An analysis of housing credit program for urban hoausehold case study in HCMC housing development bank(HDBANK)

VIETNAM-NETHERLANDSPROGRAMMEF O R M.AINDEVELOPMENTECONOMICSANANALYSISOFHOUSINGCREDITPROGRAMFOR URBANHOUSEHOLD CASESTUDYINHCMCHOUSINGDEVELOPMENTB ANKHDBANK ATHESISPRESENTEDBYDOHONGNGOC IN

VIETNAM-NETHERLANDSPROGRAMMEF O R M.AINDEVELOPMENTECONOMICS

ANANALYSISOFHOUSINGCREDITPROGRAMFOR

URBANHOUSEHOLD CASESTUDYINHCMCHOUSINGDEVELOPMENTB

ANK(HDBANK)

ATHESISPRESENTEDBYDOHONGNGOC

INPARTIALFULFILMENTOFTHEREQUIREMENTFOR THE

DEGREEOFMASTEROFARTSINDEVELOPMENTECONOMICS

SUPERVISOR

“Icertifythatthesubstanceo f thisstudyhasnotalreadyb een s u b mi t t ed f o r anydegreeandisnotbeingcurrentlysubmittedforanyotherdegree

Icertifythattothebestofmyknowledgeanyhelpreceivedinpreparingthisthesis,andallsourcesused,havebeenacknowledgedinthisdissertation.”

HoChiMinhCity,February2009

DoHongNgoc

VietNami s goingo nth e wayo f modernization,i n d u s t r i a l i z a t i o n a n d esp eci

al ly o f globalizationwiththepurposeofeconomicdevelopmentandenhancingthelifestandardoftheresident.ThisimpliestoincreasefurtherwithariseintheurbanizationlevelsandinthepopulationalongwithincreasingthedemandforhousinginurbanofVietNam.Tosolvethedemandofurbanhousehold,thegovernmenthasmanypoliciestosupporttheresidentsuchashousingfinancesystemfrombankorotherfinancialinstitution,housingprogramforlowincome Thisstudyonlyconcentratestoanalysishousingcreditprogramf r o m b a n k f o r u r b a n h o u s e h o l d o n t w o m a j o r a s p e c t s T h

e f i r s t i s t h e determinantsofprobabilitytogetahousingloan.Andthesecondisthedeterminantsofhousingloanamount.Sothehouseholdshouldimprovetheircharacterandcapacitytobeableto‘borrowhousingloa

havesuitablecreditpolicyandconditionforthecustomertospeedupeffectiveandsustainablecreditdevelopment

TABLESO FCONTENTS

Certification , i

Acknowledgement , ii

Abstract iii

Contents i

Listoftablesandfigures viii

Abbreviation ix

CHAPTER‘ I : I N T R O D U C T I O N 1

1.1Problemstatement I 1.2Objectivesofthestudy 1

1.2.1Generalobjective 2

1.2.2Specificobjective 2

1.3Researchq u e s t i o n 1.4 Summaryonresearchmethodology a n d data 2

1.5Theorganizationofthethesis 3

CHAPTERII:LITERATUREREVIEW 4

2.1Theorybac 2.1.1Majorconcepts 4

HouseholdCredit Borrowing Householdc r e d i t market 2.1.2Banking theory ‘ 4

Creditmanagement CreditanalysisandloandecisionIssuesincredit market 2.2ExperiencesofhousingdevelopmentinsomeAsiancountries 7

2.2.1InSingapore 8

2.3Theoreticalmodelsandempiricalstudiesforhousedemand 12

2.3.1Generalob servations 12

2.3.2Determinantsofhousingloan 13

23.3Determinantsofloanamount 15

2.3.4Theoreticalm od e ls 16

Thebasicmodels 16

Theextendedmodels 16

2.3.5Empiricalmodelsappliedinpreviousstudies 17

CHAPTERIII:RESEARCHMETHODOLOGY 20

3.1Analyticalframework 20

3.1.1Hypotheses 20

3.1.2Determinantso f theprobability 20

3.1.3Determinantsofloanamount 21

3.1.4Specificempiricalmode ls 22

Model1 22

DescriptionofthemodelI 22

Definitionandexplanationofvariablesofthemodel1 22

Expectedsignsofthevariables’coefficients 23

Model2 24

Descriptionofthemodel2 , 24

Definitionandexplanationofvariablesofthemodel2 24

Expectedsignsofthevariables’coefficients 25

3.2 Datasource 3.2.1 Datasource 26

Whereisdatasource? 26

Whatisitsva1idip? 26

Whenaretheycollected? 26

Population 26

3.2.2Sampling 27

Samplingmethod 27

3.3 Analysism e t h o d s 29

3.3.1 Stat isticaltestsfordescriptiveanalysis 29

3.3.2 Correlationanalysis 29

3.3.3 Statisticaltestsforvalidityofspecificmodels 30

3.4Analysistool 30

CHAPTERIV:RESULTSAND DISCUSSION , 31

4.1 SituationofhousingcreditprogramforurbanhouseholdinHeChiMinhCity 31

4.1.1Housingdemandofurbanhousehold 31

4.1.2Nationalstrategyonhousinguptotheyear2010 31

4.1.3 Theoverviewofurbanfinancialsystem,borrowingbyurbanhouseholdsand housingf i n a n c e project 32

FinancialsystemandsourceofcredittourbanhouseholdsinVietNam 32

Overviewofborrowingby urbanhouseholds 32

4.1.4 HCMCHousingdevelopmentprogram 35

4.2HCMCHousingDevelopmentBank 35

4.2.1OverviewofHDBank 35

4.2.2 HousingcreditprogramofHDBank 38

4.3HCMCHousingDevelopmentBank 40

4.3.1 Analysis o f borrower’c h a r a c t e r i s t i c s 40

4.3.2 Correlationa n a l y s i s 44

4.3.3 Statisticaltestsforvalidityofspecificmodels 47

4.3.4Descriptioncollectingdataandchoosingsuitablemethod 48

4.4Resultsofmodelstestingandexplanation 49

4.4.1Empiricalresult—ModelI ‘ 49

4.4.1.3 Analysisthefactoraffecttotheprobabilitytogethousingloanforhousehold.

50

4.4:2Empiricalre‘sult—Model2 54

4.4.2.1Entermethod 54

4.4.2.2 BackwardLRmethod 54

4.4.2.3 Analysisthefactoraffecttotheprobabilitytogethousingloanforhousehold 54

CHAPTERV:CONCLUSIONA N D IMPLICATION 58

5.1Conclusionontheappliedmethodologyandlimitation 58

5.2 Co nclusiononthestudiedresults 58

5.3Policyimplicationinmacrolevel 59

5.4PolicyimplicationforHDBankaswellashousingcreditprogram 59

ReferencesAnne

x

DLH:DepartmentofLandandHouse

CHAPTERI : INTRODUCTION

1.1Problems t a t e m e n t

Theworldisflatonallfieldsbyglobalization,informationtechnologydevelopmentespeciallyintheeconomicfield.VietNamalso followsthistendencyb y joiningeconomicorganizationsinareaaswellasintheworldsuchasAFTA,WTO

Economicdevelopmentandreformsinthesectorhasbroughtincreasedurbanization.Urbanpopulationisexpectedtoincreasefurtherwithariseintheurbanization

levelsandinthepopulation.InaresearchofJBIC(1999)statedthatVietNamhasbeenexperiencingr a p i d u r b a n i z a t i o n o w i n g toeconomic d e v e l o p m e n t a f t e r theDoiMoipolicy,a n d urbanpopulation i s predictedt o increaseto46millioni n 2025f r o

m 1 5millionin1995

Urbandevelopmentand housingsector, especiallyi n HanoiandHCMC,is urgentlychallengedb y s w e l l i n g m i g r a t i o n f r o m r u r a l a r e a s , e x p a n d i n g i n f o r m a

l s e t t l e m e n t ,

emergingrelocationneedsbyinner-cityredevelopment,accelerating reformofSOEsthatprovidedt h e i r employees

w it h houses.Thisimpliesdemandf o r housingw o u l d increaseatafasterpaceinurbanVietNamintheshorttermtomediumterm

Tos o l v e u r b a n developmentandh o u s i n g p r o b l e m fort h e r e s i d e n t , V i e t

N a m islearningvaluablelessonsf r o m o t h e r c o u n t r y ’ s differentmodelsofh o u

s i n g development.Vietnameseauthoritiesclearlyorganizedandexposedaparticularplansuchasurband e v e l o p m e n t po li cy , r e a l e s t a t e institution, h o u s i n g d e v

e l o p m e n t a n d housingfinance Withhousingfinance,

theauthorityspecifiestwoaspectsaremunicipalhousingfunda n d h o u s i n g f i n a n

c e f a c i l i t y I n m u n i c i p a l housingf u n d , respective“Housingfund”wasestablishintheearly1990’s

in HCMCandin1998inHanoi.Thesefundsmobilizedcapitalsprimarilyfromthesalesrevenueoftheformerstate-

ownedhouses,andareusedforhousingfinance.AnotherfacilitynamedHIFUwassetupinHCMCin1997.HIFUmobilizescapitalsfrombankloans,equityandtrustfundentrustedbythe

Another furtherissueconcernsthisstudyisthehousingfinanceproject willsetupafacilitytoprovidemortgagesandloansforurbanlow-

incomeandpoorpeopletoimprovetheirpropertyorbuildorbuynewhomes.ItwillalsopromoteinstitutionalstrengtheningandcapacitybuildingtodevelopVietNam'shousingfinancesystem

1.4 Summaryonresearchm e t h o d o l o g y a n d data

Themethodisused,includingstatisticalanddescriptiveanalysis,reviewofhistoricaltrends,andcomparativemethods.Apartform,quantitativemethodisextensivelyused

Creditisthetradeofmoney,goodsorservicesatthepresenttimeforapaymentinthefuture.Creditcanbeprovidedinmanydifferentformsandunderawidevarietyofarrangements( K i n n o n Sc

o t t , 2000)

Borrowingisonesideofcredit.Ingeneral,borrowingisdefinedasthattobetransferredpropertyrightonagivenobject(e.g.sumofmoney)inexchangeforimplementingobligationofaclaimonspecifiedobject(e.g.acertainsumofmoney)atspecifiedpointoft i m e i n t h e f u t u r e I n e x t e n s i o n o f t h i s d e f i n i

t i o n , b o r r o w i n g b y h o u s e h o l d s , particularlyurbanhouseholdisdefinedasactivitiesofhouseholdstoobtainexternalresourcestosupportotherhouseholdactivitieswithobligationtorepayinfuture.Inotherway,borrowingismadebyhouseholdtofinancehousehold'sbudgetdeficit

Housingcreditmarketthepresenceofheterogeneityamongdifferenthouseholdinducestosituationwherebyhouseholdsfallintobudgetdeficitwhilesomeothersareinbudgetsurplus.Therefore,thedeficithouseholdsdesiretoborrowinordertocovertheirdeficitwhilesurplushouseholdsa l

s o desiretolendoutfortheiri n t e r e s t Consequently, householdcreditmarketisestablishedtofacilitateborrowingandlendingofhouseholds.Creditmarketfunctionistotransferpurchasingpowerfromsurplushouseholdstodeficitonesbyissuingandacquiringofmoney-denominateddebt

2.1.2Bankingtheory

Creditmanagement:howtodeterminethecreditworthiness?

4

termloandecision.Creditanalysisisanimportantstepwiththepurposeusingtomakeloandecision:acceptorrejectissuingcredit.Inordertomakecreditdecisionbanksmustdothreestepsfollowing:

- Collectingsu ffi cie nt &accurateinformation

- Analyzingandprocessingdatacollected

- Predictingabilityofrepayingseedandinterestofhousehold

Bycreditanalysis,bankscanreplacetheirexperiencesabouthouseholdandtheirprojectappliedforloanwithscientificallyargumentandevidencesrelyoninformationanddataprocessing.Therefore,creditanalysishelpbanksavoidingtwotypesofmistake:(1)givecreditforbadclient,(2)andrejectingthegoodone

InformationusingforcFeditanalysis

-Analysiscontents:analysisshouldbetargetedevaluationofcapacityrepayingloanthatmean,itevaluatewhethercustomercanrepayseedmoneyandinterestornot.Toappreciaterepaymentcapacityofcompany,wehavetodeterminedfactorseffectingtocustomer’srepaying-

debtcapacity.Inotherhand,creditanalysiscontentsshouldbeconcentratedintoanalyzefactorseffectingtoabilitytomeetobligation.Basically,abilityofrepayingloanisinfluencedby:

Therearetwomajorwaystoexplorecausesofcreditrationing.Firstly,traditionalviewsconsidercreditrationingresultedfromgovernmentinterventionsoncreditmarketbyimposinginterestrateceilingonlendinginstitutions.Interestrateisexogenouslyheldundermarketclearinglevel.Withinterestratekeepartificiallylow,somepotentialborrowerswhowant

distributedasymmetiicallya m o n g marketparticipants

Fragmentationofcreditmarketstronglyaffectstheborrowingbehaviorsofurbanhouseholds.Fragmentationofcreditmarket,firstly,isthoughtasaconsequenceoftherepressiveg o v e r n m e n t p o l i c y C e i l i n g r a te ondepositan d loanrateimposedbycentralbankinducestoseverecreditrationinginformalfinancialsector.Resultingfrominter-

linkagebetweenformalandinformalfinancialmarketstheunsatisfieddemandofhouseholdsforformalloanflowsintoinformalfinancialsectorandputdemandforinformalloanstoriseup.Secondly, it isviewedthatfragmentationofhouseholdcreditmarketiscausedbystructuralandinstitutionalf e a t u r e s ofcreditmarketi n developingcountries I n addition, fragmentationofcreditmarketmayalsoresultfromweaknessintheinfrastructure

6

sectorsareparalleldevelopedbecausetheyservedifferentsegmentsofcreditmarket

-I n conclusion,underperfectcreditmarket,borrowing,alongwithsaving,allowsurbanhouseholdstomaximizetheirutilityovertime.Resourcesorendowments,incomes,andactivitiesofhouseholdsdeterminethedemand

forloan.Theeffectsofthosefactorsonthedemandofurban

householdsforcreditarecalled"demandsideeffects".Ontheotherhand,c r e d i t marketc o n d i t i o n s a n d relationship betweenurbanhouseholdsandfinancialintermediariesaffectborrowingbyurbanhouseholds.Ifcreditmarketisinefficient,someofpotentialhouseholdborrowersfailtoaccesstocreditmarket.T h e r e f o r e , s e v e r i t y of creditrationingi s anexplanationforcreditconstraintofurban households;andhighfragmentationofcreditm a r k e t i s anexplanation f o r va r i o u s b o r r o w i n g

b e h a v i o r s o f ur ba n households.Borrowingbyurbanhouseholdsissubstantiallydeterminedbyconditionofcreditmarketsocalled"supplysideeffects".Thus,borrowingbyurbanhouseholdsisjointlyaffectedbybothdemandandsupplysidefactors

2.2 ExperiencesofhousingdevelopmentinsomeAsiancountries:

AswithLatinAmericaandAfrica,thenumberofurbanresidentsisfastexpandinginAsia.A s i a i s alsohometothel a r g e s t concentration o f poorpe o p l e i n theworld(Chapmaneta1,1999;Montgomeryeta1,2001).Aboutaquarter

ofthetotalurbanpopulationinAsiaislivingbelowthepovertylinealthoughtheproportionmaybehigherinsomecountries.IndiaandChinaeachholdsaboutathirdoftheregion’surbanpopulationwithmanylivinginrelativepoverty(Jacquemin,1999).Ofthe12millionpeopleinMumbai,forexample,about50percentlivesinslums,dilapidatedhousesandonpavements.Intheextreme,theyjointhenumberofhomelesspeople,estimatedtobeinexcessof100millionintheworld(UNCHS,1999).Inonerecentestimate,AsiaalonewillneedtoinvestasumofUS$280billionayearoverthenext30yearstomeetthebasicneedso f thepopulationi n housinga n d otherurbans e c t o r s (BrockmanandWilliams,1 9 9 8 )

ThelackofhousingaccessisoneofthemostseriousandwidespreadconsequencesandcausesofpovertyinAsiancities.Theimprovementsinhousingthatareimportanttoimprovingthequalityoflifeamongthepooroftendoesnotreceivetheattentiontheydeservefrompolicymakers(Da

niere,1 9 9 6 )

T o makeanyappreciableimprovement,substantialgovernmentspendingisneeded,bothinthephysicalexpansionofthecity’sinfrastructurea ndimplementationo f povertya lleviationprograms.Buttressedbytheheritageofliteraturethatarguestheimportanceofa

ffordableandimprovedhousingin

analysisoftheperformanceo f housingdevelopment.

FollowbyGlobalurbandevelopmentmagazineinSingapore(GUDS,1 1 / 2 0 0 7 ), inafundamentalperspective,withoutparalleleconomicdevelopment,the

housingimprovementswould nothaveadvancedsodramatically.DeliberateactionwastakentodiversifytheeconomyandprovideemploymentinSingapore.Witheconomicgrowth,thenominalhouseholdincomehadincreased.RealGDPhadgrownatanaverageof8.6%peryearoverthe30-

yearperiodfrom1965to1999.ThishadfuelledgrowthinrealpercapitaGDPfromS$4000in1965toS$32,000in1999(whileinflationremainedlow,around2to3%peryear).Atthehouseholdlevel,theaveragemonthlyhouseholdincomeincreased.AsNgandYap(2001)illustrated,from1988to1998,averagemonthlyhouseholdincomehadincreasedby6.7%peryear,leadingtohigherassetownership.Theproportionofhomeownershippublicflatsexpandedfrom26percentin1970to92percentofthehousingstockby1999

Althoughthefinancingofpublichousingdrawsfromthegeneral

generationpotentialofthissector.By2000,theHDB(HousingDevelopmentBoardofSingaporewasestablishedinthebeginningofyear1960)inprovidingatotalhousingenvironmentforallwholackhasinitiatedtheconstructionofmorethan850,000dwellingunits,1‘ 9,500commercialpremises,12,800industrialpremises,morethan1460schoolsandcommunityfacilities,45parks,17,347markets/

backgroundofthecountry’seconomicprogress,Singapore’sexperiencealsodemonstratestheemployment-hawkercenters,andnumerouscarparks.Theconstructionofthesefacilitieswhileprovidingimprovedhousingandbetterqualityoflifeforthepoorhascreatedconstructionjobsandhasahighmultipliereffect.Reflectingontheeconomicimpact,somehousingscholarssuchasSandilands(1992)havedescribedtheconstructionsectorasaleadingsectorsinceitsgrowthratesareabovetherateofgrowthofoverallGDP.Othershavewrittenaboutthepumpprimingeffectofpublicsectorhousingconstruction(seeKrauseetal,1987)

Aswithmanyothercities,Singapore’squesttoprovidei t s poorresidentswith go

odlivingenvironmentcisnotnew.Adequateshelterwiththepromiseofadecentlifeofdignity,goodhealth,safety,happinessandhopeisonethemethathasbeenrepeatedinternationallyandenshrinedinsuccessiveUnitedNationsdeclarations(see,forexample,

UNCHS,1 9 9 8 ; 1 9 9 9 ; WorldB a n k , 1 9 9 3 ) TheS i n g a p o r e d ev e l o p me n t e x p

e r i e n c e ,

however,showsthatpublichousing(evenhigh-rise)forthelowerincomefamiliesneednotdegenerateintopolarizedandmarginalenvironments.Nonetheless,thereemergenceofthehomelessunderscorestheurgency

forfurtherresearch.Inparticular,thetrendtowardstallerhousingpresentschallengesThepoorofSingaporedonothavethealternativetooptoutofthishousing.Inthisregard,weareremindedofMitlin’s(2001,p5l2)exhortationtounderstandandfollowtherealitiesofthepoorinthecontinuingefforttocreateaffordablehousingthatseektoaddresstheirdiverseneeds

Insummary,Singapore’ssystemofhousingdevelopmentwithasingleempoweredauthorityresponsibleforhousingdeliverymaynotbethemodelforallcountries,buteffectivepragmaticmanagementprinciples(suchasinclusivehousingandwideninghomeownershipopportunityforlower-

families,directedassistanceforlow-incomerenterhouseholdsa n d continualre vie w ofhousingaccess) apply inmostcontexts.Thereisagrowingliteraturethatemphasizesacomprehensiveapproachtohousing.SimilartosituationofChinaandThailandorotherAsiancountries,VietNamcangetthemostsuitablelessonsforhousingmarketandpolicyinthewayofeconomicdevelopment,

2.2.2InChina

China’shousingmarketandpolicycontextarerelativelyunique,differingfromthoseoftheuropeandtheUS,includingthepost-

Communistcountries (WangandMurie1999,Naughton1994).ThissectionthereforereviewChina

’shomeownership-orientedhousingpolices.Inthissectionandthroughoutthepaperthediscussionfocusesonurbanhousingpolicyonlybe.causeofthedifferentrulesandinstitutionalarrangementgoverninghousinginruralandurbanareas

Privatization

Aseconomic‘reformsdeepenedinthe1990sChina’spolicymakerssoughttoprivatizemuchofthepublicly-ownedhousingstockthathadbeenpreviouslyrentedfromthestateorstate-

ownedenterprises(SOEs).Indoingsothegovernmentwasmotivatedbyanumberoffactors,foremostofwhichwasthefactthatmaintenancecostlevelsranwellabovethenominalrentspaidbytenants.Zhang(2003)citesfiguresindicatingthatasof1991rentongovernment-ownedhousingaveraged0.13Y/

m2oflivingspace(enterprise-ownedhousingwasevencheaper)whileupkeepexpensesaveraged2.31

Y/m2.Undertheseconditionshousingcostsaccountedforonly

reformsdesigned t o encouraget h e development o f housingm a r k e t s L i u , Park,a n dZheng’s(2002)analysisoftherelationshipbetweenhousinginvestmentandeconomicgrowthfoundsignificantpositiverelationshipsoverboththeshortandlongruns:anotherimportantpolicymotivationforspurringdevelopmentofhousingmarkets.

HousingProvidentFund

TheHousingProvidentFund(HPF)wasdesignedin1992tohelpweanemployeesfromworkplacehousingprovision.Assuch,itwaspairedwithreformofthesalarysystem.Insteadofprovidinghousingdirectlyandpayingemployeesacorrespondinglylowersalary,theprogram’sgoalwastoenlistpublicsectoremployeesinthedevelopmentofthecommercialhousingmarketbyraisingtheirincomes

kindhousingbenefit,therebyencouragingthemtofindhousinginthemarketplace(Wang2001).Thereformwaspartofamoregeneralefforttohaveindividualsandmarketsreplacegovernmentandworkunitsastheentitiesresponsibleforhousing

butsiphoningtheincreaseintosavingsaccountsdedicatedtohousing,whilereducingtheirin-finance(Lee2000).Becauseemployerparticipationisnotmandatoryintheprivatesector,theprimaryHPFbeneficiariesaregovernment,party,SOE,andotherpublicsectorworkers,althoughsomeprivatefirmsandforeignjointventuresalsomatchemployeecontributions

InarecentoverviewofChina’shousingpolicy,Sun(2004)criticizesthetargetingoftheHPFsystem.Thisisreinforcedb y thefactthatevenmostworkingl o we r -

Declaration”affirmingthatsound,sanitaryandaffordablehousingforeveryoneiscentraltothewell-beingofnations.Italsoreaffirmedthathousingismorethanshelter;itisapowerfulenginethatcreatesopportunityandeconomicgrowth.Severalotherprincipleswerealsopromulgated:

(a)Housingasasustainednationalpriority:Housingisalong-termprocessthatrequiresastablepolicyframeworkandnational priorityattention

(b)Housinga s a n e n g i n e o f s o c i a l a n d e c o n o m i c d e v e l o p m e n t : H o u s i

n g b r i n g ssignificantbenefitsintermsofemploymentcreation,domesticcapitalmobilizationandsocialwellbeinginthefaceofthemajorchallengesposedbypopulationgrowthandurbanization.(SeeseminardetailsandBellagioHousingDeclarationinGHBNewsletter,41stedition,2005)Theconclusionsfrom

thismostimportantconferenceindicatedthatmanycountriesrecognizedthathousingismorethanshelter.Itisoneoflife’sessentialsandaprocessorengineofeconomicandsocialdevelopment.TheGovernmentshouldgiveahigh-priorityforestablishingalong-termhousingpolicyandstrategy

2.2.4 InKorea

In1962,KoreaNationHousingCorporation(KNHC)wasestablishedwiththemissionofimprovingthepubliclivingstandardsandwelfarethroughhousingconstructionandurbanredevelopment

KNHCi s a 1 0 0 percents t a t e

-o w n e d c -o m p a n y D u e t -o i t s s t r -o n g l i n k s w i t h t h egovernment,ithasbeenprovideddirectfundingassistancebythegovernmentintheformofequitycontributionsandloansfromtheNationalHousingFund

KNHC'sorganizationconsistsofMainOfficewith20Divisionsunder4HeadDivisionsand1 ResearchI n s t i t u t e , 2RegionalH e a d D i v i s i o n s i n SeoulandGyeonggi,and 1 0BranchOfficesinothermajorcities

However,theliabilities,theaccruedinterestofwhichshouldbepaidbyKNHC,areonly2,254billionwonoftotal9,301billionwon

Tenantsand.housingbuyerswillpaytheinterestexpensesoftherest(7,047billionwon)

whichchieflycomesfrom NationalHousingFunds

KNHCwillb ereborna s

Anyfuturechangesinratingwouldoccurifthecountry'ssovereignratingischanged,itsaid.Downwardpressuremay occurifthegovernment'sfiscalconditionweakens,orifthecorporationisprivatized.RivalratingsagencyStandard& Poors(S&P)alsogavethecorporationa foreign-currencycreditratingof"Aminus"andadomestic-

currencyratingof"A."S&P'soutlookforthecorporation'screditratingis"stable."

Thecreditratingreflectsthecorporation'sfirmstatusintheSouthKoreanhousingmarketanditshousingprojectsforthecountry'slow-incomepeople

2.3 Theoreticalmodelsandempiricalliteratureforhousingdemand

2.3.1Generalobservations

Housingloanforhouseholdseemtobeavailableinmanycountries,includingatleastFinland,UK,Japan,Spain,Portugal,Italy,France,Norway,Sweden,US,Australia,Germany,Belgium,Thailand,Philippines Thisappliesespeciallywelltocontributionsthatconsiderindebtednessasaproblem.Itseemstobe

particularlydifficulttofindsimulationbasedanalysesonhouseholddebt.Instead,descriptiveanalysesseemtobemorecommonplace.Thereareafewtheoreticalcontributionsonhouseholddebt.Thepermanentincomehypothesis,presentedbyMiltonFriedmanin1957,statesthatpeoplebaseconsumptiono

n whattheyconsidertheir‘normal’incomeeventhoughtheirincomesmayvaryconsiderablyintheshortterm.Thismaycreateoccasionalneedstoincurloan.Thelifecycleapproachissomewhatsimilartothepermanenti n c o m e hypothesis,butitemphasizestheimpactofchangesinwealthonconsumption.Neitheroftheseapproachesfocusesonproblemsrelatedtoindebtednessofhousehold.Thispartfocuseso n d e t e r m i n a n t o f h o u s i n g l o a n a n d l o a n a m o u n t c

a u s e d b y h o u s e h o l d ‘indebtedness

Beforegoingtotheliteratureofhousingloanandloanamount,reviewingsomeliteratureofhousingdemandandhousingcreditinsomecountrieshelpknowdeeplybelowliteratures

12

rij——r H j , t j , x,Yi,;ri,zj„i;-)

wherePisthepriceofaunitofhousingservicesincommunity/

tenurechoicej,IisthestatutoryHjjpropertytaxrate,Pisthepriceofthecompositegoodthatisthenumeric,Yisincome,Xisavector ofhouseholdcharacteristicsthatareindependentofthechoiceofcommunity/tenure,Zi s a j

vectoro f l o c a l p u b l i c g o o d s a n d o t h e r c o m m u n i t y characteristics,andcontains unobservableijcharacteristicsthatvaryacrosshouseholdsandcommunities

Householdincomeandthepriceofthecompositecommodityareexogenous.Thepriceofhousingreflectsthesupplypriceofhousingandanycapitalizationofthecommunitymixofpublicservicesandtaxlevels.Pisconstantacrossallinanygivenj,butdiffersacrossHjjurisdictionsandacrosstenurestatus

ClusandRalph(2007)alsohadresearchofhousingdemand Beyondmoney,monetarypolicyandfinancialdevelopmentshousingmarketsarecertainlyalsoinfluencedbyotherfactors,suchastaxes,demographicsandotherdevelopmentsdeterminingthedemandforhousing.Thisresearchalsostatedtherelationsbetweenhousingloanandhousingdemand.MarcoSalvi(2007)alsopresentedthemodelforthedemandofhousingintheGreaterZuricharea.Besidesthat,therearejustfewempiricalofhousingdemandsuchasBajariandKahn(2002);Ferreira(2004);Bayer,McMillan,Ruben(2002).Allthesepapersexposeanalysisconcernedtohousingdemand.Theseliteraturesofhousingdemandprovethathousingdemandisalwaysburningissueinmanycountriesintheworld

2.3.2Determinantsofhousingloan

Thereseemtobehardlyanytheoriesondeterminantsofhousingloanforhousehold.Instead,therearenumerousempiricalanalysesonhouseholds’debtservicingdifficulties

Maya n d T u d e l a ( 2 0 0 5 ) u s e d Britishd a t a t o s t u d y w h i c h factorsd e t e r

m i n e d thelikelihoodofh a v i n g d e b t s e r v i c i n g d i f f i c u l t i e s U n e m p l

o y m e n t , highl e v e l s o f indebtednessandahighproportionofnon-collateral

debtincreasedthelikelihoodofproblems.Difficultiesseemedtobeofpermanentnature;pastproblemswereagoodpredictoroffutureproblems.Therewasalmostnoevidenceofhousingwealthpreventingdifficulties.Thismightbedue

difficulties,eventhoughcollateralcertainlyreducesbanks’creditrisks

MayandTudelaintroduceanewconcept,namely‘debt-at-risk’,anindicatorofcreditrisk.Itissimplythesumofhouseholdlevelhousingdebtmultipliedbythehouseholdlevellikelihoodoffinancialdistress.Ifitispossibletoidentifythedeterminantsofthelikelihoodofdistress,andifmicroleveldataareavailable,itispossibletocalculatetheaggregateamountof‘debtatrisk’andhowitwouldreacttochangesintheparameters,suchasincome,age,housevalue,housesize,etc.Thesectionsafterofthispaperapplythisconcept

LiuandLee(1997)usedv ar i o u s methodstostudythedeterminantso f housinglo

an

defaultsinTaiwan.Severalfactors,includingtheloan-to-valueratioandthelevelofeducation,s e e m e d t o c o n t r i b u t e t o t h e o c c u r r e n c e o

f p r o b l e m s P r o b l e m s w e r e particularlyc o m m o n p l a c e a m o n g theyoungest.Bowie-

CairnsandPryce(2005)foundwithBritishdatathathouseholddebtservicingabilitywasanincreasingfunctioninthelevelofeducation,ageandmarriedstatus.Familieswithmanychildrenweremorelikelytohaveproblems.Geographicfactorsseemedtoplaysomerole.Partially,Bowie-

CairnsandPrycementionsomemajorcharacterseffecttotheloanpaymentasfollow:

NumberofchildF£!ninahouseholdandpaymentdifficulties

Anincreaseinthenumberofchildreninahouseholdisassociatedwithhigheroutgoingsandlessavailablefinancestorepaydebt.Itisworthexploringtheirexperienceofmaintainingpayments.However,withineachyearcomparisonbetweenhouseholdswithdifferentnumbersofchildrenconfirmsthat,inmostcases,asthenumberofchildrenincreasestherateofrepaymentdifficultyandarrearsincreases

SimilartothecaseinHDBank,theexpectedresult CairnsandPryce.TheresultofregressionofthisresearchwillbeshowndetailsinchapterIV

likesresultofBowie-

Astoloanswithnocollateral,Del-RioandYoung(2005b)concludedthathighlevelsofdebtandfactorsrelatedtomarriedstatusandethnicitywererelevanttotheoccurrenceofproblemsamongBritishhouseholds

14

Intheseresearches,majorvariablesstronglyeffecttotheprobabilityofhousingloanwhicha r e i n c

o m e , a g e , s e x , h o u s e v a l u e , h o u s e s i z e , p r i n c i p a l , r e s i d e n t i a l status,occupation,interest,maritalstatus,credittype,etc.InrealconditionofVietNamandabilitytogetthedata,theauthorwillchoosesomevariablesinthemodelassex,age,education,income,size,housevalue,maturity,collateralsandloanamountfortheprobabilitytogetahousingloan.BanksinVietNamusuallyhavehousingcreditwithcommonconditionsasprincipal,income,interest,maturity.Butinsituationofeconomicdevelopingandpressureofjoiningtheworldeconomic,commercialbankinVietNamshouldhasmorecreditprogramespeciallyhousingcreditasmentioningwithflexibleanddiversifiedconditionformanyobjectives.This

researchbuildsamodelwithmanyvariablest o g e t m e a n i n g v a r i a b l e s a n d m a i n

v a r i a b l e s h a v e d e e p l y e f f e c t t o t he probabilitytogetahousingloan.Fromtheresultofthisresearch,commercialbankwillhasmorehousingcreditprogrambasedoncharacteristic

Brown,Garino,TaylorandPrice(2003)found

thatoptimismseemedtostrengthenthedemandfornon-collateralloans,eventhoughafteracertainlevelthedegreeofoptimismhadnoimpact.Factorssuchasspouseincomeandsavingsseemedtohavenoimpact

RiiserandVatne(2006)presentedobservationsonNorwegiandata from198G—

2003.Householddebthadbeenonincrease,especiallyamongtheyoungesthouseholdsandthosewithlowincome.Thegrowthoffinancialwealthhad takenplaceaboveallinhouseholdswithnodebt

Magri(2002)studiedtheoccurrenceofdebtamongItalianhouseholds.Higherincomestrengthenboththe‘demandforloansandtheavailabilityofcredit,whereasbeinganentrepreneur

strengthenedthedemandforcreditbutmadeitmoredifficulttoobtainloans

BrownandTaylor(2005)studiedthedeterminationofhouseholdfinancialwealthanddebtintheUK,GermanyandtheUS.Therewasaclearcorrelationbetweenfinancialwealthanddebt.Ifhouseholdswithnodebtwereexcluded,thecorrelationvanished

propertyincomeofpensioners.Thiscouldbethoughtofasarisingfromacutinthestatepensionoraworseninginpayoutsfromcompanypensions.Itismodeledas20%pointdeclineintheagepremiuminoldagethatisassumedtobepermanentandoccursunexpectedlyinthe2026—

30period(itreducesthenon-propertyincomeof

thoseover60by20%).Whentheshockoccurs,allcohortsreducetheirconsumptionofgoodsandhousing,butthosewhowillhavejust

retiredreducetheirconsumptionthemostastheyexperiencethelargestproportionatedeclineintheirlifetimeincome.Thedeclineofaround12%(forthoseaged61

65)intheirimmediatespendingissmallerthanthedeclineintheirnon-propertyincomebecausetheirspendingisalsodependentonwealthwhichisnotaffectedbythechangeinincome.ThisresultisthesimilartothisresearchandinVietNam.Whentheoldofhouseholderincreasesorthehouseholderisonretire,theprobabilityofhousingcreditdecreases

Crook(2001)analyzedthe1995USSurveyofConsumerFinancesdata;thedemandforhouseholdloansseemedtobeanincreasingfunctioninincomeandfamilysize

DavydoffandNaacke(2005)presentedapurelydescriptivereportonthedistributionofhousingandconsumer

loansinFrance,Britain,GermanyandItaly.HousingloanswereparticularlycommonplaceintheUKbutremarkablyexceptionalinItaly,eventhoughowner-

occupiedhousingisparticularlycommonplaceinItaly.Inallthecountriesthedeterminantsofhousingloanamountwererathersimilar

Lendingornotandhowmuchforlendingareoneofthemostimportantaspectsofboththelenderandtheborrower.Therearealsoresearchesconcernedloanamount.Similartothemodelofhousingloan,themodelofhousingloanamountisbuiltwithvariablesassex,age,education,income,size,housevalue,maturity.Inreal,thismodelhasdetailanalysisofhousingcreditforthehousehold

2.3.4Theoreticalm o d e l

s Thebasicmodel

ThebasicmodelofChung(2000)basedonassumptionsthatthereisahouseholdlivesintwoperiodswithinaperfectmarket.Thehouseholdhasainter-temporalutilityfunctionandbehavesrationally

Thehouseholdchoosetoconsumeatthelevelsthatmaximizeitsutilityovertime.Ifitscurrentincomeislessthanitscurrentconsumption,thehouseholdmustborrowtoobtainhigherlevelofutility

Generally,thebasicmodelindicatesthefactorsaffectinghouseholddemandforloanarecurrentconsu

mptionlevel,incomeandasset.Itimpliesthatthedemandofhouseholdfor

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WhereAs isinitialamountofassets;YiIsthecurrentincome;Yisfutureincome;andrismarketrateofinterest.Theequationexplicitlyindicatesthatthedemandofhouseholdsforloan

risesifpreferenceforcurrentconsumptionbeinghighorexpectedincomeincreasingo r amountofinitialassetsandcurrentincomeaswellasinterestratesdropping.Thus,thebasicmodelshowsthatborrowing,alongwithsaving,allowsthehouseholdto

smoothitsconsumptionpathandtomaximizeitsutilityovertime

Theextendedmodel

Inextensionofthebasicmodel,suchfactorsashouseholdresources,activitiesandflowsofresourcesareincludedtoidentifydeterminantsofthedemandofhouseholdsforloan;andsomeassumptions a r

e changed T h e models h o w s thatt h e de ma nd o f urbanhouseholdsforloanincreaseswithitsliquidityrequirementsforactivities.Chung(2000)writethatlevelofhouseholdbudgetdeficitdeterminesthelevelofborrowing:B=dR- ;wwhheerreeBBisthelevelofborrowing;dRisthechangeinassets;Yj isincomejthofthehousehold;andFgistheoutflowofexpendituretofinanceactivitygg.Increasesinsuchhousehold‘activitiesasconsumption,productionandinvestmentcreateincreasingo u t f l o w

s o f household r e s o u r c e s I f i n f l o w o f resources f r o m i n c o m e generatingactivitiesandassetswouldnotmeetoutflows,demandforloanmayrise.Theaboveequationshowsthatthedemandofthehouseholdforcreditappearswhenflowsofincomeandchangesinhousehold'sresourcesdonotmeetdemandforfundingthehouseholdactivities

Hence,thedemandforloanappearsand riseswhenhouseholddeficitgap appearsandbroadens.Thedemandofthehouseholdforloanisdeterminedbyhouseholdresourcesandactivities.2.3.5Empiricalmodelsappliedinpreviousstudies

ModelappliedbyEgertandMihaljek(2007).

Egerta n d Mih al jek ( 2 0 0 7 ) h av e b o t h s h o w n thath o u s e p r i c e d y n a m i c s a r e usuallymodeledintermsofchangesinhousingdemandandsupply(seeexHMTreasury,2003).Onthedemandside,keyfactorsaretypicallytakentobeexpectedchangeinhouseprices(PH),householdincome(Y),therealrateonhousingloans(r),financialwealth(WE),demographicandlabormarketfactors(D),theexpectedrateofreturnonhousing(e)andavectorofotherdemandshifters(X).Thelattermayinclude3proxiesforthelocation,a

geandstateofhousing,orinstitutionalfactorsthatfacilitateorhinderhouseholds’

OzlemOzdemir(2004)constructeda

conceptualmodeltoexplaintherelationshipbetweenconsumercreditclients’paymentperformanceandcreditcategory,interestrate,sex,age,maritalstatus,income,loansize,maturity,residentialstatusandoccupation.Theequationofthemodelisasfollows:

A=o+§collateral+yjcreditriskorborrowervariables+‹ptrelationshipfactors+(rother+c

Where

Collateralisthecollateralvirtueaspercentageofloanvolume,

Creditriskorborrowercharacteristicsvariablesincludeavectorofjvariablesthatshowthedirectandindirectcreditoftheborrowersuchasassetsize,age,liabilities-to-assetsratio,currentratio,interestcoverageratio,andthelike,

Relationshipfactorsrepresentavectoroftvariablesthatshowtherelationshipbetweentheborrowerandfirmsuchashousebankstatus,relationduration,andnumber

ofbanksthattheborrowerhasrelationshipswith

Otherrepresentsavectorofrvariablesthatcapturestheyearsoflending,banktypeofthelendingbanks,sectorclassification,etc

ModelappliedbyL.Ellis,J.LawsonandL.Roberts-Thomson( 2 0 0 3 )

Fromt h e r esul t o f ane c o n o m e t r i c m o d e l , t h r e e k e y v a r i a b l e s e f f e c t t o t h eh

o us in gleverageforhouseholdasageofthenhouseholdhead,householdincomeandhouseholdhousingwealth

ModelappliedbyI.BalkirFatmaHassanIsmailandS.Al-Segini( 2 0 0 6 )

TomeasurethepossiblerelationbetweenvariablesandtheamountofloanorgrantallocatedtotheUAEnationals,threeregressionmodelsareused.Thegeneralspecificationofthemodelsisasfollows:

withvariableswhichcanbegottenthedataandinformation.ThedetailofthemodelforthisresearchwillbeshowninthenextchapterIII

3.1 Analyticalframework

3.1.1 Hypotheses

The

aboveanalyticalgroundproposesthatcharacteristics,endowmentsofhouseholdsandloancharacteristicswoulddeterminetheprobabilityofgettingahousingloanofaborrower.Therefore,thefollowinghypothesesareraised

3.1.2 Determinantsoftheprobabilitytogetahousingloan

Thismodelshowsthedeterminantsoftheprobabilitytogethousingloan.Thetesteddeterminantsoftheprobabilitytogetahousingloanaresex,age,educationlevel,incomeofborrowerandHowdothevariablesaffecttotheprobabilitytoborrowofurbanhouseholdsandwhichvariable

isstronglyaffectstheprobabilitytoborrowofurbanhouseholds.Thevariabledefinitionofthismodelasfollow:

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Educationofhouseholdleader:levelofeducationaffectsrobustlytheiroccupationandincome.Thestabilityofoccupationandhighincomeensurethecapacitytopaybackthehousingloan

Incomeo f household:t h e l e v e l a n d the s t a b i l i t y of incomea r e important f a c t o r

s i n

evaluatingthecapacityofrepaymentfromhousehold

Sizeofhousehold:thisfactoraffectsstronglysavingsandexpendituresofhousehold.Becauseanincreaseinthenumberofchildreninahouseholdisassociatedwithhigheroutgoingsandlessavailablefinancestorepaydebt,itisworthexploringtheirexperienceofmaintainingpayments

Numberofincomeearnersinhousehold:thisfactorvigorouslyimpacttosavingsandincomeofhousehold.Themoreincomeearners,themoresavingsare

Valuesofhouse:housevalueisvaluated

asacollateralsecurityincasewithoutcollateralforhousingSloan.Besideshousevalueshowthesavingsofhouseholdatthetimewherethehouseholdgettheloanandtheloanamountwhichthehouseholdwanttoget.Maturity:intuitively,probabilityofcreditforhousingincreaseswhenmaturityincreasesbecause

themoreprobabilityofperiodicrepaymentfromhousehold.Itmeansthatthelongerterm,thesmallerperiodicprincipalandinterestofhousehold

Collateral:Assetpledgeincaseofdefault.Ifloanwasguaranteedbymortgageorpledgeasset,itwillcementresponsibilityandobligationofborrower.In

caseofinsolvent,collateralturntobesecondreceivableofbanks,however,mortgageorsecurityassethasaccommodatetorealisticc o n d i t i o n s

Loanamountorloansize:effecttoprobabilityofcreditdelinquencyincreases

whentheloansizeincreases.Sothisfactorwilldefineapositiverelationshipbetweenloansizeandhousehold’paybackperformance,assumingthereisnoinflation.Thelendersgenerallyprefergivingthiskindofcreditforlowerloansizeinordertodecreasetheirrisk

3.1.3Determinantsofloanamount

Thesecondmodelattemptstoprovethatcharacteristicsandendowmentsofhousehold,andloancharacteristicsdetermineloanamountsborrowed.Thetesteddeterminantsofloana m o u n t a r e a g e o f households, h o

u s e h o l dsize,house o f value,householdexpenditure,occupationsofhouseholdmembersand

numbersofdependants Which

amount.Thevariabledefinitionofthismodelasfollow:

• Dependentvariable

Theloanamountofhousingloan forhousehold:thisvariableismeasuredb a s i n g onprivatecharacteristicsofborrowersandstatusofborrowers’household

B- + a ; S E X + a AGE+ a EDU+ I NCOME +a5SIZE+HHNO+

a7HOUSEVAL+ agMATUR+a9COLL+aieLA

• Definitionandexplanationofvariablesofthemodel1:

+Dependentv a r i a b l e :

Bistheprobabilitytogetahousingloan.It’sabinaryvariablehavingtwovalues(0;1).Value[TJmeansacasethatborrowergotahousingloanwhilevalue[0]indicatesacasethatborrowerwasrefused

2 AGE - More agei s l e s s p r o b ab i l i t y to getloan,

3 EDU + Ifthehouseholdheadhashighereducationlevel,theprobab

ilitytogethousingloanwouldbehigher.Inthiscase,theexpectedsignis(+);incontrary,theexpectedsignis(-)

4 INCOME + Moreincomeismoreabilitytogethousingloan

becausehighincomeguaranteehighpayment

5 SIZE - Bigsizeofhouseholdistoincreaseexpendituretogetherwith

decreasingincomeaswellasdecreasingpayment

householdnumbercanearnmoreincomealongwithincreasingpaymentcapacity

hashousevalueasmuchaspossiblebecauseh o u s e v

a l u e i s t h e c o l l a t e r a l o f t h e housingl oa nandhousevalueis highwhichmeansthatloa

islowandriskfromthehouseholdalsoislow

8 MATUR + Longtermofloanmaturityissynonymouswithincrea

singpaymentformhousehold.Thelongermaturityofhousingloan,thesmallertheperiodicprinciplewhichtheymusttopay.Itmeans

thattheirincomeensurerepaymentfromhousehold

9 COL + Ift h e h o u s e h o l d headhascollateral,t h epr

behigher.Inthiscase,theexpectedsignis(+);incontrary,theexpectedsignis(-)

theh i g h e rprobabilitytogetthehousingloanis

Model 2

24

+ Moreageislessloanamount.

3 EDU + Ift h e h o u s e h o l d h e a d h a s h i g h e r e d u c a

t i o nlevel,t h e h o u s i n g l o a n a m o u n t w o u l

4 INCOME + Morei n c o m e i s more h o u s i n g l o a n a m o

u n t becausehighincomeguaranteeshighpayment

5 SIZE - Bigs i z e o f h o u s e h o l d ist o i n c r e a s eexpe

ndituretogetherwithd e c r e a s i n g incomeaswellasdecreasingpayment.Itmeansthatbiggersizeislessloanamount

increasingpaymentcapacity.Somorehouseholdnumbercanearnismoreloanamount

HOUSEVAL

+ Householdha s housevalueasmuchaspossi

blebecausehousevalueisthecollateralofthehousin

gl o a n and h o u s e v a l u e i s highwhichmeansthatloanamount

frombankislowandriskfromthehouseholdalsoislow

8 MATUR + Longt e r m o f l o a n m a t u r i t y i s s y n o n y

m o u swithincreasingpaymentformhousehold.Thelongermaturityofhousing

loan,thesmallertheperiodicprinciplewhichtheymusttopay.Itmeansthattheirincomeensurerepaymentfromhousehold.S o morematurityismoreloanamount

2isthesimilartothemodel1.Butthesignofagevariableisdifferentfromthemodel2.Theagevariableinthemodel2willbepositivesign.Inlaborage,themoreageisthehigherworkingpositionandincome

3.2 Datasourceandsampling

3.2.1Datasource

DataisusedinthisthesiscollectedfromdatabasesystemofHDBank

Dataincludes bothindividualinformationandhouseholdinformationoftheborrower.Theborrowersarethepersonswhocangethousingloan(inmodel1&2)andcannotgethousingloan(inmodel1)

26

authorwanttoapplytheresultofthisresearchtorealityofVietnameseeconomyespeciallyHDBankcase.NowVietNamhasmanydifficultiestofacethehighinflation,economic

crisisallindustries,tighteningmoneypolicyofSBV OncemoreimportantthingistheviolentcompetitioninbankingfieldatthetimeofundertakingtoparticipateinW T O T h i s r e s e a r c h w i l l h a v e

m a n y m e a n i n g f o r ban kt o f i n d o u t t h e s t a b l e developingstrategyparticularinc

hasafortunatechangetojoinmodemprojectofbankinallmodule(kernel,generalledger,customerlending,branchteller ).That’scorebankingproject.Almostofdataforthisthesiscanbeextractedfromthecorebankingsystem.AnotherfortuneissupportandpermissionofHDBankgeneraldirectortoallowandtosignadecisionfortheauthortogetthedata

Theconditionsforgettingthedataforthisthesisare:

- Loaninformationandcustomerinformationfromheadofficeandbrancheso

fHDBankinHCMC.Becauseofgeographicconditions,it’sdifficulttogetdataofsomevariablessuchassizeofhousehold,thenumberofhouseholdcan

earnincome fromarchivesofbranchesareoutHCMC

- Loaninformationandcustomerinformationmusthasenoughforallvariablesofthesissuchas:sex,age,education,incomeofhousehold,sizeofhousehold,housevalue,maturityloan,collateral,loanamount

DataisusedintheanalysisfromthecorebankingofHCMCHousingDevelopmentBank.Theanalyzeddataareoftheyear2005,2006and2007.Thereasonwhychoosetheseyearare:

- Theinflationrateislowsononeedtochangesomevariablevalueinfixedlevel;

-R e a l estatemarketisstableandhasgoodgrowth;

-RegulationandpolicyofHDBankareconsistent,stable,nosignificantchangescomparewiththeyear2008

Population(totalcasesofborrowersandloansthatyouareabletoaccess)

Totalcasesofborrowerscangetthehousingloansare1408casesinHCMCbranches.Icannotdefineexactcasesofborrowersbecausemanycasesarenotkeptinarchives

3.2.2Sampling

Samplesize

Thesamplesizeconsistsof306observedcases.Ofwhich,thereare198casesgettingahousingloanfromtheHDBankand108casesrefusedtogettheloan.ComparedtothetotalborrowingcasesoftheHCMCbranchoftheHDBank,thesampleoccupies21.7%

Samplingmethod

-Bythepossibilitytogetaloan:thepopulationisdividedintotwostratums:thecasesthatw e r e a c c e p t e d a n d r e f u s e d t o getthehousing l o a n ( 6 5 % a n d 3 5 % ofcasesaskingloanfromtheHDBank—figure2.1)

- Bytheobservedyearsincombinationtothegrowthrateinbusiness( f i g u r e 2.2):thesamplesaredrawnbyyearfollowingthepercentageo f eachyearbusinessi n c

Figure2.1sho ws thest ru ct ur e ofthepossibilityt o gethousingloanornot.Totally,

Blmprobabllltyt o

g e t loan

28

Figure2 2 s h o w s thestructureofs a m p l e s in

everyyearbyprobabilityandimprobability.Theobservationwillbepickedfollowbygrowthratepercentageoftotalhousingloanamount.Totalhousingloanamountinyear2005,2006,2007are413,591,2268billionVNDwithinturnpercentageare43%

ThecasesacceptedforahousingloanThecaserefusedtogetahousingloan

Oyear2005

■ year2006 Oyear2007

3.3 Analysism e t h o d s

3.3.1Statisticaltestsfordescriptiveanalysis

Descriptiveanalysiswillbeappliedinthestudytounderstandthecentraltendency,thedispersionandthedistributionofthesamples.DetailofstatisticaltestfordescriptiveanalysiswillbepresentedinchapterIV(item4.3)

- Multico-linearitytest:Multico-linearitytestslinearrelationshipsbetweentwoormoreexplanatoryvariables.

- Autocorrelationtest:Durbin-Watson(DW)testwillbeusedforautocorrelationofvariables

3.4Analytictool

AlldataofthisthesiswillberunbySPSSsoftwareincludesanalysessuchas:statisticaltestsfordescriptiveanalysis,correlationanalysis,testsforvalidityofspecificmodels