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Using linked consumer registers to estimate residential moves in the United Kingdom

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  • Justin T. van Dijk
  • Guy Lansley
  • Paul A. Longley

Abstract

This paper argues that frequently updated data on the nature of residential moves and the circumstances of movers in the United Kingdom are insufficient for many research purposes. Accordingly, we develop previous research reported in this Journal to re‐purpose consumer and administrative data in order to develop annual estimates of residential mobility between all UK neighbourhoods. We use a unique digital corpus of linked individual and household‐level consumer registers compiled by the UK Consumer Data Research Centre, comprising over 143 million unique address records pertaining to the entire UK adult population over the period 1997–2016. We describe how records pertaining to individuals vacating a property can be assigned to their most probable residential destination, based on novel methods of matching names, assessing household composition, and using information on the date and probable distance of residential moves. We believe that the results of this analysis contribute highly granular, frequently updated estimates of residential moves that can be used to chart population‐wide outcomes of residential mobility and migration behaviour, as well as the socio‐spatial characteristics of the sedentary population.

Suggested Citation

  • Justin T. van Dijk & Guy Lansley & Paul A. Longley, 2021. "Using linked consumer registers to estimate residential moves in the United Kingdom," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1452-1474, October.
    • Handle: RePEc:bla:jorssa:v:184:y:2021:i:4:p:1452-1474
    DOI: 10.1111/rssa.12713
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    References listed on IDEAS

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    1. Lansley, Guy & Longley, Paul, 2016. "Deriving age and gender from forenames for consumer analytics," Journal of Retailing and Consumer Services, Elsevier, vol. 30(C), pages 271-278.
    2. Everett Lee, 1966. "A theory of migration," Demography, Springer;Population Association of America (PAA), vol. 3(1), pages 47-57, March.
    3. M. Bell & M. Blake & P. Boyle & O. Duke‐Williams & P. Rees & J. Stillwell & G. Hugo, 2002. "Cross‐national comparison of internal migration: issues and measures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(3), pages 435-464, October.
    4. Travers, Tony & Tunstall, Rebecca & Whitehead, Christine M. E. & Pruvot, Segolene, 2007. "Population mobility and service provision: a report for London Councils," LSE Research Online Documents on Economics 42756, London School of Economics and Political Science, LSE Library.
    5. David J. Hand, 2018. "Statistical challenges of administrative and transaction data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 555-605, June.
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    Cited by:

    1. Jonathan Reades & Loretta Lees & Phil Hubbard & Guy Lansley, 2023. "Quantifying state-led gentrification in London: Using linked consumer and administrative records to trace displacement from council estates," Environment and Planning A, , vol. 55(4), pages 810-827, June.
    2. Tian Lan & Paul A. Longley, 2023. "An Individual Level Method for Improved Estimation of Ethnic Characteristics," International Regional Science Review, , vol. 46(3), pages 328-353, May.
    3. Paul A. Longley & Justin Dijk & Tian Lan, 2021. "The geography of intergenerational social mobility in Britain," Nature Communications, Nature, vol. 12(1), pages 1-8, December.

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