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Ethnic Population Projections: Review of Models and Findings
Phil Rees
School of Geography, University of LeedsPaper 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
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
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
Ethnic definitions: variation over spaceENGLAND AND WALES SCOTLAND NORTHERN IRELAND
All Ethnic Groups All Ethnic Groups All Ethnic Groups
White: British White White
White: Irish Indian Irish Travellers
White: Other White Pakistani and other South Asians Mixed
Mixed: White and Black Caribbean Chinese Indian
Mixed: White and Black African Others Pakistani
Mixed: White and Asian Bangladeshi
Mixed: Other Mixed Other Asians
Asian or Asian British: Indian Black Caribbean
Asian or Asian British: Pakistani Black African
Asian or Asian British: Bangladeshi Other Black
Asian or Asian British: Other Asian Chinese
Black or Black British: Black Caribbean Others
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
1991 census ethnic category Component 2001 census ethnic categoriesWhite White: British
White: IrishWhite: Other0.5*Mixed: White and Black Caribbean0.5*Mixed: White and Black African0.5*Mixed: White and Asian
Black Caribbean Black or Black British: Caribbean0.5*Mixed: White and Black Caribbean
Black African Black or Black British: African0.5*Mixed: White and Black African
Black Other Black or Black British: Other
Indian Asian or Asian British: Indian0.5*Mixed: White and Asian*Proportion Indian
Pakistani Asian or Asian British: Pakistani0.5*Mixed: White and Asian*Proportion Pakistani
Bangladeshi Asian or Asian British: Bangladeshi0.5*Mixed: White and Asian*Proportion Bangladeshi
Chinese Chinese or Other: Chinese
Other Asian Asian or Asian British: Other
Other Groups Chinese or Other: OtherMixed: Other
T
Recognizing mixed ethnicity
Additional considerations
Regions and migration
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.
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
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
Survival in
DESTINATIONS England and Wales ScotlandNorthern Ireland
Rest of world Deaths Totals
Existence in:
City of London and
Westminster … CardiffStart
Populations
ORIGINS Zone names Zones 1 … 374 375 376 R D
England and Wales
City of London and Westminster 1 SS 1,1
… MS 1,374 MS 1,375 MS 1,376 ES 1 D 1 SP 1
: : : … : : : : : :
Cardiff 374 MS 374,1… SS 374,374 MS 374,375 MS 374,376 ES N374 D 374 SP 374
Scotland 375 MS 375,1… MS 375,374 SS 375,375 MS 375,376 ES 375 D 1(3) SP 375
Northern Ireland 376 MS 376,1… MS 376,374 MS 376,375 SS 376,376 ES 376 D 375 SP 376
Rest of world Immigrants R IS 1… IS 374 IS 375 IS 376
0 0 IS *
Totals Populations * FP 1 FP 374 FP 375 FP 376 ES * D * T **
New model design
Inputs to the projection
Base populations
Mortality
Immigration
Internal migration
Emigration
Fertility
MORTALITY RATES
STANDARDISED MORTALITY RATIOS
POPULATION DATA
REGRESSION ANALYSIS
DEATHS DATA
2001 Vital statistics
Countries & Local Authorities
2001 Mid year Estimates
Countries & Local Authorities
SMR = f(SIR)
•All LAs in UK•LAs in E,W,S,N•‘Ethnic’ vs ‘Non-Ethnic’
2001 , UK Standard
Countries & Local Authorities
2001, UK Standard
Countries & Local Authorities
STANDARDISED MORTALITY RATIOS BY ETHNICITY
2001, UK Standard
Countries & Local Authorities
LIFE TABLES & SURVIVORSHIP PROBABILITIES BY ETHNICITY
2001 (Calendar Year)
Countries & Local Authorities
RESIDENTS DATA
2001 Census Tables S16,S65
Countries & Local Authorities
LIMITING LONG TERM ILLNESS DATA
2001 Census Tables S16,S65
Countries & Local Authorities
STANDARDISED ILLNESS RATIOS
2001 , UK Standard
Countries & Local Authorities
STANDARDISED ILLNESS RATIOS BY ETHNICITY
2001, UK Standard
Countries & Local Authorities
RESIDENTS DATA BY ETHNICITY
2001 Census Tables ST 101, 107, 207, 318
Countries & Local Authorities
LIMITING LONG TERM ILLNESS BY ETHNICITY
2001 Census Tables ST 101, 107, 207, 318
Countries & Local Authorities
Females SIRs1801601401201008060
Fem
ales
SM
Rs
180
160
140
120
100
80
60
Fit line for TotalNSWENSWE
Males SIRs1801601401201008060
Male
s S
MR
s
180
160
140
120
100
80
60
Fit line for TotalNorthern IrlandScotlandWalesEnglandNorthern IrlandScotlandWalesEngland
Female SIR175.00150.00125.00100.0075.0050.00
Fem
ale
SM
R
150.00
125.00
100.00
75.00
50.00
Fit line for TotalEthnic minorty <= 8.2%Ethnic minorty > 8.2%Fit line for TotalEthnic minorty <= 8.2%Ethnic minorty > 8.2%
ETH_Min
R Sq Linear = 0.484
Male SIR175.00150.00125.00100.0075.0050.00
Ma
le S
MR
150.00
125.00
100.00
75.00
50.00
Fit line for TotalFit line for TotalEthnic minority <= 8.2%Ethinc minorty > 8.2%Ethnic minority <= 8.2%Ethinc minorty > 8.2%
ETH_Min
R Sq Linear = 0.583
0 50 150 250
050
100
150 White British
Num
ber
of L
As
0 50 150 250
050
100
150
97 (m)96 (f)
0 50 150 250
050
100
150 White Irish
0 50 150 250
050
100
150
109 (m)100 (f)
0 50 150 250
050
100
150 Other White
0 50 150 250
050
100
150
79 (m)83 (f)
0 50 150 250
050
100
150 White & Black Caribbean
0 50 150 250
050
100
150
135 (m)133 (f)
0 50 150 250
050
100
150 White & Black African
Num
ber
of L
As
0 50 150 250
050
100
150
121 (m)117 (f)
0 50 150 250
050
100
150 White & Asian
0 50 150 250
050
100
150
108 (m)107 (f)
0 50 150 250
050
100
150 Other Mixed
0 50 150 250
050
100
150
115 (m)110 (f)
0 50 150 250
050
100
150 Indian
0 50 150 250
050
100
150
99 (m)122 (f)
0 50 150 250
050
100
150 Pakistani
Num
ber
of L
As
0 50 150 250
050
100
150
133 (m)159 (f)
0 50 150 250
050
100
150 Bangladeshi
0 50 150 250
050
100
150
138 (m)152 (f)
0 50 150 250
050
100
150 Other Asian
0 50 150 250
050
100
150
105 (m)119 (f)
0 50 150 250
050
100
150 Black Caribbean
0 50 150 250
050
100
150
110 (m)122 (f)
0 50 150 250
050
100
150 Black African
SIR
Num
ber
of L
As
0 50 150 250
050
100
150
83 (m)98 (f)
0 50 150 250
050
100
150 Other Black
SIR
0 50 150 250
050
100
150
129 (m)135 (f)
0 50 150 250
050
100
150 Chinese
SIR
0 50 150 250
050
100
150
60 (m)67 (f)
0 50 150 250
050
100
150 Other Ethnic Group
SIR
0 50 150 250
050
100
150
87 (m)80 (f)
White British
Asian or Asian British: Pakistani
Chinese
Rank Ethnic groupMean e0
WomenRank Ethnic group
Mean e0
Men
1 Chinese 82.1 1 Chinese 78.12 Other Ethnic 81.5 2 Other White 76.93 Other White 81.3 3 Other Ethnic 76.24 White British 80.5 4 Black African 76.1
All groups 80.5 All group 76.0 5 Black African 80.4 5 White British 75.96 White Irish 80.3 6 Indian 75.57 White-Asian 80.0 7 Other Asian 75.28 Other Mixed 79.9 8 White-Asian 75.19 Other Asian 79.5 9 White-Irish 74.910 White-Black African 79.5 10 Other Mixed 74.611 Indian 79.3 11 Black Caribbean 74.412 Black Caribbean 79.1 12 White-Black African 74.2
13White Black Caribbean 78.7 13 Other Black 73.4
14 Other Black 78.5 14 White-Black Caribbean 73.415 Bangladeshi 77.7 15 Pakistani 73.116 Pakistani 77.3 16 Bangladeshi 72.7
1995 2000 2005
75
80
85
Townsend deprivation quintiles
Life
exp
ect
an
cy a
t bir
th, U
K
T 1 (least deprived)T 2T 3T 4T 5 (most deprived)
1995 2000 2005
72
74
76
78
80
82
Life
exp
ect
an
cy a
t bir
th, m
en
, UK
Industrial Legacy Established Urban Centres Young & Vibrant CitiesRural Britain Coastal Britain Averageville
Prosperous Urbanites Commuter Belt Multicultural Outer London Mercantile Inner London Cosmopolitan Inner London Northern Irish Heartlands
1995 2000 2005
78
80
82
84
86
88
Life
exp
ect
an
cy a
t bir
th, w
om
en
, UK
Industrial Legacy Established Urban Centres Young & Vibrant CitiesRural Britain Coastal Britain Averageville
Prosperous Urbanites Commuter Belt Multicultural Outer London Mercantile Inner London Cosmopolitan Inner London Northern Irish Heartlands
Concluding RemarksThis 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.
