Presentation on theme: "Scottish model of housing supply and affordability Chris Leishman, Department of Urban Studies, April 2008."— Presentation transcript:
Scottish model of housing supply and affordability Chris Leishman, Department of Urban Studies, April 2008
Project overview Project team drawn from: –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” 1- 2 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: –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 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 sub- national unit Constituent local authority areas Aberdeen City RegionAberdeen City and Aberdeenshire AyrshireEast Ayrshire, North Ayrshire, South Ayrshire Dundee City RegionDundee, Angus, Perth and Kinross Edinburgh City Region Edinburgh, Midlothian, West Lothian, East Lothian, Fife Glasgow City RegionGlasgow, North Lanarkshire, South Lanarkshire, East Renfrewshire, Renfrewshire, Inverclyde, East Dunbartonshire, West Dunbartonshire StirlingStirling, Falkirk, Clackmannanshire Highlands and IslandsArgyll & Bute, Highlands, Moray, Eilean Siar, Orkney, Shetland Borders, Dumfries & Galloway
Change of Approach/Perspective Adopting affordability targets (as an additional goal), fundamentally changes the nature of planning for housing. Many come to housing from a social perspective – meeting need (housing as a merit good). 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”?
An Alternative Approach Population (t-1) + (Births-Deaths) + International Migration Population of type (i) Inter- regional Migration Households of type (j) Prob (individual of type (i) forms household type (j) ) Number of owning households Number of private renters Number of social renters Prob (household of type (j) is in each of the 3 tenures) Demand for housing services by owners Supply of owner- occupier housing services House prices AFFORDABILITY Earnings Rents Vacancies, demolitions, second homes
Central Issues: Affordability Affordability cannot be stabilised by matching the number of housing units to be built to the expected growth in households. Typically this will lead to worsening affordability since this does not take into account increasing housing demand by existing households as their incomes rise. 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). (ii) This is why NHPAU finds that house prices might be 10 times incomes in 2026. 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 Demolitions Higher levels of construction designed to improve affordability may mean higher levels of vacancies and demolitions. 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. But higher construction gives the important opportunity to improve the overall quality of the housing stock.
Central Issues: Different Target Measures of Affordability This is difficult and there is no single “correct” measure. 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). Overall probably better to develop a range of indicators
Central Issues: Spatial Targets In England, regions are the unit of analysis large scale. At that level it is usually possible to design supply scenarios that improve affordability. 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.