1. © University of Reading 2006www.reading.ac. ukSeptember 19, 2015 The CLG Housing Affordability Model: Recent Findings Geoffrey Meen

2. To put your footer here go to View > Header and Footer2 Developments over the last year (originally constructed as part of government’s response to Barker 1) (i) Tenure choice: Can we move towards higher levels of ownership? (ii) Modelling demolitions and vacancies: Do increased levels of construction mean higher demolitions? Do they imply increases in vacant homes? Do they mean concreting over the Greenbelt? Do they mean hastening urban decline? (iii) Adopting an additional “target” in terms of affordability fundamentally changes the nature of planning for housing.

3. To put your footer here go to View > Header and Footer3 Change of Approach/Perspective Many of us 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”? Therefore, the starting point is the market outcome.

4. To put your footer here go to View > Header and Footer4 The Traditional Approach to Planning for Housing Based on detailed population projections and household representative rates (HRRs) by age, gender, marital status. HRRs are trend based. Implicitly, they assume the historical trend for affordability continues. This is not the same as housing need. However, the aim of affordability targets is to change the historical trend and, therefore, a trend based approach is not appropriate. Official projections do not capture the effects of improving or worsening affordability on the rate of household formation. Improvements to affordability through extra construction generate extra households (although not proportionately). Worsening affordability (cf. NHPAU projections) implies household formation will be lower than official figures.

5. To put your footer here go to View > Header and Footer5 2004-based Household Projections Only 20,000 out of 150,000 annual increase in one person households are under age of 35.

6. To put your footer here go to View > Header and Footer6 Other Problems with the Traditional Approach (1) Revisions to Regional Spatial Strategies are slow. In recent years revisions to household projections are upwards, but changes to Spatial Strategies lag behind  increases market pressures. The approach deals only in numbers of units – a house is a house – and does not distinguish between the quality of the different units or the quantity of housing services each dwelling contains. But the price effects differ. This implies that matching the number of units to the number of households is not sufficient to stabilise affordability. Typically, the quantity of housing services must rise faster than households in order to take into account the increased demands of existing households.

7. To put your footer here go to View > Header and Footer7 Housing Supply under RPG and draft RSS Chasing a moving target?

8. To put your footer here go to View > Header and Footer8 Other Problems with the Traditional Approach (2) The accuracy is questionable. Although household revisions are upwards, 1996-based projections for the last 10 years over- estimated the outturn – related to worsening affordability?

9. To put your footer here go to View > Header and Footer9 Net Additions versus Gross New Completions RPGs are based on net additions, but the table below shows that net additions are a combination of new building, net conversions, net changes in use and demolitions. Hence an increase in net additions does not necessarily imply an increase in new construction (on Greenfields). One of the innovations of the new model is to determine conversions, change in use, demolitions with only gross completions as exogenous.

10. To put your footer here go to View > Header and Footer10 Matching “Units” The following must hold at all points in time. But it does not necessarily imply that the increase in dwellings has to match household growth under a market system. It has been argued that vacancies, second homes, demolitions are historically small and are “fixed”. But in a market system, vacancies and demolitions may be higher. All items below have to be modelled.

11. To put your footer here go to View > Header and Footer11 An Alternative Approach This models: (i) Household formation (ii) Tenure (iii) Interregional migration (iv) Demand for housing services (v) House prices (vi) Rents (vii) Vacancies, demolitions, second homes, conversions, changes in use. (conversions/changes in use are simple equations in the model and are not discussed here. Most of these change with variations in affordability. Therefore increases in net additions to the stock affect all the above.

12. To put your footer here go to View > Header and Footer12 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

13. To put your footer here go to View > Header and Footer13 The Demand for Housing Services The key factor is: (i) The income elasticity (responsiveness) of housing demand relative to the price elasticity (responsiveness) of demand. (ii) 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). (iii) In the model, the former is approx. 1.0 and the latter -0.5. (iv) This is why NHPAU finds that house prices might be 10 times incomes in 2026. Current housing plans do not rise faster than 2004- based household projections.

14. To put your footer here go to View > Header and Footer14 Household Formation & Affordability If, under current RSS, affordability is expected to worsen, then household formation is likely to be below official projections. Or, at least, a higher percentage of these households will require support in the social sector.

15. To put your footer here go to View > Header and Footer15 Ownership & Affordability (1) The percentage of households who are owners depend on (i) ownership housing costs, (ii) rents, (iii) ability to acquire the deposit, (iv) incomes. Broadly, household formation depends primarily on demographics, but tenure on economic factors. The model assumes that over the long run, rents rise in line with ownership costs. Otherwise there would be major (implausible) tenure shifts.

16. To put your footer here go to View > Header and Footer16 Ownership & Affordability (2)

17. To put your footer here go to View > Header and Footer17 Household Flows: Official & “Market” Projections (constant real housing costs)

18. To put your footer here go to View > Header and Footer18 Household Flows: Official & “Market” Projections (market clearing housing costs, rents rise with ownership costs)

19. To put your footer here go to View > Header and Footer19 Achieving 75% Ownership Even with “constant real costs”, ownership is hard to increase substantially by 2015. Key problem remains inability to meet deposit requirements as house prices rise. Meeting 75% depends heavily on London, where the rate is currently low. But price problems are greatest there. “worsening affordability case” assumes official household projections are met, but those who cannot be housed in the market sector are housed in the subsidised social sector. There is little change in the ownership share by 2015.

20. To put your footer here go to View > Header and Footer20 Why are housing demolitions so low? Diversity of property rights Land use controls and building regulations (limit filtering of the stock) Externalities – historical importance of buildings Housing shortages, which raise house prices and extend the average property life (obsolescence condition). Overall, if we have a system that is more market orientated, we might expect demolitions to move a little closer to the commercial property sector (although not completely) and the average property life to fall. But historical data and experience will be a poor guide to the future.

21. To put your footer here go to View > Header and Footer21 Which properties are most likely to be demolished? Properties do not depreciate linearly – hedonic analysis suggests the relationship is U-shaped. Surviving Victorian properties in many parts of the country are valued more highly than properties built in the post war period. This implies that if demolitions are to take place, they should be properties built between 1950 and 1970, not necessarily Victorian properties in urban areas. Decisions on demolitions need to look at the market.

22. To put your footer here go to View > Header and Footer22 Higher Vacancies in the Future? (i) Historically, vacancies may have been low because of shortages (opportunity cost of holding properties vacant is high). (ii) A well-functioning housing market will always require a certain level of vacancies (for search). Therefore, vacancies are not necessarily “bad”. (iii) We need to know what vacancies should be in equilibrium i.e. the rate towards which the housing system should converge.

23. To put your footer here go to View > Header and Footer23 Long-Term Vacancies: Influences (1) Model distinguishes between LT (greater than 6 months) and ST vacancies. The size of the housing stock The level of local deprivation The difference between the number of households and the housing stock Perhaps the novelty is the inclusion of the Index of Multiple Deprivation. The idea is that areas of high deprivation typically have higher vacancies (low demand areas) than LADs with low deprivation. The following table shows the equilibrium (LT) vacancy rates. Note that housing shortages (London?) would reduce the values in the table.

24. To put your footer here go to View > Header and Footer24 Long-Term Vacancies: Influences (2) LT vacancies are approximately 50% of all vacancies. Therefore, if ST vacancies have a similar equilibrium, we would expect total vacancies to be around 3%-4% of the private housing stock and the model as a whole should converge to these values.

25. To put your footer here go to View > Header and Footer25 Second (holiday) homes (1) For this part of the model, we are not interested in second homes, which are held for investment purposes and are let out as private rentals – they do not “remove” properties from the market. But holiday homes do and are modelled explicitly. We model the probability that a household, who already owns a first home will also own a holiday home. SEH data are used. The probabilities depend on income, age, gender, marital status and location of second home. According to model estimates, well over 90% of holiday homes are owned by the over 40s.

26. To put your footer here go to View > Header and Footer26 Second (holiday) homes (2) Unsurprisingly, ownership of holiday homes is quite sensitive to incomes. London households are most likely to have a holiday home. NE households are the least likely.

27. To put your footer here go to View > Header and Footer27 Model Properties: Increasing Housing Construction (1) In the model, the main policy instrument is now gross housing starts, rather than net additions to the stock. Demolitions, conversions etc. are determined within the model. Suppose we increase housing starts (relative to the base) by 100,000 units spread across the regions according to current RPG shares (and scaled for social housing). The increase is probably ridiculously high, but illustrates some points. A crucial finding arises: In previous versions of the model, a one unit increase in starts implicitly led to a one unit increase in net additions. This now depends on the level of vacancies. For regions where vacancies are below equilibrium, the relationship is closer to one-to- one than in regions where vacancies are in equilibrium. In the latter, demolitions are proportionately higher.

28. To put your footer here go to View > Header and Footer28 Model Properties: Increasing Housing Construction (2) The table shows the distribution of the increase in housing and vacancy rates in the Base. Note Vacancies are negative in London. This appears to be an implication of current plans. Also vacancies in most regions are below equilibrium.

29. To put your footer here go to View > Header and Footer29 Model Properties: Increasing Housing Construction (3) Tables concentrate on changes in affordability, net additions, vacancies, household formation in the market sector, and the private housing stock.

30. To put your footer here go to View > Header and Footer30 Model Properties: Increasing Housing Construction (4) Net additions are approximately half the increase in gross starts – the difference is mainly due to demolitions. But the increase is larger in London where vacancies were well below equilibrium in the Base. In the simulation, the vacancy rates are much closer to equilibrium. Affordability improves by 0.8 percentage points  similar to earlier versions, but are not comparable, because of changes in quality (not discussed here).

31. To put your footer here go to View > Header and Footer31 Model Properties: Increasing Housing Construction (5) The table shows the induced increase in market households arising from the increase in the private housing stock. As before it is only about a third with a bigger effect in London. Therefore, it is still the case that an increase in construction is not matched by household formation.

32. To put your footer here go to View > Header and Footer32 Conclusions (1) One of the big questions that arose in previous model versions was, “who will live in the extra homes?”: (i) It remains the case that only about a third are taken up in the market sector by new household formation. Existing households take up rest, moving upmarket as affordability improves. Implies that filtering occurs and demolitions if there are excess properties. (ii) But, for most regions, vacancies are likely to be below equilibrium on current housing projections (notably in London) if official household projections are to be achieved. Therefore, much of the increased construction (or rather filtered properties) restores vacancies to equilibrium. Unless additional construction is large, increases in demolitions are likely to be modest. (iii) If only market demand (rather than official household projections) is to be met, then demolitions could be noticeably larger, leading to improvements in the quality of the housing stock. (iv) But improving affordability requires the stock of housing services to rise faster than the number of households.

33. To put your footer here go to View > Header and Footer33 Conclusions (2) (v) The quantity of housing services rather than the number of units is the important concept for affordability. We have to take into account the increasing demand for housing services by existing households as incomes rise. (vi) Housing services can be increased by conversions, renovations, changes in use, demolitions as well as by new building. Therefore, it does not necessarily imply that affordability targets require more new building on Greenfield sites. This depends on where households wish to live (and needs sub-regional analysis). (vii) The results do not imply the destruction of urban centres through demolitions. If demolitions are to occur (and these are likely to continue to be small), they are more likely to be in areas dominated by properties built between 1950-1970.