School of the Built Environment Housing Conditions of Migrant Workers in Shenzhen Ya Ping Wang School of the Built Environment, Heriot-Watt University,

School of the Built Environment

Housing Conditions of Migrant Workers in Shenzhen

Ya Ping Wang School of the Built Environment, Heriot-Watt

University, Edinburgh

Prof. Yanglin Wang and Prof. Jiansheng WuCollege of Urban and Environmental Science, Beijing

University


Permanent and Temporary Population in Shenzhen

Year

Total population at end of

year (1000)

Population with

residence cards

(hukou) (1000)

Population with

temporary residence

cards (1000)

% of residents

with temporary

cards

1980 332.9 320.9 12.0 3.6 1985 881.5 478.6 402.9 45.7 1990 2019.4 686.5 1332.9 66.0 1995 3451.2 991.6 2459.6 71.3 2000 4329.4 1249.2 3080.2 71.1 2004 5975.5 1651.3 4324.2 72.4


Most Migrants live in Urban Villages

No. original

households

No. of original residents

No. of Private

buildings

No. of migrant tenants

Migrants per

Original households

Xiameilin 572 1376 716 61811 108 Shangmeilin 241 651 400 41384 171 Xianshan 514 1319 684 28000 55 Shangshan 497 1068 966 75000 151 Some examples from Futian


Questions

• What relationship between housing and poverty can we identify in the fast urbanising and prosperous region?

• Does hukou status have an influence over housing conditions in regions with a mix of rural to urban and urban to urban migrant population?

• How does housing condition for migrants in Shenzhen compare with other cities?


Data Collection

• A sample size of about 800 households.

• Stratified systematic sampling method: – three different zones – a number of urban villages in each zone

(Figure 1). – individual migrant households selected

systematically.


Location of case study urban villages1 ． Futian village; 2 ． Shawei village; 3 ． Xiangxi village; 4 ． Hubei village;

5 ． Shangmeilin, Xiameilin and Hebei villgages; 6 ． Shuibei village; 7 ． Dushu village; 8 ． Baishizhou village; 9 ． Tanglang village; 10 ． Buji and Longlin Villages; 11 ． Langxin

and Tianxin villages


Migrants is a very mixed group

Origins of residence registration Urban Rural

Total

Number % Number % No. % Household type Single person household 153 56.5 223 46.6 376 46.6 Families 118 43.5 313 58.4 431 53.4 Sex of head of household Male 189 69.7 374 69.8 563 69.8 Female 82 30.3 162 30.2 244 30.2 Marital status of head of household Single 122 45.0 176 32.8 298 36.9 Married/Divorced/Other 149 55.0 360 67.2 509 63.1 Number of children of married couple or divorcee No child 35 25.0 23 6.5 58 11.7 1 66 47.1 139 39.3 205 41.5 2 29 20.7 133 37.6 162 32.8 3 8 5.7 46 13.0 54 10.9 4 2 1.4 9 2.5 11 2.2 5 0 0.0 4 1.1 4 .8 Final education level of the head of household Not finished primary School

5 1.8 14 2.6 19 2.4

Primary School 12 4.4 62 11.6 74 9.2 Junior Middle School 44 16.2 280 52.2 324 40.1 High School 67 24.7 117 21.8 184 22.8 Career/Technical Certificate

38 14.0 33 6.2 71 8.8

College Diploma 50 18.5 21 3.9 71 8.8 University Degree 48 17.7 8 1.5 56 6.9 Postgraduate degree 7 2.6 1 0.2 8 1.0


Sources of housing (%)

Shenzhen Shenyang Chongqing Housing Tenure No. respondents % % % Owners 11 1.4 8.7 1.2 Provided by employers 107 13.3 5.0 5.7 Rented from the market 675 83.6 82.6 81.7 Borrowed from friend/relative 14 1.7 1.9 2.5 Total 807 100.0 100.0 100.0 Notes: Shenyang and Chongqing surveys were conducted in 2000; Shenzhen survey in 2005/06.


Condition: Sharing House sharing No. of

households % Floor space per

person (m2) Sharing a room with others 187 23.2 7.7 Family use 1 room 131 16.2 13.0 Family use 2 rooms 5 0.6 42.6* Family use 1 whole unit 479 59.4 23.7 Other 5 0.6 25.6 Total 807 100.0

One person households

Two or more person households

No. of Households

% No. of households

%

Sharing a room with others 162 43.1 25 5.8 Family use 1 room 57 15.2 74 17.2 Family use 2 rooms 2 0.5 3 0.7 Family use 1 whole unit 152 40.4 327 75.9 Other 3 0.8 2 0.5 Total 376 100.0 431 100.0

Note: * The small number of cases and the unexpected large space per person may indicate that this category is not reliable. Respondents may have included all housing areas including these used by other families sharing with them.


Housing floor space a) Among households that has exclusive use of a housing unit

No. of respondents

Average housing

floor space of the unit

Standard Deviation

Average housing

floor space per person

Standard deviation

From urban areas 181 43.4 21.3 26.7 18.8 From rural areas 298 45.2 24.8 21.9 16.2 Male 355 45.8 23.1 22.1 16.8 Female 124 40.8 24.3 28.5 18.1 b) Among those who sharing a room No of

respondents Average housing

floor space per person

Standard Deviation

Average No. of persons in

room

Standard deviation

From urban areas 46 9.5 6.1 3.0 2.3 From rural areas 131 7.0 5.4 4.3 3.2 Male 114 7.4 5.9 4.33 3.5 Female 63 8.1 5.3 3.4 1.9 Overall 7.7

(1.5-45) 5.7 4.0

(2-20) 3.1


Sharing a room

Number of persons sharing a room Number of respondents

%

2 people 77 42.5 3 people 32 17.7 4 people 28 15.5 5 to 10 people 36 19.9 10 to 20 people 8 4.4 Total 181 100.0 Housing floor space per person Less than 2 m2 13 7.3 2.1-4 m2 37 20.9 4.1-6 m2 49 27.7 6.1-8 m2 20 11.3 8.1-10 m2 27 15.3 10-15 m2 18 10.2 Over 15 m2 13 7.3 Total 177 100.0



Income distribution

Income per capita Head of households Partner No. of

Households % No. of

respondents % No of

respondents %

<500 77 10.0 19 2.6 13 5.8 501-1000 205 26.7 165 22.1 77 34.6 1001-1500 133 17.3 124 16.6 51 23.0 1501-2000 122 15.8 153 20.6 29 13.0 2001-2500 45 5.9 40 5.3 7 3.2 2501-3000 55 7.1 77 10.4 15 6.7 3001-4000 42 5.5 49 6.6 8 3.6 4001-5000 48 6.2 57 7.6 9 4.1 5001-10000 33 4.3 51 6.9 10 4.6 >10000 9 1.2 10 1.3 3 1.4 Total 769 100.0 745 100.0 222 100.0


Average monthly rent

No. of respondents Average monthly rent

Whole group 805 534 One person households

Male Female From urban areas From rural areas

375 217 158

153 222

422 403 448

512 360

Sharing a unit with others 182 342 Sharing a room with others 130 203

Multi-person households Headed by a male Headed by female Family head from urban areas Family head from rural areas

430 344 86

118 312

632 640 600

741 590


Housing and food costs

Affordability

On housing On food On housing and food Percentage income spent No. of cases % No. of cases % No. of cases % Less than 10% 141 21.0 123 16.1 7 1.0 11-20% 221 32.9 219 28.7 44 6.6 21-30% 142 21.1 188 24.6 110 16.4 31-40% 71 10.6 124 16.2 120 17.9 41-50% 46 6.8 68 8.9 113 16.9 More than 50% 51 7.6 42 5.5 275 41.1 Total 672 100.0 764 100.0 669 100.0


Housing preferences Suitable house under

current income Ideal house if income increased in the future

No. of Respondents

% No. of Respondents

%

Current house or rent other urban village housing

547 67.9 149 18.5

Rent government sponsored cheap rental housing

73 9.1 27 3.4

Rent private housing in commercial housing estate

70 8.7 86 10.7

Buy housing in urban village 8 1.0 44 5.5 Buy government sponsored affordable housing

52 6.5 146 18.2

Buy ordinary commercial housing 38 4.7 310 38.6 Other 17 2.1 42 5.2 Total 805 100.0 804 100.0


Conclusion: Housing and Poverty

• 40 percent of the sample is in housing poverty. – 220 (58.5%) out of 376 single person

households has 5 square metres or less living floor space.

– 101 (30.6%) out of 330 families live either in only one room or have to share a room with other people.


Conclusion: Rural migrants vs Migrants

• Housing condition among migrants from urban areas is slightly better than rural migrants.

• This, however, could be the result of differences in educational background.


Conclusion: Comparison with other cities• Migrant housing condition in Shenzhen is not

worse than that in other cities due to the huge number of migrants

• Housing condition is not much better either in a rich city

• However, we are looking at young working age persons, who work very hard for long hours.


A major challenge for Shenzhen• As a new city, the proportion of migrants among

the total population is extremely large. • Improving migrant housing will be a long and

hard process.• Redevelopment should be progressed with

caution.• Other soft policy options should be tested,

aiming for a gradual improvement and upgrading.


A fragmented and divided housing market

Factory dormitory and construction site shelter

Older houses in suburban villages

New houses in suburban villages

Older houses in inner city villages

Privatised older public houses

Government sponsored rental housing

New houses in inner city villages

Economic/affordable housing

Ordinary commercial housing

Luxury flats

Townhouse/cottages

Owners’ ladder Renters’ Ladder

The rich

The professionals

Low and middle income official urban residents

The original village residents

The urban migrants and established rural migrants


Informal Market

Formal Market

The rich and international migrants


Our recommendation:Integration of different housing markets

Factory dormitory and construction site shelter

Older houses in suburban villages

New houses in suburban villages

Older houses in inner city villages

Privatised older public houses

Government sponsored rental housing

New houses in inner city villages

Economic/affordable housing

Ordinary commercial housing

Luxury flats

Townhouse/cottages

Owners’ ladder Renters’ Ladder

The rich

The professionals


The original village residents

The urban migrants and established rural migrants


Informal Market

Formal Market

The rich and international migrants

Documents

School of the Built Environment Housing Conditions of Migrant Workers in Shenzhen Ya Ping Wang School of the Built Environment, Heriot-Watt University,