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Demographic change and population projections

Demographic change and population projections

These are the slides from a public lecture I gave for Geography Education Online. The video of my talk can be found here: https://geographyeducationonline.org/event/demographic-change-and-population-projections

Nik Lomax

March 22, 2022
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  1. Demographic change
    and population
    projections
    Dr Nik Lomax
    School of Geography, University of Leeds
    [email protected]

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  2. Why do we need demographic
    estimates and projections?
    • To understand and plan for demand on
    services and resources
    • To allow governments to formulate policy
    based on evidence
    • Demography is at the heart of all human
    systems
    • Planning, environment, inclusion, health

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  3. Source: https://population.un.org/wpp/
    2050
    9.96bn
    2020
    7.79bn
    1950
    2.54bn

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  4. Pressure from both
    growth and decline

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  5. Population
    growth
    The 47 least developed countries are
    amongst the world’s fastest growing
    populations
    Puts pressure on already strained resources
    However, where young populations are
    growing this provides an opportunity for
    rapid economic growth known as the
    demographic dividend

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  6. Sub-Saharan Africa: growth
    in working age population

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  7. Spain: an ageing (and declining)
    population

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  8. Potential Support
    Ratios
    • PSR is the number of working
    people for each person aged
    over 65
    • Provides a measure of the
    ‘burden’ placed on the working
    age population
    • Implications for health and social
    care as well as economic
    pressures
    0
    2
    4
    6
    8
    10
    12
    14
    1950 1970 1990 2000 2005 2010 2015 2020 2030 2050 2075 2100
    number working age to 65+
    Potential Support Ratio
    Sub-Saharan Africa Spain
    Source: Author’s calculations from https://population.un.org/wpp/

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  9. The demographic
    transition
    the transition from high to low
    death and birth rates
    Formal theory Notestein (1945)
    Source: https://www.buddinggeographers.com/demographic-
    transition-model-dtm/

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  10. Other theories of demographic transition
    Second demographic transition (van der Kaa 1987): fertility falls below
    replacement (due to the rise in contraception use and women in the
    workforce)
    Third demographic transition (Coleman 2006): when smaller birth
    cohorts reach the labour market, the demand for labour rises, and is
    filled by international migration
    Fourth demographic transition (Frey 2015): the spatial distribution of
    ethnic minorities (of immigrant origin) shifts from their initial places of
    settlement (mainly large cities) to other parts of the country

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  11. What are the
    demographic
    components
    of population
    change?
    Births
    Deaths
    International migration
    Internal migration (important for
    change at the sub-national level)

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  12. The contribution of
    the demographic
    components to
    population change
    fluctuate over time
    • Natural change = births minus
    deaths
    • Net migration = in migration
    minus out migration

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  13. Demographic
    components
    can change due
    to external and
    internal events
    Source: https://theconversation.com/whats-happened-to-uk-
    migration-since-the-eu-referendum-in-four-graphs-127891

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  14. Types of
    projection
    • results based on the input data you use
    • Can create scenarios where you alter
    the assumptions about the input data
    Deterministic
    • Based on running the model many
    times, sampling from a range of
    possibilities in the component dataset
    • Usually report the average and quantify
    the uncertainty that exists
    Probabilistic

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  15. Scenarios from
    a deterministic
    model
    • National Population
    Projection produced by ONS
    every two years
    • Latest projections are based
    on 2018 data
    • Driven by assumptions about
    the future trend of the
    demographic components
    • Uses a cohort component
    model (more later)

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  16. UK population in 2043 using different
    assumptions
    "high population" variant assumes
    high fertility, life expectancy and
    net migration
    4.3 million above principal projection
    "low population" variant assumes
    low fertility, life expectancy and net
    migration
    5.2 million below principal projection

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  17. Probabilistic
    projection
    for the UK
    • Median = 72.5 million
    • Upper 95% = 74.7 million
    • Lower 95% = 70 million
    • Produced by the United
    Nations using UK data
    Source: https://population.un.org/wpp/Graphs/Probabilistic/POP/TOT/826

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  18. Where do
    the UK data
    come from?
    Births are registered with the General Register Office
    and this is a legal requirement. Age of mother and
    sex of child is recorded
    Deaths are registered with the General Register
    Office and this is a legal requirement. Reported by
    age, sex and local authority of residence
    International migration data comes primarily from a
    survey at the border called the International
    Passenger Survey
    Internal migration data comes from re-registrations
    with a doctor reported in NHS data (and other
    adjustments, e.g. for university students)

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  19. How are
    these data
    used in
    projection
    Cohort component
    model
    Applies demographic
    rates to different
    population sub-groups

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  20. The cohort
    component
    projection
    model
    •Previous year data and census
    Resident population in base year
    •e.g. an 18 year old becomes 19
    Age on the resident population
    •Age specific fertility rate calculated from most recent five-year trend
    Add births
    •Age specific mortality rate calculated from most recent five-year trend
    •In migration assigned using a migration matrix
    Subtract deaths
    •Age specific out migration rate calculated from most recent two-year
    trend
    Add and subtract internal migrants
    •Age and sex international migration trend – most recent five-year
    average
    Add and subtract international migrants

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  21. How do we
    decide what
    assumptions
    to use in the
    model?
    Trends in past data
    Ask the experts
    Scenarios
    Incorporate uncertainty

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  22. UK trends in
    components

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  23. Source: ONS, https://bit.ly/3dMkEAD

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  24. Component rates vary by demographic group:
    fertility
    Source: ONS, https://bit.ly/3dw9NKW

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  25. Component rates vary by demographic group:
    mortality
    0.00
    0.10
    0.20
    0.30
    0.40
    0.50
    4 9 141924293439444954596469747984899499
    Probability of dying
    Age
    Age Specific Mortality
    Male Female
    Source: ONS, https://bit.ly/3dw9NKW
    Source: author calculations from ONS, https://bit.ly/2UdrW9o

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  26. Component rates
    vary by demographic
    group: migration
    • Wilson, T., 2010. Model
    migration schedules
    incorporating student
    migration peaks.
    Demographic research, 23,
    pp.191-222.
    • Rogers, A. and Castro, L.J.,
    1981. Model migration
    schedules.
    0.00
    50.00
    100.00
    150.00
    200.00
    250.00
    300.00
    0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
    Migrants per 1,000 population
    Internal migration rate (2020)
    Male Female
    Childhood
    Student
    Labour force
    Retirement Elderly
    Source: author calculations from ONS https://bit.ly/2UHFfPB

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  27. Substantial spatial variation in component
    rates
    0.0
    20.0
    40.0
    60.0
    80.0
    100.0
    120.0
    140.0
    160.0
    under 18 under 20 20-24 25-29 30-34 35-39 40-44 45 and over
    Births per 1,000 women
    Age Specific Fertility Rates (2019)
    Islington Camden Bradford Slough
    Source: https://www.ons.gov.uk/visualisations/dvc417/index.html

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  28. Other
    demographic
    variation
    “Almost universally, women with higher
    levels of education have fewer children.
    Better education is associated with lower
    mortality, better health, and different
    migration patterns”
    • Lutz and Samir (2011)
    It is well established that demographic
    rates vary substantially by ethnic group
    • Coleman (2010)
    Lutz, W. and Samir, K.C., 2011. Global human capital: Integrating education and population. Science, 333(6042),
    pp.587-592.
    Coleman, D. (2006). Immigration and ethnic change in low-fertility countries: A third demographic
    transition. Population and development Review, 401-446.

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  29. Demographic rates by ethnic group
    0
    20
    40
    60
    80
    100
    120
    140
    160
    <20 20-24 25-29 30-34 35-39 40+
    ASFR, 2001
    White Black-Caribbean Black-African Indian
    Pakistani Bangladeshi Chinese Other
    0
    20
    40
    60
    80
    100
    120
    140
    160
    180
    200
    0to4
    5to9
    10to14
    15to19
    20to24
    25to29
    30to34
    35to39
    40to44
    45to49
    50to54
    55to59
    60to64
    65to69
    70to74
    75+
    BAN
    BLA
    BLC
    CHI
    IND
    MIX
    OAS
    OBL
    OTH
    PAK
    WBI
    https://www.ethpop.org/

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  30. https://theconversation.com/what-the-uk-population-will-look-
    like-by-2061-under-hard-soft-or-no-brexit-scenarios-117475

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  31. Direct and
    indirect
    impact of
    migration
    assumptions
    • numbers of people who enter
    the country through immigration
    or leave through emigration
    Direct Impact
    • Cumulative over time with
    influence on fertility and
    mortality
    Indirect impact

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  32. Direct impact
    • Cumulative contribution of
    immigration and emigration
    to 2061
    • Baseline scenario results
    Immigration Emigration Net
    White British 6,338,023 7,822,886 -1,484,863
    Black Caribbean 177,491 301,973 -124,482
    Bangladeshi 266,143 232,433 33,709
    Other Black 164,182 116,796 47,386
    Mixed 802,122 435,129 366,993
    Pakistani 1,077,808 501,435 576,373
    Other 1,237,843 419,949 817,894
    Black African 1,368,427 417,984 950,444
    Other Asian 1,864,125 787,998 1,076,127
    Chinese 2,070,552 774,963 1,295,588
    Indian 2,345,361 756,360 1,589,001
    White Other 10,203,796 3,671,332 6,532,464
    Total 27,915,872 16,239,237 11,676,635

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  33. International
    migration
    assumptions
    under each
    scenario
    • Combination of models fit to
    previous migration data,
    continuation of trends and
    interpretation of policy
    Lomax, N., Wohland, P., Rees, P. and Norman, P., 2020. The impacts of
    international migration on the UK’s ethnic populations. Journal of
    Ethnic and Migration Studies, 46(1), pp.177-199.

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  34. Results under different scenarios

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  35. Results under different scenarios
    Group 1 – very reliant on international migration to grow

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  36. Results under different scenarios
    Group 2 – somewhat reliant on international migration to grow

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  37. Results under different scenarios
    Group 3 – continue to grow under all migration scenarios

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  38. Results under different scenarios
    Group 4 – decline under all migration scenarios

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  39. https://theconversation.com/what-the-uk-population-will-look-
    like-by-2061-under-hard-soft-or-no-brexit-scenarios-117475

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  40. https://theconversation.com/what-the-uk-population-will-look-
    like-by-2061-under-hard-soft-or-no-brexit-scenarios-117475

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  41. Short term
    shock – the
    effect of
    COVID-19
    (2020) mid-year population estimates year to June 2020 have
    just been released
    Provides a glimpse of the effects of COVID-19 on population
    change
    Deaths 13% higher than the previous year
    Internal migration down 11% on the previous year
    International migration very similar to previous year
    Number of births was lowest since 2003 (but continuation of
    trend)
    Lowest growth in two decades

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  42. Future shocks
    ENVIRONMENTAL
    PRESSURES
    CONFLICT &
    GLOBAL EVENTS
    ECONOMIC
    PERFORMANCE
    PANDEMICS

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  43. The Census
    as a
    benchmark
    Image by PaulSh on Flickr.

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  44. Small area
    demographic
    profiles
    • Demographic data used
    to understand all kinds of
    spatial phenomena
    • Composite indicators
    provide insight in to the
    make-up of areas
    • See
    https://maps.cdrc.ac.uk

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  45. What next?
    Take a look at the data,
    visualisations, methods and
    assumptions used in
    population projections
    • Global data from the
    United Nations
    • UK data from the ONS
    Think about (and challenge)
    the validity of model outputs
    • “All models are wrong, but
    some are useful” (George
    E. P. Box)

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  46. List of resources and references
    • UN World Population Prospects: https://population.un.org/wpp
    • Office for National Statistics National population projection data and method:
    https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/pop
    ulationprojections/bulletins/nationalpopulationprojections/2018based
    • Office for National Statistics subnational population projection data and methods:
    https://www.ons.gov.uk/releases/subnationalpopulationprojectionsforengland2018base
    d
    • CDRC maps: https://maps.cdrc.ac.uk
    • Van de Kaa, D. J. (1987). Europe's second demographic transition. Population bulletin, 42,
    1-59.
    • Coleman, D. (2006). Immigration and ethnic change in low-fertility countries: A third
    demographic transition. Population and development Review, 401-446.
    • Frey, W. H. (2015). Diversity explosion: How new racial demographics are remaking
    America. Brookings Institution Press.

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  47. Demographic change
    and population
    projections
    Dr Nik Lomax
    School of Geography, University of
    Leeds

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