Si-ming LiCentre for China Urban and Regional Studies, Hong Kong Baptist University, Kowloon, Hong Kong

Zheng YiChongqing Planning and Design Institute

Quan HouCentre for China Urban and Regional Studies, Hong Kong Baptist University, Kowloon, Hong Kong

Using Mortgage Loans to Finance Home Purchase in Urban China: A Comparative Study of Guangzhou and Shanghai

China’s Urban Land and Housing in the 21st Century HKBU, Hong Kong, December 2007

Outline

Mortgage Loan Users 3.

Mortgage Loan Using4.

Concluding Remarks5.

The 2005 Guangzhou / 2006 Shanghai Survey2.

Introduction1.

Housing and urban development are heavily dependent on the nature of the housing financing system and the availability of credit (Zhang, 2000)

From an individual's perspective, access to housing finance is of critical importance in achieving homeownership

Underpinning the rising rate of homeownership in the West are reforms in the financial market (Angel, 2000; Li and Yi, 2007)

In China, the restructuring of the housing financing system is probably more fundamental than in developed market economies (Zhang, 2000)

Urban Housing Finance

Institutional change in urban housing finance (Wang, 2001; Li and Yi, 2007)

1992-1998:

Sales of public housing to sitting tenants at heavily discounted prices

1994, establishment of Housing Provident Fund (HPF) nationwide

Further liberalization of the housing finance system

Post-1998 developments:

1998, to end welfare allocation of housing

Increasing reliance on the market to satisfy housing needs

From in-kind to monetary subsidy, principally given by government organisations and other non-enterprise state work units

Urban Housing Finance in China

Mortgage Loans

A Necessity

Rising prices render home purchase increasingly difficult, especially for people lacking subsidies or savings

Access to Mortgage finance for the first time in China is of significant importance to the household in entering homeownership and consequently building wealth through mortgage payment and home price inflation

Bringing the case of China closer to the situation in the West (McDonald, 1974; Kain and Quigley, 1972)

Mortgage Loans

A Possibility

At about the same time the Chinese state has endeavoured to build a thriving and modern banking system

Strict conditions of borrowing have limited its effectiveness before the late 1990s (Zhang, 2000)

Since then, the state has entrusted the newly restructured state commercial banks to extend mortgage loans (Li and Yi, 2007)Commercial banks compete intensively for mortgage business, since it is considered low risk loans (Shen, 2000; Yeung and Howes, 2006)

Outstanding Mortgage Debt in Shanghai

72344

650

1087

1709

24562645

2484

0

500

1000

1500

2000

2500

3000

1999 2000 2001 2002 2003 2004 2005 2006

Year

Mor

tgag

e Loa

n (R

MB

100,

000,

000)

Clearly use of mortgage loans has been showing rapid increases

The graph is about Shanghai, but other cities exhibit similar trends

Data from the People's Bank of China show that Shenzhen (30%) and Chongqing (34%) have the highest percentages of home purchase financed by mortgage loans

But the same data show that to date the majority of home purchase remain financed by personal savings and other means

Is the use of mortgage loan in China a matter of choice?

Or is it more of a result of supply restriction?

Development of Mortgage Loans in China

Literature Review

Study on mortgage lending in Western countries focuses mainly on racial disparities in mortgage lending (eg., Kain and Quigley, 1972' McDonald, 1974; LaCour-Little, 1999)

Reflected in the China context is the discussion of disparities brought forward by the implementation of the HPF (Chen et al., 2006; Chang, 2006)

And its performance (Wang, 2001; Yeung and Howes, 2006; Li and Yi, 2007)

Mortgage loans by commercial banks rarely studied. Exceptions:

•Deng et al (2005): relates borrower's characteristics to prepayment behaviour. •Li and Yi (2007): Personal savings and parental support are the most important sources of funding for home purchase. Urban residents in China are still reluctant to borrow mortgage loan.

Absence of multivariate analysis on the access and use of mortgage financed by individual families

Literature Review

Study ObjectivesBased on data generated by household surveys conducted in Guangzhou (2005) and Shanghai (2006-7) , the present paper tries to examine:

Who are the mortgage loan users, and how would they compare with homebuyers relying on other means?

Some authors (PBC, 2005; Chang, 2006), based on the experience in the West, believe that mortgage users are the better-off groups. If this is the case then it may be argued that lender’s assessment of credit worthiness is an important factor determining mortgage access? The concerns regarding uneven access to mortgage finance in the Western literature would then apply to the Chinese case.

For those who have made use of mortgage loans, what are the factors determining the amount borrowed?

People in the Shanghai and Guangzhou samples who have bought commodity housing from 1998 onwards

Number of commodity homebuyers in the Shanghai sample: 559

Number in the Guangzhou sample: 415

The effectiveness of the HPF is quite limited. In particular, the use of HPF loans in Guangzhou is close to non-existent (Li and Yi, 2007). Thus the following analysis focuses on mortgage loans by commercial banks.

Data

The Surveyed Households in Guangzhou

The Surveyed Households in Shanghai

Frequency of Mortgage Finance in the Purchase of Commodity Housing

CityLoan Users

Non Loan Users

Total

Guangzhou 110 305 415Shanghai 174 385 559

Guangzhou 27% 73% 100%Shanghai 31% 69% 100%

N

%

Financing Source for Purchase of Commodity House (Guangzhou)

8067

27702261

339 301 119 74 15 12 6 30

100020003000400050006000700080009000

Pers

onal

Savi

ngs

Pare

ntal

Cont

ribu

tion

Comm

erci

alMo

rtga

ge L

oan

Sale

of

Prev

ious

Pers

onal

Loa

n

Draw

fro

m HP

F

Othe

rs

Work

Uni

tLo

anWo

rk U

nit

Subs

idy

Gove

rnme

ntSu

bsid

y

HPF

LoanHo

usin

g Fi

nanc

e (R

MB 1

0,00

0)

Financing Source for Purchase of Commodity House (Shanghai)

11496

7297

43953617

782 953 551 1600 179

946

0

2000

4000

6000

8000

10000

12000

14000Pe

rson

alSa

ving

s

Pare

ntal

Cont

ribu

tion

Comm

erci

alMo

rtga

ge L

oan

Sale

of

Prev

ious

Pers

onal

Loa

n

Draw

fro

m HP

F

Othe

rs

Work

Uni

tLo

an

Work

Uni

tSu

bsid

y

Gove

rnme

ntSu

bsid

y

HPF

Loan

Hous

ing

Fina

nce

(RMB

10,

000)

Composition of Financing Purchase of Commodity House

58%

20%

16%

2%2%1%0%1%

37%

24%

14%

12%3%6%2%2%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Guangzhou Shanghai

Others ( I ncl ude GovernmentSubsi dy)

Work Uni t (Subsi dy + Loan)

HPF (Draw + Loan)

Personal Loan

Sal e of Previ ous House

Commerci al Mortgage Loan

Parental Contri buti on (Donati onand Lendi ng)

Personal Savi ngs

Differences between loan and non-loan users: Univariate Analysis

Average Age of Household Head

36. 5

37. 3

36. 3

39. 6

34

35

36

37

38

39

40

Guangzhou Shanghai

Ave

rage

Age

Loan UsersNon Loan Users

Household Income

7. 3

13. 7

9. 5

11. 3

0

2

4

6

8

10

12

14

16

Guangzhou Shanghai

Hou

seho

ld In

com

e(R

MB

10,

000)

Loan UsersNon Loan Users

Work-unit Types

12%

23%

29%

11%

26%

17%

20%

24%

12%

28%

9%

29%

30%

26%5%

15%

37%

22%

22%4%

0%

20%

40%

60%

80%

100%

GZ LoanUsers

GZ Non LoanUsers

SH LoanUsers

SH Non LoanUsers

I ndi vi dual l y owned busi nessForei gn enterpr i ses and Si no- f orei gn enterpr i sesPr i vate enterpr i sesSOEs and Col l ect i ve- owned enterpr i sesGovernment department and quasi - state i nst i tut i ons

Occupation Status

32%

25%

16%

27%

1%

28%

17%

17%

37%

1%

2%

21%

23%

49%

5%

10%

24%

25%

36%

4%

0%

20%

40%

60%

80%

100%

GZ LoanUsers

GZ NonLoan Users

SH LoanUsers

SH NonLoan Users

OthersMi ddl e and hi gh rank cadres and prof essi onal sLow rank cadresCl er i cal and techni cal workersManual and servi ce workers

Education Attainment

3%14%

58%

26%

2%10%

46%

42%

0%0%21%

79%

3%5%

28%

64%

0%

20%

40%

60%

80%

100%

GZ LoanUsers

GZ Non LoanUsers

SH LoanUsers

SH Non LoanUsers

Pr i mary or Bel ow J uni or SecondarySeni or Secondary Tert i ary or Above

Received Parents’ Contributions

42%

59%56%

66%

0%

10%

20%

30%

40%

50%

60%

70%

Guangzhou Shanghai

Rec

eive

Par

ents

'C

ontr

ibut

ion

(%)

Loan UsersNon Loan Users

Received Parents’ Contributions

7. 5

12. 713. 6 13. 2

02468

10121416

Guangzhou Shanghai

Pare

nts'

Con

trib

utio

n(R

MB 1

0,00

0)

Loan Users Non Loan Users

Comparison between mortgage loan users and non-loan users: Summary

Aspect Guangzhou ShanghaiAge LU ≈ NLU LU < NLUHousehold Income LU < NLU LU > NLU

Work-unit Type

Occupation Status Lower status Higher statusEducation Less educated More educatedReceived Parents' Contributions

Less likely to be government or quasi-state institution employees, More likely to be private enterprise employees

Less likely

Multivariate Analysis: Binominal Logit RegressionTo see if the above findings hold after controlling for other variables

Independent Variable: Use Commercial Mortgage Loan = 1, Otherwise = 0

Explanatory Variables and Results

Socio-economic and demographic variables:

Age, Work unit type, Education attainment, Years of residence in the city, insignificant for both GZ and SH;

Household registration (migrants more likely to use mortgage loans) significant for GZ;

Occupation status (middle and high rank cadres and professionalsmore likely to use mortgage loans) significant for SH

Housing attributes: Tenure of last home (1=own, 0=rent), HPF account (1= yes, 0=no), insignificant for both GZ and SH

Binominal Logit Regression: Continued

Most significant variables

GuangzhouB Sig. B Sig.

Housing price 0.029 .001*** 0.015* .000*** Household income -0.084 .003** -0.0185 0.1381Parents' contribution in home purchase (1=yes, 0=no)-0.600 .023* -0.1747 0.5231

Shanghai

Multivariate Analysis: Regression on the Amount Borrowed

Adjusted R Square: 0.824 for GZ model, 0.218 for SH model

Explanatory Variables and Results

Socio-economic: Age, Work unit type, Occupation status, Education attainment, Household registration, all insignificant for both models

Housing attributes: Tenure of last home, insignificant for both models

B Sig. B Sig.

Age -0.119 0.29 -0.08 0.629

Household Income (in 10,000 yuan) -0.526 .001*** -0.09 0.4919

Housing price (10,000 RMB) 0.734 .000*** 0.18 0.000***

Work unit types

SOEs and collective-owned enterprises (+)

Government Department and Quasi-state Institutions -2.223 0.312 2.65 0.4252

Private Enterprises -1.052 0.58 4.66 0.0671

Foreign Enterprises and Sino-Foreign Enterprises 1.261 0.579 1.34 0.6002

Individually Owned Business -0.08294 0.971

Job Rank

Manual and Service Workers (+)

Clerical and Technical Workers 0.186 0.928 0.74 0.9143

Low Rank Cadres (non university teacher) -1.237 0.561 2.26 0.7408

Middle and High Rank Cadres and Professionals -1.848 0.34 1.95 0.7708

Self-employed 2.05 0.7956

Education Attainment

Primary and Below

Junior Secondary -0.428 0.915

Senior Secondary 0.904 0.808

Tertiary or Above 1.464 0.709 -1.18 0.6307

Ownership of Previous Home (1 = Owned) 2.198 0.095 -0.58 0.7562

HPF Account (1 = Yes, 0 = No) 1.74 0.341 -5.41 0.0538

Parents' Contribution in Home Purchase (1 = Yes, 0 = No) -6.037 .000*** -4.55 0.0432*

Average years of residence in Guangzhou -0.0881 0.139

(Constant) 7.108 0.19 18.27 0.0777

Adjusted R Square

F

N

0.824 0.218

4.404***

154

30.803***

110

Regression on the Amount borrowed: continuedMost Significant Variables

B Sig. B Sig.Household income(RMB 10,000)

-0.526 .001*** -0.089 0.492

Housing price(RMB 10,000)

0.734 .000*** 0.176 0.000***

Parents’contribution inhome purchase(1=yes, 0=no)

-6.037 .000*** -4.552 0.043*

HPF Account (1 =Yes, 0 = No)

1.740 0.341 -5.412 0.054

VariableGuangzhou Shanghai

Concluding Remarks

Both similarities and differences are found regarding the use of mortgage loans in Shanghai and Guangzhou

In both cities, government or quasi-state institution employees are less likely to employ mortgage loan, whilst private sector workers are more likely to use mortgage loans

Also in both cities, mortgage loan users are those ones less likely to receive parents’ contribution in home purchase

Shanghai loan users compared with non loan users: younger, higher income earners, with higher occupation status, and more educated. In this respect the Shanghai case is more similar to the West;

However, in Guangzhou the higher income persons are less likely to resort to mortgage finance, suggesting that in this city if possible people are reluctant to borrow.

Concluding Remarks

In determining whether and how much to borrow mortgage loan:

Parental contributions reduce both the possibility of borrowing mortgage loan and the amount borrowed

Rising housing price on the other hand increases the possibility of borrowing and the amount borrowed

Suggesting that increasingly mortgage finance has become a need for entering homeownership