Determinants affect the access to formal informal credit and its impact on sales growth

PROBLEMSTATEMENT

Smallandm e d i u m scaledenterprises( S M E s ) p l a y asignificantr o l e i n economicdevelopm ent.D a t a collectedfromM i n i s t r y ofP l a n n i n g andInvestment(MPI)showedt h a t S M E s co ntributedabout40%toGrossDomesticProduct(GDP),30%tototalexportturnover,and15%togover nmentrevenue’scontribution.Furthermore,SMEsalsoplaycriticalroleintermofemploymentgene rationandmakeajob forover60%employees.

However,ac co rd in g to t h e reporto f MPIin2 0 1 2 , returno n revenueof SME s stayedat2 8

% in2007anddecreasedto2.34%in2009.Inaddition,basedonthedatasetcollectedfromGeneralStat isticsOffice(GSO)ofVietnamin2011showedthatSMEsrepresentedjustover4 3 % aggregategr ossincomeofallendeavorsandjustunder14%aggregateprofitbefore duty.These numbersarequitemodestcomparedto SMEs’contributiontoeconomy.

Capital is a crucial input factor for manufacturing and business operations According to data from the Central Institute for Economic Management (CIEM) in 2013, out of over 2,500 SMEs surveyed, 74% accessed financing sources, with formal loans comprising approximately 72% Informal loans and a combination of sources accounted for about 20.24% and 7.83%, respectively Among the 662 firms that applied for bank loans, only 158 reported difficulties in obtaining financing, primarily due to administrative hurdles in securing bank clearance and a lack of collateral.

Numerous empirical studies demonstrate the positive impact of formal finance on firm performance Ayyagari, Demirgüç-Kunt, and Maksimovic (2010) analyzed data from Chinese firms in 2003 and found that financing from official sources significantly enhances firm performance, while informal financing does not yield the same benefits Similarly, Saeed (2009) highlighted that formal financing positively influences firm outcomes, whereas informal sources can diminish these results In practice, many enterprises struggle to secure full funding through standard mechanisms, often resorting to alternative sources such as family, partners, relatives, or even the black market to meet their financial needs.

Alongwithofficialsourceoffund,non- officialfinanceinsomeempirical studiesisalsoconsideredasanalternativechanneltofillin the demandforfinanceoffirms, especiallyindevelopingcountrieswheretheweaknessoffinancialand legalsystemexist.Thiscanbeseenc l e a r l y through A l l e n , C h a k r a b a r t i , De,andQ i a n (

2 0 1 2 ) ’ss t u d y whent h e y d o researchf o r s m a l l andmediumsized enterprisesinIndia.Theau thorsclaimedthatnon- legalgovernancemechanismsdominatelegalmechanismi n solvingd i s p u t e s , o v e r c o m i n g bureaucraciesandfosteringfirm’sperformance.Inanotherstudy,suchasDegryse,Lu,andOngena(2 013),theauthorsuggestthatthecombinationofformalandinformalfundisanoptimalchoicefor smallfirms,especiallyin emergingcountries,where asymmetric informationis prettysevere.

Therearemanysourcestofinancefirm’sbusinessoperationsuchasfromretainedearnings,issui ngstocks,borrowingfromfinancialinstitutionsorevencombinationtwo- threet h a t ofsources.Duetoanimportantroleofcapital,manyempiricalstudiesworldwideinvestig atet h e r e l a t i o n s h i p betweens o - c a l l e d capitalstructureandf i r m performance.T h e structureofcapitaldescribesthewaythatfi rmsraisedtheirneedstoestablishorexpandtheirbusinessactivities.Inotherwords,capitalstructu reisdefinedas“therelativeamountofdebtandequitythatfirmsneedtofinance”(T.D.K.Nguyen&Ramachandran,2006).Figure1.1presentsthecategorizationofcapitalstructureforfurtherinforma tion.

Whiletherearemanyempiricalstudiesexploretheconnectionbetweeninternal- externalfinanceorbankcreditandcreditconstraintonfirmperformance,veryfewpapersevaluatethei mpactofformaland informal financeonsalesgrowth.

RESEARCHOBJECTIVE

RESEARCHQUESTIONS

This studywill investigatethedeterminantsaffecttheaccesstoformaland informalfinanceanditsimpactonSMEs’salesgrowthbyu s i n g s m a l l andmediumsizedenterpris esinVietnamin 2013 Thereisalot ofinformationin thistypeofdataset,howeverIjustcollectthedataregardingto theaccess toformalandinformalfinance. 1.55THESTRUCTUREOFSTUDY

Therearefivechaptersinthisstudy.Chapter1describesproblemstatement,researchobjective,ands copeo f t h e study.C h a p t e r 2 discussest h e relatedliteratureandpreviousempiricalstudies.Dat aandmethodologyareillustratedinchapter3.Fortheempiricalresultsw e canfind inchapter4,andchapter5concludestheresearch.

Figure 2.1 The expected rate of return of lenders

Chapter2 reviewss o m e relatedliteraturesaswellasempiricalr e s u l t s derivedfrompreviou sstudiesinthesimilarconsideredproblems.Thefirstsectionpresentstheoriese x p l a i n i n g accesstofinanceoffirms,aswellasareviewofempiricalstudiesaboutthisissue.T h e reviewo n theo riesandempiricalstudieso n t h e impactso f financingchoiceandsalesgrowtharepresented in thenextsection

Asymmetricinformationisconstruedasonehasmoreadvantageousinformationthantheother sinthe sametransaction.Thebehavior oflenderinasymmetricinformationshouldbe explored firstlytounderstandthemechanismwhysomeapplicantsreceiveloan,butsomedon o t AccordingtoJaffeeandStiglitz(1990),theexpectedrateofreturnoflendersisrepresenteda safunctionofquotedinterestrate, and ithasconcaveshapeasinFigure2.1: whereverticalandh o r i z o n t a l a x i s arerepresentedbyexpectedrateo f r e t u r n o f l e n d e r s an dinterestrate,respectively.r* is theoptimalinterestrate

Thereexistsanexcessofdemandforcredit,itisundoubtedthatlenderswillincreasetheirl o a n int erestrate,whichisseenasthepricehastobepaidforborrowingmoney.Accordingtot h e l a w o f de mandandsupply,ani n c r e a s e i n pricewillleadt o adecreasei n quantitydemandedanda risein q u a n t i t y supplied,until marketclearing isrestored.However,attheo p t i m u m quotedinte restrate(r*),thereisnoincentiveforlenderstoraisetherateofinterest.T h i s i s becauseoft w o rea sons:a d v e r s e s e l e c t i o n andmoralhazard,whicha r e discussedhereafter.

Iftherateofinterestincreases,saferapplicants,whoneedfundtofinanceprojectswithl o w r i s k andl o w return,w i l l b e unablet o p a y at highinterestrate,anddroppedo u t o f t h e market.Incont rast,riskierapplicants,whohavehighriskandhighreturn,areonlyremainingi n themarket.Thiswi llleadtoanincreaseinriskofdefaultonloan(apromiseofrepaymenti s broken),so adeclineinlenders’expectedrateofreturn(Stiglitz&Weiss, 1981)

Themoralhazardrepresentsthesituationinwhichindividualorcooperation(borrowers)doesn othaveanincentivetodoaswhattheycommittedinthecontractafterthetransactionhadbeencarr iedout.Accordingly,inordertooffsetthehighinterestrate,theborrowersarem o r e likelytoun dertakeriskyprojects,this will lead to ahigherrisk ofdefaultoncredit,andalowerlenders’expectedrateofreturn.

Asthoseproblemsmentionedabove,althoughfacingtheexcessdemandforcredit,lenderswoul dnotrespondtomarketbyincreasingtherateofinterestforborrowers.Andint h i s situation,alth oughtherearepeoplew h o arewi ll in g topayatahigher levelofinterest,lendersremainunchanged atthelevelofoptimalinterestrate,andlimitloanforborrowers.Ino t h e r words,firmsare constrictedcreditin asymmetricinformation.

According to this theory, small firms must carefully choose the amount of debt and equity financing they utilize to balance the associated benefits and costs Debt financing offers advantages over equity financing, primarily because interest payments are tax-deductible, while equity income is subject to corporate tax However, increasing debt can also heighten financial risk, making it less cost-effective compared to equity financing As debt financing rises, firms may experience an increase in marginal costs and a decline in marginal benefits To optimize their overall value, firms should strike a balance between the benefits of tax shields and the costs of financial distress, effectively trading off the proportions of debt and equity financing to achieve equilibrium.

Besides,followtrade- offtheory,firmshavemoretangibleassetsandmoreprofitablearepredictedt h a t a r e l i k e l y t o o b t a i n highdebtratio,w h i l e e q u i t y financingi s anticipatedf o r t h o s e firmswithhighintangible assets.

Int h i s theory,b o r r o w e r s , e s p e c i a l l y s m a l l f i r m s , t e n d t o u t i l i z e internalfinancefi rstly,followedbydebt,andf i n a l l y externale q u i t y i s considered(Myers& M a j l u f , 1 9 8 4 ) T h e s e prioritiesreflectcostofvariousfinancingsourceswhereexternalequity’scostishigherthant h e others.Asaresult,externalequitymaynottheoptimalchoicetowardssmallenterprises,t h i s isbecauseofsomereasonsasfollows:i/

Stockmarketflotationisveryexpensiveandtheinitialpublicofferingsareunderpricing,t h e s e thin gscreatedisadvantagesf o r s m a l l enterprises.ii/

Foragivenlevelofrisk,highercostofequityissubjected bysmallfirmsascomparedtolargec ounterpartsduetosmallfirmeffectwhentheyo b t a i n stockmarketflotationi i i /

Awidershareownershipisoneofth e prerequisitesforstockmarketflotation.Howevert h i s m a y l e a d t o l o s s o f controlo f initialmanagerso r t h e problemo f takeoverp o s s i b i l i t y

Agencytheoryclaimedthatthereismoralhazardandadverseselectionproblemexistsincontra ctualarrangementsbetweens m a l l firmsa n d lenders.Thesep r o b l e m s arel i k e l y t o b e m o r e s evereandthecoststosolvethembyusingmonitoringandbondingareveryexpensivef o r smallen terprises.Anotherwaytosolvetheseproblemsisusingmorecollateralinlendingt o smallfirmsto avoidagencyproblemsandhelpbankstoaligninterests(Chittendenetal.,1 9 9 6 )

Abovei s t h r e e i m p o r t a n t theoriesr e l a t i n g t o f i n a n c i n g d e c i s i o n s , andthroughoutm anyempiricalevidences,pecking orderanda g e n c y theoriesseemtobe supported overtrade -off t h e o r y (Chittendenetal.,1996)

Inordertoinvestigatethedeterminantsaffectfinanceaccessibility,mostofpapersp r i m a r i l y focusonthe accessto formalloan rather thaninformalloan, andvery fewpapersexamin edb o t h financingsourcessimultaneously.Int h e i r regressionm o d e l s , t h e dependentvariabless uchasformalandinformalchoicesareusuallybinaryvariable,whichisafunctiono f firmage,firmsi ze,firmownership,owner’seducation,owner’sgender,theageofmanager,collateral,andnetworks.

U s i n g firm- leveldata,andm o s t l y employedlogitm o d e l (thereisonepaperusedmultivariableprobitmodel)to finddownfactorsaffecttheprobabilityo f accessto thesefinancingsources.

Research on the determinants of formal finance accessibility indicates that firm age and size have a significant positive effect on obtaining official loans, though results are mixed for informal finance options Specifically, older firms tend to have better access to informal finance (Essien & Arene, 2014) Conversely, young firms, particularly those owned by women, often struggle to accumulate sufficient social capital and assets, making it challenging to secure bank loans; thus, non-official loans become a viable alternative for these enterprises (Akoten, Sawada, & Otsuka, 2006) Additionally, firm size does not appear to influence access to informal credit (Essien & Arene, 2014) Ownership type also plays a role, as private firms are less likely to access official credit compared to state-owned firms (Kumar & Francisco, 2005).

Empirical studies indicate that better-educated owners tend to have easier access to credit (Nikaido, Pais, & Sarma, 2012), although Rand (2007) suggests the opposite may be true The relationship between gender and formal credit access remains unclear; while many studies assert that male-headed firms have an advantage in securing bank loans, Yaldiz, Altunbas, and Bazzana (2011) propose that formal credit may be more accessible for female-owned enterprises Some research indicates no significant difference in credit access between men and women (Fatoki & Asah, 2011; Harrison & Mason, 2007), yet female-owned firms often rely on informal credit due to asset shortages (Akoten et al., 2006) The impact of owner age on credit access is also ambiguous; younger owners are often perceived as inexperienced and may borrow from friends and family rather than formal institutions, although Vos, Yeh, Carter, and Tagg (2007) note that young managers tend to utilize bank loans more than older counterparts Additionally, collateral significantly enhances the likelihood of accessing formal credit Lastly, the effect of networking on credit accessibility is complex, with most studies highlighting a positive correlation between strong connections with lenders and credit access, while relationships with government officials can negatively impact bank financing (Le, Venkatesh, & Nguyen, 2006).

Tosumup,basedontheoreticalliteratureandmanyotherempiricalstudies,factorsaffectcredita c c e s s i b i l i t y c a n b e dividedinto3 s u b - groupsi n c l u d i n g owner/ manager’scharacteristics,firm’scharacteristicsandnetworks

Owner’sage,educationandgendercanbeaddedintheregressionasproxyvariablesforowner’sc haracteristics.

Junior managers, often perceived as inexperienced due to their youth, typically face challenges in social interactions that limit their social capital, making it harder for them to secure bank loans (2006) Research indicates that young owners, aged 21 to 35, are more inclined to borrow from friends and family rather than formal financial institutions, aligning with findings by Omboi and Wangai (2011) In contrast, senior managers tend to accumulate assets that can serve as collateral, granting them easier access to formal financing However, a study by Vos et al (2007) suggests that younger entrepreneurs are actually more likely to seek external financing options, such as bank loans and overdrafts, compared to their older counterparts.

Intermofthesecondowner’scharacteristic,theeffectofeducationonabilitytoaccessinstitut ionalcreditisfoundmixed.Educationalattainmentisseenasanimportantly positiveindicatorind emandfor institutionalcreditofsmall firmsbyO mb oi andWangai(2011).Inl i n e withthisstat ement,Nikaidoetal.

Research indicates that firms with better-educated owners are generally able to access credit more easily due to their superior understanding of application procedures and enhanced managerial skills in finance, marketing, production, and international business (Kumar & Francisco, 2005) However, a study by Rand (2007) suggests that highly educated owners may actually experience a negative impact on their likelihood of securing credit, as they tend to avoid applying for bank loans if they anticipate a high chance of rejection.

Owner’sgenderi salsoconsideredaso n e o f t h e factorsaffectst h e a b i l i t y toaccesst o bankcr edit.Femalemanagersfacemanyd i f f i c u l t y i n o b t a i n i n g b a n k l o a n d u e t o lacko f assets,whicharerequiredbyformalinstitution,sotheydependmoreonmicro- financesector(Akotenetal.,2006).OmboiandWangai(2011)claimedthatdemandforinstitution alcredit offemalesownedfirmsarefoundtobelessthanmalesownedfirmsduetosomeofculturaln o r m s Furthermore,a c c o r d i n g t o Nikaidoetal.

Research indicates that women-owned firms face greater challenges in accessing credit compared to their male counterparts, primarily due to their underprivileged status and lack of collateral (Toni et al., 1998) However, some studies suggest that there is a positive relationship between women and bank credit, with no significant differences in institutional loan applications between genders (Fatoki & Asah, 2011; Harrison & Mason, 2007) Furthermore, obtaining bank loans may be easier for women, leading them to rely less on informal lending mechanisms (Yaldiz et al., 2011).

Oneofthemostimportantindicatorsthataffectcreditaccessibilityaswellasfirmperformanceisf irmsize.Dependonthepurposeofresearch,andtheavailabilityofdata,firms i z e canbeproxiedby totalemployees(Becchetti&Trovato,2002;Klapper,Sarria-Allende,

&Sulla,2002),totalsales(Degryseetal.,2013;Rahaman,2011)ortotalassets(Allenetal.,2 0 1 2 ; Essien&Arene,2014;Rahaman,2011).Bigstenetal.

(2003)arguedthatwhilelargerfirmsaremorelikely too b t a i n bankloan,itgoesopposite dire ctionforsmaller ones.Beck,

Demirgüç-Kunt and Maksimovic (2005) analyzed a firm-level database across 54 countries and highlighted the significant impact of firm size on credit accessibility They found that small and medium-sized enterprises (SMEs) encounter greater challenges related to financial, legal, and corruption barriers compared to larger firms These obstacles negatively affect the performance of SMEs, aligning with Saeed's (2009) findings, which suggest that smaller firms face more financial constraints Due to their inability to provide the necessary information and collateral required by banks, SMEs tend to rely more on non-market sources of finance than their larger counterparts.

Okura (2008) highlights the significance of firm size in accessing credit, noting that smaller firms rely more on informal credit, internal funds, and equity, while larger firms receive over 40% of their working capital from formal institutions, compared to just 16% for smaller enterprises This creates a positive correlation between bank accessibility and firm size Kumar and Francisco (2005) identify several challenges small firms face in securing bank credit, primarily due to market imperfections that result in informational opacity and poor financial reporting, making it difficult for creditors to assess the firm's quality (Binks & Ennew, 1996) Additionally, small firms are perceived as riskier due to their limited ability to diversify outputs and client bases (Klapper et al., 2002) Information asymmetry, including adverse selection and moral hazard, further complicates credit access, leading to credit rationing by commercial banks (Stiglitz & Weiss, 1981) To mitigate these issues, small firms often resort to posting collateral (Angelini & Di Salvo).

&Ferri,1998).However,whilelargerfirmsoftenownmoreassetswhichcanbeprovidedascollater alinbank’sperspective,smallfirmsfacemoredifficultthantheircounterparts(Angelinietal.,1998)

Firm age significantly impacts credit accessibility, with smaller and younger firms often facing more constraints compared to their larger counterparts Research by Levenson and Willard (2000) suggests that older firms benefit from greater access to bank credit due to their accumulated social capital and established credit history, which lenders rely on for loan decisions (Musamali & Tarus, 2013) Fatoki and Asah (2011) found a positive correlation between firm age and bank credit access, indicating that older firms enjoy enhanced credit opportunities In contrast, there is little evidence to support that younger firms, particularly those aged 1 to 4 years, can access formal financial institutions effectively.

Togetherwithfirmsizeandfirmage,manyempiricalstudiesalsoconsidertypeoffirm,i n d u s t r y andregiondummyvariableaso n e oft h e firm’sc h a r a c t e r i s t i c andfurthermore,recei ving assistancefromthegovernmentisalsoinvestigatedwhenoneexploreswhichfactorsaffecttheabilityof gettingbankloan.

KuntandLevine(2005)’sresultpointedo u t thatw h i l e theaccesstodebtfinanceofstateandforei gn-ownedfirmsbecomemuchmoreeasier,family- ownedfirms,soleproprietorship(private)andpartnershipenterprisesfacegreaterfinancialobstacle s.A c c o r d i n g toKu ma r andFrancisco( 2 0 0 5 ) , firmsowned bygovernmentarem o r e l i k e l y t o a c c e s s t o bankcredit,ascomparedt o privatefirmso r firmsownedbyprivateforeign.Aboutthe relationshipbetweenindustryandcreditaccessibility,Toninetal.

The nexus between targeted enterprises and loan providers reflects the economic environment perceived by creditors, with sectors such as retail, trade, and services benefiting more from formal finance compared to others Regional disparities significantly influence access to formal credit; for instance, individuals in suburban areas face greater challenges in obtaining bank loans than those in urban settings, as many creditors primarily serve urban locales due to institutional locations In Vietnam, firms located in the Red River Delta and Southeast regions are more likely to experience credit constraints than those in other areas Additionally, government assistance plays a crucial role in bank credit accessibility, as evidenced by findings that state-directed lending to certain firms enhances their ability to secure loans, although this support does not directly impact firm growth.

Anotherfactort h a t p l a y s importantr o l e i n accesst o debtfinancei s networks,andt h e result sarequitemixedbetweenformalandinformalfinance.However,ingeneraltheroleofnetworksisco nfirmedpositivelyrelatedwithcreditaccessibility.

Int h e absenceo f collateralandfacet h e issuescomingf r o m asymmetricinformation,firmsco uldutilizet h e i r bankingrelationshipt o overcomet h e problemandgetbankl o a n (Fraser,Bhaumi k,&Wright,2013).AccordingtoAkotenetal.

(2006),lendersarelikelytodependo n reputationa n d t h e socialnetworkso f borrowerswhenthey makelo an decisions.Furthermore,forthosefirmshavelongerrelationshipwithbanksaremoreli kelytoborrowatlowerinterestrateaswellaslesslikelytopostcollateral,comparedtotheotherfirms (Berger

&Udell, 1 9 9 5 ; U z z i , 1 9 9 9 ) However,t h e f i n d i n g is f o u n d di ff er en tl y inEssienandAre ne(2014)’sstudy.Accordingly,thereisnoevidencesupportstherelationshipbetweennetworksan dformalcreditaccess,whereastheroleofsocialcapitalissignificantlypositiveeffectoninfo rmalcreditaccess.

Furthermore,followPengandLuo(2000),usingdatafromChina,therearetwotypesofnetw orksincludingnetworkwithgovernmentofficialsandnetworkwithotherfirm’smanager.Accordingt otheseauthors,boththeformerandthelatternetworksplayasignificantroleinaccesst o bankl o a n andi m p r o v i n g f i r m performance.A n explanationgivenf o r a p o s i t i v e relationshipbetw eengovernmentofficialsandaccesst o bankcrediti s t h a t proceduresw i t h governmentorganizati onsandbanksmaybereducedwith this closedconnection.However,accordingtoLeetal.

(2006)’sfindings,usingdatafromsmallandmediumsizedenterprisesinVietnam,theyindicatedt h a t w h i l e t h e connectionbetweenm a n a g e r o f o t h e r organizations,friendsdoespositively impa ctbankloan, thenexusbetweenfirmsandgovernmentofficialsn e g a t i v e l y affectsbankfina nce.Itisbecausesuchrelationshelpfirmstohavemoreopportunitiest o o b t a i n governments u p p o r t programandgetm o n e y , a n d t h e s e sourcesa r e cheaperthanformalloan.

According to Modigliani and Miller (1958), in a world with symmetric information, no taxes, and no transaction or bankruptcy costs, a firm's capital structure does not influence its value or cost of capital, indicating that debt and equity financing are interchangeable However, when the assumptions of their model are relaxed in 1963, changes in capital structure become significant, with increased debt leading to a higher firm value and a lower weighted average cost of capital (WACC) While leveraging can provide tax-shield benefits, it also introduces risks such as financial distress and bankruptcy costs, which complicate the trade-off between these advantages and potential downsides The trade-off theory suggests that higher profitability correlates with a greater reliance on debt due to tax-shield benefits, although this relationship is not absolute.

Peckingo r d e r t h e o r y i n d i c a t e d t h e orderofp r i o r i t y i n t h e u s e o f f u n d Accor dingt o which,enterprisesi n i t i a l l y usedinternalf i n a n c i n g source,f o l l o w debta n d equity.It meanst h a t i f firmsgetm o r e p r o f i t , t h e y tend t o u s e t h e i r retainearningst o financet h e i r b u s i n e s s operation,ratherthanborrowfromexternalfinance.Sothemoreprofitablefirmsare,theles susageoftheirdebt is.

Anothertheorythatreflectsthenexusbetweencapitalstructureandfirmperformanceisa g e n c y theory.A c c o r d i n g tot h i s theory,t h e r e i s a g e n c y problemb e t w e e n stockholdersandd ebtholders.Inp a r t i c u l a r , t h e formerw a n t t o t a k e r i s k i e r projectsanddemandf o r higherret urn.However,debtholdersaremorelikelytochooselessriskyprojectsandacceptlowerreturn. Inthecaseofsuccessoftheproject,anextrareturnwillbetransferredtostockholdersandiftheproje ctisfailure,alllosseswillbedividedbetweenstockholdersanddebtholders(Jensen& Meckling,1

Enterprises with higher levels of debt tend to pursue lower-risk projects due to the inherent financial constraints they face Following Myers' (1977) discussion, the conflicting objectives of shareholders and debtholders often lead to underinvestment by firms Specifically, firms experiencing higher growth have more future investment options compared to those with lower growth However, as firms accumulate more debt, their investment opportunities diminish since the wealth generated is increasingly transferred to debtholders rather than retained by shareholders Consequently, firms with higher growth prospects typically exhibit lower debt-to-equity ratios.

However,thenegativerelationshipmentionedabovecouldbemitigatediffirmsuseshorttermd ebtinsteado f l o n g termd e b t (Myers,1 9 7 7 ) Iti s l i k e l y t h a t t h e r e e x i s t t h e p o s i t i v e rela tionshipbetweenshorttermdebtandfirmperformanceiffirmsreplacelong termcreditbys h o r t termcredit.Inmyo p i n i o n , thisprepositioni s m o r e relevanti n thecaseo f s m a l l andm e d i u m sizedenterprisesinVietnamwhereshorttermloanisdominant,ascomparedt olongtermloan.

Trade-offtheory Positive Performance impactsdebt

Peckingorder theory Negative Performance impactsdebt

Whilethemajorityofpapersfocusoninternalandexternalfinancingortheeffectofbankfinancea ndcreditconstrainto n salesgrowth,a fewp a p e r s investigatesh o w formalandinformalcreditaff ectsfirmperformance.Dependentvariableisfirmperformance,andthere aret w o m e t h o d s o f cal culationf o r t h i s v a r i a b l e , suchast h e changeinlogarithmo f salesrevenue(Ayyagarieta l , 2

To investigate the impact of financing choices on firm performance, the dependent variable is typically modeled based on various financing sources, including formal, informal, and internal options, along with factors such as firm age, size, ownership type, industry classification, and credit constraints According to studies by Allen et al (2012), Ayyagari et al (2010), and Saeed (2009), the bank finance variable is endogenous To address this issue, researchers have employed collateral as an instrumental variable or considered the percentage of state-owned firms and the total bank credit allocated to each firm within the state.

S u , andX u (2013)claimedt h a t informalfinanced u m m y i s sufferedfrom endogeneityissue,andundergroundfinanceafterwarddummyisusedasinstrumentalvariable(I V).Allofthesethingsshowthatfinancingchoices,forexample,formalandinformalsourceareendoge nous,andu s i n g i n s t r u m e n t a l variablei s t h e p o p u l a r m e t h o d t o overcomet h e p r o b l e m Basedo n A y y a g a r i etal.

( 2 0 1 0 ) ’sd i s c u s s i o n , d u e t o p r o p r i e t a r y informationobservedbybank,t h e proble mo f s a m p l e selectionb i a s o c c u r s , andHeckmantwo- stageprocedureisemployedtoovercometheissue.Thismethodisalsousedinempiricals t u d y of Degryseetal.

(2013).Accordingtotheauthors,datasetisusedtorunregressionlesst h a n fullobservations,soth ereissampleselectionbias.However,theauthorsdonotmentiont h e endogeneityprobleminth eirstudy.Throughoutsomepapersmentionedabove,theeffecto f formalandinformalcredito n sa lesgrowthisambiguous.Forexample,regardingt o t h e impactofformalsourceonfirmperformance, Ayyagarietal.

(2010)andSaeed(2009)claimedt h a t officialc r e d i t playss i g n i f i c a n t l y p o s i t i v e r o l e i n im provingfirmperformance.WhereasA l l e n etal.

Thatf i n d i n g i s alsosimilart o (Yiuetal.,2013)whentheyinvestigatet h e effecto f alternati vef i n a n c i n g channelonsalesgrowth.Withregardt o theeffectofnon- standardfinancingsourceonfirmperformance,ontheonehand,thepositiveroleofthistypeoffundisf o u n d in(Allenetal.,2012)and(Yiuetal.,2013).Ontheotherhand,thisroleisnegativelyimpact onfirmperformance(Saeed,2009)orthereisnoevidencesupporttheeffectofnon- officialfinancingsourceonoutcomes(Ayyagariet al., 2010)

Formoredetails,thenexusbetweenfinancingandgrowthhasbeeninvestigatedbymanyresearch ers,andempiricalstudiesworldwideclaimedthattheunderdevelopedfinancialsystemorthelimitat ionofcreditaccessibilityisoneofthemainreasonsthatconstraintsfirmperformance,particularl yinsmall-mediumsizedenterprises.Forexample,Becketal.(2005)usedt h e cross- countriesdatasett o investigatet h e effecto f financial,l e g a l constraintsandcorruptiono n firmper formance.T h e y indicatedt h a t financialconstraintsadverselyaffectgrowthrateoffirm,particularl ysmallfirms.

Rahaman (2011) analyzed firm-level panel data from 1991 to 2001 to determine if variations in firm growth could be attributed to differences in financial structure and access to funding The study measured firm performance through the change in the logarithm of employment, influenced by growth lag, firm characteristics, and financing sources Internal funds and bank credit were identified as key financial sources, with their accessibility quantified by amount Rahaman noted econometric challenges, including endogeneity related to financing sources and autocorrelation due to growth lag, suggesting that Generalized Method of Moments (GMM) estimation was the best solution The findings indicated that internal and external financing are not perfect substitutes, with a cost wedge creating external financing constraints While internal financing significantly impacts firm performance, this effect diminishes as access to bank credit increases Financial constraints greatly influence firm performance, but easing credit limits encourages firms to rely less on internal finance and more on external sources, particularly evident in small firms.

In a study by Shinozaki (2012) analyzing cross-sectional data from Vietnam, Laos, the Philippines, and Indonesia in 2009, the impact of external funding on the growth of small and medium enterprises (SMEs) was examined The research utilized total annual sales value as the dependent variable, influenced by firm size, approved loan amounts, and lines of credit as external financing By applying the Ordinary Least Squares (OLS) method for regression analysis, the findings indicated that formal financing channels significantly boost SME growth Specifically, a one percentage point increase in bank credit correlates with a 0.4 percentage point rise in sales growth for larger companies, while this effect is even greater for SMEs, reaching 0.68 percentage points at a 1% significance level.

FIRM’SACCESS TOFINANCE

Theoreticalstudies

Asymmetricinformationisconstruedasonehasmoreadvantageousinformationthantheother sinthe sametransaction.Thebehavior oflenderinasymmetricinformationshouldbe explored firstlytounderstandthemechanismwhysomeapplicantsreceiveloan,butsomedon o t AccordingtoJaffeeandStiglitz(1990),theexpectedrateofreturnoflendersisrepresenteda safunctionofquotedinterestrate, and ithasconcaveshapeasinFigure2.1: whereverticalandh o r i z o n t a l a x i s arerepresentedbyexpectedrateo f r e t u r n o f l e n d e r s an dinterestrate,respectively.r* is theoptimalinterestrate

Thereexistsanexcessofdemandforcredit,itisundoubtedthatlenderswillincreasetheirl o a n int erestrate,whichisseenasthepricehastobepaidforborrowingmoney.Accordingtot h e l a w o f de mandandsupply,ani n c r e a s e i n pricewillleadt o adecreasei n quantitydemandedanda risein q u a n t i t y supplied,until marketclearing isrestored.However,attheo p t i m u m quotedinte restrate(r*),thereisnoincentiveforlenderstoraisetherateofinterest.T h i s i s becauseoft w o rea sons:a d v e r s e s e l e c t i o n andmoralhazard,whicha r e discussedhereafter.

Iftherateofinterestincreases,saferapplicants,whoneedfundtofinanceprojectswithl o w r i s k andl o w return,w i l l b e unablet o p a y at highinterestrate,anddroppedo u t o f t h e market.Incont rast,riskierapplicants,whohavehighriskandhighreturn,areonlyremainingi n themarket.Thiswi llleadtoanincreaseinriskofdefaultonloan(apromiseofrepaymenti s broken),so adeclineinlenders’expectedrateofreturn(Stiglitz&Weiss, 1981)

Themoralhazardrepresentsthesituationinwhichindividualorcooperation(borrowers)doesn othaveanincentivetodoaswhattheycommittedinthecontractafterthetransactionhadbeencarr iedout.Accordingly,inordertooffsetthehighinterestrate,theborrowersarem o r e likelytoun dertakeriskyprojects,this will lead to ahigherrisk ofdefaultoncredit,andalowerlenders’expectedrateofreturn.

Asthoseproblemsmentionedabove,althoughfacingtheexcessdemandforcredit,lenderswoul dnotrespondtomarketbyincreasingtherateofinterestforborrowers.Andint h i s situation,alth oughtherearepeoplew h o arewi ll in g topayatahigher levelofinterest,lendersremainunchanged atthelevelofoptimalinterestrate,andlimitloanforborrowers.Ino t h e r words,firmsare constrictedcreditin asymmetricinformation.

According to this theory, small firms strategically determine the optimal mix of debt and equity financing to balance the associated benefits and costs Debt financing is often more advantageous than equity financing due to the tax-deductibility of interest payments, while equity income is subject to corporate tax However, increasing debt levels can elevate financial risk, making debt less cost-effective compared to equity As debt financing rises, marginal costs increase and marginal benefits decline To optimize overall value, firms must find a balance between the benefits of tax shields and the costs of financial distress, necessitating a careful trade-off in their financing choices.

Besides,followtrade- offtheory,firmshavemoretangibleassetsandmoreprofitablearepredictedt h a t a r e l i k e l y t o o b t a i n highdebtratio,w h i l e e q u i t y financingi s anticipatedf o r t h o s e firmswithhighintangible assets.

Int h i s theory,b o r r o w e r s , e s p e c i a l l y s m a l l f i r m s , t e n d t o u t i l i z e internalfinancefi rstly,followedbydebt,andf i n a l l y externale q u i t y i s considered(Myers& M a j l u f , 1 9 8 4 ) T h e s e prioritiesreflectcostofvariousfinancingsourceswhereexternalequity’scostishigherthant h e others.Asaresult,externalequitymaynottheoptimalchoicetowardssmallenterprises,t h i s isbecauseofsomereasonsasfollows:i/

Stockmarketflotationisveryexpensiveandtheinitialpublicofferingsareunderpricing,t h e s e thin gscreatedisadvantagesf o r s m a l l enterprises.ii/

Foragivenlevelofrisk,highercostofequityissubjected bysmallfirmsascomparedtolargec ounterpartsduetosmallfirmeffectwhentheyo b t a i n stockmarketflotationi i i /

Awidershareownershipisoneofth e prerequisitesforstockmarketflotation.Howevert h i s m a y l e a d t o l o s s o f controlo f initialmanagerso r t h e problemo f takeoverp o s s i b i l i t y

Agencytheoryclaimedthatthereismoralhazardandadverseselectionproblemexistsincontra ctualarrangementsbetweens m a l l firmsa n d lenders.Thesep r o b l e m s arel i k e l y t o b e m o r e s evereandthecoststosolvethembyusingmonitoringandbondingareveryexpensivef o r smallen terprises.Anotherwaytosolvetheseproblemsisusingmorecollateralinlendingt o smallfirmsto avoidagencyproblemsandhelpbankstoaligninterests(Chittendenetal.,1 9 9 6 )

Abovei s t h r e e i m p o r t a n t theoriesr e l a t i n g t o f i n a n c i n g d e c i s i o n s , andthroughoutm anyempiricalevidences,pecking orderanda g e n c y theoriesseemtobe supported overtrade-off t h e o r y (Chittendenetal.,1996)

Empiricalstudies

Inordertoinvestigatethedeterminantsaffectfinanceaccessibility,mostofpapersp r i m a r i l y focusonthe accessto formalloan rather thaninformalloan, andvery fewpapersexamin edb o t h financingsourcessimultaneously.Int h e i r regressionm o d e l s , t h e dependentvariabless uchasformalandinformalchoicesareusuallybinaryvariable,whichisafunctiono f firmage,firmsi ze,firmownership,owner’seducation,owner’sgender,theageofmanager,collateral,andnetworks.

U s i n g firm- leveldata,andm o s t l y employedlogitm o d e l (thereisonepaperusedmultivariableprobitmodel)to finddownfactorsaffecttheprobabilityo f accessto thesefinancingsources.

Research on the determinants of formal finance accessibility reveals that firm age and size significantly influence the ability to secure official loans, although results for informal financing options are mixed Notably, older firms tend to have better access to informal finance, as highlighted by Essien and Arene (2014) Conversely, younger firms, particularly those owned by women, often struggle to accumulate sufficient social capital and assets, making it difficult for them to obtain bank loans; thus, non-official loans become a viable alternative Additionally, firm size does not appear to impact access to informal credit, and the type of ownership plays a crucial role in formal credit accessibility, with private firms being less likely to secure official credit compared to state-owned enterprises (Kumar & Francisco, 2005).

Empirical studies indicate that better-educated business owners are generally more successful in accessing credit (Nikaido, Pais, & Sarma, 2012), although Rand (2007) suggests an opposing view The relationship between gender and formal credit access remains unclear; while some studies show male-headed firms have an advantage in obtaining bank loans, Yaldiz, Altunbas, and Bazzana (2011) argue that female-owned enterprises may have better access to formal credit Other research indicates no significant difference in credit access between genders (Fatoki & Asah, 2011; Harrison & Mason, 2007) However, female-owned firms are often more reliant on informal credit sources due to asset limitations (Akoten et al., 2006) The impact of the owner's age on credit access is also ambiguous; younger owners may lack experience and social capital, leading them to borrow from friends and family Conversely, Vos, Yeh, Carter, and Tagg (2007) suggest that younger managers are more inclined to utilize bank loans and overdrafts Collateral significantly enhances the likelihood of obtaining formal credit, as noted in various studies Lastly, the role of networks in credit accessibility is complex, with most research highlighting a positive correlation between strong connections with lenders and credit access, although relationships with government officials may negatively impact bank financing (Le, Venkatesh, & Nguyen, 2006).

Tosumup,basedontheoreticalliteratureandmanyotherempiricalstudies,factorsaffectcredita c c e s s i b i l i t y c a n b e dividedinto3 s u b - groupsi n c l u d i n g owner/ manager’scharacteristics,firm’scharacteristicsandnetworks

Owner’sage,educationandgendercanbeaddedintheregressionasproxyvariablesforowner’sc haracteristics.

Junior managers, often perceived as inexperienced due to their youth, typically face challenges in accessing bank loans due to lower levels of social capital Research indicates that young owners, aged 21 to 35, are more inclined to seek financial support from friends and family rather than traditional financial institutions This aligns with findings from Omboi and Wangai (2011), which highlight that senior managers can leverage accumulated assets as collateral, making it easier for them to secure loans from banks In contrast, Vos et al (2007) suggest that younger entrepreneurs are more likely to utilize external financing options, such as bank loans and overdrafts, compared to their older counterparts.

Intermofthesecondowner’scharacteristic,theeffectofeducationonabilitytoaccessinstitut ionalcreditisfoundmixed.Educationalattainmentisseenasanimportantly positiveindicatorind emandfor institutionalcreditofsmall firmsbyO mb oi andWangai(2011).Inl i n e withthisstat ement,Nikaidoetal.

Research indicates that firms with better-educated owners often have easier access to credit, as these owners are typically more adept at navigating application procedures and possess essential managerial skills in finance, marketing, production, and international business (Kumar & Francisco, 2005) However, a study by Rand (2007) suggests that highly educated owners may actually face a negative impact on their likelihood of obtaining credit, as they may choose not to apply for bank loans if they anticipate a higher chance of rejection.

Owner’sgenderi salsoconsideredaso n e o f t h e factorsaffectst h e a b i l i t y toaccesst o bankcr edit.Femalemanagersfacemanyd i f f i c u l t y i n o b t a i n i n g b a n k l o a n d u e t o lacko f assets,whicharerequiredbyformalinstitution,sotheydependmoreonmicro- financesector(Akotenetal.,2006).OmboiandWangai(2011)claimedthatdemandforinstitution alcredit offemalesownedfirmsarefoundtobelessthanmalesownedfirmsduetosomeofculturaln o r m s Furthermore,a c c o r d i n g t o Nikaidoetal.

Research indicates that female-owned firms face greater challenges in accessing credit compared to their male counterparts, primarily due to their underprivileged status and lack of collateral (Toni et al., 1998) However, some studies suggest that there may be no significant difference in the likelihood of women and men applying for institutional loans, with women potentially finding it easier to obtain bank loans (Yaldiz et al., 2011) Additionally, findings from Fatoki & Asah (2011) and Harrison & Mason (2007) support the notion that women and men have similar access to institutional credit.

Oneofthemostimportantindicatorsthataffectcreditaccessibilityaswellasfirmperformanceisf irmsize.Dependonthepurposeofresearch,andtheavailabilityofdata,firms i z e canbeproxiedby totalemployees(Becchetti&Trovato,2002;Klapper,Sarria-Allende,

&Sulla,2002),totalsales(Degryseetal.,2013;Rahaman,2011)ortotalassets(Allenetal.,2 0 1 2 ; Essien&Arene,2014;Rahaman,2011).Bigstenetal.

(2003)arguedthatwhilelargerfirmsaremorelikely too b t a i n bankloan,itgoesopposite dire ctionforsmaller ones.Beck,

Demirgüç-Kunt and Maksimovic (2005) analyzed a firm-level database from 54 countries and highlighted that the size of a firm significantly impacts its access to credit They found that small and medium-sized enterprises (SMEs) encounter more challenges related to financial, legal, and corruption barriers compared to larger firms This disadvantage adversely affects the performance of SMEs, a finding that aligns with Saeed's (2009) research SMEs often face financial constraints, struggle to provide the necessary information and collateral required by banks, and consequently rely more on non-market sources of financing than their larger counterparts.

In Okura's (2008) study, firm size significantly impacts access to credit, with smaller firms relying more on informal credit, internal funding, and equity Formal institutions provide over 40% of working capital to larger firms, while only 16% goes to smaller enterprises, highlighting a positive correlation between bank accessibility and firm size Kumar and Francisco (2005) explain that small firms struggle to access bank credit due to market imperfections, such as informational opacity and poor financial information quality, which make it difficult for creditors to assess their viability (Binks & Ennew, 1996) Additionally, small firms are perceived as riskier due to their limited ability to diversify output and client bases, leading to concerns about unsustainable earnings (Klapper et al., 2002) Information asymmetry, including adverse selection and moral hazard, further exacerbates credit rationing by commercial banks (Stiglitz & Weiss, 1981) To mitigate these challenges, posting collateral is often recommended (Angelini & Di Salvo).

&Ferri,1998).However,whilelargerfirmsoftenownmoreassetswhichcanbeprovidedascollater alinbank’sperspective,smallfirmsfacemoredifficultthantheircounterparts(Angelinietal.,1998)

The age of a firm significantly influences its access to credit, with older firms enjoying greater accessibility compared to younger ones Research by Levenson and Willard (2000) highlights that smaller and younger firms face more constraints than their larger counterparts This is attributed to older firms having accumulated social capital and a robust credit history, which bank lenders rely on for loan decisions (Musamali & Tarus, 2013) Fatoki and Asah (2011) further emphasize the positive correlation between firm age and access to bank credit, noting that as firms age, their credit accessibility increases Conversely, there is a lack of evidence supporting the notion that younger firms, particularly those aged 1 to 4 years, can effectively access formal financial institutions.

Togetherwithfirmsizeandfirmage,manyempiricalstudiesalsoconsidertypeoffirm,i n d u s t r y andregiondummyvariableaso n e oft h e firm’sc h a r a c t e r i s t i c andfurthermore,recei ving assistancefromthegovernmentisalsoinvestigatedwhenoneexploreswhichfactorsaffecttheabilityof gettingbankloan.

KuntandLevine(2005)’sresultpointedo u t thatw h i l e theaccesstodebtfinanceofstateandforei gn-ownedfirmsbecomemuchmoreeasier,family- ownedfirms,soleproprietorship(private)andpartnershipenterprisesfacegreaterfinancialobstacle s.A c c o r d i n g toKu ma r andFrancisco( 2 0 0 5 ) , firmsowned bygovernmentarem o r e l i k e l y t o a c c e s s t o bankcredit,ascomparedt o privatefirmso r firmsownedbyprivateforeign.Aboutthe relationshipbetweenindustryandcreditaccessibility,Toninetal.

In 1998, it was asserted that the relationship between enterprises seeking credit and the decisions of loan providers is influenced by the economic environment perceived by creditors Key sectors such as retail, trade, and services benefit more from formal finance compared to others Additionally, geographical factors play a significant role in credit accessibility; for instance, Tonin et al (1998) noted that individuals in suburban areas face greater challenges in obtaining bank loans than those in urban settings, as some creditors primarily serve urban regions due to institutional locations, thereby limiting resource allocation In Vietnam, research by Mai (2014) indicated that firms in the Red River Delta and Southeast regions are more likely to experience credit constraints than those in other areas Lastly, government assistance is closely linked to bank credit accessibility, as highlighted by N.T Nguyen (2014), who found that state directives to banks to lend to specific firms significantly support loan acquisition, although this assistance does not directly influence firm growth.

Anotherfactort h a t p l a y s importantr o l e i n accesst o debtfinancei s networks,andt h e result sarequitemixedbetweenformalandinformalfinance.However,ingeneraltheroleofnetworksisco nfirmedpositivelyrelatedwithcreditaccessibility.

Int h e absenceo f collateralandfacet h e issuescomingf r o m asymmetricinformation,firmsco uldutilizet h e i r bankingrelationshipt o overcomet h e problemandgetbankl o a n (Fraser,Bhaumi k,&Wright,2013).AccordingtoAkotenetal.

(2006),lendersarelikelytodependo n reputationa n d t h e socialnetworkso f borrowerswhenthey makelo an decisions.Furthermore,forthosefirmshavelongerrelationshipwithbanksaremoreli kelytoborrowatlowerinterestrateaswellaslesslikelytopostcollateral,comparedtotheotherfirms (Berger

&Udell, 1 9 9 5 ; U z z i , 1 9 9 9 ) However,t h e f i n d i n g is f o u n d di ff er en tl y inEssienandAre ne(2014)’sstudy.Accordingly,thereisnoevidencesupportstherelationshipbetweennetworksan dformalcreditaccess,whereastheroleofsocialcapitalissignificantlypositiveeffectoninfo rmalcreditaccess.

Furthermore,followPengandLuo(2000),usingdatafromChina,therearetwotypesofnetw orksincludingnetworkwithgovernmentofficialsandnetworkwithotherfirm’smanager.Accordingt otheseauthors,boththeformerandthelatternetworksplayasignificantroleinaccesst o bankl o a n andi m p r o v i n g f i r m performance.A n explanationgivenf o r a p o s i t i v e relationshipbetw eengovernmentofficialsandaccesst o bankcrediti s t h a t proceduresw i t h governmentorganizati onsandbanksmaybereducedwith this closedconnection.However,accordingtoLeetal.

(2006)’sfindings,usingdatafromsmallandmediumsizedenterprisesinVietnam,theyindicatedt h a t w h i l e t h e connectionbetweenm a n a g e r o f o t h e r organizations,friendsdoespositively impa ctbankloan, thenexusbetweenfirmsandgovernmentofficialsn e g a t i v e l y affectsbankfina nce.Itisbecausesuchrelationshelpfirmstohavemoreopportunitiest o o b t a i n governments u p p o r t programandgetm o n e y , a n d t h e s e sourcesa r e cheaperthanformalloan.

FINANCINGCHOICESANDSALESGROWTH

Theoreticalstudies

According to Modigliani and Miller (1958), in a world with symmetric information, no taxes, and no transaction or bankruptcy costs, a firm's capital structure does not influence its value or cost of capital, indicating that there is no distinction between debt and equity financing However, when the assumptions of the Modigliani and Miller framework are relaxed in their 1963 study, changes in capital structure begin to impact the firm's value and weighted average cost of capital (WACC) Specifically, increasing debt relative to equity can enhance firm value while reducing WACC Despite the tax shield benefits associated with higher leverage, this approach carries risks such as financial distress and bankruptcy costs, leading to a trade-off between the advantages of tax shields and the potential downsides Consequently, the trade-off theory suggests that while higher profitability may correlate with increased debt due to tax shield benefits, this relationship is not absolute.

Peckingo r d e r t h e o r y i n d i c a t e d t h e orderofp r i o r i t y i n t h e u s e o f f u n d Accor dingt o which,enterprisesi n i t i a l l y usedinternalf i n a n c i n g source,f o l l o w debta n d equity.It meanst h a t i f firmsgetm o r e p r o f i t , t h e y tend t o u s e t h e i r retainearningst o financet h e i r b u s i n e s s operation,ratherthanborrowfromexternalfinance.Sothemoreprofitablefirmsare,theles susageoftheirdebt is.

Anothertheorythatreflectsthenexusbetweencapitalstructureandfirmperformanceisa g e n c y theory.A c c o r d i n g tot h i s theory,t h e r e i s a g e n c y problemb e t w e e n stockholdersandd ebtholders.Inp a r t i c u l a r , t h e formerw a n t t o t a k e r i s k i e r projectsanddemandf o r higherret urn.However,debtholdersaremorelikelytochooselessriskyprojectsandacceptlowerreturn. Inthecaseofsuccessoftheproject,anextrareturnwillbetransferredtostockholdersandiftheproje ctisfailure,alllosseswillbedividedbetweenstockholdersanddebtholders(Jensen& Meckling,1

Enterprises with higher levels of debt tend to pursue lower-risk projects, which can lead to underinvestment due to conflicting goals between shareholders and debtholders, as discussed by Myers (1977) Specifically, firms with higher growth potential have more future investment opportunities compared to those with lower growth However, as a firm's debt increases, its investment opportunities diminish because the wealth generated will primarily benefit debtholders rather than shareholders Consequently, firms that experience higher growth are generally associated with a lower debt-to-equity ratio.

However,thenegativerelationshipmentionedabovecouldbemitigatediffirmsuseshorttermd ebtinsteado f l o n g termd e b t (Myers,1 9 7 7 ) Iti s l i k e l y t h a t t h e r e e x i s t t h e p o s i t i v e rela tionshipbetweenshorttermdebtandfirmperformanceiffirmsreplacelong termcreditbys h o r t termcredit.Inmyo p i n i o n , thisprepositioni s m o r e relevanti n thecaseo f s m a l l andm e d i u m sizedenterprisesinVietnamwhereshorttermloanisdominant,ascomparedt olongtermloan.

Trade-offtheory Positive Performance impactsdebt

Peckingorder theory Negative Performance impactsdebt

Empiricalstudies

Whilethemajorityofpapersfocusoninternalandexternalfinancingortheeffectofbankfinancea ndcreditconstrainto n salesgrowth,a fewp a p e r s investigatesh o w formalandinformalcreditaff ectsfirmperformance.Dependentvariableisfirmperformance,andthere aret w o m e t h o d s o f cal culationf o r t h i s v a r i a b l e , suchast h e changeinlogarithmo f salesrevenue(Ayyagarieta l , 2

To investigate the impact of financing choices on firm performance, researchers typically model the dependent variable as a function of various financing sources—both formal and informal—as well as internal factors, firm age, size, ownership type, industry, and credit constraints According to studies by Allen et al (2012), Ayyagari et al (2010), and Saeed (2009), the bank finance variable is endogenous; thus, they utilized collateral, state ownership percentages, or total bank credit allocated per firm as instrumental variables to address this issue.

S u , andX u (2013)claimedt h a t informalfinanced u m m y i s sufferedfrom endogeneityissue,andundergroundfinanceafterwarddummyisusedasinstrumentalvariable(I V).Allofthesethingsshowthatfinancingchoices,forexample,formalandinformalsourceareendoge nous,andu s i n g i n s t r u m e n t a l variablei s t h e p o p u l a r m e t h o d t o overcomet h e p r o b l e m Basedo n A y y a g a r i etal.

( 2 0 1 0 ) ’sd i s c u s s i o n , d u e t o p r o p r i e t a r y informationobservedbybank,t h e proble mo f s a m p l e selectionb i a s o c c u r s , andHeckmantwo- stageprocedureisemployedtoovercometheissue.Thismethodisalsousedinempiricals t u d y of Degryseetal.

(2013).Accordingtotheauthors,datasetisusedtorunregressionlesst h a n fullobservations,soth ereissampleselectionbias.However,theauthorsdonotmentiont h e endogeneityprobleminth eirstudy.Throughoutsomepapersmentionedabove,theeffecto f formalandinformalcredito n sa lesgrowthisambiguous.Forexample,regardingt o t h e impactofformalsourceonfirmperformance, Ayyagarietal.

(2010)andSaeed(2009)claimedt h a t officialc r e d i t playss i g n i f i c a n t l y p o s i t i v e r o l e i n im provingfirmperformance.WhereasA l l e n etal.

Thatf i n d i n g i s alsosimilart o (Yiuetal.,2013)whentheyinvestigatet h e effecto f alternati vef i n a n c i n g channelonsalesgrowth.Withregardt o theeffectofnon- standardfinancingsourceonfirmperformance,ontheonehand,thepositiveroleofthistypeoffundisf o u n d in(Allenetal.,2012)and(Yiuetal.,2013).Ontheotherhand,thisroleisnegativelyimpact onfirmperformance(Saeed,2009)orthereisnoevidencesupporttheeffectofnon- officialfinancingsourceonoutcomes(Ayyagariet al., 2010)

Formoredetails,thenexusbetweenfinancingandgrowthhasbeeninvestigatedbymanyresearch ers,andempiricalstudiesworldwideclaimedthattheunderdevelopedfinancialsystemorthelimitat ionofcreditaccessibilityisoneofthemainreasonsthatconstraintsfirmperformance,particularl yinsmall-mediumsizedenterprises.Forexample,Becketal.(2005)usedt h e cross- countriesdatasett o investigatet h e effecto f financial,l e g a l constraintsandcorruptiono n firmper formance.T h e y indicatedt h a t financialconstraintsadverselyaffectgrowthrateoffirm,particularl ysmallfirms.

Rahaman (2011) analyzed firm-level panel data from 1991 to 2001 to explore whether variations in firm growth could be attributed to differences in financial structures and access to internal and external funding Firm performance was measured by the change in the logarithm of employment, influenced by growth lag, firm characteristics, and financing sources Internal funds and bank credit were considered distinct financing sources, quantified by amount The study identified econometric issues such as endogeneity linked to financing sources and autocorrelation due to growth lag, necessitating the use of different GMM estimation methods The findings indicated that internal and external financing are not perfect substitutes, with a cost wedge between them creating external financing constraints While internal financing significantly impacts firm performance, this effect diminishes as access to bank credit increases Financial constraints notably influence firm performance, but easing credit limits encourages firms to rely less on internal finance and shift towards external sources, which are particularly vital for enhancing performance in small firms.

In a study by Shinozaki (2012) examining cross-section data from Vietnam, Laos, the Philippines, and Indonesia in 2009, the impact of external funding on SME growth was analyzed The research utilized total annual sales value as the dependent variable, influenced by firm size, the amount of approved loans, and lines of credit considered as external financing By applying the OLS method for regression analysis, the findings indicated that formal financing channels significantly accelerate SME growth Specifically, a one percentage point increase in bank credit correlates with a 0.4 percentage point increase in sales growth for large companies, while this effect is even more pronounced in SMEs, showing an increase of 0.68 percentage points at a 1% significance level.

Becchetti and Trovato (2002) examined the factors influencing the growth of SMEs and the impact of external finance on firm performance by analyzing panel data from 4,000 Italian SMEs between 1989 and 1997 Their study identified the employment growth rate as a function of firm size, age, ownership, leverage, and various dummy variables such as sector, industry, region, government subsidies, exports, and rent They introduced a binary variable to denote external financing sources, indicating firms that requested but did not receive bank loans Using OLS methodology, the authors concluded that SME growth is influenced not only by firm size and age but also by bank credit limitations Additionally, they found that small firms exhibit a higher potential average growth rate, which may be hindered by existing bank credit constraints.

Therearetwocontradictingviewsonhowdifferentfinancingsourcesaffectfirmperformance. Ontheonehand,thepredominantviewsclaimedthatsignificantlypositiveroleo f formalfinanci ngsectorcontributestohigherenterprisesgrowth,whilethereisnoevidenceo r t h e findingsarem i x e d f o r informalone.O n t h e o t h e r hand,s o m e p a p e r s arguedt h a t i n transitioneconomieswher ethelackofprofessionalfinancingmarketandthelimitedofcredita c c e s s i b i l i t y ofsmallf irmsareoccurred,informalfinance isseenasanalternativefinancingchannelforsmallfirmstosee krecourse(Jain, 1999).

In a study conducted in 2010, researchers analyzed 240 Chinese firms across 18 cities to determine if informal financing serves as a perfect substitute for formal channels and enhances firm performance more rapidly The study focused on the log change in firm sales as the dependent variable, influenced by various factors including bank access, self-financing, and other characteristics such as firm age, size, ownership type, city, industry, and competition The findings aimed to evaluate the impact of formal funding on firm performance, as outlined by Ayyagari et al.

( 2 0 1 0 ) , bankd u m m y i s subjectt o e n d o g e n e i t y problemandduetoproprietaryinform ationobservedbybank,sampleselectionb i a s occurs.Theauthorsusedcollateralasinstrument variableandemployedHeckmantwo- stagep r o c e d u r e t o overcomet h e s e problems.T h e resultssuggestt h a t formalcreditplaysp o s i t i v e effectonsalesgrowth.Tocomparetheroleofformalandinformalinimprovingfirmperf ormance,t h e a u t h o r s dividedi n t o t w o panelsf o r eachs o u r c e o f financeandemployed

OLSm e t h o d regardlesso f e n d o g e n e i t y p r o b l e m betweenformals o u r c e andsalesgro wth.Again,t h e authorclaimedt h a t w h i l e formalfinanceplaysa s i g n i f i c a n t l y p o s i t i v e r o l e i n p r o m o t i n g h i g h e r firmperformance,therei s n o evidencef o r informalfinancingso urce.Inaddition,non- standardfinancingmechanismisnoteffectivechanneltosubstituteformalsectorf o r m a k i n g h i g h e r firmp e r f o r m a n c e , andt h e contributiono fReputationa n d relationshipt ofastestg r o w i n g firmsi n less-developedcountriesmayb e overestimatedbyA l l e n etal.(2012).

Saeed (2009) analyzed firm-level data from the World Bank Enterprise Survey, focusing on 15,39 Brazilian small and medium-sized enterprises (SMEs) from 2000 to 2005, to explore the relationship between various financing sources and business growth The study measured the percentage change in full-time employment or sales over the last three years as a function of formal, informal, and internal finance, while also incorporating financial liberalization indices and financing constraint variables Saeed identified formal financing as an endogenous variable, utilizing state ownership as an instrumental variable and employing 2SLS methodology The findings indicate that formal financing significantly enhances enterprise performance, whereas informal funding has a detrimental effect Additionally, internal finance emerged as a crucial factor for improving firm performance, while financial constraints negatively impacted outcomes However, an increase in the financial liberalization index was found to alleviate these constraints and improve overall firm performance.

The role of standard financial mechanisms in enhancing firm performance is significant, yet non-legal mechanisms offer an alternative financing channel in markets characterized by imperfect information A study by Allen et al (2012) utilized aggregate country-level and firm-level data from the Prowess database in India (1996-2005) to analyze the impact of bank credit access on firm performance, measured by percentage changes in sales revenue The analysis included variables such as firm age, size, industry type, and whether the firm is publicly listed, with bank finance treated as endogenous To address potential biases, the authors employed a two-stage least squares (2SLS) approach using instrumental variables, including the number of bank branches per firm in a state and total bank credit disbursed Contrary to expectations, the findings revealed no evidence supporting a positive relationship between the formal financial sector, backed by legal systems, and firm performance Instead, firms in India showed a preference for non-standard financing sources supported by non-legal systems.

Usingthedatasetcompriseof284Chineseprivatefirmsacross19citiesin2006,Yiuetal. (2013)investigatedtheeffectofalternativefinancingchannelsuchasundergroundfinanceo n sales growth.Dependentvariableisreturnonassetrepresentedasfirmperformance,whichi s a functiono f undergroundfinanced u m m y , formalfinanced u m m y , f i r m age,firms i z e , leverage,industr ydummy,o p e r a t i n g cashflow,andtheinteractiontermbetweenprovincial marketizationi n d e x andu n d e r g r o u n d finance.A c c o r d i n g t o Y i u etal.

( 2 0 1 3 ) , undergroundfinanced u m m y i s sufferedfrome n d o g e n e i t y p r o b l e m , s ound ergroundfinanceafterwardd u m m y isusedasinstrumentalvariableandemployed2SLStosolvet heproblem.Inaddition,f o l l o w Yiuetal.

(2013),thedatasetjustcompriseofprivatefirmdata,sotheissueofsampleselectionoccurs.T h e au thorsappliedHeckmant w o - s t a g e proceduret o overcomet h i s problem.Afterall,t h e r e s u l t s suggestt h a t i n transitionecon omieslikesC h i n a , w h i l e non- marketsourceoffinance,namelyundergroundfinanceandtradecredit,issignificantlyp o s i t i v e effectonhighergrowthrateofprivatefirms,formalfinancingchannelisnot.Moreover,thecrucialro leofundergroundfinanceisclearlyportrayedinprovinceswithlessgovernmentassistant,l e s s cr editmarketizationandlacko f economicdevelopmento f non-state.

(2013).Therearethreeresearchquestionsarisenfromtheseauthors,suchasi)fundingfrominformal sourceishigherconnectedwithsmallfirm’sgrowth,ii)co- funding,specifically,formalandinformalfinance,i s ano p t i m a l choicef o r s m a l l firmst o e n h a n c e growthrate,andi i i ) i n t h e c a s e o f co- existence,aminorityproportionofinformalsourceiscloserrelatedtosalesgrowthofsmallfirms.

The dataset consists of 3,837 Chinese firms across 108 cities in 2005, used to analyze sales growth The dependent variable is the logarithmic change in sales, influenced by formal and informal finance, firm age, firm size, ownership type, province, and industry Utilizing the Heckman two-stage procedure, the study finds that informal finance positively impacts sales growth for small firms but negatively affects larger firms Additionally, co-funding emerges as an optimal strategy for small firms to enhance sales growth, effectively addressing the challenges posed by banks in information-asymmetric markets.

Int h i s chapter,datas o u r c e andt h e m e t h o d s ofanalyzingt h e researchproblemsarepr esented.Wefirstpresentthedatasource.Thenwepresentthebivariatemodelforanalyzingt h e choi ceofformalandinformalfinance.Afterthatthemodelforanalyzingtheimpactsoffinancingchoic eonfirmperformanceispresented.The methodaddressingendogeneityinthism o d e l i s alsodiscussed

DATA

The primary data for this research is derived from a 2013 survey of Small and Medium-sized Enterprises (SMEs) conducted by the Central Institute for Economic Management (CIEM) This comprehensive survey interviewed over 2,500 SMEs across ten regions, including Phu Tho, Hanoi, Ha Tay, Hai Phong, Nghe An, Quang Nam, Khanh Hoa, Lam Dong, Ho Chi Minh City, and Long An Notably, Ho Chi Minh City had the highest number of observations at 636, followed by Nghe An with 358 and Ha Tay with 345 The majority of the firms surveyed were household establishments with ten or fewer employees While the dataset encompasses various characteristics of these firms, this analysis specifically focuses on their access to formal and informal finance Out of the 2,500 enterprises sampled, 533 accessed formal loans, while 150 and 58 firms obtained funding from informal sources and both types of funding, respectively.

METHODOLOGY

Determinantsaffectfirm’saccesstofinance

Formal i =α0+α1Firmage+α2Firmsize+α3Governmentassistance+α4Networks+α5A g e +α6Gen der+ α7Education+α8Ownership +α9Industry+α10Region+ε1 (1)

Informal i =α0+ α1F i r m age+α2Firmsize+α3Governmentassistance+α4Networks+α5A g e +α6G ender+ α7Education+α8Ownership +α9Industry+α10Region+ε2 (2)

Definitionofeachvariablein equation(1)and(2)isreportedinTable3.1,inwhichnetwor kscompriseofnetworkwith firm,bank,official andnetworkwith others.

Formal =1 iffirmsobtainformalloan,0 other Informal =1 iffirmsobtaininformalloan,=0ot

Firmsize is proxied bytotalassets inb i l l i o n VNDattheendofthes urvey

Thenumberof banks that firmsregularlycontactwith + + (Berger&Udell,19

Thenumberof others thatfirmsregularlycontactwith + + (Le etal., 2006)

Age Ageofbusinessownerfromyearo fbirth to 2012 + - (Akotenetal.,2006

(2006)’sdiscussion,makingadecisiontoborrowmoneyfromofficialo r non- officialf i n a n c i n g s o u r c e maybeoccurredi n s i m u l t a n e o u s manner.S o I amp l a n n i n g to conductbivariateprobitmodeliftheerrortermintwoequationsiscorrelatedwitheachother.Otherwis e,probit modelcanbeappliedseparately.

Becauset h e r e aret w o financingc h o i c e andI d e f i n e t h e m asbinary,a bivariatep r o b i t m o d e l isappropriate.Inthismodel,therearetwobinaryoutcomesy1andy2(formorethant w o , w e must applymultivariableprobit),soIalsohavetwolatentoutcomesy1*andy2*. y1,y2areequalto1ifandonlyifthelatentvariabley1*andy2*aregreaterthanzero,0otherwise

Inshort,the errorterm𝜀 1and 𝜀 2has distribution asfollows:

So, if thetwodisturbancesarerelatedwitheachotherby𝜌value,wecanemploy bivariate probitmodel (and maximumlikelihoodmethod isemployedto estimatethevalueof

𝜌,𝛽 1 ,𝛽 2 ) (1) ,if not,probitmodelcanbeappliedseparatelyfor thetwo equations.

Financingchoicesandfirm’sgrowth

GROWTH_1=α0+α 1 F o r m a l +α 2 Informal+α3Firmage+α4Firmsize+α5Governmentassistanc e+α6Age+α7Gender+α8Education+α9Ownership+α10Industry+ε (5)

GROWTH=α0+α 1 Formal+α 2 Informal +α3Firmage+α4Firmsize+α5Governmentassistance+ α6Age+α7Gender+α8Education+α9Ownership+α10Industry+ε (6)

Inwhich,formalandinformalisconsideredasfinancingchoices.Andthedefinitionofeachvari ableis described inTable3.2

Variable Definition Expected sign Reference

Formal =1 iffirmsobtainformalloan,and0 + (Ayyagarietal., otherwise 2010;Essien&

Informal =1 iffirmsobtaininformal loan,and0otherwise +/- (Allenetal.,2012;Essie n&Arene,2 0 1 4 )

Firmage Thenumberoffirm’sagefromitsestablishm entto 2012 - (Nelson&Winter,200

Firmsize is proxied bytotalassets in billionVNDattheendofthe survey +

Education =1 iffirmreportedin specificeducation,0otherwise + (Kumar&Francisco,2

The relationship between formal finance and sales growth is complicated by endogeneity issues, as discussed by Saeed (2009) and highlighted by Allen and Qian (2009) due to self-selection bias in financing choices Yiu et al (2013) further note that informal finance also experiences similar endogeneity challenges affecting firm performance Both formal and informal financing sources are thus impacted by this problem, leading to biased and inconsistent results if Ordinary Least Squares (OLS) methods are used without addressing it The most effective approach to resolve this issue is to identify an appropriate instrumental variable (IV) that is strongly correlated with the endogeneity variable but does not directly influence sales growth Once a suitable IV is established, it allows for accurate predictions, enabling the reliable application of the OLS method.

In this context, networks can be classified as an independent variable (IV), with four distinct types identified in the dataset: networks with firms, government officials, banks, and others An increase in the number of supportive networks enhances firms' access to both official and unofficial financing Reflecting on Vietnam's financial system, characterized by a lack of transparency and high corruption levels, firms with extensive social capital gain a significant advantage For instance, strong connections with banks expedite loan processing compared to other applicants Additionally, in accessing unofficial finance, individuals can act as guarantors, facilitating easier loan approvals As firms secure more funding for their operations, their performance tends to improve Consequently, networks are closely linked to loan accessibility but do not directly influence firm performance.

Formal i =α0+α1Firmage+α2Firmsize+α3Governmentassistance+α4 Networks+α5A g e +α6Ge nder+ α7Education+α8Ownership +α9Industry+α10Region+ε1

Informal i =α0+ α1Firmage+α2Firmsize+α3Governmentassistance+α4 Networks+α5A g e +α6G ender+ α7Education+α8Ownership +α9Industry+α10Region+ε2

GROWTH_1=α0+α 1 Formalh a t + α 2 Informalh a t +α3Firmage+ α4Firms i z e + α5Governmen tassistance+α6Age +α7Gender+α8Education+α9Ownership+α10Industry+ε (7)

GROWTH=α0+α 1 Formal h a t + α 2 Informalh a t +α3Firmage+ α4Firmsize+ α5Governmenta ssistance+α6Age+α7Gender+α8Education+α9Ownership+α10Industry+ε (8)

Theestimatesfrom(7)and(8)arethenfixed forbiasduetoendogeneity.Thenextchapterprese ntstheresultsfromthese regressionanalyses.

Chapter4 f i r s t presentst h e overalld e s c r i p t i v e statisticso f t h e dataset.T h e empirical resultsontheaccesstoformalandinformalfinance,aswellasthedifferenteffectsbetweenofficialand non-officialfinancings o u r c e o n firmperformancew i l l b e presentedanddiscussed.

DESCRIPTIVE RESULTS

Variable Obs Mean Std.Dev Min Max

Table4 1 presentst h e s u m m a r y s t a t i s t i c s i n c l u d i n g t h e n u m b e r ofo b s e r v a t i o n s , mean,standarddeviation,andm i n / m a x Overall,therearemorethan2500 firmsinthe sampleweuse.Twotypesofmeasurementa boutsalesgrowthemployedinthisthesis,includingthelogchangeinsalesrevenuedenotedbygro wth_1andtheotheroneisthepercentagechangeinsalesgrowthdenotedbygrowth.A c c o r d i n g t o T a b l e 4 1 , t h e overallgrowthratei s 0.09%,rangingf r o m -

The study reveals that firms have an average age of 14.55 years, with a minimum age of 1 year and a maximum of 59 years The mean total assets of these firms amount to 5.38 billion VND, ranging from 0.001 to approximately 204 billion VND On average, firms maintain regular contact with nearly 28 other businesses, with a range of 0 to 300 connections Additionally, firms have established relationships with an average of 1.39 financial institutions, with a minimum of 0 and a maximum of 13 The analysis of social networks indicates that firms typically engage with about 1.62 government officials, with a range from 0 to 21, while the average number of other connections is 5.45, spanning from 0 to 100 Lastly, the average age of business owners is around 45 years, with ages ranging from 18 to 69.

Variable Obs Mean Std.Dev Min Max

NotcompletedelementaryGr aduatedfromelementaryGra duatedfromsecondaryGradu atedfromhigh school

0.52%,theoppositedirectionisobservedinfemale- headedfirmswiththemeanofgrowthis1.03%,m u c h h i g h e r t h a n t h e i r counterparts.Howev er,t h e rangeofs a l e s growthi n male-headedfirmsishigherthanfemale- ownedfirms,andthecorrespondingfiguresare373.54%and281.04%

Regardingtoeducationalattainment,thenumberofownersgraduatedfromhighschoolisdomina nt,relativetotheothergroups.However,thepositivemeanofgrowthforthosefirmshaveowners withhighesteducationalattainmentjuststandsinthesecondposition,asopposedt o thosefirmswith managerswhograduatedfromelementary(0.17%versus2.44%).Besides,t h e negativegrowthrat eisobservedinfirmswithownerswhograduatedfromsecondaryandn o t completede l e m e n t a r y s c h o o l M o r e specifically,a greaterreductioni n averages a l e s growthisfoundwithow nersnotcompletedelementary(2.74%)andmaximumgrowthrateis recordedat35%whilethatfiguresare0.56%and181%,respectively,forfirmswithownersgradu atedfromhighschool.

Variable Obs Mean Std.Dev Min Max

At first glance, five out of seven categories show a positive growth rate, with household establishments leading in participation compared to other legal statuses The partnership and cooperative types exhibit the highest mean growth rates at 15.87% and 6.16%, respectively In contrast, private and limited companies contribute modestly to firm performance, with growth rates of 0.58% and 0.70% Interestingly, household ownership, despite having the highest maximum growth rate of 293.75%, shows a low mean growth rate of only 0.52% Additionally, joint stock companies with state capital report the lowest mean growth rate of -1.71% and a maximum growth rate of 32.06%.

Variable Obs Mean Std.Dev Min Max

Deltaarethefirstandthesecondhighestwiththe correspondingfiguresare7.95%and3.81%.Inadd ition,them a x i m u m growthrateinNorthCentralCoastis235.69%,thesecondhighestinsevengr oups.O n t h e o t h e r h a n d , t h e lowestgroup,regardingt o t h e m e a n ofgrowthandt h e m a x i m u m growthrate,isCentralhighlandwith thenumbersare8.78%,and25%,respectively.Whilethem a x i m u m growthratei n RedR i v e r D eltai s highestandrecordedat2 9 3 7 5 % , therei s a reductioni n t h e a v e r a g e growthr a t e by

2 0 4 % , t h e secondlowestint h e sevenregions.Besides,South- easti s a n o t h e r regiont h a t w e a r e concerned,althoughi t i s amongstregionsw i t h highestmaxi mumgrowthrate,themean ofgrowthis still lowandreducedby1.64%.

Variable Obs Mean Std.Dev Min Max

The food and beverage industry leads with 785 observations, significantly outpacing other sectors Notably, two-thirds of these entities exhibit a negative average growth rate, particularly within the textile, rubber, furniture, and fabricated metal industries While the textile industry boasts a high maximum growth rate of 133.33%, it faces a substantial average decline of 3.78%, likely due to the lingering effects of the 2008 financial crisis In contrast, the food and beverage sector shows positive growth, with the highest average growth rate of 3.22% and a remarkable maximum growth rate of 293.75% Due to insufficient data, the construction and water treatment sectors were excluded from the analysis.

Variable Obs Mean Std.Dev Min Max

The financing choices of firms reveal that formal funding sources are the most popular, with 533 observations, followed by informal sources at 150 and a combination of both at 58 Despite this, the contribution of the official sector to average growth is insufficient compared to firms that utilize multiple funding sources Specifically, firms relying solely on formal channels experience an average growth rate of 2.44%, while those borrowing from two sources achieve a threefold increase This indicates that firms utilizing both formal and informal funding can attain a higher mean growth rate, making it an optimal choice Notably, the highest growth rate is observed in firms that exclusively obtain loans from the informal sector, reaching an impressive 181.04%.

Variable Obs Mean Std.Dev Min Max

Governmentassistanceintechnology 55 9.06 23.02 -23.29 102.74 Accordingt o Table4 6 , governmentassistancealsoplaysanimportantr o l e i n s u p p o r t i n g firmperformance.Themeanofsalesgrowthissignificantlyhigheriffirmsreportedtheyreceivedassi stancefromt h e government,comparedt o t h o s e doesn o t gett h i s s u p p o r t (2.16%versus-

Technical assistance, such as human resources training and trade promotion programs, significantly impacts average growth rates at 9.06%, compared to a modest 1.72% for firms receiving financial assistance Additionally, firms that receive technological support achieve higher maximum growth rates (130.6%) than those relying on financial aid (102.74%) However, the number of entities benefiting from technical assistance is limited, with only 55 observations To enhance firm performance, the government should increase opportunities for businesses to access this type of support.

Accordingtofigure(4a),itislikely thatthereisanegativerelationshipbetweenageoffirma ndtheir performance.Mostof observations focusedprimarily from1to35 yearsold, w h i l e someissparsefrom40to 60yearsold.However,themeanofgrowthisprimarilybelow1 0 0 %

Ap o s i t i v e relationshipbetweentotalassetsandt h e growthr a t e o f f i r m i s showedinfigur e(4b).Themajorityobservationoftotalassetsfocusedunder50billioninVND,andtheaveragegrowth rate is below100%.

Thescatterinfigure(4c),itislikelythatthereisanegativeconnectionbetweennetworksw i t h fi rmsandfirmperformance.Overall,t h e averagegrowthratei s alsobelow100%,t h e spreadof data is focusedprimarilyfrom 1 to 100partnerships.

Theplotinfigure(4d)showstherelationshipbetweenthenumberofbanksthatfirmsgetacquai ntanceandfirm’sperformance.Thisnumberisquitesmallandfocusedprimarilyfromz e r o t o

Figure(4e)showstheconnectionbetweenfirm’sperformanceandthenumberofofficialst h a t firmsgetacquaintanceswith Iti s likely thatthereis ad own wa rd re la ti on sh ip betweennetw orkswithofficialsandfirm’sperformance.Similartonetworkswithbank,thenumberofofficialsisfo cusedfromzero to 7.

Anegativerelationshipbetweenfirm’sperformanceandnetworkswithotherpartnershipsi s in dicatedinfigure(4f).Mostofobservationsarefocusedprimarilyfromzeroto30,someissparsefrom

Figure(4g)considerstheconnectionbetweenageofownerandfirm’sperformance.Accordingtot his plot, it is likelythathighergrowthrateisobservedin thosefirmswithyoungmanager,specificallytheageofmanagerisbelow35yearsold,andfollowedby60yearsold.Furthermore,thespreadofdatasetis quiteequalandfrom23 to 69yearsold

REGRESSION RESULTS

Formal i =α0+α1Firmage+α2Firmsize+α3Governmentassistance+α4 Networks+α5A g e +α6Gen der+ α7Education+α8Ownership +α9Industry+α10Region+ε1

Informal i =α0+ α1Firmage+α2Firmsize+α3Governmentassistance+α4 Networks+α5A g e +α6Ge nder+ α7Education+α8Ownership +α9Industry+α10Region+ε2

Table4.8Determinantsofformal/informalfinance accessibility( Fullversionispresentedi n Appendix6 )

***, **, and *presentstatisticalsignificance levelat1%,5%,and10%,respectively.z- statisticsarereportedinparentheses.

Table 4.8 presents the findings from both the bivariate probit and probit models The results indicate that the rho value is 0.003 with a probability greater than chi-squared of 0.9591, suggesting that the error terms of each equation are not correlated Consequently, we can independently analyze each equation using the probit model Additionally, the outcomes from both the bivariate probit and probit models show no significant differences, allowing us to utilize either set of results For this analysis, I have opted for the probit results for convenience in relation to upcoming outcomes.

The analysis of factors influencing the likelihood of securing formal loans reveals several key insights According to Table 4.8, column (3), firm size, government assistance, and strong banking connections positively impact access to official loans, while networking with officials and firm age have negative effects Further details in Table 4.8, column (4) show that firm size, government assistance, and close relationships with banks are statistically significant at 1%, indicating a strong correlation with loan accessibility Specifically, a 1 billion VND increase in firm size (total assets) correlates with a 0.6 percentage point increase in the probability of obtaining a loan from formal sources, highlighting that larger firms have a greater capacity to secure bank loans.

D.K NguyenandRamachandran( 2 0 0 6 ) ’d i s c u s s i o n , whent h e asymmetricinformationan da g e n c y p r o b l e m b e c o m e pronounced,a s s e t s , s p e c i f i c a l l y t a n g i b l e asset sw i t h highvaluecouldhelpfirmsenhanceformalfinanceaccessibilitysmoothly.Again,thepo sitiveconnectionbetweenthesizeoffirmandfirmperformanceisfoundin(Becketal.,2005

;Bigstenetal.,2003;Saeed,2009)’sfindings.Next,receivingsupportfromthegovernmentandha vingclosedrelationshipwithbanksalsopositivelyhelpfirmstoaccessbankloanat1 % levelo f s ignificance.Specifically,i f f i r m s receivegovernmentassistance,t h e p r o b a b i l i t y of gettingofficialloanwillincreaseby35.4percentagepoints,ascomparedtot h o s e firmsnot.Inp ractice,underthedirectionofthegovernment,policylendingwithlowinterest/ softl o a n s fromVietnamDevelopmentBanko r VietnamBankf o r SocialPolicy,t a x exemptio no r r e d u c t i o n ared e p l o y e d t o f a c i l i t a t e S M E s developandaccessm o r e t o standard finance.

Itisanadvantageingetting formalloanfor thoseenterpriseshavinga goodrelationship withbanks.Theresultssuggestthataoneunitchangeinthenumberofbankst h a t firmsregular lycontactwith,increasestheprobabilityofaccesstoformalloanby0.06,ceterisp a r i b u s T h e p o s i t i v e relationshipbetweent h e s e t w o explanatoryvariablesandformalcreditaccessibil itycouldbefoundandreconfirmedin(Fraseretal.,2013)and(N.

T.Nguyen,2014).However,at10%significantlevel,networkwithpoliticiansisnegativeeffect onobtaining bankl o a n A oneun it change i n thenumber of politicians that firmsre gularly contactw i t h w i l l leadt o a decreaseo f 0 0 1 i n t h e p r o b a b i l i t y o f gettingbankl o a n , h o l d i n g o t h e r thingsremainunchanged.T h e negativerelationshipbetweenofficialnetwo rksandaccesst o bankl o a n i s i n accordancew i t h Leetal.

In a 2006 study, researchers examined the access to formal loans among Vietnamese private firms, revealing a negative relationship between connections with government officials and the ability to secure bank loans The authors noted that strong ties to government officials facilitate access to aid donations and government support programs, which are often more affordable than bank loans, thereby reducing the necessity for bank borrowing Additionally, the study found that while networks with other firms had a negative impact, connections with different networks positively influenced access to bank loans; however, these effects were not statistically significant.

The age of firms negatively impacts their ability to secure formal financing, showing statistical significance at the 10% level Interestingly, this finding contrasts with the majority of existing empirical studies Specifically, for every additional year of a firm's age, the likelihood of obtaining a bank loan decreases by 0.2 percentage points Accurately determining the age of firms in Vietnam is challenging, as companies that go bankrupt disappear from the market, while former owners often establish new businesses, creating a phenomenon known as "new bottles sold wine." This complicates the measurement of a firm's true age in the Vietnamese context.

Regardingtoowner’scharacteristicssuchastheageofowner,genderandeducationalattainm ent,theresultsindicatedthatthosevariablesarenon- statisticallysignificantat10%level.However,malemanagerswithhighereducationalattainme ntarefoundeasieraccesst o bankloanthantheothers,butnotsignificant.Theinsignificanteffecto fowner’seducationongettingloanfromfinancialinstitutionsisin accordancewith N T.Nguy en

(2014)andT h a n h , Cuong,Dung,andC h i e u ( 2 0 1 1 ) whent h e a u t h o r s investigatedetermi nantsaffecttheaccesstoformalfinanceofSmallandMediumSizedEnterprisesinVietnam.Overal l,t h e signo f genderande d u c a t i o n i s asexpected,exceptt h e signo f owner’sage,but all arenotsignificant.

Withregardtoformofownership,theresultspresentedthatlimitedliabilityandjoint- s t o c k companyh a v e higherprobabilityo f accesstostandardfinancethanhouseholdestabl ishmentby1 7 3 a n d 2 4 3 percentagep o i n t s , r e s p e c t i v e l y at1%significantl e v e l TheseoutcomesareconsistentwithDemirgỹỗ-

KuntandLevine(2005)wherestateownedcompanieshavem o r e advantageoust h a n h o u s e h o l d establishmenti n o b t a i n i n g formalfinance.Further,undergonethefinancialcrisisi n2008,thegovernmentimplementedsomepoliciestofacilitateSMEsdevelopmentaswellasthe creditaccessofthesefirms.Somepoliciescouldbegivensuchassupporting thefinancialinst itutions tolend more,establishingcreditguaranteefu nds , p r o m o t i n g financialconsulting.I n addition,t h e governmentalsosupportsSMEstopreparetheproceduretomeetthefinancialinstit ution’srequirements.A s a consequence,b o r r o w i n g f r o m formals e c t o r s ee ms t o b e m or e accessibleovertheperiodofsurvey,especiallyforlimitedliabilityandjoint- stockcompany.

The analysis of industry dummy variables indicates that the wood and wood products sector has 9.3 percentage points higher access to official finance compared to the food and beverages sector, at a 1% level of significance Additionally, furniture manufacturers and textile industries have easier access to standard loans, with 10 and 12 percentage points higher access, respectively, at 5% and 10% significance levels Conversely, the services sector shows a lower accessibility to formal finance compared to the food and beverages sector, with a difference of 4 percentage points, though this finding is not statistically significant These results contradict the findings of Toni et al.

(1998),whiletheyclaimedthatmain sectorssuchastradeandservicesfoundeasiertogetform alloan,relativeto other industries,

SMEsdatainVietnamshowedreversedoutcomes.Itislikelythatservicesectorhasnotbeenaspe arheadindustryinVietnamatleastin2012.Thenumberofserviceenterprisesandthecontribu tionofthesefirmstoGrossDomesticProduct(GDP)isnotlargeenough(36-

37percentagesofGDPaccordingtoMinistryofForeignAffairs).Asaresult,policiessupportfrom thegovernmentandtheaccesstoformalcreditofthistypeofindustryisquitelow,relativet o t h e o t h e r groups.T h e l a s t i s t h e effecto f regiono n accesstoformalcredit.

According to the findings presented in Table 4.8, at a 1% significance level, the Red River Delta, North Central Coast, and Southeast regions exhibit a lower probability of accessing formal credit compared to the Northeast regions, with differences of 14, 13, and 22 percentage points, respectively This aligns with Mai's (2014) research, which utilized SME data from 2011 to analyze the determinants affecting access to institutional credit Mai concluded that firms in the Red River Delta and Southeast areas face higher credit constraints compared to those in the Northeast This raises the question of why certain regions have a more favorable access to formal credit than others.

(2012)claimedt h a t enterpriseslocatedinindustrialzone,aremorelikelytoobtainofficialcredit thantheothers.LookingbacktothecaseofVietnam,accordingtothedatasetpublishedonMPI’s officialwebsite,w h i l e thereare8industrialzoneslocatedinRedRiverDelta,thesefigure sare4and3inNorthcentralcoastandSouth- eastregions,respectively.Asaresult,theaccesstoinstitutionalcreditoffirmslocatedinRedRiv erDeltaismoreavailablethantwom e n t i o n e d regions.However,i t i s s t i l l lowert h a n Northeastareasb a s e d o n t h e resultsindicatedinTable4.8

The determinants influencing the likelihood of choosing informal loans reveal that enterprises with strong relationships with banks, particularly male-headed firms, have a positive impact on access to informal credit Notably, older managers are less likely to seek non-official credit The data indicates that a one-unit increase in the number of banks a firm regularly contacts enhances the probability of accessing informal credit by 1.8 percentage points, all else being equal While networking with others does not affect formal loan access, it significantly increases the likelihood of obtaining non-formal credit, with a 10% significance level showing that each additional contact raises this probability by 0.001 The positive correlation between social networks and informal credit accessibility is supported by Essien and Arene (2014), who emphasize the importance of close connections between borrowers and lenders in informal contexts In less developed countries like Vietnam, where financial and legal systems are underdeveloped, social networks play a crucial role in facilitating credit access For instance, strong relationships with banks can expedite loan processing, while informal arrangements may allow individuals to act as guarantors, ensuring debt repayment Overall, these findings underscore the vital role of social networks in transition economies.

Receiving government assistance is viewed positively; however, firm age and size negatively affect access to informal financing sources, although these variables are not statistically significant at the 10% level Notably, the owner's age has a negative and significant impact on access to informal credit at the 5% level Specifically, for each additional year in the owner's age, the likelihood of accessing informal credit decreases by 0.1 percentage points, all else being equal This indicates that older managers are less likely to secure informal loans compared to their younger counterparts, which aligns with the findings of Akoten et al.

In 2006, it was found that younger business owners with fewer assets and limited social networks tend to rely more on borrowing from family and friends compared to older entrepreneurs Male-headed firms have an easier time securing informal loans, with male-owned businesses being 1.9 percentage points more likely to obtain informal credit than female-owned firms, although this finding was not statistically significant Educational attainment showed a positive but insignificant effect on borrowing Additionally, joint-stock companies were found to have a 3.6 percentage point lower probability of accessing informal loans compared to household businesses, likely due to government policies that favor formal credit for larger companies In terms of industry, only the machinery and equipment sector demonstrated a higher likelihood of accessing informal credit than the food and beverage sector by 8 percentage points Lastly, firms in Central Highland areas had a 10 percentage point higher probability of accessing informal credit compared to those in Northeast regions, likely due to the density of banks and economic activity levels, with areas like Lam Dong facing lower economic activity and bank density compared to major cities like Ho Chi Minh City and Hanoi.

In examining the factors influencing firms' access to formal and informal financing sources, I conducted a regression analysis to test for endogeneity in growth The dependent variables used were growth_1, representing the log change in sales revenue from 2011 to 2012, and growth, defined as the percentage change in sales revenue over the same period However, the regression using growth faced endogeneity issues (refer to Appendix 9) To address this, I employed two-stage least squares (2SLS) with Networks as the instrumental variable (IV) The findings on how various financing sources impact firm performance are detailed in Table 4.9.

***, **, and *presentstatisticalsignificance levelat1%,5%,and10%,respectively.t- valueisreportedinparentheses.

Overall,thesignofvariableinbothgrowth_1andgrowthmodelarequiteconsistentw i t h eachother.Throughouttwomethodsofcalculationfordependentvariable,theresultss t a t e t h a t whereasofficiall o a n doesp o s i t i v e l y affectfirmperformance,t h e r o l e o f n o n - officialcreditonsalesgrowthisambiguous.

Firstly,weconsidertheresultsofgrowth_1,whichispresentedinTable4.9,column(7).Bas edontheresultsofendogeneitytesting(seeAppendix8),growth_1isnotexperiencedendog eneityproblem,soOrdinaryLeastSquare(OLS)simplycanbeapplied.Inaddition,inordertoint erpretthemarginaleffectingrowth_1model,itisquitedifficult,s o Ijustsimply tellthedirecti onofeffectonfirmperformance.AccordingtoTable 4.9,column(7),thefinancingchoicessho wedapositiverelationshipwithsalesgrowth.However,whileonlyofficialcreditissignificantat5

Research indicates that there is no evidence supporting the role of non-official loans in firm performance at a 10% significance level, aligning with Ayyagari et al (2010), who assert that the formal sector significantly contributes to enhancing firm performance Interestingly, the impact of firm age on growth rate is negative and significant at the same level, consistent with findings from Rahaman (2011) and the evolutionary theory proposed by Nelson and Winter (2009) According to this theory, the effect of firm age on performance varies based on the innovation process within the industry Specifically, in a "routinized regime," where innovation stems from accumulated non-transferable knowledge, firm age positively influences performance Conversely, in an "entrepreneurial regime," where knowledge is less routine, the relationship between firm age and performance becomes negative.

Firm size significantly influences performance, with larger firms experiencing reduced barriers to growth related to access and cost of finance, as supported by Kumar and Francisco (2005) Increased firm size also mitigates challenges such as high tax rates and corruption, leading to enhanced benefits for performance While government assistance positively impacts performance, it is not statistically significant at the 10% level Owner characteristics reveal that age negatively affects outcomes, as older managers tend to be more risk-averse, resulting in slower growth compared to younger owners Industry analysis indicates that most sectors exhibit lower sales growth than the food and beverage industry, particularly in rubber-plastic, fabricated metal, machinery-equipment, and service sectors, which show significantly lower growth rates at the 1% level Notably, firms owned by partnerships or cooperatives demonstrate higher growth rates than those operated as household businesses, significant at the 10% level.

The article discusses the second method of calculating sales revenue growth, highlighting the issue of endogeneity in growth measurement To address this, the author utilized Networks as instrumental variables (IV) and the Two-Stage Least Squares (2SLS) method, as Ordinary Least Squares (OLS) yielded biased and inconsistent results Additionally, the findings in Table 4.8 indicate that financing decisions are not interrelated Consequently, the outcomes derived from both bivariate probit and probit models are consistent The primary interpretation focuses on the results presented in Table 4.9, specifically column (10), while column (9) serves as a reference.

Table 4.9, column (10), illustrates the impact of different financing choices on sales growth, revealing that both formal and informal credit are statistically significant at the 1% level Notably, access to formal credit correlates with a higher growth rate of 11.23% compared to firms without such access, while informal credit is associated with a significant reduction in growth rate by 40.52% This aligns with Saeed (2009), who noted that formal financing positively affects firm performance, whereas informal sources have the opposite effect Overall, the findings indicate a positive and statistically significant role of formal credit in fostering sales growth, with no evidence supporting a negative relationship between underground credit and firm performance Additionally, the relationship between firm age and growth is negative and significant at the 10% level, indicating that a one-year increase in firm age results in a decrease in sales growth.

The analysis of SMEs in Vietnam reveals that most firms operate within a household basement framework, lacking a "routinized regime" that fosters innovation through transferable knowledge This results in a negative correlation between firm age and growth rate in Vietnam While firm size positively influences sales growth, its significance diminishes in certain models Government assistance is closely linked to access to official loans; however, its importance in growth models is less pronounced and not significant at the 10% level This may be due to the state's ability to direct banks to lend more, thereby impacting formal credit access rather than directly influencing sales growth Additionally, similar to previous findings, the effects of gender and owner’s education on growth rates are not statistically significant at the 10% level, but the age of the owner significantly negatively impacts firm performance at the 5% level, with a one-year increase in owner age leading to a decline in performance by 14.1 percentage points, ceteris paribus.

KEYFINDINGS

This study utilized a bivariate probit model and instrumental variable method to analyze the determinants affecting access to formal and informal financing sources for Vietnamese SMEs in 2013 The findings reveal that firm size, government assistance, and strong relationships with banks significantly enhance the likelihood of obtaining formal credit Contrary to previous research, factors such as firm age and connections with government officials are shown to decrease the probability of securing official loans Additionally, owner characteristics like age, gender, and education do not significantly influence access to formal credit Notably, limited and joint-stock companies have a higher chance of accessing official financing compared to household establishments Firms operating in sectors such as textiles, wood products, furniture manufacturing, and chemicals are more likely to secure formal financing than those in the food and beverage industry Furthermore, SMEs located in the Red River Delta, North Central Coast, and Southeast regions exhibit a lower probability of accessing formal loans compared to those in the Northeast region.

Regardingtodeterminantsaffecttheaccesstoinformalsource,thisstudysuggeststhatgoodco nnectionw i t h b a n k s ando t h e r s playanimportantr o l e i n o b t a i n i n g n o n - f o r m a l f u n d M o r e interestingly,w h i l e owner’sageandgenderd o n o t impacto n p r o b a b i l i t y ofgettingformalloan,thesevariablesaresignificanteffectonobtainingnon- formalcredit.Indetail,o l d ownersarel e s s l i k e l y toborrowfrominformalsectorandm a l e - h e a d e d firmshaveahighprobabilityofaccesstonon- formalsource,ascomparedtotheircounterparts.Furthermore,thefindingsalsoindicatethatfir mageandfirmsizearenotconsideredasam a t t e r ingettingnon- formalloan.Besides,firmsdobusinessinmachinery- equipmentorfurnituremanufacturing,andlocatedincentralhighlands,Mekongdeltaaremoreli kelytoborrowfrominformalsource.

Withthesecondresearchquestion,howdifferentsourcesoffinanceaffectsalesgrowth,thest udyclearlyindicatesthatformalloanplaysapositiveroleinfosteringfirmperformance,w h i l e t h e r o l e o f informals o u r c e i s negativeorn o i m p a c t o n enhancinggrowthrateforbo thmeasurements.ThesefindingsareinlinewithAyyagarietal.

(2010)wheretheauthorsclaimedthatnon- standardfinancingmechanismisnoteffectivechannelt o substituteformalsectorforenhanc inghigherfirmperformance.Furthermore,whiletherelationshipbetweenf i r m ageandgrowthr a t e i s negativeandsignificanti n b o t h t w o measurements,theeffectoffirmsizeongrowthissi gnificantlypositiveornoimpact.Goesagainstcommonwisdom,thisstudyindicatesthatwhilet heageofownerissignificantly negativeimpacto n firmperformance,gendera n d educational attainmento r governmentassistanced o n o t affectsalesgrowth.Besides,firmsa r e l i s t e d i n j

POLICYIMPLICATIONS

Empirical results indicate that firm performance can be significantly enhanced through increased access to bank credit However, many firms face administrative challenges in obtaining clearance from bank authorities, which accounts for 40.25% of their difficulties Other obstacles include a lack of collateral (27.67%) and complex government regulations (16.98%) To improve conditions for firms seeking loans, the government should simplify administrative procedures and address non-performing loans to widen credit access for SMEs Additionally, maintaining macroeconomic stability, with inflation rates below double digits and low lending rates, is crucial Establishing more credit guarantee funds for SMEs and offering short training courses on financing requirements will further support businesses The data also suggests that firms run by younger entrepreneurs tend to grow faster than those led by older owners To boost economic performance and firm growth, the government should create a favorable legal environment for startups and facilitate access to formal loans Industries such as textiles and furniture manufacturing experience less sales growth reduction due to easier access to formal finance, while sectors like apparel and rubber-plastic products face greater challenges Therefore, the government should focus on providing better access to official finance for these struggling sectors, alongside training programs on the business environment, export opportunities, and quality assurance initiatives like ISO 9000 to foster higher growth rates.

LIMITATIONSANDSUGGESTIONSFORFURTHERSTUDY

Limitations

Thestudyjust explorethedatasetofgrowthratein oneperiodanddueto thenon- a v a i l a b i l i t y of data, thisresearchcouldnotinvestigatetheimpactof internal fund, somefinancialindexesaswellaslagofgrowthon firmperformance.

Suggestionsforfurtherresearch

Asthelimitations thatI mentionedabove,one couldemploy alarger datasetcombi ningmanyp e r i o d o f growthr a t e anda p p l y G M M m e t h o d t o s o l v e e n d o g e n e i t y probleminpaneldata.Besides,somefinancialindexessuchasReturnonasset,leveragea ndthe lagofgrowthshould beconsideredingrowth’sequationforaccurateevaluation.

Thiss t u d y just examinest h e effectofformala n d informalf u n d o n s a l e s growthaswella sthedeterminantsimpactprobabilityofaccesstothesesources.Forfurtherresearch,o n e couldin vestigateo t h e r f u n d s suchasinternalandexternal,h o w t h e s e f u n d s affectsalesgrowthore mploymentgrowthinpaneldata.Inaddition,formalandinformalinthiss t u d y arebinaryvari able,andfor thefuturestudy,usingtheamountofformalandinformall o a n toevaluatetheeffectofthese sourceson outcomes is notthebadideas.

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HAS FIRM APPLIED FOR BANK LOANS OR OTHER FORMAL CREDIT SINCE 2011

DID FIRM EXPERIENCE ANY PROBLEMS GETTING THE LOAN?

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(1) See Greene,WilliamH.,Econometric Analysis,seventh edition,Prentice-Hall,2012 ,p.780

THE REASONS WHY FIRMS EXPERIENCED THE DIFFICULTIES IN GETTING BANK LOAN

Did not deliver a proper description of the potential of the enterprise Complicated government regulations

Administrative difficulties in obtaining clearance from bank authorities Other

WHY HAS THE FIRM NOT APPLIED FOR FORMAL LOANS SINCE 2011

Don’t want to incur debt Process too difficult Didn’t need one Interest rate too high

WHY FIRMS HAVE BORROWED FROM INFORMAL SOURCES SINCE 08/2011

Couldn’t get formal credit Most favourable interest Easier formalities

No collateral required Flexible payback Other

WHICH SOURCE OF LOAN IS CONSIDERED THE MOST IMPORTANT FUND FOR FIRM'S OPERATION

mvprobit(formal=firm_agetotal_assetsgov_assNW_firmNW_bankNW_officialNW_othersagegenderedu4

>edu5ow2ow4ow5ow7indus2indus3indus4indus5indus6indus8indus9indus10indus11indus12indus13

>indus16regi5regi6regi7regi8regi9regi10)(informal=firm_agetotal_assetsgov_assNW_firmNW_ban

> kNW_officialNW_othersagegenderedu4edu5ow2ow4ow5ow7indus2indus3indus4indus5indus6indus

>8indus9indus10indus11indus12indus13indus16regi5regi6regi7regi8regi9regi10),draws(500)

Coef Std.Err z P>|z| [95%Conf.Interval] formal firm_age total_assets gov_ass

NW_firmNW_b ankNW_offic ialNW_other s age gender edu4ed u5ow2o w4ow5o w7indu s2indu s3indu s4indu s5indu s6indu s8indu s9 indus10 indus11 indus12 indus13 indus16 regi5re gi6regi

000888.0292881.212594.0027374.2609821-.0008782.0077218.0050102.2131026.4893372.3539335.4500048.7353217.75948211.022724.7146873.4398775.6091019.5433359.757089.9186388.5412514.4524842.2743253.3964016.5844644.1609298-.2974679-.285148.3561845.5484499-.7481714.3646312-.5318684 informal firm_age total_assets gov_ass

NW_firmNW_b ankNW_offic ialNW_other s age gender edu4ed u5ow2o w4ow5o w7indu s2indu s3indu s4indu s5indu s6indu s8indu s9 indus10 indus11 indus12 indus13 indus16 regi5re gi6regi

probitformalfirm_agetotal_assetsgov_assNW_firmNW_bankNW_officialNW_othersagegenderedu4edu

>5ow2ow4ow5ow7indus2indus3indus4indus5indus6indus8indus9indus10indus11indus12indus13in

>dus16regi5regi6regi7regi8regi9regi10,robust

RobustSt d.Err z P>|z| [95%Conf.Interval] firm_age -.0069978 0036932 -1.89 0.058 -.0142363 0002407 total_assets 0214619 0041744 5.14 0.000 0132803 0296435 gov_ass 1.016597 1035941 9.81 0.000 8135568 1.219638

NW_others 0009691 0034714 0.28 0.780 -.0058348 007773 age -.0022391 0036872 -0.61 0.544 -.009466 0049877 gender 0732318 0728943 1.00 0.315 -.0696383 2161019 edu4 1713202 1668699 1.03 0.305 -.1557387 4983792 edu5 0442459 1652582 0.27 0.789 -.2796543 3681461 ow2 1757441 1315887 1.34 0.182 -.0821649 4336531 ow4 277403 246368 1.13 0.260 -.2054694 7602754 ow5 5560958 1016867 5.47 0.000 3567935 7553981 ow7 7115023 1639406 4.34 0.000 3901845 1.03282 indus2 369446 1836585 2.01 0.044 0094819 7294101 indus3 -.1778858 2477457 -0.72 0.473 -.6634585 307687 indus4 -.1035102 3317133 -0.31 0.755 -.7536563 5466359 indus5 3044673 1149246 2.65 0.008 0792193 5297154 indus6 3441633 1986185 1.73 0.083 -.0451217 7334483 indus8 4115039 2472147 1.66 0.096 -.0730281 8960358 indus9 2291564 1670091 1.37 0.170 -.0981753 5564881 indus10 1123924 1781841 0.63 0.528 -.236842 4616269 indus11 0648812 1038471 0.62 0.532 -.1386554 2684178 indus12 0098976 2075245 0.05 0.962 -.3968431 4166382 indus13 3230368 1325006 2.44 0.015 0633403 5827332 indus16 -.1391756 1393509 -1.00 0.318 -.4122983 1339471 regi5 -.5321599 1148322 -4.63 0.000 -.757227 -.3070929 regi6 -.5599238 1346637 -4.16 0.000 -.8238599 -.2959878 regi7 0823861 1323032 0.62 0.533 -.1769233 3416955 regi8 1753878 1733091 1.01 0.312 -.1642918 5150674 regi9 -1.030858 140634 -7.33 0.000 -1.306496 -.7552208 regi10 0360703 1639441 0.22 0.826 -.2852543 3573949

=.19706922 variable dy/dx Std.Err z P>|z| [ 95% C.I ] X firm_ageto tal_~s gov_ass*

_oth~s ageg ender* edu4* edu5*ow2

*ow7*ind us2*indu s3*indus

*indus6* indus8*i ndus9*in dus10*in dus11*in dus12*in dus13*in dus16*re gi5*regi

6*regi7* regi8*re gi9*regi

probitinformalfirm_agetotal_assetsgov_assNW_firmNW_bankNW_officialNW_others agegenderedu4e

>du5ow2ow4ow5ow7indus2indus3indus4indus5indus6indus8indus9indus10indus11indus12indus13

>indus16regi5regi6regi7regi8regi9regi10,robust

The analysis reveals that firm age and total assets have no significant impact on the outcome, with p-values of 0.432 and 0.188, respectively Notably, the variable NW_bank shows a strong positive correlation, with a z-value of 6.70 and a p-value of 0.000, indicating its significance Age is also significant, with a z-value of -2.13 and p-value of 0.033 Other variables, including gender and various educational levels, do not show significant effects, with p-values exceeding 0.1 Industry variables exhibit mixed results, particularly indus12, which is significant at the 0.036 level Regional variables show varied significance, notably regi8 with a p-value of 0.022 The constant term is significantly negative, suggesting a baseline effect on the model.

=.06881388 variable dy/dx Std.Err z P>|z| [ 95% C.I ] X firm_ageto tal_~s gov_ass*

_oth~s ageg ender* edu4* edu5*ow2

*ow7*ind us2*indu s3*indus

*indus6* indus8*i ndus9*in dus10*in dus11*in dus12*in dus13*in dus16*re gi5*regi

6*regi7* regi8*re gi9*regi

predictinformal_res,de(401mi ssingvaluesgenerated)

***, **, and *presentstatisticalsignificance levelat1%,5%,and10%,respectively.z- statisticsarereportedinparentheses.

Variable Obs Mean Std Dev Min Max formal_pb informal_pb formal_mv informal_mv 2181

sumformal_pbinformal_pbformal_mvinformal_mv

reggrowth_1formalinformalfirm_age total_assets gov_assage genderedu4edu5i.industry1i.ownersh

2113F(27,2085)= 2.35 Prob>F =0.0001 R-squared =0.0266 Root MSE =.24307 growth_1 Coef.

RobustStd Err t P>|t| [95%Conf.Interval] formal informalfirm

_agetotal_as sets gov_ass age gender edu4ed u5 industry1

reggrowthformalinformal firm_age total_assetsgov_assagegender edu4edu5i.industry1 i.ownership

2109F(27,2081)= 2.27 Prob>F =0.0002 R-squared =0.0306 Root MSE ".791 growth Coef.

RobustStd Err t P>|t| [95%Conf.Interval] formal informalfirm

_agetotal_as sets gov_ass age gender edu4ed u5 industry1

reggrowth_1formalinformalfirm_agetotal_assetsgov_assagegenderedu4edu5i.industry1i.ownersh

2388F(25,2362)= 2.72 Prob>F =0.0000 R-squared =0.0285 RootMSE = 2575 growth_1 Coef.

RobustSt d.Err t P>|t| [95%Conf.Interval] formal informalfirm

_agetotal_as sets gov_ass age gender edu4ed u5 industry1

reggrowthformalinformalfirm_agetotal_assetsgov_assagegenderedu4edu5i.industry1i.ownership

2382F(25,2356)= 2.41 Prob>F =0.0001 R-squared =0.0278 RootMSE ".643 growth Coef.

RobustSt d.Err t P>|t| [95%Conf.Interval] formal informalfirm

_agetotal_as sets gov_ass age gender edu4ed u5 industry1

reggrowthformal_mvinformal_mvfirm_agetotal_assetsgov_assagegenderedu4edu5i.industry1i.own

2129F(25,2103)= 2.57 Prob>F =0.0000 R-squared =0.0309 RootMSE #.099 growth Coef.

RobustStd Err t P>|t| [95%Conf.Interval] formal_mv informal_mvf irm_agetotal

_assets gov_ass age gender edu4ed u5 industry1

reggrowthformal_pb informal_pbfirm_age total_assetsgov_assagegenderedu4edu5i.industry1i.own

2129F(25,2103)= 2.41 Prob>F =0.0001 R-squared =0.0296 Root MSE #.114 growth Coef.

RobustStd Err t P>|t| [95%Conf.Interval] formal_pb informal_pbf irm_agetotal

_assets gov_ass age gender edu4ed u5 industry1