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Scottish model of housing supply and
affordability
Chris Leishman, Department of Urban Studies, April 2008
Project overview
• Project team drawn from:
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University of Glasgow
University of Reading
Strathclyde University
Newhaven Research
• Extends development of an affordability and planning /
housing policy simulation to Scotland
• Project heavily focused on delivery of a useful simulation
model reflecting macro, demographic and policy
scenarios
• Very long term in scope (30 years, rather than “normal” 12 year economic model)
The housing market as an endogenous system
• Earlier studies saw house prices as determined in
isolation, i.e. a closed system
• House prices, construction, migration etc modelled as if
independent…
• Meen et al (2005) include modules for:
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household formation,
labour market,
housing activity,
tenure choice and,
migration
Modelling challenges
• More “realistic”, but much more complex
• Approaches emphasise endogeneity…
• For example, new-build supply should stabilise
prices…but some demand follows availability, so supply
may increase migration (will this increase prices?)
• Example 2: rising in-migration increases demand, and
should increase prices, and this should increase supply…
Modelling challenges (2)
• Macro-economic shocks may affect different parts of UK /
Scottish housing market at different rates and times (e.g.
interest rate changes or wealth effects)
• Non-linearities. For example, a rise in migration would
affect an overheated market differently to one with
“normal” market conditions.
Key outputs
• A simulation model (in Excel or similar)
– At Scotland level
– Based on changeable macro-economic and population scenarios
– Planning / land release / house building are the likely key policy
variables
– Model then predicts affordability over 30 years (defined as median
price to income, and LQ price to income)
Choice of geography
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England model is largely regional
Scottish model will be at national (Scotland) level…
…with an important sub-national element to the work
Arguably, the usefulness of policy tools increases below
regional level (but see later health warnings about this!)
• Chosen geography required to have:
– long run economic coherence
– a credible spatial scale for house prices, labour, migration
– data availability
The sub-national level
Proposed subnational unit
Constituent local authority areas
Aberdeen City Region
Aberdeen City and Aberdeenshire
Ayrshire
East Ayrshire, North Ayrshire, South Ayrshire
Dundee City Region
Dundee, Angus, Perth and Kinross
Edinburgh City
Region
Edinburgh, Midlothian, West Lothian, East
Lothian, Fife
Glasgow City Region
Glasgow, North Lanarkshire, South Lanarkshire,
East Renfrewshire, Renfrewshire,
Inverclyde, East Dunbartonshire, West
Dunbartonshire
Stirling
Stirling, Falkirk, Clackmannanshire
Highlands and Islands
Argyll & Bute, Highlands, Moray, Eilean Siar,
Orkney, Shetland
Borders, Dumfries &
Galloway
Borders, Dumfries & Galloway
Housing and
Affordability: 4
Lessons from England
Geoffrey Meen
March 29, 2016
© University of Reading 2006
www.reading.ac.
Change of Approach/Perspective
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Adopting affordability targets (as an additional goal),
fundamentally changes the nature of planning for housing.
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Many come to housing from a social perspective – meeting
need (housing as a merit good).
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Adding affordability changes the emphasis – housing is
dominated by the market and, given likely market
outcomes, we need to treat the externalities that arise, i.e.
the market will not guarantee decent homes for all. Extra
“target” but no extra “instrument”?
Population (t-1)
+ (Births-Deaths)
+ International
Migration
An Alternative Approach
Inter-regional
Migration
Prob (individual of type (i)
forms household type (j) )
Prob (household of type (j) is in
each of the 3 tenures)
Demand for housing
services by owners
Population
of type (i)
Households
of type (j)
Number of owning households
Number of private renters
Number of social renters
House prices
Rents
Supply of owneroccupier housing
services
Vacancies,
demolitions, second
homes
AFFORDABILITY
Earnings
Central Issues: Affordability
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Affordability cannot be stabilised by matching the number of housing units to be
built to the expected growth in households.
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Typically this will lead to worsening affordability since this does not take into
account increasing housing demand by existing households as their incomes rise.
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Formally this is the case if the income elasticity of housing demand is greater than
the price elasticity.
(i)
If the former is greater than the latter, then as incomes grow over time, affordability
will worsen unless the supply of housing services grow faster than the number of
households (or interest rates rise).
This is why NHPAU finds that house prices might be 10 times incomes in 2026.
(ii)
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As an aside, the credit crunch may improve affordability in the short run, but the
underlying problems do not disappear in the long run.
Central Issues: Vacancies and Demoliti
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Higher levels of construction designed to
improve affordability may mean higher levels of
vacancies and demolitions.
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This is because current levels are constrained by
supply shortages and high prices. This extends
the effective lives of existing properties and
increases the opportunity cost of holding
dwellings vacant.
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But higher construction gives the important
opportunity to improve the overall quality of the
housing stock.
Central Issues: Different Target Measur
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This is difficult and there is no single “correct”
measure.
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Price/income ratios suffer from problems:
(i)
The variable is non-stationary
(ii)
It doesn’t take account of interest rates
(iii) Border problems between regions
(iv) Low prices may reflect low quality of services in
an area (MIT study).
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Overall probably better to develop a range of
indicators
Central Issues: Spatial Targets
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In England, regions are the unit of analysis
large scale.
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At that level it is usually possible to design
supply scenarios that improve affordability.
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But at smaller spatial scales (possibly those in
Scotland?) the induced migration flows in
response to higher construction may make
targetting difficult if not impossible.