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Understanding the transient population: insights from linked administrative data

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Abstract

There is growing evidence that frequent residential relocation is often associated with adverse socio-economic outcomes related to education, health and wellbeing. Prior research aimed at exploring the extent of residential movement has usually been restricted to survey evidence or infrequent census data. This study makes use of newly linked administrative data to design a framework for quantifying different levels and types of residential movement for an entire population. Within this context, we are able to derive working definitions for the transient and vulnerable transient. We also assess their interaction with a number of social service providers as well as important life events, both prior to and during the sample period. Our research contributes to understanding the key risk factors (in terms of both experience and intensity) associated with transience for adults, youth and children.

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Fig. 1

Source: Matched population between Census 2013 and address table in the IDI. Number of moves based on information from address table. Authors’ compilation (Numerical data for table is available upon author request)

Fig. 2

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Notes

  1. Changes in neighbourhood qualities and social characteristics, associated with residential movement, may also influence labour market activities and employment outcomes (Weinberg et al. 2004; Bayer et al. 2005; Oishi 2010). This highlights the complexity of this field of research where the same factors can be both determinants and outcomes (of frequent moves).

  2. While our study focuses only on individuals who move between residential locations, in some circumstances, transience has also been used to refer to homelessness (Polio 1997; German et al. 2007; Bender et al. 2010).

  3. Note this is not the case for homeless individuals.

  4. Territorial local authorities are geographic units defined under the Local Government Act—there are 67 of these units across NZ (Statistics NZ 2017). In our preliminary analysis we find that 93% of the sample population only moved within a region, and among them, 97% only moved within a territorial local authority over the three-year reference period.

  5. Data was collected on five occasions—when the child was 9 months, three, five, seven, and 11 years.

  6. Note that while there was usually a 5 year gap between Census waves, there was a 7 year gap between the 2006 and 2013 waves, due the impacts of the Christchurch earthquake in 2011.

  7. Comprehensive information about the IDI is available through the Statistics NZ website at http://archive.stats.govt.nz/browse_for_stats/snapshots-of-nz/integrated-data-infrastructure.aspx.

  8. The majority of health care in NZ is publicly funded through taxation. The Ministry of Health oversees this sector, while much of the day-to-day business, and around three quarters of the funding, is administered by district health boards (DHBs). This includes funding for primary care, hospital services, public health services, aged care services, and services provided by other non-government health providers. Primary health organisations ensure the provision of essential primary health care services, mostly through general practices and nurses, to people who are enrolled (i.e. registered) with the PHO.

  9. The National Health Index number is a unique identifier that is assigned to every person who uses health and disability support services in NZ.

  10. Note that because we do not know the composition of this potential group, it is difficult to speculate regarding the direction of impact on the quantification of transient and vulnerable transient persons.

  11. We also conducted the Census versus address table comparison based on the second question in Table 2. The match rate was 79% and 80% for movers and non-movers, respectively.

  12. This final exclusion was minor in nature and only related to 1461 individuals.

  13. This is in line with the classification used by Rumbold et al. (2012) and Hutchings et al. (2013), who show that children who are subjected to at least one residential move per year on average (based on the total number of moves they consider in a given period), are at a greater risk of suffering from mental health problems and poor academic outcomes.

  14. A meshblock is the smallest geographic unit used by Statistics NZ. The median size of this unit was 87 people (across 35 households) in 2006—see Meehan et al. (2018).

  15. Except for demographic characteristics, which are based on the start of the reference period—01 August 2013.

  16. We are unable to rescale these intensity variables for consistency due to the structure of the relevant datasets.

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Acknowledgements

We are grateful to several individuals and organisations for providing us with helpful comments. This includes the Social Policy Evaluation and Research Unit—Superu (Jason Timmins and John Wren); Victoria University of Wellington (Phillip Morrison) and Statistics NZ’s microdata team. We also thank Superu for sponsoring this research. Any errors or omissions remain the responsibility of the authors.

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Authors and Affiliations

  1. Faculty of Business, Economics and Law, School of Economics, Auckland University of Technology, Auckland, New Zealand

    Nan Jiang

  2. Faculty of Business, Economics and Law, NZ Work Research Institute, Auckland University of Technology, Auckland, New Zealand

    Gail Pacheco & Kabir Dasgupta

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  1. Nan Jiang
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Correspondence to Gail Pacheco.

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The results in this article are not official statistics, they have been created for research purposes from the Integrated Data Infrastructure (IDI), managed by Statistics NZ. The opinions, findings, recommendations, and conclusions expressed in this article are those of the author(s), not Statistics NZ. Access to the anonymised data used in this study was provided by Statistics NZ in accordance with security and confidentiality provisions of the Statistics Act 1975. Only people authorised by the Statistics Act 1975 are allowed to see data about a particular person, household, business, or organisation, and the results in this report have been confidentialised to protect these groups from identification. Careful consideration has been given to the privacy, security, and confidentiality issues associated with using administrative and survey data in the IDI. Further detail can be found in the Privacy impact assessment for the Integrated Data Infrastructure available from http://www.stats.govt.nz.

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Jiang, N., Pacheco, G. & Dasgupta, K. Understanding the transient population: insights from linked administrative data. J Pop Research 36, 111–136 (2019). https://doi.org/10.1007/s12546-019-09223-y

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