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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-

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POPGROUP

  • user group meeting-

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POPGROUP User Group (Scotland)

Ladywell House, Edinburgh

January 2012

edge

analytics

edge

analytics

Dr Peter Boden John McCarthy

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POPGROUP

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Presentation content

  • Introduction
  • POPGROUP developments
  • User issues
  • Derived Forecast Module
  • Housing-led forecasts
  • Q & A
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POPGROUP

  • user group meeting-

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Introduction

  • 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

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POPGROUP

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POPGROUP - Demographic Forecasting

Aberdeen City Aberdeenshire Argyll & Bute Birmingham City Blackburn with Darwen Blaenau Gwent Bournemouth Bradford Brighton & Hove Buckinghamshire Caerphilly Cardiff Carmarthen Ceredigion Cheshire West & Chester City of Edinburgh Conwy Cornwall Cumbria Denbighshire Derbyshire Dorset Dudley East Sussex Fife Flintshire General Register Office for Scotland Glasgow & Clyde Valley Glasgow City Gloucestershire Greater London Authority Gwynedd Hampshire Herefordshire Highland Kent Leeds City Leicestershire Luton Marja‐aho Arkkitechdit Oy Merseyside Information Service Midlothian Milton Keynes Monmouthshire Nathaniel Lichfield & Partners National University of Singapore Neath Port Talbot North Ayrshire North Yorkshire Northamptonshire Northern Ireland Statistics & Research Agency Northumberland One North East Oxfordshire Pembrokeshire Pima Association of Governments Poole Powys . Renfrewshire Rochdale Royal Borough of Windsor & Maidenhead Salford City Leeds University Sheffield Shropshire South Lanarkshire Southern California Association of Governments South West Observatory Staffordshire Stirling Stoke on Trent Swindon Tameside Teeside Valley JSU Telford & Wrekin The National Assembly for Wales The Vale of Glamorgan Torfaen U.S. Census Bureau University of Manchester University of Strathclyde University of West of England Warwickshire West Northamptonshire JPU West Sussex Wiltshire Worcestershire Wrexham Yorkshire & Humber Public Health Observatory Aberdeen City Aberdeenshire Argyll & Bute Birmingham City Blackburn with Darwen Blaenau Gwent Bournemouth Bradford Brighton & Hove Buckinghamshire Caerphilly Cardiff Carmarthen Ceredigion Cheshire West & Chester City of Edinburgh Conwy Cornwall Cumbria Denbighshire Derbyshire Dorset Dudley East Sussex Fife Flintshire General Register Office for Scotland Glasgow & Clyde Valley Glasgow City Gloucestershire Greater London Authority Gwynedd Hampshire Herefordshire Highland Kent Leeds City Leicestershire Luton Marja‐aho Arkkitechdit Oy Merseyside Information Service Midlothian Milton Keynes Monmouthshire Nathaniel Lichfield & Partners National University of Singapore Neath Port Talbot North Ayrshire North Yorkshire Northamptonshire Northern Ireland Statistics & Research Agency Northumberland One North East Oxfordshire Pembrokeshire Pima Association of Governments Poole Powys . Renfrewshire Rochdale Royal Borough of Windsor & Maidenhead Salford City Leeds University Sheffield Shropshire South Lanarkshire Southern California Association of Governments South West Observatory Staffordshire Stirling Stoke on Trent Swindon Tameside Teeside Valley JSU Telford & Wrekin The National Assembly for Wales The Vale of Glamorgan Torfaen U.S. Census Bureau University of Manchester University of Strathclyde University of West of England Warwickshire West Northamptonshire JPU West Sussex Wiltshire Worcestershire Wrexham Yorkshire & Humber Public Health Observatory

edge

analytics

edge

analytics

  • Model development
  • Configuration & calibration
  • Distribution
  • Technical support

Key demographic issues Population Growth Smaller households Population ageing Ethnic change

Edge Analytics 2012

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POPGROUP

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Edge Analytics 2012

POPGROUP Developments

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POPGROUP

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Developments

  • Derived Forecast model
  • Data Modules

– Household projections – Limiting long-term illness – Disability

  • Excel 2007 compatibility
  • Excel 2010 compatibility
  • Consultation on PopGroup version 4 developments
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POPGROUP

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Edge Analytics 2012

User issues

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POPGROUP

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Edge Analytics 2012

The planning context

  • 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

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POPGROUP

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Edge Analytics 2012

The planning context

  • 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

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POPGROUP

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Example 1 – scenario development

Change % Change % Employment ‐ Scenario A 110,990 35% 56,534 43% 2,912 3,052 3,403 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 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 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% 1,631 561 15yr CR 49,484 15% 31,211 24% ‐88 1,518 938 Trend‐led

1

Jobs‐led Dwelling‐led

2 For consistency across all scenarios, the average per year is taken from 2009/10 ‐ 2025/26. Historical population statistics are

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.

Population Growth Scenario Net Migration Dwellings Jobs Change 2006‐2026 Population Households1 Average per year2

Household totals for 2006‐2007 were supplied by Cardiff Council.

High Medium Low

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POPGROUP

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Example 2 – scenario development

250,000 270,000 290,000 310,000 330,000 350,000 370,000 390,000 410,000

Population

SNPP Migration‐led ‐ R Net‐Nil Migration‐ R Draft Review RSS ‐ R Approved RSS ‐ R AMR Dwelling Trajectory ‐ R Economic ‐ R

Average per year Scenario Population Change Population Change % Households Change Households Change % Net Migration Dwellings Jobs 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% 399 ‐581 AMR Dwelling Trajectory ‐ R ‐4,672 ‐1.5% 12,363 9.8% ‐301 550 ‐413 Change 2010 ‐ 2033

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Edge Analytics 2012

Derived Forecast Module

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Edge Analytics 2012

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

Household Type

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.

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Edge Analytics 2012

Derived Forecasts - method

D =Derived Category Forecast P =Population ‘at risk’ Forecast R =Derived Category Rates

Population Forecast

Population forecast by age and sex

Derived Category Rates

Rates by age and sex (e.g. headship rates, disability rates)

Derived Category Forecast

Forecast for Derived Categories (e.g. Households, disability)

Population Forecast

Population forecast by age and sex

Derived Category Rates

Rates by age and sex (e.g. headship rates, disability rates)

Derived Category Forecast

Forecast for Derived Categories (e.g. Households, disability)

a = age-group s = sex u = Sub-population y = year d = derived category g = group (usually an area, but can be an ethnic group or social group)

D a,s,u,y,d,g = P a,s,u,y,g * R a,s,u,y,d,g / 100

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Edge Analytics 2012

DF Model - structure

Make choices on model configuration Run Setup to create ‘skeleton ’ files

DFPop DFPopAdjust DFRates DFSubPop DFFactor DFScenario

Skeletons

DFScenario.xls DFScenario.xls

Population of skeleton files by user to create model ‘input’ files

DFPop DFPopAdjust DFSubPop DFRates DFCons

Inputs: Population Inputs: Rates Inputs: Constraints Configure Model scenario Run Model to produce output files

DFForecastDetail_ ID DFForecastTotal_ ID DFRatesOut_ ID DFRiskPop_ID

Outputs

DFCons DFFactor DFReporter_ ID

Start DFSetup Run Setup to create ‘skeleton ’ files

DFPop DFPopAdjust DFRates DFSubPop DFFactor DFScenario

Skeletons

DFScenario.xls DFScenario.xls

Population of skeleton files by user to create model ‘input’ files

DFPop DFPopAdjust DFSubPop DFRates DFCons

Inputs: Population Inputs: Rates Inputs: Constraints Configure Model scenario Run Model to produce output files

DFForecastDetail_ ID DFForecastTotal_ ID DFRatesOut_ ID DFRiskPop_ID

Outputs

DFCons DFFactor DFReporter_ ID

DFSetup

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Edge Analytics 2012

Housing-led forecasts Jobs-led forecasts

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Edge Analytics 2012

POPGROUP & policy scenarios Population Households Labour force

  • Not in households

x Headship rates x Activity rates

Revised migration

  • vs. Housing supply

Sharing,Vacancy rates, Second homes, Housing land

  • vs. Jobs supply

Unemployment, Commuting, Jobs creation

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Edge Analytics 2012

Questions & Answers

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Edge Analytics 2012

End