Two-mode clustering through profiles of regions and sectors

Christian Haedo and Michel Mouchart
Additional contact information
Michel Mouchart : Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2022015, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: This paper is concerned with simultaneously regrouping regions and sectors when analyzing the relative sectorial specialization of regions and the relative regional concentration of sectors. An automatic two-mode clustering algorithm is proposed with a view toward a concept of overall localization, corresponding to a discrepancy between an actual two-way contingency table (regions × sectors) and an hypothetical table reflecting independence between regions and sectors. This procedure identifies similar regions (respectively sectors) according to the relative sectorial (respectively regional) structure. This algorithm significantly reduces the size of the original table and obtain an optimal collapsed table with low level of information loss vis-à-vis the degree of overall localization. The properties and results of the algorithm are discussed through two applications, namely Argentina and Brazil.

Keywords: Relative; sectorial; specialization; ·; Relative; regional; concentration; ·; Overall; localization; ·; Two-mode; clustering; ·; Biclustering; ·; Hierarchical; clustering; ·; Correspondence; analysis; ·; Large; two-way; contingency; tables; ·; Permutation; bootstrap (search for similar items in EconPapers)
Pages: 26
Date: 2021-03-10
Note: In: Empirical Economics, 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:aiz:louvar:2022015

DOI: 10.1007/s00181-022-02201-z

Access Statistics for this paper

More papers in LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA) Voie du Roman Pays 20, 1348 Louvain-la-Neuve (Belgium). Contact information at EDIRC.
Bibliographic data for series maintained by Nadja Peiffer ().