A stochastic independence approach for measuring regional specialization and concentration

This paper proposes an integrated framework for discussing issues related to regional concentration, sectorial specialization and overall localization by considering these concepts as a row-column association– or non-independence– in a two-way contingency table ‘regions × sectors’. This is the approach of stochastic independence, in which the degree of concentration, or of specialization, is measured by discrepancies among distributions: between profiles and a uniform distribution for absolute concepts; between profiles and the corresponding marginal distribution for relative concepts; or between the joint distribution and the product of the marginal distributions for overall localization. This paper discusses the benefits of this integrating approach, particularly for the practitioner facing a multifaceted literature.

• metadata
• relations

Document type	Article de périodique (Journal article) – Article de recherche
Access type	Accès restreint
Publication date	2018
Language	Anglais
Journal information	"Papers in Regional Science" - Vol. 97, no. 4, p. 1151-1168 (2018)
Peer reviewed	yes
Publisher	Wiley-Blackwell Publishing, Inc. (Hoboken)
issn	1056-8190
e-issn	1435-5957
Publication status	Publié
Affiliations	UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles UCL - SSH/LIDAM/CORE - Center for operations research and econometrics
Keywords	Absolute and relative concentration ; absolute and relative specialization ; overall localization ; stochastic independence ; contingency tables
Links	http://hdl.handle.net/2078.1/187203[Handle] https://doi.org/10.1111/pirs.12294[DOI]

See also
	[boreal:111481]	A stochastic independence approach for different measures of concentration and specialization