Fordham Research

Examples of key techniques for SHMAs

The Practice Guidance provides a context for methods used to generate the key outputs of PPS3. For example it allows calculation of the housing needs figures. As discussed in the SHMA Introduction, it does not provide all that is required for PPS3 purposes.

The following is a toolkit developed by Fordham Research for SHMA purposes:

1. Housing market gaps

In most parts of Britain, due to the rapid rise of house prices, wide gaps have developed between different tenures. The favourite image of a housing ladder has become out-dated: the gaps are far too big to be likened to the rungs of a ladder, where households go from social rent, to market rent and then to ownership. Even partial ownership (via shared equity for instance) is still far too expensive for households who are on the lower rungs to actually climb up to.

We have devised the following graphic to illustrate:

• Local prices across the market in £ per week
• Affordability gaps

The figures are based on:

1. Plotting the weekly cost of housing for each tenure group (on the vertical y-axis), against the notional numbers of households (illustrated only figuratively by the orange curve) along the horizontal x-axis
2. This is done for 2-bed dwellings only for illustrative purposes
3. The bars on the gap graphs show key tenure distinctions:
   • Newbuild to buy
   • Second-hand to buy
   • Private rental
   • Inferred mid-point of intermediate band
   • Social rent
4. Between each of the bars is a gap. The main two gaps of interest are:
   • The Rent/Buy gap: households in this gap can afford market rent without the need for Housing Benefit, but cannot afford to buy outright. Hence they are potentially candidates for partial equity forms of housing: shared ownership
   • The Intermediate gap: Intermediate housing is defined in PPS3 as housing at between a social rent and market rent. Although technically intermediate housing begins at £1 or so below market rent level, housing at such a weekly cost would clearly not be of much use to households in housing need. We put the mid-point on the graph and infer the weekly costs. This normally addresses the needs of rather less than half of those in intermediate housing need, but that is a difficult enough task, as it is difficult to produce newbuild housing at this level of weekly cost.
5. To enable comparisons, the capital cost of buying new and second hand housing is expressed as a weekly cost (by analogy like a mortgage payment). The technicalities of doing this are demonstrated in our reports.

This is a simple and elegant model that helps in grasping the impact of prices. Above all it aids understanding of the terms affordable housing, social housing and intermediate housing. It helps to distinguish between the role of products such as shared ownership and low cost home ownership.

2. Financial capacity

For analysing the movement of households between these gaps, it is necessary to be careful about the nature of the financial information used. Before the house prices rises, and expansion of home ownership in the past decade or two, it was possible to measure affordability by a price to income ratio. This can still be calculated, but it means very little in terms of analysing the future of a given housing market. The housing market is in large part driven by financial capacity: household income+savings+equity. This is termed 'financial capacity' and an example looks like this:

The following table provides median financial capacity figures by tenure. Median is used because it provides a 'typical' figure (the middle household in the range) and is not distorted by there being a few very wealthy households at the top end of the range, as the mean average can be.

Median financial information by tenure
Tenure	Median annual gross household income	Median savings	Median equity	Financial capacity
Owner-occupied (no mortgage)	£15,999	£16,359	£169,821	£234,176
Owner-occupied (with mortgage)	£33,090	£1,785	£77,189	£178,246
Social rented	£8,416	£339	£0	£25,588
Private rented	£17,778	£631	£0	£53,966
AVERAGE	£20,376	£2,375	£74,634	£138,137

The total financial capacity figure is based on a x3 multiple of income for mortgage. However as can be seen from the table, the general conclusion would be similar if x4 multiple were taken, and for lower income households it is unlikely that they would be much above a 3.5 multiple. With that note, the table shows some striking results:

1. For owners without mortgage (many of them retired) the proportion of equity and savings in overall financial capacity is about 80%. Even if a 3.5 multiple were used, the non-income element would still be about three quarters of the overall purchasing power of this group
2. For owners with mortgages the proportion of non-income elements of financial capacity falls to 44%, and would go down to nearer a third if the income multiple were raised to 3.5
3. In the case of both rented tenures, there is only a small savings figure (though this can be much higher in other areas) and of course no owned equity (though such households may be able to borrow or gain equity from other family members when considering a purchase). The financial capacity of such households varies considerably with tenure. The private rented households have about twice the financial capacity of the social renting ones. This is normal, as the private rented sector contains both households who are too poor to enter the market (and who depend on Housing Benefit to do so) and those who are aspiring towards buying, (and who have much higher incomes).
4. When compared with the price of entry level purchase housing, which in this case is be about £180 per week (for a second hand 2 bed dwelling), it is obvious that none of the renting households has any hope of climbing to full scale equity ownership. Even the private renters, on average, have only about a third of the necessary financial capacity, and this would not be materially altered by taking a higher mortgage multiple. Of course within the broad private renting group there will be households on much higher incomes who can consider purchase, with or without the assistance of the 'bank of Mum and Dad'.

The Table therefore presents the stark affordability issue: with the inclusion of financial capacity it can clearly be seen that those owner-occupiers without a mortgage could on average easily afford the £180 per week of an entry level purchase cost in the area. Those with mortgages (financial capacity £178k or more on a higher multiple) will in many cases have bought at lower prices than prevail today but in any case have about the necessary financial capacity to access at today's prices even on a x3 multiple. But both groups of renting households are nowhere near being able to afford to buy.

3. Housing market flows

Housing markets are typically thought of as areas within which some fraction, typically 70% of households, both move home and travel to work. Such a level of 'self-containment' is in practice very high. Most housing markets in Britain are not so self-contained: 50-60% is more normal.

Although self containment is considered an important factor it is difficult to apply to areas of high in-migration such as London. We have developed an approach using survey data to model the flows of households into and out of housing markets and sub-markets. This allows a picture to be developed of the nature of individual and grouped housing markets.

The first example below is drawn from our work in Manchester, and shows dramatically how the housing markets of the six submarkets used for this study differ: from the almost closed East Manchester to its extremely open neighbour, the City centre. That analysis was focussed effectively on phase of household within the life cycle (emerging, with children at home, and not with children at home).

The subsequent diagram is geared to the specific requirements of the middle statement in para 22 of PPS3 was taken from our work for Colchester.

These analyses, and the tabulations behind them, allow the middle requirement of PPS3 para 22 to be met in terms of the types of households likely to require market housing.

4. Balancing housing markets

The analysis required to produce the main PPS3 outputs involves modelling the whole housing market. This includes assessing the financial capacity of households, and also the dynamics of their flows, as in the topics just outlined.

The Balancing Housing Markets (BHM) model developed by Fordham Research is based partly on the technique of 'gross flows' developed by Christine Whitehead in the early 1990's. However that approach looked only at past trends. This did not seem adequate to model a market, which in practice never repeats the past (as the use of past trends would imply). Instead we have used the forecasts implied by households statements of what they 'would expect' to move to. This is distinct from what they might aspire to. The household questionnaire data upon which it is based asks what households planning to move would both like and would expect. The patterns are quite reasonable: households might aspire to own, but expect to privately rent, etc. An example is provided below:

Housing tenure aspirations and expectations
Tenure	Like	Expect
Buy own home	48.6%	29.6%
Council rented	14.7%	14.7%
RSL rented	5.2%	5.2%
Private rented	25.6%	46.7%
Tied	5.6%	1.7%
Shared ownership	0.0%	1.5%
House/flatshare in the private rented sector	0.3%	0.3%
TOTAL	100.0%	100.0%

The following box provides a subjective description of the fairly complex workings of the model. It concludes by showing, by size and tenure, the types of new housing which would best match the shortfalls in a given housing market.

Summary of the BHM process

The BHM process involves matching size, type and tenure of dwelling supply against both housing demand (i.e. housing that the household involved can afford) and housing need (in cases where the household cannot afford the size/location of housing that it requires). So far as possible expectations of future moves are used. The main area where this is not possible is net in-migration, since clearly future in-migrants are not surveyed. Hence in-migration is estimated from recorded recent in-migrants. The process of arriving at an allocation of sizes and tenures of housing, matching supply with demand, is complex. It typically involves upwards of 20 iterations. The combination of technical analysis and judgement involved is informed by the stakeholder comments gathered at the start of the SHMA, and by secondary data on the area. However the process cannot, if it is to be a reliable guide to that market, be based on a simple formula. The nature of the interactions between supply and demand across five sub-groups of tenures and four sizes of dwelling cannot be made into a mechanical analysis without losing practical relevance to the market(s) in question. The combination of quantitative and qualitative analysis in one calculation process is a novel one. It is prompted by the complexity of the task. As a result of its origin, the process cannot be made completely transparent (as can an arithmetic calculation) but enough cross-checking can be done to reassure a detached observer. In most cases the obvious cross-check for the affordable part of the calculation is the CLG Needs Mode. The market side of the calculation is more easily checked against stakeholder evidence.

The following table and chart show example results. They indicate the pattern of newbuild which would best meet both the housing market demand and the housing need of the area. They are not prescriptive as to sites, since each site will have its own local market and context for which a mix and design will be needed. They do provide, at district or sub-district level, a guide as to what forms of housing are most needed.

Balancing Housing Markets results (per annum)
Tenure	Size requirement				TOTAL
	1 bedroom	2 bedrooms	3 bedrooms	4+ bedrooms
Owner-occupation	-102	489	310	276	974
Private rented	261	-48	-178	-105	-70
Intermediate	73	83	38	0	193
Social rented	71	9	89	158	328
TOTAL	303	534	259	329	1,425

Information of this kind has been used to evaluate Regional Spatial Strategy (RSS) targets (in Trafford MBC for instance) where the demand greatly exceeded the then current RSS target. Since an expansion above the existing RSS target was permitted by the land supply and encouraged by the BHM, the Borough were encouraged to seek a much higher RSS target. This finding of course could be and has been reversed on other occasions. The RSS target is typically based on demography (household projections) and policy factors which may or may not be supported by the trends in the housing market.

NHPAU and Fordham Research

The National Housing and Planning Advice Unit was set up by CLG (the Government department which controls housing and planning policy) in mid 2007. Its role is to 'provide independent advice to national and regional government about the affordability of market housing'.

NHPAU has already published a report (Developing a target range of the supply of new homes across England: Oct 07) which brings together a range of evidence. It suggested that an annual total of 270,000 new homes per annum would control housing price rises more effectively than the 240,000 proposed by the Government.

The issue is not yet resolved, since the analytical base for such estimates is not yet fully established. Fordham Research has held discussions with NHPAU about carrying forward existing research to examine more closely the relationship between house prices and new housing supply.