Publication
Clustering techniques applied on cross-cectional unemployment data
| Summary: | Using a cross-section database that observes the Portuguese labour market in two different phases of the business cycle, the present paper aims to address the issue of the segmentation of the Portuguese labour market taking into account the heterogeneity resulting from different unemployment characteristics observed along the Portuguese geographical space and applying two optimization clustering methods: the k-means and the spectral methods. The k-means is a traditional optimisation clustering method applied to cluster data observations. Spectral clustering is an alternative method based on the computation of the dominant eigenvalue of a matrix related with the distance among data points. The results obtained by the two methods are not identical but are very close and show that, apart the economic phase of the cycle, Portugal presents two very different profiles of registered unemployment. One of them can be considered problematic because it presents a higher percentage of unemployed women, long duration unemployed and unemployed with low levels of formal education - these are the groups that present more difficulties in the labour market and for which is more difficult to find a job after losing one. The segmentation of the labour market is a reality and the labour market is not adjusting to the business cycle. |
|---|---|
| Main Authors: | Balsa, Carlos |
| Other Authors: | Nunes, Alcina; Barros, Elisa |
| Year: | 2013 |
| Country: | Portugal |
| Document type: | conference output |
| Access type: | open access |
| Associated institution: | Instituto Politécnico de Bragança |
| Language: | English |
| Origin: | Biblioteca Digital do IPB |
| _version_ | 1867172780442648576 |
|---|---|
| author | Balsa, Carlos |
| author2 | Nunes, Alcina Barros, Elisa |
| author2_role | author author |
| author_facet | Balsa, Carlos Nunes, Alcina Barros, Elisa |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Balsa, Carlos\",\"Person.identifier.orcid\":\"0000-0003-2431-8665\"},{\"Person.name\":\"Nunes, Alcina\",\"Person.identifier.orcid\":\"0000-0003-4056-9747\"},{\"Person.name\":\"Barros, Elisa\",\"Person.identifier.orcid\":\"0000-0001-8515-695X\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Balsa, Carlos Nunes, Alcina Barros, Elisa |
| datacite.date.Accepted.fl_str_mv | 2013-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2014-09-12T14:38:47Z |
| datacite.date.embargoed.fl_str_mv | 2014-09-12T14:38:47Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.titles.title.fl_str_mv | Clustering techniques applied on cross-cectional unemployment data |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Balsa, Carlos Nunes, Alcina Barros, Elisa |
| dc.date.Accepted.fl_str_mv | 2013-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2014-09-12T14:38:47Z |
| dc.date.embargoed.fl_str_mv | 2014-09-12T14:38:47Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/10419 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | International Center of Mathematics CIM - Portugal |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.title.fl_str_mv | Clustering techniques applied on cross-cectional unemployment data |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_c94f |
| description | Using a cross-section database that observes the Portuguese labour market in two different phases of the business cycle, the present paper aims to address the issue of the segmentation of the Portuguese labour market taking into account the heterogeneity resulting from different unemployment characteristics observed along the Portuguese geographical space and applying two optimization clustering methods: the k-means and the spectral methods. The k-means is a traditional optimisation clustering method applied to cluster data observations. Spectral clustering is an alternative method based on the computation of the dominant eigenvalue of a matrix related with the distance among data points. The results obtained by the two methods are not identical but are very close and show that, apart the economic phase of the cycle, Portugal presents two very different profiles of registered unemployment. One of them can be considered problematic because it presents a higher percentage of unemployed women, long duration unemployed and unemployed with low levels of formal education - these are the groups that present more difficulties in the labour market and for which is more difficult to find a job after losing one. The segmentation of the labour market is a reality and the labour market is not adjusting to the business cycle. |
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| person_str_mv | Balsa, Carlos Balsa, Carlos https://www.ciencia-id.pt/DE1E-2F7A-AAB1 DE1E-2F7A-AAB1 http://orcid.org/0000-0003-2431-8665 0000-0003-2431-8665 Nunes, Alcina Nunes, Alcina https://www.ciencia-id.pt/1111-680F-0CAF 1111-680F-0CAF http://orcid.org/0000-0003-4056-9747 0000-0003-4056-9747 Barros, Elisa Barros, Elisa http://orcid.org/0000-0001-8515-695X 0000-0001-8515-695X |
| publishDate | 2013 |
| publisher.none.fl_str_mv | International Center of Mathematics CIM - Portugal |
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| spelling | engInternational Center of Mathematics CIM - PortugalporUsing a cross-section database that observes the Portuguese labour market in two different phases of the business cycle, the present paper aims to address the issue of the segmentation of the Portuguese labour market taking into account the heterogeneity resulting from different unemployment characteristics observed along the Portuguese geographical space and applying two optimization clustering methods: the k-means and the spectral methods. The k-means is a traditional optimisation clustering method applied to cluster data observations. Spectral clustering is an alternative method based on the computation of the dominant eigenvalue of a matrix related with the distance among data points. The results obtained by the two methods are not identical but are very close and show that, apart the economic phase of the cycle, Portugal presents two very different profiles of registered unemployment. One of them can be considered problematic because it presents a higher percentage of unemployed women, long duration unemployed and unemployed with low levels of formal education - these are the groups that present more difficulties in the labour market and for which is more difficult to find a job after losing one. The segmentation of the labour market is a reality and the labour market is not adjusting to the business cycle.application/pdfporClustering techniques applied on cross-cectional unemployment dataPersonalBalsa, CarlosDSpacehttp://dspace.org/items/d0e5ccff-9696-4f4f-9567-8d698a6bf17dDSpacehttp://dspace.org/items/d0e5ccff-9696-4f4f-9567-8d698a6bf17dBalsaCarlosCiência IDhttps://www.ciencia-id.ptDE1E-2F7A-AAB1ORCIDhttp://orcid.org0000-0003-2431-8665Researcher IDhttps://www.researcherid.comM-8735-2013Scopus Author IDhttps://www.scopus.com23391719100PersonalNunes, AlcinaDSpacehttp://dspace.org/items/f96c3560-c1d3-432c-aa84-49982ea86106DSpacehttp://dspace.org/items/f96c3560-c1d3-432c-aa84-49982ea86106NunesAlcinaCiência IDhttps://www.ciencia-id.pt1111-680F-0CAFORCIDhttp://orcid.org0000-0003-4056-9747Researcher IDhttps://www.researcherid.comM-8259-2013Scopus Author IDhttps://www.scopus.com55907654000PersonalBarros, ElisaDSpacehttp://dspace.org/items/29601d32-5c12-4b5f-84ec-55d83617d04eDSpacehttp://dspace.org/items/29601d32-5c12-4b5f-84ec-55d83617d04eBarrosElisaORCIDhttp://orcid.org0000-0001-8515-695XHostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.pt2014-09-12T14:38:47Z20132013-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/10419http://purl.org/coar/access_right/c_abf2open access3431458 bytesother research producthttp://purl.org/coar/resource_type/c_c94fconference objecthttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/3ca92775-cfcd-4dce-a603-c944c674f291/downloadDGS II 2013 - International Conference and Advanced School Planet Earth - Dynamics, Games and Sciences II3333Lisboa |
| spellingShingle | Clustering techniques applied on cross-cectional unemployment data Balsa, Carlos |
| status | SINGLETON |
| title | Clustering techniques applied on cross-cectional unemployment data |
| title_full | Clustering techniques applied on cross-cectional unemployment data |
| title_fullStr | Clustering techniques applied on cross-cectional unemployment data |
| title_full_unstemmed | Clustering techniques applied on cross-cectional unemployment data |
| title_short | Clustering techniques applied on cross-cectional unemployment data |
| title_sort | Clustering techniques applied on cross-cectional unemployment data |
| url | http://hdl.handle.net/10198/10419 |
| visible | 1 |