The Competitiveness of Latin-American Economies: Consolidation of the Double-Diamond Theory

Abstract

The aim of this research is to assess the competitiveness of countries through the
development of a new model, which is much simpler than those currently in use. The
premise of this research is based on the fact that the current models contain numerous
indicators/measures and cannot be applied to other contexts, such as the Latin American
(LA) one. Based on the “diamond competitiveness” approach, we developed a model for
the LA economies (Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru,
Uruguay and Venezuela). Our model has clear implications for both academics and
policymakers and could help design state policies to improve economic growth,
especially for the less developed LA economies.

Full text

1/6/2016 ThecompetitivenessofLatinAmericaneconomies:Consolidationofthedoublediamondtheory
http://www.sciencedirect.com/science/article/pii/S0939362516300413 1/43
Article outline Show full outline
Highlights
Abstract
JEL classification
Keywords
1. Introduction
2. Research model
3. Sample and methodology
4. Conclusions and implications
5. Uncited references
References
Figures and tables
Table 2
Table 3
Table 5
Table 4
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doi:10.1016/j.ecosys.2015.10.003
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EconomicSystems
Availableonline31May2016
InPress,AcceptedManuscript—Notetousers
ThecompetitivenessofLatinAmericaneconomies:
Consolidationofthedoublediamondtheory
SegundoCastroGonzálesa, ,J esúsC.PeñaVincesb, , ,JorgeGuillenc,
aIENBusinessSchool,UniversidaddelEste(UNE),PuertoRico
bCollegeofEconomicsandBusiness,DepartmentofBusinessManagementandMarketing,Universityof
Seville,AvenidaRamónyCajal,s/nSevilla,41018,Es paña
cESANGraduateSchoolofBusiness,Peru
Received22January2015,Revised31July2015,Accepted29October2015,Availableonline31May
2016
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Highlights
Basedonthe“diamondcompetitiveness”approach,weevaluatedthe
competitivenessofLatinAmerican(LA)economies.
Ourresearchhasclearimplicationsforacademicsandpolicymakers,especially
concerninglessdevelopedLAeconomies.
TheresultsshowthatinLatinAmericatherearethreedistinctcompetitivelevels:
high,mediumandlow.
Abstract
Theaimofthisresearchistoassessthecompetitivenessofcountriesthroughthe
developmentofanewmodel,whichismuchsimplerthanthosecurrentlyinuse.The
premiseofthisresearchisbasedonthefactthatthecurrentmodelscontainnumerous
indicators/measuresandcannotbeappliedtoothercontexts,suchastheLatinAmerican
(LA)one.Basedonthe“diamondcompetitiveness”approach,wedevelopedamodelfor
theLAeconomies(Argentina,Bolivia,Brazil,Chile,Colombia,Ecuador,Paraguay,Peru,
UruguayandVenezuela).Ourmodelhasclearimplicationsforbothacademicsand
policymakersandcouldhelpdesignstatepoliciestoimproveeconomicgrowth,
especiallyforthelessdevelopedLAeconomies.
JELclassification
F14;F63;F52;R11
Keywords
Globalcompetitiveness(domestic/international);LatinAmericaneconomies;
Developingcountries;Emergingeconomies;Economicdevelopment
1.Introduction
Thefinancialdownturnofindustrializedcountries−withparticularreferencetothemore
specificeconomiccrisissufferedinEurope,whichhashadaknockoneffecton

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1/6/2016 ThecompetitivenessofLatinAmericaneconomies:Consolidationofthedoublediamondtheory
http://www.sciencedirect.com/science/article/pii/S0939362516300413 2/43
worldwiderecovery−hasledtotheoveralleconomyoftheLatinAmericanregionbeing
viewedinapositivelight.Opinionsvoicedineconomicandacademiccirclespointto
SouthAmericaandAsiaasthemotorsoffutureworldwidegrowth,atleastforthenext
decade(WEF,2012aandWEF,2012b).ThisisbecauseSouthAmerica(SA)hasshown
economicstabilityandaconsiderableimprovementininternationalcompetitiveness
(Feinberg,2008).Furthermore,severalinternationaleconomicagentsandinvestors
havemadeapositiveassessmentofSA,viewingtheregionnotonlyasatraditional
exporterofrawmaterialsbutasapossiblestrategicpartnerforprocessingrawmaterials
intofinalproductsandactingasatrusteeoftheirinvestmentsandproductiveprojects.
MarianneVanSteen,spokespersonoftheEuropeanUnioninSouthAmerica,recently
commented:“Companiesfromtheeurozoneareconsideringthepossibilityofextracting
andtransformingrawmaterials,particularlyinPeru,andexportingthem,giventheglobal
economiccrisis”.
Kalimeris(2012)suggeststhatthereisadirectandpositiverelationshipbetween
economicgrowth,foreigndirectinvestment(FDI)andcompetitiveness,especiallyin
timesofglobaleconomiccrisis.Thequestionthereforearises:Domethodologically
reliablesourcesthatmeasurethecompetitivenessofSouthAmericancountriesexist?A
reviewofinternationaleconomicsandbusinessjournalshighlightsthelackofasingle
definingstudythatexaminesthecompetitivenessoftheSouthAmericanregion.The
purposeofthisresearchisthereforetofillthisinherentgap.
WeshouldnotetheexistenceoftheyearlypublicationsoftheWEF(2014)andIMD
(2014),whichassessthecompetitivenessofnationsannuallybycompilingalistof
rankings.Thepublicationsproducedbythesetwoorganizationsarewellknownand
usedbygovernments,economicagentsandresearchers,whoalmostconsiderthem
bibles.Someacademicsbasetheirresearchontheresultspublishedinthesereports.
TherearealsosomepublicationsdedicatedtoSouthAmericancountries(Gariazo,2004,
GarcíaVega,2011andLora,2005).TheWEFandIMDreportshave,however,been
criticizedbyagroupofacademics(PeñaVinces,2009andLora,2005).Thecriticisms
andobservationshighlightaseriesofweaknesses,rangingfromalackofreliabilityofthe
surveysonwhichthemodelsarebased(specifically,lowparticipation)tothelackofa
robuststatisticalanalysisduetothearbitraryallocationofthe“weights”ofthe
competitivenessindicatorsusedintherankings,leadingtoacertainbiasandlow
reliability(ChoandMoon,2000,Kaplan,2003andLall,2001;Lora,2000;Squallietal.,
2008).
Ourstudypresentsasolutiontotheproblemshighlightedintheliteraturereview.First,
weusestructuralequationmodels(SEM)toassigntheweightsthateach
competitivenessindicatorprovides,amethodwhichallowsustoproposeaparsimonious
modelthatisstatisticallyreliable(PeñaVincesetal.,2012).Theseindicatorshavebeen
takenfromdatapublishedbyinternationalorganizationssuchastheWorldBank(WB),
theInternationalMonetaryFund(IMF),DoingBusiness(DB)andtheEconomic
CommissionforLatinAmericaandtheCaribbean(ECLAC).Secondly,theweights
calculated(λ)wereusedtogeneratearankingofthecompetitivenessofSouthAmerican
countriesusingthedoublediamond(DD)model.Thisensuredthatourstudywouldhave
implicationsforacademicsaswellaspractitioners,giventhatthetoolwillbeusefuland
statisticallyreliable,whilealsobeingmethodicalandimpartial(Lora,2005andChoand
Moon,2000).Inturn,policymakerscanidentifythemostrelevantvariableswhen
establishingmacroeconomicandinvestmentpolicies.
2.Researchmodel
Thestartingpointistoclearlydefinethemeaningof‘countrycompetitiveness’.According
toKrugman(1994),countrycompetitivenessisachievedbyproducingthegreatest
numberofgoodsandservicesthatcompeteworldwide,whichallowsthecountry’s
inhabitantstoenjoyanimprovedandsustainablestandardofliving.Garelli(2006)stated
thatcompetitivenessistheabilityofcountriestocreateandmaintainanenvironmentthat
supportsthecompetitivenessofcompanies.Kalimeris(2012)definedcompetitiveness
asthedegreetowhichanationcanproducegoodsandservicesthatcanwithstand
internationalmarkets,undertheconditionsofafreemarketandfaircommerce,while
maintainingandincreasingtheactualincomesofitsinhabitantsoverthelongterm.
PreviousconceptscomplementtheWEF’s(2015)definitionofnationalcompetitiveness
asthesetofinstitutions,policiesandfactorsthatdeterminethelevelofproductivityofa
country.Thelevelofproductivity,inturn,setsthelevelofprosperitythatcanbeattained
byaneconomy.

1/6/2016 ThecompetitivenessofLatinAmericaneconomies:Consolidationofthedoublediamondtheory
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Porter(1990)putforwardoneofthefirstproposalstoexplainthecompetitivenessof
nations,consideringfourdeterminantfactors:factorconditions(FC),demandconditions
(DC),relatedandsupportingindustries(RSI),andfirmstrategy,structureandrivalry
(FSSR).Heproposedthatthestrongerthesefactorswere,themorestrengthacountry
hadtocompeteinternationally,whichinturnmeantthatthesecountriescouldattract
internationalcompaniesmoreeasily,soastoestablishtheirpresenceinthecountryof
originthroughFDI(Dunning,1993andGugler,2007).Oneofthemaincontributionsof
Porter’s(1990)modelisthatacountry’scompetitivenessissystemicanddependsonthe
interactionamongthesefactors(FC,DC,RSI,andFSSR).Competitivenessshould
thereforenotbeevaluatedasanindependentvariablebutasaresultofthefourfactorsof
Porter’s(1990)model(PeñaVinces,2009).Thisworkcoincideswiththesystemic
approachtocompetitiveness,asdoothers,suchasChoetal.(2009),ChoandMoon
(2000)andLiuandHsu(2009).
Rugman(1991)criticizedPorter’smodelbecauseitcouldnotbeappropriatelyappliedto
smallcountrieswithastrongexportperformance.Toaddresstheselimitations,Moonet
al.(1995)proposedthedoublediamond(DD)model(Fig.1),whichincorporatesthe
activitiesofmultinationalcompaniesandtheroleofgovernments.
Fig.1.
Thedoublediamondmodel.
Source:AdaptedfromChoandMoon(2000)
Asmentionedintheintroduction,theWEFIMDreports,whichalsoassessthe
competitivenessofcountries,raisedanumberofissuesforseveralresearchers.Cho
andMoon(2000)andKaplan(2003)disputetheWEFandIMDreports,highlightingthe
largenumberofindicatorsthataresourcedfromquestionnaires(between60%and70%)
withalowresponserate(between15%and35%).ChoandMoon(2000)indicatethat
thesereportsdonotproperlyexplaintheweightofthefactors,whichthemselvesare
arbitrary,andthatitisnotclearwhysomevariablesaremoreimportantthanothers.
Kaplan(2003)andLall(2001)highlightthatthebasisonwhichtheWEFIMD
competitivenessindicatorsareconstructeddisplaysanalytical,methodological,and
quantitativeweaknesses.Squallietal.(2008)arguethatthedatausedbyWEFIMD
lacksthestatisticalproceduresforextremedata,andthatcertainindicatorsareassigned
inanarbitrarymanner(forexampleutilitarianpatents).Saidauthorssuggesttheuseof
structuralequationstoimprovethemodelandavoidacertainstatisticalvulnerability.
Lora(2005)statesthattheassessmentsmadebytheseinstitutionsfavorrichand
industrializedcountries,astheyalsotopthelist.Duetothelowresponseratesofthe
surveys,thearbitrarinessoftheweights,lackofappropriatestatisticalmethodsand
partialitytowardsrichcountries,theresultsofthereportsofWEFIMDshow
inconsistencies(ChoandMoon,2000,Kaplan,2003,Lall,2001,Lora,2005andSqualli
etal.,2008).
Basedonthisidea,thisstudyevaluatesthecompetitivenessofSouthAmericaina
regionalcontext,duetotheimportanceoftheregionatatimewhenthephrase“Latin
Americaisinvogue”isfrequentlyuttered.Oursearchforliteraturerelevanttoregional
competitivenessuncoveredstudiesofcertainregionsoftheworld,butalsoalackof
researchexaminingtheSouthAmericanregionasawhole.Somestudieson
competitivenesshavebeencarriedoutconcerningspecificeconomicsectors,suchas
thosebyPietrobelliandRabellotti(2005),whoexaminedtheincreasedcompetitiveness
ofclustersandsupplychainsinLatinAmerica,orCerdaetal.(2008),whoanalyzed
Chileanwineexports.AmongthestudiesonthecompetitivenessofLatinAmerica,wedid
Figureoptions

1/6/2016 ThecompetitivenessofLatinAmericaneconomies:Consolidationofthedoublediamondtheory
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notfindanyusingthedoublediamondapproachtoanalyzethecompetitivenessofthe
SouthAmericanregion.Therearesomepublishedstudiesthatrelatetocertainindustrial
sectorsoftheLatinAmericancountriesortoparticularcountries.AmongtheseareStone
andRanchhod(2006)analyzingthecompetitivenessofBrazil,Russia,IndiaandChina
(BRIC)inthecontextofitbeingmorerobustthanthePorterdiamondmodels,theworkof
BarragánandUsher(2009)usingthe“doublediamond”modeltoexaminethesourcesof
competitivenessoftheautoindustryandautosuppliers,andpossiblespillovereffectsin
Mexico,PeñaVinces(2009)examiningthecompetitivenessofPeruandChile,and
CastroGonzálesetal.(2013),wholookatthecompetitivenessofPuertoRico,Costa
RicaandSingapore.Conversely,alltheseauthorssuggestusingmorereliablestatistical
modelstoassesscountrycompetitiveness,butnoneputthisintopractice.
3.Sampleandmethodology
OfthetwelveLatinAmericancountries,tenwerechosenforthisstudyonthebasisof
dataavailability,asaquantitativemodelwasusedforthepurposeofthisresearch.
GuyanaandSurinamewereomittedfromthestudyduetoalackofdata.Thecountries
includedareArgentina,Brazil,Colombia,Peru,Venezuela,Chile,Ecuador,Bolivia,
ParaguayandUruguay.
Weusedtheaveragesofdatarelatingtotheperiod20002010inordertoreflectthe
generaltendencyofthedataandminimizetheeffectsofanyoutliers.Thevariablesused
werebasedonthefactorsincludedinPorter’s(1990)diamondmodelandthe
subsequentdoublediamondmodel.Wetakethedoublediamondapproach(Moonetal.,
1995)asthemaintheoreticalbasisforourmodelofcompetitivenessinordertocalculate
theweightsandrankings(seeFig.1),asthismodelrectifiesthedeficienciesofPorter’s
model(1990).TheDDmodelwasselectedbecauseitisoneofthemodelsthat
effectivelyoperationalizethecomplexconceptofcompetitivenessinasimpleway,
especiallywhencomparativelyanalyzingthecompetitionbetweencountries,sincethe
resultisreducedtoacomparisonofareasbetweencountries(CastroGonzálesetal.,
2015andMoonetal.,1995).However,itshouldbenotedthattheDDmodelhasa
weakness:theweightsassignedtothedifferentfactorsareproportionaltothenumberof
factorsusedineachconstruct.Thisstudyproposestocorrectthisweaknessbyusing
partialleastsquaresstructuralequationmodeling(PLSSEM)tocalculatetheweightsof
theindicatorsused.OneofmainadvantagesofPLSSEMisthestandardizationofthe
measuresofaconstruct,whichmightbescalesoramounts(Chin,1998andHairetal.,
2013).
ThefactorsusedintheDDmodelaremicroeconomicandmacroeconomicindicators
recommendedinpreviousresearch.Suchindicatorsaretheresultoftheexecutionofthe
countries’policies,basedonthecriterionsusedinanalyzingcompetitiveness
(particularlyinundevelopedregionssuchasSouthAmerica).
Takingintoaccountthattheprocessoftheinternationalizationofhomecompaniesis
conditionedbythepoliticalactionsoftheirgovernments(Saavedra,2012andGonzález,
2006),itisalsoimportantthattheDDmodelincorporatesvariablesrelatedtotheexport
ofhomeindustriestoforeignmarkets(PeñaVincesetal.,2012).
Cartwright(1993),Lagrosen(2007)andMoonetal.(1998)confirmedthattheDDmodel
isusefultoanalyzethecompetitivenessofsmallcountrieswithhighexportintensity.We
usedthemodelbecause,althoughthecountriesstudiedareconsideredtobepartofthe
SouthAmericanregion,assmalleconomiestheyarecomparedwiththemostdeveloped
onesintheworldintermsofGDP.Ofthetencountriesanalyzed,ninearesmall
economies,withtheexceptionofBrazil.Inaddition,becausetheDDmodelissetto
100%oftheseeconomies,wherethegreaterpartofGDP(over50%)isbasedon
exports,eachfocusesonthecomparativeadvantagesitpossesses,sothatextractive
andagriculturalexportproductsmostlyprevail.
TheDDmodelhasbeenvalidatedinpreviousstudies(CastroGonzálesetal.,2013,
Moonetal.,1998,MoonandLee,2004,PeñaVinces,2009andWyk,2010);however,it
hasaseriousshortcoming:theweightofthefactorsusedforeachconstruct(factorof
competitiveness)isproportionaltothenumberofindicators,andthesameweightis
giventoeachfactor/indicator.TheDDmodelwasusedbyMoonetal.(1995)tomitigate,
amongstotherthings,thearbitraryweightsassignedbyWEFIMD.However,asCastro
Gonzálesetal.(2013)andSardyandFetscherin(2009)note,thiscontinuestobea
weaknessofthemodel.Toovercomethisissue,weusedPLSSEMtoassignthe
weights/loadsofeachfactorthatformspartoftheconstructbasedonitsvariance.In

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otherwords,thestatisticalcontributionoftheindicatorsdenotesthecompetitiveness
(PeñaVincesetal.,2012).
TheconceptualframeworkofthisstudyistheresearchofMoonetal.,1995andMoonet
al.,1998,whocreatedandoperationalizedtheDDmodel(seeFig.1)featuringthesame
variablesproposedbyPorter(1990),butwithtwoapproaches:alocaldiamondandan
internationaldiamond.
3.1.TheLatinAmericandoublediamond(LDD)
Aspreviouslymentioned,theDDiscomprisedoffourdeterminingfactorstakenfrom
Porter’s(1990)diamond.AdaptedtothecontextofLatinAmerica,thefactorsareas
follows.
3.1.1.Factorconditions(FC)
3.1.1.1.Localfactorconditions(LFC)
FollowingtherecommendationsofLiuandHsu(2009),weincludedtheworkforce
participationrate,asthisisanimportantfactorwhenanalyzingtheeconomicconditions
ofacountry.Wealsoexaminethenumberofscientific/technicalarticlespublishedand
thenumberofresearchersworkingonresearchanddevelopment(R&D)activities.
Theseindicatorsdemonstratewhethertheresearchofacountryanditsapplications
haveadirecteffectonitscompetitiveness(DufourandGingras,1988,Moonetal.,
1998andPeñaVinces,2009).ChoandMoon(2000),PeñaVinces(2009)andChiuand
Lin(2012)alsocontemplatethepercentageofagriculturallandaspartoftheconstruct,
asthisindicatesthephysicalresourcesatthedisposalofcompaniesfromcertain
industrialsectors.Theseresourcescanthenbemadeintoproductswithgreateradded
value.Agriculturallandandthetotalincomefromnaturalresources(anapproximationof
nationalnaturalresources)arethereforealsoconsidered.Owingtothelackofnon
renewableenergyandthehighcostsinvolved,Dögletal.(2012)suggestthatcountries
needtouserenewableenergy,asthisencouragesthecountry’sindustriestobecome
moreinnovativethroughtheuseoflesscontaminatingproductionsystems(PeñaVinces
andDelgadoMárquez,2013).Wethereforealsoconsiderthisinthemeasurementof
localfactorconditions.FollowingtherecommendationsofMoonetal.(1998),theliteracy
rateisalsoconsidered,asisthemigrationrate,astheamountofmigrationincreases
whencountriesexperiencenegativeeconomicdevelopment(KentorandSanderson,
2009).ThecompletelistofindicatorsisshowninTable1,identifiedbyLFC1…LFC8.
Table1.
Indicatorsusedinthemodelandtheircorrespondingcodinganddatasources.
LOCALFACTORS INTERNATIONALFACTORS
Factor
Localfactorconditions
(LFC)
Source Factor Internationalfactor
conditions(IFC)
Source
LFC1
Shareofworkforce(%
population)
IMF IFC1 Exports.goods/services(%
GDP)
IMF
LFC2
Literacyrate(%olderthan15
yrs.old)
IMF IFC2 Growthinexportsof
goods/services(%)
IMF
LFC3
R&Dexpenditure(%of
GDP)
IMF IFC3 Directforeigninvestment
(Inflows%GDP)
WB
LFC4
Scientific/technicalarticlesin
journals(x100)
IMF IFC4 Directforeigninvestment
(Outflows%GDP)
WB
LFC5
Agriculturalland(%totalland) WB IFC5 Industrialaddedvalue(%
GDP)
IMF
LFC6
Prod.Renewableenergy
(kilowatts)
IMF IFC6 Manufacturingaddedvalue
(growth%)
IMF
LFC7
Totalincomefromnat.
resources(%GDP)
IMF
LFC8
Netrrateofmigrations(%
pop.)
IMF
Localdemandconditions
(LDC)
Internationaldemand
conditions(IDC)
LDC1
PublicspendinginEdu.(%
GDP)
IMF IDC1 Exportsofservices(%
GDP)
IMF
LDC2
Enrollintertiary.Edu.(%pop) IMF IDC2 Growthinexportsof
services(%)
WB
Grossdomesticproductp/c IMF IDC3 Externalbalance(%GDP) WB

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LDC3 (cte.a$2.000)
LDC4
GrowthofGDPpercapita(%) IMF IDC4 Commercialtransactions
(%GDP)
WB
LDC5
Importsofgoods/services(%
GDP)
BM IDC5 Totalreserves(%totalext.
debit)
IMF
LDC6
Annualpop.Growthrate(%) IMF IDC6 Totalunemployed.Rate(%
workingpop.)
IMF
LDC7 RateofgrowthofGDP(%) IMF
LocalRelatedand
supportingindustries
(LRSI)
InternationalRelatedand
supportingindustries
(IRSI)
LRSI1
Internetusers(per100
people)
IMF IRSI1 Airtransportationcargo
(MMofTMKm.)
IMF
LRSI2
Mobilephoneusers(x100) IMF IRSI2 Applicationsforpatentsby
residents(#)
IMF
LRSI3
Trainlines(totalKm.) IMF IRSI3 Qualityofportinfrastructure
(WEF)
WEF
LRSI4
Roaddensity IMF IRSI4 Scientific&technological
articlesinJournals(#)
WB
LRSI5
Secureinternetservers(x
MMpers.)
IMF IRSI5 Incomefromminerals(%
GDP)
IMF
LRSI6
Telephonelines(per100
people)
IMF IRSI6 Incomefromgas(%GDP) IMF
LRSI7
Electricityconsumption
(kilowattspercapita)
BM IRSI7 Containercargobyports
(m.de20feet)
WB
LocalFirm strategy,
structureandrivalry
(LFSSR)
InternationalFirm
strategy,structureand
rivalry(IFSSR)
LFSSR1
Realminimumwage(2000
annualindex)
ECLAC FSSRI1 Companywellknown
abroad(%)
WB
LFSSR2
Averagewage/annual(2000
index)
ECLAC FSSRI2 Companieswithmajority
shareholders(%)
WB
LFSSR3
Businessstartupcosts(%
incomep/c)
DB FSSRI3 Exportvalueindex(2000
base)
WB
LFSSR4
Timeneededtostarta
business(x10days)
DB FSSRI4 Export.Countries/growth
n/region(%total)
WB
LFSSR5
Growthvalueaddedservices
(annual%)
WB FSSRI5 Taxesaveragesfor
products(%)
WB
LFSSR6
Businessesinservices(%
GDP)
WB FSSRI6 PCsandcomponents.
exports(%Serv.exports)
WB
FSSRI7 Exportstodeveloped
countries(%exports)
WB
FSSRI8 Hightechexports(%
exports)
WB
FSSRI9 ConsumerPriceindex WB
3.1.1.2.Internationalfactorconditions(IFC)
Ineconomiescharacterizedbylesseconomicdevelopment,FDI(inbound)propels
nationstoachieverapideconomicdevelopment.FDImeasurestheabilityofcompanies
andgovernmentstoexploittheadvantagestheyprovide(Clarke,2009andPeñaVinces,
2009).LiuandHsu(2009)andPostelnicuandBan(2010)alsorecommendincludingthe
exportofgoodsandservicesasafactorinIFC,asthisreflectstheabilityofindustriesto
commercializeproductswithgreateraddedvalue.Tothisend,thegrowthofannual
exportswasemployedasameasurementparameter.CastroGonzálesetal.(2013)and
PeñaVinces(2009)alsoproposeusingtheaddedvalueprovidedbytheindustriesofa
countryasanindicatorofIFC.Thisindicatorshowstheextenttowhichnational
production(exporting)isacceptedinforeignmarkets,takingintoaccountthatmore
developedmarketshavehigherdemandsthanthoseinLatinAmerica(thecompletelist
ofindicatorsisshowninTable1,identifiedasIFC1toIFC6).
3.1.2.Demandconditions(DC)
3.1.2.1.Localdemandconditions(LDC)
Theeducationlevelofconsumersdeterminesthelevelofsophisticationofthemarket
(LiuandHsu,2009).Therateofenrolmentinsecondaryandtertiaryeducationis
Tableoptions

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consideredasanindicationofthesophisticationofdemand.Duetothefactthattherate
ofenrolmentisrelatedtogovernmentinvestmentinpubliceducation,weusedspending
inpubliceducationandtherateofenrolmentintertiaryeducation.Theannualpercapita
growthofGDPisconsidered,asthisimplicitlyreflectsthespendingpowerofthecitizens
(CastroGonzálesetal.,2013andChiuandLin,2012).TherateofGDPgrowthis
employedasitissynonymouswithproductivity(LiuandHsu,2009,Moonetal.,
1998andPeñaVinces,2009).Thelevelofimportedgoodsandservicesalsoindicates
thelevelofsophisticationofdemand(PeñaVinces,2009),andtherateofpopulation
growthisalsoincludedasitreflectsthegrowthoflocalmarkets(PeñaVinces,
2009andPorter,1990).ThecompletelistisincludedinTable1,identifiedasLDC.
3.1.2.2.Internationaldemandconditions(IDC)
SardyandFetscherin(2009)usetheexportsofgoodsandservicesthatcompanies
producetoindicatetheinternationaldemandconditions.Forthepurposeofthisstudy,we
employedthreeindicatorsthatarecloselyrelatedtothistopic:servicesexports(IDC1),
annualgrowthofservicesexports,andcommercialtransactions.Externalbalance
(IDC3)measuresthelevelofcompetitivenessofcertainmacroeconomicand
microeconomicindicatorsofcountries,asindicatedbyJüppnerandSchneider(2012).
VanRijckeghemandWeder(2001)notethatcountrycompetitivenessisaffectedbythe
totalreservesheldbyacountry,asthisimpliessoundfinancialmanagementofthe
economicsectorsandgovernment.Wethereforeusedthetotalaccumulatedreservesto
reflectthisvariable.Asalastindicator,weusedthetotalunemploymentrate,giventhat
countriescharacterizedbyahighlevelofunemploymenthavediminishedbuyingpower,
whichinturncouldaffectthesupplyofnationalproductioninforeignmarkets(Castro
Gonzálesetal.,2013andClarke,2009).AfulllistofindicatorsisavailableinTable1.
3.1.3.Relatedandsupportingindustries(RSI)
3.1.3.1.Localrelatedandsupportingindustries(LRSI)
Moonetal.(1998)andPostelnicuandBan(2010)indicatethatinformationtechnologies
arerelatedtotheefficiencyandsecurityofthecommercialcommunicationsofacountry.
Basedonthis,wehaveincludedthefollowingasindicatorsofLRSI:a)internetusers,b)
mobilephoneusers,c)numberofsecureinternetservers,andd)accesstolandlines.
Clarke(2009),MoonandLee(2004)andSardyandFetscherin(2009)emphasizethat
transportationinfrastructureisthekeytothegrowthofindustries,sowehavechosento
includethedensityofroadsandtotalnumberoftrainlines.Finally,PostelnicuandBan
(2010)andDögletal.(2012)suggestthatelectricalenergyconsumptionratesshouldbe
contemplatedasawaytomeasurethedegreeofindustrializationofacountry(seethe
listinTable1).
3.1.3.2.Internationalrelatedandsupportingindustries(IRSI)
Foraneffectiveinternationalizationprocess,countriesneedtohaveacomprehensiveair
transportationandmaritimeinfrastructure.Thus,weincludethequalityofseaports
(Clarke,2009,Moonetal.,1998andPeñaVinces,2009).Asameasurementparameter,
weusedmillionsoftonsofairtransportationandcontainertrafficintheports(Castro
Gonzálesetal.,2013).LiuandHsu(2009)takethenumberofresearchstudies
publishedtoindicatethedegreeofinternationalizationoftheacademicandbusiness
sectors,andthuswestudiedthenumbersofpatentssubmittedbyresidentsandarticles
publishedinindexedandtechnicalpublications.
Weshouldalsonotetheinclusionofdatapertainingtotheexportofmineralsandnatural
gasfromLatinAmerica,giventhattheseindustrieslendtheirweighttotheeconomic
growthoftheregion(PeñaVinces,2009)andboostthegrowthofotherservices(banks,
transportation).FollowingtherecommendationsofChiuandLin(2012),weincludedthe
incomefrommineralsandgas.
3.1.4.Firmstrategy,structureandrivalry(FSSR)
3.1.4.1.Localfirmstrategy,structureandrivalry(LFSSR)
Thereasonableminimumsalaryofacountryservesasabasisforeconomic
developmentgiventhatitscitizenshaveaccesstothebasicfamilyshoppingbasket,
whichitselfisthebasisforthegrowthofestablishedcompaniesinstableeconomies(Liu
andHsu,2009andSardyandFetscherin,2009).Anappropriateenvironmentinwhichto
dobusinessbecomesanattractiveelementforcompanieswishingtoestablish

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themselvesthere.FollowingtherecommendationsofChiuandLin(2012),indicators
suchasthetimerequiredtostartabusinessandthenecessarycostsinvolvedwere
used.Itisimportanttonotethatcompaniesrequirethehelpofthirdpartiesinorderto
growandcompeteinforeignmarkets,particularlyservicecompanies(Heizerand
Render,2011),andthereforethegrowthofvalueaddedinservicesandthepercentageof
businessinserviceswereusedasmeasurements(seeTable1).
3.1.4.2.Internationalfirmstrategy,structureandrivalry(IFSSR)
AccordingtoAgosin(2009),thediversificationofacountry’sexportsisoneofthemain
driversofeconomicgrowth.Tothisend,weincludedtheindexvalueofexports,the
nationalproductionexportedtodevelopingcountriesandhighincomecountries,as
indicatorsofIFSSR.Inthesamevein,CastroGonzálesetal.(2013)andPeñaVinces
(2009)suggestthathightechexportsshouldalsobeincludedinthisvariable,asthey
reflecttheexportpotentialofthenationalindustriesandtheabilitytocompetewithother
productsinforeignmarkets.Theseauthorsrecommendincludingexportsrelatedto
communicationssystems,suchascomputersandsoftware,astheysuggestthisreflects
theleveloftechnologicaldependencyofacountry.Thecostsofexportproductprices
werealsoincludedduetothefactthatacountrycharacterizedbyhighexportcostswill
facedifficultieswhencompetingwithproductswithcheaperprices(Sardyand
Fetscherin,2009).RamírezandFlores(2006)purportthat,inLatinAmerica,companies
wherethecontrollingshareholdersareownersachieveagreaterdegreeof
competitivenessincertainindustriesduetotheeasewithwhichtheseentrepreneurs
implantglobalcorporatestrategies.Basedonthis,weusedtheproportionofcompanies
withmajorityshareholding(FSSR2).Finally,theindexesofconsumerprices(FSSR9)
havebeenusedinthisconstruct,astheyareoneofthefactorsinfluencingthe
internationalcompetitivenessofcountries,giventhattheyimprovethecountries’
macroeconomicconditions(PérezandBermúdez,2012).
Table1providesasummaryofalltheindicatorsoftheLatinAmericanDDmodel(LADD).
Thetablecomprisestwosections.Thesectionontheleftreflectsnationalvariables,
whileinternationalvariablesareshownontheright.Thefirstcolumnshowsthecodes
usedinPLSSEM,thesecondthecorrespondingindicatoranditsunit,andthethirdthe
datasource.
Aspreviouslyindicated,theDDmodel(Moonetal.,1995andMoonetal.,1998)served
asatheoreticalbasisfortheconstructionofourLatinAmericanmodelofglobal
competitiveness.Fiftyeightindicators/measurementswerethususedtocalculatetheLA
DDmodel.Thestudycoverstheperiodfrom2000to2010.Inordertocalculatethe
competitivenessranking,theaverageofeachfactorwascalculatedinordertoreflectthe
generaltendencyofeachofthefactorsandeliminateanyunexpectedrandomevents.
ThedatawascompiledfromdifferentdatabasessuchasthoseoftheIMF(International
MonetaryFund),WB(WorldBank),BD(DoingBusiness),andECLAC(Economic
CommissionforLatinAmericaandtheCaribbean).
3.2.AnintroductiontoPLSSEM
Thepartialleastsquaresstructuralequationmodeling(PLSSEM)procedurehasbeen
gaininginterestanduseamongresearchersofmanagementandeconomicsbecauseof
itsabilitytomodellatentconstructsunderconditionsofnonnormalityandsmallto
mediumsamplesizes(Chin,1998;DíazCaseroetal.,2011andPeñaVincesetal.,
2012).Forthisreason,wechosethisparticularstatisticaltechnique.Theuseofthis
techniqueinvolvestwostagesorapproaches:(1)theevaluationofthemeasurement
model;and(2)theassessmentofthestructuralmodel.Hairetal.(2013)recommend
usingPLSSEMwhenthephenomenaunderstudystemfromatheoryexaminedatthe
macrolevelandtherelevantvariablesareunknown.Aswedonotknowtheweightofthe
factors/itemsandtheirrelevanceintheconstructofcompetitiveness,weemployedthe
PLSSEMtechniqueusingthePLSGraph®softwaredevelopedbyChinandFrye(2003).
PLSSEMsuggeststhatalatentconstructsharesmorevariancewithitsindicatorsthan
withitself(Hulland,1999)(seeFig.2),sothatwhenspecifyingthestructuralparameters
andmeasurementoftheconstruct,theprocesscanbedescribedasshowninFig.3.

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Fig.2.
Latentconstruct.
Fig.3.
Latentconstructprocessandcorrespondingparameters.
BasedonFig.3,wecanmathematicallyexpressalatentvariable(construct)as:
Source:AdaptedfromRobertsandThatcher(2009)
3.2.1.ThePLSSEMprocedureanditsresults
InthefirststageofthePLSSEMprocedure,theconstructswereevaluatedtoassess
theirreliabilityandvalidity.Thevalidityofconstruct(VC)measureshighquality
measurementsorindicators.VCconcernsthedegreetowhichascalehasan
appropriatesampleofitemstorepresenttheconstructofinterest—thatis,whetherthe
domainofcontentfortheconstructisadequatelyrepresentedbytheitems(Chin,1998;
Nunnally,1997).Individualitemreliabilitywasassessedbyanalyzingthestandardized
loadings(Hairetal.,2011).Inorderforanitem’smeasurementtobeacceptedaspartof
aconstruct,itmustexceedathresholdof0.40whenthemeasurementscalesareapplied
acrossdifferentcontexts,inourcasetotheLatinAmericancontext(PeñaVincesetal.,
2012).Althoughsomeoftheitemsdonotfitthisrule,wedecidednottoeliminatethemfor
tworeasons.Thefirstisthatwearenotvalidatingscales;onthecontrary,weare
evaluatingtheimportancethatanindicatorhasaspartoftheconstruct.Anotherreasonis
thattheconstructconformstotherestoftherequirementsforaPLSSEM.Theseresults
canbeseeninTable2.Thecommunalityoftheindicatorswasalsoestimated.This
evaluationindicatesthequantitativevalueaddedtotheconstruct.Forexample,a
communalityvalueof(λ2)0.55squaredwouldgiveusavalueof0.3025,meaningthat
only30%ofthevarianceoftheindicatorisrelatedtoitsconstruct(seeTable2).Onthe
otherhand,thereliabilityattributesinaPLSSEMseektoanalyzewhetherthetheoretical
conceptscorrectlymeasuretheconstructviatheobservablevariables(Hairetal.,2013),
inotherwords,assesswhethertheindicatorsreallymeasurewhattheyaremeantto
measure(Nunnally,1978).
Table2.
Resultsofthefactorsofthenationaldiamondandtheinternationaldiamond.
NationalDiamondFactors InternationalDiamondFactors
Variable
Weight
(λ)
Communality
(λ2)
CR Direction Variable Weight
(λ)
Communality
(λ2)
CR Direction
Localfactorc onditions 0.753 Internationalfactorconditions 0.720
LFC1 0.4157 0.1728 (+) IFC1 0.1568 0.0246 (+)
LFC2 0.5487 0.301 (+) IFC2 0.9679 0.9369 (+)
LFC3 0.7187 0.5165 (+) IFC3 0.2923 0.0854 (+)
LFC4 0.822 0.6757 (+) IFC4 0.16 0.0256 (+)
LFC5 0.3609 0.1302 (+) IFC5 0.8647 0.7477 (+)
LFC6 0.5248 0.2754 (+) IFC6 0.4116 0.1694 (+)
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LFC7 0.1277 0.0163 (+) Internationaldemandconditions 0.805
LFC8 0.5944 0.3534 (+) IDC1 0.8089 0.6543
Localdemandconditions 0.790 IDC2 0.5133 0.2635
LDC1 0.2997 0.0898 (+) IDC3 0.4604 0.212 (+)
LDC2 0.7466 0.5573 (+) IDC4 0.8819 0.7777 (+)
LDC3 0.8938 0.799 (+) IDC5 0.2587 0.0669 (+)
LDC4 0.5496 0.3021 (+) IDC6 0.8086 0.6538 (−)
LDC5
0.6047 0.3656 (+) InternationalRelatedand
supportingindustries
0.858
LDC6 0.8376 0.7016 (+) IRSI1 0.8458 0.7153 (+)
LFC7 0.039 0.0015 (+) IRSI2 0.9514 0.9052 (+)
LocalRelatedandsupporting
industries
0.923 IRSI3 0.2246 0.0505 (+)
LRSI1 0.902 0.8136 (+) IRSI4 0.9546 0.9113 (+)
LRSI2 0.7971 0.6354 (+) IRSI5 0.1895 0.0359 (+)
LRSI3 0.4808 0.2312 (+) IRSI6 0.3134 0.0982 (+)
LRSI4 0.5943 0.3533 (+) IRSI7 0.9931 0.9862 (+)
LRSI5
0.9193 0.8452 (+) InternationalFirmstrategy.
structureandrivalry
0.779
LRSI6 0.9452 0.8934 (+) FSSR1 0.243 0.0591 (+)
LRSI7 0.8461 0.7159 (+) FSSR2 0.7622 0.5810 (+)
LocalFirmst rategy.structure
andrivalry
0.804 FSSR3 0.4222 0.1782 (+)
LFSSR1 0.2072 0.0429 (+) FSSR4 0.5049 0.2549 (+)
LFSSR2 0.5826 0.3394 (+) FSSR5 0.0572 0.0033 (−)
LFSSR3 0.5152 0.2654 (−) FSSR6 0.6918 0.4786 (+)
LFSSR4 0.8134 0.6617 (−) FSSR7 0.5649 0.3192 (+)
LFSSR5 0.7774 0.6043 (+) FSSR8 0.6477 0.4195 (+)
LFSSR6 0.8351 0.6974 (+) FSSR9 0.7523 0.5660 (−)
Notes:Toestimatetheconstructreliability(CR),wehaveutilizedanonparametrictechniqueofre
samplingwith500samplesfollowingChin’s(1998)recommendations.Thisisbootstrapping,whichentails
repeatedrandomsamplingwithreplacementfromtheoriginalsampletocreateabootstrapsample(Hairet
al.,2011).
Followingtheanalysis,thenextstepinthisfirststageistheevaluationoftheconstruct
reliability(CR).Nunnally(1978)establishedthataCRoravaluegreaterthan0.70is
requiredintheearlystagesofresearch.Allconstructsforourresearchrecordedvalues
abovethesetlimitof0.70(Table2).Simultaneously,theconvergentvalidity(CV)ofthe
constructwasevaluated.CVisusuallyassessedbytheaveragevarianceextracted
(AVE)(FornellandLarcker,1981).Finally,weevaluatedthediscriminantvalidity(i.e.,the
diagonalinTable3)indicatingtheextenttowhichagivenconstructdiffersfromother
constructs(Henseleretal.,2009).WefollowedFornellandLarcker’s(1981)approach,
whosuggestthattheAVEshouldbegreaterthanthevariancebetweentheconstructand
otherconstructsinthemodel(i.e.,thesquaredcorrelationbetweentwoconstructs).Our
modeldoesn’trecordvaluesbelow0.50ofAVE.Thecompetitivenessdimensionsshow
discriminantvalidity(seeTable3)andconvergentvalidity,asthevaluesofthe
correlationsarelowerforeachconstructthanbetweenthemselves.
Table3.
Thecorrelationmatrixofthenationalandinternationaldiamondfactors.
NationalDiamond
LatentVariable AVE DV (1) (2) (3) (4)
(1)Factorconditions 0.523 0.723 1
(2)Demandconditions 0.549 0.740 0.119 1
(3)Relatedandsupportingindustries 0.641 0.800 0.028 0.450 1
(3)Firmstrategy,structureandrivalry 0.559 0.748 0.432 0.130 0.133 1
InternationalDiamond
LatentVariable AVE DV (1) (2) (3) (4)
(1)Factorconditions 0.500 0.707 1
(2)Demandconditions 0.559 0.741 0.568 1
(3)Relatedandsupportingindustries 0.596 0.772 0.038 0.382 1
(3)Firmstrategy,structureandrivalry 0.540 0.735 0.854 0.351 0.468 1
AVE:AverageVarianceExtracted;DV:Discriminantvalidity.ForDV,diagonalelementsshouldbelarger
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thanoffdiagonalelements.
Notes:ToestimateCR,AVEandDV,wehaveutiliz edanonparametrictechniqueofresamplingwith500
samplesfollowingChin’s(1998)recommendations.Thisisbootstrapping,whichentailsrepeatedrandom
samplingwithreplacementfromtheoriginalsampletocreateabootstrapsample(Hairetal.,2011).
ThesecondphaseofPLSSEMisanassessmentofthestructuralmodel.PLSSEM
evaluatestheindividualpathestimatesorstandardizedregressioncoefficients(β),
analyzestheassessmentofthecoefficientofdetermination(R2)oftheendogenous
constructs(Hairetal.,2011;RoldánandSanchezFranco,2012),andfinallyassesses
thepredictiverelevanceoftheendogenousconstructs(Q2).Hairetal.(2013)suggest
thatthethreepreviousestimationsshouldonlybeappliedwhentestingahypothesis,
whichisnotthecasehere.
Asindicatedpreviously,wefocusourattentionondeterminingtheweight/loadingsofthe
indicatorsofacountryforcompetitiveness.Wearenottestingahypothesis(variable
dependents).Nevertheless,wewouldliketohighlightthatthisispartofaclearlineof
research,sincenoauthorhasyettestedthedirectionalityofthefourfactorsof
competitiveness.
GiventhatPLSSEMisawellknownstatisticaltechniquetowhichmanyinternational
contributionshavebeendevoted(e.g.DíazCaseroetal.,2011,PeñaVincesetal.,
2012andPeñaVincesandUrbano,2014),wewillnotgointoitindepth.Ascanbeseen
inFig.1,ourmodelevaluatescompetitivenessfromasystemicapproach(Choand
Moon,2000andPorter,1990).
TheresultsofthelocalcompetitivenessstudyareshowninTable2.Thesecondcolumn
showsthefactorialweight(λ)foreachofthefactorsusedtocalculatethe
competitivenessdiamonds.Thefactorialweightindicateswhatthefactorcontributesfor
eachofthelatentvariables(determinantsoftheDD).Thethirdcolumnoutlinesthe
correspondingcommunality(λ2)andthefourththereliabilityoftheconstruct(α).Inthe
fifthcolumn,basedoneconomicandinternationalbusinesstheory,wepresentthe
directionofeachvariableconsideredasacomponentofglobalcompetitiveness.
3.3.Evaluationoftheresultsandcompetitivenessranking
ThecompetitivenessrankingsoftheSouthAmericancountries(seeTable5)were
estimatedusingtheweightsofthecommunalities(λ2),whichwereassignedtoeach
factorusingPLSSEMandtheaveragevaluesfortheyears2000to2010.Thecountry
whichoccupiesthefirstpositionhasthehighestlevelofcompetitivenessatbothlocal
andinternationallevels.Therankingfollowsadescendingorder,meaningthatthe
countrywiththeleastcompetitivenessisplacedlast.Theproceduresforcompilingthe
rankingsareasfollows:
Table5.
CompetitivenessrankingofSouthAmericancountries.
LocalCompetitiveIndexesforeachcountry:
Tableoptions
Tableoptions
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whereLCIj=localcompetitivenessindexofacountryj,(j=1,2,….10);LCFi=local
competitivenessoffactorsiofacountryj;λ2LCFi=communalityofthelocalFCiofa
countryj.LDF=localdemandfactorsiofacountryj.λ2LDFi=communalityofthelocal
DCiofacountryj;LRSI=localLRSIiofacountryj;λ2LRSIi=communalityofthelocal
RSIiofacountryj;LFSSRi=localFSSRiofacountryj;λ2LFSSRi=communalityofthe
localFSSRiofacountryj.
Usingthesamecriteria,calculationsweremadefortheinternationalcompetitiveness
indexesofthecountries:
whereICIj=internationalcompetitivenessindexofacountryj,(j=1,2,….10);
ICFi=internationalcompetitivenessoffactorsiofacountryj;λ2ICFi=communalityof
theinternationalFCiofthecountryj.IDFi=internationaldemandfactorsiofacountry
j.λ2IDFi=communalityoftheinternationalDCiofacountryj;IRSIi=localIRSIiofa
countryj;λ2IRSIi=communalityofthelocalRSIiofacountryj;LFSSRi=international
FSSRiofacountryj;λ2LFSSRi=communalityoftheinternationalFSSRiofacountryj.
Thecommunalityhasbeencalculatedusingvariousformulas,asitrepresentstheweight
orimportanceofaparticularfactorindeterminingcompetitiveness.Forexample,the
localcompetitivenessindexhasbeencalculatedforBrazil(LCIBr):
LCIBr = 2.86
Thelocalandinternationalcompetitivenessindexesarecalculatedonthebasisofthe
abovecriteriaandthepreviousformulas.Thecountrywiththehighestlocaland
internationalcompetitivenessvalueisassignedanominalvalueof100,andthe
remainingcountriesarethenbenchmarkedagainstthemostcompetitivecountry.Finally,
thecountriesarelistedindescendingorderagainstthisreferencevalue.Global
competitivenesshasbeencalculatedfollowingtherecommendationsoftheauthorswho
(2)
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•
•
developedthemodel,Moonetal.(1995),asvalidatedbyMoonandLee(2004),Peña
Vinces(2009)andCastroGonzálesetal.(2013),whoviewthedegreeoflocal
competitivenessasequallyimportantastheinternationalcompetitivenessofcountries
(seeTable4).Variousauthors(PeñaVinces,2009andCastroGonzálesetal.,2013)
havenotedthatinternationalcompetitivenesscannotexistwithoutlocalcompetitiveness.
Table4.
ResultsofthelocalandinternationalcompetitivenessindicatorsofLatinAmericancountries.
Competitiveness
Indicators Brazil Colombia Argentina Peru Venezuela Chile Ecuador Bolivia Paraguay
Localcompetitiveness
Factorconditions 1.10 0.46 0.67 0.41 0.43 0.52 0.43 0.44 0.46
Demand
conditions
0.49 0.38 0.66 0.39 0.52 0.55 0.49 0.49 0.49
Relatedand
supporting
industries
0.96 0.71 1.00 0.56 0.74 1.15 0.61 0.38 0.50
Firmstrategy,
structureand
rivalry
0.31 0.39 0.49 0.36 0.23 0.49 0.38 0.09 0.18
Local
Competitiveness
Index
2.86 1.95 2.82 1.72 1.92 2.71 1.92 1.40 1.62
Local
Standardized
Index
100 68.07 98.62 60.04 67.09 94.85 66.91 48.81 56.73
InternationalCompetitiveness
Factorconditions 0.29 0.29 0.34 0.33 0.38 0.40 0.33 0.36 0.27
Demand
conditions
0.02 −0.01 0.01 0.05 0.04 0.08 0.03 0.11 0.11
Relatedand
supporting
industries
184.05 26.41 51.67 11.74 14.68 45.35 7.19 0.48 0.26
Firmstrategy,
structureand
rivalry
0.78 0.45 0.51 0.65 0.45 0.61 0.55 0.57 0.70
International
Comp.Index
185.14 27.14 52.53 12.77 15.55 46.44 8.10 1.52 1.33
International
Standardized
Index
100 14.66 28.37 6.90 8.40 25.08 4.38 0.82 0.72
Global
competitiveness
100 41.37 63.50 33.47 37.75 59.96 35.65 24.81 28.72
BasedonTable4andadheringtothepreviousprocess,asummaryisprovidedofthe
local,internationalandglobalLatinAmericancompetitivenessrankings.Thishasalso
beenrankedfromthemosttotheleastcompetitive.Theresultsofglobalcompetitiveness
areshowninTable5.
AnalyzingtheresultsofTable4,thefollowingcharacteristicsareobserved:
TherearethreeSouthAmericaneconomiesthatstandoutintermsof
competitivenessoverthepasttenyearsanalyzed(Brazil,ArgentinaandChile,in
thatorder).Thismeansthatboththedomesticandinternationaldiamondsare
locatedinthesameorder,soitcouldbearguedthatintheSouthAmericancontext
thesethreecountriesenjoystableandwellpositioneddeterminants,whichreflect
theirglobalcompetitiveness(Table5).
Inthisfirstgroup,Brazilisnotablebecauseitsnationaldiamondshowsadvantages
overArgentina(↑64.2%)andChile(↑111.5%)inthefactorconditions.However,the
factorrelatedandsupportingindustriesshowdisadvantagescomparedtothese
countries(↓Chile84%,Argentina↓96%and96%).Intheinternationaldiamond,
particularlyintherelatedandsupportingindustriesfactor,Brazilisratedhigherthan
ArgentinaandChile,andinaccordancewithquantitativeinformation,thisisbecause
Brazilhas9942publishedscientific/technicalarticlesinjournalsper100,000people,
whileArgentinaonlyhas3220andChile1537.
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•
BasedonTable5,theremainingsevencountrieshaveadifferentorderinthe
rankingsofglobalcompetitiveness(nationalandinternational).Amongthesesix
countries,thecountrythatstandsoutinnationalcompetitivenessisUruguay,
becauseitexceedsitsnearestcompetitor,Colombia,by37.3%[93.47/68.07].
Nevertheless,whentheinternationaldiamondisanalyzed,Colombiaexceeds
Venezuelaby74.4%andistheclosestcountrytoitsinternationalcompetitiveness.
Inadditiontotheoverallcompetitivenessscores(Table4),therearetwosubgroups
ofcountrieswithdistinctpositionsinthenationalandinternationalrankings,dueto
thedynamismoftheireconomiesandstrongfocusonsomeindicators.These
countrieswithunusualbehaviorinbothnationalandinternationalcompetitiveness
canbeseenasevidencethattheuseofPLSSEMcapturesthesedynamicevents.
4.Conclusionsandimplications
Thefirstobjectiveofthisinvestigationwastodeterminetheweights(importance)ofthe
factorscomprisingthelatentvariablesstudied.ThiswasduetothelimitationsoftheDD
modelandthetraditionalmodelsofWEFandIMD.Specifically,thesemodels
proportionallyandarbitrarilyassigntheweightofthefactorsofeachcompetitiveness
determinant.UsingPLSSEM,theseloadswerecalculatedandthecommunalityvalue
(λ2)wasassignedtoeachfactor,thusprovidingasolutiontotheinherentlimitationsof
previousstudies(CastroGonzálesetal.,2013,LiuandHsu,2009,Moonetal.,1995,
Moonetal.,1998,PeñaVinces,2009andSardyandFetscherin,2009).
ThisstudyhighlightsthefactthatcertainfactorsarenotsignificantintheDDmodel,
whichmeansthatsomevariablesdonotaddvaluetothecompetitivenessofcountries
duetotheirminimalloadingweight.Thecriteriathattheauthorsusedtoselectthe
variablesthatdonotaddvaluetotheconstructwerebasedonHairetal.’s(2014)
assertions.Usingthesamelogic,theindicators’commonalityandavalueof0.50or
higherindicatesthat,onaverage,theconstructexplainsmorethanhalfthevarianceofits
indicators.Conversely,acommonalityoflessthan0.50indicatesthat,onaverage,more
errorremainsintheitemsthanthevarianceexplainedbytheindicator.Thisstudyfollows
therecommendationsofChoetal.(2008)toperformstudiesofregionalcompetitiveness
ratherthanplacingallcountriesoftheworldinoneranking,sinceonesizedoesnotfitall
whenanalyzingthecompetitivenessofcountrieswithvariousattributes,asdifferent
countriesrequiredifferentcriteria.Assuch,thisstudybecomesausefultoolforfuture
researchintheLatinAmericanregion.
Amongthevariablesthatdidnotcontributesignificantlytothelocalcompetitiveness,we
found:1)Intermsoffactors,thepercentageofagriculturallandofacountry[LFC5;
λ2=0.1302]andthetotalincomefromnaturalresources[LFC7;λ2=0.0163],which
supportsthehypothesisofPorter(1990),whostatedthatcountriesarenotmademore
competitivethroughtheirendogenousresourcesbutthatwealthiscreatedthroughthe
competitivenessoftheirindustries.2)Asfarasdemandconditionsareconcerned,the
rateofgrowthofGDP[LDC7;λ2=0.0015].Asregardsstrategy,structureandrivalry,a
factorthatdoesnotexertinfluenceoncompetitivenessistherealminimumwage
(FSSR1;λ2=0.0591),asnotedbyFrearetal.(1992).Inthemselves,lowwagesonly
facilitatecomparativeadvantages,andiftheyarenotadministeredcorrectlytheydonot
becomeasourceofcompetitiveadvantage.Therearealsootherindicatorsof
competitivenessthatdonotappearimportant(λ2)intheDDmodel,whichprovidesa
clearlineofinvestigationforfutureresearch(seeTable2).Thesestudiesshouldstriveto
understandwhythesefactorsdonotappeartospureconomicdevelopmentinLatin
America,whentheyhavedonesoinmoreadvancedeconomies.
ThemostrelevantfactorsfordetermininglocalcompetitivenessintermsofFCwerethe
expendituresonR&D(LFC3;λ2=0.5165)andthearticlespublishedinscientificjournals
(LFC4;λ2=0.6757),whichisinlinewiththereviewedliterature(DufourandGingras,
1988,LiuandHsu,2009,Moonetal.,1998,PeñaVinces,2009andCastroGonzáleset
al.,2013).Thisdatashowsthatresearchandscientificpublicationshaveadirecteffectin
improvingacountry’scompetitiveness.InDC,themostimportantfactorsareenrolment
intertiaryeducation(LDC2;λ2=0.5573),GDPpercapita(LDC3;λ2=0.7990)and
annualpopulationgrowth(LDC6;λ2=0.7016),whichisalsoconsistentwiththeliterature
(LiuandHsu,2009andMoonetal.,1995).ForlocalRSI,fivefactorshadvaluesgreater
than0.64,whichhighlightstheimportanceoftheDDmodel.Finally,threefactorsstand
outwhendetermininglocalfirmstrategy,structureandrivalry,namely,thetimeneededto
startabusiness(LFSSR4;λ2=0.6617),thegrowthofvalueaddedinservices(LFSSR5;

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λ2=0.6043)andthepercentageofservicecompanies(LFSSR6;λ2=0.6974).Thisdata
showstherecenttendencyofnationalindustries,whereserviceindustriesplaya
decisiveroleindoingbusinessabroad(HeizerandRender,2011).Thisshouldalsoserve
asawakeupcallforLatinAmericanpolicymakerstoeasebureaucraticredtapeand
allowbusinessestoopenasquicklyaspossible.
Thefindingsofthisresearchalsoidentifiedvariousfactorsthatarenotrelevantto
internationalcompetitiveness:first,inFCtheexportofgoodsandservices(IFC1;
λ2=0.02462),duetotheinconsistenciesshownovertheperiodstudied,andthedirect
foreigninvestment“outflow”(IFC4;λ2=0.0256),owingtothefactthatLatinAmerican
countriesaremainlyrecipientsratherthanexportersofFDI;second,inDCthe
percentageoftotalreserves(IDC5;λ2=0.0669).Third,inRSItwofactorshadlow
values:thequalityoftheportinfrastructure(IRSI3;λ2=0.0505),asthesevaluesdonot
holdanystatisticalinputλ2,probablyduetothelackofrepresentativesurveys(datafrom
theWEF),andincomefromminerals(IRSI5;λ2=0.0359),whichisinlinewiththe
proposalsofPorterandKlaus(2008),whosuggestthatcompetitivenessisnotabout
achievingahighervolumeofexportsandcheaperworkforce,butensuringthat
businessesandpersonnelaremoreproductive.Lastly,inreferencetothestrategic
factor,theaveragetaxappliedtoproducts(FSSR5;λ2=0.0359)isnotimportant.
Ofthe28internationalfactors,wefoundthat22areimportant;however,weshouldnote
thatinFCthegrowthofgoodsandserviceexports(IFC2;λ2=0.9369)isparticularly
relevant.Thisisinlinewiththeclassicaltheoryofeconomicgrowth,wheretheprosperity
ofanationisdirectlyrelatedtothegrowthofitsexportsandthevalueaddedtoindustry
(IFC5;λ2=0.7477),wherebycountriesachievemorecompetitiveadvantageswhen
nationalproductionaddsvalue.Second,indemandconditions,themostimportant
factorsarethegrowthofservicesexported(IDC1;λ2=0.6543),commercialtransactions
(IDC4;λ2=0.7777),andtotalunemployment(IDC6;λ2=0.6538),whichsupportsthe
conceptsofthetheoriesofeconomicgrowthandcountrydevelopment(Krugman,1994).
Inrelatedandsupportingindustries,threefactorsstandout:freightcargo(IRSI1;
λ2=0.7153),patentssubmittedbyresidents(IRSI2;λ2=0.9052)andseacontainers
(IRSI7;λ2=0.9862),whichallreflectthequalityandquantityofacountry’sexportsand
innovations,asstatedbyLiuandHsu(2009)andCastroGonzálesetal.(2013).Lastly,in
internationalFSSR,weidentifiedtwoimportantfactors;theconsumerpriceindex
(FSSR9;λ2=0.5660)andlocalshareholding(FSSR2;λ2=0.5810).
Intermsofglobalcompetitiveness(Table5),ourresultsshowthatBrazilisthemost
competitivecountryintheLatinAmericanregion.ItisfollowedbyArgentina,Chile,
UruguayandColombia.Thesefiveeconomiesthushavethebestcompetitive
advantagescomparedtotheremainingLatinAmericancountries.WithregardtoFDI,the
aforementionedcountriescouldbethefirsttobechosenbyforeigninvestors.The
countrieslaggingbehindintermsofcompetitiveness,namelyVenezuela,Ecuador,Peru,
ParaguayandBolivia,shouldstrivetoimprovethedeterminingfactorsthatcouldboost
theirinternationaleconomicdevelopment.Specifically,theyshouldincreasespendingon
R&D,increasethenumberofarticlesinindexedpublications,improvetheinfrastructure
relatedtoinformationandcommunicationstechnology(ITC),andencouragethecreation
ofservicecompanies.
Theanalyzeddatahasenabledustoidentifythreedistinctcompetitivelevels(high
mediumlow)intheLatinAmericanregion.Thecountriescharacterizedbyahighlevelof
competitivenessareBrazil(100),boastingaclearadvantageoverthesecondplaced
Argentina(63.50),whichisfollowedbyChileandUruguay,whosescoresare59.96and
48.19,respectively.ThecountrieswithmediumcompetitivelevelsareColombia(41.37),
Venezuela(37.75),Ecuador(36.65)andPeru(33.47),whosescoresindicatethattheir
competitiveindicatorsareclosetooneanother,andwhocompeteamongstthemselves
toattractforeigncapitalandtechnology,asnotedbyFeinberg(2008).Paraguay(28.72)
andBolivia(24.81)comprisethegroupofcountrieswithlowcompetitivelevels.
Regardinglocalcompetitiveness,Brazilisthebestplacedcountry,followedby
Argentina,Chile,UruguayandColombia,whilstVenezuela,Ecuador,Peru,Paraguay
andBoliviafollowinsuccession.WhileitistruethatBrazilandArgentinaboastlarge
quantitiesofendogenousresources,theydonothavesignificantnaturalresourcessuch
asminerals,gas,petrol,etc.,whichotherlesswellplacedcountriessuchasVenezuela,
Peru,EcuadorandBolivia,whicharecategorizedastraditionalminingcountries,have.
TheseresultssupporttheideasofPorter(1990),insofarascompetitivenessisnotonly
relatedtotheresourcesofacountrybutalsorequiresthecompaniesbasedtheretobe

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moreinnovative.
OuranalysisofinternationalcompetitivenessrevealsthatBrazilhasasuperior
competitiveadvantageovertheothercountriesincludedinthestudy.Theseadvantages
areduetofactorssuchasthecapacityandqualityofitsairtransportation,thenumberof
patentsdeveloped,thenumberofscientificandtechnologicalarticles,lowtechnological
dependency,astableconsumerpriceindex,andexportsproducednationallywithhigh
addedvalue.Somecountries,suchasArgentinaorChileandtoalesserextent
Colombia,showsignsoffollowingBrazil,althoughthedatashowstheystillhavesome
waytogo.Withthisinmind,oneappreciatestheneedtoevaluatecountriesusingboth
localandinternationalindicatorsinordertoobtainanoverallviewoftheir
competitiveness(Moonetal.,1995andMoonetal.,1998).
Giventhatthedatausedinthisresearchistheaveragefigurefortheelevenyears
coveredandthatthetechniquesemployedaremoresophisticatedthanthoseofthe
traditionalWEFandIMDmodels,wewouldexpectourresultstodifferslightlyfromthose
oftheseinstitutions,whichbasetheirfindingsondatafromthepreviousyear.According
tothe“GlobalCompetitivenessReport20112012”(theresultsofwhicharebasedon
datafrom2010),thefivemostcompetitiveeconomiesinSouthAmericaareChile,Brazil,
Uruguay,PeruandColombia,whereasourfindingsproducethefollowingresults:Brazil,
Argentina,Chile,UruguayandColombia.OurinvestigationidentifiesArgentinaasthe
secondmostcompetitivecountry,whilePerudoesn’tfigureinthetopfive.Themain
reasonforthisisthatwhenapplyingourmodel,Argentinahasacompetitiveadvantage
overChileandtheotherremainingcountries(seeTable5).Infact,intermsof
internationalcompetitiveness,ArgentinaissuperiortoPeruby31points,particularlyin
referencetotheinternationalrelatedfactorandsupportingindustries,whicharerelated
toR&D,indexedpublications,etc.,whilePeruhasseriousshortcomingsintheseareas.
AccordingtoWEF,theleastcompetitivecountriesareBoliviaandParaguay.Thesetwo
countriesalsofigureastheleastcompetitiveinourmodel,althoughtheorderisreversed.
Thisstudyisnotwithoutitslimitations.Duetolackofspace,wewereunabletocarryout
amoreindepthanalysisandcomparethevariousindexesforallcountries,whichneeds
tobeaddressedinfutureresearch.Weusedtheaveragesofdatarelatingtotheperiod
2000to2010.InordertovalidatetheDDmodel,futureresearchshouldusetheaverages
forshorterperiods,forexamplethreeyears,andapplythemovingaveragemethodto
contrastthedatawithotherglobalcompetitivenessrankingssuchasWEForIMD.
Finally,themethodologyusedinthisresearchshouldbereplicatedwithothereconomies
ofCentralAmericaandtheCaribbean,aswellasotherworldregions.Similarly,anatural
progressionofthisworkwouldbetoanalyzeinternationalcompetitivenessfromamulti
levelfactorapproach(regionwide,sector,andcountry,countrysectorspecificand
idiosyncraticcomponents)todeterminewhethersimilarresultsareobtained,giventhat
weneedtocontinuetolearnmoreaboutthedifferentaspectsofLatinAmerican
economiesduetothelackofempiricalstudiesfromthesecountries.Becausethe
indicatorsusedinmeasuringthecompetitivenessofcountriesreflectedadifferentlevel
ofimportanceinthecommonalitiesassignedtotheregionandthelevelofdevelopment
amongthecountries,replicatingthismodelforotherregionssuchasAfricaorAsiaisa
taskforthefuture.Itwouldalsobeinterestingtoevaluatethefourfactorsdetermining
competitivenessasconditioningit,whichimpliesthecreationoftheconstructof
competitivenessasadependentvariable,sinceourresearchhasinvestigated
competitivenessfromasystemicpointofview.
Anissuethatwehavenotaddressedinthisstudyisthefactthatthereareother
indicatorsthatalsohaveanimpactonthecountrycompetitivenessofLatinAmerican
economies,whichshouldbetakenintoaccountwhencompetitivenessisstudied.
Likewise,wemustmentionsomedifficultiesthatcouldoperateasindicatorsinamodelof
competitiveness.Ofthefactorswhichmighthaveanimpactwewouldliketocite,for
example,theterrorismthatpersistsinColombiaandmakesforeigndirectinvestors
chooseotherlocations.However,Colombiaisnotauniquecase;therearealso
remnantsofterrorisminPeru.Ontheotherhand,highlevelsofmetropolitan
delinquencies,suchasrobberiesinmunicipalareas,aregeneralizableforallLatin
Americancountries,includingBrazil.Theseissueshinderthegrowthofthetourism
industry.
AccordingtoWorldBank(2015)statistics,onlyaround15%ofthetotalexportsofthelast
decadewerehightechnologyexports,confirmingthatmostLatinAmericanexportsare
basedontraditionalproductsthatareintensiveinlaborandagriculturalresources.

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Agosin,2009
BarragánandUsher,2009
Cartwright,1993
CastroGonzálesetal.,2013
CastroGonzálesetal.,2015
Cerdaetal.,2008
Clarke,2009
ChiuandLin,2012
Chin,1998
ChinandFrye,2003
ChoandMoon,2000
MoonandKim,2009
Anothermorevisiblefactorthatconstrainsthecountries’competitivenessbutisdifficult
toestimateinvolvestheexistenceofcorruptionwithinpublicinstitutionsinLatinAmerica.
Thisproblemresultsinalimitationofdoingbusiness,becausebehindtheinstitutions,
therearepeoplewhooftendonotworkifcompaniesdonotgivethemaneconomic
incentiveorgift.
5.Uncitedreferences
MoonandKim(2009),DoingBusiness(2013),ECLAC(2013),IFM(2013),andWEF
(2015).
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1/6/2016 ThecompetitivenessofLatinAmericaneconomies:Consolidationofthedoublediamondtheory
http://www.sciencedirect.com/science/article/pii/S0939362516300413 42/43

1/6/2016 ThecompetitivenessofLatinAmericaneconomies:Consolidationofthedoublediamondtheory
http://www.sciencedirect.com/science/article/pii/S0939362516300413 43/43