 Matching and clustering in square contingency tables. Who matches with whom in the Spanish labour marketPablo Álvarez de Toledo, Fernando Núñez and Carlos Usabiaga Computational Statistics & Data Analysis, 2018, vol. 127, issue C, 135-159 Abstract: The general framework of contingency tables is used to develop previous methodological contributions on labour matching data. A contingency table is generated by the combination of the multiple characteristics that define each row and column category (worker and job categories in our field). In this context, a dimension problem arises that has to be addressed. Two key concepts related to the labour matching process are defined: propensity to match and similarity in the matching. Both measures can be divided into partial components which allow a better understanding of the underlying structure of the data. On the basis of the methodological contribution proposed, an application to the Spanish labour market is conducted, which relies on a large database of administrative microdata (Continuous Working Life Sample, MCVL). A scenario in which each worker category and each job category is defined by the combination of two attributes (location and occupational level) is displayed. Keywords: Contingency tables; Propensity to match; Factor decomposition; Clustering; Labour matching data; Spanish labour market (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:127:y:2018:i:c:p:135-159 DOI: 10.1016/j.csda.2018.05.012 Access Statistics for this article Computational Statistics & Data Analysis is currently edited by S.P. Azen More articles in Computational Statistics & Data Analysis from Elsevier |
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