Provincial Clustering in the Southern of Thailand: Concept and Empirical

Kiatkajon Chairat, Sumalee Santipollavut and Supachart Sukharomana

Applied Econometrics and International Development, 2015, vol. 15, issue 1, 161-172

Abstract: This paper presents the geographical cluster as provincial clustering in 14 provinces in the Southern part of Thailand. We formulate 24 indicators as variable base on three major concepts of cluster, which are Spatial, Functional and Micro-foundation concepts. Factor analysis show that these indicators can determine provincial clustering. Cluster analysis describes provincial clustering (group) trend from 2 groups up to 13 groups and can be categories into 5 cases from 3 to 7 groups. In each case, we can determine forms of group using the proximity criteria. Discrimination analysis help classified the most appropriate form in each case. Under the indicators of three concepts of cluster, 3 and 4 groups are appropriate form and indicate that provinces within group are closely located, making the provincial linkages and consistent with the definition and goal of the provincial clustering.

Keywords: Geographical cluster; Provincial clustering; Agglomeration effect. (search for similar items in EconPapers)
JEL-codes: N95 R12 R58 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.usc.es/economet/reviews/aeid15112.pdf
No.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eaa:aeinde:v:15:y:2015:i:1_12

Ordering information: This journal article can be ordered from
http://www.usc.es/economet/info.htm

Access Statistics for this article

More articles in Applied Econometrics and International Development from Euro-American Association of Economic Development
Bibliographic data for series maintained by M. Carmen Guisan ().