ARCHIVE NOTES

Study: 3561

Please note the following

1 The following variable where used m the creation of derwed variables

INDIV94 - MATPRIND94 - AGE18, MONTHTC, CHILD1HHOLD94 - AGEMATWAITL94 - I

2 The variable QTR represents the quarter of the year m which the mtervlew took place

1 April, May, June 19942 July, August, September, 19943 October, November, December 19944 January, February, March 1995

3 On the household file the variable YTETMPO has a variable label ‘whether on agovernment trammg scheme’ and the following value labels

1 ‘with an employer who was prowdmg work experience or practical trammg’2 ‘at a college or trammg centre’3 ‘temporarily away from an employer or project’4 ‘temporarily away from a college or trammg centre’

4 On the watmg hst fie the variable GROUP IS a serial number to mdlcate the number ofthe group wlthm the household

5 Where the value labels on the portable file and m the questionnaire confhct, the correctversion WIII always be the one on the portable file

; 3561

There are 6 fdes with the following data The fde name m shown m brackets

1 Household file - mformatlon about each sampled household mtervlewed(hhold94 MC)

2 Indiwdual file - mformatlon about each mdlvldual m each household mtervlewed(mdw94 esc)

3 Famdy umt fde - mformat]on about each famdy umt m each household mterv[ewed(famun94 esc)

4 Waiting list fde - mformatlon about each waltmg hst group m each household

mtetwewed (wald94 esc)5 Prwate renting tenancy group file - mformat[on about each private renting tenancy

group (prgrp94 esc)

6 Tenancy group mdwldual ffle - mformatlon about each mdwldual m each tenancygroup mterwewed (pnnd94 esc)

The results presented m the Housing m England 1994/5 report were weighted to take account ofnon-response and grossed up to gwe population estunates The percentages were based on thesegrossed and weighted figures hmtructtons are gwen below on which we@rt variable to use foreach data fde Please note the grossed figures are m thousands, so need to be mult[phed by

1000 to gwe the actual populahon figure

For analyses based on the majority of variables, the household fde should be weighted by the

variable H4A A number of questions (I e the attdude questions) were only included m the

questlonnaue for 6 months (from October 1994 to March 1995) If analyses are to be conductedon these variables and population esornat= are reqmred, the data should be weighted by thevariable H4ATT (which Msimply H4A rnultlphed by 2) The variable names of those variables

added for only 6 months start wdh either HAS, PHA or EHCS

The we[ght variable for this fde M H4AT As with the household fde some of the attitudequestions were only m the questloma[re for 6 months These all begin HAS or PHA. If snalyslsat the tenancy group level IS done on these questions a new weight variable wdl need to becreated. TIus should be H4AT rnultlphed by 2 However, for tenancy groups where the head oftenancy group M also the head of household dre attitude questions have already been copiedonto the household fde

If the mdmdual, waltmg hst, fsmdy umt or tenancy group md[wdual fdes are to be analysedthen the data must be weighted The variable H4A should be copied from the household fde andused to weight the waltmg hst, Urdwldual and farmly umt data The variable H4AT should becopied from the tenancy group fde and used to weight the tenancy group mdmdual data

user 1“s

I,Pph.o,, I 259

Appendix ADefinitions and terms

-..

- 2,

260 FIOLSIXC,~,.cww ,,,,,,,

Area type

ACORN Clzssdlcahon

The ACORN c[assilicaucm Ma means of dassfymg areas

accordtng m .,anous Census characttnmcs devued by CAC1

L]mtted An ACORN code m assigned to each Census

Enumcrauon DMtnct (ED) which m then mpmd m all

posccodcs wmhn theED

The hst below shows the 6 ACORN rnqor categories and tie

17 groups Each ACORN group Mfurther dmded m a

number of area types (not shown here) The descnpuons

are C%CI’S

Category A. Affluent suburban and ruraf are=

I Weal&y achwvers, S.burba” AIeas

2 Atlluent Greys, Rural Commu”mes

3 Prosperous Penuoners, Retirement Areas

Category B Affluent fanuly areas

4 Aftlxnt Execuuves, Farmly tiem

5 Well-off Workers, Famly Areas

Categcq C Affluent urban arem

6 AmU.31L Urba”mes, Town and Cmy Areiw

7 Prosperous Pro feswxmls, MetrOpOhran Areas

8 Better-Off Extcuuves, Inner Cq titas

Category D Mature home o-g areas

9 Comfortable Middle Agers, Mature Home Owning AIcas

10 Skdled Workers, Home Ow’mng Areas

Category E New home owmng arem

11 New Home Owners, Mature Commumues

12 Wfute Collar Workers, Bet[m-Off Mulu-Eth”,c Areas

Category F CouncII estates and low income areas

13 Older People Less Prosperous Areas

14 Councd Esume Restdents, Better-off Homes

15 Councd Esmte Rewdems. H,gh U“employmem

16 Co”ncd Esmte Res,de”ts, Greatest Hardsh,p

17 People m Mulu-Ethn!c, Low-[ncmne AIeas

Deprived area

This mnsms of Gm”ps 13 15, 16 and 17 wh!ch are Older

people and less prosperous areas, - counc!l estate restdenw

and high unernployme”t, cou”cd mute restde”ts a“d

greatest hardsh~p, a“d people m rn”lu-edi”lc, Iow-t”cmne

areas It alsm t“cl”des from Gm”p 14 cou”cd areas WIJ

young farmhes and many lone pam”ts, muin+ccup~ed

terraces z“d m“lu-edm!c areas, low me councd houn”g and

less welldf farmhes, and from Group 8

parually genmfied muln+dmtc areas

Urban/Runi areas

The clamficauo” ISbawd on the pop”lauo” we of the area

which mnt.m”s [he posml secwr (CNtie Iargesl part of K)

Urban area are those areas With a rewdenc populauon of at

lea-w 10,000

Arrears

Morrgagc arrc.rs was de fi”cd z being behind wmh the

morLgage p?.yme”Ls at dle “me of ,“tervlew

Rent arrears was defined as being at least two weeks behind

wti tit rent

Bedroom standard

Th!s concept Mused as an md,camr of occuparmn de”smy A

smndard n“rnber of bedmmns Mallocawd m each

household m accordance wwh m age/sex/manral scams

composmon and tit relauonsh,p of the members m one

anotier A separate bedroom ISallocated m each rnarned

couple, any other pemo” aged 21 or over, each pau of

adolescents aged 10.20 of the same sex, and each pair of

chddrcn under 10 Any unpmrcd person aged 10-20 ,s

pawed, !f posstble wth a chdd under 10 of the same sex, or,

if that ISnot posmble, hem she Mgiven a separate bedroom,

as Many unpamed chdd under 10 This srandard IS then

compared wth the actual n“mbm of bedrooms (mcl”d~”g

bedsmers) amdable for dm sole use of the household, and

ddferencm are rabulated BecbocmM converted m other uxs

arc not counced as andable unless they have been de”oced

as bedrooms by the !“fonnants, bedrooms “OKacmally m

u= are counced unless unmhabwable

Dependent children

Dependent chddre” are persons aged under 16, or single

persons aged 16 to 18 and m full-urne educacm”

Deprived area

seeAreatype

Economic activity

Working employees and selkmployed pemo”s, people o“

Government Tmmmg Schemes

Unemployed people WWJOUCa job who were a$adable to

wart work m the NO “As after mcernew and had mher

looked for work ,“ the four week b-eforc the t“[erwav or

were wamng to start a new,ob diey had already obramed,

rims M rhe ILO de fi”uon of ““employed

3

APPE.DIX 261

Econormcally macuve all mhers who were not working,

they include people who were permanently wck or disabled,

reured, m fuii-tmw educauon or looking after tie famdy or

home

Eccmormcally acuve persons wc those who were working or

unemployed ,“ the wctk before mten%w

Full-ume scudenn are classdied according to theu rcporrs

of what they were doing m the reference week (for example,

!f N was dun”g the vacanon and hey bad a full-urnepb,

hey would be classdied as working full rime) The excepno”

Mpeople vmrkmg part mm bemuse they am at school or

college who arc damtied as fuil-urm students

Persons on Govemme”t Trammg Schemes are dassdied u

Worh”g full tune

Family

A famdy “mt !s deii”ed as o“e of

(a) a rnarned m mhabmng couple wth “o

chddren

(b) a married or cobabmng couple/lone parem

and cbe,r never.marned chdd(ren), prowded

these chddren have no chddren of dmr own

(c) one person

Two people of dw same sex wbo described duemselves as

‘partners’ were classdied as a cobabm”g couple

In genecd fanuhes cannot span more than two genemuo”s,

!e grandpare”~ and grandchddre” cannot belong m the

same firmly l%e excepuon to dus Mwhere there ISno

parent m the howhold and N m estabbshed char a

grandparent ISacung m place ofa parent

Adopted and s[epchddrc” belong to the same farmly as

tbe,r adoptmc[steppare”m Foster chddren, however, are

not part of the foster-pare”n farndy

Household

A bouschold Mdefined as o“e person hnng %“e m group

ofpeoplc who have ticaddrc$s ztieiro”lyormzn

res,dence a“d who e!thcr share one meal a day or share a

bring room

Head of household

The head of the household Ma member of the bouschold

and (m order of precedence) mher rhe husband of tie

person, or the pew”, who

(a) owns the household acconmmdatm”

(b) M@iily respo”s,blt for be rent or

(c) has the acconmmdauo. by virtue of some

relat, onshtp m the owner m cases where & owntr or

tenant E .OL a household member

Whn two members of a difme”t sex have equal cla,m, che

male ,s taken as the household head Wle” two members

of dm same sex have equal damn, tie elder Mrake” as dw

bouseboid head

Household membership

Peopk are regarded as hmng at dw address ,f they (m tie

mfwrnam) crmmder the address to be tkmr ma,” res,de”ce

There arc, ho”wer, certain rules wb[ch rake pnomy over

*M cncenon

(a) Cbddren aged 16 m over who IN. away from home

for the pll~Oses of work or wudy a“d come home only

for the bobdays are not included at due parental address

under any cwcumsta”ces

(b) Chddren of any age away from home m a

cemporary,ob and chddren under 16 at boarding

school are always included m the parental bouseboid

(C) PcOple who have bee” ZWdyfrom the address

continuously for SIXmo”tbs m Io”ger are excluded

(d) People who have bee” bvmg ccmunuously at dw

address fors= rno”tis or longer are mcl”ded even ti

they have tie!. rn~” residence elstwhere

(e) Addresses used only as second homes are “ever

co unced as mam residences

Household type

The ma” dam,ficano” of bouschold (ype uses tie follmvmg

ca [ego nes

Marrwd couple wti “o depmdmt chddre”

(reamed and cohabumg m“ples WIJ no chddre” m

wrh nondependent chddre” o“(y)

Mmncd couple wmh dependent cb,ldren (mmed and

cohabmng couples wmh depc”de”t cbddcm)

Lone pare”~ fanuly

(one parent wmb depend.”t chddrm)

Large adult household

(Includes fla[ sh~.rs, tone parcnrs wwh nondependent

chddrcn (only) and households comammg more dmn

one couple or Io”e parem fmdy)

One male

One female

4

262 ! ,,<,,,,., ,\ ,.,,,.,,,, <,,c,,

The ,,,,,,, ,.d coup[. and lone p.,, c,, t lho,,schdd ,, [pm ,,,,,Y

mcludc IXIL Ipe(W,IIr,,,,,ly u,ms c!?AIILXO,, m the

LOUpk/]OllC rl<l,tml f.,,,,,ly

Income

Tables um.dl! show d). gi-m! wctkly ,n.mn. ot d,.

]hOLlsc hold held fol unm u I led th~,,dh or dlc ],?, !1( wLcLly

Illcolllc Orcollplcs cm.$, ,Ilco,nc ,s ,,, c”n, e Ildo,e ‘my

ddLICtl 011S b KMU, LAh[m!l.i) h7SLII.,!ILCc“nc, ,h~ltl<>,lb

The cthlc, (,, Ch.,[>m b ,how [t,. d,qms<d]lc ,,,co,ne or

mrmnc> g, oup> T[m t, obmned by summmg d,.

com[]oncn Ls of ,ncomc of e.,ch pe,so,, Iqcct 16 II, ewe, ,,,

chc Lenallq group [ 1 (nc]uck em ,1, ”~$ h 0.1 mqllownenl,

poli[ 0, Ios&[,0!71 Wlr’mplo>tnc(>l> suite I>etlcti& a“d

pens,ons, ,.come from mwsmie.ss ci”d ochct (emtpcs such

as nl.,, nwnance allowances met wdcnt g, ants rzxN<monal [m, ua”cc pension ccmtrlhutm”>, LL”mn

who ,pc, ””s and , e@r n,zi,”ccnance pay,,,e,,u have bee,,

clcductcd O om earnings m arr,\,e at dmpos~ble mcmne

Marital status

,Ma, ILd smuts K bzsed on dw t,nfomm” t s opmmr And “my

dlffet from legal marital SMCUSU“, d.ccd ad,,lu ofthc Sa.,c

O, oppos!ce sex arc classed as cohab, ung [f they CO!lSKIC!

thcmsdv.s m b. hvmg mgcther as . couple Cohah~tmg

tahcs rN’CCCdC”CCO\rtr other cZ[eg0nc5

Moving households

~ n,ownz household ,, uw.~11~-I homeho[d wh,ch h,u been

m he p,ment add,cj> rO, ICSS th,, i, OrICp<,, [11a r.,,

rcg, on.d t-i bles, IL mclLId.$ households Ic,Idcnl F<,,1.ss ~h,m

(I,lc, ,.l, ,

NC,,, Ihccld, d IIu,,?d,dd ,,,. ho,” ,“1,,, ,,C,C ,)C,L,],~ [,. ,<(,,,

[m,,,’h old .C dlc[, ,,,.,,,0,,, KM,.,, Lo,, u,l,lmq II. Id, ,,,.

(1,0,. ,,1,,, ,“.,. Ilo,,,ch,>ld 1,. ,d ,, d,.,, p, ’,,,,,,, ,Cld, e,,

Non self-contained accommodation

Hc)t>.cltc,kl, ,.,,. c1 ,,,,l,. d ,, 1,,,,,~ ,,, ,,<),, ,.[[.’O,, ( ,md

,.<<>,,,, !,,>,1 ,,,,,,, ,( ,I!’y ,1, ,,LCI , L,, ch<, , 1> ,d,, cmt, <1, 1<,,1, ,

,“,111 m,)(l), , 1,(,1 (,’hohl i), ,[ ,1,., d, ,,( (1 ! II ,11 (), \! ,,,, ,..

,,1,,,1, ,, ,, ,,..,l. <1 ,,, 0,,1, , ,,, qc~ 1,,,,,, <,,,. ,,, ,1<,[ 11,,

,’., >,,,,,, <,,[ ,,,,>,, l,, ,,1011,., 1-{0,,,, 1,,, [<1, ,,1,,,1, ,1, ,,, d ,

‘(),,,,,l (,,, L ,7[, 1,,,. 1, ,11 ),,,1 (,,1,’,. ”,,. 1, ,(1 ,11 I I,’,,

!C’,, !,, nlo<l ,1!0!, [,< 1,,,,,1 11,.,! <)L,,,, 1, c,,,, do<>, >,.,. ,,<,,

,,),,,71 .,1 ,s I,v,,lg ,,, ,,”,, ,.[1-,,),>1 ,,,,. d Uo,,, mi)d !(, (),,

5

Region

in Ily\cs m the 1994/5 Repot t me Ihawd on dle ne,,

SO!.,,l,,l .111Ofr,,, ,C~,O,l,, ,,1 [hC ]qg3/+ @X3,t, [“+’S

1,.,(. h<ix-d o,, vm, d.!,d $lJu, L,c.I ,eg,c),,s The d.[L,O,lSh, rl

hc (WC C,, d,. L>w, AI,,, kw,o,,s ,\ She,,,, I,eI”,v

Gwmmnt OflmF%gmn

North East

North West

Merseywde

Yorkshire andHumberwde

East Midlands

West Midlands

South West

Eastern

South East

London

County Slandard SLMistlcalnqlm

Cleveland

i

NorthDurham

NorthumbedandTyne and Wear

Cumbrla

Cheshwe

1Noflh West

Greater Manchester

Lancashire

Merseyslde

[1Humberslde Yorkshtre andNonh Yorkshue HumbersldeSouth Yorkshme

,

West Yorhshwe

11

Derbyshire East MidlandsLe!cestersh(re

LmcolnshlreNorfhamptonsh,re

Nortmghamshlre

[1

Hereford and West M#dlandsWorcester

Shropshlre

Staff ordshlr%Warw,ckshlreWest M!dlands

Avon

CornwallDevon

DorsetGloucestersh(reSomerset

Wlltshlre

CambrldgeshlreNorfolk

Suffolk

Bedfordsh!re

EssexHertfordshlre

BerKsh,reBuckmghamsh[re

East SussexHampsh!re

Isle of W(ghtKent

OxlordshtreSurrey

West Sussex

Grea[er London

South West

East Anglla

South East

London

APPENDIx 263

Rents Tenancy

Local aurhonty and houmng assomanon tenantsRena are based on the amount paid per week, adjusted to

mke account of any rent hohday Wamr rates were included

If tiey were pa,d as part of tie rcn[

Private tenantsComparable weekly rent was defined zs the charge for the

accommodauon rmnus any add~uo”al cha~es for sernces

hke telephone usage or decmcty Water rates were “CIt

included m mn~

Rooms

These are defined as habnable moms, mcludmg kmchens at

least 2 meres vnde, a“d cxclud,ng rooms wh,ch are used for

buslncss pmpos.es and dmse mt mrmdly used for hvq ,“,

such as barhrooms, todets, storerooms, panmes, cellars a“d

garages Shared kmhens are not included m the room

count

Second homes

Second homes are propemcs which are not rhe houxhold s

mam residence Howcwm, properues wh~ch are the nm”

residence of someone else, or which the owner mcends m

sell because they have moved are not counced as second

homes

Socio-economic group

The basic occupauo”al claswficauon used ,s the Rcg-Ismar

General’s mci=conomtc grouping m Swdard

occupauonal class~ficauon, OPCS (HMS0,Lo”do”,1990)

A collapsed versmn of ttm dassdicabon has been used t“ the

tables as follows

Desmphve de fmhon SEG numbers

Pro feswond 3,4

Employers and managers 1,2,13

[ntcrmcdmte and,””mr

non-manual 5,6

Skdled manual 8,9,12,14

Sem!-skdled manual

and personal smwces 7,10,15

Unskdlcd manual 11

Occ”pauon dmids were collected for economically acuve

a“d reured people U“ernployed people are coded

according to the,r last occ”panon, and reured people are

coded according to tkmr preno”s nm” occ”pano”

The renung agrerme”t whereby [c”anr-i rent be

accommodauon or occupy n free of charge

Head of tenancy

The head of tenancy ,s defined as the person t“ whose name

the accommodauon ,s re”md unless that person ,s a reamed

or cc-habmng woman 1“ such cases N ,s the wvxrmn’s

husband or parmer who Mde fi”cd as be ce”anc m the same

~.y that the deki”, ”on of head of hotih old, by sramcmd

convcnuon, gwes pnonly m the male partner

Tenancy group membership

Evepmne covered by the same re”tmg agreemem who

shares the legal srac”s m“fcrred by the agreement and

whose accornmodarm” ,s pad for by a s,”gle re”L

Tenancy group type

The mam classdicauo” of tenancy group type “XS the

fOllOWl”g CilLegO”es

One adult (aged 1659)

Two adults (aged 1&59)

Couple UIrh dependent chdd(ren)

Lone parent wd! dependent chdd(re”)

farge mamly adult

(Includes lone parcnu wti nondependent chddren

and tenancy groups comammg more than one couple

or lone parent famdy as well z house a“d flat sharers)

Two adults (at least o“e 60 or over)

One ad”h (64 or OV.Y)

Owners

tier occ”pued accomrrmdauo” ISacconmmdauo” w’hmh

Mowned o“mghc or kmng bo”ghc WIrh a mortgage or being

bought as p~t of a shared mvnersh,p scheme

Socd seclor renten

Th,s cacego~ !“cludes houwholds mm”g from a local

authonry or New Town mrpm-auon and rho= re”n”g from

ho”s~”g asmcm”ons, cooperaoves and chamable trusts

6

Private rentem

This sector covers all other tenants mcludmg all whose

accommodauon ,s ued m dw?mjob h also includes people

hvmg rent free (for cxarnple, people hvmg m a flat

belonging to a relarwe) a“d squamers

Urban/rural area

See area type

Waiting list applicants

Wamng hst apphca”s are Fanuhes m ,“dmduals who arc on

a w-amng hsc for mu”cd or houw”g assoc~auon

accommodmmn They could be couple or lone parent

famd,es, one-perm” farmly u“m, or chddren aged 16 or

over Groups which conmm tie household head are

referred to as ‘emsu”g hou=holds , tho$f wh,ch do not

contain the household head are referred m as ‘pOLc”Ual

ncw households

7. . .

Appendix BSurvey designand response

266 IIOLS,YC,\ L.(J\\D),WW

1. Sample design

The SEH sample ISselected from the small users versmn of

[he postcode address file (PAF) A cw~scage sample destgn m

used wwh powcodc sectors, wh~ch are smular m mm to

wards, as the primary sampbng unm (PSUS) The dewgn

mvolvm both smauficauon and clustering

lnmally, postcode sectors m England wccc allocated m

ma,or strata on the basis ofsmndard sramucal re~on The

sectors were dtsrnbu[cd bemvee” 9 regmns and a dtsu”cuon

was made between rncmopohran and “o”-metropobta”

axcas resulu”g m 15 major wan

1~

3

4

5

6

7

8

9

10

11

12

13

14

15

North Mempol,tm

North Non Mcmopobmn

Yorkshme and Hurnbers,de Meuopobra”

York-shine and Humberwde Non Metropolitan

North West Metropobtzm

NordI West Non Mctropohra”

East Midlands

wesl M,dlands Metropol,m”

West Midlands Non Maropobmn

Eam A@a

Inner London

Outer London

Outer So”dI East Merropohtan

Outer So”d! Eaw Non LMeuopobum

south west

Wmhm each major m-aturn postcode sectors were straukied

according m selected hmm”g and econormc !“d,camm

from the 198 I Census Secmrs were mmally ranked

according to the proportion of households m pnvacely

rcnred accmmnodanon, &en dmded mm four bands

conmmmg appmx,mately the same “umber of ho”sehcdds 1

Table B1 The sample of addresses and households

Smlmctmd●ddrns9a

ln,Ugib18 ,ddr,s,a,Demallsh.d or d.nllctUsad sol.ly for husln.~ WOOS..Temporav accornrnodalloo onlyEinPtvAdd,,,, “,1 I“c,dOthar Inellglhlm

T,tal I“mu,lbl.

E,t” P,o,s, holdsId,ntlf,,d at m,ltl household ,We’,es

Totml .Ii.cti.. Mmp19 of h.u”lwlds

M contactFI,I,*,I

n oao

166785226

! 348497214

3236

24844

6a6

25510

113438a3

20ml

W,thm each band, sectors were rt.ranked accmdmg to the

proporuo” of houseboldsl bw”g I“ local authority

accommodate” a“d bands were subdmded w give eight

bands of appmxmmrdy equal sue pm major stratum ( 120

bands m all) Finally, wdun each band, s-xtors were re-

ranked accord[”~ m tie pmporuo” of bous@bold heads I“

socm-econom,c groups 1 to 5 or 13 (Pmfessmnak,

Employers a“d Managers)

MaJor strata were dmded t“to 780 mmor suata of equal S,ZC,

the number of nmmr srram being propomonal to the sue of

the rnqm wrm”rn O“? PSU was selecced from each nmmr

wrat”m a“d 65 sdecno”s were allocaced m each nm”ch of

the year so as m prowde, as far as poas,ble, a rmtmnally

represe”muw sample each quartm WKhm each PSU, 36

addresses were wlected, represe”ung o“e mtcrmewer q“ma

The total set sample sue of dIe SEH was 28,080 address-es

(36 addresses ,“ 780 q“mas) The debvery po,”L m“nt for

England at the “me of the PSU selecum was 20,528,528

Tbe samphng fraction “as dmcfcm 1/731

Conversmn of addresses to ho~ehohis

Most addresses conmmymt one household, about 12%

contain no households (for example msut”nons a“d

addre~es used solely for b“smess purposes), whale orhem

conmm more rhan o“e private household On SEH,

tnterwcws were caned o“t with dl households at m“lu-

housebold addresses

Table B1 shows the “umber of private households ~de”ti,ed

at the 28,080 sampled addresses

2. Data collection

In fomnauo” for the SEH ,s mllccted week by week

thro”gho”t tht year by ccmIp”Ler amstcd personal mterne”

(CL4H) The suwey mm on a financml year and mterwcws

took plact between April 1994 a“d March 1995 Incernews

were soughL WIJI dw household head or partner at each

=mpled household 1“ terra” cmc”msm”ces, an mmrwmv

may be carrwd out WIrh anodwr household member t tic

head 0, pXlllCr ,s nor avadable Thu w “ecessiw’y ,“ only

2% of households

lnternewers workl”g on the SEH form pam of the mm-all

Sot!.1 Sumcy field force Before wor’kmg on SEH, they

attend a bneti”g sessto” and “e” recrum are accompa”,ed

m the field by a Wu”mg officer

Totml ,u.b,, ,f h,uschold, I,t,rrlmw,d

9

,,,,.,,,, I 267

3. Response

Table B2 show the response rate among ebglb]e households

for each govemmenc office region and England as a whole

Overall, mam mternem were achieved mtb 80% of ebgble

households, 4% were not conracted and 15% refused to rake

part Response rates ofatlezt80% wereachtevedm all

regtons cxccpc London (75%)

ALthe households wh,ch agreed m be mterwewed, 2125

Pn=tely renunglenancy group swereldenufied Apnvate

renters mcemcwwas camedoutwh2071 kmancygroups,

97% of hose ehgble

TableB2 Responsebygovernment office region

Gavwnmm!olllcaregion Intmw.w Ilonconhcl Relusal Total

Emu18nd 80 4 15 100

North East a4 3 13 100Ywk.hlra and Humbermde a3 3 14 100fhnih W9SI 81 4 15 100East Mldlandl 81 4 16 100W*I1 Midlands 80 3 16 1111Eastwn a{ 5 15 (00Gr88t8r London 75 a !7 100R,II 01 south Eul 81 4 15 lWSouth West 81 4 15 100

Notes:

1 The PAFmcludes anmd!cator of theesumated number

of separme un!ts or households at each dehvery point

(address) and his mulu+ccupancy count IS used to

esumate the total number of households

10

In dus report results arc presented as esrmnamd total

numbers of households and as percentages based on those

numbers rarhcr than d!recdy on the sample numbers Th~s

annex describes how tit sample was grossed “p m prmnde

[he esumaced muds, and shows the effect on a “umber of

key measums te”ur’e, household mm, household

composmon and employment status

Outline of the grossing

The grossing method Msmular co [he method used for the

1993/94 SEH2 and m predecessor, tie Housing Trader w

tie 1991 Labour Form Sur,,eyL However tie spec,d

adjustment m MS mn”re a“d houxhold mm pmpornons

uwd for the 1993/94 SEH was not repeated for the 1994/95

suwey

There are several stages m the grossing The first Mto use

the samphng fracuon and response mte Broadly, ti the end

result of samphng and no”-cespo”se !s chat there ISa“

mcernew for one m a dmusa”d households, tie grmm”g

factor ISone thousand The I“IWIJ gmsw”g mtnpe”sates for

dflerent response rate~ among households that were more

or less dti,cult m find at home, measured by the “umber of

caJls needed co make con~c~

The remam!ng stages adjust the facton so that rhere Man

exact match wuh populauon esumaces, separately for mafes

and females and for broad age groups An ,mporrant

feature of the SEH gmss”g u rhat thM Mdone by adjusn”g

rhe hctors for whole households, not by adjusung the

factors for t“d,wduak The pOpUkitJO” figures be,ng

matched exclude people who are not covered by the SEH,

chat M those m bed-and-breakfast accommodanon hostels,

remdenual care homes a“d oduer L“SUOJUO”S There Ma

final stage wh,ch appbm only to private tenancy groups

Thm compensates for the wnafl dropout becwe” che mam

%e Of tie SUL’WYand tie PnV_NCren[em mOdule

The effect of grossing

Tables Cl to C4 show dm effecu of gross,”g on. “umber of

key ho”schold charactemucs The maI” pO!”l.i are

Temxc (Table Cl ) - the pmpcmmn of households

rcnrmg privately increases from 9 2% 109 8%, wmh dw

proporuons m tie other ce”urm fafhng shghdy m

compcmauon

Household sue (Table C2) - one person households

,“crmse from 24870 m 26 9’% whale the prOpOrtlO”

wth four or more persons fafls from 23 7% to 21 8%

Household type (Table C3) - apart from o“e person

households, rhe largest tffcct ,s o“ OXp{eS WMJI

depcndcnl chddrcn, reduced from 269% co245%

The proporuon of Ionc parent households ISalso

reduced, from 6 2’% m 5 7’%

Econonuc acwdy statu of the head of household

(Table C4) - hule affected

Are the grossed estimates right?

Grossing has the largest effect on csumaccs of private

c.mnng and on household Nze The quesuon arises of

“heti.er the grossed esumate are right.

Private renters

Two Imes of twdence from the Cemus support the esurnate

of private renters

1 The des,gn of tie SEH ISvery smular to rhat of the LFS m

1991 (bm not to the LFS m Iatcr years, when N changed)

An OPCS smdy of response b,as m tie 1S91 LFS using

mfomnauon from be 1991 Cemm showed dIaL the rcspo”x

rate was sgmficandy lower among privately rcnung

households than for dl wnures together,806% compared

WIdI 85 4% The grossing compensates for the resulting

under-representatmn of pm-ate renters m the sample

2 The grossing method for the SEH m also essemmfly dm

same as was used for the 1991 LFS Housing Trader The

proporuon of pm-at. r.”tees from the grossed 1991 LFS

Housing Trader, 9 4%, was m exact agrccmcnc WIdI the

proporuon from the 1991 Census Before grossing, the

Housing Trader proporuon of pmatc renters w only 8 6%

Afdmwgh tie exactness of the agmmn.mt of the grossed

figure may owe wmedung m chance. the LFS, bke all

sample smweys, ISSubject m samphmg mnabdq -,1,$

ncvcrdmlcss rcassunng

Household sue

Agmn a comparison of the 1991 LFS With the 1991

Census supports tie SEH esuinaces Gmssmg mcrtased

he proporuon of one persm households m the 1991

LFS Hous!ng Trader from 25 O% w 26 1%, SUIIa btde

short of the Census figure of 26 6% The 1994/95 SEH

growing mcream tie pmpomon of one person

households by shghtly more tian d,d the 1991 gmssmg,

from 248% to 269%

When comparmg 1999/94 and 1994/95 SEH resuhs K

should bc remembered that tie adjustme”c of the 1993/94

SEH proporuon m one p-srson ho”wholds to match dIe LFS

270 HOUSl,.>C I,NE,VU,l \[> 19’14, W

propornon resulted m ratier too many onc person

households The 1993/94 report expla!ns the adjustment

and why u was, m rcuospect, too drasuc

Household we

Comparison wth population figures shows that chddren are

over-represented m the sample Since chddren are e,ther m

households consmung of a couple wmh chddren or a lone

parent wmh chddrc., dns means that those two household

types mus[ also be over-represenccd The grossing correctty

compensace~

The stages of grossing

The OutJme atmve described the smgcs briefly In order,

hey were as follows

Sampfmg frachon and response rate

1 Calculace factors from the aamphng fracuon and

response mtes Response rates were calculated sepantely

according to the number of calls needed to make contacL

Hard 10 contact households who do, evcnmmlly, gwc an

mtermmv tend m be dtierent from those found more easdy

In paruculzu rhcy are more kkely to b-e private renters and to

TableCl Tenure

be small households ,“ 1994/95 a.crage household size fell

from 26 persons for households mcmwewed on the first call

m 1 7 for dins-e mcermwed only after 8 calls or more

Response races fall = the number of calls needed to make

co”tacc (or the call number when the mcemewer gwes up)

t“crcazes The effect, rhere fore, IS to gwe a h,ghcr grosmng

factor to the households mterncwed only after many calls

To avo]d random effcc~ of small sample stze, numfws of

calls were grouped mto four mnges 1 or 2, 3, 4 or 5, and 6

or more

Age composm.n of the household

2 Calculate correcuon factors to achmve an exact match

wmh OPCS figures for the populauon by age group The

figures include only peopk m the private household

populanon, excluding ties-e m msutunons The method

employs household Lypes defined tn terms of the youngest

person m the household It s!arm wmh all households wth

chddren under 5 The correcuon factor for tAex

householdss wmply the numhr of chddrcn m the

populanon aged under 5 dmded by the Inmal esumatc from

the prenous wage of gcossmg The next step !s to deal wmh

households WdI chddrcn aged 5 m 15 but none younger

The,r correcbon factor gets rhe number of chddren aged 5

Grmsl”g Owtnr wcuplad Social rantmd Prl.8t# rnntad

Owned Buying wih Counc,l ho,sl”g unfurmshed Iwmshed All ,ant,d Alloutr!ght a mongago assoc,atlon grlvat,ly 18””,,1

parce”ragasUngrmad 255 426 1s9crossed

39 64 28 92 !000252 424 187 39 66 32 98 1030

Table C2 Household size

Gross{.q On. venom Two Persona Th,m P~”O”S Four permns FIwemmons S11of mom wmt’d All Moan

pwcentagas numberU“g,oss,d 248 34a 167 159 56 22 1000 2507Gloved 269 347 165 147 51 20 1000 2436

Table C3 Household Woe.,

Gro;dng with dqmdant chlldrm NOn-dapmd.al Chlldm. onlv )4. chlldfm All

couple Lom parent couple Lone parent COUP!+onk kqe adut hQusehoU One Femon

prce”tagesUngrosmd 269 62 74 28 2a 9 31 24 e 1000G,ot*8d 245 57 79 29 2a 7 34 269 1030

I“cl”dl,q,,hu Wh ch,ldrc,

Table C4 Economic acttvdy status of the head of household

GrOulng In .mpleymenl Unemployed or Ret(red Permanently $Ick Other AllFull t(me. Pall lime bd,%m “0 v/oh or d!sabled lmactwa

UnormsadGrm,ad

Pmmlaws512 48 66 272 44 58 1000514 46 66 276 42 57 IWO

Indd,, ,“k,lownWmh,r1“,1,, p,” ,Im,

AP,t.VDIX 271

to 15 nghc, after allowing for lhose m households wlh

younger chddrcn, whose numbers were fixed m tic first

step The method proceeds up the age ranges m s!mdar

fashton A refinement from age 20 upward N co introduce a

further dwmon, mm hou~bolds that CO”SNCof

people m the youngest age group only and those uwb older

persons The alm ,s w cotrect for the under-rcprcsentauon

m the sample of young adults m households constsung only

of young adults, relauve to young adults stall hvmg m tie

parenral home From age 30 upwards, the age groups arc

broad (30 to 44, for example) as response does not va~

raptdly wmh age at ages above 30 Tbe mecbod Mdescribed

more fully m the Housing Trader to the 1991 Labour Force

Survey 1

.4ge and sex

3 CaJculace correcuon factors co get tie numbers of cacb

sex right wdun each age group [n the young adult and, to

a lesser extent the middle aged groups dnerc are too few

men and too many women, borh m tie sample and after the

grossing up m dm pomc The method sun keeps to

household factors Households are again allocated to types

based on tie age of the youngest person m the household

buc dIM ume based also on whedner dw people m the

youngest age group are all male, afl female or there are

members of boti sexes The medmd proceeds up the age

ranges as for the prcwou.s srage No adjustment Mmade to

housebohls wth cbddren up to age 15 (correcuon factor

1 O) No adjustment Mmade, e!tber, m households With

boti males and fcmdes m the youngest age group Factors

are calculated for households With all males or all females m

the youngest age group to gNe an exact maccb wmh the

populauon figures for the age group by sex

Regmn

4 Finally, calc”latc corrccuon factors to gwe an exact match

wmb the total populauon figures m each re~on, With the

memopobtam areas mated a separate reg!ons and Inner

London treaLed separately from Outer London Tbe factors

correct for response rates hat are lower m some re~onb

than m others Response races arc lower m London, and

especmlly m Inner London

Prwate tenancy groups

5 [n 1994/95jLMt 37. of the ccnancy groups tdenufied m

dIe household ,nterwe” d~d “m prowde a useable mternew

An uplift was therefore apphed m the grossing factors used

for tenancy group tables (but not for privately renting

bo”sebolds) In 1994/95a rckinemen[ stemmed from the

obsenmuon hat nearly all of the loss of wnancy groups after

a successful household mtm’new came from lodgers form!ng

p.rt of rbetr landlord s household, and from tenancy groups

m mulu-tenancy bousebolds These IWOgroups togeher

were therefore gwen a htgber uphft factor than the odwr

groups, 118 compared WIrh 101

Notes

Department of the Envmonmenc Hmtng m Engfmd

HOUn.g T..,h to lb 1988 and 1991 Lafmu form

Suruqp HMSO, 1993

Hazel Green and Jacqul Hansbro Hm.g m England

1993/94 HMSO, 1995

Sources of error in surveys

Ltke all esumates baxd on samples, tic Ksults of tie SEH

are subject m various poss,ble sources cd error The mml

error m a survey esurnate IS the d[fferemcc bemcc” ~hc

esumace denv.sd from the dam collected and tic ne VaIue

for the populauon The LOtd cmor can be d,wded mto two

ma,” ypes systemauc c,ror a“d ra”clorn c,,o,

Systemauc error, m bins, covers those sources of error which

wll “m average to zero over repems of the surwey Bms may

occur, for example, If certain secuo”s of the populauo” are

omtLted from the sampb”g frame, because non-respondent-s

to he survey have d, ffcrc”t charactensucs to respondents,

or f ,ntcmewers systcmancally ,“flue”ce responses t“ o“e

way or another When carrying out a survey, subwarud

effort-s are put Into the awmdance of systcmauc errors but K

M poss,ble that some may SUII occur

The most ~mporrant compo”e”t of random error M

sampbng emor, which Mthe error that arises because the

esnmatc Mbased on a sample survey rather than a full

census of the populauon The results obtained for any single

sample may, by chance, wwy from tie true values for rhe

populauon but tie vanauon would be expected to average

to zero over a “umber of repeafi of the survey Tbe amo”nc

of vanano” depends on the mm of tie sample and tie

sample design and werghung rnetiod

Random error may ah rinse from other sources, such as

winauon m the mforma”tzs t“terpretauon of the qumrxms,

or mtcmewer vanatm” Effort! arc made m mt”tm,s tfIcx

effects dmough t“terwewer trammg and through pdot work

Confidence intervals

.Ahhougb the esurrcme pmd”ced from a sample suwey wll

rarely be !denucal m the pop”lauo” wd”e, wausacal tieory

allows us LOmcas”re OK .uc”racy of any survey result The

standard CITOCca” be esumated from the values obwuned

for the sample and rfm allows calc”laaon of confidence

mwrvals wb,cb g,ve an ,“d!cauon of tie range m wh,ch the

tIUC pOp”klDOn wd”e Mhk+ m fall

Thu report gives tie 9590 confidence i“terwds amu”d

selected sumey csumates The mtcrwd E calculated as 196

umes the standard error on ember s,de of dIc esnmaced

percenmge or mea” sI”ce, under a normal d,snbuuon,

95% of values be W’KFH” 196 swindard errors of the mean

value ff u were posmble m repeat tie sumey under rhe same

condmmns many nmm, 95% of these confidence m[erwds

“ould mmam the pop”lano” v-due Th,s does nOL

guarantee hat the mterwds calculated for a“y

16

.WTNUI.273

parncular sample wdl conram the populauon val”cs but,

when zssesm”g the results of a m“glc NX-Jey, at ,s usual to

assume chat here Monly a 5% chance that tic tme

pop”lacton wdue falls o.tmde the 95% confidence ~“mnal

calculated for be survey esumate

Confidence intervals forpercentages and means

The 95% confidence interval for a sample percentage

esumate, p,Is given hy the formula

p+/- 1 96xse(p)

where se(p) represents the wandard error of tic

percenuigc esumate

For results based on a mrnple random sample (srs), wh,’h

has no cl”sten”g or stranficauo” m wmgbn”g, es”mau”g

standard errors Msmimghtforwzwd 1“ the case ofa

percentage, the standard emor !s based on the percemage

melf (p) a“d rhe subs.wnple swe (n)

,e(p).4p(loo.p)/n

When, as 1“ rhe case of die SEH, the sample dmgn E not

s!mplc random, the standard emor needs m be m“lupbed by

a demgn factor (deft) The dexgn factor M tie rauo of the

standard error wrh a complex sample desrgn COthe

standard error rhar would have been ach!eved wmh a simple

random sample of tie same stze Tbe 95% confidence

mtem-al for a percentage from the SEH Mtherefore

calculated as

P +/- 1 96x d.!t . ~p(l 00-P) /n (J)

The 95% confidence mterwal for a mean (x) ,s PVC” by

x +/- 1 96 x deft x duarzme(x)/rI (2)

The standard errors, des,gn factors a“d 95% co” fide”ce

mtemals for selected perce”mgcs and means csumated from

the SEH are gwe” m Tables DI-D2 for howeholds and D4-

D5 for pnvace renters tenancy groups Tbe errors shown are

for wghced dam

214 HOUSIYG 1X EvIA..U 1W4/’J5

Confidence intervals forgrossed estimates

Tables D3 and D6 shows samphng errors for selected

grossed esumates for households and tcnzmcy groups

respectwdy The grossed number of households of a

paruc.lar type (g) can be represented by

~= c/n x N

where c = dIe “umber of households of a partl~”kir

type m the sample

I n. the mtdl sample s,ze

N = che uxal “umber of households m England

As explained I“ Appe”du C, die SEH sample w grossed m

populauon tmals m that tberc ISno sampbng error

assocmted With N Tbe mphng emor of the grossed esumate

(g) can ~.r.fore be represented by the error assoclaccd wth

(c/n), rh.t E, the pmpomo” of such households m the

sample Tbe smndard cmors and confidence mterwals for rhe

grossed esumate can rber.efore be calculated wmply by

muluplp”g I& comespond,ng errors for tie percentage

csumates by the we~gh ted sample twal

The above method has been used m d.env.e the errors for

grossed esumates based m the full sample For esumatcs

hued on subsarnples (~”cludmg tenancy groups), a sbght

rctinmne”t has m be appbed because the wmgh[ed number

of bouscholds m the subsanple M not fixed by populano”

figures The characcensac ha first m be expressed as a

percentage of the total sample a“d the” the method above

can be appbed

How to estimate sampling errors forother characteristics

For percenmgcs based o“ the full sample of households,

swmdard errors can be esumated using formula 1[ The

~ample sue n !s Lhe unwe!ghted sample Lotal, 20,483 The

design [actor should be tbe factor for a variable m Table D 1

or D2 which ISbkely to be clustered m the same way Errors

for grossed esummes m“ be calculwcd w“g tie rnmhod

described above

For esuma[es based on subsamples, the summary tables show

unwelghrerl subsample s,zes for selected chaacccnsucs or an

approx,mauon Mgwc. by the number of tbousa”ds ,“ tie

corresponding cell m the cables Tbe des!gn factor could be

den as dw factor for a mmdar characccnsuc However,

dcstgn fac[ors for characlcnsncs based on subsamplcs are

generally smaller than those for charactensucs based on tie

total sample Therefore, lf dm demgn factor for the

cbaraccensac ISCIOX to 10, N ISprobably sui%cmn[ to use

the S= standard error for esnmates based on a subsample

Notes

1 There N no stmple method of esumaung means breed

on we!ghced data

17

Table D1 Sampllng errors using weighted data percentagesHouseholds

Charact,,lstlc Parcmtag. (p) Unwmghtad ham Standard .rror 01 @ 95% confldanm mteml Ouslgn factor

. ...””...” .,, . . . . . . . . . . . . . . . . . . . . . . . numberNumb,, i, H,ussboldOne petsm households

TmumOwner Occ.pica

All S,,,,1 RanlemRant.d from Council m Mew T.wnRented Irom Houslflg Aasmlatlm

Pr,vale rm!eraRented gr,”ately ,, f,,m,h,dRented privately fwmshed

VPO Of acco-odallonHmm datachedHouse smn, #eta,h,dHoum 1,,”,,Fbl o, mm,.malt,, PUVOM bulllFlal or mmsondla, conv.mlon

Mumbar 01 Slo,q!ThnaFourFtw la “I,,Tan or m,,,

Em,ic W9,P SI b-d of bo!imh,ldWhitelndl.nPakiStanl ,, Bangl,de,hlW.st IndiaOther m mlmd

Econmlc IE9WS .ltil” 1“”~

Ow.9r OccuQlam% h.ads In amployrne.1% heads “n,m#lo”,d

Ca.ncll .nd Al t.m.mb%hinds In ampl.aymml% heads unemployed% head. .Cooomkally I..etlva

M.rltil st.tui wltblm t..um0wn9r OccuPl*m% heads ml mankd or cc.h.biting

Cauncll and Al 19nni,% h,,d, married m cohab,tlng% head, WXad or sa~,r,t,d% h,ads Wldowad% h.ads d.gl. and n.vm mamlad

Hawhald co.Pdtlom wlthlm t.nunOwner OccuVl*m% COu@, m Chtldmn?. Cougl. wth ch,ldrm% Len. o.rml% Larg, adult gro,~% On. real.% on, I,mal,% One dng(a adult

C,u,cll .,d MT t,n.ati% COUPI., m Ch,ldran% CO”PI, with chlld,,n% L,”, 0,,,”(% Larg. adult wow% on8 male% On. Imule% one single adult

,=,-,,-,=

269

676

2261e739

98e632

20832

282136

5

109321607

94613

12le

65 e33

263124

813

2e 7

41171247172

,,”,,, ”., V=,.=$JW”

20483 038

2047e047

043042022

031021022

204830550520 se039033

20483037021020009

20478029016015011011

!3 939

3862

(3 947

3 ee3

047016

0780580 ae

043

090062076072

!mr..,)<.w

2616 2764

66 e8 6852

2176 234417e8 1952347 433

919 104 I619-701277 363

1972 21883098 330227 Oe 2934<2e4 1436435 565

1017 11 e3279 361121 199052 08e

9403 9517099 161071 129098 142158 202

64 ee 6672299 361

2477 27 e31126 13545958 6302

27 e6 2954

3924 427e(588 le322321 26191579 1861

1394743

273275887

125211

3 ee3224175

147e

139242382

041039014

02026

03039

06506605e04e0660730 e7

4220 43802654 2e 06

243 297541 e19619 921

1191 13092034 21 e6

2113 23671621 187912e6 1514

666 e741261 15192277 25633649 3991

24

43

405661

4e2282

951684

I el218

169172225159

183203213143114

1707

101012

! 12

113( 021091 (9

0991030 9e104I oei 071 (2

097107105112119105112

276 H0U51\C[\ LVCIA.VII 1!3YW!5

TableD1continued SdMplMgerrors using weighted data pWCi?fltageSHouseholds

Charactnr!sllc Pmc,nt,ns (p) Unwalqhtad basin Standard nrror 01 P 95% co. fldanca Intwvml D8slgn Iactor

Paxantaga number percentdga percentage numbermaws

Hous8holdheads rmtdent Iesa than 1 you

NW Heads% Owner 0ccu@8r5% Cmmc!l or Now Town tenants% Mousing Au.cIallon tenants% Rent9d O:lV1tdY unlurn,shed% R,”l,d !l,t”,td” f,[nlshed

Exlstlno Hsads% 0wn8r Occucuen% Council or New Town lenanls% Hou:ino A!soclallon I@nznli% Renlnd Prlvalaly, unfumwhed?. Ranted Prwately, Iurmshed

R.cah9d hauslna bmfltfuIhstrsmt

All sounl ranlad sector tenantscouncil tenantsH A Imnants

Expect ta buy som.whara

All social rented ssctor lmtanlscouncil fmantsH A Ienants

Prlmte ranters

ExP,ct to h’! Prms8mtPrOWtY

All social rented sactor tanantsCouncIi tamnls

Prlvale renters

H9nnholds with sccnd ham-

toe

445200

6413e152

50019069

14199

20476 0 2e

I 15a169

3610

133062113

14

097074047067074

1025 1135 127

4119 4781 1161739 2261 113479 80! 114

1159 1601 1111246 !794 137

4810 51901755 2045

598 7821279 1541845 1135

643 4618 0 7e 6277 6583650 084 6336 6664612 193 5742 649e

231 4266 066225

2181 2439069

26421 t5.23e5

175 2297 2983

010114112116149

110811

080110

620 e90 207 5794 6606 127

65 4266 044 764-936 10694 052 83608 104192 106

44 925 069 30476 57524 103

Ii 20462 0 OT O 9e2S 1 23T2 10s

TableD2 Standarderrors for meansHouseholds

Chamctarlstlc Maa” UnwalQkted bua %tands,d wrof of P 05% c0n114*mc* Imtnrwl Dmlom ttdaf

f par weak numow L p8r Wenfi i per wsa n.mow

u rmtan.,ho”slq b9m91h 4S25

All Soual rantad sector tenants 177 030 1711 1e29 111Cc.unc,lIo..nts 172 031 1659 1781 109H A Imnants 201 087 183e 2181 113

All P,(Vat8 ,8”1811 695 1526 182 6S 93 7307 131In Uolumlshmdammwnodatlon 59 165 5577 6223 104m Iurmshad mcommodatloa e8 e 370 el 55.9605 149

U mmt h9fuc housing bameflt 4379

All social renlmdSmclorlananli 364 031 3779 3901 I 3eCouncil l*nmts 371 032 3647 3773 151H A Imanu 458 096 4392 476e 13

All @t. r.nt.m 512 1344 { 91 4746 5494 12la Unlufnlshed auommodatio. 40a 170 3747 4413 093h lurnhh.d aummnc.daitm 696 3 et 6213 7707 i 34

W,.kl, h.usl,, beaem 4464

fill Soc,al ,mma SWtm I,mms 207 039 1994 2146 123CO.OCII tnnants 199 038 1916 2064 119H A tenants 255 I le 2319 27e1 ( 20

All Pr,vate re”larl 546 441 172 5123 5797 112m unlummh.d accommodate.n 491 I 64 45 e9 5231 1051. Wnlsh,d accmmnodat,o. 698 439 6120 7640 127

Umtga,9 Pavmnt vu wok 571 6303 0 S1 55 aa 5822 111

noms Pm pmsam (rmnslowners 27 20481 001 264 272 111social rmtml 23 002 226 234 116Prlvat, ranlerl 25 004 242 25e

‘3 19

Table 03 Samplmg errors using weighted data Grossed up figuresHouseholds

Chmaclwlsllc Estlmma U,W#10ht8d b8:8 Slznda,d ,rro, 01 B 95% conf[danm ,ntafv.1 D9s,m Iaclor

(howd”d, number thousands tho.sinds numberMumhr 1“HeusshddO.a Parson households

T.aumOwn.r Occupied

All Social Rent,r,Rented km C.uncll m NW TwoR,nl,d l,mn Ho,slng A,,,d,llm

Pnva18 ranlarsRanted prlv.1.ty .nlufnishadRant.d prwataty !urnuhnd

TYP. ●f ..co=datloaHaus, d,lich,dHo”s8 s,ml .d,tachadH.u.a I.rrac.Flat o, rn,lsmerla Pumme MOFlat or malson.rh convmmon

Mulnb., ,1 Sto,w,Thre,FourFtv, 10 “1,8Tan o, nmra

Emmlc ,mup of hud.1 h.u”h.ldWMI,IndianPakwt.nl or BanQlad.shlwed IndianOth,r ,, mlr,d

Eco”.mlc status wlthl” tcmur,Ow”ar Occu,l,”% treads In .mgloymwd% h.ads unwnplqad

C*uncll and MT Ian.mls% hsadl In ,mpl.ym,nl% hsads ““wnployad7. hsads aco.omlcnlly I.actlv.

Ma,nal 12,sm WItblmtam”,,Ownar Occ”,lm%haads 001 nurrl.d or mhabltlno

Cauncll and MT I.n.mls% haads m.nled or cokablting% haads dlvort.d M smbarmhd% hasds Wld.w,d% ha.ds d.gl. and n.v.r mardmd

Hwm9boldl Wllh “.X,4 ham”

5306 20483 76 5 (57 5455 124

2047892

858343

614244

!3 326 13 !46 13506

4277 46113514 3840

683 851

143

146I 56161

44443677

767

( 9361302

634

1616 20561220 1364

548 720

3893 43216104 65085336 57822524 2 S22

148002182

19516

I 84161218

18917222

159

! 832032131431 !4

117107

1111

112

112

113102109119

i 03

20483109103114

76

4107630655592673

995 66 866 1124

2151627325143

73423919

2 OOa 2294545 709249 401106 180

2047057323021

18639262204235362

1a527 la751!99 325145 263194 276321 40321

20469

8768438

6322

8645 8a91395 4a1

96a455

2254

292232

20483

911 1025412 498

2191 2317

3820 57 3706 3932

I 5076289!0633

33232827

204a2 15

1442 1572583 673655 965580 6e6

215 166 244

201

278

Table04 Standard errors for we!ghted data percentagesPrwate lenancles

Characteristic ,%c,”taae ID) Unwmahted base Standard error 01P 95% mnl!dnnce Intewal D.sign !actor

percentaoa ““mber pwce”tageTypn of Tmm.mcy

percentage2006

n.mb8r

Acsurudtisured shotiholdAII I,mcd .“d ~ shmih,ld IU.,CICI

167399566

7863

142

85111196

82

::

1:?300!37315

22

115230321159146

28

261272145114

54154

66(70341

3::20

439217117

86921831

112626022

2:2417

17421526526

::134

7937609002608R6

103153147

067062091

092081123

0 7s0400 M

083(44195126259065

1468 18723690 42905372 5948

649 911508 752

1242 1590

670 1030951 1269

1719 2201

669 975062 218

78d 1132

125I 42135

114I 15119

I 50i (6141

130157137

Ragulatad reglslerodRegulated non regtsleredAll Regulated

HoI accesstblo 10th8 pubhc, PayI rentI/d acmss,bla 10 th8 Wbllc renl freeAll t.namcms not accmslU* t9 th9 publlc

Rmldenl landlordNo mcur!lyBcSlda.t landlord 8*4 no l@curlti

TYPE,1 Prop.rt!

AS..r.d and Assur.d AWhoid !,”anc\asD,ta,hed ho,,,S*ml dmtachmdhou$aT,r”mti ho”,,Hal purposmbwltFlat, otherOthecl business

R#@#ledOetachea house3mm de!ach,d housaT,,raeed h,,,,Flat Purposa builtFlat oth8rOtharl busmms

r.”.”,,.. “01 acc*ssib18 to th# publfcD,lachad ho”%aSemi dmlach,d housnTerraced housaFlat PurPom bulllFM olh,,Otharl bUSl,,SS

1140527 853

1268 18522616 33821123 16172642 3658

090 344

019134143123188151

317

432

177

192252274218240103

23e225218169129194

17538645424e393103

236141100091101036054

774 15261806 27942673 37471:&3 ::;:

078 462

032106104106121I 11

2144 30762279 31611023 1877809 1471287 793

1160 1920

0411051281101 !8111

,%,dmf Iandlod and no s#c.rlryDatach,d houseSaml-delach*d houmT,rrac,d hou,aFl,t P“,P,S, b“,ltFlat other

317 1003842 2457

2520 4300384 1356

2390 3930003 401

094136( 27I 17112098Othar/ busmms

Fnllly COmp.sltl,”

A,s”md and Assured ,ho,ihol# t,n.”elm1 adult ag,d 16-592 adults agad 1659C,”PI, WOII dependent chlld(mn)Lom parent wtlh detandmt chlld(ren)LarPe mm”ly adull2 adults at Iaul one 60 or owar1 adult 60 or 0“,,

11403927 48531894 2446974 1366682 103e722 1118103 251206 416

161115104( 10116098105

R,gulaf,d1 adntl anad 16.592 adults aged 1659COUPI* wllh dependent chdd(ran)Lon8 parent with d,pmdanl chlld(ren)Lam. manly adull2 adults al laasl mm 60 or 0V811 adult 60 m ,“,,

T,”.”C,,S “01 aum,,bl, 10 Iha publ,c1 adull annd 16592 adults agad 1659Coupla ‘#oh dap.ndmt chlld(rm)Lam par.nl w,th dapandant child(ren)Lam. ma,nly adult2 adults at least Ona 60 or over1 adult 60 or,,,,

Ras,d#nl lmdloti and nO MC”,ltY

1 ad,ll ag,d 16592 ,d”t: ag,d 1659Counl. w,th d,pmdenl chlld(ran]Lo.. parent with dapmdml chlld(mn)LarEa mainly adull2 adults at least ma 60 or over1 adult 60 or mar . .

317I oe101118092103105087

1911 3s1 5s078158254268

22623221e077127129166

746 1494350 890290 910071 3695!6 11421952 29483645 4695

4321297 21831695 26052423 3277

109 411561 1079579 10851015 1865

1241171 Ou( 01095097101

177308192065000I 25058218

7326 e534384 1136037 217000 000030 520034 194

433 1267

1010%091000101086103 21

.,,,..]. I 279

Table 04 (continued) Standard errors for weighted data percentagesPrwate tenanc{es

Chamclmisllc Percentage (p) Unwa,ghled basa Standard #rror 010 95% mnf,d.nc. ml.rval C18*IU” f,cto,

wcentaoe number nercmlaoe nercentam numbethm.mtk cb.nctmlsllcs

A$s.,ed and Ass.md shm!hold !mnanctuMm undw 30Women under 30Mm 30.59Women 30 59M*” 60 or ,“.2,Women 60 or over

R,#”laf.dMm under 30Women under 30M*” 3059worm. 30-59M., 60 or ,,8,Worm. 600,0,,,

T.nanclm nm accms)bl. t. th. publicM.. untiw 30Women .nd.r 30Mm, 30-59Womm 30 59Mm 60 of mmworm” 60 m ,,,,

R.std.nl I.ndlo,d and no s.c.,#vMe. und., 30Wmnm und.r 30Mm 3059woman 30 59M8n 60 or overwoman 60 m 0.8,

Ewloyrn.mt status

Ass””d and Assu,,d ,hmlhold tm,nci,’Wmilng lull limaWotilng pad limaUn.mploy.dRatl,adFull tlma Oducallo.Othar Inacllvm

#,gu/. fedWc”iln, t“ll-!lmaWotwn. part tlmmUmmployedRallmdFull tlm. aduc.llmOthw lnacllw

Tenancl.s ..1 .cc.s.!bl. 10 lh. p.bllcWorklna full-lkmworking pad tlm.Un,mQloyedRallmdFull Ilme eduutlonOlha< Inactl”a

R..id.nt I,”dlmd and “o S,C”,,WWww”g 1“11urn,Wmklq pad IkmUn.m@.y.dR,tl,edFull !lrm .ducatlc.n

1 (38190 3068 3812

1800 23602647 3293790 1150224 416128 312

344 ( 35119121104095107

20 e 143165092049047

297973222

3170703

052028242153283247

032 172027 083

1736 2684550 1150

3255 43652536 3504

109095104098104096

22165

381302

432185

276945

113115

233083240104195

1393 2307107 433

220 1160250 658

124106100104

748 1512827 1473

094123165

177408156293

494945

442354

3214 4946866 22542258 3602

174 810194 7e6101 799

119130

3431621 5(I 7e

100lW

092114

1137I 99094124061221103

45781

15741

152112

4180 4960626 99+

1327 1e13290 53o

!087 1953

1351151151042 oe

1!918 1322

316242122134276037204

2195066

53704

124

1716 2634261 739397 923

4629 5911033 113

e40 1640

104099096098108

11

429791

2923

(150934

218092075164052

74 e3 8337110 470083 377829 1471

( 11113104106

012 192144 536

116115I

(77376

54!7760

234

48817335416245

2804 4716201 e79

i076 24642e1 919

1458 3222522 145e

134101123091141106Othw macttva 99 239

22

280 HO.5,NG ,. ,Ncu,ll IW,p,,

Table05 Standarderrors using we!ghted data meansPrwate tenanc,es

Char. cisr,stlc Mean Umvmghled base Slandard mm, ,1 P 95% conlldmca ,nlawal Omlm factor

Rooms o,, Person 24 2125 004 232 24e 14rm,mcy s,m (pe.agte) !9 2071 004 182 19a 136Cmnparabla .aekl” m“t (E) 628 1758 161 00643 0066 13H,u,,,g Ba,eflt (weekly f) 545 I 801 163 0051 0058 114Comparibta woe~ rml !8s housng benefll (C) 479 1505 173 4451 5129Disrloubl, weakly ,ncml, (f)

1232178 1819 737 20335 23225 132

Table06 Sampllngerrors errors usingweighteddata Grossedup figuresPrwate lenanc,es

Chamlmllc Mean Unwalghled base standard Srlor 01 p 95% conlldmm d“tmval Des,gn Iacior

lhou$ands

TYP8 of !snlng

“Umber thousands the”.w”ds number

2066Assured 367 23 323 411 125AaI”,8d sh,fthald

RWulated877 34 81 944 142311 20 272 350 119

Not ,Cceu,bla 10 the ,Ublk 431 27 378 4S4 141R.sbmnt landlord and “o security 211 19 114 248 137