal dynamics that characterize the localization processes of firms. The proposed methodology allows to explore the possibility that the spatial and temporal phenomena, producing the observed pattern of firms at a given moment of time, interact to provide space–time clustering. The presence of significant space–time interaction implies that an observed pattern cannot be explained only by static factors but that we should also consider the dynamic evolution of the spatial concentration phenomenon. Indeed, for example, new firm settlements may display no spatial concentration if we look separately at each moment of time and yet they may present a remarkable agglomeration if we look at the overall resulting spatial distribution after a certain time period. In general, without knowing the temporal evolution of the phenomenon under study it is not possible to identify the mechanism generating its spatial structure. As a matter of fact, different underlying space–time processes can lead to resulting spatial patterns which look the same. The methodology is illustrated with an application to the analysis of the spatial distribution of the ICT industries in Rome (Italy), in the long period 1920–2005. The problem of disentangling spatial heterogeneity and spatial dependence phenomena when detecting for spatial clusters of firms is the topic of the second essay, “Measuring industrial agglomeration with inhomogeneous K-function: the case of ICT firms in Milan (Italy)”. Spatial clusters of economic activities can be the result of two distinct broad classes of phenomena: spatial heterogeneity and spatial dependence. The former arises when exogenous factors lead firms to locate in certain specific geographical zones. For instance, firms may group together in certain areas in order to exploit favourable local conditions, such as the presence of useful infrastructures, the proximity to the communication routes or more convenient local taxation systems. The phenomenon of spatial dependence, which is often of direct scientific interest, occurs instead when the presence of an economic activity in a given area attracts other firms to locate nearby. For instance, the presence of firms with a leading role encouraging the settlement of firms producing intermediate goods in the same area or the incidence of knowledge spillovers driving industrial agglomerations. This essay suggests a parametric approach based on the inhomogeneous K-function that allows to assess the endogenous effects of interaction among economic agents, namely spatial dependence, while adjusting for the exogenous effects of the characteristics of the study area, namely spatial heterogeneity. The approach is also illustrated with a case study on the spatial distribution of the ICT manufacturing industry in Milan (Italy). The third paper is titled “Weighting Ripley’s K-function to account for the firm dimension in the analysis of spatial concentration”. In the methodological context of the continuous space-based measures of spatial clustering, firms are identified as dimensionless points distributed in a planar space. In realistic circumstances, however, firms are generally far from being dimensionless and are conversely characterized by different dimension in terms of the number of employees, the product, the capital and so on. This implies that a high level of spatial concentration can occur, for example, because many small firms cluster in space, or few large firms (in the limit just one firm) cluster in space. A proper test for the presence of spatial clusters of firms should thus consider the impact of the firm dimension on industrial agglomeration. For this respect, the third essay develops a methodology based on an extension of the K-function considering firm size as a weight attached to each of the points representing the firms’ locations

Methods for detecting spatial clustering of economic activities using micro-geographic data

This PhD thesis consists of three self-contained but related essays on the topic of empirical assessment of spatial clusters of economic activities within a micro-geographic framework. The tendency of economic activities to be concentrated in a specific territory is well recognized, starting at least from the seminal studies by Alfred Marshall (Marshall, 1920). This spatial behaviour is not fortuitous; by concentrating in some areas firms enjoy a number of advantages, which then have implications for local economic growth and regional disparities and, as a consequence, are object of study in the fields of economics, geography and policy making. It has been recognized, however, that a major obstacle to further comprehension of the agglomeration phenomena of firms is the lack of a method to properly measure their spatial concentration. The most traditional measures employed by economists, indeed, are not completely reliable. Their most relevant methodological limit lies in the use of regional aggregates, which are built by referring to arbitrary definitions of the spatial units (such as provinces, regions or municipalities) and hence introduce a statistical bias arising from the chosen notion of space. This methodological problem can be tackled by using a continuous approach to space, where data are collected at the maximum level of spatial disaggregation, i.e. each firm is identified by its geographic coordinates, say (x, y), and spatial concentration is detected by referring to the distribution of distances amongst economic activities. The main purpose of the dissertation is to contribute to the development of this kind of continuous space-based measures of spatial clustering. The scientific context and motivation are outlined in depth in the first three chapters. Then the first essay introduces the space–time K-function empirical tool, proposed in spatial statistical literature, into economic literature in order to detect the geographic concentration of industries while controlling for the temporal dynamics that characterize the localization processes of firms. The proposed methodology allows to explore the possibility that the spatial and temporal phenomena, producing the observed pattern of firms at a given moment of time, interact to provide space–time clustering. The presence of significant space–time interaction implies that an observed pattern cannot be explained only by static factors but that we should also consider the dynamic evolution of the spatial concentration phenomenon. Indeed, for example, new firm settlements may display no spatial concentration if we look separately at each moment of time and yet they may present a remarkable agglomeration if we look at the overall resulting spatial distribution after a certain time period. In general, without knowing the temporal evolution of the phenomenon under study it is not possible to identify the mechanism generating its spatial structure. As a matter of fact, different underlying space–time processes can lead to resulting spatial patterns which look the same. The methodology is illustrated with an application to the analysis of the spatial distribution of the ICT industries in Rome (Italy), in the long period 1920–2005. The problem of disentangling spatial heterogeneity and spatial dependence phenomena when detecting for spatial clusters of firms is the topic of the second essay, “Measuring industrial agglomeration with inhomogeneous K-function: the case of ICT firms in Milan (Italy)”. Spatial clusters of economic activities can be the result of two distinct broad classes of phenomena: spatial heterogeneity and spatial dependence. The former arises when exogenous factors lead firms to locate in certain specific geographical zones. For instance, firms may group together in certain areas in order to exploit favourable local conditions, such as the presence of useful infrastructures, the proximity to the communication routes or more convenient local taxation systems. The phenomenon of spatial dependence, which is often of direct scientific interest, occurs instead when the presence of an economic activity in a given area attracts other firms to locate nearby. For instance, the presence of firms with a leading role encouraging the settlement of firms producing intermediate goods in the same area or the incidence of knowledge spillovers driving industrial agglomerations. This essay suggests a parametric approach based on the inhomogeneous K-function that allows to assess the endogenous effects of interaction among economic agents, namely spatial dependence, while adjusting for the exogenous effects of the characteristics of the study area, namely spatial heterogeneity. The approach is also illustrated with a case study on the spatial distribution of the ICT manufacturing industry in Milan (Italy). The third paper is titled “Weighting Ripley’s K-function to account for the firm dimension in the analysis of spatial concentration”. In the methodological context of the continuous space-based measures of spatial clustering, firms are identified as dimensionless points distributed in a planar space. In realistic circumstances, however, firms are generally far from being dimensionless and are conversely characterized by different dimension in terms of the number of employees, the product, the capital and so on. This implies that a high level of spatial concentration can occur, for example, because many small firms cluster in space, or few large firms (in the limit just one firm) cluster in space. A proper test for the presence of spatial clusters of firms should thus consider the impact of the firm dimension on industrial agglomeration. For this respect, the third essay develops a methodology based on an extension of the K-function considering firm size as a weight attached to each of the points representing the firms’ locations

Agglomeration externalities, innovation and regional growth: Theoretical perspectives and meta-analysis

Technological change and innovation and are central to the quest for regional development. In the globally-connected knowledge-driven economy, the relevance of agglomeration forces that rely on proximity continues to increase, paradoxically despite declining real costs of information, communication and transportation. Globally, the proportion of the population living in cities continues to grow and sprawling cities remain the engines of regional economic transformation. The growth of cities results from a complex chain that starts with scale, density and geography, which then combine with industrial structure characterised by its extent of specialisation, competition and diversity, to yield innovation and productivity growth that encourages employment expansion, and further urban growth through inward migration. This paper revisits the central part of this virtuous circle, namely the Marshall-Arrow-Romer externalities (specialisation), Jacobs externalities (diversity) and Porter externalities (competition) that have provided alternative explanations for innovation and urban growth. The paper evaluates the statistical robustness of evidence for such externalities presented in 31 scientific articles, all building on the seminal work of Glaeser et al. (1992). We aim to explain variation in estimation results using study characteristics by means of ordered probit analysis. Among the results, we find that the impact of diversity depends on how it is measured and that diversity is important for the high-tech sector. High population density increases the chance of finding positive effects of specialisation on growth. More recent data find more positive results for both specialization and diversity, suggesting that agglomeration externalities become more important over time. Finally, primary study results depend on whether or not the externalities are considered jointly and on other features of the regression model specification

Multinational Corporations as Catalyst for Industrial Development: The Case of Poland

In a recent model Markusen and Venables (1999) describe the conditions under which foreign direct investments (FDI) can act as a catalyst for local industrial development. We apply this framework to the case of Poland, allowing for the entry of multinationals in both intermediates and consumption goods industry. We check these assumptions against empirical evidence, exploring agglomeration patterns of multinational and domestic firms at the regional level, and constructing an econometric model able to measure the interactions between the two classes of firms. We find evidence going in the direction of both direct spill-overs and backward and forward linkages between domestic and multinational firms.http://deepblue.lib.umich.edu/bitstream/2027.42/39752/3/wp368.pd

Infrastructure endowment and investment as determinants of regional growth in the European Union

This paper analyses the role of infrastructure endowment and investment in the genesis of regional growth in the European Union. It assesses the economic effects of the existence and improvement of transport networks in light of their interactions with innovation and local socio-economic conditions. The analysis accounts for spatial interactions between different regions in the form of spillovers and network externalities. The regression results highlight the impact of infrastructural endowment on regional economic performance, but also the weak contribution of additional investment. Regions having good transport infrastructure endowment and being well connected to regions with similar good endowments tend to grow faster. However, investment in infrastructure within a region or in neighbouring regions seems to leave especially peripheral regions more vulnerable to competition. Furthermore, the positive impact of infrastructure endowment on growth tends to wane quickly and is weaker than that of, for example, the level of human capital