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https://hdl.handle.net/10620/17748
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DC Field | Value | Language |
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dc.contributor.author | Boulton, C | en |
dc.contributor.author | Fry, J | en |
dc.date.accessioned | 2019-04-13T03:37:53Z | en |
dc.date.accessioned | 2013-10-08T21:31:22Z | en |
dc.date.available | 2013-10-08T21:31:22Z | en |
dc.date.issued | 2013-08 | en |
dc.identifier.isbn | 978-1-74037-446-0 | en |
dc.identifier.uri | https://hdl.handle.net/10620/17748 | en |
dc.identifier.uri | http://hdl.handle.net/10620/3837 | en |
dc.description.abstract | This paper uses longitudinal information from the calendar in the Household, Income and Labour Dynamics in Australia (HILDA) Survey to track monthly education and labour market activities from 2000 to 2010 for about 6500 working age individuals. The techniques of optimal matching and cluster analysis (OMCA) are used to identify and group individuals with similar patterns of activities into ‘pathways’. Seventeen pathways are identified. Although each pathway contains some variation between the sequences of activities, distinct patterns can be observed. For youths aged 15–24 in 2001, five pathways are identified: three associated with increasing education levels and transitions to work; one associated with churning in and out of work; and one dominated by young women withdrawing from the labour force to raise children. Activity sequences for young adults aged 25–39 are grouped into four pathways: two involving work (one with increasing education); and two involving prolonged periods outside the labour force associated with raising children (with one pathway showing subsequent return to work). Mature adults aged 40–54 in 2001 follow one of four pathways: one dominated by work; two dominated by women spending time outside the labour force raising children (with one return to work pathway); and one pathway associated with early retirement. For seniors aged 55–64, four pathways are identified: one dominated by work; and three associated with retirement or transitions to retirement. The analysis in this paper can be a valuable input to identifying relationships between pathways and outcomes, and the individual characteristics that are associated with specific pathways. That analysis could then inform strategies to reduce the risk of unsuccessful labour market outcomes, such as prolonged unemployment. | en |
dc.publisher | Media and Publications - Productivity Commission | en |
dc.subject | Employment -- Parental leave | en |
dc.subject | Ageing -- Intentions | en |
dc.subject | Ageing -- Retirement | en |
dc.subject | Education and Training | en |
dc.subject | Employment -- Labour mobility | en |
dc.title | Prevalence of Transition Pathways in Australia | en |
dc.type | Reports and technical papers | en |
dc.identifier.url | http://www.pc.gov.au/__data/assets/pdf_file/0011/125885/transition-pathways.pdf | en |
dc.identifier.survey | HILDA | en |
dc.description.institution | Productivity Commission | en |
dc.title.report | Staff Working Paper | en |
dc.description.keywords | Optimal matching and cluster analysis | en |
dc.description.keywords | Education and labour market transitions | en |
dc.description.keywords | HILDA calendar | en |
dc.description.pages | 144 | en |
local.identifier.id | 4287 | en |
dc.publisher.city | Canberra | en |
dc.description.additionalinfo | To facilitate the analysis of calendar data in the Household, Income and Labour Dynamics in Australia (HILDA) survey and to demonstrate the operation of the optimal matching and cluster analysis (OMCA) techniques - the authors have provided examples of the Stata programs developed for this analysis. The programs are available at http://www.pc.gov.au/research/staff-working/transition-pathways/programs Users must be familiar with — and have access to — HILDA data (confidentialised Release 10 data were used for this paper) and the Stata statistical package (version 11 or later, with the SQ suite of commands downloaded from the Stata website). The Productivity Commission does not provide technical support, and does not accept liability for any errors that may be in these programs or for any inferences from the use of these programs. | en |
dc.subject.dss | Learning, education and training | en |
dc.subject.dss | Ageing | en |
dc.subject.dss | Labour market | en |
dc.subject.dssmaincategory | Ageing | en |
dc.subject.dssmaincategory | Employment | en |
dc.subject.dssmaincategory | Education and Training | en |
dc.subject.dsssubcategory | Labour mobility | en |
dc.subject.dsssubcategory | Retirement | en |
dc.subject.dsssubcategory | Parental leave | en |
dc.subject.dsssubcategory | Intentions | en |
dc.subject.flosse | Ageing | en |
dc.subject.flosse | Employment and unemployment | en |
dc.subject.flosse | Learning, education and training | en |
dc.relation.survey | HILDA | en |
dc.old.surveyvalue | HILDA | en |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.openairetype | Reports and technical papers | - |
item.fulltext | No Fulltext | - |
Appears in Collections: | Reports |
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