ProblemStatement
Thefinancialcrisisfrom2007to2009intheUnitedStateswerementionedth ew o r s t c r a s h o f e c o n o m i c s y s t e m i n WallS t r e e t s i n c e t h e G r e a t D e p r e s s i o n happened in1930sbyresearchofLee, RabanalandSandri(Janu ary,2010) This traumahighlyc o n t r i b u t e d t o thefailure ofkeyb u s i n e s s e s , r e d u c e d t h e livingstandards,andalsoresultedinaslowdownofwholenationalproductionactiviti es.I t initiallystartedwiththeU.Smortgagemarketandspreadoutitsimpactoverthew o r l d as“dominoeffect”.
Vietnamesee c o n o m y n o w i s i n t e g r a t e d itsd o m e s t i c markett o w a r d s w o r l d w i d e Therefore,theindustrialrealestatemarketinVietnamcouldnota voidt o beinfluencedinthistwistingcurse.AccordingtothestudyofJehanandLu ong(2 008) ,theyprovidedtheproblemsofVietnamrealestatemarketinfrontofglobalf i n an c i a l crisis.Theirpriorityisgivenbylackof capitalresourceswhichcamefromc r e d i t agenciesorfinancialinstitutions.Thefuncti onofmanycreditmarketsseriouslystoppedtofunctionatallandimpactedonotherindustr ies.Mostoflocalc r e d i t i n s t i t u t i o n s a d m i t t e d t h a t t h e p r o c e s s t o o k extremec o n s t r a i n s t o p r o v i d e lendingcreditstoSmallandMediumEnterprises(SMEs).Theproblemisdescribeda s a d o w n s i d e b o t t l e n e c k e f f e c t i n t h e c r e d i
2 t s y s t e m b e c a u s e t h e t i g h t m o n e t a r y po lici esofgovernments.Basingon researchpaperofPhametal.(August,2013), theyc l a r i f i e d t r a n s p a r e n t l y t h e i m p o r t a n t c o n t r i b u t i o n o f
The Vietnamese economy, particularly the real estate sector, has faced significant challenges, including a liquidity freeze and a sharp decline in housing prices, leading to an estimated $3.1 billion in unsold inventory among listed real estate companies in 2012 This downturn has resulted in the closure of 10,077 local real estate enterprises due to low trading liquidity in 2013 The two largest cities, Ho Chi Minh City and Hanoi, experienced substantial inventory levels, with Hanoi holding over 6,580 unsold apartments and Ho Chi Minh City having 7,830, valued at 12,900 billion VND and 17,480 billion VND, respectively Addressing these bottlenecks is crucial for the government to restore economic growth.
Whent h e t o t a l d e m a n d u n e x p e c t e d l y d r o p p e d t o a l o w e r l e v e l , t h e companiesdidnotknowhowtosettledowntheircurrentdebts.MostofVietnameseenterpr isesstillarevulnerabledue tonotonlyvolatilityoffinancialmarketbutalsod i f f e r e n t ec o n o m i c sc e n a r i os O n e m o r e r e a s o n i s t h a t mosto f Vietnameseenterprisesaredevelopingandlimite dexperiences,sotheymayreceivethep r o s p e c t o f d e f a u l t whent h e c r i s i s s u d d e n l y comei n t o t h e m ( J e h a n a n d L u o n g , 2 0 0 8 ) Themainspecificationoft herealestatemarketistorequireahugeamounto fcapitaltoaccomplishthehousingproject s.
Evaluating the effectiveness of capital structure in the real estate sector is challenging due to time lags in various economic scenarios, which can lead to poor financial decisions While the equity market may react swiftly to changes, it takes time for these changes to influence business activities Companies risk deeper financial troubles if they do not promptly address current issues by adjusting their capital structure to more sustainable levels.
Vicol(2010)successfullydemonstratedinhisthesisresearchthatrealestatecompa niesint h e c r i s is s ce n a r i o s w o u l d f ac e a l o t o f i s s u e s r e la t i n g t o t h e i r o w n b u s i n e s s activitiessuchasfinancialcashflow,generaloperations,inventories,and depreciation methodologyaffectingtheiradjustmentsofcapitalstructure.
Thea u t h o r r e a l i z e s t h a t t h e r e i s a n a b n o r m a l p h e n o m e n o n i n V i e t n a m e s e enterprisesrelatedtorealestatesector.Thehighdebtratiointheirfinancial statementalertedtherisk- ontobusinessactivitieswhenthemarketcrashed.A l t h o u g h facingwithhighinte restexpensesandlowlevelofmarketdemand,mosto f r e a l e s t a t e e n t e r p r i s e s a r e w i l l i n g t o b o r r o w m o r e s h o r t - t e r m de b t s i n o r d e r t o maintaint h e i r c u r r e n t b u s i n e s s a c t i v i t i e s T h i s s t r a n g e p h e n o m e n o n w i l l bee x p l a i n e d byhypothesesandassumptionsinthisst udyarebasingontwoprimarytheoriesofcorporatecapitalstructuredecisionswhicha r e rankedastheoriesoftrade- offandpeckingorder.However,notonlyalloftheproblemscamefromtheinternalbus inessoperations,butalsothesepotentialexternalitiesmayimpacton thec o n s e q u e n c e s , suchasmonetarypoliciesandmanagementlevels.
Byapplyingtheories o f t he trade- offa n d peckingorder, we expecttofind d o w n thedeterminantswhichwillmakeany significanteffectoncapitalstructureinr e a l estatecorporationstowardsaspecificoptimalfina ncialdecisioninthefuture.
ResearchObjectives
First ofall,thisresearchpapertriestoverifyc l e a r l y t h e conceptsandprioritiesofde f i n i n g corporatecapital structure ByTrade- offan d PeckingOrdertheories,theauthorwantstotesttheimpactofboththeoriesoneac hofd e t e r m i n a n t s
Secondly,theauthorwouldliketostartwithanalyzingthedebtratioduringthec risis.KantorandHoldsworth(2010)showedthattheleverageoffirmgradually increasedinthecrisisandalsocontinuedtorisesharplyinpost- crisisduetotimelags.T h e s e timel a g s w e r e r e f e r r e d t o t h e d e l a y o f t h e p r o j e c t c o n s t r u c t i o n T h e i n e f f i c i e n t accountreceivablesalsodeterminedthe lackofcapitalor riskycapitalstructurewhicho w n e r s hadt o b o r r o w mored e b t s i n o r d e r t o s e t t l e d o w n t h e s e problemsinthecrisisstage.TheresearchbyK ang,Maysami,Mensah,andPham(2013)demonstratedthatthenegativeopera tingbusinessofrealestatecompaniesperformedgloomyvisionsinthecrisis.Hig hinterestexpensesjustwipedouttheire a r n i n g s , andcashflowgraduallyshifte dfrompositivesigntonegativesignoverthisp e r i o d F u r t h e r m o r e ,
K i m a n d S t o n e (1999)f i g u r e d o u t t h a t h i g h l e v e r e d co r p o r at io n s mightf a c e a n u n e x p e c t e d c u t - o f f o f l e n d i n g c r e d i t s f r o m f i n a n c i a l institutionswhichwasimitatedo b v i o u s l y intheirthesis.I t s e f f e c t o f f i n a n c i a l d i s t r e s s maydrivet h e c o m p a n y goba nk ru pt T h e u rg en tr esp ons e f r o m board o f di rect or s istodivestinnon- coreprojectsandreducegoodsormaterialsininventoryatadiscountpricetosurviveinthemar ket.
Finally,inthemodernage,thereisanewtrendforfirmsinthecrisismayu s e s p i n — offs t r a t e g y w h i c h mayh e l p p a r e n t c o m p a n y t o a c h i e v e a n e f f i c i e n t c a p i t a l structureorlowerdebtratiobyexcludingseveraldebtamounts.Bas ically,t h e s p i n - o f f s t r a t e g y d o e s n o t c h a n g e t h e l e v e r e d r a t i o s i n c o n s o l i d a t e d f i n a n c i a l statement.Butthisstrategysomehowwillhelpbusinesstogetbetter financialratioso f p a r e n t company.T h e p a r e n t c o m p a n y h a s h i g h o p p o r t u n i t i e s tob e r a i s e d i t s creditbyratingagencies.Therearealsoalternativesol utionsofinternalfinancing(Nguyen,2010)suchaspre- salesystemtothebuyersordiversifiedbusinesssectori n ordertostayinthemarket.Ing eneral,theauthorspecifiestheirmechanismsbytypicalexamplesinthedataset.
ResearchQuestions
Whatt h e keydeterminants maket h es i g n i f i c a n t e x p os u r e s onca p i t a l st ructureinVietnameserealestateenterpriseswhichimportantlyneedtobe answeredinthisstudy.Theefficientoptimizationwillbeananswerforthosereal estateenterpriseswhicharestrugglingwithdebtandinterestcoverageindiffe rentb u s in e s s prospects.
Ingeneral,theoptimallevelwillfollowtheindustrialbenchmarksofd i f f e r e n t stagesofeconomy.Basingonprevioustheoriesoftrade- offandpeckingo r d e r , therecanbeseveralquestions,whichconcernthechoiceofca pitalstructure,ar e t e s t e d bys t a t i s t i c s a n d r e g r e s s i o n m o d e l T h e w r i t e r mentionst h e m i n t h r e e assumptions:firstly,thedebtleverageof onecompanyadjuststogodowngraduallyd u r i n g t h e c u r r e n t c r i s i s Secondly,r e a l e s t a t e companiesw i l l s t r u g g l e w i t h l e s s financialbudgetbydebtissuers.Finally ,t h e r e l a t i o n s h i p b e t w e e n d e b t a n d p r o f i t a b i l i t y i s e x p e c t e d t o p e r f o r m a d i v e r g e n t t r e n d T h i s w o u l d h e l p w r i t e r t o analyzea n d e v a l u a t e Viet namesel i s t e d r e a l e s t a t e c o r p o r a t i o n s w i t h r e s p e c t toc a p i t a l struct ure.
Scopeofstudy
Inthispaper,thewriterwouldliketousepaneldatawhichcombinedboth cr o s s sectionandtimeseries.Paneldatatendstoprovidemoreaccurateestimationso f r e l a te d determinants i nregression m o d e l F u r t h e r m o r e , it allows us toid en ti fy andmeasureexactlythechangesofdeterminantswhichwecannotdetectbysinglec r o s s s e c t i o n o r s i n g l e times e r i e s m e t h o d o l o g y F i x e d E f f e c t M o d e l (F EM)a n d R a n d o m EffectModel(REM)arecomparativemethodologiestoevaluatet hes i g n i f i c a n t r e s u l t s o f r e g r e s s i o n model.T h e t e s t o f Hausmanw i l l b e a p p l i e d todifferentiatebetweenFEMandREM.
Thereare56observationsinthedataset.Theyarelistedrealestatecompani esinVietnamesestockmarket.Theprimarydata,includingbalancesheet,incomestat ementandcashflowstatementarecollectedfromStateSecuritiesC o m m i s s i o n (SSC).Thesurveyperiodislimitedfrom2010to2013
Structureofthesisresearch
The thesis research is structured into five chapters, each addressing critical components of the study Chapter I provides an overview, outlining the research objectives, questions, and scope Chapter II focuses on a literature review of pecking order and trade-off theories derived from previous studies Chapter III presents the analytical framework, detailing the research methodology, data collection, and introduction of determinants In Chapter IV, the results and explanations of regression model testing are discussed, highlighting the statistical significance between Fixed Effects Model (FEM) and Random Effects Model (REM) Finally, Chapter V concludes the study, summarizing major findings and limitations while suggesting avenues for future research improvements.
Thisc h a p t e r w i l l p r e s e n t t h e p r i n c i p a l o f ModiglianiandMiller,p e c k i n g o r d e r , andt ra de- of f t h e o r i es Ea ch oft h e o r i e s e v a l u a t e s t he di ff er en t purposes o f c a p i t a l structurerelatedtofinancialdecisionsof company.Therearetwopartsint h i s ch apter.Firstly,theempiricalstudiesreviewtheefficienciesofpreviouspapers.Secondly,h y p o t h e s i s o f v a r i a b l e s w i l l e x p l a i n t h e i r s p e c i f i c impactso n c a p i t a l structure.
ReviewofEmpiricalStudies………………………………………….72 2 Hy pothesisofVariables
DependentVariable:DebtRatio
Total assets represent the proportion of assets financed by liabilities, providing insight into the financial health of real estate enterprises By analyzing this debt ratio, stakeholders can assess an enterprise's stability However, this metric has limitations; it may overstate financial leverage if a company has significant outstanding payments to suppliers, deferred revenues, or tax obligations A higher total liability relative to total assets indicates reduced equity independence, which can lead to financial crises due to debt interest pressures.
IndependentVariables
There is no consistent estimation of how profitability affects capital structure Generally, profitable firms have incentives to raise their debt levels to benefit from tax shields According to pecking order theory, corporations prefer internal funding, such as retained earnings, over external financing from financial institutions However, in times of financial distress, companies often resort to borrowing from external sources, such as corporate bonds or equity, to meet urgent funding needs Conversely, trade-off theory suggests a positive relationship between profitability and debt ratio, as increased leverage can generate more income This paper aims to analyze the ratio of earnings before interest, taxes, depreciation, and amortization (EBITDA) to enterprise value (EV) as a more suitable indicator of profitability in the real estate industry, compared to the EBIT to total assets ratio Enterprise value provides a clearer perspective on a company's worth, especially for real estate firms that may possess indirect assets under construction or generate goodwill income The inverse relationship between leverage and profitability is expected to shift under varying economic conditions.
Rajan and Zingales (1995) highlighted the ambiguous relationship between firm size and capital structure, suggesting that larger firms face a lower probability of bankruptcy Frank and Goyal (2003) noted an inverse relationship between business scale and bankruptcy risk, emphasizing the dilemma large holdings face when deciding whether to increase debt to expand assets Their findings indicated that larger firms tend to be more leveraged, benefiting from higher credit ratings and lower default risks, which attract greater attention from financial analysts and rating agencies Consequently, larger firms can issue more debt at reduced capital costs In summary, while the pecking order theory suggests a negative relationship between size and debt ratio, the trade-off model indicates a positive correlation.
Thevolatilityfrombusinessperformanceisthebestrepresentativeindicatort o measuretheprobability ofrisk.Accordingtotrade- offmodel,whenthestandardd e v i a t i o n ofprofitabilitywasincreasing,theexpect edreturnsalsotendtoincreaseast h e normalc o n s e q u e n c e s ( K e s t e r , 1 9 8 6 )
T h e b u s i n e s s r i s k w o u l d i n c r e a s e i n h i g he r levelduetothevolatilityofearni ngs.However,anegativerelationisfoundby(Bradleyetal.,1984)and(TitmanandW essels,1988).Inthisstudy,theauthorw an t s t o f o l l o w B o o t h e t a l
( 2 0 0 1 ) ’ s f o r m u l a f r a m e w o r k byc a l c u l a t i n g a periodically standarddevi ationineac hofreal estatecompanies The volatilityofe a r n i n g s b e f o r e i n t e r e s t , t a x e s , d e p r e c i a t i o n , a n d a m o r t i z a t i o n ’ s g r o w t h (EB ITDA_GROWTH) infiscalyearbasiswillindicatewelltheriskfrombusinessperfor mances.Forthisdeterminant,theauthorgenerallyputsthepositivesignfort h e standarddeviationofEBITDA_GROWTHanddebtleveragetotesthoweffectiv et h e e n t e r p r i s e w o u l d i n c r e a s e 1 % o f l e v e r a g e t o c r e a t e a n amo unto f earnings. d) Depreciation
Somepreviousempiricalstudies confirmedthe theoreticalpredictionoftrade- offmodel,s u c h a s K i m a n d S o r e n s e n ( 1 9 8 6 ) c o n f i r m e d t h e p o s i t i v e r e l a t i o n s h i p of d e p r e c i a t i o n a n d deb t r a t i o H o w e v e r, a n e g a t i v e r e l a t i o n be t w e e n non- debtt a x s h i e l d s a n d l e v e r a g e i s a l s o f o u n d by( H u a n g a n d S o n g , 2 0 0 2 ) a n d
Titman and Wessels (1988) highlighted that when an asset depreciates, its book value decreases correspondingly due to accumulated depreciation Assuming total liabilities remain unchanged, the ratio of total liabilities to total assets increases as the value of total assets declines In this study, the author adopts the methodology of Titman and Wessels to calculate the depreciation ratio by collecting enterprise depreciation on a fiscal year basis and dividing it by total assets Consequently, an inverse relationship emerges between the depreciation ratio and debt leverage.
Normally,thecostsoffinancialdivisionscomefrominterestexpenses.Z h a n g a ndLi(2008)revealedthathigherinterestexpenseswillstimulatethedebt leverag e.Basingontrade- offtheory,theydemonstratedtheevidence thatintereste x p e n s e s becameataxs hieldtoreducetheamountoftaxes,andcreatedanincentivetou s e t he h i g h a m o u n t s o f d e b t e v e n t u a l l y H o w e v e r , a r i s e o f i n t e r e s t expensew i l l a lso u ne x p e c t e d l y argue t h e c o n f l i c t between d e b t h o l d e rs t oe q u i t y h o l d e r s , andtheshare holderstomanagers.Thepositivesignificanceofthesedeterminantstodebtratiowillb elikelytoexpectinregressionmodel.
DebtInterest NaturalLogarithmofI nterestExpenses (+)Trade-off
Fromprevious s t u d i e s , t h e w r i t e r p o i n t s o u t f i v e determinantsw h i c h h a v e d i f f e r e n t e f f e c t s o n c a p i t a l s t r u c t u r e D e b t r a t i o w i l l b e p r e s e n t e d f o r d e p e n d e n t v ar i a b l e i n r e g r e s s i o n model.T h e r e a r e t w o mainp a r t s i n t h i s c h a p t e r Theyare analyticalframeworkand introductionofthe regressionmodel.Theanalyticalframeworkreviewsthe impactofindependent var iablesondebtratio whiler e g r e s s i o n modeldescribesthemodel’sshape,method ofdatacollectionandresearchstatistic.
AnalyticalFramework
Assho wn infi gu re 3 1, t he f r a m e w o r k an al yses thec on seq uen ce o f c a u s e andeffectthatmayprovideultimatelytherelationshipresults.Inthegraph,i nternalitiesandexternalitiesaretwomainfactorswhichcausethegreatesteffectonc a p i t a l s t r u c t u r e A s t h e w r i t e r m e n t i o n e d inp r e v i o u s p a r t s , t h e e x t e r n a l i t i e s o f governmentpoliciesandmanagementlevelsshouldnottestinthispaperduetolack o f information.F o r t h e i n t e r n a l d e t e r m i n a n t s , t h e r e a r e f i v e f a c t o r s s u c h a s s i z e , p r o f i t a b i l i t y , volatility,depreciationratio,anddebtinterestcoststhat maygivethe clearimpacttodebtratio.Basingonhistoricresearchesofauthors,theytypical lyconcludedthedifferentsignsofeachfactortowardsdebtratio.
RegressionModel
AssumptionsofRegressionModel………………………………1 6
The article discusses the impact of five determinants on the debt ratio of companies, particularly focusing on Vietnamese real estate corporations that rely heavily on capital lending from commercial banks and financial credit issuers It examines the relationship between the debt ratio and independent variables using a linear functional form based on descriptive statistics, while also incorporating a quadratic term to explore potential nonlinear relationships in the regression model Despite adding these determinants to the statistical equation, the writer found no significant improvement in the squared determinants of the regression model Additionally, the Fixed Effect Model (FEM) and Random Effect Model (REM) are compared as statistical methodologies for this regression analysis, with the Hausman test determining the most suitable model for the analysis.
LimitationsofRegressionModel
a) Inr e g r es s i o n m o d e l , t h e w r i t e r onlydiscusses o n i n t e r n a l d e t e r m i n a n t s Theexternaldeterminantsofgovernmentpoliciesandmanagementskills areambiguousinformationandthelackofdata.Theyaredeterminedbysocialp r e f e r e n c e s andbusinessdevelopmentrespectively.Theeffectofexternalitieswillb e explainedmoreinpartoftheconclusions. b) Someo u t l i e r s seemtobe quite influentiali n thedatas e t Iftheseo b s e r v a t i o n s madeanysignificantchangesinr esult,wewouldliketousedummydatapointsforregressionmodel. c) Datasetisshortduration(from2010to2013).So,itwouldnotperform well thestatusofobservationduetotimelags.
EquationofRegressionModel………………………………… 173 2
- 𝑋 1 ,𝑋2,𝑋3,X4,andX5arepresentedbydepreciationratio,s i z e , debtint erest,profitability,andvolatilityrespectively.
All data sources areavailable attheState Securities Commission ofVietnam( S S C ) from2010to2013.Therearetotal56realestatecompaniesarelisted onHo
ChiM i n h S t o c k E x c h a n g e ( H S X ) a n d H a n o i S t o c k E x c h a n g e ( H N X ) T h e mainstandardo f t h o s e s e l e c t e d companiesist h a t t h e i r marketc a p i t a l i z a t i o n s mustbeo v e r 100billionVND.Someofthemarediversifiedinmanyrealestatesub- sectors,includingconsultant,supplier,contractor,etc.Inthispaper,theauthorusesd e s c r i p t i v e statisticstoobservethecurrentdebtratioinVietnameselistedrealestatecompanies.Th ecomparativestatisticalmodelsofFEMandREMwillprovidethee f f e c t offive determinantstochangesindebtratio.Thedatasetwilldesignas datedp an el d a t a , w h i c h i d e n t i f y company’s n a m e s a s c r o s s s e c t i o n s e r i e s a n d yearsa s dateseries.
Vietnameserealestatemarketjustslightlypassedoverthebottomofcrisis.Att hisstage,thebubbleofrealestateindustryseemstobepredictablytriggeredb ytightmonetaryp o l i c i e s i n o r d e r t o r e d u c e t h e h i k e ra t e s o f i n f l a t i o n , a n d tostabilizet h e macr o eco no mi cs T h e c u t t i n g c r e d i t f o r t h e r e a l e s t a t e m a r k e t c a u s e s a n e g a t i v e impact onrealestatecompanies.Thepricesofland,h ousing,andofficeleasehadd ecl in ed significantlytothelowestlevel,whichmostof investorsforcedtosell- offa b o u t 50%fromtheiroriginalvalues,comparedtothepastgorgeousperiod
.The f a i l u r e of price equilibriumbetweensellersandbuyersinthisprocessalsoleadedtothel o w t r a d i n g l i q u i d i t y , b a n k r u p t c y , a n d h i g h u n e m p l o y m e n t r a t e i n r e a l e s t a t e sector.
Descriptivestatisticspresentsthebriefsummariesofobservationsindataset.Thed e s c r i p t i v e g r a p h s a l s o mentiona b o u t t h e d i s p e r s i o n o r c e n t r a l t e n d e n c y o f o b s e r v a t i o n s TheRegressionlinewillpointouttherelationshipbetweendebtrat ioa n d itsdeterminants.Theauthorbasesonresultofthistesttoconfirmtheshapeofreg ressionmodel.Thematrixcorrelationalsopresentstotestthemulticolinearyofr e l a t e d determinantsinregressionmodel.
Leveragetestingprovidesageneralanalysisofdeterminantsvolatility.M e a n , median,and standarddeviation arethreemainindicatorsin this statistic. Thet i m e periodwillbaseonthedataset.Thepurposeofleveragetestingistoknowtheave raged e b t r a t i o o f industrialr e a l e s t a t e Wec o m p a r e somet o p h o l d i n g s w i t h h e a l t h y capitalstructures.Hence,wemayapplythebenchmarkofthisratio(opt imalcapitalstructure)fortheVietnamesemarket.
Linearr e g r e s s i o n w i l lh e l p t o e x p l a i n t h e i m p a c t o f e x p l a n a t o r y v a r i a b l e s (depreciation r a t i o , s i z e , d e b t i n t e r e s t , p r o f i t a b i l i t y , a n d v o l a t i l i t y ) o n d e p e n d e n t variable(debtratio).Dependingontheresearchof Song(2005),heclearlyprovedt h a t d e b t r a t i o isa n i m p o r t a n t c o n c e p t t o d e f i n e a n d u n d e r s t a n d o b v i o u s l y t h e financialriskincapitalstructure.T heriskfromfinancialoperationswillchallengeacorporationtosettledownallliabilityobli gationsforshort,mediumandlongtermp r o s p e c t s ofbusinesscampaign.
Since2008,mostofrealestatecompanies’profitsinVietnamaredisruptedb yfinancialobligationswiththeescalatinginterestcoverageratioanddebtratio s.Themodelisstructuredbypaneldata.Theadvantageof panel dataismentionedc l e a r l y byBaltagi( 1 9 9 5 ) t h a t h e t e r o g e n e i t y b o u n d s t o i n d i v i d u a l s , companies,n a t i o n a l i t i e s , etc.Thespecificationsofpaneldataregressio nmodelwilltakehet erog en eity explicitlybyallowingforindividual–specificvariables.
Therearesixpartsinthischapter.Twofirstpartsreviewthescaleoflistedr eal estatecompaniesinVietnamesestockexchangesandhistoricdevelopment ofreale s t a t e s e c t o r s i n Vietnam.N e x t t h r e e p a r t s p e r f o r m t h e r e s u l t a n d t e s t i n g ofr e g r e s s i o n model.Finalpartconcludessomegeneralopinionaboutsignifica ntlevelo fmodel.
OverviewofRealEstateCompaniesinVietnam
Vietnameser e a l e s t a t e markets h o w s a q u i t e d i s c r e t e d e n s i t y i n t e r m s o f q u a l i t y andquantity.In2013,therearearound60realestatecompanie slistingonVietnameses t o c k marketa n d t h e i r marketc a p i t a l i z a t i o n s e s t i m a t e 1 2 5 t h o u s a n d b i l l i o n s , a n a v e r a g i n g c o n t r i b u t i o n o f 1 0 % i n the w h o l e market.I n t o p l e a d i n g companies,V i n g r o u p ( V I C ) a n d H o a n g A n h
G i a L a i ( H A G ) seemst o d o m i n a t e o t h e r domesticcompetitorsbasingonenor mousincomesandrevenuesalesinyearbasis.Mostofrealestateprojectsarelocally focusinginHanoi,HoChiMinh,andfewoffrontiercities.
Thespecificationsof r e a l estate co mp an ies depend o ntwom a i n e le me nts : hugeamountofcapitalandsufficientlandproperty.Theentrybarrierofreales tatemarketstaysatnormallevelincomparisontobankingoroilandgasindustries. ItmeansthatVietnameserealestateenterprisespotentiallyh a v e moreroomstod e v e l o p i n f u r t h e r p r o s p e c t I n r e a l e s t a t e market,e n t e r p r i s e s m o s t l y d o m i n a t e a g a i n s t othercompetitorsbylandlocationsandnumbersoflandowne rship.Thoset w o f a c t o r s w i l l p r e s e n t t h e v i s i o n o f e a c h r e a l e s t a t e c o m p a n y w h e n b o a r d o f director ssetupthepro-formafinancialprojections.
Since1990,Vietnameserealestatemarkethasenduredthreetimesoffrozenliquidi tya n d threet i m e s o f p r i c e b o o m i n g T h e r e c e n t b o o m i n g o f r e a l e s t a t e marketrecordedin2007to2008whenahugeamountofFDIrushedintoVietnamecono my.However,afterthishistoricglory,thedeclineofhousingdemandr e f l e c t e d o n t h e s l u m p o f r e a l e s t a t e market.Thef i g u r e 4 1 h a s performedt h e d o w n t r e n d ofrealestateindexwhichsufferedlossesof60-
70%ofitsoriginallevelsin ce 2010.Onemoreimportantspecificationofrealestatecomp aniesisdeferredr e v e n u e s , whichcamefromtheinvestor’saccounttoinvestth ecurrentrealestatep r o j e c t s Incentralphase ofcrisis,thisamountwillbelo werthanthe pre- crisisperiodduetomostoftheinvestorsfeellackofconfidencetoputmoretheircapitalsi nt o realestateenterprises.Infact,aslongasthecrisishasremainedineconomy,t h e realestatecorporations trytoescapeoutt h e marketsharebysellingoffthei rg o o d s withalargeproportioninprice.
Figure4.1:The com pa ri so n of VN Index andRealEs ta te Index fromthep e r i o d 2010-2013.Data:Vietstock
ImpactsofVietnameseRealEstateMarket
InflowCapitaltoRealEstateMarket
CreditAgenciesprovideslendingcapitaltoenterprisesthroughbyfinancialservi ces.Themainspecification ofrealestatesectoristo requirea largeinvestmentcap i t al attheinitialstageforvariouspurposes, suchassitecle aringcosts,co n s t ru c t i o n c o s t s , a n d l a b o r c o s t s , e t c T h e r e f o r e , r e a l e s t a t e c o m p a n i e s alwaysneedsufficientbudgetsfromcreditinstitutionstofulfilltheirproj ects.
Basingonhighdebtratio, theoperating activitiesof rea lestateenterp risesmostly areimpactedbylending interest rateandmonetarypoliciesfromState Banko f V i e t n a m ( S B V ) Ast h e theoryo f macroeconomics,h i g h i n t e r e s t r a t e w o u l d r e d u c e theincentivesofinvestment.
ForeignDirectInvestment(FDI)willimprovetheeconomicdevelopmentbyinvesti ngtourbaninfrastructure,securities,orjointventure.Moreover,thecapitalso f F D I w i l l c r e a t e morej o b s toV i e t n a m e s e l a b o r f o r c e a n d r e d u c e t h e u n em p l o y m e n t r a t e V i e t n a m h a d a s t a b l e p o l i t i c s a n d a p p l i e d i n t e r e s t i n g regulationst o a t t r a c t f o r e i g n e r s i n r e c e n t years.S i n c e 2 0 0 6 , V i e t n a m o f f i c i a l l y becamea membero f WorldT r a d e O r g a n i z a t i o n ( W
T O ) , w h i c h r e m a r k e d c o m p l e t e l y animportantstageofintegratedecon omy.Intheageofglobalization,F D I isincreasinglyplayinganimportantroletocount ry’sdevelopment.Specifically,infigure4.2,FDIestablishedarecordofinflowregistrat ioncapitaltoVietnamesemarket,upto70billionUSDin2008.Althoughthe econo myhadto
F D I( U Sb ill io n) strugglewithglobalfinancialcrisis,Vietnammaintainedtoattractover15billion
Fordevelopingcountries,therelationshipbetweenFDIanddebtratioisalsoco n s id er ed inthisthesis.Firstandforemost,FDImaycomefromtheinternationalc r e d i t institutionswhichprovidepreferentialcapitalstodomesticenterprises.I tiscal l ed a t r a n s f e r r e d c a p i t a l f r o m d e v e l o p e d c o u n t r i e s t o d e v e l o p i n g c o u n t r i e s i n o r d er t o s e e k m o r e b e n e f i t s Secondly,t h e l o c a l r e a l e s t a t e c o m p a n i e s c a n i s s u e internationalconvertiblebondstoattractmoreFDI’sca pitals.Althoughtheirdebtr a t i o w i l l i n c r e a s e , theyc a n a v o i d t h e c o n f l i c t o f d i l u t e d e a r n i n g s p e r s h a r e toc u r r e n t shareholders.Finally, t othosed ebtratios,whicharemostlystructuredbyinternationalcapitals,mayfacewithar iseindebtinterestcostsduetotheriskofe x c h a n g e rates.
N um be ro fu rb an ci ti es P er ce nt ag e%
LandandPropertyLaw
2009andvalidatinguntil2013,thecu r r en t landandpropertyownershiplawislimite dtheforeigner’sabilitiestobuyp e r m a n e n t l y a h o u s e o r l a n d i n Vietnam.T o stimulatet h e d o m e s t i c r e a l e s t a t e market,t h e a u t h o r i t i e s r e c e n t l y r e d u c e d t h e t a x r a t e s o f c o m m e r c i a l h o u s e p r o j e c t i o n s , andapprovethene wlawtoexpandtherequirements ofowninglandan d propertyforforeigners inVietnam.This windfallsomehowbooststhehigheri n v e s t m e n t s onVietn ameserealestatesector.
UrbanizationinVietnam
AccordingtoWorldBank’sThe 2014Revision, Vietnamisoneofthe top countrieswhichhadfastestspeedofurbanizationinSouthEastAsiacountries.Thenum berofcitieswasrisingsharplyyearbyyear.Itisanessentialstepofmodernindustrialr evolutioninVietnam.
However,t h e f a s t s p e e d o f u r b a n i z a t i o n a l s o r e q u i r e s t h e q u a l i t y o f u r b a n infrastructureandcontrolofhousingconstruction.Thismakesapositiveimp actonp o t e n t i a l g r o w t h f o r V i e t n a m r e a l e s t a t e c o m p a n i e s M o r e u r b a n c i t i e s a p p e a r s , moredemandofhousings,commercialtradecenters,ent ertainments,etc.willalsomovetohigherlevels.
Economicgrowthrate(GDP’sGrowthrate)
Theeconomicgrowthrateshowsthecloserelationshipwithdevelopmentofr ea l e s t a t e s e c t o r Whent h e e c o n o m y isb o o s t i n g , t h e d e m a n d o f l e a s i n g o f f i c e s , commercialtradecenterswill risetocatchupthisconvergenttrend.More over,a p e r s o n , w h i c h h a s h i g h e r income,r e q u i r e s d i v e r s i f i e d l u x u r y p r o d uc t s i n s t e a d o f normalproducts.Thisphenomenonalsogeneratesquickly thesale revenuesforreale s t a t e companies.
Figure4.4:VietnamGDP’sGrowthRatefrom2004-2013.Data:WorldBank
DescriptiveStatistics………………………………………………….264 4 Lever ageTesting
The coefficient ofdetermination,R- squaredlinearisequalto0.791saysthat79.1%ofthevariationindebtinterest(Y)ise xplainedwellbythelinearrelationwithd e b t r a t i o ( X ) T h i s l e a ve s 2 0 9 % o f t h e v a r i a t i o n i n d e b t i n t e r e s t leftt o b e ex p l a i n ed byotherf act or s (exceptX ) Thisresultmeasuresthest ro ng relationof twovariables:debtratioanddebtinterest byleast-squaresregressionline.
( H N X : P V R ) iso n e o f s u b s i d i a r i e s o f P e t r o V i e t n a m A l t h o u g h PVR’sd ebtratiomaintainedatlevelof50%,butitsdebtinterestisapproximatelye q u a l toz ero.
Inthisgraph,theresultofR- squaredlinearisequalto0.795saysthat79.5%o f thevariationindepreciationratio(Y)isexp lainedwellbythelinearrelationwithd eb t r a t i o ( X ) T h i s l e a v e s 2 0 5 % o f t h e v a r i a t i o n i n d e p r e c i a t i o n r a t i o l e f t t o b e explainedbyotherfactors(exceptX).This resultalsomeasuresthestrongrelationo ftwovariables:debtratioanddepreciationratio(X :Y).
( 0 5 9 : 0 2 1 ) , a n d ( 0 3 9 : 0 2 8 0 T h e s e t w o o b s e r v a t i o n s a r e signi fi cant ly scatteringfarawayfromR-squaredlinear.
Next,theresultofR- squaredlinearisequalto0.805saysthat80.5%ofthev a r i a t i o n incompany’ssize( Y)isexplainedclearlybythelinearrelationwithdebtratio( X ) T h i s l e a v e s o n l y
1 9 5 % o f t h e v a r i a t i o n i n c o m p a n y ’ s s i z e l e f t t o b e ex p l a in ed byother factors(exceptX).Thisresultalsomeasuresthestrongrelationo ftwovariables:debtra tioandcompany’ssize(X:Y).
ThisgraphalsoappearsfewvaluesactingasoutlierstostayawayfromR- squaredlinear.Vingroup(HSX:VIC),HoangAnhGiaLai(HSX:HAG)andKinhB a c CityDevelopmentHolding(HSX:KBC)areparticularlyscatteringfarawaytoR- squaredlinearbecauseofenormousvaluesintotalassets.Theirsizespresentedthevalue ofYwhichmostlyrecordedover4.5.
R- squaredlinearisequalto0.801saysthat80.1%ofthevariationinp r o f i t a b i l i t y (Y)isex plainedclearlybythelinearrelationwithdebtratio(X).Thisl e a v e s 19.9%ofthev ariation inp r o f i t a b i l i t y lefttobeexplainedbyotherfactors ( e x c e p t X).Int hiscase,thedensityofvaluessetscloselytoR- squaredlinearandexplainsveryw e l l t h e r e l a t i o n s h i p o f t w o v a r i a b l e s : d e b t r a t i o a n d p r o f i t a b i l i t y (X:Y).
( H S X : D 2 D ) performedi t s scatterplotat(0.67:3.57)i n year2 0 1 3 T h e h i g h n u m b e r p r o f i t a b i l i t y o f 3 5 7 e x p l a i n e d thatD2Dachievedagoodearning sbyincreasingdebtratiofrom
2011to2 0 1 3 Incontrast,FLCGroup(HSX:FLC)showeditsscatterplotat(0.07:-4)whichdemonstratedadownwardsignofbusinessperformance.
R- squaredlinearisequalto0.793saysthat79.3%ofthevariationinv o l a t i l i t y (Y)isexplai nedobviouslybythelinearrelationwithdebtratio(X).Thisleaves2 0 7 % o f t h e v a r i a t i o n i n v o l a t i l i t y l e f t t o b e e x p l a i n e d byo t h e r f a c t o r s (except X) Therelationshipofdebtratioandvolatility(X:Y)showsthenegativetrendba singonthedownwardslopeofR-squaredlinear.
(HNX:PFL)continuouslyp e r f o r m e d downwardbusinessearningswhichE B I T D A’ s growth decreasedoverseven t i m es since2010 M o r e o v e r , PVCPetro
Development(HNX: PTL)and PV2InvestmentJSC (HNX:PV2) showedthehighnumberofv o l a t i l i t y duetone ga ti ve p r o s p e c t s o f g r o w t h a n d d
Basingonresultsoftable4.1,thewritercontinuestouset- testtocheckthesi g n i f i c a nt correlationbetweendebtratioandeachofdeterminants.Thehypot hesisH 0is equaltozerowi ll presentthesignificant correlation betweent wo variables ,whileH0differsfromzerowillshownorelationshipbetweenthosetwovariables.
Asshownintable4.2,theresultsfromregressionmodel(FEMm eth o d o l o g y) b e t w e e n d e b t r a t i o a n d e a c h ofdeterminantss u c h a s d e b t i n t e r e s t , depreciation ratio,prof itability,size,andvolatility areconcludedthatallofd et e r m i n an t s hadtheirt- statisticvaluesaresurpassedthetestofsignificantlevelat1 0 % Their t-statisticfellbeyondthe rangefrom-1.363 to+1.363(Seein
Appendix2,3,4,5,and6).Therefore,wecouldrejectthehypothesisH 0is equaltozero.
Fromthetable4.3,wecanconcludethattherearelargedistancesbetwee nmax i m u m valuesandminimumvaluesinyearbasis.Whilelargerealestatecomp aniesareacquiringhugeamountsoftotalassetbyacceptingthehighratiosofd e b t overe quity,whereassmallercompaniesperformedlowdebtlevels.Forexample,V i n g r o u p JSC.
2013byaveraging370.5%.Thetotalliabilityalsoheldana v e r a g e o f 7 4 % i n i t s t o t a l a s s e t i n t h e samep e r i o d o f time.O n t h e o t h e r h a n d , C en tu r y 21JSC.
(HSX:C21)remainedlowlevelofdebtforfouryears,averaging1 8 5 % ofdebttoe quityand15.5%ofliabilitytototalasset.Thiswouldexplaintopositivetrendbetwe enhighdebtratioandreputationorlargeamountsoftotalasset.Whenthecreditagenciesconsi dertogivethelendingcreditsbetweenVICandC21,theypreferVICtoC21basingonassetv aluations.Themorecapitalintotalassets,theeasiertheownerofthiscompanycanraiseth edebtlevels.
In 2012, the Vietnamese economy faced significant challenges, including declining aggregate demand, high inflation, and rising debt levels, with debt-to-equity ratios reaching 141.6% and 114.5% respectively The ratio of liabilities to total assets exceeded 50% in both 2011 and 2012, reflecting soaring interest rates, as many commercial banks and credit agencies offered rates over 20% per annum Despite sharp declines in revenue sales, real estate enterprises continued to increase their debt levels to maintain market presence The growing standard deviation during these years indicated high volatility, which ultimately posed risks of excessive debt and potential bankruptcy for real estate companies.
ResultsofRegressionModel
MulticollinearityTestbyCorrelationMatrix
Totestmulticollinearityofregressionmodel,thewriterbasesoncorrelationm atrixt o c h e c k w h e t h e r o r n o t e a c h p a i r o f t w o v a r i a b l e s i s h i g h c o r r e l a t e d Byo b se r v i n g t h e c o r r e l a t i o n t a b l e , thep a i r o f D E B T _ I N T E R E S T a n d S I
Z E i s q u i t e s ig n i f i c an t coefficientcorrelation,whichisrecordedat 0 494. Thisalsoconsidersd o u b t f u l ly thatthispairmayappearmulticollinearyphenomenon.
DEBT_INTERESTnowisquestionablevariableinregressionmodelbasingo n t w o r e a s o n s F i r s t o f a l l , D E B T _ I N T E R E S T h a s n o s t a t i s t i c a l s i g n i f i c a n c e a t l ev el of1 0% withlowimpactonmodel(0 0 02 %) Secondly, a quit ehighcorrelationofDEBT_INTEREST andSIZEmayleadtomulticollineari tyinr e g r e s s i o n model.ByapplyingW-
UsingWald- TesttoAdjustCoreRegressionModel…………… 364.5.3RegressionModel…
Testtocheckwhetherornottheunnecessary presenceofdeterminants Thehy pothesisH0:INTERESTwillbesetequallytozero.TheresultannouncedthatF- statisticisequalto0.485andP- valueise q u a l to0.627,whichislargerthan0.10.ItmeansthatDEBT_INTERESTh adnostatisticalsignificanceatlevelof10%.Intheconsequences,thedeterminantnamelyD
Firstofa l l , t h e re a re f e w considerationsabout th e presence of D E B T _ I
N T E R E S T i n regressionmodel.The coefficientofDEBT_INTEREST performsaninsignificantimpact(𝜷=0.002)onregressionmodel.Thise x p l a i n e d whendebtinterestexpensesincreasedby1%,thelevelofdebtwouldriseroughly 0.002%.Thelendinginterestraterosedramaticallyfrom2010to2013,andsurpassedmo stlyover20%perannumfromcreditagencies,whichwouldleadtohigherinterestexpense s.Itisveryambiguoustodistinguishbetweenrisinginterestr a t e andhigher debtratiowhich caused interestexpensestoescalate uncontrollably.I n short,DEBT_INTERESTwouldremovetotheregressionmodelist otallylogical.
Intable4.5,R-squaredshowsthesameleveltoinitialR- squared(0.863or86.3%),whileadjustedR- squared=0.814ishigherthaninitialadjustedR-squared
DEPRECIATION_RATIOandPROFITABILITYhavestatistical signi ficance a t l e v e l o f 1 0 % , w h i l e S I Z E a n d V O L A T I L I T Y i n d i c a t e s t a t i s t i c a l significance a t l e v e l of5 % T h e l a r g e s h i f t b e l o n g s toD E P R E
C I A T I O N , w h i c h jumpsupfromthep- valueof0.048(4.8%)to0.053(5.3%),andstatisticals i g n i f i c a n c e alsochangesf romlevelof5%tolevelof10%consequently.
Jarque-BeraTestforNormality(inResiduals) ………………… 374 6 ResultExplanations……………………………………… ………… 38C H A P T E R V:CONCLUSIONS
B e r a methodology( B o w m a n & S h e n t o n , 1 9 7 5 ) T h i s t e s t s t a t i s t i c c o m p a r e d t o chi- squareddistributiontomatchthenormaldistribution.ThehypothesisH0:Residualsa r e n ormaldistribution.Thevalueofp-valueisequaltozero(Jarque-
(SeeinAppendix12).Itmeansthatweconfirmativelyrejectthenull hypothesis.Inshort,theresidualsarenotnormaldistributioninregressionmodel.
FromtheFEMregressionmodelintable4.5,𝜷�i sequalto-0.933 showst h e inverserelationshipbetweendepreciationratioandde bt ratio.I n case t h e rest of determinantdidnotchange,whentheratioofdepreciationtototalassetsincreasedby 1%,s o t h e d e b t r a t i o w o u l d d e c r e a s e t o -
0 9 3 3 % T h e i m p a c t o f d e p r e c i a t i o n r atio seemstobelogicaltodebtratio.Th emoredepreciationtheenterprisessettob e , thelessvalueoftotal assetswillbe Int he consequences,the dec li ne oftotalasset’svaluewouldleaddebtratiotoi ncreaseuptonewhighlevel,iftherewasaconstanttotalliability.
With𝜷 2is equalto0.117,sizeofcompaniesalsomadeasignificante f f e c t ond e b t r a t i o I t i s q u i t e s i m p l e t o u n d e r s t a n d t h a t t o t a l a s s e t i s b u i l t u p b ydebt structure.Forexample,$1oftotalassetiscomingfrom$0.7oftotalliabilityand
$0.3oftotalequity.Anincreaseof1%ofcompany’ssizewouldleadthedebtratioalsomo veup0.117%.Itisnodoubttoconsiderthattrade- offtheoryisabsolutelyt r u e i n t h i s s i t u a t i o n T h e h i g h i n c r e a s e i n t o t a l a s s e t w i l l r e f l e c t t h e e n t e r p r i s e s ’ growthambitions.Firmstendtoexploitaggressivel y higherlevelsofdebtoroptimaldebtlevelinordertospreadouttheirbusinessmarketsh ares.Inshort,thelarger amountoftotalassettheownershave,thehigherlevelof debttheytendtosuffer.
The performance of business operations reveals a significant relationship between profitability and debt levels, with a statistical significance of 0.028 at a 10% level When profitability increases by 1%, the debt ratio also rises by 0.028% This suggests that higher profitability in operating businesses may stem from increased debt levels However, given the low impact of the debt ratio, this conclusion may not hold in different economic contexts This aligns with the pecking order theory, which posits that real estate enterprises with strong profitability or retained earnings are likely to fund their projects without seeking additional loans Consequently, this trend of rising profitability year after year could lead to a decrease in the debt ratio.
Finally,thedeterminantnamelyvolatilitypresentingtheriskonorriskof frelatedt o p r o f i t a b i l i t y , s h o w s t h e𝜷 4i s e q u a l t o 0 0 4 0 ( s t a t i s t i c a l s i g n i f i c a n c e atlevelof5%).Thepositiverelationshipbetweenvolatilityanddebtratioisd e f i n i t e l y logicalandmeaningful.Whilevolatilityexposestheriskfrombusinessactivities,t h e debtratioperformstheriskfromfinancialleverage.Thehigherpercentag eofv o l a t i l i t y o r t h e r i s k o f b u s i n e s s a c t i v i t i e s i s , t h e h i g h e r r i s k o f f i n a n c i a l s t a t u s throughbyhigherdebtratiowillbetriggered.
Someargumentsandopinionswillbepresentedinthischapter.Ingener al,althoughregressionmodelexplainedquitewellthesignificantlevel,itstillremainsso melimitationsanddifficulties.Therearefivemainpartsinthischapter,includings u m m a r y ofresearchmethodology,majorfindings,policyimplications, limitations,and furtherresearches.
SummaryofResearchMethodology………………………………….405 2 M ajorFindings……………………………………………………… 415 3 PolicyImp lications
The regression model revealed a significant 86.3% impact of various determinants on the capital structure of listed real estate companies in Vietnam from 2010 to 2013 Key factors included depreciation ratio, company size, profitability, and business activity volatility Despite the stock market crashes hindering capital mobilization for listed enterprises, the State Bank of Vietnam implemented expansionary monetary policies to encourage increased debt levels However, companies must carefully weigh the balance between interest rates and risk when considering additional financial leverage.
Secondly,thethesisresearch resultsprove thatdepreciation ratioand company’ssizearetwomainfactorsputtingthedominatedpressuresondebtratio,p r e s e n t - 0.933%and0.117%respectivelyinthecrisisstage.Thenegativesignofdepr eciation demonstrates thatthe lower valueoftotal asset will leadto higher debtratioifthereassumesaconstant totalliabilities Thetrade- offtheoryalsoobviouslys p e c i f i e s thatanincreaseintotalassetwilltrade- offwithhigherfinancialleverages.
Finally,thetheoryofpeckingorderseemstoprovideunclearevidenceso fprofitabilitytocapitalstructure.Inthisresearchpaper,theregressionmodelonlyp o i n t s o ut t h a t a r i se o f p r o f i t a b i l i t y ofo p e r a t i n g b us i n e ss ha s b e e n cre ate d fro mincreasinglevelsofdebt.However,increasingprofitabilityyearbyyearmaylower thedebtratiobecauseenterprisestendtosupportfortheircurrentprojectswithou tborrowingmorebudgetfromcreditinstitutions.The writerdoesnothavee noughevidencetoconfirm whetherornotpeckingordertheorymadeanimpact oncapitalstructure.
Basingonresultsofregressionmodel,thisresearchpapersomehowexplainstheim pactofeachdeterminanttolistedrealestateenterprises’capitalstructure.Thetrade- offtheorydemonstratescorrectlyitseffectsontotalassettocapitalstructurew h i l e p e c k i n g o r d e r p r o v i d e s a m b i g u o u s l y i t s impactonp r o f i t a b i l i t y t o c a p i t a l structure.ThewriterfoundthatFixedEffectModelgavethesignific antresultsind a t e d paneldataratherthanRandomEffectModelbasingoncomparin gR- squaredstatisticsa n d H a u s m a n t e s t A l t h o u g h t h i s modelf a i l s t o a p p r o v e n o r m a l d i s t r i b u t i o n , butthereisnoeffectofmulticolinearityandnon- linearequation.
Firstly,f r o m t h e r e s e a r c h r e s u l t s , t h e f i n a n c i n g c a p i t a l d e c i s i o n s d i d n o t p e r f o r m exactlytheimpactof Pec ki ng Orderbyusingreta inedprofitto raisethe workingc a p i t a l Itmeanst h a t t h e b o a r d o f m a n a g e m e n t p r e f e r s tou s e e x t e r n a l fi nan ci ng b u d g e t s byi s s u i n g n e w b o n d s o r s t o c k s r a t h e r t h a n i n t e r n a l f i n a n c i n g capital.T h i s r e s u l t i m p l i e s thatl i s t e d c o m p a n i e s a r e t a k i n g a d v a n t a g e s o f s t o c k markettoraisepreferen tialcapitalbygovernment’sencouragement.However,thea b u s e ofdebtfinanc ingisalsopointedoutthehardpressuresonbankingsystem,securitiesmarkets,andthecorporategovernancestructureofthelistedfirms.
Thesecondpolicyimplicationsis thattheTrade- offtheory performedlessimpactonVietnameseevidenceduetocentrallyplann edeconomy.Thestatekepti t s consolidatedstakesinsomelistedrealestatecompa niestocontrolmanagement governance.Itmeansthatthecostoffinancialdistressessuchasbankruptcycostsa n d a g e n c i e s c o s t s a r e n o t s i g n i f i c a n t M o r e o v e r , somec o m p a n i e s enjoyedt h e p r e f e r e n t i a l t a x es bysupporto f l o c a l g o v e r n m e n t I f t h e V ie tna mese g o ve r n m e n t didn ot c h a n g e i t s a d m i n i s t r a t i o n t o wa r d s l i s t e d co m p a n i e s, t h e s e companiesf e e l s a f e eveninthecrisiscomparedwiththeircompetitio nsintheprivatesector.
Althoughreceivingthegoodresultsfromregressionmodel,butthelimitationo fdataset (from2010to2013),whichonlyshowsthecentral stageofcrisis,causestheunclearconfirmationabouttheefficiencyofpeckingordertheory.
Besidest h a t , t h e w r i t e r c o n s i d e r s t h a t t h e l a c k o f e x t e r n a l d e t e r m i n a n t s o f governmentinterventions(riskofpolicies,thelandownershipcertificatep r o c e d u r e s , e t c ) a n d s p e c i f i c a t i o n s o f e a c h c o m p a n y ( h i s t o r i c r e p u t a t i o n s , mana gement decisions,thegrowthdevelopment),woulddefinitelychangethec u r r e n t re sults.
Vingroup (HSX: VIC) and Hoang Anh Gia Lai Group (HSX: HAG) stand out in the real estate sector with total assets of approximately 750 trillion VND and 300 trillion VND, respectively, significantly surpassing their peers While other real estate companies face challenges in raising debt, VIC and HAG continue to have strong opportunities to secure funding from external credit institutions due to their high credit ratings However, the limited dataset restricts the ability to eliminate these outliers.
Someofl i s t e d rea lestate c o r p o r a t i o n s hav e d i v e r s i f i e d sec to rs inb u s i n e s s r ev en u e s F o r ex am p l e , HoangAnhGia LaiGroup (HSX: HAG)is a typicald e m o n s t r a t i o n ofexternal investments Last year,sugarcaneandrub berwere t wo largestsectorstocontributeover7 0 % ofHAG’srevenues.F u r t h e r m o r e
, f o r T h u D u c House(HSX:TDH),over32%ofrevenuebreakdowncamefromi mportand exports e r v i c e s o f a g r i c u l t u r a l p r o d u c t s i n 2 0 1 3 D r e a m H o u s e I n v e s t m e n t C o r p
(H S X: DRH)announcedthatin 20 13, o v e r 80 % ofr eve nu e breakdown bas edonchemicalsa n d f e r t i l i z e r s I t isq u i t e r e a s o n a b l e tou n d e r s t a n d t h i s s t r a n g e p h e n o m e n o n duetothefrozenliquidityofrealestatemarket.Th eseaboveenterprisesmustexpandtheirtraditionalbusinesstoothersectors,whichhel pthemt o surviveinthecrisis.Ingeneral,thiswouldputthepressureontheconfidenceo fr e s e a r c h study.
Forfurtherresearch paper, asufficient data set,including a longperio doft im ea n d l i s t o f r e a l e s t a t e e n t e r p r i s e s , w i l l p r o v i d e m e a n i n g f u l c o n c l u s i o n s t o persuadecompletelythereaders.Therefore,theeffici encyofstudyinrealitytendstoincreasesignificantly.
Focusingoneachofthecompanies’revenuebreakdowntodistinguishb e t w e en mainrealestateactivitiesandexternalbusinesses.Infact,inhardstageofrealestat esector,therearealotofexamplesmentionedthechangesoftraditionalb u s i n es s activitiestoavoidthebankruptcy.Hence,itwillhelpthestudytou n d e r s t a n d sp ecificallythefinancialdecisionsandgrowthdevelopmentsfromeachr e a l estatemanag ements.
Thel a s t l i m i t a t i o n i n t h i s r e s e a r c h p a p e r i s t h a t t h e f i n a n c i a l s o l u t i o n s oradvicesdidnotnotice toimprovethereal estate com pa nie s The w ri t er feels thisi s s u e tobequitecomplicatedwhenmostoflistedrealestatecompa niesaremuchdepending ongovernmentpolicies.ItcanbeexplainedthatViet namisreformings l o w ly about p r o p e r t i e s p o l i c i e s a n d r e g u l a t i o n s Whent h e p o l i c i e s a r e c h a n g i n g quickly,theallocationsofdisbursementalsogoesaw ayfromoriginalpredictions.T h e s e obstaclesareconstrainingthedevelopmentofcompet itiverealestatemarket.
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5 CLG CotecInvesment&Land-HouseDevelopment HSX
17 HQC HoangQuanConsulting-Trading-RealEstate HSX
DependentVariable:DEBT_RATIOMet hod:PanelLeastSquares
Variable Coefficient Std.Error t-Statistic Prob.
AdjustedR-squared 0.795593 S.D.dependentvar 0.175750 S.E.ofregression 0.079459 Akaikeinfocriterion -2.011874
DependentVariable:DEBT_RATIOMet hod:PanelLeastSquares
Variable Coefficient Std.Error t-Statistic Prob.
AdjustedR-squared 0.801096 S.D.dependentvar 0.175750 S.E.ofregression 0.078382 Akaikeinfocriterion -2.039161
DependentVariable:DEBT_RATIOMet hod:PanelLeastSquares
Variable Coefficient Std.Error t-Statistic Prob.
AdjustedR-squared 0.805242 S.D.dependentvar 0.175750 S.E.ofregression 0.077561 Akaikeinfocriterion -2.060228
DependentVariable:DEBT_RATIOMet hod:PanelLeastSquares
Variable Coefficient Std.Error t-Statistic Prob.
AdjustedR-squared 0.793561 S.D.dependentvar 0.175750 S.E.ofregression 0.079853 Akaikeinfocriterion -2.001978
DependentVariable:DEBT_RATIOMet hod:PanelLeastSquares
Variable Coefficient Std.Error t-Statistic Prob.
AdjustedR-squared 0.816051 S.D.dependentvar 0.173072 S.E.ofregression 0.074229 Akaikeinfocriterion -2.136319
Method:PanelEGLS(Cross- sectionrandomeffects)Dat e: 12/13/14T i m e : 11:28
Variable Coefficient Std.Error t-Statistic Prob.
APPENDIX 8 :RESULTSOFREGRESSIONMODELTOCAPITALSTRUCTURE F ROM2010TO2013(FIXEDEFFECTMODEL)
DependentVariable:DEBT_RATIOMet hod:PanelLeastSquares
Variable Coefficient Std.Error t-Statistic Prob.
AdjustedR-squared 0.813149 S.D.dependentvar 0.175750 S.E.ofregression 0.075970 Akaikeinfocriterion -2.090204 Sumsquaredresid 0.940750 Schwarzcriterion -1.161139 Loglikelihood 295.1028 Hannan-Quinncriter -1.715188
APPENDIX 9 : RESULTS OF REGRESSION MODEL TO CAPITAL STRUCTUREFROM2010TO2013EFF
Variable Coefficient Std.Error t-Statistic Prob.
AdjustedR-squared 0.814020 S.D.dependentvar 0.175750 S.E.ofregression 0.075793 Akaikeinfocriterion -2.097685 Sumsquaredresid 0.942113 Schwarzcriterion -1.183851 Loglikelihood 294.9407 Hannan-Quinncriter -1.728817
WALD-TEST TO VERIFY THE PRESENCE OF
TestStatistic Value df Probability t-statistic 0.485865 163 0.6277
Variable Fixed Random Var(Diff.) Prob.