Changing Residential and Employment Distributions in

Guangzhou

An Analysis of Commuting Flows

Tremendous transformation of China cities

• Gradual weakening of the work-unit system

• Dismantling of work-unit compounds for real estate developmentWorking and living within a work-unit

compound increasingly less common

• Land re-commodification and the (re)emergence of the urban rent gradientRe-emergence of the CBDSpatial differentiation of land use in response

to differential rent

• Local government as an active agent in urban restructuringDevelopment zones and industrial

suburbanizationCentral city redevelopment and showcase

projects by municipal governments

• Phenomenal growth in the real estate industryMassive real estate developments, especially

on the urban fringe (in the form of xiaoqu or largely gated residential estates)

• Equally massive investments in transport infrastructures: urban motorways, metro systems

• Significantly affects where people live and where they work

• Hence the pattern of commuting– Time and distance (and hence cost) of

commute– Pattern of the commuting flows over the city,

and implications for traffic congestions– Means of commuting

Data and Methodology

• Two household surveys in Guangzhou2001: 1500 households2005: 1203 households

• Multi-level probability proportionate to size sampling – To ensure spatial distribution of the sample

approximates the spatial distribution of the population

– Level 1: Urban Districts (qu)– Level 2: Streets or Sub-districts (jiedao)

• Residence/workplace recorded at street ( 街道办 )/postal zone levels

• Both retrospective residential and job histories dated back to 1980 available

• Commute distance calculated using Geographic Information Systems (GIS)

Guangzhou

• Inner Core: Yuexiu, Liwan and Dongshan and the northern strip of Haizhu

• Inner Suburbs: The rest of Haizhu, Tianhe, Fancun, southern Baiyun and part of Huangpu

• Outer Suburbs: Panyu and the rest of Baiyun and Huangpu

Changing Distributions of Residence

53. 2

29. 2

38. 446. 5

8. 4

24. 3

0

10

20

30

40

50

60

I nner Core I nner Suburbs Outer Suburbs

Resi dence Di st r i but i on 2001 (%)

Resi dence Di st r i but i on 2005 (%)

Changing Distributions of Employment

61. 3

36. 6 34. 7

46. 7

3. 9

16. 7

0

10

20

30

40

50

60

70

I nner Core I nner Suburbs Outer Suburbs

Empl oyment Di st r i but i on 2001 (%)

Empl oyment Di st r i but i on 2005 (%)

Changing Mode of Transport

15. 3

25. 3

20. 6

14. 5

33. 2

43. 2

6. 1

1. 8

20. 4

8. 6

2. 8

6. 4

1. 50. 10

5

10

15

20

25

30

35

40

45

On f oot Bi cycl e Publ i c Shut t l eBus

Motorcycl e Pr i vateCar

Others

Transport Mode 2001 (%) Transport Mode 2005 (%)

Results:

• Mean commute distance increased from 4.6km in 2001 to 5.7 km in 2005

• Mean commute time from 26 min to 28 min– => mean commute speed from 10.4km/h to

12.2 km/h– Probably a result of the commencement of the

Metro System in 1999 and subsequent extensions in recent years

Pattern of Commute, Guangzhou 2001

Pattern of Commute, Guangzhou 2005

Commuting Pattern

• Despite the longer average commute distance, long distance suburb-central city commute actually declined:

• % people lived in inner suburb and commute to central city: from 46.3% to 26.6%

• % people lived in outer suburb and commute to central city: 47.8% to 18.2%

Factors affecting commute distance: Equations without Location Dummies

2001 2005

Gender (1=male)

-642.38 ** +84.10

Not significant

Income +13.89 *** +16.78 ***

Constant 5259.84 4438.87

Gender

• 2001 eqtn: gender takes on the “wrong” sign but highly significant– Lingering influence of work units in assignment of

housing– Gender inequality in housing assignment within a

work unit– Inclusion of the residential location dummies renders

it insignificant.

• 2005 eqtn: “correct” sign, although insignificant; increasing resemblance of western norm

• Positive and Significant in both 2001 & 2005 eqtns.

• Income elasticity increased over time• Increasing validity of the Alonso-Muth model

(greater tendency for high income households to move to the suburbs) ?

• Inclusion of the residential location dummies significantly reduces the income effect in 2005

• Increasingly, income has an effect on commute distance via its effect on residential location.

Income

2001 2005

Occupation

Hidden=Manual Self-employed -2092.17*** -428.93

Skilled and clerical 422.15 98.38

Junior managerial -22.76 766.31

Middle and senior managerial

420.18 1140.60*

Professional 541.10 1015.00

Occupational status

• Relation between occupational status and commute distance weak in 2001

• A clear association is discerned in 2005

• Association strengthened significantly with inclusion of residential location dummiesHigh-status workers more likely to occupy

inner locations, after controlling for income

2001 2005

Work Unit Type (hidden=private & others)

SOE -383.24 304.49

Gov’t -1150.76*** -1056.50**

Industry (1=manufacture)

+342.10 -1056.50**

Industry and enterprise type

• Workers in gov’t and Party organizations had shorter commutes than those in other work units, but the difference was smaller in 2005, compared with 2001– Gov’t and Party organizations only began to earnestly

implement housing reforms after 2000

• Workers in manufacturing had shorter commutes in 2005– Out-migration of manufacturing jobs have not brought

about increase in commuting distance

Conclusions

• Rapid suburbanization of both residence and jobs in Guangzhou

• Intra-zone traffic today dominates the commuting scene in both central city and suburbs

• Gender and income effects increasingly resemble those found in the West

• But lingering influence of the work unit system is still apparent.