Metropolitan Areas in Spain and Italy

Metropolitan areas concentrate the main share of population, production and consumption in OECD countries. They are likely to be the most important units for economic, social and environmental analysis as well as for the development of policy strategies. However, one of the main problems that occur when adopting metropolitan areas as units of analysis and policy in European countries is the absence of widely accepted standards for identifying them. This severe problem appeared when we tried to perform comparative research between Spain and Italy using metropolitan areas as units of analysis. The aim of this paper is to identify metropolitan areas in Spain and Italy using similar methodologies. The results allow comparing the metropolitan realities of both countries as well as providing the metropolitan units that can be used in subsequent comparative researches. Two methodologies are proposed: the Cheshire-GEMACA methodology (FUR) and an iterative version of the USA-MSA algorithm, particularly adapted to deal with polycentric metropolitan areas (DMA). Both methods show a good approximation to the metropolitan reality and produce very similar results: 75 FUR and 67 DMA in Spain (75% of total population and employment), and 81 FUR and 86 DMA in Italy (70% of total population and employment).metropolitan areas, polycentricity, commuting

Polycentric metropolitan areas in Europe towards a unified proposal of delimitation

Metropolitan areas concentrate the main share of population, production and consumption in OECD countries. They are likely to be one of the most important units for economic, social and environmental analysis as well as for the development of policy strategies. However, one of the main problems that occur when adopting metropolitan areas as units of analysis and policy in European countries is the absence of widely accepted standards for identifying them. This severe problem hinders comparative research between European countries using metropolitan areas as units of analysis. In this text we defend the necessity of a methodology to identify metropolitan areas in Europe. This methodology should fulfil three requisites: first, to be useful for analysis and planning, which requires to represent in a realistic way economic, social and environmental phenomena; second, to be applicable to all the European countries; and third, to be flexible enough to deal with the existence of different administrative and territorial structures across countries as well as to take into account that many metropolitan areas, particularly the largest ones, are polycentric. The aim of this paper is to identify metropolitan areas in Spain and Italy using similar methodologies and to evaluate their application to other European countries. The results allow comparing the metropolitan realities of these countries as well as providing the metropolitan units that can be used in subsequent comparative researches. Two methodologies are proposed: the Cheshire-GEMACA methodology (FUR) and an iterative version of the USA-MSA algorithm, particularly adapted to deal with polycentric metropolitan areas. Both methods show a good approximation to the metropolitan reality and produce very similar results: 75 FUR and 67 DMA in Spain (75% of total population and employment), and 81 FUR and 86 DMA in Italy (70% of total population and employment).

The effect of asylum seeker reception centers on nearby house prices:Evidence from The Netherlands

With 20,945 asylum applications in 2016, the Netherlands received the tenth highest number of asylum requests in Europe. From the time of their arrival, and until a decision on their asylum requests is made, asylum seekers are sheltered in asylum seeker reception centers (ASRCs) across the country. This paper tests whether the opening of reception centers affects the prices of nearby houses. In doing so, likely differential effects across urban and non-urban areas, as well as for ASRCs of distinct capacities to host asylum seekers, are considered. The analysis uses hedonic regressions that are based on a staggered difference-in-differences design. Estimation comes from 2009–2017 information on the transaction prices of houses (N = 347,479) and the locations and opening dates of nearby ASRCs (N = 75). The results indicate that the opening of ASRCs causes the prices of some houses to fall by approximately 9.3%. However, this estimated effect pertains solely to single-family houses in less densely populated areas and for ASRC of high hosting capacity, whereas in cities no economically or statistically significant effects are found. The findings of this study have implications for the design of public policies that regard the spatial dispersion of ASRCs

Monitoring land use in cities using satellite imagery and deep learning

Over time, cities expand their physical footprint on land and new cities emerge. The shape of the built environment can affect several domains which are policy relevant, such as carbon emissions, housing affordability, infrastructure costs, and access to services. This study lays a methodological basis for the monitoring and consistent comparison of land use across OECD cities. An advanced form of deep learning, namely the U-Net model, is used to classify land cover and land use in EC-ESA satellite imagery for 2021. This complements conventional statistical data by monitoring large surfaces of land efficiently and in near real-time. In specific, following the availability of detailed data for model training, built-up areas in residential or business-related use are mapped and analysed for 687 European metropolitan areas, as a case application. Recent urban expansion’s speed and shape are explored, as well as the potential for assessing land use in cities beyond Europe

¿Afecta la política de cohesión europea a la dinámica empresarial regional?

This paper assesses whether European Cohesion Policy funds from the 2007-2013 programming period affected business dynamics in European regions. Using a regression discontinuity approach, the analysis shows that regions receiving more funds experienced higher firm births, without statistically significant firm deaths, resulting in positive net firm creation and growing firm-related employment. In addition, this study confirms previous findings in the literature according to which regions receiving more funds show higher increases in gross value added per worker. Finally, funds have a significantly higher effect on net business employment creation in regions with lower levels of perceived corruption, although this is not necessarily conductive to higher levels of labour productivity in those regions.Este documento evalúa si los fondos de la Política de Cohesión Europea del período de programación 2007-2013 afectaron la dinámica empresarial en las regiones europeas. Usando un enfoque de discontinuidad de regresión, el análisis muestra que las regiones que reciben más fondos experimentaron un mayor nacimiento de empresas, sin muertes de empresas estadísticamente significativas, lo que resultó en una creación neta de empresas positiva y un aumento del empleo relacionado con las empresas. Además, este estudio confirma hallazgos previos en la literatura según los cuales las regiones que reciben más fondos muestran mayores incrementos en el valor agregado bruto por trabajador. Finalmente, los fondos tienen un efecto significativamente mayor en la creación neta de empleo empresarial en regiones con niveles más bajos de corrupción percibida, aunque esto no conduce necesariamente a niveles más altos de productividad laboral en esas regiones

Questioning polycentric development and its effects: issues of definition and measurement for the Italian NUTS 2 Regions

Polycentric development is a widely-used term both in academic research and in the normative agenda. However, its theoretical foundations and economic implications are still unknown and the concept of polycentricity still does not have a shared definition, or a shared measurement method. The aim of this paper is twofold. Firstly polycentricity is defined and measured at a NUTS 2 regional level, by comparing functional and morphological methods. Secondly, in the light of the role assigned to polycentric development in terms of policy, the paper investigates the relationships between the degree of regional polycentricity and the key economic variables of performance – namely competitiveness, social cohesion and environmental sustainability. The main finding was that functional and morphological methods led to similar results. In addition, a correlation was found between polycentricity and a more unequal income distribution and a higher level of productivity, especially when polycentricity was measured in functional terms. No stable correlations were found between polycentricity and measures of environmental sustainability, such as land consumption and greenhouse emissions

Questioning polycentric development and its effects: issues of definition and measurement for the Italian NUTS 2 Regions

Polycentric development is a widely-used term both in academic research and in the normative agenda. However, its theoretical foundations and economic implications are still unknown and the concept of polycentricity still does not have a shared definition, or a shared measurement method. The aim of this paper is twofold. Firstly polycentricity is defined and measured at a NUTS 2 regional level, by comparing functional and morphological methods. Secondly, in the light of the role assigned to polycentric development in terms of policy, the paper investigates the relationships between the degree of regional polycentricity and the key economic variables of performance – namely competitiveness, social cohesion and environmental sustainability. The main finding was that functional and morphological methods led to similar results. In addition, a correlation was found between polycentricity and a more unequal income distribution and a higher level of productivity, especially when polycentricity was measured in functional terms. No stable correlations were found between polycentricity and measures of environmental sustainability, such as land consumption and greenhouse emissions

Questioning polycentric development and its effects: issues of definition and measurement for the Italian NUTS 2 Regions

Polycentric development is a widely-used term both in academic research and in the normative agenda. However, its theoretical foundations and economic implications are still unknown and the concept of polycentricity still does not have a shared definition, or a shared measurement method. The aim of this paper is twofold. Firstly polycentricity is defined and measured at a NUTS 2 regional level, by comparing functional and morphological methods. Secondly, in the light of the role assigned to polycentric development in terms of policy, the paper investigates the relationships between the degree of regional polycentricity and the key economic variables of performance – namely competitiveness, social cohesion and environmental sustainability. The main finding was that functional and morphological methods led to similar results. In addition, a correlation was found between polycentricity and a more unequal income distribution and a higher level of productivity, especially when polycentricity was measured in functional terms. No stable correlations were found between polycentricity and measures of environmental sustainability, such as land consumption and greenhouse emissions

Consistent metropolitan boundaries for the remote sensing of urban land

This paper introduces an internationally consistent definition of metropolitan areas to the literature regarding the remote sensing of urban land use or land cover. In the cross-comparison of land use or land cover for explicitly bounded urban areas, the observed ‘economic’ definition is argued to hold distinct potential merits over administrative or agglomeration-based boundaries, which typically underpin other studies. To illustrate the proposed merits as well as their implications for the remote sensing literature, the empirical analysis considers the case of 687 European metropolitan areas. Across these metropolitan areas, whose boundaries are defined jointly by the OECD and the European Commission, land cover and land use are segmented in a fusion of imagery from radar and optical sensors in Sentinel satellites. Segmentation is achieved using deep learning in a well-established model architecture. The analytical focus is on built-up areas that are in a residential use or in a commercial or industrial use. Map classifications and accuracy measures are obtained for cities as well as their respective commuting zones as these together embody metropolitan areas. The results underline that not only land use area estimates but also map classification accuracy vary widely across individual metropolitan areas. Whereas classification accuracy to some degree varies for metropolitan areas within as well as between countries, classification accuracy is positively associated with population size and built-up area density as regression analysis confirms. Additionally, the extent of built-up areas in distinct uses is shown to vary across different types of metropolitan (sub-)areas. This study's findings highlight the typically unobserved role that study area definition and selection may play in affecting outcomes in remote sensing studies in urban settings, as relevant to both studies of single as well as multiple urban areas. The consistent comparison of remote sensing outcomes across metropolitan areas may further promote generalization in a growing and global field and potentially supports better-informed policy making processes.</p

Living Near to Attractive Nature? A Well-Being Indicator for Ranking Dutch, Danish, and German Functional Urban Areas

While nature is widely acknowledged to contribute to people's well-being, nature based well-being indicators at city-level appear to be underprovided. This study aims at filling this gap by introducing a novel indicator based on the proximity of city-residents to nature that is of high-amenity. High-amenity nature is operationalized by combining unique systematic data on people's perceptions of what are the locations of attractive natural areas with data on natural land cover. The proposed indicator departs from the usual assumption of equal well-being from any nature, as it approximates the 'actual' subjective quality of nature near people's homes in a spatially explicit way. Such indicator is used to rank 148 'cities' in the Netherlands, Denmark, and Germany. International comparability of the indicator is enhanced by the use of a definition of cities as functional urban areas (FUAs), which are consistently identified across countries. Results demonstrate that the average 'nearness' of FUA populations to high amenity nature varies widely across the observed FUAs. A key finding, that complements insights from existing city-level indicators, is that while populations of FUAs with higher population densities may live relatively far from nature in general, they also live, on average, closer to high-amenity nature than inhabitants of lower density FUAs. Our results may stimulate policy-debates on how to combine urban agglomeration with access to natural amenities in order to account for people's wellbeing