Skip to main content
SpringerLink
Log in

The impact of education-bound mobility on inter-regional migration age profiles in Australia

  • Published:
Applied Spatial Analysis and Policy Aims and scope Submit manuscript

Abstract

Research on internal migration age profiles is important for understanding the dynamics of a country’s population geography, creating accurate population estimates in non-census years, and smoothing migration age profiles for sub-national population projections. In the international literature, internal migration age profiles are often characterised as relatively stable over time and space, and consisting of gradual changes in migration intensities from one age to the next – as depicted by the widely-used model migration schedule. However, a few migration age profiles in Australia are known to exhibit highly age-specific ‘spikes’ related to movement to higher education institutions. This paper undertakes an investigation of inter-regional migration age profiles in Australia to determine the extent of the phenomenon. Data from the Australian 2011 Census are used to create inter-regional migration probabilities by single years of age, together with more specific probabilities describing university-bound and boarding school-bound migration. Migration age patterns at three spatial scales of region are examined. It is shown that university-bound age-specific spikes are present in the majority of regional in- and out-migration age profiles in Australia at either age 18 or 19. In many cases this results in the peak migration probability occurring at these ages. Boarding school-bound migration is less significant and present in a smaller proportion of regional migration age profiles. In preparing smoothed migration age profiles for sub-national population projections it is imperative to smooth out noise but retain these significant education-bound migration spikes. Further work is required to determine the optimum ways of smoothing these migration age profiles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Australian Bureau of Statistics (ABS) (2010) Australian Statistical Geography Standard (ASGS): Volume 1 – Main Structure and Greater Capital City Statistical Areas, July 2011. Catalogue No. 1270.0.55.001. Canberra: ABS

  • Bell, M. (1995). Internal Migration in Australia 1986–1991: Overview Report. Canberra: Australian Government Publishing Service.

    Google Scholar 

  • Bell, M., Blake, M., Boyle, P., Duke-Williams, O., Rees, P., Stillwell, J., & Hugo, G. (2002). Cross-national comparison of internal migration: issues and measures. Journal of the Royal Statistical Society A, 165(3), 435–464.

    Article  Google Scholar 

  • Bernard, A., Bell, M., & Charles-Edwards, E. (2014). Life course transitions and the age profile of internal migration. Population and Development Review, 40(2), 213–239.

    Article  Google Scholar 

  • Blakers, R., Bill, A., Maclachlan, M., & Karmel, T. (2003). Mobility: Why Do University Students Move? Canberra: Department of Education, Science and Training.

    Google Scholar 

  • Chiang, C. L. (1991). Competing risks in mortality analysis. Annual Review of Public Health, 12, 281–307.

    Article  Google Scholar 

  • Congdon, P. (2008). Models for Migration Age Schedules: A Bayesian Perspective with an Application to Flows between Scotland and England. In J. Raymer & F. Willekens (Eds.), International Migration in Europe: Data, Models and Estimates (pp. 193–205). Chichester: John Wiley & Sons.

    Google Scholar 

  • De Beer, J. (2011). A new relational method for smoothing and projecting age specific fertility rates: TOPALS. Demographic Research, 24(18), 409–454.

    Article  Google Scholar 

  • De Beer, J. (2012). Smoothing and projecting age-specific probabilities of death by TOPALS. Demographic Research, 27(20), 543–592.

    Article  Google Scholar 

  • Department of Education, Training and Youth Affairs (DETYA) (2001) Higher Education Students Time Series Tables: Selected Higher Education Statistics. Canberra: DETYA. http://www.industry.gov.au/HigherEducation/HigherEducationStatistics/Pages/Library%20Card/Publications/2000TimeSeries.aspx accessed 22 June 2014

  • Department of Industry, Innovation, Science, Research and Tertiary Education (DIISRTE) (2012) 2011 Student Full Year. [Online statistical publication]. Canberra: DIISRTE. http://www.industry.gov.au/highereducation/HigherEducationStatistics/StatisticsPublications/Pages/2011StudentFullYear.aspx accessed 22 June 2014

  • Duke-Williams, O. (2009). The geographies of student migration in the UK. Environment and Planning A, 41(8), 1826–1848.

    Article  Google Scholar 

  • Flood, J., Maher, C., Newton, P., & Roy, J. (1991). The Determinants of Internal Migration in Australia. Melbourne: CSIRO.

    Google Scholar 

  • Guardian Australia (2014). ‘Budget: university students to pay more with removal of caps on fees’ Guardian Australia [online]. http://www.theguardian.com/world/2014/may/13/budget-university-students-to-pay-more-with-removal-of-caps-on-fees, accessed 13th May 2014

  • Liaw, K., & Nagnur, D. N. (1985). Characterization of metropolitan and nonmetropolitan outmigration schedules of the Canadian population system, 1971–1976. Canadian Studies in Population, 12(1), 81–102.

    Google Scholar 

  • Millington, J. (2000). Migration and age: The effect of age on sensitivity to migration stimuli. Regional Studies, 34(6), 521–533.

    Article  Google Scholar 

  • Mulder, C. H. (1993). Migration Dynamics: A Life Course Approach. Amsterdam: Thesis Publishers.

    Google Scholar 

  • Norton, A. (2013). Mapping Australian higher education. 2013 Version. Melbourne: Grattan Institute.

    Google Scholar 

  • Office for National Statistics (ONS). (2013). Analysis of internal migration research series, years ending June 2009 to June 2011. London: ONS.

    Google Scholar 

  • Openshaw, S. (1984). The Modifiable Area Unit Problem. Norwich: GeoBooks.

    Google Scholar 

  • Plane, D. A., & Heins, F. (2003). Age articulation of US inter-metropolitan migration flows. The Annals of Regional Science, 37(1), 107–130.

    Article  Google Scholar 

  • Rees, P. (1986). Choices in the construction of regional population projections. In R. Woods & P. Rees (Eds.), Population Structures and Models: Developments in Spatial Demography (pp. 126–159). London: Allen and Unwin.

    Google Scholar 

  • Rees, P. (1997). Problems and solutions in forecasting geographical populations. Journal of the Australian Population Association, 14(2), 145–166.

    Article  Google Scholar 

  • Rees, P., Bell, M., Duke-Williams, O., & Blake, M. (2000). Problems and solutions in the measurement of migration intensities: Britain and Australia compared. Population Studies, 54(2), 207–222.

    Article  Google Scholar 

  • Rogers, A., Little, J., & Raymer, J. (2010). The Indirect Estimation of Migration. Dordrecht: Springer.

    Book  Google Scholar 

  • Rogers, A. (1975). Introduction to Multiregional Mathematical Demography. New York: John Wiley.

    Google Scholar 

  • Rogers, A., & Castro, L. J. (1981). Model Migration Schedules. Research Report RR-81-30. Laxenburg: International Institute for Applied Systems Analysis.

    Google Scholar 

  • Rogers, A., Racquillet, R., & Castro, L. J. (1978). Model migration schedules and their applications. Environment and Planning A, 10(5), 475–502.

    Article  Google Scholar 

  • Rowland, D. T. (1979). Internal Migration in Australia. Canberra: ABS.

    Google Scholar 

  • Schofer, E., & Meyer, J. W. (2005). The worldwide expansion of higher education in the twentieth century. American Sociological Review, 70(6), 898–920.

    Article  Google Scholar 

  • Wilson, T. (2010). Model migration schedules incorporating student migration peaks. Demographic Research, 23(8), 191–222. www.demographic-research.org/.

    Article  Google Scholar 

  • Wilson, T. (2011). Modelling with NEWDSS: producing State, regional and local area population projections for New South Wales. In J. Stillwell & M. Clarke (Eds.), Population Dynamics and Projection Methods: Essays in Honour of Philip Rees (pp. 61–97). Dordrecht: Springer.

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Queensland Centre for Population Research, School of Geography, Planning and Environmental Management Chamberlain Building, The University of Queensland, Brisbane, Qld 4072, Australia

    Tom Wilson

Authors
  1. Tom Wilson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tom Wilson.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wilson, T. The impact of education-bound mobility on inter-regional migration age profiles in Australia. Appl. Spatial Analysis 8, 371–391 (2015). https://doi.org/10.1007/s12061-014-9124-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12061-014-9124-0

Keywords

Search

Navigation