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Sheffield Strategic Housing Market Assessment November 2013 Annex Report 2: Technical Annex

https://www.sheffield.gov.uk/

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Contents

Contents ............................................................................................................ i

1 Introduction ............................................................................................ 1

1.1 Structure of this annex ............................................................................................. 1

2 Survey deployment and response ............................................................ 1

2.1 Introduction ............................................................................................................... 1 2.2 Sample frame ............................................................................................................. 1 2.3 Sampling ..................................................................................................................... 1 2.4 Survey deployment .................................................................................................... 4

2.4.1 Wave A 4 2.4.2 Wave B 4 2.4.3 Wave C 5 2.4.4 Wave D 5 2.4.5 Response rate 6

2.5 Sample Error .............................................................................................................. 6 2.6 Weighting and Grossing ........................................................................................... 6

3 Estimate of housing need ....................................................................... 9

3.1 Estimate of the backlog of housing need ............................................................ 10

3.1.1 Households in unsuitable housing 10 3.1.2 Sub Total: All households in unsuitable housing and need to move 11 3.1.3 Percentage unable to afford to move 13 3.1.4 Homeless households 14 3.1.5 Annual total backlog of existing housing need 15

3.2 Estimate of newly arising housing need ............................................................... 16

3.2.1 New household formation 16 3.2.2 Percentage unable to buy or rent in the market 18 3.2.3 Existing households falling into priority need 19

3.3 Estimate of the supply of affordable housing ..................................................... 20

3.3.1 Supply of social relets 20 3.3.2 Supply of Shared Ownership re-sales 22 3.3.3 Units taken out of supply of affordable housing 22 3.3.4 Committed units of new affordable supply 23

3.4 Overall annual shortfall calculation ...................................................................... 23

References ...................................................................................................... 24

Sheffield SHMA Annex Report 2: Technical Annex

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1 Introduction

This technical annex is intended to act as a reference document for the Sheffield Housing Survey – a major household survey – and the Housing Needs Model produced by the partnership for Sheffield’s 2013 Strategic Housing Market Assessment (SHMA). The results of the survey are presented throughout the SHMA main report and are used to inform the Housing Needs Model. The main outputs of the Housing Needs Model are summarised in Chapter 6 of the SHMA main report.

A multi-method approach was used to provide a robust assessment, in line with Strategic Housing Market Assessments Practice Guidance.1 The study employs a blend of secondary data, primary survey data, and qualitative insights. Secondary data sources, such as those drawn from the Census and other official data sources, are used where appropriate – as encouraged in the practice guidance – although in many places this is augmented with analysis of the 2013 Sheffield Housing Survey. Appendix 1 of the main report provides a copy of the print questionnaire for this survey. A separate annex to the main report, Annex Report 1: Home Truths II, contains an analysis of a programme of qualitative work, which is used to highlight Sheffield resident’s perceptions of housing need, the housing market, quality of housing and neighbourhoods. The findings of Home Truths II triangulates the evidence from the housing survey and confirms the robustness of key quantitative findings from the survey.

1.1 STRUCTURE OF THIS ANNEX

This annex is structured into two main chapters (not including this introduction).

Chapter 2 provides technical details of the design and deployment of the Sheffield Housing Survey, including details of the sampling and weighting techniques used.

Chapter 3 provides further technical information on the derivation of key inputs to the housing needs model presented in the main SHMA report (Chapter 6).

1 DCLG (2007).

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2 Survey deployment and response

2.1 INTRODUCTION

This section of the Annex provides key details of the selection of the sample for the survey, the deployment of the survey instrument (postal and online questionnaires), and the response rates to several waves of the survey.

A copy of the questionnaire is provided in the main report (Appendix 1).

2.2 SAMPLE FRAME

The sample frame for the Sheffield Housing Survey was all households within the city of Sheffield, excluding those living in the Peak District National Park (although note that we have defined a Peak District housing market area [HMA] comprising neighbourhoods that are outside the park’s legal boundary but within Sheffield. See Chapter 2 of the main report for further details.)

The sample frame was drawn from an extract of the Council Tax database drawn on 31 January 2013. The extract included properties for which there was an exemption (e.g. student properties) but excluded those properties registered as empty. The full file contained 233,991 records.

These were geocoded against the August 2012 version of the Office for National Statistics Postcode Directory (ONSPD) using the full postcode from the Council Tax data. 233,956 records (99.985%) were successfully matched and assigned a map location to the nearest 100m. Of the 35 records not matched the majority were clearly erroneous, relating to deleted properties that had not been removed from the database and which had null postcodes.

The geocoded records were then assigned one of Sheffield City Council’s 100 defined neighbourhoods on the basis of point-in-polygon membership. Neighbourhood labels were attached successfully to 233,757 of 233,956 (99.915%) geocoded addresses (199 addresses have no neighbourhood, because their postcode centroid positioned them outside the city boundary).

2.3 SAMPLING

A random sample of approximately 18,000 addresses was drawn from the sample frame using the random selection algorithm in SPSS version 19, stratified by neighbourhood using the syntax shown in Box 2.1.


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Box 2.1. Stratified random sampling syntax.

COMPUTE ran1 = uniform(1).

RANK

VARIABLES=ran1 (A) BY r_neigh

/PERCENT into neighpct

/PRINT=NO .

SELECT IF (neighpct <= 7.7003).

EXECUTE .

The total selection made using this technique resulted in a sample of 17,951 cases (7.7003% of the cleaned sample frame, or 1 in 13 addresses).

The household survey was completed by a total of 3,363 households from all parts of the city. The survey was deployed in four waves. The first, wave A, was a random sample of addresses from across the city. Subsequent waves were used to boost underrepresented areas of the city or groups of the population.

The sample was sorted by the Council Tax reference. Each record was then assigned a unique survey code which comprised of a two digit neighbourhood identifier, a five digit serial number, and a one digit checksum. The serial number was designed to reduce the likelihood of consecutive numbers appearing (which might be easily guessable) and to permit easy identification by the data entry team of the responding neighbourhood.

Table 2.1 shows the final profile of the sample by neighbourhood.

Finally, six duplicate or erroneous records were discarded at the mailing stage because they were found to have unparseable addresses despite having valid postcodes. The total number of mailings for the main survey (‘wave A’) was 17,944.

Survey deployment and response

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Tab

le 2.1

. Neig

hb

ou

rhood

pro

file of ra

nd

om

sam

ple stra

tified b

y n

eigh

bou

rhood

.

Neighbourhood

n

%

Cum.

%

Abbeyfield

207

1.2

1.2

Acres Hill

104

.6

1.7

Arbourthorne

182

1.0

2.7

Base Green

114

.6

3.4

Batemoor /

Jordanthorpe

189

1.1

4.4

Beauchief

47

.3

4.7

Beighton

152

.8

5.5

Bents Green

50

.3

5.8

Birley

260

1.4

7.3

Bradway

145

.8

8.1

Brightside

162

.9

9.0

Brincliffe

155

.9

9.8

Broomhall

274

1.5

11.4

Broomhill

162

.9

12.3

Burncross

96

.5

12.8

Burngreave

54

.3

13.1

Chapeltown

369

2.1

15.2

Charnock

151

.8

16.0

City Centre

442

2.5

18.5

Colley

136

.8

19.2

Crookes

329

1.8

21.1

Crookesmoor

35

.2

21.3

Crosspool

203

1.1

22.4

Darnall

254

1.4

23.8

Deepcar

195

1.1

24.9

Dore

287

1.6

26.5

Ecclesall

146

.8

27.3

Ecclesfield

162

.9

28.2

Endcliffe

200

1.1

29.3

Fir Vale

169

.9

30.3

Firshill

63

.4

30.6

Firth Park

33

.2

30.8

Flower

100

.6

31.3

Fox Hill

194

1.1

32.4

Fulwood

186

1.0

33.5

Neighbourhood

n

%

Cum.

%

Gleadless

218

1.2

34.7

Gleadless Valley

228

1.3

35.9

Granville

100

.6

36.5

Greenhill

266

1.5

38.0

Grenoside

150

.8

38.8

Greystones

233

1.3

40.1

Hackenthorpe

207

1.2

41.3

Halfway

175

1.0

42.2

Handsworth

379

2.1

44.4

Heeley

269

1.5

45.9

Hemsworth

102

.6

46.4

High Green

305

1.7

48.1

Highfield

218

1.2

49.3

Hillsborough

263

1.5

50.8

Hollins End

204

1.1

51.9

Housteads

97

.5

52.5

Langsett

126

.7

53.2

Lodge Moor

134

.7

53.9

Longley

225

1.3

55.2

Lowedges

173

1.0

56.1

Loxley

50

.3

56.4

Manor

322

1.8

58.2

Meersbrook

297

1.7

59.9

Middlewood

204

1.1

61.0

Millhouses

151

.8

61.9

Mosborough

166

.9

62.8

Nether Edge

391

2.2

65.0

Netherthorpe

144

.8

65.8

New Parson Cross

171

1.0

66.7

Norfolk Park

250

1.4

68.1

Norton

154

.9

69.0

Old Parson Cross

372

2.1

71.0

Oughtibridge

66

.4

71.4

Owlthorpe

102

.6

72.0

Park Hill

64

.4

72.3

Ranmoor

160

.9

73.2

Richmond

166

.9

74.1

Rural Area

98

.5

74.7

Sharrow

251

1.4

76.1

Shirecliffe

100

.6

76.6

Shiregreen

336

1.9

78.5

Sothall

166

.9

79.4

Neighbourhood

n

%

Cum.

%

Southey Green

159

.9

80.3

Stannington

151

.8

81.2

Stocksbridge

259

1.4

82.6

Stubbin / Brushes

162

.9

83.5

Tinsley

118

.7

84.2

Totley

115

.6

84.8

Upperthorpe

106

.6

85.4

Wadsley

145

.8

86.2

Walkley

232

1.3

87.5

Walkley Bank

104

.6

88.1

Waterthorpe

202

1.1

89.2

Westfield

116

.6

89.9

Wharncliffe Side

45

.3

90.1

Whirlow / Abbeydale

49

.3

90.4

Wincobank

148

.8

91.2

Wisewood

161

.9

92.1

Woodhouse

336

1.9

94.0

Woodland View

229

1.3

95.2

Woodseats

269

1.5

96.7

Woodside

170

.9

97.7

Woodthorpe

151

.8

98.5

Worrall

50

.3

98.8

Wybourn

214

1.2

100.0

Total

17951 100.0


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2.4 SURVEY DEPLOYMENT

The survey was deployed in four waves, A-D. Table 2.2 summarises the survey waves and responses.

Table 2.1 Survey distribution.

Survey wave

Total (excluding

D) Total

A (original mailout)

B (community email lists)

C (booster mailout)

D (students)

Number of survey mailings 17,944 3,315 1,500

Approx. 30,000 22,759

Over 52,000

Response 2,241 312 134 676 2,687 3,363 Response rate % 12% 9% 9% n/a 12% n/a

Source: UoS and Sheffield City Council

2.4.1 Wave A

Wave A was the main, stratified random sample mail out with a closing date of 27 March 2013. Responses were incentivised with a £100 High Street voucher, which was sent to a random selected respondent who had given their contact details for the purpose.

Each respondent could elect to return the completed printed survey in a supplied ‘response paid’ envelope, or they could choose to complete an online version of the survey. The online version was only available to those invited to participate and users had to enter their unique survey serial number to complete the online survey.

The online survey was available at http://sheffieldhousingsurvey.org.uk/.

The majority of respondents elected to return the postal version of the questionnaire, although 151 respondents in Wave A completed the online version. A helpline (telephone and email) was available to help respondents complete the survey. Approximately 60 individuals contacted the helpline.

A check was made of the final data file to ensure that multiple entries with duplicate serial numbers were not received, although none were found.

2.4.2 Wave B

Following monitoring of Wave A’s response rate and in order to boost response from some underrepresented groups, especially city centre residents, an online-only version of the survey was distributed to members of selected community email lists maintained by Sheffield City Council for the purposes of community consultation. These lists had 3,315 members and attracted 312 responses (9% response rate), all of them online except in a small number of cases where a paper copy was

http://sheffieldhousingsurvey.org.uk/


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specifically requested. Respondents of Wave B were also eligible for the incentive draw and the helpline was also available to them.

2.4.3 Wave C

Again following monitoring of Wave B’s response rate and in order to boost response from selected Housing Market Areas (see Chapter 2 of the main report), a booster sample of printed questionnaires was sent to an additional random sample of addresses from seven selected HMAs:

Chapeltown/Ecclesfield

City Centre

East

North West

Rural Upper Don Valley

Manor/Arbourthorne/Gleadless

Stocksbridge and Deepcar

The random sample was again stratified by neighbourhood using a variant of the syntax in Box 2.1. 1,500 additional addresses were sampled, as shown in Table 2.2.

Table 2.2. Wave C sample by HMA.

HMA Sample

Chapeltown/Ecclesfield 237 City Centre 148 East 270 North West 326 Rural Upper Don Valley 50 Manor/Arbourthorne/Gleadless 355 Stocksbridge and Deepcar 110 Total 1,500

This booster sample attracted 134 responses (9% response rate). 125 were postal responses and 9 were made online. Respondents of Wave C were also eligible for the incentive draw and the helpline was also available to them.

2.4.4 Wave D

Waves A-C under-represented full time students (because the Council Tax database did not generally include first year residents of University-owned and managed purpose-built student accommodation). For this reason, a final survey wave was deployed using direct email to students of the University of Sheffield, and using social media and a link from Sheffield Hallam University student website portal. The link was to a special, expanded online version of the survey aimed at students. It included several additional questions aimed at eliciting basic details on term and vacation time addresses, and student status.


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Owing to differences in the two University’s email list management and policies it was not possible to adopt the same approach. Consequently, it is not possible to ascertain the extent to which the link was propagated, and the final response rate is not known although the method yielded an additional 2,687 responses from students, all of them online.

2.4.5 Response rate

The overall response rate (excluding wave D) was 11.8%. Wave D was excluded from this calculation because the sampling method used was purposive and it was not possible to know how far the survey link had been propagated. The additional 2,687 responses from students were used to weight the final sample data file so that it better reflected the household structure of the city.

2.5 SAMPLE ERROR

It was calculated that using standard assumptions about variability of 50% of any variable, that the confidence limit was +/- 2.21% at the 99% level, and +/- 1.68% at the 95% level. This means that in general we expect the ‘true’ answer to lie within a range of 2.21% of the given answer 99% of the time, and within 1.68% of the given answer 95% of the time. These calculations were based on the formula given in Dixon and Leach (1977), applying a population of 223,906 (the number of occupied household spaces in Sheffield according to the 2011 Census) and a sample size of 3,363 (the total number of responses).

2.6 WEIGHTING AND GROSSING

The survey data file was weighted using post-stratification to better reflect the underlying tenure composition of the population of households and their geographic distribution. This was done by producing a cross tabulation of tenure by HMA from both the survey and 2011 census (at the output area level) and producing weights that compensated for the cell-wise differences between the two tables. These weights were then applied to the survey data file in SPSS. Several key variables were then tested against the 2011 Census to validate the weights. The impact of the final weighing is shown in in Table 2.3 for the tenure profile of the final weighted dataset.

The weights were also adjusted so that all analysis was grossed up to the number of households in Sheffield.


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Table 2.3 Outcome of post-stratification household weighting by tenure.

Tenure Census

proportion %

Proportion of weighted data

file %

Owned: Owned with a Mortgage or Loan 31.23 30.90 Owned: Owned Outright 27.11 31.70 Shared Ownership: Part Owned and Part Rented 0.38 0.30 Social Rented: Rented from Council 17.71 15.90 Social Rented: Other 7.04 5.90 Private Rented: Private Landlord or Letting Agency 14.18 13.20 Private Rented: Other 1.37 0.80 Living Rent Free 0.98 0.20

Source: Sheffield Housing Survey, 2013 and Census, 2011

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3 Estimate of housing need

The Housing Needs Model was prepared in accordance with the DCLG guidance to assess the number of dwellings needed per annum to enable households who cannot access market housing (at reasonable expense) to be housed.

“[H]ousing need is defined as ‘the quantity of housing required for households who are unable to access suitable housing without financial assistance’. For the purposes of assessment, this means partnerships need to estimate the number of households who lack their own housing or live in unsuitable housing and who cannot afford to meet their housing needs in the market.” (DCLG, 2007, P.41, emphasis in original)

The evidence in the SHMA is intended to produce a single estimate of the number of dwellings required to meet housing need. The numerical estimates are a key component of the overall report and DCLG sets out guidelines for the process for combining evidence for the Housing Need Model, which is outlined in Chapter 6 of the SHMA main report.

The DCLG guidance sets out five stages to estimate the level of housing need. The stages are:

Current housing need,

Future housing need,

Affordable housing supply,

Housing requirements of households in need, and

Bringing the evidence together

The analyses of these stages are undertaken in Chapters 5 and 6 of the main report. The needs model relates directly to these stages, but uses a four-stage process. This technical appendix draws out the calculations used to provide evidence for each of the values in the need model, and each sub-stage is indicated within the four overall stages:

Estimate of the backlog of housing need (sub-stages 1-5)

Estimate of newly arising need (6-8)

Estimate of the supply of affordable housing (9-11)

Bringing the evidence together in the overall annual shortfall (12)

These stages and sub-stages correspond to sections and lines of the model summary, which is presented as Table 6.1 of the main report. The remainder of the technical appendix is structured according to the four stages.


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3.1 ESTIMATE OF THE BACKLOG OF HOUSING NEED

DCLG guidance recommends using survey-based data for addressing the backlog of housing need as secondary data is unlikely to adequately address the issues related to housing need.

“Partnerships need a good understanding of the scale of current housing need, including any backlog, at the local authority level. However, it can be difficult to obtain a complete and robust estimate of backlog due to data limitations. Traditionally, local surveys have been used although these can be costly to administer and difficult to interpret.” (DCLG, 2007, P.43)

The recent census of population (2011 Census) provides extensive background information about the population in Sheffield, and some relevant information about housing within the market area. The limited time lag between 2011 and 2013 enables greater use of the census as a credible source of information than many other SHMAs have been able to. The census is used where appropriate, and has provided a source for triangulation with other information sources, but the census does not adequately address all of the issues required in a calculation of housing need, aspirations and preferences. Therefore, for the calculation of the backlog of housing need, the Sheffield Housing Survey data is used as the primary source to provide the robust and consistent approach required.

The total annual number of dwellings to reduce the backlog of housing need calculation is divided into five lines in the housing needs model. The first line calculates the overall number of households in unsuitable housing. The second line removes households whose housing need could be met without the need to create additional affordable housing opportunities, whether that is by remaining in situ, movements within the social rental stock, or from out-migration from the overall total. The third line deflates the sub total to the number of households that are financially unable to meet their housing need through the market (whether rental or owner occupied). The fourth line estimates the number of existing homeless households requiring housing. The fifth line distributes the total backlog of need over five years to provide the total annual need to reduce the backlog of housing need. Each line is now described further in turn.

3.1.1 Households in unsuitable housing

The number of households in unsuitable housing is calculated using the data from questions A7 and A8 in the survey (the full survey can be found in the appendix of the main SHMA report).

Households in unsuitable housing include households in all tenures where the current situation of the household is inadequate. The reasons for inadequacy were surveyed in question A8. The options include aspects related to the household (e.g. financial) and the physical elements of the dwelling they reside in. In addition to the responses provided by the household about question A8, other questions in the survey enable a calculation of technical overcrowding (e.g. A4 and A9). This possibility enables a refined approach to analyse the overall number of households in unsuitable housing, which takes account of overcrowding. This approach divides the total population of households in unsuitable housing into three categories:

Estimate of housing need

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Category 1: households that identify themselves as in inadequate housing for any reason other than the dwelling being too small (e.g. access, maintenance, disrepair, unhygienic conditions, expense, insecurity, harassment, inadequate services, and so on);

Category 2: households that identify themselves as in inadequate housing because the dwelling is too small, and these households are technically overcrowded according to our own assessment (see below); and

Category 3: households that do not identify themselves as in inadequate housing, but are technically overcrowded.

The computation for technical overcrowding uses the Sheffield Allocations Policy’s bedroom standard and applies this to the survey responses for household size and number of bedrooms. 2

The results are outlined in Table 3.1 below. Combining the three categories, 27,857 households in Sheffield are in inadequate housing.

Table 3.1. Households in unsuitable housing (A7, A8, A4, A9)

Household in unsuitable housing No. % of all

households

Households in unsuitable housing (sum cat 1, 2, 3) 27857 12.1%

cat 1: hhld says unsuitable (any reason other than too small only) 23789 10.3%

cat 2: hhld says unsuitable (too small only) and is technically overcrowded 1324 0.6%

cat 3: hhld says adequate, but technically overcrowded 2744 1.2%

Source: Sheffield Housing Survey, 2013

Whilst slightly different to the steps implied by the DCLG guidance, this explanation of the current level of housing need provides a logical and transparent framework, and avoids the challenge of double-counting as outlined in the guidance.

3.1.2 Sub Total: All households in unsuitable housing and need to move

The gross figure of existing households in unsuitable housing includes many households who do not require new affordable housing. Households may be included in line 1 but do not count towards the overall number in housing need for an array of reasons. Having the financial ability to afford market housing (whether private rental or owner occupation) means that a household does not need affordable housing to meet their household’s need. This is a significant element and is applied in the following line (3). Prior to removing households who can afford

2 This assessment applied the bedroom standard implied by the Sheffield City Council allocations

policy to the household composition of survey respondents. For example, non-related adults require a separate room, as do children of the opposite sex. See page 11 of the Sheffield Allocations Policy issue 6.


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market housing a number of categories need to be removed from the overall number in unsuitable housing. These categories are:

households where technical overcrowding can be removed by a concealed household moving out;

households who currently reside in the social rented stock and any movement would have a zero net impact upon the level of housing need (a movement would require, but at the same time also release an existing affordable home); and

households whose housing need is met by moving out of Sheffield (i.e., out-migration).

The combination of these categories is removed from the total number of households in unsuitable housing to provide the sub total of all households in unsuitable housing and who need to move.

The first calculation is the number of households in each category that can be removed by resolving the inadequacy ‘in situ’. No households from category 1 are removed as the issues relate to problems that cannot be resolved through a concealed housing moving out, e.g. suffering harassment from a landlord. For categories 2 and 3 some households’ problem with housing can be resolved through a concealed household moving out, and these are removed using answers in Section E of the survey. Whilst these ‘concealed households’ may contribute to the overall level of need, they are counted instead in line 6 of the needs model and are removed from this section to avoid double counting.

The removal of households in the social rented sector (SRS) requires a note. The assumption that household movements within the SRS stock should be removed from the overall level of households in unsuitable housing is based on a matching assumption, whereby the existing stock is assumed to be able to adequately support a redistribution of households on a one-for-one basis. Line 2 therefore includes an adjustment to the unsuitable housing resolved within SRS stock to take account for the reality of an imperfect distribution of available property sizes to cater for the household sizes of those requiring housing. This was achieved by comparing the size (bedroom) profile of houses being released by vacating tenants with those required by households. This was subject to a matching constraint: households needing a smaller property could in theory be allocated a larger property (although we do recognise that is rarely done in practice, and the removal of the spare room subsidy further diminishes this likelihood), while those needing a large property would not be housed in a smaller property. Hence, there was a matching deficit of large family homes and we found that a 1-for-1 match was not possible, but that there would be an inefficiency in matching that accounts for approximately 6% of the stock, and can be seen in Table 3.2. The percentage is derived from the mismatch between the stock of households who will be moving out of their current SRS property and their preferences for larger properties (we have used 3 bedrooms and larger) based upon the ability of households to be allocated larger homes than their needs, but not smaller.


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Households whose housing needs will be met outside of Sheffield, through out-migration, are discounted from the total. This can be calculated in a number of ways including using historic migration trends, migration forecasts and survey estimates. This model uses projections based on the survey, including answers to Section D of the household survey about households’ future housing intentions and the locations they expect to move to. This accounts for 484 households (see Table 3.3).

3.1.3 Percentage unable to afford to move

Of the households that are in unsuitable housing and need to move, some can afford to meet their need within the market. The percentage unable to afford to rent or buy only is included.

The percentage applied is the proportion of households indicated in the survey who have been wanting to move but not able to do so (question D3) and could not move for financial reasons (question D4, response categories a, b, c, g, h, i and j). The resulting proportion of 67.1% of households is further validated by comparison with the 67% of households found in Sheffield City Council’s own

Table 3.2 Mismatch between size of properties and housing preferences

Bedrooms

Implied no. of properties released

No. of households with needs for

property of this size Cumulative mismatch (preferences to size, including larger property sizes)

5+ 105 15 105 – 15 = 90

4 214 867 214 – 867 + (90) = –563

3 2941 3363 2941 – 3363 + (–563) = –985

2 4468 4622 4468 – 4622 + (–985) = –1139

1 2786 1646 2786 – 1646 + (–1139) = 1

Source: Sheffield Housing Survey. Note that the cumulative mismatch between implied supply and demand mismatch for properties of 3 bedrooms and greater is 985. This represents approximately 6% of the 15,033 households expected to resolve their housing needs within the SRS stock.

Table 3.3 Households in unsuitable housing where need is met ‘in situ’

MINUS 1. of which overcrowded is 'resolved in situ' Num.

% of all households

cat 1: hhld says unsuitable (any reason other than too small only*) -658 -0.3%

cat 2: hhld says unsuitable (too small only*) and technically overcrowded -1254 -0.5%

MINUS - unsuitable housing resolved within SRS stock -(15033) -6.5%

Adjustment to account for bed size mismatch in SRS turnover 6%

Subtotal MINUS - unsuitable housing resolved within SRS stock -14131 -6.1%

MINUS - unsuitable housing resolved by out migration -484 -0.2%

Source: Authors’ calculations based on Sheffield Housing Survey.


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model of the affordability of one bedroomed properties to newly-forming households.

3.1.4 Homeless households

Line 4 of the housing need model includes households who require housing because of homelessness. The backlog of homeless households is taken from the number of eligible, unintentionally homeless and in priority need individuals (290) in 2013, as accepted by Sheffield City Council. This is derived from the P1E returns made by SCC (see Table 3.5). The P1E form is part of English local housing authorities’ statutory obligation under homelessness legislation and provides an accurate and up to date summary of the authority’s records of homeless presentations.

Table 3.4 Reasons given why household is unable to move (but would like to)

Reason Percentage of Responses

a Cannot afford the monthly cost of a mortgage 25.4%

b Cannot afford the deposit on a house 43.3%

c Cannot afford moving costs 29.2%

d Local education choices 4.6%

e Family reasons 14.6%

f Location of employment 5.4%

g Lack of affordable rented housing 39.8%

h Rent/mortgage arrears 9.9%

i Unable to sell 11.2%

j Negative equity 7.0%

k Need advice/support to move 16.3%

Percentage of households who would like to move, but identify as unable to move for financial reasons (respondents choosing any one or more of a,b,c,g,h,i,j) 67.1%

Source: Sheffield Housing Survey.


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3.1.5 Annual total backlog of existing housing need

Standard SHMA practice reduces the existing backlog of need within the area to an annualised target spread over 5 years, hence the reduction to 20% of overall backlog. The precise time period to meet the target can be altered if the Local Authority sets different time period to meet its objectives as per the SHMA guideline set out by DCLG, which is quoted extensively to provide the evidence for a 5-year period.

“The quota should be based upon meeting need over a period of five years, although longer timescales can be used. In particular, there may be merit in linking quotas to the remaining time period of adopted housing policies in plans. For the component of need derived from existing affordable housing tenants, partnerships could estimate the proportion that are expected to be re- housed based on previous allocations. Whilst the decision is the responsibility of individual local authorities, partnerships should bear in mind the need for comparability. Partnerships should avoid using a period of less than five years in which to meet unmet current need.

If a five-year period is used, this means that 20 per cent of current unmet need should be addressed each year. The output of this should be an annual quota of households who should have their needs addressed.” (DCLG, 2007, P.52)

For illustrative purposes only the Total Backlog of Need is distributed over a range of time periods, from 3 years to 7 years. As indicated above, the normal 5-year distribution is used in the Housing Needs Model (see Table 3.6).

Table 3.5 Homeless numbers, 2013

White Black Asian Mixed Other Ethnicity Not Stated

All Ethnicity Groups

Eligible, unintentionally homeless and in priority need

183 30 25 17 15 20 290

Eligible, homeless and in priority need, but intentionally so

24 2 2 1 3 3 35

Eligible, homeless but not in priority need

199 49 23 16 30 21 338

Eligible, but not homeless 95 17 7 8 14 10 151

Ineligible 4 3 0 0 5 5 17

Total decisions (sum of rows 1 to 5 above)

505 101 57 42 67 59 831

Source: P1E, January-March 2013


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3.2 ESTIMATE OF NEWLY ARISING HOUSING NEED

An estimate of newly arising housing need is made in addition to the estimate of the backlog of housing need. DCLG guidelines (2007) indicate that there are numerous possibilities for forecasting newly arising need and new household formation. We have used the Sheffield Housing Survey as the primary source of information for this stage, but we also draw upon Sheffield City Council’s records, for example on estimated average rents and homeless presentations.

3.2.1 New household formation

The SHMA outlines two possible ways of calculating new household formation, and is reprinted here for clarity:

“It is first possible to use population and household projections to predict levels of new household formation (the net change between periods). This technique, however, is prone to the 'circularity' problem in that projections are essentially based on historical trends that are themselves a result of past market conditions and constraints. They

reflect effective rather than notional demand. For this reason, a second method is

often employed: the use of survey data on moving needs and expectations. In the household survey we asked respondents about the expected movement of their household and any concealed households. One major problem with using survey data in this way is that it has been shown in various studies that households tend to systematically over-predict their likelihood to move or to form (Watkins et al., 2012). Studies in a range of countries including the UK, the US and the Netherlands all support the need to adopt a deflator to household survey predictions

of mobility. Once we have adjusted for over-prediction, we estimate that new

household formation will lead to 2,269 new households in the city per year over the next 5 years (line 6 in Table 7.1). Once adjusted in this way, the figure is broadly compatible with that suggested by the ONS subnational population projections for households over the period 2013-2018.” (SHMA main report, p. 113.)

Table 3.6 The total annual backlog through scenarios of 3-7 year progressive targets for

reduction.

TOTAL BACKLOG 7892

Annualised over 3 years 2631





Source: Composite of Backlog of Housing Need using Sheffield Housing Survey and P1E sources


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Whilst secondary data can be used to project household formation the guidelines recognise that there are problems with essential data at the local level. Our approach has been to start with estimates of the level of new household formation that are implied by several household projections including the SNPP-based projections (see main report) but also other projections that we have reviewed. We then test these against different methods of deriving new household estimates from the household survey.

First, we looked at new household formation as implied from simply looking at the number of households likely to move to a different home. Underpinning this is a basic assumption that the majority of these households would prefer a home in the city (i.e. undertaking an adjustment move to cater for changed circumstances or needs), but that the houses they release might be taken up disproportionately by those moving into the city (given increases in population and household projections).

A basic analysis of the survey shows an annualised household formation level of 13,351 (see Table 3.7a). As noted earlier, we know that survey respondents tend to overestimate the actual household formation rate significantly, and so a reduction to 17% of this value is applied in line with previous research (Watkins, 2012). This gives a figure of 2269. The level of new household formation implied by this calculation is consistent with the household projections we looked at (chapter 5 of the main report).

An alternative approach is to estimate new household formation as arising from concealed households that might form (drawing on questions E1 and E2 from the survey). These questions ask whether there are current household members (and if so, who) who are looking to form their own household in the next three years. Information is sought on up to two such household members (and so calculations are likely to be an underestimate of the true number). Table 3.7b summarises the survey response to these questions.

Table 3.7a D2 Do you think you are likely to move to a different home in the future?

Answer Percentage Implied No.

Yes, as soon as possible (e.g. 1 month) 3.0% 6976

Yes, within a year 7.6% 17618

Yes, in 1 to 2 years 7.0% 16187

Yes, in 3 to 5 years 11.3% 25975

No, don't want to 32.5% 74767

No, but would like to 7.1% 16418

Don't know 31.4% 72431

Total 100.0% 230372

Yes Total 29.0% 66756

Yes Total annualised (at 5yrs) n/a 13351

Deflated to 17% of projection n/a 2269



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This method results in an estimate of around 1,660 households per annum, although it must be noted that this is likely to be an under estimate for the reasons given above.

On balance, given that we find that the various methods result in broadly consistent estimates of new household formation we adopt the figure of 2,269 as suggested by both the survey and household projections.

3.2.2 Percentage unable to buy or rent in the market

Of the total new household formation, some households will be able to meet their housing requirements within the market at an affordable rate for that household. The percentage of newly forming households unable to afford to buy or rent in the market is therefore applied to the overall newly arising need. We calculate the percentage using the projected incomes of newly forming households in question E12 of the survey and applying this to average rental levels and lower quartile house prices provided by Sheffield City Council (using their mix-adjusted method for house prices).

In line with national research (e.g. the English Housing Survey) the percentage of newly forming households unable to afford to rent or buy is higher than the percentage of existing households unable to afford. Comparing 80% market rent for a one or two bedroom property in the city (as the lowest cost option in comparison to buying) at 30% of household income, 75% of households could not afford to rent or buy within the market (Table 3.8).

Table 3.7b Questions E1/E2: Are any existing members of your household looking to move into their own accommodation in the next three years? [If so], who is looking or likely to look for accommodation in the next three years?

Answer Person 1 Person 2

Parent / Grandparent 127 136

Child aged 16 or over 17502 6157

Partner/Spouse 887 207

Lodger 659 62

Friend 895 1396

Other 1075 200

Total 21145 8158

Total (person 1 and 2) 29303


Of which 17% (to adjust for unrealised expectations) 1660

Source: Sheffield Housing Survey, and authors’ calculations.


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The distribution of incomes of newly forming households is outlined in Table 3.9 below. The 75% unaffordability figure is based on the cumulative percentage of households earning less than £14,999 (i.e. 65%) and an assumption of even distribution of incomes in the £15,000-£19,9999 bracket deflated to 0.6 of the overall percentage (i.e. 10%) to account for the approximate midpoint of that bracket.

3.2.3 Existing households falling into priority need

Existing households falling into priority need are added to the newly forming households unable to buy or rent in Sheffield. These households are by definition unable to find suitable market housing. The P1E returns provide annual data on homeless presentations and acceptances, the average for 2008-12 is 3,127 presentations and 1,326 acceptances (see Figure 3.1).

Table 3.8 Average market rent, affordability assumption and percentage of newly forming households unable to afford market provision

80% of Average Market Rent (monthly) for a two bedroom dwelling £450

80% of Average Market Rent (annual) for a two bedroom dwelling £5,400

Assume housing costs of 30% income is affordable £18,002

% of households unable to afford £18k 75%

Source: Sheffield City Council and Sheffield Housing Survey, 2013

Table 3.9 Question E12 Distribution of income of newly forming household

Up to £4,999 26%

£5,000 - £9,999 16%

£10,000 - £14,999 23%

£15,000 - £19,999 17%

£20,000 - £24,999 14%

£25,000 - £29,999 2%

£30,000 - £34,999 2%

£35,000 - £39,999 0%

Total 100%



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Figure 3.1 Presentations and acceptances of homelessness

Source: P1E, 2013

3.3 ESTIMATE OF THE SUPPLY OF AFFORDABLE HOUSING

The total number of affordable dwellings added to the existing stock (where positive) will alleviate some of the pressure on the total level of housing need. The supply of affordable housing includes the supply of social relets, the number of shared ownership re-sales and the number of new affordable homes built, minus the number of affordable houses removed from the stock. The total affordable supply (per annum) is estimated in stage 3 of the housing need model at lines 9, 10 and 11.

3.3.1 Supply of social relets

The supply of affordable housing in line 9 of the need model is derived from the supply of social relets and the level of shared ownership re-sales.

DCLG practice guidance outlines that the estimate of supply of social relets can be attained using historic data trends using secondary data, primarily HSSA 3 and CORE4 data. While guidance suggests that it is normal to use a three-year average, it also outlines possible deviations from this practice, for example because of a change in the stock base predicted. Figure 2.2 reveals that the level of relets amongst the Housing Association stock is steady over the period 2008-12, whilst the relet figure fluctuates extensively within the Council stock over the same period (Figure 2.2.).

The variation in historic relets reveals the necessity for lengthy averages and the likely volatility in relet levels in the future projections. A three-year average would not include the significant decline in 2009, and would over inflate the number of relets, and as such we use a five year average. Ongoing assessment of these levels is necessary for understanding whether future supply is meeting projected future need.

3 Housing Strategy Statistical Appendix, now Local Authority Housing Statistics (LAHS). 4 Continuous Recording of Social Housing lettings and sales, collected by the Homes and

Communities Agency.

0

1000

2000

3000

4000

5000

2007 2008 2009 2010 2011 2012

Presentations Acceptances


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The precise levels historically are broken down by category in the table 2.10. Using the HSSA and CORE data the average for relets during 2008-12 is 3728.

Fig 2.2 Number of social relets per annum for Sheffield Homes and Housing Association stock 2008-12

Source: HSSA and CORE, 2013

Table 2.10 Level of social rental sector relets in Sheffield 2008-12

2008 2009 2010 2011 2012 5 yr ave.

LA lets to tenants new to the SRS 2400 2644 2608 2658 2610 2584

General Needs lets to tenants from Private Sector 522 715 532 657 344 554

Tied/rented with job 2 4 4 5 0 3

Private rented sector 110 136 152 173 109 136

Owner occupation 45 54 67 64 24 51

Mobile home/caravan 1 2 1 0 0 1

Living with friends/family 364 519 308 415 211 363

Council lets to tenants from Private Sector 571 630 655 654 442 590

Tied/rented with job 4 3 1 2 1 2

Private rented sector 41 54 70 79 49 59

Owner occupation 45 22 45 30 23 33

Mobile home/caravan 1 2 0 0 0 1

Living with friends/family 480 549 539 543 369 496

Relets to tenants new to SRS 3493 3989 3795 3969 3396 3728

Source: HSSA and CORE, 2013

0

1000

2000

3000

4000

5000

6000

2008 2009 2010 2011 2012

AllCORE Sheffield City Council stock Housing Association stock


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3.3.2 Supply of Shared Ownership re-sales

The number of Shared Ownership properties resold per annum is calculated using a regional average of resale for Yorkshire and Humber (2%) applied to the overall number of Shared Ownership properties in the city. The average level of resale fluctuates between 2.5% and 1.6% in Yorkshire & Humberside over the period 2004-11.

Table 2.11. Average resale percentage of Shared Ownership for Yorkshire and Humberside 2004-11

Yorkshire & Humberside 04/05 05/06 06/07 07/08 08/09 09/10 10/11 Ave

Percentage 1.7% 1.6% 2.5% 2.9% 1.9% 1.6% 2.0% 2.0%

Implied number 16 15 23 27 18 15 18 18

Source: CORE and RSR as quoted in Clarke and Heywood, 2012

The overall effect on the model is very small on account of the small size of the Shared Ownership sector in the city. The survey reveals there are 921 properties in the city currently in Shared Ownership. When these are multiplied by 2% we estimate that 18 Shared Ownership properties will be available for resale per annum. Whilst 18 is used in the housing needs model, Table 2.11 reveals that a variation of less than ten properties per annum over the period 2004-11 and hence at any annual level is unlikely to have a significant impact on the overall average estimate of affordable housing shortfall.

3.3.3 Units taken out of supply of affordable housing

The next step is to subtract vacancies (if applicable) and units taken out of management (including Right to Buy, RTB).

The total number of properties indicated by SCC that are likely to be demolished between 2014 and 2018 (six years) was 317. The precise rate of demolition over those years is likely to vary considerably, but computing an average annual rate of demolition over these six years, which is 53 properties, is acceptable.

Forecasting the average number of RTB units removed from the social stock where households’ properties are currently inadequate need is more complex. The calculation utilised uses the average number of RTB transactions over the period 2010-13 (114 per annum) and then deflates it by the average relet rate of council stock (10.8% for the period 2009-12). This is done to avoid overestimating the impact of RTBs on households in need. It should be recalled that an RTB does not generally remove an affordable housing unit (in the short term at least) but simply transfers its tenure.

We estimate, then, that the average number of RTBs which might otherwise house a household in need is 12 per annum. When combined with the forecast number of demolitions per annum, 53, this gives a total average of 65 properties per annum taken out of the supply affordable housing.


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3.3.4 Committed units of new affordable supply

The DCLG Practice guidance suggests that new affordable supply should be estimated based on committed units of affordable supply. However, in reality this is not certain and, in line with Sheffield’s previous SHMAs , we have taken an average based on recent delivery. This produces an estimate of approximately 201 new affordable dwellings based on the period 2008-13. We have rounded this to 200 in the needs model for simplicity.

Table 2.12. The number of affordable units delivered each year, 2007-13

Affordable housing delivery 07/08 08/09 09/10 10/11 11/12 12/13 Ave. 08-13

HCA Funded 294 178 290 168 270 76 196

Section 106 11 14 7 0 0 0 4

TOTAL 305 192 297 168 270 76 201

Source: Sheffield City Council, 2013

This estimated figure is unlikely to match the actual figures for each year in the near future, as the actual delivery of new affordable dwellings will fluctuate depending upon wider economic circumstances, market conditions and wider development processes (for example the outcome of renegotiations of S106 agreements). The significant fluctuation between 2011/12 (270) and 2012/13 (76) highlights this potential fluctuation in future delivery.

3.4 OVERALL ANNUAL SHORTFALL CALCULATION

The overall annual shortfall calculation draws together the summary of evidence provided in lines 1-11 of the needs model to estimate the required number of dwellings per annum to meet existing and projected future need taking into account the projected level of affordable supply. This projection of overall annual shortfall is determined by combining the total annual need to reduce the backlog (stage 1) with the total newly arising need (stage 2), and the subtracting the total annual supply of affordable housing (stage 3). This is summarised in the SHMA report thus:

Requirementt+5

= (NeedBacklog,t + Need

Arising,t:t+5) – Supply

t:t+5.

where t is the current time period (2013) and t+5 is the horizon period of the SHMA in years.


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References

Clarke, A. and Heywood, A. (2012) Understanding the second-hand market for shared ownership properties, Cambridge Centre for Housing and Planning Research, University of Cambridge.

DCLG (2007) Strategic Housing Market Assessment practice guidance Version 2, Department for Communities and Local Government.

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