Abstract:A quite robust model of differential growth rates of per capita income in the major functional urban regions of the European Union is presented and tested for the 1980s. The results underline the important role of purely spatial economic processes in differential regional growth and suggest that the pattern of European urbanisation tends itself to generate systematic divergence of mean per capita incomes between neighbouring city-regions, even though the mechanism generating this divergence of mean incomes is … Show more
“…Comparative studies are generally based on population indicators [6,9,32]. There are, however, numerous examples in which population and economic development do not necessarily go hand in hand.…”
Measuring shrinkage and its effects appears as a fundamental issue in cities’ research. Also, shrinkage is a spatial phenomenon defined by data and information based on space dimension relying on a spatial information. The wide use of geo-information is a useful aid to extend common statistic analyses integrating data collected at different levels, comparing data at a municipal level to data referring at census area level (particularly useful for detailed analyses at a neighbourhood scale). Such analyses are particularly suitable for medium and large cities shrinkage analyses, where different neighbourhoods could have different levels of shrinkage and could need distinct strategies to face such phenomenon. Another methodological problem is the interrelation with other spatial units and nearby cities, which can have an influence on urban labour market, economic development, migration flows and housing market. Thereby, the definition of an appropriate regional context is of crucial importance. After an introduction about a comparison between common statistic analyses and geo-statistical methods, with a short literature review, the paper includes an empirical section describing the case of de-industrialized Taranto city, measuring the major indicators of shrinkage, with data referring to census area level, trying to understand if there are shrinking neighbourhoods in the city of Taranto and what is the appropriate regional shrinking context. Then, the paper continues with a section in which the theoretical knowledge is evaluated comparing theory strongholds to main features of shrinkage exemplified by the case of Taranto, trying to contribute to a better understanding of the questions addressed, highlighting the unresolved problems to address some conclusions about still open research challenges
“…Comparative studies are generally based on population indicators [6,9,32]. There are, however, numerous examples in which population and economic development do not necessarily go hand in hand.…”
Measuring shrinkage and its effects appears as a fundamental issue in cities’ research. Also, shrinkage is a spatial phenomenon defined by data and information based on space dimension relying on a spatial information. The wide use of geo-information is a useful aid to extend common statistic analyses integrating data collected at different levels, comparing data at a municipal level to data referring at census area level (particularly useful for detailed analyses at a neighbourhood scale). Such analyses are particularly suitable for medium and large cities shrinkage analyses, where different neighbourhoods could have different levels of shrinkage and could need distinct strategies to face such phenomenon. Another methodological problem is the interrelation with other spatial units and nearby cities, which can have an influence on urban labour market, economic development, migration flows and housing market. Thereby, the definition of an appropriate regional context is of crucial importance. After an introduction about a comparison between common statistic analyses and geo-statistical methods, with a short literature review, the paper includes an empirical section describing the case of de-industrialized Taranto city, measuring the major indicators of shrinkage, with data referring to census area level, trying to understand if there are shrinking neighbourhoods in the city of Taranto and what is the appropriate regional shrinking context. Then, the paper continues with a section in which the theoretical knowledge is evaluated comparing theory strongholds to main features of shrinkage exemplified by the case of Taranto, trying to contribute to a better understanding of the questions addressed, highlighting the unresolved problems to address some conclusions about still open research challenges
“…An empirical analysis of urban growth in Europe was elaborated in Cheshire and Carbonaro (1996) and the model used is set out in the Appendix. For a number of reasons, variables that were likely to be important in at least some areas were not included.…”
Section: The Impact Of Territorial Competition On Local Growthmentioning
This paper analyses the policy implications of territorial competition; that is the promotion of local economic development in competition with other territories. It does so both in analytical and empirical terms moving from a wider supranational and analytical standpoint to a more practical and local one. The impact of territorial competition in welfare terms depends critically on the perspective adopted. Some policies are pure waste even from the point of view of the initiating territory. Other policies may have a positive impact in economic welfare terms, viewed from the perspective of the territory, but be zero sum from a wider perspective. There may also be policies, however, which increase economic welfare, both locally and from a wider perspective. This suggests that there is a case for providing a supranational regulatory framework. The empirical section first examines the evidence as to whether local policies for economic growth do, in fact, have any impact. The paper concludes with an examination of the actual policies pursued in a sample of European regions and draws out some conclusions for local policy makers.
“…People might choose to live in the non-metro areas, which usually have a lower living cost, and commute to the metro areas in order to pursue a higher paying job (Partridge, Ali, & Olfert, 2010). Cheshire and Carbonaro (1996) showed that a strong positive relationship exists among the length of a commuting trip, income, and measures of human capital. Urban areas with higher income growth attract commuters from neighboring areas, thus increasing their workforce and total GDP.…”
This paper examines the importance of metropolitan spillover effects on the economic growth of non-metropolitan counties in the state of Indiana by using panel data from 2003 to 2013. I hypothesize that metro economic size and non-metro counties' locations, along with other metro social and economic factors, will have significant impact on non-metro counties' economic growth. Based on the results from the Random-effects Generalized Least Squares (GLS) and the population-averaged Generalized Estimating Equations (GEE) regressions, metro GDP and population have significant, positive impacts on non-metro counties' economic growth, while non-metro counties' locations (i.e., the distance to a metro county), metro K-12 school enrollment, the wage gap and the number of commuters between metro and non-metro areas have significant, negative effects on the economic growth of non-metro counties in Indiana. Some of the dummy variables also showed significant association with the non-metro counties' economic well-being.
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