Prevalence of Transition Pathways in Australia
Staff working paper
This paper by Jane Fry and Clare Boulton was released on 29 August 2013.
The analysis in this paper identifies broad patterns - or pathways - in labour market and education activities associated with different life stages. It uses a novel approach - optimal matching combined with cluster analysis - to analyse 10 years of calendar data from the Household, Income and Labour Dynamics in Australia (HILDA) survey.
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- Prevalence of Transition Pathways in Australia (PDF - 2790 Kb)
- Prevalence of Transition Pathways in Australia - by chapters (Word/ZIP - 2125 Kb)
- Key points
- 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'.
- Much of the wider literature considers transitions from one activity to another (such as study to employment, or employment to retirement). OMCA applied to calendar style data for other countries shows that there can be multiple transitions (such as reversals or repeated activities, like returning to the labour force or churning in and out of employment) and different pathways can arise with key life events (such as leaving education, family formation or retirement).
- 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.
- Successful and unsuccessful outcomes in the labour market can be related to the pathways that individuals follow. 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.
Patrick Jomini (Assistant Commissioner) 03 9653 2176
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 - we have provided examples of the Stata programs developed for this analysis.
You 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.
A Master Program links to 3 additional programs.
- The first additional program uses the calendar data to create a dataset that is suitable for OMCA.
- The second additional program performs optimal matching and produces a dendrogram which users must analyse before specifying a suitable number of pathways in the master program.
- The third additional program determines which pathway each observation belongs to. This program also:
- creates sequence index plots (showing the monthly activities of individuals) and analyses the concentration of unique sequences for each pathway
- creates datasets that can be used to draw chronographs (showing the percentage of individuals in each activity for each month) in Excel
- produces files that can be merged with data on individual characteristics for descriptive analysis based on other (annual) HILDA data.
Please note: HILDA data are not included with the programs. If you wish to access these data, you must apply to the Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA).
- Cover, Copyright and publication detail, Contents, Acknowledgments and Abbreviations
- Key points
- Chapter 1 Introduction
- 1.1 Transitions and outcomes in Australia - what has been studied?
- 1.2 Why pathways are important
- 1.3 Roadmap
- Chapter 2 Transitions as sequences
- 2.1 Research approaches to transitions
- 2.2 Study characteristics in the transition pathways literature
- 2.3 Key findings of the transition pathways literature
- Chapter 3 Pathways and estimates of prevalence
- 3.1 Pathway summary
- 3.2 Selected pathways
- Chapter 4 Future directions
- 4.1 Summary
- 4.2 Additional analysis
- 4.3 Further potential uses of OMCA in areas of policy interest
- Appendix A HILDA and the calendar data
- Appendix B Optimal matching and cluster analysis
- Appendix C Results