POPGROUP - user group meeting- Dr Peter Boden analytics analytics edge edge John McCarthy POPGROUP User Group (Scotland) Ladywell House, Edinburgh January 2012 Slide 1
POPGROUP Presentation content - user group meeting- • Introduction • POPGROUP developments • User issues • Derived Forecast Module • Housing-led forecasts • Q & A Slide 2
POPGROUP Introduction - user group meeting- • Edge Analytics provides expertise in geographical modelling and research with a specialism in demographic forecasting and scenario planning • This expertise is based upon 20 years experience in the application of modelling methods to support investment, planning and policy development in the public and private sector, both in the UK and internationally • Edge Analytics is contracted by the Local Government Association (LGA) to support and develop POPGROUP ‐ a suite of demographic forecasting used by local planners across the UK Edge Analytics 2012 Slide 3
POPGROUP POPGROUP - Demographic Forecasting - user group meeting- Aberdeen City Aberdeen City Cornwall Cornwall Herefordshire Herefordshire North Ayrshire North Ayrshire Salford City Salford City The Vale of Glamorgan The Vale of Glamorgan Aberdeenshire Aberdeenshire Cumbria Cumbria Highland Highland North Yorkshire North Yorkshire Leeds University Leeds University Torfaen Torfaen Argyll & Bute Argyll & Bute Denbighshire Denbighshire Kent Kent Northamptonshire Northamptonshire Sheffield Sheffield U.S. Census Bureau U.S. Census Bureau Birmingham City Birmingham City Derbyshire Derbyshire Leeds City Leeds City Northern Ireland Statistics & Northern Ireland Statistics & Shropshire Shropshire University of Manchester University of Manchester Blackburn with Darwen Blackburn with Darwen Dorset Dorset Leicestershire Leicestershire Research Agency Research Agency South Lanarkshire South Lanarkshire University of Strathclyde University of Strathclyde Blaenau Gwent Blaenau Gwent Dudley Dudley Luton Luton Northumberland Northumberland Southern California Southern California University of West of University of West of Bournemouth Bournemouth East Sussex East Sussex Marja ‐ aho Arkkitechdit Oy Marja ‐ aho Arkkitechdit Oy One North East One North East Association of Governments Association of Governments England England Bradford Bradford Fife Fife Merseyside Information Merseyside Information Oxfordshire Oxfordshire South West Observatory South West Observatory Warwickshire Warwickshire Brighton & Hove Brighton & Hove Flintshire Flintshire Service Service Pembrokeshire Pembrokeshire Staffordshire Staffordshire West Northamptonshire JPU West Northamptonshire JPU Buckinghamshire Buckinghamshire General Register Office for General Register Office for Midlothian Midlothian Pima Association of Pima Association of Stirling Stirling West Sussex West Sussex Caerphilly Caerphilly Scotland Scotland Milton Keynes Milton Keynes Governments Governments Stoke on Trent Stoke on Trent Wiltshire Wiltshire Cardiff Cardiff Glasgow & Clyde Valley Glasgow & Clyde Valley Monmouthshire Monmouthshire Poole Poole Swindon Swindon Worcestershire Worcestershire Carmarthen Carmarthen Glasgow City Glasgow City Nathaniel Lichfield & Nathaniel Lichfield & Powys . Powys . Tameside Tameside Wrexham Wrexham Ceredigion Ceredigion Gloucestershire Gloucestershire Partners Partners Renfrewshire Renfrewshire Teeside Valley JSU Teeside Valley JSU Yorkshire & Humber Public Yorkshire & Humber Public Cheshire West & Chester Cheshire West & Chester Greater London Authority Greater London Authority National University of National University of Rochdale Rochdale Telford & Wrekin Telford & Wrekin Health Observatory Health Observatory City of Edinburgh City of Edinburgh Gwynedd Gwynedd Singapore Singapore Royal Borough of Windsor & Royal Borough of Windsor & The National Assembly for The National Assembly for Conwy Conwy Hampshire Hampshire Neath Port Talbot Neath Port Talbot Maidenhead Maidenhead Wales Wales Key demographic issues • Model development analytics analytics edge edge Population Growth • Configuration & calibration Smaller households Population ageing • Distribution Ethnic change • Technical support Edge Analytics 2012 Slide 4
POPGROUP - user group meeting- POPGROUP Developments Edge Analytics 2012 Slide 5
POPGROUP Developments - user group meeting- • Derived Forecast model • Data Modules – Household projections – Limiting long-term illness – Disability • Excel 2007 compatibility • Excel 2010 compatibility • Consultation on PopGroup version 4 developments Slide 6
POPGROUP - user group meeting- User issues Edge Analytics 2012 Slide 7
POPGROUP The planning context - user group meeting- • A decade of change (2001-2007) – Housing boom – High mobility – EU expansion – Rising fertility • A decade of change (2008-2012) – Financial crisis – Economic recession – Low mobility – Housing development decline Edge Analytics 2012 Slide 8
POPGROUP The planning context - user group meeting- • A new administration • Decentralisation - localism • Demographic uncertainty – Fertility rise peaked? – Significantly reduced mobility – Reduction in EU migration – Points Based System – impact? • ONS revisions to MYE, new SNPP – new Census data still 2 years away • RSS targets now redundant • Robust and local demographic statistics are key to renewed planning efforts Edge Analytics 2012 Slide 9
POPGROUP Example 1 – scenario development - user group meeting- Average per year 2 Change 2006 ‐ 2026 Scenario Households 1 Population Net Dwellings Jobs Migration Change % Change % Employment ‐ Scenario A 110,990 35% 56,534 43% 2,912 3,052 3,403 High SNPP (WAG 2008 ‐ based) 106,448 33% 55,193 42% 2,443 2,920 3,214 Employment ‐ Scenario B 93,458 29% 49,346 37% 2,061 2,617 2,688 Max CR 83,696 26% 45,242 34% 1,532 2,368 2,304 Population Growth Medium Migration ‐ led recalibrated 79,365 25% 43,484 33% 1,330 2,261 2,133 Employment ‐ Scenario C 73,974 23% 41,360 31% 1,112 2,133 1,893 SNPP (WAG 2006 ‐ based) 61,174 19% 36,081 28% 600 1,860 1,602 Low 5yr CR 57,939 18% 34,677 26% 314 1,728 1,275 10yr CR 56,006 18% 33,885 26% 222 1,680 1,198 Natural Change 46,814 15% 33,069 25% 0 1,631 561 15yr CR 49,484 15% 31,211 24% ‐ 88 1,518 938 1 Household totals for 2006 ‐ 2007 were supplied by Cardiff Council. Trend ‐ led 2 For consistency across all scenarios, the average per year is taken from 2009/10 ‐ 2025/26. Historical population statistics are Jobs ‐ led available to 2008/9 so no additional constraints are applied in these years. Trend scenarios begin in 2009/10 and dwelling and employment constraints apply from 2009/10. Dwelling ‐ led Slide 10
POPGROUP Example 2 – scenario development - user group meeting- 410,000 390,000 370,000 350,000 Population 330,000 310,000 290,000 270,000 250,000 SNPP Migration ‐ led ‐ R Net ‐ Nil Migration ‐ R Draft Review RSS ‐ R Approved RSS ‐ R AMR Dwelling Trajectory ‐ R Economic ‐ R Change 2010 ‐ 2033 Average per year Population Population Households Households Scenario Net Migration Dwellings Jobs Change Change % Change Change % SNPP 75,315 24.5% 41,502 32.0% 2,499 1,855 1,250 Migration ‐ led ‐ R 56,885 18.5% 37,730 29.9% 2,135 1,688 934 Economic ‐ R 54,150 17.6% 36,735 29.1% 2,035 1,642 803 Draft Review RSS ‐ R 25,630 8.3% 25,134 19.9% 937 1,120 262 Approved RSS ‐ R 25,515 8.3% 25,086 19.9% 933 1,118 261 Net ‐ Nil Migration ‐ R ‐ 2,384 ‐ 0.8% 8,976 7.1% 0 399 ‐ 581 AMR Dwelling Trajectory ‐ R ‐ 4,672 ‐ 1.5% 12,363 9.8% ‐ 301 550 ‐ 413 Slide 11
POPGROUP - user group meeting- Derived Forecast Module Edge Analytics 2012 Slide 12
POPGROUP Household Type - user group meeting- The GROS 2008-based household projections define 8 household types. The table below lists the full labels for each household type, which can be used within the Derived Forecast input and output files. Household Type 1.1 adult 2 + children 1.1 adult, 1 child 1.1 person female 1.1 person male 1.2 person all adult 1.2 + adult 1 + children 1. 3 + person all adult 1.Non ‐ heads Edge Analytics 2012 Slide 13
POPGROUP Derived Forecasts - method - user group meeting- Derived Category Rates Derived Category Rates Population Forecast Population Forecast Population forecast by age and sex Population forecast by age and sex Rates by age and sex Rates by age and sex (e.g. headship rates, disability rates) (e.g. headship rates, disability rates) Derived Category Forecast Derived Category Forecast Forecast for Derived Categories Forecast for Derived Categories (e.g. Households, disability) (e.g. Households, disability) D a,s,u,y,d,g = P a,s,u,y,g * R a,s,u,y,d,g / 100 a = age-group D =Derived Category Forecast s = sex u = Sub-population P =Population ‘at risk’ Forecast y = year d = derived category R =Derived Category Rates g = group (usually an area, but can be an ethnic group or social group) Edge Analytics 2012 Slide 14
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