Como se pode distinguir Évora do resto do Alentejo: Uma abordagem de estatística espacial Reportar como inadecuado




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Abstract

Évora county and above all, the city is often cited as a case of success in terms of regional development, as it stands out in terms of social, economic, and demographic indicators from the rest of the region where it is located, i.e. the Alentejo Portugal. This fact makes it relevant: i to measure the -distance-, in terms of those indicators, between the municipality of Évora and the municipalities of the rest of Alentejo, and ii to detect the occurrence of spatial clusters in order to verify to what extent is positioned in advantage in relation to its neighboring counties, its NUT III Alentejo Central and its NUT II Alentejo. In methodological terms, those two tasks are performed in the paper through the use of spatial statistical techniques, including multidimensional scaling and determination of local indicators of spatial association. These techniques, by their simplicity and easiness of application, can be readily used in other cases, which can be seen as a pedagogical purpose intrinsic to this work.



Item Type: MPRA Paper -

Original Title: Como se pode distinguir Évora do resto do Alentejo?: Uma abordagem de estatística espacial-

English Title: How can Évora be distinguished from the rest of Alentejo: A spatial statistics approach-

Language: Portuguese-

Keywords: Évora; Local indicators of spatial association; Multidimensional scaling; Portugal; Spatial autocorrelation; Spatial clusters.-

Subjects: A - General Economics and Teaching > A2 - Economic Education and Teaching of Economics > A22 - UndergraduateC - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: GeneralR - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R12 - Size and Spatial Distributions of Regional Economic ActivityC - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions-





Autor: Caleiro, António

Fuente: https://mpra.ub.uni-muenchen.de/22057/







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