Slide 1 - Yorkshire _ Humber Assembly by forrests

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									Proposed Methodology for Determining a Housing Supply Range for each Region
Caroline Purdey National Housing & Planning Advice Unit
Caroline.purdey@nhpau.gsi.gov.uk Tel: 023 9295 8158

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In developing our proposed supply ranges we want to ….
• Consider accepted methodologies

• Draw on existing expertise
• Use a multi-faceted approach • Incorporate an affordability focus

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We will use three approaches ….

• Demographic • Economic Growth Predictions • Affordability Model
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Demographic Based Method

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Projected Growth in Households

+
Additional Demand for Second Homes

+
Existing Constrained Demand

+
Expected Vacancies in New Supply

=
Required Housing Supply
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Projected Growth in Households
• 04 based Household Projections
• Revised 04 based Household Projections • Scaled Household Projections based on 06 National Population Projections • Scaled Household Projections based on 06 National Population Projections High Migration Variant
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Projected Growth in Households in Yorkshire and Humber
40000 35000 30000 25000 20000 15000 10000 5000 0

2004/05

2005/06

2006/07

2007/08

2008/09

2009/10

2010/11

2011/12

2012/13

2013/14

2014/15

2015/16

2016/17

2017/18

2018/19

2019/20

2020/21

2021/22

2022/23

2023/24

2024/25

04 HH proj (unrev) 06 scaled higher mig (based on 04 unrev)

06 scaled (based on 04 unrev)

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2025/26

Impact of Migration • Look at trend in International Migration

• Look at trend in Internal Migration
• Consider Short-term Migrants

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Demand for Second Homes

• Historic data from:
– Survey of English Housing – Council Tax Data

• Modelled demand for holiday homes

(Reading Affordability Model)
– Dependent on predicted number of owneroccupiers (by age, sex, cohabitation status, dependent children) and income – Models number of owners not location
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Estimate using... • Trend-based assumption • Fixed assumption

• Proportion of stock
• Generalised version of Reading Model equation factored up cover all second homes
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Existing Constrained Demand • Overcrowded households • Concealed households

• Shared dwellings
• Homeless
• Temporary Accommodation

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Data Sources Survey of English Housing
– Overcrowded households – Concealed households – Shared dwellings

CLG homelessness statistics
– Homeless Acceptances – Temporary Accommodation

Avoids double-counting
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Issues

Issues

• Not all sharing families and concealed
households want to live separately; some prefer to live as part of an extended family • Use weights based on past survey data on the number of households that would prefer to have their own homes

• Identify groups of sharing ‘one-person’
households and consider separately

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Homelessness and Temporary Accommodation • Identify by type of accommodation
– Bed & breakfast/hotels – Hostels/Women's refuges – LA/RSL, or rented direct with private landlord – Homeless at home

and only include those not occupying an existing household space • Ignore Rough Sleepers?
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Other Constrained Demand Other Constrained Demand • Potential First-time buyers not occupying a household space e.g. living with parents • Other households that haven’t formed –based on change in average household size over time by age?
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Expected Vacancy Rate in New Supply

• Historic data from:
– Housing Strategy Statistical Appendix (HSSA) – Council Tax data

• Estimated Equilibrium Vacancy Rate
– from Reading Affordability Model work (but long-term vacancies as % of private stock)

• Government Target of 3% (June 1995)
• Regional Targets (from RSS)
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Incorporate using... • National or Regional Vacancy Targets • Average over last 3 (or 5) years • Trend based assumption • Estimated Total Equilibrium Vacancy Rate based on Reading Model work

Allow for change in vacancy rate in existing stock
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What else? • Buy-to-sit
– not thought to be significant

• Movement between private households and communal establishments
– can’t identify a data source

• Unfit homes
– don’t affect net additions
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Economic Growth Based Method

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This part has two components ….
• Using Economic Growth Based Models e.g. Experian • Considering the impact of greater prosperity (resulting from economic growth) on demand for housing from the existing population

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Experian modelling of Economic Growth, Demographics and Household Formation

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Experian modelling of Economic Growth, Demographics and Household Formation
• Most Regional Development Agencies have used the services of either Experian or Nathaniel Litchfield Partners to understand the impact of economic growth forecasts on population and household growth and therefore housing demand projections. • NHPAU hope to revise this work for all the regions using the Experian model populated with the most recent data available. • These estimates will draw on each regions own assumptions for economic growth.
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‘Top-down’ approach to forecasting
used in the Experian Model
International model

Industry model Employment model

UK macro model

Long-term supplyside view

Regional model

Long-term subnational supplyside view

County model

LAUA model
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Long-Term Modelling Approach

Starting Position
Industry Model
School Leaver Results

Employment Rate (workplace-based) Migration Population/ Households

Industrial Structure

Qualifications
Infrastructure (airports)

Productivity

GDP

Employment
Housing Supply Constraint

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Modelling population
ONS MYE by local authority National ONS MYE

Sub-national ONS projections

National GAD projections

RSS housing allocations (Eng)

Migration Population

Households

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Indicators that we also might consider are:
• Employment (or Unemployment) rates
• Household Gross Disposable Income (GDI) per head • Earnings (by place of residence)
etc.
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Affordability Model Based Method

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Using the Reading Affordability Model to answer the question:

How many additional houses are needed to stabilise affordability?

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What do we mean by stabilise?
a)ensure the affordability ratio in 2016 equals the 2007 level

b)ensure the affordability ratio in 2026 equals the 2007 level c)stop when the affordability ratio reaches a level and remains at that level

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Using what trajectory?

• Affordability is affected by both the timing and
level of house building

• For this work we use a very simple trajectory:
– maintaining current ‘net additions’ (based on 05/06 data) to 2008
– increasing ‘net additions’ by the same amount each year (i.e. straight line) to the target level – and maintaining this level to 2026/ 2031

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HH 240K(by 2016)
40,000 35,000 30,000
Housing Figures

25,000 20,000 15,000

10,000
5,000 0 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026

NE NW YH EM WM EE GL SE SW

Year

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Using what regional distribution? • The starting point will be the distribution of
household growth across the regions based on the revised 04 household projections

• We will then consider additional scenarios where
any further growth is distributed:
– across all the regions – in the least affordable regions (SE, SW, E) – in the London travel to work data (excluding London) – across the regions using policy based assumptions similar to those made by CLG
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We model two options:
• Changing the target level of net additions for a given year e.g. 240,000 in 2016

• Changing the total level of net additions over
a given time period e.g. total build for years 2008 to 2016 inclusive

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Finally, we will combine the results from the three approaches to get Housing Supply Ranges

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