P ROBLEMSTATEMENT
Researchobjectives
Thisstudyd e t e r m i n e s t h e r e l a t i o n s h i p b e t w e e n l o a n s a n d n u m b e r o f e m p l o y e e s , w a g e s i n smallandmediumenterprises.From that,researchoffersthepolicyimpli-c a t i o n s toimprovetheactivityofbusiness.
Mainresearchquestion
Thisthesisinvestigates theimpactof loantoemployeeonthenumberofemployeesa n d thelabourcostsbyusingthedatasetofSur veyofSmallandMediumEnterpris- es whichisdonebytheCentral InstituteforEconomicManagementandpart ner.T hedataiscollectedfrom2009to2013duetoitsavailability.
P r o p en si t y ScoreMatchingMethod(PSM)combinedwithDifferenceinDifference(D D), accuracytestofmodel.
Thisthesisconsistsoffivemainchapters.Chapteroneisintroduction.Chaptertwoislite raturereview,includingreviewoftheoryandreviewofempiricalstudiesthatr el a t ed t otheimpactofloantoemployeeinSMEs.Chapterthreeisresearchmeth- odology;inthischapterwillbepresentaboutanalyticalframeworkandthemethod- ology,va ri ab le m e a s u r e , d e s c r i p t i v e s t a t i s t i c s t o d a t as e t C h a p t e r f o u r i s r e s e a r c h r e s u l t s , includingoverviewoftheresearchtopic,descriptivestati stics,resultsanddicussions.Chapterfiveisconclusionsand policyimplicatio nsinadditionthatislimitsofthestudy.
REVIEWOFTHEORY
Definitionof small andmediumenterprisesand types ofcredits
Enterprises can be classified based on the number of employees, including full-time, part-time, and non-permanent staff The World Bank defines enterprise scales as follows: microenterprises have 1 to 9 employees, small businesses have 10 to 49 employees, medium-sized businesses have 50 to 299 employees, and large enterprises have 300 or more employees In Vietnam, this classification also considers industry distinctions, as outlined in Decree 90/2001/ND-CP and Decree 56/2009/ND-CP.
CPsaidthatsmallb u s i n e s s e s from10to200employees,mediumbusinesseswith200to 300employ-eesinallindustriesexcepttradeandservices(Appendice1).
Capital( K ) i s u n d e r s t o o d a s t h e i n p u t s f o r p r o d u c t i o n s e r v e s a s machinery,equipment,l a n d , o r f i n a n c i a l ca pi tal I t ismobilizedfromvariousso ur ces A c - c o r d i n g tothisapproach,capitalandloanareunderstoodtobeidentical.
Informalcreditisacreditthatisprovidedbyfinancialintermediarieswhodonoth a v e thef unctionoflending.Itexistsmainlyintheformofprivateloanswithhighinterestratesand asymmetricinformation.
Theimpactof loans toemployeefrom producer theory
Loansdonotdirectlydevelopbusinesses.Thisfinancialsourcewill beallocatedthroughinvestmentininputssuchasworkshop,equipment,machinery,technology,
+ Increase Ability to invest + Increase investment by using better technology + Create opportunities to expand the small businesses + Diversification of economic activities
+ Increase in income for workers. + Increase Employment
Increas- ing of loans humanr es o u r c es , t h e n e x p a n d p r o d u c t i o n a n d b us i n e ss a c t i v i t y toi n c r e a s e s a l e s , p r o f i t a b i l i t y andscaleexpansion(NguyenKimAnhetal,2011).Whe nbusinessesinvestresources,theywillhiremorelabours,paymorewages(Figure2.1).
Accordingtoproducertheory,enterprisesoperateontheprincipleofminimizingp r o d u c t i o n costs.Whenloansincreased,thatisdescribedasfollows:
SupposetheproductionfunctionofenterpriseisQ=f(K,L)withtheoutputQ.Qisdep endentontheinputs(capitalK,laborLandotherfactors).Theunderlyingassu mp t i o n toproducertheoryistheminimumcostofinputs,denotedC.Thenext importantassumptionisthemarginalproductivityofcapital(MPK= f
Optimizingtheamountofcapitalandlaborinputofbusiness,KandLtomini- mize(2.1)withconstraints(2.2).Lagrangemultipliermethodisappliedtosolvetheproblem,L agrangeequations:
Source:SimulationPindyck,RobertS.andDanielL.Rubinfeld(2013),Gr aph7 8 , page253.
WithC0initialresources,businessrearchsmaximizeproductivityatoutputQ0w i t hinputK0an dL0.
Intheshortterm,thebusinessisdifficulttominimizecostsbecauseofthefix- ednessofcapitalelements.So,whenthecapitalincreases,resourceswillbeCredit +C0,productionincreasesintoQ1credit,hiringmoreworkersatL1.
Inthelongterm,businesseswilladjustboththeKandL,sothatthemarginalco st perunitofproductionincreasedfromtheadditionofonelabourequalsmargin- al c o s t p e r u n i t o f p r o d u c t i o n i n c r e a s e d f r o m t h e a d d i t i o n o f o n e u n i t o f c a p i t a l Fromequation(2.7):
So,inthelongterm,thebusinesscaninvestmorecapitalatK2andlabouratL2,b u t thebes tsituation:minimizethecostwithoptimaloutputisQ2credit.
Theoretically,businesseswillusetheloantoexpandtheirproductionbymore investinginthenumberofemployees;andwithfixedwage,thecostoflabourish i g h e r Fromthetheoryabove,thesubjectwillfocusontwohypotheses:
H2.1Formala n d i n f o r m a l c r e d i t h a v e a p o s i t i v e impactont h e l a b o u r co stsi n SMEs.
Factorsaffectingtheoperationof thebusiness
ThesubjectofthestudyistheimpactofloantosmallandmediumenterpriseinV i e t Na m,inotherwords,thecausalrelationshipoftheloantothesalaryandem- ploymentofSMEsbasedontheproducertheory.Businessesthattaketheinitiativet o loa nmaybedifferentfromabusinessthatdoesnotactivelyloantoexpandpro- d u c t i o n Withoutaloan,businesseswillusecapitalmoreefficiently, butusingmorelabour.Thenumberofemployeesandsalariesareinfluencedbymanyotherfact ors,a n d loanisjustoneofmanyfactors.Thestudyidentifiesanumberoffactorsth ati n f l u e n c e wagesandemployment,loanfirmsthathavethepotentialtobiastheim- pactofloans:
Labour productivity:The economist saidthatthe business wanttoincrease sala- ri e s foremployees, theymust i n c re a se l a b o u r productivity I f l a b o u r prod uctivity d o es notincrease,butwagesrise.Thatwillcausecapitaldeficitsbeca useproduc-tioncostsincrease.
Property:Itisoneofthemostvisibleinformationaboutthebusiness.Businessc r e d i t islimitedbylackofcollateral(GertlerandGilchrist,1991).
Yearsofbusiness:InVietnam,theageofabusinessinfluencestheviabilityandd e v e l o p m e n t ofthatbusiness(Hansenetal.,2009).Bentolilaetal.(2013)conclud- ed t h a t a g e a f f e c t s l a b o u r i n t h e e n t e r p r i s e B e c a u s e b u s i n e s s e s c o n n e c t t o m a n y sources,includingfinancialinstitutions.Therefore,theabilitytolo aniseasythann ew l y establishedenterprises.
Ownershipf o r m : eac htypeo f b u s i n es s, salarypolicyand rec ru it me nt wi ll b e d i f f e r e n t Typeofenterpriseaffectingtheparticipationofpreferentialinte restratep a c k a g e (DinhTuanMinhetal.,2010).Foreignownershipinfluencestheefficien cyaswellastheabilityofSMEstojointheinternationalproductionnetwork(Harvie,20
Characteristicsgroupoftheindustry:Eachindustryproduces differentproducts,s o thecombinationofcapitalandlaborisdifferent(Bentolilaetal,2013). Thecom- plex c a r e e r s r e q u i r e s k i l l e d l a b o r , a n d a r e highlyp a i d H i g h p r o f i t i n d u s t r i e s a r e moreaccessible tofinancialsources.Differenttechnologicallevelsapproachdiffer- e n t creditguarantees(Oh,Inha,etal,2009).
MarketSize:Theups anddownsofthemacroeconomyaffectthesize ofthe b u s i n e s s Enterprisesoperatingintheexportsectoraremorelikelytohaveaccesstoc r ed i t thaninthedomesticmarket(DinhTuanMinhetal.,2010).
Characterizedgroupbysize:Largefirmsthatapproachbanksorformalfinan- ci a l institutionsareeasierthansmallbusinesses(Harvie,2010).InAsia,companiesd ep en d onbanksaremainlylargecompanies(Claessensetal,2000).Medium- sizedfirmshaveaccesstoamuchhigherinterestratesubsidypackagethanmicroen ter- p r i s e s (Signore, 2015) Enterprisesize isoneofthefactorsaffectingthebu sinessperformanceo f V i e t n a m e s e e n t e r p r i s e s ( A r i K o k k o a n d F r e d r i k Sjoholm,2004;H a n s e n etal,2009).
Financialcapacity:It isalso consideredbymanyeconomiststobe characterizedbyitssize(Ramanathan,2002).Inamarketeconomy,financialcapacityis notonlyf r o m owncapitalbutalsofromloansources.Sobesidesfinance,loansals oaffectt h e employeeinthebusiness.
Regionalcharacteristics:Inputandoutputmarketsforenterprisesareasnearaspo ssi ble, t he moreaccessiblethebusinessis,thelesstimeandexpenseforthebusi- n e s s UrbanenterprisesintheSouthhavesignificantlyhigherinvestmentprobabili- t i e s than thoseintheNorthandruralenterprises(CIEM,2014),buturbanenterpris- es arelesslikelytosurvivethanrural(Hansenetal,2009).
WhenstudyingSME,itisdifficulttoidentifymicroenterpriseswiththecharac- teristicsofahousehold(Hulme,2000).Therefore,thecharacteristicofthebusinesso w n e r (sometimesalsothehouseholdhead)hasanimportantroleinallhouseholdbusi nessactivities.
REVIEWOFEMPIRICALSTUDIES
Impactof loan toSMEsinVietNam
WithmarketfailuresaffecttheoperationofSMEs,theStateneedstointervenet o helpSMEsdevelopsustainably,createjobsforworkers,increasewagesandin- c r e a s e socialwelfare.ThereasonswhichfortheStateinterveneinsupportingSMEsw e r e s ummarizedbytheWorldBankin2004:
Incompletei n f o r m a t i o n : I n f o r m a t i o n a s y m m e t r y m a k e s t h e m a r k e t f a i l u r e a n d financialinstitutionproblems,hinderingthedevelopmentofS MEs.Thesolu- t i o n istoimproveinstitutions,improvefinancialmarkets,andprovidedirectfinanc- i n g fromgovernmentforSMEstopromotegrowthanddevelopment.
PositiveExternal:SMEloanwillhelptoimprovecompetitivenessand entre- p r e n e u r s h i p ThegrowthofSMEsmakestheeconomychangeabouteffective nessa n d productivity,a n d i n c r e a s e s i n s o c i a l w e l f a r e f r o m t h e i n c r e a s e d b e n e f i t s o f c o m p e t i t i o n
PovertyRe d u c t i o n T o o l : T h e r i s e o f S M E s h e l p s t o promotee m p l o y m e n t moret h a n t h e g r o w t h o f l a r g e e n t e r p r i s e s b e c a u s e o f t h e m o r e l a b o r - i n t e n s i v e SMEs.Therefore,thepoliciessupportSMEstobelinkedtosocialwelfare.
In 2013, the SME Development Fund was established with a chartered capital of 2,000 billion VND Circular 13/2015/TT-BKHDT outlines the priority areas for support and the criteria for selecting beneficiaries In 2016, SMEs were offered a preferential interest rate of 5.5% for short-term loans and 7% for medium- and long-term loans; however, the fund's resources were insufficient to meet the enterprises' needs (Nguyen Xuan Thanh, 2016) Currently, the total credit debt for SMEs exceeds 977 trillion VND, accounting for approximately 25% of the economy's credit debt, as reported by the Ministry of Finance (State Bank, 2015).
State- ownedc o m m e r c i a l b a n k s , f o r e i g n b a n k s , j o i n t v e n t u r e s p r o v i d e f i n a n c e f o r S M E s a t a moderatel e v e l T h e o t h e r f u n d s comefromd o n o r o r g a n i z a t i o n s ( W o r l d Bank,2007).SOEsalsoloans,thatmakesthebudgettoSMEsle ss(PhamC h i Lan,2016).Economicstimuluspackagein2009combinedwith thefinancialinstitutionrestructuringeventin2012makescreditgrowthin2009and2010 highert h a n 30%.Inthisstimuluspackage,creditguaranteesforSMEsaccountedforabout29%(DinhTuanMinhetal,2010;TranHoangNhi,2009).
Infact,SMEshavelowofficialloaningrates.Theymustsatisfymanycriteria,re gulation,collateralassets,credithistoryfromcommercialbanks(PhanThiLinh,2 0
1 5 ) T h e r e f o r e , b u s i n e s s e s n o t onlyloanfromcommercial b a n k s b u t a l s o l o a n f r o m o t h e r i n f o r m a l s o u r c e s I n V i e t n a m , i n f o r m a l l o a n s a r e t h e mains o u r c e o f creditforSMEs,accountingforabout80percent,andofficialloansac countfor30p e r c e n t Smallbusinessesmainlyloanfromnon- banksourcessuchasinternalfunds
(savings,retainedearnings,familynetworks)andtheinformalsector(moneylend-ing)(OECD,2006).
Previousresearches
Intermsofbusiness,Wang(2013)usespaneldatabycollectingthedatasetfrom2 0 1 0 to2 011tolookattheimpactofmicrofinanceonnextyear'sperformance,in- cludingnetprofitgrowthandrevenuegrowth.DatacoveragewascollectedinTai- zh o u , ZhejiangProvince,China.Hisresearchshowsthatmicrofinancehaspl ayeda n importantroleinthegrowthofrevenueandprofitabilityofSMEs.Butthelimi- t a t i o n ofthearticleistheshorttimedata,soitisimpossibletostudytheimpactofmi c r of i n an c e onthegrowthofemploymentandwages.
Intermso f e m p l o y e e s , Ber ge r( 1 9 8 9 ) a n d P e t e r s e n ( 19 94 ) a r g u e s t h a t m i c r o - fi nance forSMEstendstostabilizeincomesratherthantoincrease,inotherwords,t o m aintainb u s i n e s s a c t i v i t y andn o t c r e a t e j o b s T w o o t h e r s t u d i e s u s e r a n d o m samplingontheeffectivenessofcorporategrantsforsimilarresults.Micro- enterpriser e s e a r c h , DeM e l , M c K e n z i e a n d Woodruff( 2 0 0 8 b ) c o n d u c t e d inS r i L a n k a andMcKenzieandWoodruff(2008)conductedinMexico.Randomselec teda m i c r o e n t e r p r i s e g r o u p i n e a c h c o u n t r y t h a t w a s f u n d e d f r o m 1 0 0
U S D t o 2 0 0 USD.Theauthorsfind evidencefromgrantsthatincrease incom eforbusinesses,whetherfinancedbycashorequipment,thesamematerialgives thesameresults.T h e resultsalsoshowthatone- timedonorsdonotraisepoorpeople'sincomebe- causetheroleofbusinessownersisnolongerimportant.Ontheotherhand,grantsdon otincreasetheincomeofself-employedwomen.
In a study conducted by Adorno and VandDg (2007) in Italy, the impact of subsidy policy under Law No 488/1992 was assessed using nonparametric methods and compared with conventional parameter methods, utilizing data from 1996 to 2000 The research revealed that the policy had a positive impact, with statistics indicating a decrease of 12% to 9% in certain metrics, a reduction in the number of employees by 25% to 11%, and a decline in fixed assets by 25% The findings suggested that the effectiveness of the policy increases with the level of capital subsidized; however, it also indicated a reduced marginal effectiveness of additional subsidies, implying that further subsidies may not yield significant benefits.
Signore and Pierfederico Asdrubali (2015) conducted a study combining PSM and DDM methodologies to evaluate the impact of credit on SMEs in the Middle East, utilizing data collected from 2005 to 2012 Their research indicated that the youngest and smallest SME groups benefited the most from credit access, with loans leading to a 17.3% increase in labor within the first five years By the sixth year, sales had risen by 19.6% However, SMEs faced challenges in resource allocation when relying on short-term loans, which were effectively addressed through medium-term financing solutions.
With9890businessesfromPCIsurvey,inwhere3225businessesreceiveda4%interestra tesubsidy.InVietNam,DinhTuanMinhetal.
(2010)studiedtheeffecto f i n t e r e s t r a t e s u p p o r t p o l i c y one n t e r p r i s e s ' o per at io ns T h e r e s u l t s s h o w e d t h a t interestratesubsidypackagehadhadapositiveim pactonlaborchange,butverylittle,onlyfewworkers.Enterprisesusedthiscapitaltoex pandshort-termproduc-t i o n byhiringmorelaborthaninvestinginmachinery andequipmentforlong- termp r o d u c t i o n Th e s u p p o r t was s u i t a b le for m e d i u m enterprises andmi ningco mp a- n i e s Limitationswerecross- data,sotheauthorusedtwomultipleregressionmeth- o d s andPSMonlyevaluatestheimpactatthetimeofthesurvey.
S UMMARY
Theimpactofloantosmallandmediumenterpriseshasmanydifferentresults.Basi ngontheassumptionthatpeoplearerationalatthemarginalpoint,firmswillu s e th eloantoinvestintheresourceswhichtheyusethemostprofitable.Forde- vel o p ed anddevelopingcountries,orintheshortandlongrun,themarginalutilityo f theplant,equipmentandlabouraredifferent.Theyoccurthedifferentimpactofl o a n to ment,workshops,technologytoexpandproduction.Itisevenpossibletouseloanstoinv estinotherresourcesnotforproduction.
NUMBER OF EMPLOYEES LABOUR COST
Loan (formal and informal) SMALL AND MEDIUM
The impact of loans Age of business owner The sex of business owner Loan history …
Age of busi- ness owner
Thissectionpresentsquantitativemethodsforassessingtheimpactofloancapita lan dtheproposedmodel.Section3.1saysaboutanalyticalframework.Section3
.2p r e se n t s t h e p r o p o s e d m o d e l , i n c l u d i n g t w o m o d e l s f o r t h e t w o i m p l e m e n t a t i o n st ep s, thevariablesusedforthemodel.Section3.3describesth edatausedforthemodel.
ANALYTICALFRAMEWORK
ECONOMETRICSMODELS
Impactassessmentmethodology
Thestudyestimatestheimpactofloantoemployee.Thenatureoftheimpactas- sessmentistoseethedifferenceinoutputafterintervention,relative tooutputinthea b s e n c e ofintervention.
Source:AcevedoandTan(2011).Figure1.1,Page3 Time
Inpractice,itisnotpossibletoobservethecaseofnointervention.Therefore,itisnecess arytocreateagroupthatisclosetotheparticipantgroup,calledthecontrolg r o u p andnotaf fectedbytheprogram.
Sincetheselectionvariableisnotrandom,itleadstoerrorinsampling,withun- observable characteristicsaffectingoutputandobservablecharacteristicsa ffectingt h e outcomeoreligibilityoftheloan.Therefore,theobjectiveoftheimpactass ess- mentwillbetoeliminatetheimpactofsampleselectionortofindtheappropriateme thodfortreatment.Commonmethodsinimpactassessmentstudies:
Byusingmultivariateregressionanalysis,thepolicyvariableisoneofthefactor sin fl uen ci ng theoutput.Theregressionmodelscommonlyusedare:
Witha1istherootcoordinates,,theaveragevalueofYwhenthe a2X2i=a3X3i= =akXki=0aiisthein dividualregressioncoefficients uiisestimatedresiduals,withexpectation0andfinitevariance
Tii sapolicyvariable,usuallyusingasabinaryvariable,thevalueis1iftheitho b s e r v a t i o nh a s p a r t i c i p a t e d i n t h e p r o g r a m T h e v a l u e i s 0 i f t h e ithobservationd oes notp articipateintheprogram.Policyvariablescanbecontinuoustreatment.
Xi(i=2… k)isi th i n d e p e n d e n tvariable.Thatistheobservablecharacteristicsofthebusiness.
Regressiontocontrolthedifferentiationoftheseobservationsaffectoutput, socoefficientsa k+1i s impactofjoiningtoloan.Thismethodisoftenusedintermsofd a t a at atime.Theaboveregressioncannot showtheimpactofpolicyinvolvementn o t related t ot h e d if fe re nt characteristics th at affect t he dependent v a r i a b l e This methodstronglya s s u m e s theform ofregressionandmayb e endogenous.Soapplyinglinearregressionwilloftenbein accurateinestimatingtheimpactofthepolicy.
PSMisthemethodusedtoevaluatetheimpactofatrendpoint.Assumingthata f t er controllingthedifferenceofobservations,theresultofparticipatinggroupsisthe
T probabilitymodeltocalculatethePip r o b a b i l i t yofthei th e n t e r p r i s eparticipatingint h e loa n.Khandker(2010)andRubin(1983)provethatthecomparisononP(X)isa l s o approxi matedonXundercertainassumptions.Theequationisasfollows:
Att h i s p o i n t , t h e b u s i n e s s g r o u p h a s t h e samer a n g e o f P i v a l u e s w i t h Xiattributesnottoodifferent.Basedonthegeneral support area,estab lishacontrol group(Appendix 5) Sincethen, the researchcaculatestreatment effecton the treat-ed-TOT,writtenintheformofmathematicsasfollows:
PSMhastheadvantageofidentifyingacontrolgroupthatdependsonmanyvaria- bles.However,thisapproachislimitedintermsofdata.Forunobservedattributes,i f t heerrorisnegligible,PSMshouldbecombinedwithanothermethodforregres-sion.
Thedifferenceindifferencemethodcomparestheimpactandcontrolgroupsbasedo n di fferencesintheresultsforeach observation period.Originalsurvey onboth n o n - p a r t i c i p a n t s andparticipants,theninvestigatedbothgroupsaftertheimpactofl o a n F r o m th ere, w e c a l c u l a t e d t h e d i f f e r e n ce b e t w e e n t h e m e d i a n r e s u l t s w h i c h observedintheinterventionandcontrol groupsbeforeandafter the program im- pact Thismethodhasaparallelassumption:Ifnopolicyisinvolvedthentheresultso fthetwo groupsareequal.
TheadvantageofDDisthatiteliminatessamplingerrorsandlowerscosts.B ut ifbeforetheintervention,thetrendofthetwogroupswasdifferent,thesam- plingerrormaynotbeconstantovertimeasassumedbytheDD.
Researchproposalandselectmodel
ThetopiccombinesPSMwithDDmethodtomoreaccuratelycomparecon- t r o l andparticipationunits.Thiscombinationcancalculatetheeffect ofob servedand u n o b s e r v e d t r a i t s u n d e r t h e c o n d i t i o n t h a t t h e p a r a l l e l h y p o t h e s i s e x i s t s F o r general data,theon- linelinearequationDDcalculatesthemediandifferenceintheou tp ut sbetweenparticip antsiandnon-joinjbelongingtothegeneralsupportarea:
First,w e w i l l p r e p a r e t h e r e g r e s s i o n o f a p r o b a b i l i t y f u n c t i o n thatc a l c u l a t e s t h e a b i l it y ofparticipantsofeachenterprisebasedonpre- programmedfeatures.Thenr e m o v e observationsthatarenotinthegeneralsupp ortarea(Figure3.3).Thisstepremovest h e s e c o n d k i n d o f d e v i a t i o n fromt h e o b s e r v a b l e c h a r a c t e r i s t i c s o f t h e b usin ess.
Theareaofremovingo bservations Generalsupportarea Theareaofremov- ingobservations TrendPoint Source:Khandkeretal(2010),Figure4.1,page59
OLSovertime,tocalculatetheeffectoftheprogram.Thisstepremovesthefirsttypeofe r r o r c a u s e d byt he u n o b s e r v e d c h a r a c t e r i s t i c s o f t h e b u s i n e s s A t t h i s sta ge,t h e proposed econometricmodelis:
Yit=β0+β1Time+β2Treat+β3Treat*Time+β4Zit+εit (3.6)
Time=0:Pre-programtimeistheendof2008intheresearchpaperTime=1:Post- programtimeistheendof2012intheresearchpaperTreat*Time:Interactivevari ablesofTreatandTimedummyvariablesZ itare controlvariables,bearingthechara cteristicsofthebusiness
0 1 2 3 4 :T he av er ag ev al ue oft h e par tic i pa ting group aftertheloan
Here,Timeisdummyvariable,usingtoimpactassessmentofbeginandendpro- gr am betweencontrolgroup andparticipatinggroup.It receivesthevalue“1”ifthet i m e ofsurveywasin2012,andthevalueis“0”iftimeofsurveyis2008.
Dependentvariables
LNWAGE represents the total average labor cost, including salaries, bonuses, allowances, and outsourcing, adjusted for inflation since 1994 This cost reflects the real expenditure on employees and incorporates additional labor costs like social insurance, training, and hiring Businesses that do not pay wages, such as self-employed individuals, are assigned a value of zero to maintain mathematical integrity without distorting costs The economic significance is expressed using the logarithm of the dependent variable, while lnLABOR refers to the natural logarithm of the total number of employees, encompassing both permanent and seasonal workers, regardless of their work hours This calculation captures the time taken at the end of the business year, summarized in economic accounts.
Independentvariables
DDcombinationPSM,sosomefeaturesmaybeusedforbothsteps.B u t ineachstepyouca nuseanumberofseparatevariablestoincreasethefitfore a c h model.
Anumberofstudieshaveusedtheobservedcharacteristicsofenterprisestoevalu- a t e t h e abilitytoreceivefinancialloans.DinhTuanMinhetal(2010)showedchar- acteristicsoftypeofownership.Targetmarket isdecisive forparticipatinginthe interestratesupportprogram.XWang(2013)points out that productinnovation,asw ellasmanagerialattitudesandcompetencies,laborproductivity,pastcredithisto- ry,retentionratesonimagerevenueaffectstheabilitytoreceivemicrofinance.The
(2009),somecharacteristicsaffectedt h e abilitytoreceivecreditincreasestoapointthen decreasessuchasturnover,age,enterprises i z e T h e r e a r e a l s o o t h e r c h a r a c t e r i s t i c s t h a t a f f e c t fixeda s s e t s , l a b o r productivity,R&D,ownership,andoccupation.
Somes t u d i e s u s e e n t e r p r i s e o b s e r v a t i o n a l c h a r a c t e r i s t i c s toc o n t r o l l a b o r e f f e c t s : B en to l i l a etal,
(2013)usesizecontrolvariables(assets),ageofenterprise,ageofenterprisesqu ared,provincial,sector,short-termbankdebt,long-termbankdebt.
PhamandLensink(2008)usehouseholdcharacteristicssuchasgender,marri age,ethnicity,educationlevel.Thefollowingindependentvariableswillbedefined(
Sign Variablename Describeandmeasure Markex- pectatio n
TREAT Variablejoinstoloan Dummyvariable:receivethevalueis1ifanyparti cipatingloansandthevalueis0ifnotparticipatingl oans
Dummyvariable:thevalueis1ifthetimeofsurve ywasin2012,recognizedthevalueto0iftimeofsu rveyis2008
Thevariableinteractionbetweentimeandgrou pbusinesses,estimatedcoefficientsofthevariab lesindicatetheimpactofloanstoemployeesint heenterprise
Dummyvariable:thevalueis1ifjointobor- rowoftheofficiallong- termloanbeforeprogramandthevalueis0ifnot.
Dummyvariable:thevalueis1iftheypar- ticipateintheofficialshort-termloanpro- g r a m fundsandthevalueis0ifnot.
MICRO EnterprisesScale 1 Dummyvariable:thevalueis1ifmicroen- terprisesandthevalueis0ifother -
LNASSET corporatefinancescale Naturallogarithmoftotalassetswhichcal- culat ed inmoney +
Dummyvariable:thevalueis1ifthehouse- ho ld enterprise,thevalueis0ifother -
EXPORT Market Dummyvariable:thevalueis1iftheexport,thevalu eis0if noexport +
Dummyvariable:thevalueis1ifthelandu s e ri ghts,thevalueis0ifthereisnolanduserights +
HAND Productiontool Dummyvariable:thevalueis1ifonlyhandtools,t hevalueis0ifother -
HAge entrepreneursage Measuredinyears,sincebusinessownersw as b orn +/-
Dummyvariable:thevalueis1ifmale,thevaluei s0iffemale +/-
Edu Academiclevel Dummyvariable:thevalueis1ifthehighschoolgr aduation,ifthevalueis0ifnot +
Dummyvariable:thevalueis1ifcollegean d univ ersityqualification,receivingaval-ueof0ifnot +
ShareDept Debttototalassets Liabilitiesdividedbytotalassetswhichcal- culatedinmoney - lnNSLD Labourproductivity Naturallogarithmofoutputdividedbythenumbe roffull-timeemployees +
Province Including10dummiesrepresenting10prov- incessurveyed +/-
1 Classification ofenterprises,Clause1,Article3ofDecreeNo.56/2009/ND-CP,dated30/6/2009
D ATA
Between 2009 and 2013, surveys were conducted, including direct interviews in 2013 with approximately 2,461 non-state SMEs in the processing sector (CIEM 2010, 2012, and 2014) In 2011, a follow-up survey involved 1,988 respondents from a total of 2,449 enterprises that had participated in the 2009 survey This survey spanned 10 provinces and cities, including Hai Phong, Ho Chi Minh City, Ha Tay 2, Phu Tho, Nghe An, Quang Nam, Khanh Hoa, Lam Dong, and Long An The sample selection was based on two data sources from the General Statistics Office of Vietnam (GSO), encompassing both formal and informal household enterprises.
Thestudyfocusedonthesurveyedenterprisesinallthreesurveys,toconductth estudyonthedatatable.Inaddition,anybusinessthatactuallyengagesinrealcrediti s con sideredtohavea loan.Thisstepeliminatesthe"yes"tothequestion"doesthebusinesshavealoan?"Butth efactthatitcan’tbeborrowedisnotaffectedbytheimpactoftheloan.
Alsoduetosomechangesinthequestions,therearesomeunobservabletraitsfrom2 0 0 9 t o2013,whichisunfortunatelyalimitationofthedataandaccessibilityoftheauthor'sdat a T oapply thePSM andD D combination, thesubject willselectthe p r e - p r o g r a m m e d featurestakenfromthe2009trend-scoringregression.Creditpro- grams( p o l i c y v a r i a b l e s ) a r e b u s i n e s s e s t h a t a r e b o r r o w i n g f r o m A u g u s t 2 0 0 9 t o A u g u s t 2011 Therefore, when applyingthe D D methodof p r e - p r o g r a m m e d eco- nomicaccountistheendof2008,theeconomicaccountaftertheprogramistheendo f 2012.
2 Ha TaywasincorporatedintoHanoiinearly2009.However,inHaTaythedataisstillconsideredasas e p a r a t e provi ncesothattheresultsofthesurveycanbecompared withpreviousyears.
OVERVIEWOFTHERESEARCHTOPIC
Thet o p i c u s e s d a t a s e t o f C I E M from2 0 0 9 t o 2 0 1 3 w i t h m a n y s t a t i s t i c n u m b e r which concernstoloans,labour,employment,investment,theproblemofbusi ness.T h e a i m o f p a p e r i s t o s e e k t h e impacto f l o a n t o SMEsa b o u t e m p l o y m e n t a n d wagesandanalyzeafewtheotherimpacts.
Fortheproportionofcreditsources:Inthedebtstructureovertime,thesourceo f l o a n s f r o m i n f o r m a l o r g a n i z a t i o n s i n c r e a s e d f r o m 5 3 % t o 5 9 % D a t a dif feredf r o m theOECD(2006)thatinformalloanstypicallyabout70%-
Source: Author of calculations from SME 2009, 2011, 2013
59%).Educationalattainmentalsochangedinthesample,h i g h schoolgraduationfr om59%to70%,andcollege-levelqualificationsalsoin- c r e a s e d from20%to25%.DatawasmostoftheKinh- ownedenterprise,fluctuatear o u n d 93%andlittlechanged.
Source:AuthorofcalculationsfromSME2009,2011,2013 prises,accountingforonly1.2%to4.4%.Privatebankalsoprovidedloansrangingf r o m 11%to17%.TheSocialPolicyBankhastendedtoreduceitsroleinthefor- malcreditsupplystructureforenterprises,from11%to8%.Thereisnosignificantchang einthestructureofofficialcapitalsupply.
Wheninterviewedaboutsourcesofinformalcredits,mostofthemwere fro mr e l a t i v e s , relatives,whoaccountedfor60% -
67%ofthesupply.Thisisfollowedbyo t he r privatesources,whichareprivatecreditinstit utionsfrom27%to20%.Enter- pr i se s alsoborrowfromotherenterpriseswiththeproportionfrom4%-10%.Other sourcesoffundingareinsignificant,rangingfrom2%to4%oftheinformalloanstructure.A swithformalcredit,thereisnosignificantchangeinsupplystructure.
DESCRIPTIVESTATISTICS
Table4.2displaysthestatistic summaryforallvariablesusedinthemodels.Th ep a p e r concentratestoanalyzethemainfactorsbetweenparticipatinggroupandcon- trolgroup.
Laborproductivity(mi llion / person/year)
Tolabourvariable, theaverage ofthecontrolgroupis 11- 12laborers, butpar- ticipatinggroupis25-26people.Totalassetof thecontrolgrouphastheaverageat989million,buttheparticipatinggroupis1773millio n.Thedifferenceis784mil-lion,neardoubleofthecontrolgroup.
Tosalaries,thecontrolgroupwas71millionVND,buttheparticipatinggroupi s 182 milliondong.Wesawtheparticipatinggroupinvestedintoassetsandlabourverymuch.T hemeanageofparticipationgroupexistsfrom13to14yearsandtheothergroupis15- 16years.Thescaleoftheparticipants islargerthanthecontrolgr ou p about22%
Thec o n t r o l g r o u p h a s moree x p o r t s 4 % , h a n d t o o l s l e s s t h a n 4 9 % a n d l o w technologylessthan8% Forbusiness owners, theparticipation grouphad moread- v a n t a g e s thanthecontrolgroup.Specifically,educationvariable(Edu)ofparticipa- ti o n groupgraduatedhighschoolat64%comparedto53%,andcollegequalifica- t i o n s ( P r o E d u ) w a s a t 2 3 % c o m p a r e d w i t h 1 5 % T h e meana g e ofp a r t i c i p a t i n g g r o u p (HAge)was43-44years,comparedwith46-47ofthecontrolgroup.
Thelaborproductivity(NSLD)oftheparticipatinggroupwas79millionV N D/ pe r so n / y e a r comparedwith55millionVND/person/ yearofthecontrolgroup,anaverageof24million/person/yearinastatisticallysignificant.
Thedebttoequityratio(ShareDept)oftheparticipationgroupwas16%whilethe controlgroupwas6%.
The analysis of student statistics in Table 4.2 reveals significant differences between two groups of enterprises during the pre-program period While both groups share similarities in employer gender and geographical area, the trend group outperformed the control group in various aspects Notably, participants in the trend group exhibited significantly higher wages and labor metrics Additional characteristics indicating better participation include increased exports, enhanced labor productivity, superior entrepreneurial skills, a younger workforce, and a reduced presence of micro and household enterprises (Appendices 9).
REGRESSIONRESULTS
OLSregressionresults
Afterthecorrelationanalysis(Appendices10),theOLSregression modeltoes- timatetheimpactofcredit:
(e 0.67 =1.95)forworkerswithnomeaningfulloan.Aftercontrol- l i n g forothercharacteristics,theimpactoftheloandeclinedbutremainedpositive at186%(e 1.05= 2.86)forsalaryand23%
(e 0.213= 1.23)foremployee.Controlledmodelsals oi n c r e as e d th e corrected R 2c orrection(from5% t o49%,from8%to7 3 % ) , withoutthehyperpolycermia(withvif