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OXFORD
EC0N0MICS
TECHNOLOGY
SPENDING:
DRIVINGGROWTHANDRESILIENCETHROUGHECONOMICDOWNTURNS
inassociationwith
SEPTEMBER2024
OXFORD
ECON0MICS
Tableofcontents
CONTENTS
EXECUTIVESUMMARY 4
Survivingandthrivinginthenextdownturn:
Therighttechnologyinvestmentspayoff 4
Keyfindings 5
SECTION1:Introduction 7
Box1:Auniquetechnologyspendingdataset 9
SECTION2:Evolutionoftechspend 10
TechspendhasoutpacedGDPandotherinvestments 11
Innovativedisruptionhasfavoredcertaintypesoftech
spendmorethanothers 12
SECTION3:Techspendasadriverofbusinessoutcomes 14
Morethanjustastrongcorrelationbetweentechspend
andrevenuegrowthinnormaltimesandduringdownturns 15
Techspendhasbeenimportantforresilienceandrecovery 15
Box2:Reviewofthedynamicpanelmodelusedinthisstudy 16
Datadeep-diverevealsfourkeytakeawaysfor
decisionmakers 18
SECTION4:Conclusion 22
SECTION5:Areasforfurtherinvestigation 24
Appendix1:Techspendduringrecessions 28
Appendix2:Industry-specificanalysis 31
Appendix3:Aboutoureconometricanalysis 37
ABOUTOXFORDECONOMICS 38
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ECON0MICS
EXECUTIVESUMMARY
SURVIVINGANDTHRIVINGINTHENEXTDOWNTURN:
THERIGHTTECHNOLOGYINVESTMENTSPAYOFF
Howorganizationsinvestintechnologyduringeconomicdownturnscanbeastrongindicatoroftheirperformanceduringhardtimesandtherecoveriesthatfollow.
Conventionalwisdomholdsthatcostcuttingisanessentialwaytosurvivearecession,andwhilethatmayholdtrueinsomeareas,newresearchfromEYandOxfordEconomicsshowsthat
strategicinvestmentsintechnologyduringa
downturnmaybetheleadingstrategyfor
survivingarecession—andthrivinginarecovery.
Thatdoesnotmeanorganizationsshouldblindlythrowmoneyattechnology—asmanycompanieslearnedduringtheCovid-19era,itispossibletooverspendevenwhenrealopportunitiesexist.
Muchofthefrenziedbuyingduringtheearly
2020sresultedinaglutoftechnologyassets
thatbroughtcostlycomplexitytocomputing
environmentsandcreatedatechhangover
thathashadanegativeeffectonatleastshort-termspending.
Nordoesspendingthrougharecessionmeanthatthereisasinglecorrectwaytoapproach
technologyinvestmentswhentheeconomy
goessouth.Onekeytoasuccessfulstrategyisunderstandingthenatureofthesituation—notalldownturnsarecreatedequal.Overthelastthreedecades,eacheconomiccrisishashadunique
causesandeffects,anddisparateimpacts,onparticularindustries.Thereisnoone-size-fits-allmodelfortechnologyspending.
WhenEYandOxfordEconomicsteamedupforthisresearch,wefoundlittleempiricalevidenceoftechnologyinvestmentstrategiesduring
downturnsthatcouldenablerobustguidancetocorporatedecisionmakers.Muchoftheexistinganalysisfocusesinsteadonindividualbusinesscasesorspecificproducts.
Againstthisbackground,EYandOxford
Economicscompiledasignificantnewdatasetoftechnologyspendingfrompubliclyavailableindustrydatatoextractkeylessonsfor
investmentstrategiesacrossabroadspectrum
ofindustriesandproductcategoriesinadvancedeconomies,usingeconometricanalysiscombinedwithinsightsfromacademicliteratureand
businessleaders.
Onekeytoasuccessfulstrategyis
understandingthenatureofthesituation
—notalldownturnsarecreatedequal.
Impactonrevenuegrowth
(percentagepoints,2yravg)
KEYFINDINGS
Ourresearchshowsthat,inbroadterms,industries
thatspendwiselyontechnologythrougheconomic
downturnsemergestrongerandmorecompetitive
whileavoidingtheworstofthetechnologyhypecycle.
Amongthecoremessages:
Recentanalysisofmacrotrendsconfirmsthe
increasingsignificanceoftechnologyspendinginalleconomicsectors.Thisisevidencedby
businessescommittinganincreasingshareof
revenuestotechspendovertime.Thesurgeis
morepronouncedinservicesindustries,where
increasedtechspendhasbecomeacrucialdriverofeconomicactivity.Comparedtoproducing
industries,servicesectorsarewitnessingamore
substantialproductivityboostfromtechnologicaladvancements.Importantly,newerstudiestendtofindahigherimportanceofsoftwareandcloud-
relatedproducts(preferredbyservicesindustries),whileolderstudiestendtofindabiggerimpact
ofhardwareandcommunicationstechnologies.
Techspendingcansupportrevenueresilience
duringadownturn.Onaverage,revenuesshrankby3.5percentagepointslessinindustriesenteringthe2008globalfinancialcrisis(GFC)inthetop
quartileintermsofrelativetechspend.AndduringCovid-19,industriesinthemiddleofthepack
averagedrevenuelosses8pptslargerthanthoseatthetopoftechspending.Notably,regressionresultssuggestthatshiftsinthecompositionoftechspendplayanimportantroleindownturn
resilience.Inthenearterm,reducingthelevelofoperationalexpenditures(opex)relativetorevenueshasbeenconsiderablyharmfulto
revenuegrowthduringdownturns,suggestingthatthiscouldbeasub-optimalstrategyfor
protectingprofitabilityintimesofcrisis.By
contrast,changesintechcapitalexpenditures
(capex)hadlimitedimpactsongrowth,flaggingthatmanyindustriesmayhaveoverspentduringtheGFCandCovid-19crisis.
Chart1:Two-yearavg.annualgrowthgapinindustrieswith1pptlowertechopexspendasashareofrevenues
0
-0.1
-0.2
-0.3
-0.4
COVID
downturns
Baseimpact
Additionalrecessionspeci?cimpactSource:OxfordEconomics’estimates
Thebarsinthechartillustratethe
estimatedgapsinrevenuegrowth
betweenindustrieswithdifferentlevelsoftechopexacrosstheentiresampleandduringdownturns.
Thegraybarsshowthegapovertheentiresample,andtheredbarsshowhowmuchbiggerthegapbecomesduringadownturn.Theseregressioncoefficientsessentiallyquantify
averageoutcomedifferencesacrossindustriesandcountries.Technologyexpendituresarenormalizedand
analyzedasashareofrevenues.
Toaccountforsector-specific
performance,thesefigureswere
estimatedusingOxfordEconomics’dynamicpanelmodeleconometricframeworkdiscussedinBox2andinthetechnicalappendix.
5
Last3
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OXFORD
ECON0MICS
Techspendingfuelsrecovery.Investment
intechbeforeandduringadownturncan
domorethanjustkeepbusinessesafloat;it
cancarrythemthroughandhastenrecovery.Excludingheavymanufacturersandpublic
services,averagepost-downturnrevenue
growthwithinaparentsectorwasbetween
1.2and3.8pptshigherinindustriesthat
maintainedarelativelyhighleveloftech
spendduringtheGFCrecession.1Onaverage,industriesthatgointodownturnswithlarger
sharesoftechspendalsoappeartobebetterplacedtoseizegrowthopportunitiesaftera
recession.Ourregressionresultsalsopoint
toaconsistentleveloftechopex(pre-and
duringadownturn)askeyfactorsforpost-
downturncompetitiveness.Bycontrast,capitalexpenditures(capex)intechwerenotfound
tohaveanimmediateimpactonresilience,butinsomeindustriestherewereindicationstheycouldbeimportantdriversofgrowth24-36
monthsahead,especiallyafterrecessions.
Knowyourdownturn,andtargettechnologybasedonspecificneeds.Differentlessons
applyindifferenttypesofdownturns,
whetheratechstockmarketcrash,aglobalfinancialcrisis,orpandemic-drivenshutdownoftheworldeconomy.Althoughspending
throughadownturnmaybecomethenew
normal,thatdoesnottranslateintothrowingmoneyattechnology.Understandingthe
macroeconomiccontext,includingpoliticalandsocio-culturaltrendsaswellasthe
sourceoftheshock,iscriticaltomaking
therightinvestmentdecisions.Afinancialcrisisthatreducescreditavailabilityimpliesadifferentsetoftechnologicalinvestmentsthanapandemicthatcausespeopleto
stayhomeandsociallydistance.Further,thosesameshocksimplyadifferentsetofinvestmentsforcompaniesoperatingindifferentsectors.
Afinancialcrisisthatreduces creditavailabilityimpliesadifferentsetoftechnologicalinvestmentsthanapandemic thatcausespeopletostayhomeandsociallydistance.
1Forcomparisonpurposes,thegranularindustriescoveredinthisstudyaregroupedintosixparentsectors:privateservices,publicservices,retailandwholesaletrade,transportationandstorage,heavymanufacturing,andlightmanufacturing.
SECTION1:
INTRODUCTION
7
OXFORD
ECON0MICS
Section1:Introduction
INTRODUCTION
Althoughthereisawealthofresearchdemonstratingthepositiveandsignificanteffectsoftechnologyinvestmentsonproductivityandrevenuegrowth,2,3,4a
relativelycommonstrategyencouragescompaniestoreducetheirspendingontechnologytoprotectprofitabilityduringeconomicdownturns.
AsshowninChart2,thisisthemainreasonbusinessspendingontechhasexhibitedacyclicalpatternoverthepast25years,withsignificantfluctuationsingrowth.Thereisalsoevidenceofscarring,orlong-term
damage,totechnologyspendingfollowingeconomicdownturns.
Theanalyticalworkpresentedinthispaper
revealsthatthisapproachhasbeenshortsightedandhasultimatelyharmedlong-termbusiness
success.Industriesacrossdifferentcountries
haveexhibitedvaryingresponsestoeconomic
downturns,andourempiricalstudydemonstratesthesignificantimpactofthesedifferenceson
revenuegrowth.Inparticular,thegranularity
ofouruniquetechnologyspendingdataset
(describedinBox1)allowedustouncoveruniqueinsightsabouttechspendanditscomposition
onresilience,post-downturncompetitiveness,andinnovation.
Forexample,ourdatasetrevealsthat,onaverage,companiesingoods-producingindustrieshave
cuttheirtechnologyspendingthreetimes
morethanthoseinserviceindustriesduring
challengingeconomictimes.Aftercontrolling
forsector-specificperformanceconstraints,oureconometricresultsshowthatthishastypically
contributedtolowerrevenuegrowthduringthelastthreeglobalrecessionsandinsomeinstanceshasalsoconstrainedpost-recoveryperformance.
Chart2:Globaltechspendgrowth
%growth,constantprices
12
6
0
-6
-12
199820002002200420062008201020122014201620182020
Source:OxfordEconomics’estimates
2Stiroh,K(2005).ReassessingtheImpactofITintheProductionFunction:AMeta-AnalysisandSensitivityTests.Annalesd’économieetdeStatistiqueNo.79/80,pp.529-561.Availableat
/10.2307/20777587
3Spiezia,V(2012).ICTinvestmentsandproductivity:MeasuringthecontributionofICTStogrowth.OECDJournalofEconomicStudies,Vol.2012/1.Availableat
/10.1787/eco
_studies-2012-5k8xdhj4tv0t
8
4OECD(2015).TheImpactofR&DInvestmentonEconomicPerformance:AReviewoftheEconometricEvidence.OECDDirectorateforScience,TechnologyandInnovation.Availableat
/document/DSTI/EAS/STP/NESTI
(2015)8/en/pdf
Section1:Introduction
Howtechnologyinvestments
enablegrowthandcompetitiveness
Twokeyfactorshelpexplainthestrong
relationshipbetweentechnologyspendingandgrowth.
Technologyisadriverofinnovationandcompetitivenessinthemodernglobaleconomy:
Companiesthatinvestintechnologyare
morecapableofadaptingtochanging
marketconditions,enhancingtheirproductsandservices,securingmarketaccess,andstayingaheadoftheircompetition.
Reducingtechnologyspendingduringa
downturncanimpedeacompany’sability
toinnovateandcompete,ultimatelyresultingindecreasedprofitability.
Technologyhelpsmaintainandimproveoperationalefficiency:
Byinvestinginnewtechnologies,companiescanoptimizetheirprocesses,lowercosts,
andincreaseproductivity.
Reducingtechnologyspendingduringa
downturncanconsequentlyleadtodecreasedoperationalefficiency,resultinginhigher
costsandlowerprofitabilityovertime.
Ofcourse,itispossibletooverspendon
technology.Companiesmuststrikea
balancebetweeninvestingenoughtoremaincompetitiveandinnovative,whileavoiding
certaintypesoftechnologythatmaynot
provideasufficientreturnoninvestment.Itiscrucialforbusinessleaderstocarefullyassessthecompositionoftheirtechnologyspendingagainstrelevantindustrybenchmarks.Overall,lessonsfromourstudyareintendedtoserve
asaguidelineforexecutivestofindtheoptimalcourseofactiongivencompanycharacteristicsandwheretheyareinthebusinesscycle.
BOX1:AUNIQUETECHNOLOGYSPENDINGDATASET
ThisstudyisbasedonanoriginaldatasetoftechnologyspendingputtogetherbyOxfordEconomicsin2023toprovidevaluableinsightsintotheimpactofdifferenttypesoftechnologyinvestmentsoncompanyrevenuesand
resilienceduringeconomicslowdownsanddownturns.
Agloballyconsistent,industry-leveldatasetfora
sufficientlylargenumberofcountriesisessentialfor
hypothesistestingtodeductrobustclaimsregardingtheassociationoftechnologyspendingwithperformance.
Thedatasetincludesinformationfrom11countriesandupto35industriespercountry,spanningfrom1995to2021.
Fivecoreenterprisetechnologyitemsareconsideredalongwithtwoadditionaldriversofenterprise
value,whichweconsiderpartofthebroader
“techspend”umbrella.Thesearethefollowing:
Devices:Electronics,computers,communicationequipment
Enterprisesoftware:“Pre-packaged”software
ITservices:Customand“own-account”softwareandrelatedservices
Internetandcloudservices:Dataprocessing,internetportals,searchengines
Communicationservices:Wired,wireless,satellite
ResearchandDevelopment(R&D):Innovativeactivitiestogeneratenewproducts
Brandmanagement:Advertising,media,andpublicrelationsystems,artisticoriginals
Foreach,twoadditionalbreakoutsareincluded:
Capex(capitalexpenditure):Long-termexpenditurerelatedtoplansforfuturegrowthandefficiency,
thatarepurchasedforalifespanlongerthanoneyear(e.g.,purchasesofITequipment,enterprisesoftwarerequiredtorunproductionfacilities)
Opex(operatingexpenses):Day-to-dayexpenditurerelatedtoeachindustry’sproductionrequirementsthatarepurchasedforuseinmakingtheindustry’s
product(e.g.,annualsoftwaresubscription,semiconductorsinstalledincars)
Thedataiscompiledfrompubliclyavailablesources,primarilyfromorganizationssuchastheOECD,theUSBureauofEconomicAnalysis,andtheAustralianBureauofStatistics.
9
SECTION2:
EVOLUTIONOFTECHSPEND
10
11
Section2:Evolutionoftechspend
OXFORD
ECON0MICS
Abroadreviewofexistingliteratureandabrieflookatourtechnology
spendingdatasetshowshowtechspendhasevolvedoverthepast25years,withparticularfocusoneconomicdownturns.
KEYFINDINGSANDTAKEAWAYS
Datareflectsthattechspendhasbecomeevermoreimportantacrossallsectorsoftheeconomy,outpacingrevenuegrowthovertime—especiallyforcapex.
Therisehasbeenparticularlynotableforserviceindustries,whichmayseealargerproductivitybenefitfromtechcomparedtoproducingindustries.
Techspendhasrespondeddifferentlyduringdifferentdownturns.Afteraconsiderabletechhangoverintheearly2000s,thebeliefthattechboostsproductivityandprofitabilityhas
drivenstrategyevenduringdownturns,withaspendingpeakduringtheCovid-19pandemic.
TECHSPENDHASOUTPACEDGDPANDOTHERINVESTMENTS
Thedigitalrevolutionhassupporteda
considerableriseoftechnology-related
expenditureoverthepast25years,outpacing
bothtotalinvestmentandGDP(Chart3)—hinting
Chart3:WorldGDPandinvestment
attherisingimportancebusinessesassigntotechspendingasacatalystforgrowth.Therisehas
beenparticularlynotableforserviceindustries,whichmayseealargerproductivitybenefit
Index(1997=100),in?ationadjusted
300
200
100
GDP
TotalInvestmentTechspend
0
199720002003200620092012201520182021
Source:OxfordEconomics’estimates
12
OXFORD
ECON0MICS
Section2:Evolutionoftechspend
fromtechcomparedtoproducingindustries
(Chart4)—therelativeshareoftechspendasa
percentageofrevenueswentfrom6%before
2000toover9%afterthepandemic.
Chart4:Techspend(percentofrevenues)
%%%
%%%
HeavymanufacturingLightmanufacturing
4
3
6
4
2
1
0
2
0
20002005201020152020
20002005201020152020
PrivateservicesPublicservices
12
4
8
2
4
0
0
2000200520102015202020002005201020152020
TradesTransportationandstorage
4
3
2
2
1
0
0
2000200520102015202020002005201020152020
Source:OxfordEconomics’estimates
INNOVATIVEDISRUPTIONHASFAVOREDCERTAINTYPESOFTECHSPENDMORETHANOTHERS
Theshareofrevenuesthatindustriesspendon
enterprisesoftwarehasgrownsix-foldsince1997,reachingaglobalaverageof0.6%in2021.This
reflectstheincreasingrelianceofbusinessesonsoftwaresolutionstoenhancetheirproductivity,innovation,andcompetitiveness.However,
softwareisnottheonlycategorythathasseen
asignificantincreaseinspending.Internetand
cloudservices,whichincludedatastorage,
processing,andanalytics,havealsogrown
rapidly,especiallyinthelastfewyears.Infact,theshareofrevenuesspentoninternetandcloud
serviceshasalmosttripledsincetheGFC,andisnowclosetomatchingsoftwarespending(seeChart5).Bycontrast,communicationserviceshaveexperiencedasteadydecline.Theshift
towardmobiledevicesandtheincreaseduseof
cloud-basedservices(e.g.,VoIP)havelikelyhurtcommunicationservices;however,asweexploreinthisstudy,communicationservicesarestillanimportantdriverofrevenuegrowth.
Whatexplainsthisshiftintechnologyspending?Oneofthekeyfactorsistherisingimportance
ofintangibleassets,suchasdataandcomputerservers,inbusinessoperations.Theseassets
enablebusinessestoleveragethepowerof
cloudcomputing,artificialintelligence,and
otheremergingtechnologiestocreatevalueandgaincompetitiveadvantage.Oureconometric
analysis,whichisavailableintheappendixof
ourreport,providesempiricalevidenceforthisrelationship.However,thedataweuseinour
studydoesnotfullycapturethecomplexityand
13
Section2:Evolutionoftechspend
OXFORD
ECON0MICS
dynamismofthetechnologylandscapebecausestandardindustryclassificationsarebasedon
historicaldefinitionsusedbystatisticalagenciesandmaynotreflectthecurrentandfuture
realitiesoftechnologyusage.Forexample,cloudservicesarearelativelynewphenomenonthat
spanacrossmultiplecategories,suchassoftware,
ITservices,andinternetservices.Assuch,they
maynotbeadequatelyrepresentedbyanysinglecategoryinourdata.Therefore,werecommendthatmoregranularandtimelydatasourcesbe
developedandusedtobetterunderstandthestrategicimplicationsofshiftingfromonetypeoftechnologytoanother.
Chart5:Globaltechspendevolutionbytype(percentofrevenues)
SoftwareDevicesR&DCommunicationservices
6.01.50.75
%
4.0
2.0
0.0
%
1.0
0.5
1.0
0.50
0.25
0.00
%
%
0.5
0.0
0.0
200020102020200020102020200020102020200020102020
ITservicesInternet&cloudAdvertising
Source:OxfordEconomics’estimates
%
1.5
1.0
0.5
%
0.4
%
0.80.60.4
0.2
0.0
200020102020
0.30.2
0.1
0.0200020102020
0.0200020102020
Howrecessionsshapedtechspend
Asmightbeexpected,thenatureofthedownturnaffectedtechspend—bothinthevolumeofspendandthetypesoftechnologytargeted.
Duringthedotcomcrisis,ITwasviewed
withskepticismbyexecutiveswhocut
theirtechnologybudgetstosurvivethe
downturn.Techspendingenteredaperiodofausterity.However,by2008,executivesbegantorealizethattechnologywasno
longera“nicetohave”butanecessity.
Thetypesoftechspendcutshavealso
variedsignificantlyaftereachofthepast
tworecessions.Forexample,globaldevices
spendtookahitduringtheGFCbut
wereboostedduringtheCovidpandemic,whichalsosawariseininvestments
indigitalinfrastructure.
Ingeneral,industrieshavemovedawayfromoperationalexpenditure(opex)software
spendduringeverydownturn.Instead,theyhavetakenadvantageofthesituationto
investinmorelong-termsolutions,suchassoftwarecapitalexpenditure(capex).
Formoredetailsonspendingduringvariouseconomicdownturns,seeAppendix1.
SECTION3:
TECHSPENDASADRIVEROFBUSINESSOUTCOMES
14
Section3:Techspendasadriverofbusinessoutcomes
OXFORD
ECON0MICS
KEYFINDINGSANDTAKEAWAYS
Fromcorrelationanalysis,wefindthatsectorsthatspendheavilyontechappearto
experiencegreatergrowth,especiallyinthelongterm.Keepingtechspendaconsistentlyhighshareofthetotalthusseemscrucialforsuccessaswellasresilience.
DuringCovid-19,industriesinthemiddleofthepackaveragedmuchlargerrevenuelossescomparedtothoseatthetop.
Weverifytheseobservationsviaeconometricanalysisusingadynamicpanelmodelandcontrollingfortheinfluenceofothersourcesofrevenue.
Wefindthatmaintainingorevenraisingopexisparticularlyimportantforsupporting
revenuegrowthindownturns.Thelargestandmostsignificantimpactisfoundforthe
Covid-19downturn.
OurestimatessuggestthatmanyindustriesinmanufacturingandthepublicandprivateservicessectorsunderspentintechopexduringtheGFCdownturnandoverspentin
techcapexduringtheCovid-19pandemic.
MORETHANJUSTASTRONGCORRELATIONBETWEENTECHSPEND
ANDREVENUEGROWTHINNORMALTIMESANDDURINGDOWNTURNS
Ouranalysisrevealsanuanced,multifaceted
connectionbetweentechnologyadoption
andrevenuegrowthacrossdifferentindustries.Whileapositivecorrelationisevident(asshowninChart6),oureconometricanalysisuncoversadeeperdynamic(seemainresultssection
fordetails).Weobserveavirtuouscyclewhere
acceleratedrevenuegrowthfuelstechnologyinvestment,whichinturnamplifiesbusinessperformance.Thiseffectisparticularlystrongwhencomparingcompanieswithinthesameindustrygroup,especiallythosededicating
alargershareofcoststotechnology.
Chart6:Techspendasadriverofrevenuegrowth5
Avgrevenuegrowth(1997-2021),
in?ationadjusted(%)
5
4
3
2
1
0
Techmaturity
HighLow
Heavy
manufacturing
Light
manufacturing
Privateservices
Publicservices
TradesTransportationandstorage
Source:OxfordEconomics’estimates
5Hightechmaturityincludesindustry-countryobservationswithanabovemedianlevelofteachspendrelativetorevenues.15
BOX2:AREVIEWOFTHEDYNAMIC
PANELMODELUSEDINTHISSTUDY
Adynamicpanelmodel(DPM)isatypeofregressionmodelthathasbecomethestandardtooleconomistsusetounderstandtheeffectsofbothtimeandindividualcharacteristicsonadepen-
dentvariable.Inthiscase,aDPMisidealtodirectlyestimatehowrevenuegrowthhasbeeninfluencedbychangesintechnology
expenditures,itsownpastvalues,aswellasbyotherexplanatoryvariables,suchasthesizeoftheindustryandexposureto
large-scaleeconomicdownturns(i.e.,globalrecessions).
However,estimatingadynamicpanelmodelaccuratelyisnot
straightforwardbecauseitinvolvessometechnicalchallenges.Oneofthemistheproblemofendogeneity,whichmeansthatsomeoftheexplanatoryvariablesmaybecorrelatedwithwhatisleft“unexplained”bytheregressionequation.Thiscanbias
theestimatesofthecoefficientsandleadtowrongconclusions.Severalstepsweretakentoaddressthisproblem:
First,thevariablesincludedintheregressionsweretransformedtoremovethecommoninfluenceoftimetrends.Inaddition,
thedependentvariableandselectregressorswereexpressedinrelativetermstoensurecomparabilityacrossperiodsand
countries(e.g.,techinvestmentasashareofindustryrevenues).
Additionally,laggedvariablevalueswereincludedasinstrumentsbecausethesewerefoundtobecorrelatedwiththeexplanatoryvariables,butnotwiththe“errorterm.”Theseinstrumentswereassumedtobepredeterminedandexogenousandwereused
toprojecttheendogenousvariablesintheregressionequationtoprovideconsistentestimatesofthecoefficients.
Onechallengethatariseswhenusinglaggedvaluesasinstrumentsisthatlaggedvaluesmaynotbesufficientlycorrelatedwiththe
currentvaluesoftheexplanatoryvariables,especiallyifth
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