(Luận văn thạc sĩ) an analysis of housing credit program for urban hoausehold case study in HCMC housing development bank(HDBANK)

INSTITUTE OF SOCIAL STUDIES
THE HAGUE
THE NETHERLANDS

UNIVERSITY OF ECONOMICS
HO CHI MINH CITY
VIETNAM

=======oOo=======
VIETNAM- NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

AN ANALYSIS OF HOUSING CREDIT PROGRAM FOR ·
URBAN HOUSEHOLD
CASE STUDY IN HCMC HOUSING DEVELOPMENT
BANK (HDBANK)
BQ GIAO D~C E>AO Tl;\0
TRUONG Dl;\1 H9C KINH TE TP.HCM

THUVIEN
•
1
A THESIS PRESENTED BY

DOHONGNGOC

IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE
DEGREE OF MASTER OF ARTS IN DEVELOPMENT ECONOMICS

SUPERVISOR

DR. TRAN TIEN KHAI
Ho Chi Minh City, February 2009


CERTIFICATION

"I certify that the substance of this study has not already been submitted for any
degree and is not being currently submitted for any other degree.
I certify that to the best of my knowledge any help received in preparing this thesis,
and all sources used, have been acknowledged in this dissertation."
Ho Chi Minh City, February 2009

Do HongNgoc

i


ACKNOWLEDGEMENT

i would like to express deeply my appreciation and many thanks to the following
individuals and organization helped me to finish this thesis.

Doctor Tran Tien Khai, the academic supervisor who has spent much time to give me his
guides, comments, assistance in this research.

All lecturer and staff of Viet Nam-Netherland master program which is helpful program
. for me to obtain the knowledge and the method of science studying with international
standard.

All my classmates, especiaily my group have encouragement, cooperation and help

during my stUdying and doing the thesis.

All ofmy family members have help and encouragement for me to try my best to finish
this research.

ii


ABSTRACT

VietNam is going on the way of modernization, industrialization and especially of
globalization with the purpose of economic development and enhancing the life standard
of the resident. This implies· to· increase further with a rise in the urbanization levels and
in the population along with increasing the demand for housing in urban of VietNam. To
. solve the d~mand of urban household, the government has many policies to support the
resident such as housing finance system from bank or other financial institution, housing
program for low inconie .. : This study only concentrates to analysis housing credit
program from bank for urban household on two major aspects. The first is the
determinants of probability to get a housing loan. And the second is the determinants of
housing loan amount. SO the household should improve their character and capacity to be
able to borrow housing loan from bank. Conversely, the bank also should have-suitable
. credit policy and condition for the customer to speed up effective and sustainable credit
development.

iii


TABLES OF CONTENTS
.·fi .
.

C ertl 1cat1on. ··················~····· ........................................................................................................... 1
Acknowledgement .................. :.................................................................................................. ii
Abstract ..................................................................................................................................... iii
Contents ........................................................................... :······· ................................................... .iv
List of tables and figures .......................................................................................................... viii
··Abbreviation .............................................................................................................................. ix

CHAPTER I·: INTRODUCTION .•...................·.................................................. ~ .................... !
.

.

1.1 Prob-em statement.. ~········································································································· I
1.2 Objectives ofihe stlldy ..~ ................................................................................................. l

1.2.1 General objective ........................... ~ ............................................................................. 2
1.2.2 Specific objective ....................................................................................................... 2

· 1.3 Research questions ...... ~·~··············································•···················································2
·1.4 SuJi:J.macy on rese8.rch· methQdology- and data ..............•............................................... 2

1.5 ·The organization of the thCsis ···~····················································································3
CHAPTER II: LITERATURE REVIEW ............................................................................... 4

2..1 TheOry ba~kground ......................................................................................................... 4
2.1.1 Major concepts ........................................................................................................... 4
Household
Credit
Borrowing
Household credit market

2.1.2 Banking theory ............·............................................................................................... 4
Credit management
Credit analysis and loan decision
. Issues in credit market
2.2' Experiences of housing development in some Asian countries ••..•.......••....... ;............. 7
2.2.1 In Singapore .... ;..................................................................................................... ,........8
2.2.2 In China .............................................................................................. ,....................... 9
2.2.3 In Thailand .................................................................................................................. 10

iv


2.2.4 In Korea .................................................................................................................... 11

2.3 Theoretical models and empirical studies for house demand ................................... 12
2.3.1 General observations ................................................................................................ 12
2.3.2 Determinants ofhousingloan.-.................................................................................. 13
2.3.3.Determinants of loan amount ................................................................................... 15
2.3.4 Theoretical models ................................................................................................... 16
The basic models ...................................................................................................... 16
:The extended models ........................ ;....................................................................... 16
2.3 .5 Empirical models applied in previous studies .......................................................... 17

CHAPTER III: RESEARCH METHODOLOGV............................................................... 20

·3·.1 AnalyticiJJ· framework ········~······················•·····································································20
3.1.1 Hypotheses .................... ,.......................................................................................... 20
3.1.2Detenninants ofthe probability ................................................................................ 20

3, 1.3 Determinants of loan amount ....................................................................................• 21

3.1·.4 Specific empirical models ......•................................................................................. 22
Model1 ....... _............................................................................................................... 22
Description of the model1 ....................................................................................... 22
Definition and explanation of variables of the model 1 ........................................... 22
Expected signs of the variables' coefficients ........................................................... 23
Model2 ..................................................................................................................... 24
Description of the model 2 ................. ,....................•.................................... ;............ 24
·Definition and explanation of variables of the model2 ........................................... 24
Expected signs of the variables' coefficients ........................................................... 25

3.2 Data source· aild sa~pling............................................................................................. 26
3.2.1 Data source ............................................................................................................... 26
Where is data source? ... :........................................................................................... 26
. Its
. va•I..d.Ity?....................._.............................................................................. . 26
.What-Is
When are they collected? ......................................................................................... 26
. Population .. :.... :........ ;................................................................................................ 26
3.2.2 Sampling ..........................................................................................................•......... 27

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.sample size ............................................................................................................... 27
Sampling method ....................................................................................................... 27

3.3 Analysi-s methods ······~····································································································29
3.3 .!Statistical tests for descriptive analysis ..................................................................... 29
3.3 .2 Correlation analysis .................................................................................................. 29
3.3.3 Statistical tests for validity of specific models ......................................................... 30

.

.

.

.

3.4 Analysis· too1 ........_...................................... ~ .................................................................... 30

CHAPTER IV: ~SU~TS AND DISCUSSION ....................... ,.......................................... 31

. 4.1 Situation ofhousingcreditprogram for urban household in Ho Chi Minh City ... 31
4.1.1 Housing demand of urban household ....... :............................................................... 31
4.1.2 National strategy on housing up to the year 2010 .................................................... 31
4.1.3 The overview of urban finaricial system, borrowing by urban households and
.housing finance project. ...................................................................................................... 32
Financial system and source of credit to urban households in VietNam ................ 32
Overview ofborrowing by urban households .......................................................... 32 ·
4.1.4 HCMC Housing development program .................................................................... 35

4.2 IiCMC Housing D-evelopment Bank ·························~······-············································35
·4~2.l.Overview

ofHDBank ............................................................................................... 35

4.2.2 Housing credit program ofHDBank ........................................................................ 38

4.3 HCMC ·aousing D.eveloprri.ent Bank ·····································································~·····40
.4J~1Analysis

ofborrower' characteristics ....................................................................... .40

4.3.2 Correlation.analysis ................................................................................................... 44
4.3.3 Statistical tests for validity of specific models ........................................................ .47
4.3 .4 Description collecting data and choosing suitable method ..................................... .48

·4.4 .Results ·of ~odels

~esting

and explanation .................................................................. 49

4.4.1 ·:Empirical result- Model I .................... ;.................................................................. 49
4.4.1.1 Enter method ................................................... ;............................................ 49
4.4.1.2 Backward LR method ............................... :........................... ;........ ;· .............. 50

vi


4.4.1.3 Analysis the factor affect to the probability to get housing loan for
household .................... :...................................................................................................... 50
4.4~2 Empiricalresult- Mod.el2 ............ :.......................................................................... 54

4.4.2.1 Enter method ................................................................................................ 54
4.4.2.2 Backward LR method .................................................................................... 54
4.4.2.3 Analysis the factor affectto the probability to get housing loan for
household ............................................................................................... ,.................. 54

CHAPTER V: CONCLUSION AND IMPLICATION ....................................................... 58

5.1 Conclusion on the applied methodology and limitation ....•..•....•.••.•.•..•.........••.......... 58
5.2Conclusi0n On the studie.d results ................................................................................. 58
5.3 Po.licy impli~ation in. macro levCI ................•................................................................ 59

5.4 Policy implication for HDBank as well as housing credit program •...•..••.........••..... 59
References

Annex

vii


LIST OF TABLES .
Table 1.1: Compare mean of variable
Table 1.2: Correlation Matrix
Table L3: Durbin:_ Watson in model!
Tahie 1.4: Durbin- Watson in model 2
Table 1.5: Regression result of model 1 from step 1 to step 6 by back ward method
Table 1.6: Regression result ofmodel2 froni stepl to step 6 by back ward method

LIST OF FIGURES
Figure 2.1: Structure ofprobability to get housing loan
Figure 2.2: Structure of samples possibility to get a housing loan
Figure 2.3: Growth oftotal assets and chartered capital in HDBank
Figure 2.4: Growth ofloan outstanding debts in HDBank
Figure 2.5: Outstanding ofhousing credit program and total loan outstanding in
HDBank
Figure 2.6: Regression standardized residual

LIST OF ANNEXS:

Annex 1: T-Test result
Annex 2: The result of model 1- Enter method
Annex3: The resultofmodell- Backward method
Annex 4:Theresult ofniodel2- Enter method
Annex 5: The result ofmodel2- Backward method

viii


·ABBREVIATION

HDBank: Housing Development Bank
ADB: Asian Development Bank
SBV: State Bank of VietNam
SOB: State Owned Bank
· DLH: Department of Land and House

ix


CHAPTER 1: INTRODUCTION

1.1 Problem statement

The world is flat on all fields by globalization, information technology development
especially in the economic field. Viet Nam also follows this tendency by joining
econoinic organizations in area as well as in the world such as AFTA, WTO ...
Economic development and reforms in the sector has brought increased urbanization.
Urban population is expected to increase further with a rise in the urbanization levels
and in the population. In a research of JBIC (1999) stated that VietNam has been

experiencing rapid urbanization owing to economic development after the Doi Moi
policy, and urban population is predicted to increase to 46 million in 2025 from 15
millionin 1995,
· Urban development and housing sector, especially in Hanoi and HCMC, is urgently
challenged by swelling migration from rural· areas, expanding informal settlement,
emerging .relocation needs by inner-city redevelopment, accelerating reform of SOEs
that provided their employees with houses. This implies demand for housing would
increase at a faster pace in urban VietNam in the short term to medium _term.

To solve urban development and housing problem for the resident, Viet Nam is
learning valuable lessons from other country's different models of housing
development. Vietnamese authorities clearly organized and exposed a particular plan
such as urban development policy, real estate institution, housing development and
housing finance... With· housing finance, the authority specifies two aspects are
municipal housing fund and housing finance facility. In municipal housing fund,
respective "Housing fundl' was establish in the early 1990's in HCMC and in 1998 in
Hanoi; These funds mobilized capitals primarily from the sales revenue of the former
state-owned houses, and are used for housing finance. Another facility named HIFU
was set up in HCMC in 1997. HIFU mobilizes capitals from bank loans, equity and
trust fund entrusted by the People's Committee, and it invests in urban development
including housing projects of the public developers. Besides that, housing loan
activities are chiefly supplied by state-owned commercial bank, private joint-stock
bank, municipal fund ...
This study just concentrates to analyze housing finance especially housing credit
program for household. In real, a large of the urban population lacks access to
affordable finance for housing construction or improvement, so they have to resort to
informal sources such as moneylenders, friends, relatives and credit associations ... So
investigating the determinants of access to credit and the determinants of loan amount

1

help household and· bank have change to quickly find the common result. It means
that the household satisfy bank's·loan condition to get the housing loan and the bank
has housing creditto the customer safely and effectively.
Another further issue concerns this study is the housing finance project will set up a
facility to provide mortgages and loans for urban low-income and poor people to
improve their property or build or buy new homes. It will also promote institutional
strengthening and capacity building to develop VietNam's housing finance system.

1.2 Research objectives.

1.2.1 General objective
Analysis of housing credit program for urban households by analysis the
probability of credit for household and. the deteirninants affeCt to loaiiamomil
1.2.2 Specific objective
. , The demand of house and housing system in urban VietNam.
--

- The demand of housing loan of urban household.
- The_ ~eterminants of housing credit program for urban household including·
probability of credit and loan value.
- The research analyzes the relationship between urban households and credit
market to find -out relation of characteristics and endowment of urban
households and characteristics of loan to chance to borrow, loan amount.
"' Enrich our knowledge on credit market and borrowing by household in Viet
Nam, particularly in housing credit program.
- The effective of the housing finance project to the low-income and poor
· people artd contribute the economic growth in VietNam.
- In addition, housing finance project do strengthen and capacity building to

develop VietNam's housing finance system.

1.3 Research Questions
_ How is the housing demand of urban household?
.What are the determinants of housing credit program for urban household?
How does the credit especially housing credit program contribute the economic
development and economic growth?

2


1.4 Summary on research methodology and data

The method is used, including statistical and descriptive analysis, review of historical
·trends, and·. comparative methods. Apart form, quantitative method is extensively
used;
Data is used in the analysis from the core banking of HCMC Housing Development
Banlc

1.5 Strcuture of the thesis

The thesis consists of five chapters, following chapter 1, the rest of the structure as
follow:
. Chapter 2: Literature review
Chapter 3: Research.methodology
Chapter 4: Result arid discussion
Chapter 5: ·Conclusion and Implication

3

CHAPTER II: LITERATURE REVIEW

2.1 Theory background

·. 2.1.1 Major concepts
Household is area of concern in social science. Concept of household is defined and
discussed by economists, feminists and anthropologists. Ringen (1991) defines of
household that as is a group of at least two people pools their incomes and uses income
collectively.. In house holds, income is not split up.between household members for each
to use his or her · share, at least not all of it. In large .measure, household members
cooperate on the use of income and thereby get more out of their income than they could
if each had been on his or her own .. However, there is much controversy over the
boundary of this definition. Generally, economists view household as an essential unit of
analysis and develop theory based on modeling behavior of household. There are two
themes of economi~ model of household behavior. The first treats consumption and
produce separately or simultaneously in an integrated model. The second emphasizes on
market condition, and relationship between household and market for land, labor, and
credit.
Credit is the trade of money, goods or services at the present time for a payment in the
future. Credit can be provided in many different forms and under a wide variety of
. arrangements (Kinnon Scott, 2000)
Borrowing is one side of credit. In general, borrowing is defined as that to be transferred
property right on a given object (e.g. sum of money) in exchange for implementing
. obligation of a claim on specified object (e.g. a certain sum of money) at specified point
of time in the future .. In extension of this definition, borrowing by households,
particularly Urban household is defined as activities of households to obtain external
resources to support other household activities with obligation to repay in future. In other
way, borrowing is made by household to finance household's budget deficit.
Housing credit market the presence of heterogeneity among different household induces

to situation whereby households fall into
budget deficit while some others are in budget
.
surplus. Therefore, the deficit households desire to borrow in order to cover their deficit
while surplus households also desire to lend out for their interest. Consequently,
. household credit market is established to facilitate borrowing and lending of households.
Credit. market function is to transfer
purchasing power from surplus households to deficit
.
. ones by issuing and acquiring of money-denominated debt.
.

.

.

. 2.1.2 Banking theory

Credit management: how to determine the creditworthiness?

4


In credit scoring method, the creditworthiness can be measured by the values basing on
the characteristics. However, there are some core factors that are usually used in credit
management (Kapoor, Dlabay, Hughes, 2001). They are:
Characte~:

the borrower's attitude toward his or her credit obligations.

Capacity: the borrower's financial ability to meet credit obligations.
Capital: the borrower's assets or net wealth.
Collateral: a valuable asset that is pledged to ensure loan payments.
Conditions: the general economic conditions that can affect a borrower's ability to
repay a loan. ··
Access to credit in this research can be understood as two components:
The probability to get credit from bank for household.
In case of the household can get the loan, the size of the loan is also one
compop.enf in access to credit.
Credit analysis and Loan decision
Purpose of credit analysis:

Credit analysis is a process of collecting information, analyzing information with
sciences method for the aim to understand clear about clients and their business projects,
serving process of short-term loan decision. Credit analysis is an important step with the
purpose using to make loan decision: accept or reject issuing credit. In order to make
credit decision banks must do three steps following:
Collecting sufficient & accurate information.
Analyzing and processing data collected.
Predicting ability of repaying seed and interest of household.
By credit analysis, banks can replace their experiences about household and their project
applied for loan with scientifically argument and evidences rely on information and· data
processing. Therefore,· credit analysis help banks avoiding two types of mistake: (1) give
credi(for bad client, (2) and rejecting the good one.
Information usingfor credit analysis

Collecting good information is. initial necessary when carry out credit analysis;
·quaiification of data analyzed have significant effected to result, by this, it is effected to
loan decision, the quality of data is noticed with three attributions: (1) sufficiency, (2)
timely, (3) accurately.

5


Analysis contents: analysis should be targeted evaluation of capacity repaying loan that
mean, it evaluate whether customer can repay seed money and interest or not. To
·appreciate repayment capacity of company, we have to determined factors effecting to
customer's repaying-debt capacity. In other hand, credit analysis contents should be
concentrated into analyze factors effecting to ability to meet obligation. Basically, ability
of repayingloan is influenced by:
Finance situation.
Practicability and effectiveness of projects.
Customer's attitude to refund debt.
Issues in credit market
.- .Chung (2000). Credit rationing is a condition of loan market in which the lender
supply of fund is less than borrower demand at the quoted contract term. In other
words, it means that there is excess demand. In credit market, credit rationing
appears to be an inefficient situation of credit market, where interest rate does not
work well to balance supply and demand sides.
There are two major ways to explore causes of credit rationing. Firstly, traditional
. view:s consider credit rationing resulted from government interventions on credit
market by imposing interest rate ceiling on lending institutions. Interest rate is
exogenously held under market clearing leveL With interest rate keep artificially
low, some poteritialborrowers
who want to borrow are rationed. Secondly, after
.
..
the demise of the traditional theories, a new approach to credit rationing was
developed. The new approach argued that permanent credit rationing is
considered as an equilibrium phenomenon rather than a temporary phenomenon.

. Modem theories identify problems of moral hazard and adverse selection in credit
market as a source of credit rationing when information is distributed
. asynimetrically among market participants.
.

Fragmentation of credit market strongly affects the borrowing· behaviors of urban
households. Fragmentation of credit market, firstly, is thought as a consequence
of the repressive government policy. Ceiling rate on deposit and loan rate
imposed by central bank induces to severe credit rationing in formal financial
sector. Resulting from inter-linkage between formal and informal financial
markets the.unsatisfied demand of households for formal loan flows into informal
financial sector and put demand for informal loans to rise up. Secondly, it is
viewed that fragmentation of household credit market is caused. by structural and
institutional features of credit market in developing countries. In addition,
fragmentation of credit market may also result from weakness in the infrastructure

6


that supports the financial system. Thirdly, another perspective on fragmentation
of credit market argues that formal and informal financial sectors are parallel
developed because they serve different segments of credit market.
In conclusion, under perfect credit market, borrowing, along with saving, allows
urban households to maximize their utility overtime. Resources or endowments,
incomes, and activities of households determine the demand for loan. The effects
of those factors on the demand of urban households for credit are called "demand
side effectsi'. On the other hand, credit market conditions and relationship
between urban households and financial intermediaries affect borrowing by urban
households. If credit market is inefficient; some of potential household borrowers
fail to access to credit market. Therefore, severity of credit rationing is an

explanation for credit constraint of urban households; and high fragmentation of
credit market is an explanation for various borrowing behaviors of urban
households. Borrowing by urban households is substantially determined by
condition of credit market so called "supply side effects". Thus, borrowing by
urban households is jointly affected by both demand and supply side factors.
2.2 Experiences of housing development in some Asian countries:
As with Latin America and Africa, the number of urban residents is fast .expanding in
Asia. Asia is also home to the largest concentration of poor people in the world
(Chapman et al, 1999; Montgomery et al, 2001). About a quarter of the total urban
population in Asia is living below the poverty line although the proportion may be higher
in some countries. India and China· each holds about a third of the region's urban
population with many living in relative poverty. (Jacquemin, 1999). Of the 12 million
people in Mumbai, for example, about 50 per cent lives in slums, dilapidated houses and
.on pavements. In the extreme, they join the number of homeless people, estimated to be
in excess of 100 million in the world (UNCHS, 1999). In one recent estimate, Asia alone
will need to Invest a sum of US$280 billion a year over the next 30 years to meet the
basic needs · of the population in housing and other urban sectors (Brockman and
Williams, 1998).
.

·

.

T~e

lack of housing access is one of the most serious and widespread consequences and
causes .of poverty ili Asian cities. The· improvements in housing that are important to
improving the quality of life ·among the poor often does not receive the attention they
· deserve from policy makers (Daniere, 1996). To make any appreciable improvement,

substantial government spending is needed, both in the physical expansion of the city's
infrastructure and implementation of poverty alleviation programs. Buttressed by the
. heritage of literature that argues the importance of affordable and improved housing in

7


· urban poverty reduction (see, for example, Mitlin, 2001), the immediate research issue is
how poor families can access urban shelter more affordably.
·
Experience for VietNam from other countries in Asian as follow:
2.2.1 In Singapore
.The Singapore public housing development has attracted keen research interest (see, for
example, Wong and Yeh, 1985; Yuen et al, 1999) but few have clarified the public
housing-urban poverty nexus. This provides the starting point for the present analysis of
the performance of housing development.
· Follow by Global urban development magazine in Singapore (GUDS, 11/2007), in a
fundamental perspective, without parallel economic development, the housing
improvements would not have advanced so dramatically. Deliberate action was taken to
. diversify the economy and provide employment in Singapore. With economic growth, the
nominal household income had increased. Real GDP had grown at an average of 8.6%
per year over the 30-year period from 1965 to 1999. This had fuelled growth in real per
capita GDP from S$4000 in 1965 to S$32,000 in 1999 (while inflation remained low,
around 2 to 3% per year). At the household level, the average monthly household income
increased. As Ng and Yap (2001} illustrated, from 1988 to 1998, average monthly
household income. had increased by 6. 7% per year, leading to higher asset ownership.
The proportion of homeownership public flats expanded from 26 per cent in 1970 to 92 per
cent ofthe housirig stock by 1999.
Although the financing of public housing draws from the general background of the
country's economic progress,· Singapore's experience also demonstrates the employmentgeneration potential of this sector. By 2000, the HDB (Housing Development Board of

· Singapore was established in the beginning of year 1960) in providing a total housing
environment forallwho lack has initiated the construction of more than 850,000 dwelling
units, 19,500 commercial premises, 12,800 industrial premises, more than 1460 schools
and community facilities, 45 parks, 17;347 markets/hawker centers, and numerous car
parks. The construction of these facilities while providing improved housing and better
quality of life for the poor has created construction jobs and has· a high multiplier effect.
Reflecting on the economic impact, some housing scholars such as Sandilands (1992)
have described the construction sector as a leading sector since its growth rates are above
the rate of growth of overall GDP. Others have written about the pump priming effect of
public sector housing construction (see Krause et al, 1987).
As with many other cities, Singapore's quest to provide its poor residents with good
living environment is not new. Adequate shelter with the promise of a decent life of
dignity, good health, safety, happiness and hope is one theme that has been repeated
internationally and enshrined in successive United Nations declarations (see, for example,

8


UNCHS, 1998; 1999; World Bank, 1993). The Singapore development expenence,
however; shows thatpublic housing (even: high-rise) for the lower income families need
not degenerate irito polarized and marginal environments. Nonetheless, the reemergence
of the homeless underscores the urgency for further research. In particular, the trend
towards taller housing presents challenges The poor of Singapore do not have the
alternative to opt out of this housing. In this regard, we are reminded of Mitlin's (2001,
p512) exhortation to understand and follow the realities of the poor in the continuing
effort to create affordable housing that seek to address their diverse needs.
In sumrilary, Singapore's system of housing development with a single empowered
authority responsible for housing delivery may not be the model for all countries, but
effective pragmatic management principles (such as inclusive housing and widening
homeownership opportunity for lower-income families, directed assistance for lowincome· renter households and continual review of housing access) apply in most

contexts. There is a growing literature that emphasizes a comprehensive approach to
housing. Similar to situation of China and Thailand or other Asian countries, VietNam
can get the most suitable lessons for housing market and policy in the way of economic
development.

. 2.2.2 In China
China's housing market and policy context are relatively unique, differing from those of
the urope and the US, including the post-Communist countries (Wang and Murie 1999,
·Naughton 1994). This section therefore review China's homeownership-oriented housing
polices. In this section and throughout the paper the discussion focuses on urban housing
·policy olily be.cause. of the different rules and institutional arrangement governing
. housing hi rural and urban areas.

. Privatization
As economic· reforms deepened in the 1990s China's policymakers sought to privatize
much of the publicly-owned housing stock that had been previously rented from the state
or state-owned enterprises (SOEs). In doing so the government was motivated by a
number of factors, foremost of which was the fact that maintenance cost levels ran well
above the nominal rents paid by tenants; Zhang (2003) cites figures indicating that as of
.1991 rent on government-owned housing averaged 0.13 ¥/m2 of living space (enterpriseowned housing was even cheaper) while upkeep expenses averaged 2.31 ¥/m2. Under
·these conditions housing costs accounted for only 1 percent of the average worker's
earnings.
Inl994 the Housing Reform Steering Group of the State Council unveiled several

9


reforms designed to encourage the development of housing markets. Liu, Park, and
Zheng's (2002) analysis of the relationship between housing investment and economic
growth found significant positive relationships over both the short and long runs: another

important policy motivation for spurring development of housing markets.
Housing Provident Fund

The Housing Provident Fund (HPF) was designed in 1992 to help wean employees from
workplace housing provision. As such, it was paired with reform of the salary system.
Instead of providing housing directly and paying employees a correspondingly lower
. salary, the progranfs goal was to enlist public sector employees in the development of
the coriunercialliousing market by raising their incomes but siphoning the increase into
savings accounts dedicated to housing~ while reducing their in-kind housing benefit,
thereby encouraging them to find housing in the marketplace (Wang 2001). The reform
was part of a more general effort to have individuals and markets replace government and
.work units as the entities responsible for housing finance (Lee 2000). Because employer
participation is not mandatory in the private sector, the primary HPF beneficiaries are
government, party, SOE, and other public sector workers, although some private firms
and foreign joint ventures also match employee contributions.
In a recent overview of China's housing policy, Sun (2004) criticizes the targeting of the
HPF system. This is. reinforced by the fact that even most working lower-income
households are not in the kind of official, full-time, and typically public sector positions
likely to carry an HPF benefit. ·
Affordable Housing

The other principal homeownership-oriented public policy is the development of
'affordable housing' (Jingji Shiyong Fang or 'economic and comfortable housing'). The
policy is designed for lower-middle- and middle-income urban residents and involves
·government subsidies and profit caps for developers.
2.2.3 In Thailand
.In May 2005, Veerachai Veerametheekul, Vice Minister of Finance, Khan Prachuabmob,
President of· Government Housing Bank, Pomsak Boonyodom, National Housing
Authority Governor; Kitti Pattanapongpiboon, President of Housing Loan Association
and Ballobh K.rittayanawat of the Government Housing Bank, represented Thailand at the

"More Than Shelter: Housing as an Instrument of Economic and Social Development",
an international conference organized by Harvard University's Joint Center for Housing
Studies (JCHS) in Bellagio, Italy. Important leaders from four other countries, including
· the USA, Mexico, South Africa and :kenya also attended the conference. After the
conference, the participants from five countries endorsed the "Bellagio Housing

10


Declaration" affirming that sound, sanitary and affordable housing for everyone is central
to the well-being of nations. It also reaffirmed that housing is more than shelter; it is a
powerful engine that creates opportunity and economic growth. Several other principles
. were also promulgated:
(a) Housing as a sustained national priority: Housing is a long.; term process that requires
a stable policy framework and national priority attention.
(b) Housing as an engine of social and economic development: Housing · brings
significant benefits in terms of employment creation, domestic capital mobilization and
social wellbeing in the face. of the major challenges posed by.population growth and
urbanization. (See seminar details and Bellagio Housing Declaration in GHB Newsletter,
41st edition, 2005) The conclusions from this most important conference indicated that
many countries recognized that housing is more than shelter. It is one of life's essentials
and a process or engine of economic and social development. The Government should
give a high..:priorityfor establishing a long-term housing policy and strategy..
2.2.4 In Korea
.

.

. In 1962, Korea Nation Housing Corporation (KNHC) was established with the mission of
improving the public living standards and welfare through ·housing construction and

urban redevelopment.
KNHC is a 100 percent state-owned· company. Due to its strong links with the
government, it has been provided direct funding assistance by the government in the form
. of equity contributions and loans from the National Housing Fund.
· KNHC's organization consists of Main Office with 20 Divisions under 4 Head Divisions
and 1 Research Institute, 2 Regional Head Divisions in Seoul and Gyeonggi,and 10
Branch Offices in other major cities .
A total of 3,076 ·employees is working at KNHC, including 7 executives, 844
administrative officials (27%), 1,721 engineering officials (56%) and 504 researchers and
clerks (17%) .
.As of the end of 2001, assets amol:mt to 14,374 billion won, liabilities to 9,301 billion
won, capital to 5,073 billion won. Its sales are up to 3,274 billion won.
However, the liabilities, the accrued interest of which should be paid by KNHC, are only
2,254 billion won oftotal9,301 billion won.
Temmts andhousing buyers will pay the interest expenses of the rest (7,047 billion won)
.which chiefly comes.from National Housing Funds.
The National Corporation Realizing Urban Development and Housing Welfare Korea
National Housing Corporation (KNHC) has focused on the massive construction of

11


housing unit for national housing stabilization uritil now, but will begin to lay strong
emphasis on the improvement of quality to comply with the change of life from now.
KNHC will be reborn as a future-oriented corporation with higher additive value to
realize urban development and housing welfare.
· Moody's said ·such a track record of government assistance and the possibility that
government will continue to provide financial help ensures KNHC's financial viability
and operational soundness. (website of GOLIATH -Business knowledge on demand).
Any future changes in rating would occur if the country's sovereign rating is changed, it

said.· Downward pressure tnay occur if the government's fiscal condition weakens, or if
the corporation is privatized.
Rival ratings agency· Standard & Poors (S&P) also gave the corporation a foreign.currency credit rating of "A minus" and a domestic-currency rating of "A." S&P's outlook
for the corporation's credit rating is "stable."
The credit rating reflects the corporation's firm status in the South Korean housing market
.and its housing projects for the country's low-income people.
· 2.3 Theoretical models and empirical literature for housing demand
. 2.3.1 General observations
Housing loan for household· seem to be available in many countries; including at least
Finland, UK, Japan, Spain, Portugal, Italy, France, Norway, Sweden, US, Australia,
Germany, Belgium, thailand, Philippines; .. This applies especially well to contributions
that consider indebtedness as a problem. It seems to be particularly difficult to find
simulation based analyses on household debt. Instead, descriptive analyses seem to be
more commonplace. There are a few theoretical contributions on household debt. The
permanent income hypothesis, presented by Milton Friedman in 1957, states that people
base consumption on what they consider their 'normal' income even though their
incomes may vary considerably in the short term. Thi~ may create occasional needs to
incur loan. The life cycle approach is .somewhat similar to the permanent income
hypothesis, but it emphasizes the impact ofchanges in wealth on consumption. Neither of
· these approaches focuses on problems related to indebtedness of household. This part
focuses on determinant of housing loan and loan amount caused by household
indebtedness.·
Before going to the literature of housing loan and loan amount, reviewing some literature
of housing .demand and housing credit in some countries help know deeply below
literatures.

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Firstly, there are some theories mentioned the housing demand of household. Housing

demand reflects the household's simultaneous choice of neighborhood, whether to own or
rent the dwelling, and the quantity of housing services demanded. Existing literature with
using a sample ofTampa, Florida household was showed by Carol Rapaport as follows:
Vij

=

V(PHj,tj,PX,Yi,Xi,Zj,ij) .

where P is the price of a unit of housing services in community/tenure choice j, t is the
· statutory Hj j property tax rate, P i~ the price of the composite good that is the numeric, Y
is income, X is a vector of household characteristics that are independent of the choice of
ccirn.inunity/tenure, Z is a j vector of local public goods and other community
·characteristics, and contains unobservable ij characteristics that vary across households
and communities.
Household income and the price of the composite commodity are exogenous. The price
of housing reflects the supply price of housing and any capitalization of the community
mix of public services and tax levels. Pis constant across all in any given j, but differs
across Hj jurisdictionsand across tenure status.
Clus and Ralph (2007) also had research of housing demand. Beyond money, monetary
policy and financial. developments housing markets are certainly also influenced by other
factors, such as taxes, demographics and other developments determining the demand for
· housing. This research also stated the relations between housing loan and housing
demand. Marco Salvi (2007) also presented the model for the demand of housing in the
Greater Zurich area. Besides that, there are just few empirical of housing demand such as
Bajari and Kahn (2002); Ferreira (2004); Bayer, Me Millan, Ruben (2002). All these
papers expose analysis concerned to housing demand. These literatures of housing
demand prove that housing demand is always burning issue in many countries in the
world.

2.32 Determinants of housing loan
There seem to be· hardly ·any theories on determinants of housing loan for household.
Instead, there are numerous empirical analyses on households' debt servicing difficulties.
May and· Tudela (2005) used British data to study which factors determined the
likelihood of .having debt servicing difficulties. · Unemployment, high levels of
indebtedness and a high proportion of non-collateral debt increased the likelihood of
problems. Difficulties seemed to be of permanent nature; paSt problems were a good
predictor offuture problems. There was almost no evidence of housing wealth preventing
difficulties. This might be due to the possibility that many interviewees considered
themselves to be in difficulties if the time schedule of repayments had been renegotiated
with the bank A typical household is certainly unwilling to sell the dwelling in order to

13


· service loans. Hence, the availability of collateral is of limited use in preventing reported
difficulties, even though collateral certainly reduces banks' credit risks.
May and Tudela introduce a new conCeP,t, namely 'debt-at-risk', an indicator of credit
risk. It is simply the sum of household level housing debt multiplied by the household
. · level likelihood of financial distress. If it is possible to identify the determinants of the
likelihood. of distress, and if micro level data are available, it is possible to calculate the
·.. aggregate amoimt of 'debt at risk' and how it would react to changes in the parameters,
such· as income,. age, house value,· house size, etc. The sections after of this paper apply
this concept.
Lh.t and Lee (1997) used various methods to study the determinants of housing loan
defaults in Taiwan. Several factors, including the loan-to-value ratio and the level of
education, seemed to contribute to the occurrence of problems. Problems were
·· particularly commonplace among the youngest.
.Bowie-Cairns and Pryce (2005) found with British data that household debt servicing
ability was an increasing function in the level of education, age and married status.

Families with many children were more likely to have problems. Geographic factors
seem~d to play some role. Partially, Bowie-Cairns and Pryce mention some major
characters effect to the loan payment as follow:
. Number ofchildren in a household and payment difficulties
An increase in the number of children in a household is associated with higher outgoings
and less available finances to repay debt. It is worth exploring their experience of

maintaining payments. However, within each year comparison between households with
different numbers of children confirms that, in most cases, as the number of children
increases the rate of repayment difficulty and arrears increases.
Annual household income and mortgage payment difficulties

One would expect that household income would have a strong relationship with the
probability of household experiencing mortgage arrears .
. Age and mortgage repayment difficulties

In general, one would expect that as an individual gets older, their status, income and
. financial stability will also increase.
.

.

.

Similar to the case in HDBank; the expected result likes result of Bowie-Cairns and
Pryce. The result ofregressimi of this research will be shown details in chapter IV.
As to loans with no collateral, Del-Rio and Young (2005b) concluded that high levels of
debt and factors related to married status and ethnicity were relevant to the occurrence of
problems among British households.

14


In these researches, major variables strongly effect to the probability of housing loan
which are income, age, sex, house value, house size, principal, residential status,
occupation, interest, marital status, credit type, etc. In real condition of Viet Nam and
ability to get the data, the author will choose some variables in the model as sex, age,
education, income, size, house value, maturity, collaterals and loan amount for the
probability to get a housing loan. Banks in Viet Nam usually have housing credit with
common conditions as principal, income, interest, maturity. But in situation of economic
developing and pressure of joining the world economic, commercial bank in Viet Nam
should has more credit program especially housing credit as mentioning with flexible and
diversified condition for many objectives. This research builds a model with many
variables to get meaning . variables and main variables have deeply effect to the
probability to get a housing loan. From the result of this research, commercial bank will
has more housing credit program based on characteristic of the b()rrower_in order to
undertake effectively and successfully.
2.3 .3 Determinants of housing loan amount
There seem to be some empirical regularity that has been corroborated by observations
ina:de in many different countries.
Del-Rio and Young (2005a) concluded that non-collateral loans in Britain were typically
taken by people who were in their twenties, had no children, were relatively well
educated, were employed and had optimistic expectations.
BroW11, Garino, Taylor and Price (2003) found that optimism seemed to strengthen the
demand for rion-collateralloans,.even though after a certain level the degree of optimism
had no impact Factors such as spouse income and savings seemed to have no impact.
Riiser and Vatne {2006) presented observations on Norwegian data from 1986-2003.
Household debt had been. on increase, especially among the youngest households artd
. those with low income. The growth of financial wealth had taken place above all in
households with no debt.

·Magri (2002) studied the occurrence of debt among Italian households. Higher income
strengthen both the ·demand for loans and the availability of credit, whereas being an
entrepreneur strengthened the demand for credit but made it more difficult to obtain
loans.
Brown and Taylor (2005) studied the determination of household financial wealth and
debt in the UK, Germany and the US. There was a clear correlation between financial
wealth and debt. If households with no debt were excluded, the correlation vanished.
Tudela and Young (2005) analyze the detetminants of household balance-sheet in the
UK, applying the hypothesis that· households optimize their income and consumption

15