The impacts of export and foreign direct investment on total factor productivity evidence from cross country analysis

ProblemStatement

Iti s w i d e l y b e l i e v e d t h a t p r o d u c t i v i t y o r e f f i c i e n c y o f a n e c o n o m y i s t h e mostimportantdeterminantofincomeinthelongrun.Solow(1956)explained thateconomicgrowthwithouttechnologicalprogress(onesourceofproductivitygains) c a n n o t b e s u s t a i n e d a n d w o u l d b e s t o p p e d int h e l o n g r u n P a r e n te a n d P r e sc o t t (2004)a n d H a l l a n d J o n e s ( 1 9 9 6 ) s h o w t h a t p r o d u c t i v i t y d i f f e r e n c e s e x p l a i n t h e largep a r t o f incomed i f f e r e n c e s a c r o s s c o u n t r i e s B e c a u s e o f t h e i m p o r t a n c e o f p r o d u c t i v i t y toincome,manyscholarsandresearch ers havestudiedpossiblefactorsthatcanaffectproductivity.

Inrecentyears,crossborderinvestmentandtradeactivitieshaveincrea sedr e m a r k ab l y d e s p i t e t h e s e v e r e impactso f g l o b a l f i n a n c i a l c r i s i s I n

2 0 1 0 , g l o b a l f o r e ig n directinvestment(FDI)inflowsincrease$1.24trillion,anditi sexpectedtor i s e furthertowards$1.6-

$2trillionsin2012(UNCTAD,2011).Moreimportantly,F D I andtradeareconsidereda simportantsourcesofeconomicgrowth,especiallyf o r developingcountries. However,theempiricalquestionwhether FDIandtradeb e n e f i t f o r p r o d u c t i v i t y g r o w t h ind i f f e r e n t c o u n t r i e s a t d i f f e r e n t s t a g e o f dev el o p men t isstillaquestionofdebated.

This article explores the influence of exports and foreign direct investment (FDI) on productivity growth, particularly focusing on total factor productivity (TFP) It argues that exports and FDI serve as vital channels through which best practices and technological advancements can be integrated into the domestic economy While previous research has extensively examined the relationship between exports, FDI, and economic growth, the impact on TFP remains underexplored This study aims to fill that gap by introducing new instrumental variables for exports and FDI, utilizing a comprehensive dataset that encompasses more countries and years, and considering the effects of the global financial crisis on TFP.

ResearchObjectives

ResearchQuestions

Ino r d e r t o a c h i e v e t h e s e o b j e c t i v e s , myt h e s i s i s i n a n e f f o r t t o f i n d o u t answersforthethreefollowingresearchquestions: a Howdoesproductivitygrowthvaryacrosscountries? b Doexportshaveapositiveimpactonproductivitygrowthatcountrylevel? c DoesFDIhasapositiveimpactonproductivitygrowthatcountrylevel?

ResearchMethodology

03 coun tr ies from1996to2009.First,Iemploycrosssectiondataanalysistofindout theimpactsofFDIandexportonTFP.Ialsoaddresstheproblemofendogeneity whichisthecentralofourempiricalanalysis.Becauseofthepossibilityofendoge neitybetweenexport,

FDIandTFP.IwillinstrumentexportbythelandareavariableandFDIbylagFDI,distanc efromequator(latitude)andlandareavariables, andIwillruntwostageleastsquarere gression(2SLS)withthese instruments.Asamorecomprehensivewaysofrobustnesscheck,Ialsoreportther e su lt frompanelregressions.Theuseofpaneldatahasmanyadvantagessuchasw ecouldcontrolforunobservedheterogeneityandtoruleoutthebiasofomitte dvariable.

OrganizationofTheStudy

This thesis is organized into five main chapters following the introduction Chapter 2 establishes a theoretical framework, discussing the definitions of Total Factor Productivity (TFP) and Total Factor Productivity Growth (TFPG), while presenting theoretical insights and empirical works from previous scholars Chapter 3 outlines the research methodology, detailing the methods used to estimate TFP and TFPG, as well as the models developed to identify the determinants of TFPG Chapter 4 provides an empirical analysis, starting with a global overview of TFPG performance across countries, followed by regression results derived from cross-sectional and panel data Finally, Chapter 5 concludes the research and offers policy recommendations aimed at assisting lawmakers in formulating improved policies for Vietnam.

IbeginthischapterbydiscussingsomedefinitionwhichinvolvetoTFPandTFP G.N e x t , t h e t h e o r e t i c a l b a c k g r o u n d ofT F P G a l o n g w i t h i t s d e t e r m i n a n t s i s p resented Andthenitmovestotheinsightsofempiricalworksinordertoexh ibitt h e importantroleofFDIandexportinTFPG.

TotalFactorProductivity

Shima n d S i e g e l ( 1 9 9 2 ) d e f i n e s p r o d u c t i v i t y i s “ o u t p u t peru n i t o f i n p u t employed”.Similarly,Hulten(2009)definesproductivityastheratioofre aloutputt o aunitinput.Aswemeasurerealoutputper unitofuniqueinputincludingcapital,l a b o r , wehavedefinitionsof“factorproductiv ity”(suchascapitalproductivity orl a b o r productivity) Whenwe combineproductivityof all factorsof inputs, wehaved e f i n i t i o n oftotalfactorproductivity(Kopleman,1986,p.3)

Comin( 2 0 0 8 ) s t a t e s h i s d e f i n i t i o n s a b o u t t o t a l f ac t o r p r o d u c t i v i t y i n“TheN e w P a l g r a v e DictionaryofEconomics”as“Totalfactorproductivityis theportiono f outputnotexplainedbytheamountofinputsusedinproduction”.Basingont hisdefinition, TFP r ep rese nt sh owe ff ic ie nta nd in te nsei np ut s a r e u s e d i n t he p r o d u c t i o n togenerateoutputs.

In 1956, Solow introduced the concept of Total Factor Productivity Growth (TFP Growth), which refers to output growth that cannot be attributed to input growth TFP Growth is often viewed as the "Solow residual" derived from the production function, calculated by subtracting the growth rate of inputs from the growth rate of output This concept provides valuable insights into the variations in TFP across countries, primarily driven by differences in technology.

TheoreticalBackground

ExogenousGrowthTheory

Exogenousgrowththeory,whichisknownas“neoclassicalgrowththeory”,w a s i n d e p e n d e n t l y d e v e l o p e d byN o b e l P r i z e w i n n e r R o b e r t S o l o w ( 1 9 5 6 ) a n d prominenteconomistTrevorSwan(1956).Theirmodelbecomesam ainbranchofeconomicgrowththeoryduringtheyearsof1950sand1960s.Exoge nousgrowthmodeltriestoexplainforeconomicgrowthinthelongrunbyexploringfactor slikec a p i t a l accumulation,thegrowthofpopulationaswellasproductivity.

Y=A(t)F(K,L) (2.1) withYstandingforoutputorincome,Kisthecapitalinput, Listhelaborinput. A( t ) isthetechnologicallevelorknowledgelevel,andA(t)isafunctionoftime.Inth i s m o d e l , A ( t ) i s a s s u m e d t o g r o w a t e x o g e n o u s r a t e L a b o r f o r c e L i s a l s o assumedtogrowatconstantrate

Fromt h i s e q u a t i o n , wec a n r e c o g n i z e t h a t o u t p u t p e r c a p i t a d e p e n d u p o n capitalpercapita( K) andleveloftechnologyorknowledgeA(t).However,c a p i t a l

L perworkerisassumedtoexhibit adiminishingreturn.Thatis,whenwecontinuetoincreaseK,thecontributionofKtooutput growthwilldecrease.Wecanthinkasituationwhenwecontinuetoequipourworkerswith moreequipment,then graduallyextraequipmentbecomeredundantandmarginalproductivityofcapit alw i l l decrease.Hence,tohaveapositiveoutputgrowthpercapitainthelon grun,thentechnologyisakeydeterminant.

Neoclassicaleconomistsconsider“technologyprogress”asamainsourcetointe rpretfordifferencesinincomepercapitaofcountriesaslongasdeterminelongr u n growt hofeconomies.Forinstance,Solow(1956)explainsthatapproximately9 0 p e r c e n t o f incomep e r c a p i t a g r o w t h i n U S i s d u e t o e x o g e n o u s t e c h n o l o g y p r o g r e s s Inaresearchforthecontributionofphysicalcapital,humanca pitalandtechnologytoincomedifferencebetween127countriesintheworld.HallandJones

( 1 9 9 9 ) findthattechnologyp r o g r e s s contributes8.3whilehumancapitalandphy sicalcapitalcontribute1.8and2.2tothedifferencesinincome,respectively.

However,neoclassicalmodeltreatstechnologicalprogressasanexogeno usf acto r (thatis determinedoutsidethemodelasa“mannafromheaven”).Itprovidesn o insightsfor pol icyimplications andl eaves the dr iv er o f lo ng rungrowth withunexplained manners.Toovercomelimitationsofneoclassicalgrowthmodels,lattereconomistsh a v e d e v e l o p e d n e w g r o w t h theorythatc a n e x p l a i n s o u r c e s o f technologyprogressas wellasthereasonswhyitaffecttoeconomicgrowth.

EndogenousGrowthTheory

Endogenousgrowththeoryornewgrowththeoryisaneffortofeconomists( Arr ow (1 96 2) , R o m e r ( 1 9 8 6 ) , L u c a s ( 1 9 8 8 ) , R e b e l o ( 1 9 9 1 ) , a n d Gross mana n d Helpman(1991)t o e x p l a i n s o u r c e s o f t e c h n o l o g y p r o g r e s s I n s t e a d o f l e a v i n g technologyprogressasunexplainedfactor,t h e y attempt toe x p l o r e t h e c h a n n e l s w h i c h t e c h n o l o g y progress i s a f f e c t e d I n e n d o g e n o u s g r o w t h t h e o r y , t e c h n o l o g y p r o g r e s s occursthroughinnovation,invest mentinresearchanddevelopment,etc.

Learningbyd o i n g c o n c e p t m e n t i o n s a b o u t a b i l i t y o f w o r k e r s t o i m p r o v e theirproductivitythroughrepetitiontaskandpractice.Inlearningbydoi ngmodel,b o t h comparativeadvantageandgrowthareinvolvedtotrade.Trad emaychanget h e s t r u c t u r e ofspecializationofa country,andimpactsoftraderelyonthelevelof learningexternalities.Forintra- nationalspillovers,countriesspecializeinproducingg o o d s withhigherpotentialforlearningwi llgrowfaster.

Learningbyd o i n g i s f i r s t i n t r o d u c e d byA r r o w ( 1 9 6 2 ) A r r o w c o n s i d e r s techn ol og yprogressasa part ofeconomicactivities.Hestates thatalt houghnew k n o w l e d g e canbeproducedthroughrepetitiontask,butitisdecreasing Inordertocontinuethelearningbydoing process,weneedtostimulatethisprocessbyaddingne w flowofcapital.Hence,newinves tmentisconsideredasasourceofleaningbydoing.Wewillexaminethismodelcomprehe nsivelyintheproductionfunctiontaket h e formofCobb–Douglas:

Y BK  L 1   (2.4) whereYistheoutputofeconomy,Listhelaborforce,Kisthecapitalwhichi s include dbothphysicalandhumancapital.Bisthelevelofknowledgeincreasefr omlear ningbydoingprocess.

BA.K 1   withA>0 (2.5) Fromthelearningbydoingmodel,wecanconcludethatTFPisnotanexogenousfact orasinneoclassicaltheory,andhumanknowledgeisintroducedasa n o t h e r formofTFP.

PaulRomeristhepioneerintheintroductionofR&Dmodel.AspointedoutbyRome r(1990),knowledgeorideashavecharacteristicsofpublicgood,whicharenon- rivala n d n o n - e x c l u d a b l e N e v e r t h e l e s s , t h e u s e o f somes p e c i f i c k n o w l e d g e c a n b e e x c l u d e d byl e g a l p r o t e c t i o n F i r m s w h i c h w a n t t o m a x i m i z e t h e p r o f i t s usual ly e n g a g e i n d o i n g r e s e a r c h , a n d t h r o u g h p a t e n t l a w theyc a n p r o t e c t t h e i r inventionsforacertainperiod.Theexistenceofmonopolyprofitsprovi desincentiveforfirmstoinvestinresearchanddevelopmentactivities.However,it iss e e m i m p e r f e c t l y toe x c l u d e o t h e r f i r m s f r o m u s i n g t h e k n o w l e d g e Whent h e p r o t e c t i o n timeofpatentisover,othersfirmsthatoperateinthes ameindustrycan

(2.6) whereYdenotesforoutput,Kiscapital,Aisstockofknowledgeortechnology, wh i ch i s a l r e a d y e x i s t i n t h e economy.Wec a n simplyu n d e r s t a n d A asa c c u m u l a t i o n of a l l o f k no wle dg et hat al rea dy beenc rea ted byresearchersi n t he past.

Thismodelconsistsoftwosector.Thatis,R&Dsectorandgoodsector.Thep ar t ic ul ar roleofgoodsectoristoproduceoutputfortheeconomy,andR&Dsectoristocreatene wt e c h n o l o g y ork no wle dg e L a b o r int h e economy isemployedtop r o d u c e goods(LY)ortoresearchandcreatenewideas(LA).Laboristheeconomy

(L)equal:L=LY+LA.ModelforR&Dsectoris:

A    L A (2.7) where Ad e n o t e s  f o r n e w k n o w l e d g e orn e w t e c h n o l o g y t h a t h a v e j u s t invented, istherateatwhichnewknowledgeiscreated.Thisequationshowsthat newt e c h n o l o g y (ort o t a l f a c t o r p r o d u c t i v i t y gr ow th ) w i l l i n c r e a s e w i t h t h e p r o p o r t i o n oflaborinresearchactivities.Inaddition,weknowthattherate whichresearchersc r e a t e n e w k n o w l e d g e i s a f u n c t i o n o f e x i s t e n c e k n o w l e d g e i n t h e e co n o my andnumberofscientists(L A ).Wehave:

A representsamountofscientiststosearch fornewknowledge.Ifweincreaseamountofscientists,itislikelythattheamountofknowledg eisreduceduetoduplicationsameideas.

Itisclearfromequation2.9thatnewtechnology(orknowledge)dependsona m o u n t ofscientistsandaccumulationofknowledge.

Thisequationimpliesthatcountrieswhichhavebiggerstockofknowled gewouldexperiencefastertotal factorproductivity growth.Second,count riesinvestmoreinR&DalsohashigherTFPgrowth.

DiscussionabouttheoriesthatrelatestoTFPlevelandTFPGisveryuseful.Ithe lpsusaclearerunderstandingaboutTFPaswellastofindtheanswerfortheq uesti on “WhatisthetheoreticaldeterminantsofTFP?”

Int h e n e o c l a s s i c a l g r o w t h modeld e v e l o p e d byS o l o w ( 1 9 5 6 ) a n d S w a n ( 1 9 5 6 ) , t he f u n d a m e n t a l so u r c e s o f e c o n o m i c g r o w t h a r e c a p i t a l a c c u m u l a t i o n as w ell a s t e c h n o l o g i c a l p r o g r e s s S a v i n g playsa n i m p o r t a n t rolei n c a p i t a l a c c u m u l a t i o n T o a c q u i r e t e c h n o l o g y p r o g r e s s , i t ise s s e n t i a l t o h a v e n e w technology,therefore,changesintechnologyp r i m a r i l y havea strongimpactonT F P

However,t h e l a t e r t h e o r i e s e x p l a i n t h e t e r m “ T F P ” a s a measureme nto f p r o d u c t i o n e f f i c i e n c y H a v i n g considerthisdefinition,if anyfactoraffectsoninputand outputrelationship,itwouldhaveimpactonTFP.

Therea r e m a n y f a c t o r s i n f l u e n c i n g o n bothT F P l e v e l a n d T F P g r o w t h , whichi s d e s c r i b e d ine n d o g e n o u s g r o w t h t h e o r y I n a d d i t i o n , i t s t a t e s t h a t f o u r sourcesofTFPgrowth,including“economiesofscale,resourc eallocationefficiency,t e c h n o l o g y p r o g r e s s a n d h u m a n c a p i t a l ” a r e c o n s i d e r e d f u n d a m e n t a l sources(Huong2001,p.15).Fromfourfundamentalso urces,theyhelpeconomistsf i n d outmanymorefactorswhichaffectonTFPgrow thandTFPlevelthrough4t h e s e importantchannelssuchasFDIinflow,export,in vestmentinhumancapital,r e s e a r c h a n d d e v e l o p m e n t , h e a l t h , i n f r a s t r u c t u r e , i n s t i t u t i o n , t e c h n o l o g y t r a n s f e r , et c Someofthesefactorswillbeme ntionednext. a) ForeignDirectInvestment(FDI).

Thequestionwhether F DI benefitstoproductivityofrec ip ie nt count riesisstillacontroversialquestionbetweenscholars.ManyeconomistsbelievethatFDIisg oodforproductivitygrowththroughtechnologytransferandtechnologydiffusionc h a n n e l s M o t i v a t e d byp o s i t i v e e x p e c t a t i o n o f FDI,m a n y d e v e l o p i n g c o u n t r i e s haven u m e r o u s p o l i c i e s t o a t t r a c t f l o w s o f f o r e i g n d i r e c t i n v e s t m e n t , a n d theyco nsid er F D I a s a n i m p o r t a n t e x t e r n a l f i n a n c i n g s o u r c e t o b o o s t u p e c o n o m i c g r o w t h oftheircountry. Ontheotherhand,otherscholarsbelievethatFDIhasnop ar t icu l ar impactonpro ductivitygrowth.WhatistheargumentforandagainsttheimpactsofFDIonproductivit ygrowth?DoesFDIreallybenefitforproductivityofr e c i p i e n t countries?

Multinational corporations often encounter significant disadvantages and uncertainties when investing and operating in foreign countries, primarily due to a lack of understanding of local markets and regulations To mitigate these challenges, it is crucial for these corporations to leverage advanced technology and transfer it to their foreign affiliates, thereby enhancing their competitiveness Foreign Direct Investment (FDI) serves as a key mechanism for technology transfer, facilitating the introduction of advanced technologies into the recipient economy Additionally, FDI generates positive spillover effects, such as knowledge transfer to domestic firms, which can gain insights into management practices, marketing techniques, and production methods through observation and collaboration with foreign entities Employees in multinational corporations also benefit from rigorous job training, enabling them to share acquired knowledge with local firms or establish their own businesses in the future For instance, research by Javorcik and Spatareanu (2005) highlights that 25% of middle managers in these corporations eventually transition to local firms or start their own ventures, illustrating the significant impact of FDI on local economies.

Czecha n d 1 5 % p e r c e n t o f managersi n L a v i a ac k n o w l e d ge t h a t theyha ve s t u d y skillsandexpertisemanagementpracticesfrommultinationalcorporations.

EventhoughtherearelotsoftheoriestosupportthepositiveeffectsofFDIo nproductivity,resultsfromempiricalstudiesforFDI- productivitynexusarestilla m b i g u o u s Atmicro- levelstudy,AitkenandHarrison(1999)findanegativei mp a c t ofFDIontotalfactorp roductivitygrowthamongVenezuelanfirms.Theye x p l a i n f o r t h i s negative relationship isdue to “competitioneffect”.

Thatis,mu lt in at io nal c o m p a n i e s h a v e t e c h n o l o g i c a l a d v a n t a g e s i n producingg o o d s a n d services,sotheya t t r a c t customer’sd e m a n d f r o m localfirms Asa result,localfirmshavetoreduceitsproductionandshiftitsaveragecostcurveup. Inaddition,H add ad a n d H a r r i s o n ( 1 9 9 3 ) r e a c h a s i m i l a r c o n c l u s i o n f o r firmsi n Morocco.Aitken et al.

(1996)alsoconcludethatthereisexistencethenegativeimpact ofFDIonproductivitywhentheyconductaresearchonMexicoandVenezuelafirm s.Atmacrolevelstudy,Borenszteinetal(1998)reportanegativerelationshipbetwe enFDIandeconomicgrowthof69developingcountries.Theypointoutthatrecipientc o u n t r i e s canonlybenefitfromFDIinflows if recipient countries have sufficie ntl e v e l o f humanc a p i t a l Similarly,N e l s o n a n d P h e l p s ( 1 9 6 6 ) , a n d B e n h a b i b a n d S p i e g e l (1994)interpretthatifstockofhumancapitalisweakrecipie ntcountries,“absorptivecapacity”o r a b i l i t y t o l e a r n f r o m f o r e i g n f i r m s w i l l b e limited.F D I i n f l o w s thenmayhavenegativeimpactonproductivity. b) Export.

Inliterature, economistsmentionabouttwo- waylinkageoftrade andproductivity.Thef i r s t l i n k a g e layss t r e s s o n i m p o r t a n t r o l e o f e x p o r t o n p r o d u c t i v i t y growth.Thesecondreferstoreverselinkagefr omproductivitygrowtht o export.However, thepioneers ofexport- leddevelopmenttheoryoftenemphasizet h e indispensableroleofexportsinenhancingpr oductivityandefficiency(Haddad,

Exporting serves as a vital mechanism for firms to enhance their production methods through experiential learning According to Arrow (1962), learning arises from problem-solving activities, and countries that specialize in producing goods with higher learning potential can grow more rapidly The concept of learning by exporting highlights how firms improve productivity by engaging in international markets and leveraging the production knowledge of their trading partners To succeed in foreign markets, firms must understand customer demands and comply with quality and delivery standards, often receiving guidance from foreign purchasers on efficient production management and quality control Grossman and Helpman (1991) note that foreign agents may suggest improvements in manufacturing processes To remain competitive, exporting firms must also adopt advanced technologies to meet the expectations of international customers By expanding into foreign markets, firms can achieve greater economies of scale, reducing production costs and enhancing productivity growth Empirical research consistently shows that exporting sectors are more productive than non-exporting ones (Bernard and Jensen, 1999) Additionally, export activities enable countries to acquire foreign exchange, crucial for importing high-tech products and modern machinery, thus serving as a significant source of productivity.

Exporting firms encounter significant challenges and uncertainties when entering international markets, including high trading costs related to market research, distribution setup, and transportation They often lack knowledge about foreign regulations and customer demands compared to local competitors As a result, only productive firms can absorb these costs and engage in export activities Greenaway and Kneller (2007) highlight that higher productivity is a prerequisite for firms to consider exporting, indicating a causal relationship where productivity drives export decisions Furthermore, a country's productivity growth enhances its competitiveness by lowering prices and improving product quality, enabling it to export more effectively than others.

Ifwedon’ttakeintoaccount thereversecausalityofexportandproductivityg r o w t h in o u r m o d e l , t h e r esu lt s w i l l del iv er b i a s e d co ef fi ci en t He nce, we applyinstrumentalvariabletechniquestoso lveendogeneityproblems. c)HumanCapital.

Humancapitalisthecombinationofskill,health,experienceandknowledgea b o u t t h e p r o d u c t i o n o f labor.Humancapitali s c o n s i d e r e d a s a factorw h i c h determinest e c h n o l o g y p r o g r e s s a n d t e c h n o l o g y e f f i c i e n c y I n t h e r e s e a r c h a n d d e v e l o p m e n t models,AghionandHow itt(1998)andRomer(1990)findthatnumberofresearchers(orhumancapital)help stoaccelerateTFPGthroughinnovativenewtechnology.Inaddition,NelsonandPhe lps(1996)providestronge v i d e n c e s ontheimportantofhumancapitalonTFP G,theseevidencesreflectthef a c t thatcountrieswithhigherlevelofhumancap italcaneasilyadoptandimplementadvancedtechnologyfromthetechnologicalleadercoun tries.

When assessing the benefits of Foreign Direct Investment (FDI) in recipient countries, economists often refer to "absorptive capacity," which is the ability of these countries to effectively utilize capital inflows without diminishing the return on that capital The productivity of FDI can decline if the growth of foreign investment outpaces the workers' knowledge and skills in production methods, known as human capital Borensztein et al (1998) provide compelling empirical evidence that FDI contributes to economic growth only when recipient countries possess a sufficient level of human capital As developing countries typically have lower levels of human capital, they are unable to fully leverage the advantages of FDI, which may lead to negative impacts on their economic growth and productivity.

Economists(GrillichesandMairesse(1991),HallandMairesse(1995))havewidel ya c c e p t e d t h e p o s i t i v e l i n k b e t w e e n r e s e a r c h a n d d e v e l o p m e n t a n d p r o d u ct i v it y growth.T h e ideasimply isthatinvestmenti nR&Dstim ulatesinnovation.Innovationoffergreatopportunityforinnovatingfirmstoreducep r o d u c t i o n c o s t a s w e l l a s e n a b l e f i r m s p r o d u c e n e w p r o d u c t s a n d s e r v i c e s w i t h b et ter q u a l i t y frome x i s t i n g r e s o u r c e s R & D n o t onlyp r o v i d e s p r o d u c t i v i t y a n d profits forthefirmsthatconductR&Dactivity,italso bringbenefitsforotherfirmst h a t o p e r a t e i n t h e samei n d u s t r y t h r o u g h s p i l l o v e r e f f e c t F u r t h e r m o r e , R & D e n a b l e domesticcountries todev elopitsabsorptivecapacityandadaptadvancedtechnologyintoproductioninafast erway. e)Health

Thec o n n e c t i o n o f h e a l t h a n d T F P g r o w t h s e e m s t o b e c l o s e l y a s s o c i a t e d Obviously,ahealthyworkforcewillbemoreproductive,andgoodhealthwillhe lpw o r k e r s improvetheirabilitytoadoptnewtechnology.Poorhealthnotonlyaffectst o wealthandincomeofindividualsbutalsotoproductivityoftheeconomy.Takingmalariaas anexample,thediseasewhichindicatessevereimpactofpoorhealthonproductivity.A personwhosufferfrommalariausuallysickfrom12-

Malaria, while not always fatal, significantly impacts employee productivity and economic labor supply due to persistent headaches and fatigue even after recovery High mortality rates and disease burdens deter foreign investors, as unhealthy workers exhibit lower productivity, leading to increased production costs for businesses Consequently, developing countries in tropical regions, plagued by infectious diseases, struggle to attract foreign direct investment (FDI) and face limited technological advancements Additionally, poor health conditions hinder human capital accumulation by reducing school attendance rates, ultimately stifling productivity growth and resource distribution efficiency As a result, substantial government expenditures on healthcare, such as anti-malaria initiatives and combating undernourishment, divert funds away from encouraging research and development in the private sector.

Institutions play a crucial role in explaining the disparities in wealth across countries, as effective institutions can stimulate saving and investment while ensuring efficient resource allocation, leading to higher Total Factor Productivity (TFP) growth For example, research by Easterly and Levine (2002) highlights how strong political institutions that secure land rights encourage farmers to invest in large-scale production, benefiting from economies of scale Conversely, inadequate institutions and policies can severely hinder productivity and economic growth Acemoglu, Johnson, and Robinson (2001) illustrate that colonial institutions often failed to protect private property rights, discouraging investment incentives and limiting opportunities for innovation and foreign direct investment (FDI) Additionally, scholars like North (1981), Mokyr (2002), Hall and Jones (1999), and Ashraf and Galor (2007) provide evidence that robust institutions facilitate advanced technological research and knowledge diffusion.

A robust infrastructure system, encompassing roads, electricity, and water supply, is essential for enhancing productivity and economic efficiency It fosters investment, capital accumulation, and technology transfer Hall and Jones (1996) emphasize that infrastructure is crucial in explaining why certain countries achieve higher levels of productivity, physical capital, and human capital Additionally, Aschauer (1989, cited in Isaksson 2007, p 29) highlights that infrastructure investment in the U.S yields significant economic returns for society He also notes that the decline in productivity in the U.S during the 1970s can be attributed to reduced public infrastructure investment.

TheoreticalinsightsfortherelationshipbetweenTFPandvariablesareveryne cessaryandinteresting.However,empiricalevidencesthatbasedontheoriesarem orestableandconvincing.Untilnow,studiesofdeterminantsofproductivityande f f i c i e n c y atcountrylevelarestillverylimited.Someresearch of theothersauthorsa r e listedbelow.

83countries with6timebl ocksfrom1 960-64, 1965-69, 1970-74, 1975-79, 1980-84,and 1985-89

Useregress ionanalysis with fixede ffecttoesti mateTFPfi rst.Afterth at,findoutd eterminants ofTFP

Exportshow sapositive andstatistica llysignific ant at1%le vel. Thecontribu tionofhuma ncapitalge nerallyhasp ositiveimpac tonTFP.

Trade Paneldata Poorhealth and openness Use hasnegative developing (ratioof regression and countrieswith exportplus analysisto significant

6timeblocks importto estimate effecton and

Usegrowthac countingmet hodtocalcul ateTFP.Afte rthat,findou tdetermina ntsofTFP

FDI haveap ositivei mpacto nTFPgr owth.

Opentotr adehasp ositivei mpacton TFP. rate Envelopment

Analysis (DE A)t o estimateTFPa n dfindsoutp ossible

Human Paneldata contribution capital Employ ofFDIis

Government growth positiveto share accounting TFPgrowth.

InitialTFPofco untries comparedwith exercisetocal culate

Population out absorptive relationship capability between hypothesis TFPG&FDI

In their study on the impacts of openness, trade orientation, and human capital on total factor productivity (TFP), Miller and Upadhyay (2000) analyze panel data from 83 countries spanning from 1960 to 1989 They employ econometric methods, specifically regression analysis, to estimate two TFP measures derived from the Cobb-Douglas production function, incorporating human capital as a variable in the aggregate production function The authors include six dummy variables to account for time periods and adjust their data for deviations from country-specific means However, they acknowledge the challenges of calculating TFP through regression analysis, particularly the potential endogeneity issues between output and capital, as well as output and human capital As noted by the authors, "the reader needs to keep these potential biases in mind when interpreting our findings" (Miller and Upadhyay, 2000, p 8) Furthermore, they investigate the main determinants of TFP based on their results with and without human capital included in the production function.

TF P Ofco ur se, theyp ar t i cu l ar l y interestedinopenness,tradeorientation, andhumancapitalvariables.Theyarguethatthemoreacountrytradewiththewo rld,themoreopennessofaneco n o my is,andthegreaterchancethiscountryca nadoptadvancedtechniqueof p r o d u c t i o n aswellasimportkeyinputsforproductio n.Theyfindthattheresultofacountry’so p e n n e s s hasp o s i t ivea n d s t a t i s t i c a l l y s i g n i f i c a n t o n T F P a t 1 % l e v e l Interestingly,t r a d e o r i e n t a t i o n h a s r o b u s t a n d n e g a t i v e s t a t i s t i c a l l y s i g n i f i c a n t o n T F P a t 5%l e v e l Whatd o e s i t mean w h e n t r a d e o r i e n t a t i o n h a s n e g a t i v e s i g n ?

Remembert h a t t r a d e o r i e n t a t i o n i s m e a s u r e d byt h e d e v i a t i o n o f domestic p r i c e f r o m purchasingpowerparity.Whenthedeviationsbetweenthedomesticcurre ncya n d purchasing p owe r pa r i t y increase,it meansth at home cur re nc y bec omesl e ss u n d e r v a l u e d C o u n t r i e s f o l l o w p o l i c i e s t h a t l o w e r i t s reale x c h a n g e r a t e b e l o w p u rc h a s in g p o w e r p a r i t y w il l h a v e h i g h e r T F

P A u t h o r s a l s o e x a m i n e t h e r o l e o f humancapitaltoTFPbydividingthedatainto22 lowincomecountries,38middle,a n d 2 3 i n c o m e c o u n t r i e s Theyf i n d t h a t h u m a n c a p i t a l a s s o c i a t e w i t h negativeim p act onTFPforhighincomecountri es,andhumancapitalhavepositiveimpacton T F P f o r middlei n c o m e c o u n t r i e s F o r l o w - i n c o m e c o u n t r i e s , t h e i m p a c t o f humancapitalonTFPwillchangefrom negativetopositivewhenthesecountriesh a v e higherdegreeofopenness.

Cole and Neumayer (2006) build on the work of Miller and Upadhyay (2000) by analyzing panel data from 52 countries between 1965 and 1995 to explore the impact of poor health on Total Factor Productivity (TFP) Their research highlights how poor health can hinder economic growth by reducing labor productivity They identify three key indicators of poor health: malnutrition, measured by the proportion of undernourished individuals; malaria, indicated by the area affected by the disease; and waterborne diseases, represented by the fraction of the population lacking access to clean water The authors also consider the potential endogeneity of these health indicators, suggesting that improvements in TFP could lead to reduced malnutrition rates To address endogeneity concerns, they utilize lagged variables for malnutrition, malaria, and waterborne diseases in their models and incorporate three instrumental variables related to the population and area of countries based on the Koppen climate classification.

GeigerClimateZoneB”,“density ofpo pu la ti on liveinruralandurban”, an d

“country’s e c o l o g y m a l a r i a ” f o r v a r i a b l e s m a l n u t r i t i o n , w a t e r b o r n e d i s e a s e s , a n d malaria,respectively.Thep a p e r p r e s e n t s e v i d e n t s t h a t malnutrition,malaria,a n d w a t e r borned i s e a s e s h a v e r o b u s t a n d n e g a t i v e s t a s t i s c a l l y s i g n i f i c a n t i m p a c t s o n T F P T h o u g h theirempiricalworka lsoshowevidentsabouttheimportantoftradetoTFPg r o wt h

In a study conducted by Khan (2006) on the determinants of Total Factor Productivity (TFP) in the Pakistani economy, time series data from 1960 to 2003 was utilized The author employed the growth accounting method to calculate TFP and included various factors such as Foreign Direct Investment (FDI), trade openness, and population These variables were classified into two groups for regression analysis The first group included inflation, budget deficit, education expenditure, trade openness, financial development, and population, revealing an unexpected negative and statistically significant relationship between trade and TFP In the second group, additional variables such as private credit, domestic investment, employment, government consumption, and FDI inflows were analyzed to further understand their impact on TFP.

The study finds that Foreign Direct Investment (FDI) has a positive and statistically significant effect on Total Factor Productivity (TFP) growth However, when considering all variables and running a third regression model, the results show that both trade and FDI are statistically insignificant The paper has several issues that warrant attention Firstly, the author uses time series data, which can introduce problems such as serial correlation and causal relationships between FDI and TFP that were not adequately addressed Secondly, the study is limited to only 43 observations, and the addition of 11 dependent variables may compromise the degrees of freedom necessary to produce reliable results.

Inh i s r e s e a r c h , J a j r i ( 2 0 0 7 ) e x a m i n e s t h e c o n t r i b u t i o n o f t r a d e , e d u c a t i o n l e v e l (measuredbyporportionofe m p l o y ee s w it h tertiary educ ation),andforeign o w n er sh ip onTFPgrowthonMalaysia.Theanalysisinhisp aperiscarriedoutintw o s t e p s F i r s t , h e u s e s D a t a E n v e l o p m e n t Analysis(

D E A ) a n d t h e M a l m q u i s t p r o d u c t i v i t y i n d e x t o estimateT F P G S e c o n d , h e f i g u r e o u t p o s s i b l e f a c t o r s t h a t determineTFPG.Theauthorfindsthathum ancapital,exporthavepositiveeffectso n TFPgrowth.

In their 2009 study, Woo and colleagues analyzed cross-sectional and panel data from 92 countries spanning from 1970 to 2000, revealing that Foreign Direct Investment (FDI) has a positive and statistically significant effect on Total Factor Productivity (TFP) However, their findings contradict the absorptive capacity hypothesis, which suggests that FDI can enhance a country's economic growth only after it reaches a certain level of human capital; they found no supporting evidence for this claim A notable limitation of their research is the potential endogeneity between FDI and TFP in the cross-sectional model, indicating a need for careful consideration in future studies.

Allo f t h e mentionedr e s e a r c h e s h a v e p r o v i d e d g oo dba ck gr ou nd f o r u s toc o n d u c t ourstudy.However,someresearchhassomelimitationsandtheyfa ilstopr o v i d e anaccuracyenoughtomeasuretheimpactofFDI,exportonTFPgrow th.A l t h o u g h somestudyattemptedtoestimatetherelationshipbetweenFDIandtechnol ogygrowth,t h e relationshipb e t w e e n FDIa n d t e c h n o l o g y growthisa m b i g u o u s F D I i n f l o w s c a n h e l p i n c r e a s e p r o d u c t i v i t y a s w e l l asT F P g r o w t h throughanincreaseinqualityofhumancapitalororganizationalk n o w - h o w , b u t countriestobeknowhighlyp r o d u c t i v e ismorelikelytoattractFDIinflows.Thereist hepossibilityofendogeneitybetweenFDIandTFPgrowth.

Tos u m u p , b o t h e n d o g e n o u s g r o w t h theorya n d empiricalw o r k s s t r o n g l y supporttheimportantroleofFDIandexportonTFPandefficiency.Accordingtot h e s e literature,FDIisconsideredasavehicletobringadvancedtechnology,tranferknowledge, b o o s t l e a r n i n g byd o i n g p r o c e s s o f recipientcountry.Equally,t h e c o n t r i b u t i o n o f e x p o r t t o T F P s h o u l d n o t b e n e g l e c t e d E x p o r t i n g e n h a n c e p ro d u cti v i ty t h r o u g h o u t e c o n o m i e s o f s c a l e , a n d e x p o r t h e l p i n c r e a s e e f f i c i e n c y throughlearningbydoing,learningbyexportingprocess.

Inthissection,I willspecifytheframeworkaswellasvariablesthatrelatetomym o d e l F o r mored e t a i l s o f v a r i a b l e s i n mymodel,I w i l l p r e s e n t i n m o d e l sp ecif i cation section.

Basedontheoreticalfoundationandpreviousstudiesaboutdeterminants ofT FP G, itisthe righttimetoturnourattentiontotheresearchmethodologywhichist h e centralofourem piricalanalysis.Thischapterisdividedinto3parts.Part1isaboutmethodsinprod uctivitymeasurement.Next,thesamplingmethodandc o m b i n a t i o n ofdatawill bepresented.Finally,Iwillspecifymodelsandexplainforthechoiceofvariables.

Generally,measuringTFPG iscurrentlyusedintwo followingmethods.Thef i r s t methodis thegrowthaccounting exercisewhich was initiatedbyRobert

The estimation of Total Factor Productivity (TFP) growth through regression methods can introduce significant issues, particularly the endogeneity of capital and labor inputs As highlighted by The World Bank (2000), it is crucial to consider this endogeneity when evaluating the importance of TFP growth In regression analysis, the correlation between the error term and inputs can skew results, as the logarithm of TFP is derived from the logarithm of output minus the logarithm of inputs, which are inherently linked More productive countries tend to attract both physical capital and labor, while those with advanced technology also experience higher investments in human capital Consequently, researchers employing econometric methods to estimate TFP growth must acknowledge potential biases that could affect the interpretation of their findings, as noted by Miller and Upadhyay.

(2000),p 8 ) H e n c e , i t i s n o d o u b t , B a i e r , D w y e r a n d T a m u r a ( 2 0 0 6 ) h a s e m p h a s i z e d thatemployinggrowthaccountingexercisetocalculateTFPgrowthisamores uitablemethodincomparisonwithregressionanalysis.Inthisresearch,wef o l l o w t h e w i s d o m a d v i c e o f B a i e r , D w y e r a n d Tamura( 2 0 0 6 ) byu s i n g g r o w t h accountingexercisetoestimateTFPgrowth.

Ino r d e r t o c a l c u l a t e f a c t o r s l i k e c a p i t a l , l a b o r , a n d t e c h n o l o g i c a l p r o g r e s s contributedtoeconomicgrowth,IusetheSolowgrowthmodel- thebasicm e t h o d o l o g y forgrowthaccountingexercise.Giventhenotionthatitisi mpossiblet omeasuretechnologicalprogressdirectly,thegrowthrateoftechn ologyismeasuredindirectlybycalculatingthedifferentbetweentheactualgro wthrateofo u t p u t (GDP)andthepartofgrowthrateofcapitalaswellasgrowthrateoflabor.

 (3.1) whereYitstandsfortotaloutput(GDP)ofcountryi(i=1,2,3…103)inyeart,Kitist h e c a p i t a l stockincountryi inyeart, and Litis the quantityoflaborin countryiin yeart.AiisthelevelofTFPinyeartforcountryi. iscapitalshareofoutputand βlabourshareofoutput.

Thekeyparttothism ethodologyistodetermine theparameters ofth ep ro d u c ti o n function,andβ.I f weassumethatproductionisconstantreturnsto scale,t h e n 1.

Followingt h e traditionintheneoclassicalliteraturegoing backtoSolow(1956),andβcanalsobemeasuredastheincomesharesofc a p i t a l andlabor.

Theincomes h a r e o f l a b o r ( β ) c a n b e c a l c u l a t e d a s t h e r a t i o betweent h e wageofemployeesandtheGrossDomesticProduct(GDP)foreachcountryinthe 1996-2009period.Thus,thecapitalshareintotaloutput()iscalculatedby=1 - β.

However,dataforincomeshareoflabouraswellasincomeshareofcapitalisove rwhelmingandhardtocollectforindividualcountries,almostofresearches( Bai er , D wy er an d T a mu r a (2006),Woo (2009))assumea constantincomeshareofl a b o r forallcountriesandyears.Inaddition,Gollin(2002)finds strongevidencetosupportthehypothesisofcommonincomeshareof laborforallcountriesandyears,a n d hefindsthattheincomeshareoflabourforcrossc ountryusuallyrangesfrom

1.6 to0.8.Theaveragenumberthatmostofresearchersusuallychooseequal0.65.F ur t her m o r e , Woo( 2 0 0 9 ) u s e s b o t h c o n s t a n t incomes h a r e o f l a b o r a n d a c t u a l incomes h a r e o f l a b o r d a t a fromB e r n a n k e a n d G u r k a y n a k ( 2 0 0 1 , c i t e d i n W o o 2 0 0 9, p.229)toestimateTFPgrowth.Again,hefindsverysimilarre sultsofTFPgrowthf r o m c o n s t a n t incomes h a r e a n d a c t u a l incomes h a r e

H e n c e , t h e u s e o f c o n s t a n t incomeshareoflaborisnotabigprobleminourpa per.WefollowWoo(2 00 9)byu s i n g c o n s t a n t incomes h a r e o f l a b o r e q u a l 0 6 5 f o r a l l c o u n t r i e s a n d years.Thus,incomeshareoflaborequal0.35.Tosomeext ent,westronglybelievethattheuseofconstantincomeshareoflaborequal0.65isa lsosuitablewithourdatasetsinceWoo(2009)’sdatasetincludebothdevelopedand developingcou nt ri esfrom1970to2000.An dthere isalsoempiricalevidencet osupportthe hypothesisofconstantincomeshareoflaborforallyears.

Thesecondarydataism a i n l y usedinthisstudy Thedatais theaggrega ted a t a o f 1 0 3 c o u n t r i e s i n t h e w o r l d ( i n c l u d i n g Vietnam)from1 9 9 6 t o 2 0 0

The selection of 103 countries from 1996 to 2009 for our sample is based on the availability of data, allowing for continuous estimation of Total Factor Productivity Growth (TFPG) during this period This number represents the largest dataset we have for analysis, as detailed in Table A1 of Appendix 1 The timeframe chosen is significant because it utilizes the most recent and high-quality data, providing an updated perspective on the effects of Foreign Direct Investment (FDI) and exports on TFPG Additionally, our sample encompasses the impacts of two major financial crises: the Asian Financial Crisis of 1997 and the Global Financial Crisis of 2008 We argue that if the results are significant during this period, they are likely to be even more pronounced in other timeframes.

Clearly,thereis nodataforTFPG for103countriesin theworld be t w e e n 1 9 96 and2009period.InordertostudyimpactsofFDIandexportonTFPG,w ehave t o e s t i m a t e TFPGbye m p l o y i n g g r o w t h a c c o u n t i n g e x e r c i s e a s mentioneda b o v e TocalculateTFPG,weneeddataonoutput(GDP),capitalstoc kinputandlaborinput.

• Inmypaper,IuserealGDPasanindicatorforoutputgrowth.RealGDPdat aof eachcountrycanbecollectedfromWorldDevelopmentIndicatorsofWorldB a n k

• Tom e a s u r e t h e l a b o r i n p u t , I c o l l e c t d a t a o n t o t a l e m p l o y m e n t f o r e a c h country.Da ta on t o t a l e m p l o y m e n t o f e a c h c o u n t r y canb e co ll ect ed f r o m Wor ld D e v e l o p m e n t IndicatorsofWorldBank.http://databank.worldbank.org.

Kt=(1–δ)K)Kt-1+It( 3 3 ) whereKtisthecapitalstockinyeart,Kt-1isthecapitalstockinyeart-1.

Tocomputethecapitalstock,weneeddataondepreciationrateandinitia lcapitalstocklevel(K 0 ).Inoursample,K0istheyear1996.Ifollowthemethodof

(3.4) whereK0s t an d sf o r i n i t i a l l e v e l o f c a p i t a l s t o c k , I0ist h e i n i t i a l v a l u e o f investment,gIisthegrowthrateininvestment.δ)Kistherateofdepreciationofgrossc a p i t a l

Capital stocks are assumed to be homogeneous, implying that all capital stock within a group of countries shares the same depreciation rate over time According to Bu (2004), the depreciation rate is set at 5% for developed countries and 7% for developing countries This disparity arises because developing countries typically experience higher depreciation rates due to less effective maintenance systems compared to their developed counterparts Additionally, data on total investment can be accessed through the World Development Indicators of the World Bank, with figures adjusted to 2000 constant USD.

Int h i s s e c t i o n , I onlymentiona b o u t t h e s o u r c e o f d a t a w h i c h I c o l l e c t e d from.Formoreinformationabouttheusageofdata,Iwillpresentinmodelspecificat ionsection.

• Exporti s m e a s u r e d byr a t i o o f e x p o r t toG D P ( % ) D a t a o f e x p o r t f o r 1 0 3 cou nt ri esisavailableathttp://databank.worldbank.org.

• FDIismeasuredbyratio ofnet FDI inflowsto GDP(%).Data of FDI inflows arec o l l e t e d f r o m t h e U N C T A D d a t a b a s e I t i s a v a i l a b l e a thttp:// www.unctad.org/Templates

• ThemainsourceofinflationdataisobtainedfromWorldDevelopmentIndicatorso f W orldBankh t t p : / / da t a b a n k w o r l d b a n k o r g.Inflationis proxied byannualp e r c e n t a g e ofcon sumerpriceindex(%).

• Humanc a p i t a l (HC)d a t a i s o b t a i n e d fromW o r l d D e v e l o p m e n t I n d i c a t o r s o f WorldB a n kh t t p : / / d a t a b a n k w o r l d b a n k o r ga n d B a r r o a n d L e e E d u c a t i o n d a t a s e t h t t p : / / w w w b a r r o l e e c o m / d a t a / d a t a e x p h t m.H u m a n c a p i t a l d a t a f r o m b o t h o f t h e s o u r c e is proxiedbyaveragesecondaryschoolingyearsofpopulationover15yearso l d (%).Incrosss ectionstudy,weemployhumancapitalfromWorldDevelopmentI n d i c a t o r s ofWorldBa nk.Inpaneldataexercise,weusethedatafromBarroandL e e e d u c a t i o n d a t a s e t T h e rationalef o r employingthedataf r o m BarroandLeee d u c a t i o n datasetinpanel dataisthatthedatasethasdataonafiveyearperiodbaseforeachcountry.Itissuitablewith mypaneldatabecausewealsousedataoffiveyearaverageforeach country,andwealsowanttocheckthe robustnessofFDI ande x p o r t whenweemploydifferentdatasourceforhumancapital.

• DataofpopulationiscollectedatPennWorldTable7.0.Itisavailableathttp:// pwt.econ.upenn.edu/

• Wealsoemploygovernmentexpenditureinourmodel.Governmentexpenditure i s measuredasratioofgovernmentconsumptiontoGDP(%).DataofGovernmentexpe nditureisc o l l e c t e d a t P e n n W o r l d T a b l e 7 0 I t i s a v a i l a b l e a thttp:// pwt.econ.upenn.edu/

• Dataoflandarea(km 2 )anddataofdistancefromlatitude(km 2 )thatwillbeusedf o r inst rumentalvariablesiscollectedfromCenterforInternationalDevelopment.Itisavailableat:ht tp://www.cid.harvard.edu/ciddata/geographydata.htm#general

2 0 0 9 f o r e a c h c o u n t r y u s i n g g r o w t h accountingmethod,anditwillcreatea crosssectiondatasetofTFPgrowthalongw it h v a r i a b l e s s u c h a s F D I , e x p o r t , h u m a n c a p i t a l , e t c f r o m 1996a n d i n 2 0 0 9 Secondly,asamorecomprehen sivemethodforrobustnesscheck,Ialsoreportthe robustresultsfromfixed- effectpanelregression.Next,themodelforcrosssectionr e g r e s s i o n willbepresente d.

Myr e s e a r c h i n t e n d s tou s e e c o n o m e t r i c m o d e l t o e s t i m a t e t h e e f f e c t o f exp or tandFDIontotalfactorproductivitygrowthbyfirstusingcros s-sectiondatao f country-levelfromtheperiod1996to2009.

TFPG i =α+X ji β+ε i (3.5) where‘TFPG i’ describestotalfactorproductivitygrowthofcountryi( i = 1 , 2 , 3 1 0 3 ) inperiod1996-

2009,‘Xj’mentionsthevectorofdeterminantsofTFPincountryi(i=1,2,3 103)in period1996-2009andεiisanerrorterm.

Thedeterminants(Xj)ofTFPGaregenerallyclassifiedintoFDIinflow s,exportsa n d a s e t o f c o n t r o l v a r i a b l e s T h e r e f o r e , Equation( 5 ) c a n b e w r i t t e n a s follows:

EmpiricalStudies

TheoreticalinsightsfortherelationshipbetweenTFPandvariablesareveryne cessaryandinteresting.However,empiricalevidencesthatbasedontheoriesarem orestableandconvincing.Untilnow,studiesofdeterminantsofproductivityande f f i c i e n c y atcountrylevelarestillverylimited.Someresearch of theothersauthorsa r e listedbelow.

83countries with6timebl ocksfrom1 960-64, 1965-69, 1970-74, 1975-79, 1980-84,and 1985-89

Useregress ionanalysis with fixede ffecttoesti mateTFPfi rst.Afterth at,findoutd eterminants ofTFP

Exportshow sapositive andstatistica llysignific ant at1%le vel. Thecontribu tionofhuma ncapitalge nerallyhasp ositiveimpac tonTFP.

Trade Paneldata Poorhealth and openness Use hasnegative developing (ratioof regression and countrieswith exportplus analysisto significant

6timeblocks importto estimate effecton and

Usegrowthac countingmet hodtocalcul ateTFP.Afte rthat,findou tdetermina ntsofTFP

FDI haveap ositivei mpacto nTFPgr owth.

Opentotr adehasp ositivei mpacton TFP. rate Envelopment

Analysis (DE A)t o estimateTFPa n dfindsoutp ossible

Human Paneldata contribution capital Employ ofFDIis

Government growth positiveto share accounting TFPgrowth.

InitialTFPofco untries comparedwith exercisetocal culate

Population out absorptive relationship capability between hypothesis TFPG&FDI

In their study on the impacts of openness, trade orientation, and human capital on Total Factor Productivity (TFP), Miller and Upadhyay (2000) analyze panel data from 83 countries spanning from 1960 to 1989 Utilizing econometric methods, they estimate two TFP measures based on the Cobb-Douglas production function, incorporating human capital as a factor of input To address potential biases in Ordinary Least Squares (OLS) estimations, the authors include six dummy variables for different time periods and adjust their data for country-specific deviations over time However, they acknowledge the challenges of calculating TFP through regression analysis, particularly the endogeneity issues between output, capital, and human capital The authors caution readers to consider these potential biases when interpreting their findings Based on their TFP estimations, they further investigate the primary determinants of productivity.

TF P Ofco ur se, theyp ar t i cu l ar l y interestedinopenness,tradeorientation, andhumancapitalvariables.Theyarguethatthemoreacountrytradewiththewo rld,themoreopennessofaneco n o my is,andthegreaterchancethiscountryca nadoptadvancedtechniqueof p r o d u c t i o n aswellasimportkeyinputsforproductio n.Theyfindthattheresultofacountry’so p e n n e s s hasp o s i t ivea n d s t a t i s t i c a l l y s i g n i f i c a n t o n T F P a t 1 % l e v e l Interestingly,t r a d e o r i e n t a t i o n h a s r o b u s t a n d n e g a t i v e s t a t i s t i c a l l y s i g n i f i c a n t o n T F P a t 5%l e v e l Whatd o e s i t mean w h e n t r a d e o r i e n t a t i o n h a s n e g a t i v e s i g n ?

Remembert h a t t r a d e o r i e n t a t i o n i s m e a s u r e d byt h e d e v i a t i o n o f domestic p r i c e f r o m purchasingpowerparity.Whenthedeviationsbetweenthedomesticcurre ncya n d purchasing p owe r pa r i t y increase,it meansth at home cur re nc y bec omesl e ss u n d e r v a l u e d C o u n t r i e s f o l l o w p o l i c i e s t h a t l o w e r i t s reale x c h a n g e r a t e b e l o w p u rc h a s in g p o w e r p a r i t y w il l h a v e h i g h e r T F

P A u t h o r s a l s o e x a m i n e t h e r o l e o f humancapitaltoTFPbydividingthedatainto22 lowincomecountries,38middle,a n d 2 3 i n c o m e c o u n t r i e s Theyf i n d t h a t h u m a n c a p i t a l a s s o c i a t e w i t h negativeim p act onTFPforhighincomecountri es,andhumancapitalhavepositiveimpacton T F P f o r middlei n c o m e c o u n t r i e s F o r l o w - i n c o m e c o u n t r i e s , t h e i m p a c t o f humancapitalonTFPwillchangefrom negativetopositivewhenthesecountriesh a v e higherdegreeofopenness.

Cole and Neumayer (2006) build on the work of Miller and Upadhyay (2000) by analyzing panel data from 52 countries between 1965 and 1995 to explore the impact of poor health on Total Factor Productivity (TFP) Their research highlights how poor health can hinder a country's economic growth through reduced labor productivity They identify three key indicators of poor health: malnutrition, measured by the proportion of undernourished individuals; malaria, indicated by the area affected by the disease; and waterborne diseases, assessed by the fraction of the population lacking access to clean water The authors also discuss the potential endogeneity of these health indicators, suggesting that improvements in TFP can lead to reductions in malnutrition To address endogeneity concerns, they utilize lagged variables for malnutrition, malaria, and waterborne diseases in separate models and incorporate three instrumental variables related to the population and area of countries as defined by the Koppen climate classification.

GeigerClimateZoneB”,“density ofpo pu la ti on liveinruralandurban”, an d

“country’s e c o l o g y m a l a r i a ” f o r v a r i a b l e s m a l n u t r i t i o n , w a t e r b o r n e d i s e a s e s , a n d malaria,respectively.Thep a p e r p r e s e n t s e v i d e n t s t h a t malnutrition,malaria,a n d w a t e r borned i s e a s e s h a v e r o b u s t a n d n e g a t i v e s t a s t i s c a l l y s i g n i f i c a n t i m p a c t s o n T F P T h o u g h theirempiricalworka lsoshowevidentsabouttheimportantoftradetoTFPg r o wt h

In his 2006 study, Khan examines the determinants of Total Factor Productivity (TFP) in the Pakistani economy using time series data from 1960 to 2003 He employs the growth accounting method to calculate TFP and investigates factors influencing it, including Foreign Direct Investment (FDI), trade openness (measured by the ratio of imports plus exports to total GDP), and population Khan categorizes these variables into two groups and conducts regression analysis In the first group, which includes inflation, budget deficit, education expenditure, trade openness, financial development, and population, he finds an unexpected negative and statistically significant relationship between trade and TFP In the second group, he incorporates additional variables such as private credit, domestic investment, employment, government consumption, and FDI inflows.

The study finds that Foreign Direct Investment (FDI) has a positive and statistically significant effect on Total Factor Productivity (TFP) growth However, when accounting for all variables in a third regression model, the results suggest that both trade and FDI are statistically insignificant The paper faces several issues that require attention, including the use of time series data that may introduce problems such as serial correlation and unclear causal relationships between FDI and TFP Additionally, with only 43 observations in the study, the introduction of 11 dependent variables compromises degrees of freedom, potentially undermining the reliability of the results.

Inh i s r e s e a r c h , J a j r i ( 2 0 0 7 ) e x a m i n e s t h e c o n t r i b u t i o n o f t r a d e , e d u c a t i o n l e v e l (measuredbyporportionofe m p l o y ee s w it h tertiary educ ation),andforeign o w n er sh ip onTFPgrowthonMalaysia.Theanalysisinhisp aperiscarriedoutintw o s t e p s F i r s t , h e u s e s D a t a E n v e l o p m e n t Analysis(

D E A ) a n d t h e M a l m q u i s t p r o d u c t i v i t y i n d e x t o estimateT F P G S e c o n d , h e f i g u r e o u t p o s s i b l e f a c t o r s t h a t determineTFPG.Theauthorfindsthathum ancapital,exporthavepositiveeffectso n TFPgrowth.

In their 2009 study, Woo analyzes the impact of Foreign Direct Investment (FDI) on Total Factor Productivity (TFP) using both cross-section and panel data from 92 countries between 1970 and 2000 The findings indicate that FDI has a positive and statistically significant effect on TFP However, this contradicts the absorptive capacity hypothesis, which posits that FDI can enhance a country's economic growth only when it has achieved a certain level of human capital; the study does not provide evidence to support this hypothesis Additionally, a potential issue in the research is the possibility of endogeneity between FDI and TFP in the cross-section model, highlighting the need for careful consideration in future studies.

Allo f t h e mentionedr e s e a r c h e s h a v e p r o v i d e d g oo dba ck gr ou nd f o r u s toc o n d u c t ourstudy.However,someresearchhassomelimitationsandtheyfa ilstopr o v i d e anaccuracyenoughtomeasuretheimpactofFDI,exportonTFPgrow th.A l t h o u g h somestudyattemptedtoestimatetherelationshipbetweenFDIandtechnol ogygrowth,t h e relationshipb e t w e e n FDIa n d t e c h n o l o g y growthisa m b i g u o u s F D I i n f l o w s c a n h e l p i n c r e a s e p r o d u c t i v i t y a s w e l l asT F P g r o w t h throughanincreaseinqualityofhumancapitalororganizationalk n o w - h o w , b u t countriestobeknowhighlyp r o d u c t i v e ismorelikelytoattractFDIinflows.Thereist hepossibilityofendogeneitybetweenFDIandTFPgrowth.

Tos u m u p , b o t h e n d o g e n o u s g r o w t h theorya n d empiricalw o r k s s t r o n g l y supporttheimportantroleofFDIandexportonTFPandefficiency.Accordingtot h e s e literature,FDIisconsideredasavehicletobringadvancedtechnology,tranferknowledge, b o o s t l e a r n i n g byd o i n g p r o c e s s o f recipientcountry.Equally,t h e c o n t r i b u t i o n o f e x p o r t t o T F P s h o u l d n o t b e n e g l e c t e d E x p o r t i n g e n h a n c e p ro d u cti v i ty t h r o u g h o u t e c o n o m i e s o f s c a l e , a n d e x p o r t h e l p i n c r e a s e e f f i c i e n c y throughlearningbydoing,learningbyexportingprocess.

ConceptualFramework

Inthissection,I willspecifytheframeworkaswellasvariablesthatrelatetomym o d e l F o r mored e t a i l s o f v a r i a b l e s i n mymodel,I w i l l p r e s e n t i n m o d e l sp ecif i cation section.

Basedontheoreticalfoundationandpreviousstudiesaboutdeterminants ofT FP G, itisthe righttimetoturnourattentiontotheresearchmethodologywhichist h e centralofourem piricalanalysis.Thischapterisdividedinto3parts.Part1isaboutmethodsinprod uctivitymeasurement.Next,thesamplingmethodandc o m b i n a t i o n ofdatawill bepresented.Finally,Iwillspecifymodelsandexplainforthechoiceofvariables.

Generally,measuringTFPG iscurrentlyusedintwo followingmethods.Thef i r s t methodis thegrowthaccounting exercisewhich was initiatedbyRobert

The estimation of Total Factor Productivity (TFP) growth through regression methods can lead to significant issues, particularly due to the endogeneity of capital and labor inputs As highlighted by the World Bank (2000), "The endogeneity of factor inputs should be considered when assessing the importance of TFP growth." This is primarily because the regression analysis reveals a correlation between the error term and the inputs, suggesting a causal relationship For example, the logarithm of TFP is derived from the logarithm of output minus the logarithm of inputs, yet the output is inherently linked to the level of inputs More productive countries tend to attract both physical capital and human capital, while those with advanced technology generally see higher investments in both labor and physical capital Authors utilizing econometric methods to estimate TFP growth must acknowledge that "the reader needs to keep these potential biases in mind when interpreting our findings" (Miller and Upadhyay).