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Using administrative data to improve the estimation of immigration to local areas in England

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  • Peter Boden
  • Phil Rees

Abstract

Summary. International migration is now a significant driver of population change across Europe but the methods that are available to estimate its true effect on subnational areas remain inconsistent, constrained by inadequate systems of measurement and data capture. In the absence of a population register for England, official statistics on immigration and emigration are derived from a combination of survey and census sources. The paper demonstrates how administrative data systems such as those which capture registrations of recent migrants with a local doctor, national insurance number registrations by workers from abroad and the registration of foreign students for higher education can provide data to understand patterns and trends in international migration better. The paper proposes a model for the estimation of immigration at a local level, integrating existing national estimates from the UK Office for National Statistics with data from these administrative sources. The model attempts to circumvent conceptual differences between data sets through the use of proportional distributions rather than absolute migrant counts in the estimation process. The model methodology and the results that it produces provide alternative estimates of immigration for consideration by the Office for National Statistics as it develops its own programme of improvement to subnational migration statistics.

Suggested Citation

  • Peter Boden & Phil Rees, 2010. "Using administrative data to improve the estimation of immigration to local areas in England," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(4), pages 707-731, October.
  • Handle: RePEc:bla:jorssa:v:173:y:2010:i:4:p:707-731
    DOI: 10.1111/j.1467-985X.2009.00637.x
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    Cited by:

    1. Kitty Lymperopoulou, 2013. "The Area Determinants of the Location Choices of New Immigrants in England," Environment and Planning A, , vol. 45(3), pages 575-592, March.
    2. Paolo Lucchino & Dr Chiara Rosazza Bondibene & Jonathan Portes, 2012. "Examining the relationship between immigration and unemployment using National Insurance Number registration data," National Institute of Economic and Social Research (NIESR) Discussion Papers 386, National Institute of Economic and Social Research.
    3. Thomas B. Foster & Mark J. Ellis & Lee Fiorio, 2018. "Foreign-born and native-born migration in the U.S.: evidence from linked IRS administrative and census survey records," Journal of Population Research, Springer, vol. 35(4), pages 467-498, December.
    4. Stephen Jivraj & Ludi Simpson & Naomi Marquis, 2012. "Local Distribution and Subsequent Mobility of Immigrants Measured from the School Census in England," Environment and Planning A, , vol. 44(2), pages 491-505, February.
    5. James Raymer & Xujing Bai & Nan Liu, 2020. "The dynamic complexity of Australia’s immigration and emigration flows from 1981 to 2016," Journal of Population Research, Springer, vol. 37(3), pages 213-242, September.
    6. Catherine Harris & Dominique Moran & John R. Bryson, 2015. "Polish Labour Migration to the UK: Data Discrepancies, Migrant Distributions, and Indicators of Entrepreneurial Activity," Growth and Change, Wiley Blackwell, vol. 46(2), pages 196-217, June.

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