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Spatial clustering of high‐tech manufacturing and knowledge‐intensive service firms in the Greater Toronto Area
Author(s) -
López Fernando A.,
Páez Antonio
Publication year - 2016
Publication title -
the canadian geographer / le géographe canadien
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.35
H-Index - 46
eISSN - 1541-0064
pISSN - 0008-3658
DOI - 10.1111/cag.12326
Subject(s) - downtown , economies of agglomeration , economic geography , cluster analysis , statistic , cluster (spacecraft) , business , service (business) , high tech , spatial analysis , regional science , geography , logit , marketing , industrial organization , economic growth , computer science , economics , econometrics , statistics , remote sensing , mathematics , archaeology , programming language , machine learning
Key Messages Scan statistic is a useful tool to identify and delimit geographically spatial clustering of economic activity. Spatial clusters of high‐tech and knowledge‐intensive firms in the Greater Toronto Area in Canada are identified. A logit model of cluster membership is used to confirm that proximity to major transportation infrastructure, accessibility to skilled labour, and proximity to downtown are significant factors to explain the agglomeration of firms.