Download - Si-ming Li
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