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Ethnic Population Projections: Review of Models and Findings Phil Rees School of Geography, University of Leeds Paper presented at the QMSS2 Seminar on.

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Presentation on theme: "Ethnic Population Projections: Review of Models and Findings Phil Rees School of Geography, University of Leeds Paper presented at the QMSS2 Seminar on."— Presentation transcript:

1 Ethnic Population Projections: Review of Models and Findings Phil Rees School of Geography, University of Leeds Paper presented at the QMSS2 Seminar on Multi- attribute analysis and projections of ethnic populations, Thorbjørnrud Hotel, Jevnaker, Norway Acknowledgements: ESRC Research Award RES-165-25-0032, colleagues Pia Wohland, Paul Norman and Peter Boden Paper available on: http://www.geog.leeds.ac.uk/research/projects/migrants.html http://www.geog.leeds.ac.uk/research/projects/migrants.html

2 Outline of the Paper INTRODUCTION: context, UK example, aim: to review the field of ethnic population projection, drawing mainly on UK experience INGREDIENTS: ethnic group definitions, UK experience, mixed ethnicity, ages, regions and migration, uncertainty POPULATION PROJECTION MODELS: from OPCS NCWP projections to JRF region projections via GLA, POPGROUP, Coleman & Scherbov, a new model design separating survivorship and migration INPUTS TO PROJECTION: Ethnic populations Ethnic mortality Estimation of immigration Estimating ethnic group internal migration CONCLUDING REMARKS

3 CONTEXT Third Demographic Transition Changing UK composition UK population increasing at slow rate, 0.64% in 2006-7 Variation across regions, highest in South around London 2001-6 2.7% increase in total population 0.4% decrease in White British population 23% increase in not White British population 2001: 87% White British, 13% not White British 2006: 84% White British, 16% not White British Highly variable across space: More ethnic minorities concentration in cities, in south Greatest growth in ethnic minorities outside core areas

4 Ethnic definitions: variation over space ENGLAND AND WALESSCOTLANDNORTHERN IRELAND All Ethnic Groups White: BritishWhite White: IrishIndianIrish Travellers White: Other WhitePakistani and other South AsiansMixed Mixed: White and Black CaribbeanChineseIndian Mixed: White and Black AfricanOthersPakistani Mixed: White and AsianBangladeshi Mixed: Other MixedOther Asians Asian or Asian British: IndianBlack Caribbean Asian or Asian British: PakistaniBlack African Asian or Asian British: BangladeshiOther Black Asian or Asian British: Other AsianChinese Black or Black British: Black CaribbeanOthers Black or Black British: Black African Black or Black British: Other Black Chinese or other ethnic group: Chinese Chinese or other ethnic group: Other Ethnic Group

5 1991 census ethnic categoryComponent 2001 census ethnic categories White White: British White: Irish White: Other 0.5*Mixed: White and Black Caribbean 0.5*Mixed: White and Black African 0.5*Mixed: White and Asian Black Caribbean Black or Black British: Caribbean 0.5*Mixed: White and Black Caribbean Black African Black or Black British: African 0.5*Mixed: White and Black African Black Other Black or Black British: Other Indian Asian or Asian British: Indian 0.5*Mixed: White and Asian*Proportion Indian Pakistani Asian or Asian British: Pakistani 0.5*Mixed: White and Asian*Proportion Pakistani Bangladeshi Asian or Asian British: Bangladeshi 0.5*Mixed: White and Asian*Proportion Bangladeshi Chinese Chinese or Other: Chinese Other Asian Asian or Asian British: Other Other Groups Chinese or Other: Other Mixed: Other T

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7 Recognizing mixed ethnicity Additional considerations Regions and migration

8 UK ethnic projection studies 1971 Census OPCS: NCWP, GB 1980s by OPCS 5 groups for E & W 1991 Census: London Boroughs by Marian Storkey, John Hollis and others for the GLC/GLA, and for Bradford by Ludi Simpson.

9 UK ethnic projection studies Then after the 2001 Census data again on ethnicity had been published we have a further set of local studies by Ludi Simpson and co-workers on local areas in North West England, Leicester and Birmigham. A projection using five ethnic groups was carried out by Phil Rees and John Parsons for GORS, Wales, Scotland and Northern Ireland in 2006, updated in 2009

10 UK ethnic estimate and projection studies Further GLA studies by Baljit Bains, Ed Klodawski and John Hollis National projection by Coleman and Scherbov including stochastic variants Ongoing: Phil Rees, Paul Norman, Peter Boden and Pia Wohland) Ongoing: Ludi Simpson & Nissa Finney Ongoing: James Raymer

11 New model design

12 Inputs to the projection Base populations Mortality Immigration Internal migration Emigration Fertility

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16 White British Asian or Asian British: Pakistani Chinese

17 RankEthnic group Mean e 0 Women RankEthnic group Mean e 0 Men 1Chinese82.11Chinese78.1 2Other Ethnic81.52Other White76.9 3Other White81.33Other Ethnic76.2 4White British80.54Black African76.1 All groups80.5All group76.0 5Black African80.45White British75.9 6White Irish80.36Indian75.5 7White-Asian80.07Other Asian75.2 8Other Mixed79.98White-Asian75.1 9Other Asian79.59White-Irish74.9 10White-Black African79.510Other Mixed74.6 11Indian79.311Black Caribbean74.4 12Black Caribbean79.112White-Black African74.2 13 White Black Caribbean78.713Other Black73.4 14Other Black78.514White-Black Caribbean73.4 15Bangladeshi77.715Pakistani73.1 16Pakistani77.316Bangladeshi72.7

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23 Concluding Remarks This paper has reviewed some recent work on ethnic population projection. We have reviewed the requirements of robust ethnic projections, which include proper understanding of the ethnic classifications available for use and the need to specify ages at single year resolution for projections with the greatest value. In choosing a suitable projection model for implementing the projection, it is necessary to understand fully the nature of the migration information available. A trade-off between the ease of computation of single region models and the complexity but greater theoretical rigour of multi-regional models must be arrived at. But the biggest challenge in many countries, including the UK in particular, is the lack of good data on the components of change. This requires innovative thinking about how proxy data and good statistical methods can be used to supply input variables to the projection.


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