Measure of Global Specialization and Spatial Clustering for the Identification of "Specialized" Agglomeration


Autoria(s): Haedo, Christian Martin
Contribuinte(s)

Brasini, Sergio

Data(s)

23/03/2009

Resumo

The intensity of regional specialization in specific activities, and conversely, the level of industrial concentration in specific locations, has been used as a complementary evidence for the existence and significance of externalities. Additionally, economists have mainly focused the debate on disentangling the sources of specialization and concentration processes according to three vectors: natural advantages, internal, and external scale economies. The arbitrariness of partitions plays a key role in capturing these effects, while the selection of the partition would have to reflect the actual characteristics of the economy. Thus, the identification of spatial boundaries to measure specialization becomes critical, since most likely the model will be adapted to different scales of distance, and be influenced by different types of externalities or economies of agglomeration, which are based on the mechanisms of interaction with particular requirements of spatial proximity. This work is based on the analysis of the spatial aspect of economic specialization supported by the manufacturing industry case. The main objective is to propose, for discrete and continuous space: i) a measure of global specialization; ii) a local disaggregation of the global measure; and iii) a spatial clustering method for the identification of specialized agglomerations.

Formato

application/pdf

Identificador

http://amsdottorato.unibo.it/1735/1/Christian_Haedo_tesi.pdf

urn:nbn:it:unibo-1432

Haedo, Christian Martin (2009) Measure of Global Specialization and Spatial Clustering for the Identification of "Specialized" Agglomeration, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Metodologia statistica per la ricerca scientifica <http://amsdottorato.unibo.it/view/dottorati/DOT276/>, 21 Ciclo. DOI 10.6092/unibo/amsdottorato/1735.

Idioma(s)

en

Publicador

Alma Mater Studiorum - Università di Bologna

Relação

http://amsdottorato.unibo.it/1735/

Direitos

info:eu-repo/semantics/openAccess

Palavras-Chave #SECS-S/03 Statistica economica
Tipo

Tesi di dottorato

NonPeerReviewed