Researchproblem
Over the past few decades, researchers have sought to identify the key determinants of economic growth, exploring why some nations experience rapid long-term income growth while others do not A primary challenge in this study is the lack of consensus on the main drivers of growth, as numerous factors influence economic development Two prominent growth theories—the neoclassical growth theory by Solow, emphasizing the importance of investment activities, and the endogenous growth theory by Romer and Lucas, which focuses on labor and innovation capacity—have spurred various extensions and discussions regarding sources of growth While some researchers highlight factors like labor, capital, technological progress, government spending, and trade openness, others emphasize the significance of institutions, democracy, rule of law, geography, and corruption.
Insearching fortheimportant gr ow th determinants, a lotofeco no mis ts foc uso n corruption,fo r example, L e f t (1964), B e c k e r ( 1 9 6 8 ) , L u i (1985), M a n i o n (1996), Kaufmanna n d Wei( 1 9 9 9 ) , H a q u e a n d K n e l l e r ( 2 0 0 9 ) , M o h a m e d D r i b i ( 2 0 1 3 ) , D i ab y andSylwester(2014),Pak
Hung Mo (2014) highlights the ongoing debate regarding the impact of corruption on economic growth, noting that some studies suggest a positive correlation between corruption and economic development when corruption levels are appropriate In countries with complex administrative procedures, corruption can expedite economic operations, such as obtaining licenses or building infrastructure, thus saving time for businesses (Lui, 1985) The "efficient grease" hypothesis posits that corruption can enhance economic efficiency, allowing firms that engage in bribery to access capital more easily and at lower costs Additionally, Manion (1996) points out that to avoid delays, applicants often make corrupt payments to officials for licenses, which increases bureaucrats' income and stimulates economic growth through increased spending on goods and services However, developing countries struggle to combat corruption without achieving a certain level of economic development, as efforts to reduce corruption require significant investment of time, labor, and resources.
However,a n u m e r o u s e v i d e n c e s o n s i g n i f i c a n t n e g a t i v e c o r e l l a t i o n b e t w e e n corruptiona n d e c o n o m i c g r o w t h a r e s h o w e d i n m a n y e m p i r i c a l r e s e a r c h e s a f t e r managingthevitaldeterminantsofeconomiclikegovernmentex penditure,humanc a p i t a l , t r a d e o p e n n e s s , i n v e s t m e n t , p o l i t i c a l i n s t a b i l i t y , i n c l u d i n g M a u r o ( 1 9 9 5 ) , Mauro(1996),Pak Hung Mo (2001),Pellegrini andGerlagh(2004),Lorentzen,McMilanandWacziarg(2008),Pellegrini(2011), MarieChene(2014).Forinstance,t h e causualassociationbetweencorruptionand growthhasbeeninvestigatedinthes t u d y ofMohamedDridi(2013)byemployingth eChannelMethodology(methodw h i c h wasdevelopedbyTavaresandWacziar gin2011).Basedoncross- countryd a t a including82developedanddevelopingcountries foraperiodo f1980-
2002,t h e authorfoundthatcorruptionaffectstheeconomicgrowthnegatively.Thee m p i r i c a l r e s u l t i n d i c a t e d thato n e p o i n t i n c r e a s e d i n t h e c o r r u p t i o n i n d e x w i l l g e n e r a t e 0 9 p e r c e n t d e c r e a s e d i n t h e a n n u a l g r o w t h r a t e v i a h u m a n r e s o u r c e s , governmentspending,investment,inflation, politicalcondition,andopenness.Thep a p e r f u t h e r c o n c l u d e d t h a t humanr e s o u r c e s a n d p o l i t i c a l s i t u a t i o n a r e t h e m o s t c r u c i a l transmissionchannelthro ughwhichcorruptiontransmitsits negativeimpacto n economicgrowth.Unlike MohamedDridi,Mo(2001) usedth edecomposition methodandfoundthatthepoliticalinstabilityaccountsfor53 percentofthetotalcorruptione f f e c t o n g r o w t h F u r t h e r m o r e , u s i n g c r o s s - c o u t r y r e g r e s s i o n , M a u r o ( 1 9 9 6 ) showedthestrongnegativeeffectsof corruptionongrowthin94countriesw i t h o bse rva ti on s p e r i o d f r o m 1 9 6 0 t o 1
Corruption significantly diminishes investment, particularly in the private sector, and adversely affects government spending on education, which is essential for growth (Mauro, 1996) Utilizing data from the Global Competitiveness Report Surveys of 1996 and 1997 and based on Stackelberg game theory, Kaufmann and Wei (1999) examined the link between bribery and bureaucratic inefficiency Their findings indicated a lack of support for the "speed money" hypothesis, ultimately refuting the notion that corruption can act as "efficient grease," thereby demonstrating that corruption hinders economic growth.
Besides,thecorrelationbetweencorruptionandeconomicgrowthisstilluncertain i n somefindingsfrompreviouspapers(AndvigandMoene,1990;EhrlichandLui,1 9 9
A study by Haque and Kneller (2009) utilizing the Threshold model on data from 54 developed and developing countries between 1980 and 2003 highlights significant insights regarding the interplay between corruption and economic growth Firstly, it reveals a strong negative correlation between corruption and economic growth Secondly, the study emphasizes that corruption is not static; its impact is influenced by the prevailing culture of corruption, where cultural shifts can undermine established thresholds Lastly, since most resources are state-owned, the government’s focus on corruption can hinder development progress Additionally, research by Ehrlich and Lui (1999) further supports the notion of a non-linear relationship between corruption and economic growth.
Therefore,incontributingtothediscussion,thisthesisaimsatprovidingagenerall o o k a t t h e c o r r u p t i o n a n d e c o n o m i c g r o w t h t h r o u g h r e v i s i t i n g t h e most p o p u l a r theoreticalandempiricalstudies.Thisstudyalsore- examinestheimpactsofcorruptiononeconomicgrowthinAsian countriesbyapplyingvariouseconometrictechniques.Anewdatasetiscollectedandanalyz edbyformulatingsomeeconomicgr owth equationswith possibletransmitionvariables of corruption.Theresultsw i l l supportfurtherevidencesonthecasualrelationshipbetweencorr uptionandgrowth.
Researchobjectivesandresearchquestions
Researchobjectives
Thisp a p e r m a i n l y f o c u s e s o n t h e c o r e o b j e c t i v e i s r e - e x a m i n i n g t h e e f f e c t s o f corruptiono n e c o n o m i c g r o w t h inA s i a n c o u n t r i e s f o r t h e p e r i o d f r o m 1 9 9 6 t o 2014.T h i s t h e s i s t r i e s t o u n d e r s t a n d , identify,a n d e x p l a i n h o w c o r r u p t i o n w i l l a f f e c t economicg r o w t h d i r e c t l y a n d i n d i r e c t l y v i a t r a n s m i t i o n c h a n n e l s i n t h e sample.
Researchquestions
Asabovementioned,thisthesistriestoaddresstherelationshipbetweencorruptiona n d e conomicgrowth.Therefore,thequestionsshouldberaisedasfollows:
- Howarecorruptioneffectsoneconomicgrowthviafivepossibletransmissi onchannels:i n v e s t m e n t , humanc a p i t a l , p o l i t i c a l i n s t a b i l i t y , go vernmentexpenditure,andopennesstotrade.
ThesisStructure
Chapter1 : I n t r o d u c t i o n p r e s e n t sn u m e r o u s c o n c l u s i o n s a b o u t thec o r r e l a t i o n betweenc o r r u p t i o n a n d economicg r o w t h f r o m v a r i o u s t h e o r e t i c a l a n d empiricalresearches.Besides, itexplains whatvital o bjectivesare, whatresearchquestions shouldberaisedtoanswerinthispaper.
Chapter2 : L i t e r a t u r e r e v i e w p r o v i d e sa g e n e r a l r e v i e w o f econom ictheoriesa s s o c i a t e d tothecausalcorrelationbetweencorruptionandeconomicgr owth.Thisp a rt d e s c r i b e s t h e o r e t i c a l f r a m e w o r k a n d e m p i r i c a l s t u d i e s consistentw i t h t h i s issue.Inaddition,thedefinitionsofthevariablesu sedinthemodelarementionedinthischapter.
Chapter3:M e t h o d o l o g y i sc o n c e r n e d a b o u t t h e g e n e r a l m e t h o d s a n d h o w t o checke f f e c t s ofcorruptiono n e c o n o m i c g r o w t h d i r e c t l y a n d i n d i r e c t l y , w h i c h m a i n l y involvesinthefollowingpoints:
- datasources andsampletobeus e d t oe s t i ma t e theexistence th e c o r r u p t i o n – economicdevelopmentrelationship
Chapter5 : C o n c l u s i o n s , L i m i t a t i o n a n d F u t u r e r e s e a r c h c o m e s t o t h e mainf i n d i n g s a c h i e v e d i n t h e p r e v i o u s c h a p t e r Accordingly,t h i s p a r t pointso u t t h e limitationsandfurtherstudiesconcerningtherelationshipbe tweencorruptionandeconomicgrowth
Theoreticalconceptsrelatedto economicgrowthandcorruption
Economicgrowthisanexpansioninproductivecapacityo f commoditiesandservices,a ndaveragenationalincomelevelinaperiodoftime,comparedwithana n o t h e r peri od(Perkinset.al.,2006,p.12)
Inc o m p a r i s o n o f economicg r o w t h f r o m t w o c o u n t r i e s , G r o s s D o m e s t i c P r o d u c t ( G D P ) o r GrossNationalProduct(GNP)areincommonuse.GDPandGNPcanbec a c u l a t e d i nnominaldenomination,whichincludesinflation,orinreald en o m i n a t i o n , w hichisadjustedinflation.
Despitetheabsenceofadominanttheory,almostalleconomicgrowthresearches a r g u e thatdifferencesinlevelofincomeacrossthecountriesaroundtheworldare du etodifferences infactorendowment,factorproductivity,technology, the c o m b i n a t i o n ofanytwofactors,oralltheabove.
Inthefirstgrowththeory,andperhapsthemostpopulartheory,Solow(1956)foundt h a t capit alhaslesscontributiontoeconomicgrowththanexpected,leavingalargeresidualunex plained,evenaftertakingaccountforeffectivelabor.
Following Solow's research, growth theory diverged into two main directions One direction raised concerns about the accuracy of the aggregate production function used by Solow Notably, Lewis (1954) introduced a dual-sector model, explaining economic growth through the transition of the labor force from traditional agriculture to modern industry In contrast, many economists sought to understand why the effects of exogenous technical change, known as the Solow residual, were significantly larger in reality than theoretical predictions They emphasized the interactions between political and economic factors, with key contributions from Lucas (1988), Romer (1989), and Mankiw, Romer, and Weil (1992) These efforts aimed to adjust labor for quality, leading to various endogenous growth theories that incorporated additional variables into Solow's neoclassical production function, such as human capital and R&D By integrating human capital, the cross-sectional study by Mankiw, Romer, and Weil (1992) explained approximately eighty percent of the variation in growth rates.
Althoughendogenousgrowththeoryhaspointedsomevitualelementsof theSolowr es i d u a l , RobertJ.Barro(1991),Barroandhiscolleague(1995)hasidentifiedso mea n o t h e r f a c t o r s a n d u s e d as abenchmarkfor subsequent empirical works.In details,theseeconomistscheckedthesignificanceofhumanresouces,governmentpolicie s,q u a l i t y ofinstitution,tradeopenness,freedom,developmentaid,reformsoffinance.C o n c e p t ofcorruption
Intermofdefinition,corruptionisacomplexphenomenon.Generally,corruptionist h e m isuseofentrustedauthorityforextrapositivepersonalbenefit(TransparencyInt ernationalwebsite).
Int e r m o f t y p o l o gy,c o r r u p t i o n d i v i d e d i n t o t h r e e c a t e g o r i e s a s g r a n d c o r r u p t i o n , bureaucraticcorruptionandpolitical corruption determinedbyth esectorwhereithappensandhowmuchmoneypaidoff.
Grandc o r r u p t i o n ( n e a r l y t h e samem e a n i n g a s p o l i t i c a l c o r r u p t i o n ) comprisesa b o u t a c t i v i t i e s i n v o l v i n g h i g h l e v e l o f p u b l i c a r e a t h a t f a l s i f y governmentpoliciesorthecentraloperatingofthenation.Thiskindofcorruptio niscentralized andcanaffectallcitizensinthecountry.
Bureaucraticcorruption(orpettycorruption)referstothesmallamountofm o n e y w h i c h o r d i n a r y c i t i z e n s payf o r p u b l i c b u r e a u c r a t s t o a c c e s s b a s i c co m m o d i t i e s orsevicesinplaceslikepublichospitals,schools,policedepartments,l icensingauthorities,taxingauthorities,andotheragencies.Thistypeofcorruptionh a s alsobeencalled“low-level”or“street-level”corruption.Itisdecentralizedthat thee x a c t b r i b e s t a k e n a r e n o t a r r a n g e d I t j u s t makesb u r e a u c r a t s s p e e d u p t h e procedureorskiplegalpenalties.
Politicalc o r r u p t i o n isd e f i n e d a s t h e s i t u a t i o n i n w h i c h p o l i t i c a l d e c i s i o n makersabuse theirposition toinfluencepolicies,organizations andprocesses in theallocationo f p u b l i c r e s o u r c e s a n d i n v e s t m e n t i n o r d e r t o s t r e n g t h e n t h e i r jurisdiction,positiona n d wealth.T h i s typeo f c o r r u p t i o n isa l s o c o n s i d e r e d ash av in g impactontheresultofelectionvotedbylegislators.
Intermofmeasurement,themostpopularcorruptionmeasuresusedinmoste m p i r i c a l r e s e a r c h e s aretheCorruptionPerceptionIndex(CPI),BribePayersIndex(BPI),G l o b a l C o r r u p t i o n B a r o m e t e r ( G C B ) , a n d N a t i o n a l I n t e r g r i t y S y s t e m a s s e s s m e n t s (NIS)recoredbyTransparencyInternationalinstitution;theControlofCorr uptionIndex(CC)caculatedbytheWorldwideGovernanceIndicatorgroup;theCorruptionI ndex(CI)producedbythe International countryriskguide.CPI willbea l s o employedinthisstudy.Thisindicatorhasalimitationinscope.Itjustindicatedp e r c e p t i o n s oftheextentofpublicsectionscorruption,suchasadministrativecategory,po liticalcategory.
Effectofcorruptiononeconomicgrowth:theoreticalliteratures
Owningtorent- seeking,queuemodel,andtransactioncosttheory,corruptionhasane f f e c t o n o u t p u t t h r o u g h c a p i t a l , l a b o r , a n d o t h e r e c o n o m i c f a c t o r s I t r e d u c e s p r o d u c t i v e w o r k s o d e c l i n e s a c t u a l w e a l t h creation,l o s t s g o v e r n m e n t r e v e n u e , lowersincomeequalityt hroughinefficientallocationofresourcesincludescapitala n d labor.
“RentSeeking”isoneofthemostimportantconceptinvolvesincorruption.GordonTullock o r i g i n a t e d t h i s c o n c e p t i n 1 9 6 7 , a n d i t w a s i n t r o d u c e d i n 1 9 7 4 byA n ne K rueger.KlostadandSoreide(2009)statedthatindividualsandgroupsaresaidtos eek r e n t s w h e n theyt r y t o g e t e x t r a profitsf o r themselvest h r o u g h t h e p o l i t i c a l a r en a insteadofallocationtheirtimeandskillsattherightway.
( 2 0 1 3 ) s u p p o r t e d t h a t r e n t s e e k i n g a c t i v i t i e s a s bribery,lobbying,a n d o t h e r p o l i t i c a l a c t i v i t i e s a i m i n g t o c o l l e c t t h e b e n e f i t s f r o m international tradingandgettheprofitsduringtheprocess.Becauseofrentseekingcu l tu r e (tariffon agood,restrictionsonimport,quotaonimport),themisallocationo f reso urces makesadeadweightlossinwhichno- onecanobtainsurplusandsocialben efit s d e c r e a s e H i g h e r p r i c e l e a d s t o l o w e r o u t p u t I t meanse c o n o m i c g r o w t h r e d u c e s
Queueing theory, developed by Agner Krarup Erlang in 1909, predicts queue lengths and waiting times for goods and services, making it applicable to various sectors, including businesses, shops, offices, and hospitals Liu (1985) expanded on this theory to illustrate how bureaucrats may expedite the issuance of business licenses and provide preferential treatment to those who can influence administrators, often through bribery This suggests a correlation between corruption and economic growth, as businesses may receive quicker approvals in exchange for illicit favors.
Lambsdorff(2002)metionedthattransactioncostoflegalcontractincludeseekingp ar t n er s a n d i n f o r m a t i o n c o s t s , b a r g a i n i n g a n d d e t e r m i n i n g a p p r o p r i a t e c o n t r a c t co n d it io n c o s t s , p o l i c i n g a n d e n f o r c e m e n t ofc o n t r a c t t e r m c o s t s T h e s e c o s t s o f corruptionagreementsneedstobeconcealed.S o,mostcorruptcontractsared i s c u s s ed throughbroker.
Lambsdorff(2002)alsomentionedthatifparochialcorruptionexistsinamarkettotradeg oodsandservices,thetotaltransaction costwillrisebecause thereneedtobemoree x p e n s e s t o f i n d p o t e n t i a l c o n t r a c t o r s T h e a c c e l e r a t i n g c o s t s comef r o m searchingpotentialpartners,q u a l i t y appraisal, p r o d u c t a n d i n d i v i d u a l a b i l i t y evaluationa s w e l l a s e a g e r n e s s t o a b i d e
LEKIMDUNG Page10 byc o r r u p t e d p r o d u c t s T h e s e a r c h f o r p a r t n e r s willstop w h e n thecos tsreaching marginaltransaction c o s t ofs ea r c h i n g
LEKIMDUNG Page11 onea d d i t i o n a l p a r t n e r , w h i c h i s e q u a l t o theestimatedp r o f i t g e n e r a t e d f r o m a p o t e n t i a l l y superiordealingwithanothercompetitor.
Thism e a n s t h a t t h e h i g h e r t h e m a r g i n a l t r a n s a t i o n c o s t is,t h e f e w e r p o t e n t i a l collaboratortobesought.Asaresult,entrepreneurcansavetheca pitalandinvesti n anotherproject.Whentheprojectcontinues,thiswillallowtohiremor eworkersf or systemoperationsandenhancetheproductivityofgoodsandservices.Ite nhanceseconomicgrowthaswell.
Effectofcorruptionon economicgrowth:empiricalstudies
Thesingleequationapproach
Corruption is a pervasive issue affecting nations worldwide, irrespective of their economic status or political systems Economists have long sought to understand the relationship between corruption and economic growth, yet no consensus has been reached Some researchers argue that a certain level of corruption can positively influence a country's development For instance, Leff's "grease the wheel" hypothesis (1964) suggests that corruption may stimulate economic growth by alleviating government-imposed constraints and facilitating favorable economic decisions Similarly, Lien's competitive bribery game (1986) and Lui's equilibrium queuing model (1985) indicate that corruption could potentially enhance economic growth.
Incontrast,theconcernaboutthebadimpactsofcorruptiononeconomicgrowth hasincreasedr a p i d l y i n b o t h d e v e l o p i n g a n d d e v e l o p e d c o u n t r i e s V a r i o u s emp ir ical s t u d i e s h a v e s h o w n upo n t h i s i s s u e , i n c l u d i n g M a
P e t a l ( 2 0 0 8 ) T h e s e s t u d i e s suggestedthatprivatefirmswhowingovernment’scontractsbyhighpayingarenotn e c e s s a r i l y e c o n o m i c a l l y c o m p e t i t i v e firmandsuchun- optimaluseofhumanr e s o u r c e w i l l d e s t r o y economicg r o w t h M o r e o v e r , p r i v a t e c o m p a n i e s w e r e o f t e n f o r c e d tomakeside- paymentstocorruptedgovernmentofficialsandthatcostwasof ten hugeforsma ll- scaledbutemergingfirms,whichcanbethedrivingforceforg r o w t h oftheeconomy.
Br e m p o n g (2002)modifiedthegrowthequation in alinearforminclude corr uptionasanindependentvariable: g=α o+ α 1 k+α 2 edu+α 3 x+α 4 corrupt+α 5 y 0+α6 govcon+ε i where:g:rateofeconomicgrowthofrealincome(dependentvariable)ε i: stocha sticerrorterm αi:coefficientstobeestimated k(investmentrate),edu(educationalettainmentoftheadultpopulation) ,x( g r o w t h rateofrealexport),corrupt(corruption),govcon(governm entconsumption), y o(initial levelofincome)areexplanatoryvariables
1988datasetsource)andBusinessInternational’s1984corruptionindex,M a u r o ( 1995)appliedasimpleregressionwithinstrumentalvariables(ethno- linguisticfractionalization)anda l s o s h o w e d t h a t t h e s t a n d a r d d e v i a t i o n o f corruptionindexhasnegativecorrelationwiththeannualgrowthrateofGDPperc a p i t a s i g n i f i c a n t l y B u t w i t h o u t c o n t r o l v a r i a b l e s , t h i s r e s u l t i s n o t r o b u s t A f t e r controllingforothervariables,includingsecondaryeducationin1960,go vernmentexpenditure,a s s a s s i n a t i o n s , i n v e s t m e n t , p o l i t i c a l instab ilityi n d e x , t h e e f f e c t o f corruptionongrowthbecomesinsignificant.
Nwankwo( 2 0 1 4 ) a l s o employedJ o h a n s e n co-integrationtest,g r a n g e r - c a u s a l i t y test,Unitroottest,ErrorcorrectionmechanismandOLSmethodtochec konlythesimpleeconometricmodelbelow:
Linearfunction:GDP=b0+b1*COR+Ut andLogfunction:Log(GDP)=b0+b1log(COR)+Ut
2010,Nwankwo(2014)foundthatthereisalong- runr e l a t i o n s h i p b e t w e e n c o r r u p t i o n l e v e l a n d e c o n o m i c d e v e l o p m e n t T h e a u t h o ralsoconcluded thatcorruptioninfluencesNigeria’sgrowthnegatively(b1= -4 6 8 0 )
Inc o n c l u s i o n,t h e r e a r e n o t m a n y r e s e a r c h e s f i n d i n g o u t t h e d i r e c t impacto f c o r r u p t i o n o n e c o n o m i c g r o w t h i s s i g n i f i c a n t T h e r e a s o n i s t h a t c o r r u p t i o n a s l o throughm a n y possible tr ans mi ssi onc ha nne ls suc hasi nv est men t, education, internationaltrade,politicalconditions,govern mentexpenditure, transmitsitsi m p a c t ongrowth.Sothesystemofequationappr oachusedtocalculatetheoveralleffectofcorruptionondevelopment
Thesystemofequationsapproach
Applyingthesystemofequationsapproachto checkthedirectandindirecteffectofcorruptiononthe economy,a numerous papers stated that corruption has a negativeimpactoneconomicgrowthsuchasPakHungMo(2001),Pellegriniand Gerlagh(2 00 4) ,Lorentzen,McMilanandWacziarg(2008),Pellegrini(2011),Marie Chene(2014),C a m p o s e t a l , (1999),MohamedDribi( 2 0 1 3 ) The typical systemo f equationsisspecifiedasbelow:
Directeffect:GDP=f(CPI,TV) (namedasequation1a,1b)Indirect effects:TV=f(CPI,GDP)
G i : dependentv a r i a b l e , r e p r e s e n t e d byG D P g r o w t h r a t e p e r year i i coveringtheperiodfrom1975to1996,G i (1/T)ln(YT/Y o ) ln(Yo i) : independentvariable,representedbythelogarithmofthedegreeo f i nitialincomewithnegativecoefficient,α1 c h i 2 ) z)F)F)isverysmall(0.0000),indicatingthatwerejectthatthemodelspecificationiscorrect.
In conclusion,Swilk-test,White’stest,Breusch-Pagantest,Ramsey- resettesthaveb e e n implementedtoprovetheModel1isrelatedtoeconometricissues :abnormald i st r i b u t i o n o f e r r o r t e r m , h e t e r o s c e d a s t i c i t y problem,model s p e c i f i c a t i o n e r r o r WhenanassumptionofOLSregressionisviolated,wesho uldturnoutthatapplyingOLSdirectlytothestructuralequationsofasimultaneoussystem. 4.2.2Effectsofcorruptiononeconomicgrowththroughtransmitionchannels
1 0 ) tocal culate capitalstockseriesbasedonthegrossfixedcapitalformantion.Howe ver,whenuseitasaproxyforinvestmentinthesystemofequations,regressiong avepoorresults(model2isomitted– showninAppendixC.4).So,thispapercontinuesu s i n g Grossdomesticfixedinvestmentto measurethelevelofinvestment.
Table 7: Results of3SLSregressioninasystemofstructuralequations(Equation1to6)
*Significantat10%,**Significantat5%,***Significantat1%Inwhich:Endogenousv ariables:GDP,PI,I,GOV,OPEN,HC
Exogenousvariables:CPI,LnGDP,LnPOP,URBAN,DLI,DLMI,DUMI,DHIO,DHINO
TheT a b l e 8 i l l u s t r a t e s t h e i m p a c t a n d t h e c o n n e c t i o n b e t w e e n c o r r u p t i o n a n d economicgrowthinAsiancountriesviavariousinterme diaryfactors.Thesecondcolumnrevealstheeffectsofinvestment,humancapit al,politicalinstability,governmentspending,andopennesstotradeare0.217,0.01 3,0.361,-
0.098,0.012r e s p e c t i v e l y basedonequation1(α 2to α6s h o w ninTable7).Inordertoinve stigatet h e i mp act of c o r r u p t i o n on t h e c h a n n e l s , wet r e a t c o r r u p t i o n ast he i n d e p e n d e n t variable ThethirdcolumnsummarizestheeffectofcorruptiononI,H C,PI,GOV,an d OPENare3.785,-
3.510,0.291,3.013,and13.813respectivelyb a s e d onequation2to6(β 2refers toTable7).Thecoefficientsinthelastcolumnrepresentst h e impactofcorruptiononcountrygrowt hthroughdifferent
Page48 LEKIMDUNG intermediarychannelsbymultiplyingsecondandthirdcolumn.Theseresultsneedtobee xplicated conservativelyinordertoavoidmisleadingperception.Positivesignofcoefficientindic atesthed e t r i m e n t a l relationshipb e t w e e n c o r r u p t i o n a n d g r o w t h v i a c h a n n e l b e c a u s e highercorruptionperceptionindex
(CPI)reflectslowerlevelofcorruption.I notherwords,anincreaseinCPIisassociated withhighereconomicgrowth,andc o n t r a s t
AccordingtotheresultsinTable8,theeffectofinvestmentongrowthispositive.T h e coe ff ic ie nt isp osi ti ve an dsta ti st ica ll y significanta t1 0% level.I tm ea ns 1
%increasedingrossf i x e d capital(I)wouldl e a d to0.217%increasedineconomicg r o w t h (GDP) This is suitable with growthmodelof
The coefficient of corruption on investment is positive, measured at 3.785, but lacks statistical significance, likely due to economic collapses between 1998-2000 and 2007-2009 Countries with lower corruption levels tend to attract more capital investment The relationship between these two coefficients highlights how corruption impacts growth through the investment channel Specifically, a one-unit increase in the corruption perception index, indicating lower corruption, is associated with an approximate 0.821 percentage point increase in economic growth via investment This negative correlation between corruption and growth aligns with the findings of Mauro (1995).
( 1 9 9 6 ) , Pa kH u n g Mo(2 00 1) , P el le gr in i a n d Gerlagh(2004),MohamedDribi(20 13).M a u r o (1995)clarifiedthatcorruptionred u c es t h e i n v e s t m e n t i n c e n t i v e s o f e n t r e p r e n e u r s b e c a u s e offeringh i g h e r b r i b e increasestransactioncostsodecli neprofit.
Humancapitalthatispresentedbypercentoftotalenrollmentinsecondarye d u c a t i o n overtotalofficialsecondaryeducationagepopulationrelatespositively w i t h growth.But,thecoefficientisnotsignificantevenat10%level,sowecannotc o n c l u d e thathumancapitalhasvitualroleongrowth.Anyway,thisresultreflectst h a t 1% increaseinthesecondaryschoolenrollmentrateleadsto0.013%increaseinecono micgrowth.Theunclear,weakeffectofhumancapitalongrowthwiththed a t a s e t ino urpaperissimilarwiththeresultsfromtheresearchesdonebySpiegel andBenhabib(1994),KnowlesandOwen(1995).Onthecontrarywiththismanner,c o e f f i c i en t o f c o r r u p t i o n o n h u m a n isn e g a t i v e a n d s i g n i f i c a n t a t 1 % ( e q u a l s -
3.510).I t meansc o r r u p t i o n w i l l b o o s t u p humanc a p i t a l T h e r e a s o n i s d u e t o studentsarewillingtoenrollf o r schooling, a n d corrupt educators t o obt aingoodg r a d e s easily.Asaresult,thecoefficientofcorruption(CPI)ongrowth( GDP)viahumanc a p i t a l ( H C ) i s -
0 0 4 6 , i m p l y i n g t h a t corruptioni n d e x c l i m b s by1 0 u n i t ( l o w e r c o r r u p t i o n l e v e l ) , t h e a v e r a g e e c o n o m i c d e v e l o p m e n t w o u l d d i m i n i s h by 0.46p e r c e n t a g e p o i n t a n n u a l l y p ro vi de d t h a t h o l d i n g o t h e r t h i n g s u n c h a n g e d
I t al so m e a n s t h a t c o r r u p t e d economiesa r e a s s o c i a t e d w i t h h i g h e r g r o w t h t h r o u g h humancapital.Thisresultscontradictsthe findingsof Mo(2001),Pellegriniandhisc o l l e a g u e (2004),UgurandDasgupta(2011),M.Dribi(2013)
Consideringthe3SLSregressionresults,thecorruptionindex(CPI)isstatisticall ys i g n i f i c a n t a n d h a s p o s i t i v e c o e f f i c i e n t w i t h d e p e n d e n t v a r i a b l e G D
P g r o w t h v i a p o l i t i c a l i n s t a b i l i t y ( P I ) a s e x p e c t e d I n d e t a i l s , 1 p o i n t increaseinC P I ( l o w e r corruptiondegree)willresultin0.105percentagepoi ntincreaseinthegrowthrateo f t h e e c o n o m y v i a r a i s i n g p o l i t i c a l i n s t a b i l i t y i nde x( h i g h e r s t a b i l i t y of p o l i t i c a l condition).T h i s f i n d i n g i s c o n s i s t e n t w i t h t h e s t u d y byM o h a m e d D r i b i ( 2 0 1 3 ) , Muscatellietal(2000).Thecountry withlowcorruptionlevel,highstablepoliticalconditioncanprotectenvironmentofin vestment,andpromoteeconomicd e v e l o p m e n t
Next,t h e r a t i o o f g e n e r a l g o v e r n m e n t f i n a l c o n s u m p t i o n e x p e n d i t u r e ( G O V ) t o GDPisinsignificant evenat10%levelinequation1.Thenega tivecoefficientofG O V ( e q u a l s -
0 0 9 8 ) i m p l i e s t h a t t h e d e c l i n e i n d e g r e e o f g o v e r n m e n t s p e n d i n g l e a d s toincreaseingrowth.However,inthisdataset,thecoefficientisverysmalland n o t s i g n i f i c a n t , s o w e c a n n o t makea c o n c l u s i o n a b o u t t h e l i n k a g e b e t w e e n GO V andGDPdirectly.WiththecoefficientofCPItoGOVis3.013,wecalculatedt h e e f f e c t o f corruption on growthvia governmentspending.Asa result,thecoefficientis-
0.295andsignificantat1percentlevel.Ifthecorruptionindexfallsby1unit(lo werstageofcorruption),theGDPgrowthratewillgoupby
Higher levels of corruption, as indicated by a 0.295 percentage point increase in government expenditure, are likely to accelerate economic growth This finding aligns with Mohamed Dribi's 2013 study and Mauro's 1998 research, which highlighted that in countries with significant corruption, bureaucrats tend to misallocate government budgets and public resources towards areas that are challenging to monitor effectively This mismanagement often leads to increased corruption as officials engage in dishonest practices to conceal their activities Consequently, after receiving bribes, bureaucrats may relax regulations and rules, fostering a more liberated and efficient environment for investment and international trade, ultimately contributing to the country's economic growth.
Ont h e o t h e r h a n d , g r o w t h c a n b e b o o s t e d by0 1 6 6 p e r c e n t a g e p o i n t t h r o u g h opennesst o t r a d e ( O P E N ) w h e n c o r r u p t i o n p e r c e p t i o n i n d e x c l i m b s by1 u n i t (lowerlevelofcorruption).Thiscoefficientisstatisticallysi gnificantatlevelof1%,a n d h a s e x p e c t e d s i g n I t meanst h a t l o w e r c o r r u p t i o n l e v e l isl i k e l y t o p r o m o t e g ro wt hv i a t r a d e o p e n n e s s T h i s i m p a c t i s s i m i l a r w i t h t h e p a p e r p u b l i s h e d byP e l l eg r i n i a n d G e r l a g h ( 2 0 0 4 )
G u n l a c h ( 1 9 9 6 ) a l s o i n v e s t i g a t e d thatthec l o s e d d e v e l o p i n g countrie sgrewslowerthantheopeneddevelopingcountriesthankstothetechnologyadv ancementandthet r a n s f e r o f t e c h n i c a l k n o w l e d g e m e n t H o w e v e r , c orruptionclimbsthetransactioncostoftradeopenness,notonlybribespaymentfort heallocationofquota,tariffandtradelicenses,custombureaucracy,lowtrade barriersbut a ls o contains ther is ko fc r e a t i n g illegalagreementandthelikelihood o f r e a c h i n g an agreementbythe o t h e r p a r t y (Lambsdoff, 2 0 0 2 ) E x p o r t e r s andimportershavetosubornthegovernmentofficerstoaccessthetradeactivitieswith ease.Consequently,corruptionhasadetrimentalimpactongrowthv i a theop enofinternationaltradeactivities.
Thetotalvalueofthepositiveindirectimpactofcorruptionongrowthtransmitted viathemechanismsofhumancapital(HC)andgovernmentexpenditure(GOV)is-0.341,meanwhilethetotalvalueofthenegativeindirectimpacttransferred
LEKIMDUNG Page51 throughinvestment,t h e openo f tradeac ti vi ti es, an dp ol it ic al i ns t a b i l i t y is1 0
9 2 S o , thetotalcoefficientsoftheoverallimpactofcorruptionongrowthviadifferent c h a n n e l s i s 0 7 5 1 , i n w h i c h i n v e s t m e n t a n d governments p e n d i n g a r e t h e v i t a l channels.Thesumofcoefficientoftheindirecteffectandthedirecte ffectequals
0.22.ItmeanswhenCPIincreases1unit(lowerlevelofcorruption)whileholdingo t h e r thingsunchanged,growthrateofeconomicincreases0.22percentagepoin t Tosumup ,thecorruptionperceptionindexhasapositivecorrelationwithe conomicgrowthtotally.Thismeanscorruptionhasanegativelinkagewithgrowth.T h e count rieswithlowercorruptionhavefastergrowthratethanhighercorruptioncountries.
Conclusion
Int h i s study,w e i n v e s t i g a t e d t h e r e l a t i o n s h i p b e t w e e n c o r r u p t i o n a n d economicg r o w t h b o t h d i r e c t l y a n d i n d i r e c t l y t h r o u g h t r a n s m i s s i o n c h a n n e l s w i t h o r d i n a r y leastsquareapproachandstructuralequationsofasimultane oussystemapproach.
Inconsistency withfindingsofmostofthepreviousempiricalreseaches,thispaperco nclu ded thatthei mpactofcorruptiononeconomicgrowthonthirtyAsianco un t r i es during the observationperiodfrom1996to2014issignificantlynegative.B a s e d onourregressionresu lts,wecometosomemainconclusionsasfollows:
- Iti s mores u i t a b l e tou s e s t r u c t u r a l e q u a t i o n s o f a s i m u l t a n e o u s s y s t e m approachthanordinaryleastsquareapproach(singleequationapproach)
- Thetotalpositive indirectimpactof corruptionongrowthtransmittedviathem e c h a n i s m s o f h u m a n c a p i t a l ( H C ) a n d g o v e r n m e n t e x p e n d i t u r e ( G O V ) i s only0.3 41 %, w h i l e t h e t o t a l n e g a t i v e i n d i r e c t impactr e s u l t e d fromi n v e s t m e n t , t r a d e o penn ess, andpolitical instabilityis1.092%.
Limitationsandfutureresearch
Limitations
Firstly,thisstudyexplorestheimpactofcorruptiononeconomicgrowthmeasuredbyth eincreaserateofGrossDomesticProduct(GDP).However,thisquantificationmethodhasbe engeneralizedandsystematizedwhichasaresultdonotfacilitateto trackt h e impact o f c o r r u p t i o n onv a r i o u s s e c t o r s / a s p e c t s o f t h e economy.T h e de v e l o p m e n t inseveralsectorssuchasagriculture, industry,tradingandmanufacturing,e t c i s t o t a l l y d i f f e r e n t f r o m t h e g r o w t h i n economicc h a n g e I t meansthatthisstudydoesnotspecificallyinvestigateth elevel of corruptionanditsimpactonthegrowthrateindifferentsectoroftheeconomy.
Secondly,thisstudy includesalarge n um be rofdi ff er en t countries w it h diff erent economicenvironment.Therefore,thelessonsforspecificcountryfromotherc o u n t r i e s islimited.
Thirdly,t h i s studyd o e s n o t t a k e i n t o a c c o u n t t h e impacto f financialc r i s i s o n corruptiona n d economicg r o w t h M e a n w h i l e theg r o w t h p a t t e r n o f thee c o n o m y a n d levelofcorruptionisconsiderablydifferentbefore,duringandafterthep eriodo f economicdeficiency.Withinthescopeofthisresearch,thecoefficientofinv estmentandcorruptioninModel2isprovedtobeinsignificantandthetrendofitsgrowth iserraticfrom1996to2014.
Finally,thisstudyonlyfocusesononewayrelationofhowcorruptioncouldimpactt o econo micgrowththroughintermediaryfactors,whilepayingnoattentiontother e v e r s e impactofeconomicgrowthtocorruption.Itmeansifweputmoreefforttof i n d outthet wo- waycausalitybetweencorruptionandgrowth,itmaysignificantlyp r o v i d e awiderran geofanalysisforfutureresearch.
Ino r d e r t o e n h a n c e , g e n e r a t e , b r o a d e n , a n d d e e p e n t h e p r e c i s e r e s u l t s , f u r t h e r r esearch es s h o u l d b e a d d e d measuresofmacoeconomi ce l e m e n t s s u c h a s l e g a l structure,regulationandsupervision;implemen tedwithalargersamplesizewithd if f er e n t regionsallovertheworld,withvariousmet hodologies.
Accordingtotheabove- mentionedlimitationofthispaper,furtherresearchesshouldanalyzetheperformanceo fdifferentsectorsincludingagriculture, manufacturing,industry,andtrading,etcandhowcorruptioncouldmakeinfluenceo n e achaspectatanintensivelevel.
Futherresearchersshouldcalculatetheoptimalcorruptionvalue,thepointatwhichtheec onomicgrowthmayturnfrompositivetonegativeandcontrast Thepol icym ak er s shouldsetupstandardforanti- corruptionwherebyimmediateactionmustbetakenwhencorruptionexceedstheestimate doptimallevel.
Inaddition,futurereseachersshouldfocusonanalyzingthetwo- waylinkagebet ween corruption andeconomicgrowthastheperiodicimpactofbothelementsisc r i t i c a l toexplainthenat ureofcorrelationbetweencorruptionandeconomicd evel op men t H o w e v e r , i t i s i m p o r t a n t t o p a y a t t e n t i o n w h e n d e a l i n g w i t h t h e d u p l i c a t i o n effectofthevariablessincetheimpactistransferredviadiversec h a n n e l s
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No Authors Methodology Data Results
Meta-analysis 460empiricalestimatesa boutt h e t h e relation shipb e t w e e n corrupti on andeconomicg r o w t h f rom41d i f f e r e n t theo reticala n d empiricalinvestigations.
32%oftheestimatesstated asignificantandnegative effectofc o r r u p t i o n o n growth,6 2 % s h o w e d a i nsignificantcorrelation,only 6% s u p p o r t e d f o r a signi ficanta n d p o s i t i v e rela tion.
Meta-analysis 115a n a l y t i c a l s t u d i e s focuso n l o w i n c o m e countriestoevalu atetheeffectofcorrup tiononeconomicgrowth
Theo v e r a l l e f f e c t (direct an d i n d i r e c t ) o f c o r r u p t i o n onG D P g r o w t h p e r c a p i t a in LICs(LowIn comeCountries)is-
0 5 9 percentage point.Corruptionwouldtend toimp act g r o w t h n e g a t i v e l y v i agovernmentexp enditure(-
0 2 9 percent age point).I nmixedcountries,c o r r u p t i o n ha v e “greasingthewhe els”effectthroughinvestme ntchannel(o nl y+ 0 0 4 p e
Jong- WhaL e e , s a m p l e per io d:1960-1985. totale f f e c t i s - 0545percentage point.The contributionofdirecteffe ctandt h e t r a n s m i s s i o n mechanismsd e s c r i b e d a r e : directe f f e c t (- 11.8), humanc a p i t a l ( - 1 4 8 ) , politicalinstability(-52), investment( -
Negativeimpactsofunpre dictablecorruptiononecon omicg r o w t h v i a investmen tchannel.
Datas e t c o v e r i n g 70 developed anddevelopingc o u n t r i es Observationp e r i o d isfrom1980to198
Cross sectionanalysis ,ch ann el
General Negative relationshipbetweenc o r r u p t i o n a n d growth,expres methodology, 2SLS,OLS ao n e - u n i t i n c r e a s e i n corruptio nperceptionindexreduces the outputgrowthpercapitaby 0.38percentagepoint.Thevit ualchannelv i a w h i c h corr uptionaffectsgrowthisinve stment.
Thecontributiono f f i x e d investment,tradeopenn ess,politicali n s t a b i l i t y , h u m a n capitaltothet otalnegativeeffect is
Non-linearityofcorruption- g r o w t h correlation T h e effectsofcorruption ong rowthd e p e n d s o n q u a l i t y governancer e g i m e s Int he countriesw i t h h i g h q u a l i t y institutionsregim es,ithasalargeandsignifica ntnegativee f f e c t Adve rsely,thereisnoimpactinco untriesw i t h l o w q u a l i t y governance regimes.
Methodology period1980-2002 transmission channelsthroughwhichcorru ptionop er ates a r e humanc a p i t a l (- 0.5%) a n d p o l i t i c a l instability( -
0 4 6 % ) T h e co n t ri b u ti o no f h u m a n capital, investment, inflation, politicalinstabilitytonegative im p act ofcorruptionong rowthi s 3 6 6 % , 2 2 9 % , 6.6%,a n d 3 3 8 % respectively.C o r r u p t i o n h as p o s i t i v e e f f e c t o n
Datacovering54develo ped anddevelopingc o u n t r i e s withobservedperi od1980-2003
Thereisexistenceofastron gmutualnegativerela tions hip betweencorruptionandecon omicgrowth.Corruptioni schangeablea n d t h i s rela tionshipdependsonthecult ure,anyc h a n g e s i n cultu ret e n d s t o t h e destructio nofthethreshold.Almostr e s o u r c e s b e l o n g s t o thest ate,governmentprincipall yc o n c e r n s with corruption,sodevelopmen ttrapsmoveup
GMM Datacovering33Africa nc o u n t r i e s w i t h o bservedp e r i o d from 1982to2001
General Corruptionas“speedmoney”i sefficienttoeconomicgrow th.
General “Greaset h e w h e e l ” t h e s i s , positive relationshipbetweenc o r r u p t i o n a n d growth.
14 Lien(1986) General Competitiveb r i b e r y g amewithincompletein formation
Global3866firms surveyfrom48countriesi n1996and1 9 9 7 noe v i d e n c e s s u p p o r t forthe“speedmoney”thesis,exp r e ssed differently,they refuted“efficientgrease”t hesis,socorruptionred uces economicgrowth
.xtsetidyear panelvariable:i d (stronglybalanced)timevari able:year,1996to2014 delta:1 unit
.byid:egenavg_ggfK=mean(igrowth)
.byid:genK=iusd[1]/(depreciation+avg_ggfK)
.graphtwoway(lfitvariable1variable2)(scattervariable1variable2)
LEKIMDUNG Page70 cpiunit 1.87 1.37 0.5358 0.4642 igrowth 1.21 1.10 0.8233 0.1767 hc 1.64 1.28 0.6084 0.3916 piunit 1.82 1.35 0.5487 0.4513 govgdp 1.27 1.13 0.7887 0.2113 opengdp 1.11 1.05 0.8993 0.1007
Variable VIF VIF Tolerance Squared
Eigenvalues&CondIndexcomputedfromscaledrawsscp(w/ intercept)Det(correlationmatrix) 0.2820
Source SS df MS Numberof obs= 253
AdjR-squared=0.2883 RootMSE =3.8442 gdpgrowth Coef Std.Err t P>|t| [95%Conf.Interval] cpiunit -.5154352 2099528 -2.46 0.015 -.9289696 -.1019008 igrowth 1652213 0185209 8.92 0.000 1287415 2017011 hc 0129003 0153824 0.84 0.402 -.0173978 0431984 piunit -.1179124 3505925 -0.34 0.737 -.8084585 5726337 govgdp -.0358273 0226089 -1.58 0.114 -.0803591 0087044 opengdp 004797 005932 0.81 0.419 -.0068871 016481
Fixed-effects(within)regression Numberofobs = 253
F(6,221) = 12.68 corr(u_i,Xb) = -0.1936 Prob>F = 0.0000 gdpgrowth Coef Std.Err t P>|t| [95%Conf.Interval] cpiunit 3331118 603185 0.55 0.581 -.8556188 1.521842 igrowth 1561048 0186316 8.38 0.000 1193865 1928231 hc -.0219766 0405505 -0.54 0.588 -.1018917 0579385 piunit 1347567 7562715 0.18 0.859 -1.35567 1.625183 govgdp -.1257954 1001291 -1.26 0.210 -.3231256 0715347 opengdp 024225 0187165 1.29 0.197 -.0126607 0611108
_cons 4.599427 3.710579 1.24 0.216 -2.71322 11.91207 sigma_u 2.6531922 sigma_e 3.6222947 rho 34917027 (fraction ofvariancedue to u_i)
R-sq:within= 0.2431 Obs pergroup:min= 1 between=0.5533 avg= 9.7 overall=0.3046 max= 15
Waldchi2(6) = 95.31 corr(u_i,X) =0(assumed) Prob>chi2 = 0.0000 gdpgrowth Coef Std.Err z P>|z| [95%Conf.Interval] cpiunit -.4756252 2696616 -1.76 0.078 -1.004152 0529017 igrowth 1599184 0180012 8.88 0.000 1246367 1952002 hc 0088387 0192831 0.46 0.647 -.0289555 0466329 piunit -.1357008 4215096 -0.32 0.747 -.9618445 6904429 govgdp -.0378981 0260947 -1.45 0.146 -.0890428 0132465 opengdp 0070921 0080145 0.88 0.376 -.0086161 0228003 _cons 5.065353 1.804259 2.81 0.005 1.52907 8.601637 sigma_u sigma_e rho
(b-B) Difference sqrt(diag(V_b- V_B))S.E. cpiunit 3331118 -.4756252 808737 5395505 igrowth 1561048 1599184 -.0038136 0048054 hc -.0219766 0088387 -.0308153 0356722 piunit 1347567 -.1357008 2704574 6279141 govgdp -.1257954 -.0378981 -.0878973 0966691 opengdp 024225 0070921 0171329 0169138 b=consistentunderHoandHa;obtainedfromxtregB =inc onsistentunderHa,efficientunderHo;obtainedfromxtreg
Source SS df MS Numberof obs= 253
AdjR-squared=0.3354 RootMSE =3.7149 gdpgrowth Coef Std.Err t P>|t| [95%Conf.Interval]
Equation Obs Parms RMSE "R-sq" chi2 P gdpgrowth 185 6 4.006249 0.2516 26.47 0.0002 piunit 185 9 7128735 0.4546 158.65 0.0000 igrowth 185 9 13.72176 0.0995 64.87 0.0000 govgdp 185 9 11.00549 0.2965 408.54 0.0000 opengdp 185 9 41.12856 0.0833 1336.21 0.0000 hc 185 10 12.30538 0.6324 8050.52 0.0000
Coef Std.Err z P>|z| [95%Conf.Interval] gdpgrowth cpiunitpiuni tigrowthgovg dpopengdp hc
353146 2.935143 438271 0277591 0379714 0679632 13.10168 piunit cpiunit govgdpln gdpusd lnpop urbanpop dli dlmid umidh iodhi no
4401425 0205526 3500773 0636506 -.0029047 -.6375903 -.2852201 0538677 000472 2.649453 igrowth cpiunit hc lngdpusd opengdp dli dlmid umidh iodhi no
8.626659 3302571 -.7452203 0979504 164.7687 183.1468 187.0332 168.4226 159.886 govgdp cpiunit hc lngdpusd urbanpop dli dlmid umidh iodhi no
5.159503 3001624 -2.960954 -.0607962 133.5281 153.3533 156.7431 171.6786 152.6316 opengdp cpiunit lngdpusd hc govgdp dli dlmid umidh iodhi no
20.300432.194786.48575253.358916175.562187.3237234.9295148.4636171.0144 hc cpiunit -3.50982 1.321533 -2.66 0.008 -6.099978 -.9196627 lngdpusd 13.95158 2.020281 6.91 0.000 9.991906 17.91126 edugdp 1.551186 647293 2.40 0.017 2825151 2.819857 lnpop -17.7138 2.078573 -8.52 0.000 -21.78773 -13.63987 urbanpop -.1379824 0886948 -1.56 0.120 -.311821 0358562 dli 34.80135 18.30126 1.90 0.057 -1.068452 70.67116 dlmi 45.61234 19.63624 2.32 0.020 7.126013 84.09867 dumi 38.92841 21.32442 1.83 0.068 -2.866683 80.7235 dhio 51.56339 23.37033 2.21 0.027 5.75838 97.36841 dhino 34.59282 21.59988 1.60 0.109 -7.742162 76.92781
Endogenousvariables: gdpgrowthpiunitigrowthgovgdpopengdphcExogenousvariables: cpiunit lngdpusd lnpop urbanpopdlidlmi dumidhio dhinoedugdp
*Reg3commandwithCapitalstockseries(K)calculatedfollowingmethodp r o p o s e d byRodneySmith(2010)–proxyforcapital
( g o v g d p c p i u n i t h c l n g d p u s d u r b a n p o p d l i d l m i d u m i d h i o d hi no ) (o pe ng dp c p i u n i t ln gd pus dh cg ov gd pd li dl mi dumid h i o dh in o)
Equation Obs Parms RMSE "R-sq" chi2 P gdpgrowth 163 5 6.793868 -0.9598 15.53 0.0083 piunit 163 9 5307033 0.6592 423.78 0.0000 k 163 0 7.53e+12 -0.1752 govgdp 163 8 11.29342 0.3207 73.67 0.0000 opengdp 163 8 48.94792 -0.2401 383.47 0.0000 hc 163 9 10.14695 0.6399 382.98 0.0000
Coef Std Err z P>|z| [95%Conf.Interval] gdpgrowth cpiunit piunit k govgdpo pengdp hc
-.2303119 6.272839 -1.05e-13 3026524 0422952 0642815 30.57343 piunit cpiunit govgdpln gdpusd lnpop urbanpop dli dlmid umidh iodhi no
4553923 0262272 1331635 1024583 0004436 -.9205418 -.181494 0514524 6148189 2.318664 k cpiunit hc lngdpusd opengdp dli dlmid umidh iodhi no
(omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) govgdp cpiunit hc lngdpusd urbanpop dli dlmid umidh iodhi no
5.148825 1147118 -3.579859 003655 8958745 16.18113 15.44364 30.32115 182.6229 opengdp cpiunit lngdpusd hc govgdp dli dlmid umidh iodhi no
16.712063.76899.51010663.9347954.6131451.6795888.68621-15.65922129.7234 hc cpiunit -1.735516 1.007481 -1.72 0.085 -3.710142 2391098 lngdpusd 12.03271 1.482803 8.11 0.000 9.126465 14.93895 edugdp -1.407223 5206183 -2.70 0.007 -2.427616 -.3868293 lnpop -16.09899 1.539084 -10.46 0.000 -19.11554 -13.08244 urbanpop -.2030719 0657741 -3.09 0.002 -.3319867 -.074157 dli -.0072011 6.949825 -0.00 0.999 -13.62861 13.6142 dlmi 13.50716 5.589678 2.42 0.016 2.551591 24.46272 dumi 6.983277 4.754113 1.47 0.142 -2.334613 16.30117 dhio 21.00772 4.669553 4.50 0.000 11.85556 30.15987 dhino 0 (omitted)
reg3(gdpgrowthcpiunitpiunitigrowthgovgdpopengdphc)(igrowthcpiunithcopengdplngdpusd)(hccpiunitlngdpusd)(piunitcpiu
Equation Obs Parms RMSE "R-sq" chi2 P gdpgrowth 213 6 4.539146 -0.0377 25.15 0.0003 piunit 213 10 7171053 0.4196 362.13 0.0000 igrowth 213 9 15.34428 0.1196 77.87 0.0000 govgdp 213 9 12.46649 0.0063 343.91 0.0000 opengdp 213 9 38.45849 0.1248 1287.23 0.0000 hc 213 9 13.9284 0.5866 382.05 0.0000
Coef Std.Err z P>|z| [95%Conf.Interval] gdpgrowth sqcpi piuniti growthg ovgdpop engdp hc
0312363 1.688024 4045317 -.0099152 0356612 0970822 7.805273 piunit sqcpi govgdpln gdpusd lnpop urbanpop dli dlmid umidh iodhi no
035236 0166144 2223405 0771333 -.0027254 2.255138 3.038947 3.730426 4.273281 4.875879 igrowth sqcpi hc lngdpusd opengdp dli dlmid umidh iodhi no
5572053 137195 005945 2542448 123.4555 138.7808 140.9274 138.1944 124.7118 govgdp sqcpi hc lngdpusd urbanpop dli dlmid umidh iodhi no
4630984 6935059 -1.489589 -.0994977 89.10135 100.9696 103.8591 111.3919 103.2312 opengdp sqcpi lngdpusd hc govgdp dli dlmid umidh iodhi no
1.617009 5277843 77676 3.022734 218.5248 216.5528 261.3201 187.4795 214.3863 hc sqcpi lngdpusd edugdpln popurban pop dli dlmid umidh iodhi no