Two-mode clustering through profiles of regions and sectors

Christian Haedo () and Michel Mouchart
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Christian Haedo: Fundación Observatorio PyME (FOP)
Michel Mouchart: Université catholique de Louvain

Empirical Economics, 2022, vol. 63, issue 4, No 11, 1996 pages

Abstract: 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 $$\times $$ × 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)
Date: 2022
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DOI: 10.1007/s00181-022-02201-z

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