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American Association of Geographers 2018

Nik Lomax
April 12, 2018

American Association of Geographers 2018

This is the presentation I gave at the AAG 2018 in New Orleans. It discusses ongoing work on high resolution demographic projections.

Nik Lomax

April 12, 2018
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  1. Nik Lomax
    Andrew P Smith
    AAG New Orleans
    Innovations in Urban Analytics, 12 April 2018
    High resolution demographic
    projections for infrastructure
    planning

    View Slide

  2. • The UK Infrastructure Transitions Research Consortium
    (ITRC) is a collaboration of seven universities and over
    50 partners from infrastructure policy and practice.
    • ITRC is helping governments, utility providers, designers,
    investors and insurers by developing new ways to
    evaluate the performance and impact of long-term plans
    and policy for infrastructure service provision in an
    uncertain future.
    • Supported by an EPSRC Programme Grant.

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  3. Demographics for demand
    models
    Demographic projections
    Demand
    modelling

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  4. Essential for planning the
    delivery of services and
    the allocation of resources
    to sub-national areas
    2014 sub-national population projections by ONS
    projections of diversity to 2061 from NewEthpop
    Or the assessment of population change
    for measuring demographic diversity and
    social equality
    Demographic projections

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  5. Demographic projections
    Projections are needed at high
    resolution for the MISTRAL project
    Crown copyright © 2017 Ordinance Survey
    2014 sub-national population projections by ONS
    But Spatial resolution is
    usually limited to larger
    administrative areas

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  6. Two projection approaches
    • Static sequential microsimulation constrained to
    official projections
    • Dynamic microsimulation which borrows strength
    from survey and census data as well as supply data
    from new build and housing stock information
    • The static model is delivering results, the dynamic
    model is work in progress

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  7. Data inputs
    • 2011 Census
    • Standard tables – near complete enumeration
    • Microdata – detailed attribute cross-tabulations
    • Survey data to add attributes/ calculate transition rates
    • British Household Panel Survey
    • Understanding Society
    • Ordinance Survey Mastermap & Address Point data
    • ONS population projection constraints
    • DCLG (1) household projections and (2) housing additions

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  8. Modelling approach

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  9. Population at
    MSOA scale
    Classified
    residential
    buildings
    Residential
    household size
    and type
    Demand models
    Model component integration
    Households
    at OA scale

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  10. Static sequential
    microsimulation
    Source: Lomax, N. and Smith, A P. (2017) Microsimulation for demography. Australian Population Studies, 1(1): 73-85

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  11. Dynamic microsimulation

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  12. Household Change
    Exeter
    Newcastle

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  13. Exeter
    Newcastle
    Population Change

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  14. Source: Pregnolato et al. (2018) A building stock and household
    composition model for the UK. GISRUK, Leicester, 17-20 April.
    Allocation to buildings
    • MasterMap and
    AddressPoint data are the
    input for a spatial
    allocation algorithm that
    classify the building stock
    in terms of residential
    type.
    • Spatial assignment by
    fitting buildings to
    households on the basis of
    the correlation of
    household size and
    number of rooms with
    building area footprint.
    • This allows all buildings
    footprints to be assigned a
    plausible set of household
    characteristics.

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  15. Input to demand models
    Source: Results from MISTRAL energy team, Oxford

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  16. Conclusion (1 of 2)
    • High resolution demographic projections are needed
    for effective modelling of demand across a range of
    sectors
    • Most projection models operate at aggregate scales
    • Microsimulation offers a useful tool to undertake
    modelling at fine spatial scale
    • And the potential to incorporate a range of variables

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  17. Conclusion (2 of 2)
    • Of the two microsimulation approaches:
    • Static sequential is easier to implement but misses
    much of the dynamic processes which go on as
    population changes
    • The fully dynamic model is potentially the best
    performing but very hard to implement. This is
    currently work in progress.

    View Slide

  18. Nik Lomax
    Andrew P Smith
    AAG New Orleans
    Innovations in Urban Analytics, 12 April 2018
    High resolution demographic
    projections for infrastructure
    planning

    View Slide