Unveiling Urban Sprawl in the Mediterranean Region: Towards a Latent Urban Transformation?

The relationship between form and function in European Mediterranean cities has been widely addressed from various perspectives. A number of studies indicate that, until the 1980s, compactness was a key trait of several cities of the Northern Mediterranean. However, after the ‘compact growth’ period, these cities experienced patterns of urbanization that differed from their traditional trends. Since the 1990s, sprawl, coupled with population decline in the inner cities, has become the main pattern of urban development. This article explores the key features of exurban development in the Mediterranean region in order to provide material for a discussion based on the differences and similarities in the characteristics of sprawl processes originating in the US and Northern Europe. It concludes that any debate on policy responses to sprawl must be specifically formulated according to the scope, administrative level, housing and planning system, territorial and socioeconomic characteristics of the urban system under examination. It is our belief that sprawl requires site‐specific analyses and policy strategies for the region being studied if the process is to be effectively controlled.     

The economic and environmental performances of rural districts in Italy: Are competitiveness and sustainability compatible targets?

This paper analyses the economic performances of the rural system and the level of land sensitivity to degradation in Italy. Three indicators (district value added, share of agriculture on total product, and a composite index of land sensitivity) were used to classify 784 Italian local districts into eight performance classes. Four classes share a combination of high environmental quality (in terms of land degradation), high (or low) economic performances, and high (or low) productivity of the primary sector. The remaining four are characterised by a combination of low (and declining) environmental quality, high (or low) economic performances, and high (or low) productivity of the primary sector. The eight classes were grouped into four ‘environmental quality’ types and four ‘target performance’ categories to discriminate among high- and low-performance districts by considering twelve additional variables within a Discriminant Function Analysis (DFA). 148 high environmental performance districts (18% of total) were identified mainly across the Alps and Apennine while 314 districts (41%) were classified in the lowest performance class and concentrated in flat areas of southern Italy. The districts with high environmental performances were characterised, on average, by medium to low district value added, moderately low economic weight of the primary sector, and tourism specialisation. Districts with high economic performances and low environmental performances were characterised by high sensitivity to LD, low district value added, high share of agriculture in total product, and the lowest productivity of labour in all economic sectors. In these districts the risk of entering a downward spiral of rural poverty and environmental degradation is potentially high.     

Integrating parametric and non-parametric multivariate analysis of urban growth and commuting patterns in a European metropolitan area

Quality & Quantity - Mono-centric regions have experienced a progressive transformation towards polycentric structures. Transition to discontinuous and dispersed spatial configurations was...     

Robust Small Area Estimation under Spatial Non‐stationarity

The effective use of spatial information in a regression‐based approach to small area estimation is an important practical issue. One approach to account for geographic information is by extending the linear mixed model to allow for spatially correlated random area effects. An alternative is to include the spatial information by a non‐parametric mixed models. Another option is geographic weighted regression where the model coefficients vary spatially across the geography of interest. Although these approaches are useful for estimating small area means efficiently under strict parametric assumptions, they can be sensitive to outliers. In this paper, we propose robust extensions of the geographically weighted empirical best linear unbiased predictor. In particular, we introduce robust projective and predictive estimators under spatial non‐stationarity. Mean squared error estimation is performed by two analytic approaches that account for the spatial structure in the data. Model‐based simulations show that the methodology proposed often leads to more efficient estimators. Furthermore, the analytic mean squared error estimators introduced have appealing properties in terms of stability and bias. Finally, we demonstrate in the application that the new methodology is a good choice for producing estimates for average rent prices of apartments in urban planning areas in Berlin.     

Class diversification,economic growth and urban sprawl: evidences from a pre-crisis European city

Economic expansion indirectly promotes class diversification at the neighbourhood scale with a consequent reduction of social divides at the regional scale. To verify this working hypothesis, the present study investigates class diversification at both spatial scales in a Mediterranean city (Athens, Greece) using the European Socioeconomic Classification based on population census data referring to 1991–2001, a phase of economic expansion and intense urban sprawl preceding the 2004 Olympic games. Results of multivariate analysis and diversity indexes outline a local-scale social mix associated to suburban expansion, and regional-scale class segregation, reflecting an increasing polarization in affluent and economically deprived urban districts. The contrasting pattern at the two spatial scales results in a complex social geography with class diversification and moderate changes over time in the economic spatial divide between urban and neighbouring rural areas. These findings contribute to design scale-dependent policies reducing social inequalities and improving quality of life in urban areas. Future paths for socio-spatial processes were delineated for sprawling metropolitan regions under economic expansion and discussed in the light of future demographic trends in both developed and emerging countries.     

Changes over time in the spatial structure of fertility rates as a dynamic indicator of urban transformations

Quality & Quantity - Since fertility varies largely over space responding to socioeconomic transformations, a spatially explicit analysis of birth rates may contribute to a refined...     

Measuring differences in economic standard of living between immigrant communities in Italy

Measuring differences in the economic standard of living of between natives and other ethnic groups can inform us about the relative disadvantages and inequalities within Italian society. Despite the importance of this question, the measurement of this gap is not an easy task because, when using the usual design-based approach to survey sampling inference, the available micro-data lack sufficient sample size for the majority of immigrant communities needed to obtain reliable estimates. In this paper, we show that small area estimation (SAE) techniques can be applied in a fruitful way to avoid this issue. In particular, we use an approach based on M-quantile regression for estimating the economic standard of living in each community in Italy. Our findings highlight economic disparities between natives and other ethnic groups and suggest the need to adopt specific policies that target the most vulnerable immigrant communities and are designed to improve their economic standard of living.     

Economic downturns and compositional effects in regional population structures by age: a multi-temporal analysis in Greek regions, 1981–2017

Population movements (international and internal migration) and changing fertility and mortality patterns have significantly affected demographic structures. Investigation of the relationship between (evolving) population structures and economic downturns is a key issue in economic demography. Analysis of compositional changes in regional population structures over a sufficiently long time interval may provide an informed knowledge to better understanding of this relationship and the underlying socioeconomic context in European countries. Based on these premises, Greece was considered a paradigmatic case of sequential economic expansions and recessions, impacting the structure of resident population in the last four decades. In this work, changes over time in population structures by age in Greek regions were explored (1981–2017) using a multi-temporal principal component analysis. A diachronic analysis of compositional effects of economic downturns on regional population structures indicates spatially-heterogeneous demographic processes in Greece. The subsequent recession has represented a turning point in Greek demography, consolidating changes in traditional family structures, while stimulating out-migration at younger ages to Northern and Western European regions and containing immigration from developing countries. Metropolitan areas and coastal districts had more rapid population dynamics, while peripheral rural regions experienced more rapid changes towards aging. Population aging had a short-term impact on regional population structures in Greece, with possibly negative consequences for the ability of the country’s economy to recover from crisis.

     

Toward a political budget cycle? Unveiling long-term latent paths in Greece

Quality & Quantity - Empirical studies demonstrated the existence of political budget cycles in many countries, although mechanisms underlying such cycles remain substantially unclear. The...     

Substitutability and weighting of ecological and economic indicators: Exploring the importance of various components of a synthetic index

The establishment of an information system is meaningful to develop a dynamic assessment of environmental quality and degradation. In this paper an original, empirical framework called Factor Weighting Model (FWM) is proposed to integrate different indicators into a composite index. The FWM is able to work with variables depicting different themes (e.g. climate, soil, landscape, demography, economy) collected at various geographical and temporal scales. Three case studies carried out at different spatial scales were considered as examples of FWM application to a composite index of Land Degradation. It consists of several variables collected from various data sources and available at different temporal and spatial scales, which are aggregated into some thematic indicators. The FWM approach was applied separately for each case study to the single variables transformed into sensitivity indicators through standard procedures. A multiway factor analysis (MDA) was carried out to explore over time the relationships among indicators. The importance of the environmental indicators was estimated by attributing a percent weight to each of them according to MDA outputs. Climate and soil dimensions account for the highest weights in all the cases considered. These findings are in accordance with the results obtained in previous studies. The implications of FWM in the assessment of environmental quality are finally discussed.