Bank competition and regional integration: Evidence from ASEAN nations ScienceDirect

(1)

Availableonlineatwww.sciencedirect.com

ScienceDirect

HOSTED BY

ReviewofDevelopmentFinance8(2018)127–140

Bank competition and regional integration: Evidence from ASEAN nations

Alexia Ventouri

King’sBusinessSchool,King’sCollegeLondon,UK Availableonline23August2018

Abstract

ThisstudyprovidesacharacterizationoftheAssociationoftheSouthEastAsianNations(ASEAN)bankingsystem’scompetitionunderthenew environmentthattheimplementationoftheFinancialIntegrationFramework(AFIF)implies.Wefocusonthelargestbankingmarketsintheregion, representedbytheASEAN-5.Theperiodunderstudyis2007–2016,coveringthepreparationperiodoftheASEANbankstofullyimplement thenewBankingIntegrationFramework(ABIF)in2020.PanzarandRossenon-structuralapproachisutilisedtomeasurethecompetitionlevel.

FollowingGoddardandWilson’s(2009)disequilibriumapproach,thetestforthedynamiccompetitionmeasureisalsoconductedasarobustness check.Weexaminetheevolutionofthebankingcompetitionbyobservingthetrendofthecompetitionlevelusingarollingestimationwitha5-year window.Thispaperalsoinvestigatesthefactorsthatmayinfluencethecompetitiveconditions,specificallycontrollingforstructuralconditions andinstitutionalcharacteristics.Ourmainfindingsconfirmthatbanksoperateundermonopolisticcompetition,althoughthereisstillahighlevel ofheterogeneityamongtheASEANcountries’bankingmarketandbankingintegrationsureisachallengingobjectivefortheregion.Ourresults revealapositiverelationshipbetweendensityofdemand,concentrationandcompetition.

JELclassiﬁcations: G21;L11;N20

Keywords:ASEANbankingmarket;Competition;PanzarandRosse;Disequilibriumapproach

1. Introduction

Assessing the effects of competition on financial stability is an important question for bothpolicymakers andantitrust authorities alike. Prior to the global financial crisis, a num- berofstudieshaveemphasizedtherole ofcompetitioninthe bankingindustry (e.g.BikkerandHaaf,2002;Claessens and Laeven,2004;Becketal.,2006).Thosestudiesarefocusingon investigatingtherelationshipbetweencompetitionandseveral different factors including the market structure, market con- testability,banks’efficiency,banks’risk-takingbehaviourand financialstability. Indeed,onewould expectthat whenbanks operateinamorecompetitiveenvironmenttheymaybemore likelytoengageincompetitivepoliciesachievinghigherlevels ofperformanceandotherefficiencies(Chortareas,etal.,2013, 2016).Increasedcompetitionisalsoexpectedtoeaseupaccess tofinancialservicesandexternalfinancingforwiderpopulation, improve the qualityandinnovation of the financial products,

E-mailaddress:alexia.ventouri@kcl.ac.uk

PeerreviewunderresponsibilityofAfricagrowthInstitute.

andoverallleadtoanimprovementofthecountry’seconomic welfare.

On the other hand, competition may not necessarily lead to financial stability.¹ Competition has been blamed to trig- ger an increase in risk taking activities by banks, especially when theyare forcedtooffertheirservices atmorecompeti- tiveprices(Schaecketal., 2009;Allenetal.,2011).With the global financial crisisof2008–09, thespillover effectof the crisisisevengreaterwherethedangersofahigh-riskculturein bankinghavegeneratedademand forthereassessmentof the prudentialrulescurrentlyinplace(seee.g.G30,2009;Acharya andRichardson,2009; Chortareasetal., 2011).Thisinturns has important implications for financially integratedregions, withthelatestdevelopmentbeingtheAssociationoftheSouth EastAsianNation(ASEAN).²Theaim oftheASEANBank-

1 Inthiscontext,twoviewsexistintheliterature:thecompetition-fragility andthecompetition-stability(seeBergeretal.,2009).

2 Oneofthemajorbackdropstriggeringforsuchstudyisthefinancialintegra- tionashasbeendonebyseveralregionsintheworldincludingEuropeanSingle Market,NorthAmericanFreeTradeAgreement(NAFTA),Asia-PacificEco- https://doi.org/10.1016/j.rdf.2018.08.002

(2)

ingIntegrationFramework(ABIF)istopromotecompetition, to achieve better financial inclusion and provision of finan- cialservices,strongerregionalbankingmarkets,andeventually strongerregionaleconomicgrowth(Khanetal.,2016a,2016b).

Yet,theexistingempiricalevidenceonfinancialintegration andstabilityisscant, especiallyconsideringthetimelinessof theissueandtherecentfinancialturmoilandbankinsolvencies.

Thispapercontributestotheexistingliteratureinseveralaspects:

first,itfocusontheASEANbankingmarketprovidinginsights regardingthecurrentbankingmarketcompetitionlevelandits countryspecificfactorsthathaveimportantpolicyimplications fortheregion,especiallyinlightofthecomingimplementation of ABIF.Weexpectthe current competition level amongthe ASEAN-5countriestovarygiventhedifferencesinthenature ofthebankingindustryofeachcountrywithintheregion.

Second,itusesrecentdatacoveringtheglobalfinancialcrisis of2008–09andthepostcrisisperiod.Wealsoexaminetheevolu- tionofthebankingcompetitiononASEAN-5level,representing theregion’scondition,fortheperiod2007–2016,byobserving thetrendofthecompetitionlevelusingarollingestimationwith a5-year window.Our analysis alsoconsider twosub-sample periods,with2011asthebreakpoint,toexaminehowthecom- petitionleveloftheASEANbankingmarketisaffectedbythe adoptionofASEANFinancialIntegrationFramework(AFIF),in whichABIFisoneoftheendorsedframeworks.Third,itfocuses explicitlyontheASEAN-5countries(e.g.Indonesia,Malaysia, Philippines,Singapore,andThailand)wheretheliteratureonthe topicisverylimited.ThechoicetofocusonASEAN-5coun- triesisdrivenbythefactthatABIFwillfirstlybeimplemented totheASEAN-5countriesbeforecompletely implementedto thewholeASEANregion.³

Fourth,itusesadditionalsensitivityanalysisusingthedis- equilibriumapproach(GoddardandWilson,2009),totestfor disequilibriummarketconditionsateachpointintimeduringthe observedperiod.Finally,itcontrolsforseveralselectedcountry specificcharacteristicstoexamine thefactorsdeterminingthe competitionlevelintheASEANbankingmarket.

Theremainingofthepaperisorganizedasfollows:Section2 reviewstheexistingliteratureonbankingcompetition.Section3 presentsthemethodologyanddatasources.Section4discussed theempiricalfindings.Section5concludes.

2. Literaturereview

Therecentglobaleconomicandfinancialcrisisputsthecom- petition discussion on a new basis rendering the conflicting approachesthateitherviewcompetitionasapanaceaordemo-

nomicCooperation(APEC),andmostrecentlyASEAN(AssociationofSouth EastAsianNation)withitsASEANEconomicCommunity(AEC).

3 SinceASEAN-5countriesarethefivelargesteconomiesintheASEAN region(togethertheycountformorethan87%oftheregion’stotalGDPsince 2007–2016),theuseofthefivecountriesassampleshouldbesufficientto representtheconditionofthewholeregion.Finally,thelimiteddataavailability oftheremainingASEAN-5countries(Cambodia,BruneiDarussalam,Laos, Myanmar,andVietnam)providesaconstraintforustoperformaproperresearch ontheoverallASEANregion.

nize.Accordingtothe“competition-fragility”view,competition triggersrisk-takingbehaviourofbanksgiventheirreducedfran- chisevalueduetoerodedmarketpowerandcompetition.Onthe otherhand,competitioncancreatealevelplayingfield,which canleadtoimprovedbankefficiencyandtheoverallcountry’s economy.Competitioncanalsoimprove acountry’sfinancial stability, as increased competition may reduce banks market power, andtheir abilitytochargehigher interestloantocus- tomersthatmostlikelywillleadtoanincreaseinnon-performing loan(NPL),andhenceriskinessofthebanks’portfolio.Thisis knownas“competition-stability”view.

Bergeretal.(2009)arguethatthesetwoviewsarenotcon- tradictingeachother.Theirfindingshowssomesupporttothe

“competition-fragility” viewwherebankswithhigher market power tendtohaveless risk exposure. Atthe sametime, the resultsalsoshowsomesupporttotheopposingviewthatmarket powerincreasesloanriskportfolio.Thissuggeststhatincreased market power does nothavetolead toanincrease inoverall risks.Banksmaychoosemitigatingtechniques(suchasincrease ofcapital,selectiveloanportfolio,etc.)toprotecttheirfranchise value,whichalsomightbeimposedthroughregulationssetby regulator.Becketal.(2012)andFuetal.(2014)alsoemphasize the importanceof theright regulatoryreforminordertopre- ventthenegativeimpactofcompetitiononstability.Theypoint out several factorsinforming regulatorypolicies inthe light ofincreasedcompetitionincludingtheimportanceofentryand activityrestriction,depositinsurancescheme,risk-takingincen- tives,andmarketstructure.Overall,competitionhasbeenofa particularinterestofacademicsandpolicymakersinasensethat iftherightcompetitionpoliciesareinplace,wemightexpect acompetitive,efficientandalsostablebankingsystem.Assug- gestedbyAllenandGale(2004),acomplexandmulti-faceted causeandeffectrelationshipbetweenregulationandcompeti- tionaswellasfinancialstabilitycallsforasoundpolicywhich takeintoconsiderationallfactorsthatworkbothontheoretical andempiricallevel.

Asidefromdiscussionsonrelationshipbetweencompetition andstability,thevastmajorityoftheliteratureonbankingcom- petitionfocusesontherelationshipbetweenbankcompetition andotherfactorssuchasmarketstructure,efficiency,andcon- testability.Mostoftheliteraturestudythedevelopedmarkets, suchasEuropeespeciallyinrelationtotheimplementationof theSingleMarketinitiativefortheEuropeanUnion(e.g.Bikker andGroeneveld,1998;Chortareasetal.,2011).Other studies include Bain(1951)andShaffer(1982)for theUnitedStates andMatthewsetal.(2007)for theUnitedKingdom. Interna- tionalstudiesincludeClaessensandLaeven(2004)foratotal of50developinganddevelopedcountries.

Molyneux et al. (1994) study the competitive conditions in majorEuropeanCountry for theperiod between1986and 1989andfindthatbanksinGermany,UnitedKingdom,France, and Spain operate under monopolistic condition, whereas in Italybanksoperateundermonopolyorcollusiveoligopoly.On anotherpaper,Molyneuxetal.(1996)findthatthecompetitive- nessintheJapanesecommercialbanksexperiencesomechanges betweentheperiod1986and1988whereitwasundermonopoly conditionsin1986andmonopolisticconditionsin1988.Astudy

(3)

withlargesamplesbyBikkerandHaaf(2002)investigatethe competitionacross23industrializedcountriesincludingcoun- triesinEurope,US,Canada,andJapan.Theyprovideevidence of monopolistic conditions inmost of the countriesand per- fectcompetitioninafewcases.Finally,ClaessensandLaeven (2004)measureuseasampleof50countriesfrombothindus- trialised anddeveloping countries for the period 1994–2001.

The evidence broadly suggests monopolistic condition inall countries.

Ontheotherhand,ASEAN,asadevelopingregionhasbeen playinganincreasinglyimportantroleintheeconomy.⁴Withan averagegrowthrateofaround5%inthepast10years,compared totheworld’saverageGDPgrowthrateofaround3%forthe sameperiod,ASEANisconsideredas afast-growingemerg- ingmarkets.However,althoughseveralstudieshavemeasured thelevel of competitioninthe differentbanking markets,the majorityofthesestudiestendtocoverlargeinternationalcross- countrydata samples or developed economies,and onlyfew existfortheASEANbankingmarket.WithASEAN’snotable economicgrowth,itsabilitytowithstandtheeffectoftherecent financialcrisis,andmostimportantly,thecomingimplementa- tionof ASEANBankingIntegration Framework(ABIF),itis notsurprisingthatresearchersarenowturningtheirattentionto thisregion.

Intermsofbankingintegration,HamidandLean(2016)for IndonesianCapitalMarketReview,investigatethereadinessof theASEAN-5countriesforabankingintegrationbymeasuring theconvergencelevel inpriceorreturnofassetswithsimilar characteristicsofthecommercialbanksintheASEAN-5coun- tries. The results confirm that interest rates inthe ASEAN-5 commercialbankingsectorareconverging,whichshowsthatit isreadyforanintegration.Oneofthestudiesconsideringthe competitionlevelinASEANisClaessensandLaeven(2004)’s whosamplecomprisesof50countries(bothindustrialisedand developing),including 3 of the ASEAN-5 countries(namely Indonesia, Malaysia,and the Philippines). They estimate the PanzarandRosseH-Statisticonthebasisoffourmodelsvarying intermsofestimationtechniquesaswellasintermsofdepen- dentvariablesforrobustnesspurpose.Theyresultssuggestthat countriesareoperatingundermonopolisticcompetitionforthe observedperiod.

Liuetal.(2012)focus onfourSouthEastAsiancommer- cialbankingmarket,namelyIndonesia,Malaysia,Philippines, and Vietnam, to examine how competition affects bank risk taking behaviour for aperiod between1998 and 2008.Sim- ilarly, tothe majority of banking competition literature, they alsoutilizethePanzarandRosseH-Statisticandtheyusetwo dependentvariablesforrobustnesspurposes.Theresultssuggest thatbanksoperateundermonopolisticcompetition.Theirstudy alsoshowthatcompetitiondoesnotincreasebankrisk-taking behaviourandthatconcentrationisinverselyrelatedtobankrisk, whereasregulatoryrestrictionspositively influencebankrisk-

4 Ithasacombinedgrossdomesticproduct(GDP)ofUSD2554.70billion andatotalpopulationofaround639millionasofend-2016,accordingtodata fromtheWorldBank.

taking.Khanetal.(2016a),observetheroleofcompetitionin monetarypolicytransmissionthroughthebank-lendingchannel.

Theyusetwostructural(CR5andHHI)andtwonon-structural (LernerIndexandBooneIndicator)indicesasproxiesforcom- petition.Theyconclude,assumingallmeasuresrefertothetrue competitionlevel,isthatthedecreasedlevelofcompetitionin the banking industry weakens the monetary policy transmis- sion.Khanetal.(2016b)examinestheroleofmarketstructure for growthin10emergingAsiancountiesprovidingevidence infavourofbankcompetitionsuggestingthatfinanciallydepen- dentindustriesgrowmoreinindustriescharacterizedbymore competition.

Inoneofthemostrecentstudies,Khanetal.(2017b)examine the relationshipbetweenefficiency,growth andconcentration intheASEANregion.Theresultssuggestthatefficientbanks are abletogrow fasterwhichinturnresultsinhighermarket concentrationandpower.Onamorerecentstudy,Khan etal.

(2018)provideevidencesupportingtheS-C-Phypothesisforthe ASEANbankingindustry.Finally,Nomanetal.(2017)examine theeffectofcompetitiononfinancialstabilityofthecommercial bankingmarketinASEANcountries.Theyfindthatanincrease incompetitionalongwithdecreaseinmarketpowerwillencour- agebankstoholdmorecapitalandtakelesscreditrisk,which inturnenhancesbanks’financialstability.

Nonetheless,theexistingempiricalevidenceisinconclusive andscant,especiallyconsideringthetimelinessoftheissuefol- lowingtheimplementationoftheASEANBIF,andthisisthe taskthatwepursueinthefollowingsections.

3. Dataandmethodology 3.1. Datasources

Thedatasetusedinthisstudyiscomposedofindividualbank datasourcedfromunconsolidatedstatementsofbanksoperat- ing in the five ASEANcountries, as made available through theOrbis andFitchConnectdatabase.⁵ Dataforcountryspe- cificcharacteristicsarecollectedfromtheWorldBankdatabase, includingthesizeoflandarea(insquarekilometre),concentra- tionratio(CR3andCR5),andthenumberofbankbranchesper 100,000adultsas aproxyforbanksdensity.Thechosentime spanis2007to2016.Wefocusoncommercialbanking,which comprisesoneofthelargestsegmentsofdepositoryinstitutions inASEAN.Wehavealsoscrutinizedthedatatoavoidincon- sistencies,reportingerrors,anddoublecountingofinstitutions.

Implementingtheaforementionedscreeningmethods,resultsin anunbalancedpanelof1512bankobservations.Table1illus- tratesthenumberofbanksincludedinthesample,peryearand country.

5 Specifically,fordataonASEANbankingmarket,FitchConnecthasamore completedatabaseforeachcountrysampleespeciallyintermsofperiodavail- abilityofbanklevelfinancialdata.Hence,weprimarilyusedatafromFitch Connect.Wethenmanuallyscreentoensurethereisnomissingbanknames, missingvalues,doubleentries,andotherinconsistencies.

(4)

Table1

Datadistributionbycountryandyear.

Year Indonesia Malaysia Philippines Singapore Thailand Observationbyyear

2007 33 25 18 3 15 94

2008 42 31 18 5 18 114

2009 47 31 19 6 18 121

2010 53 34 19 6 19 131

2011 61 38 22 6 20 147

2012 74 38 21 6 20 159

2013 103 38 21 6 20 188

2014 110 39 21 5 21 196

2015 109 38 20 5 21 193

2016 107 28 13 3 18 169

Numberofbankobservations 739 340 192 51 190 1512

Source:OrbisandFitchConnect.

Selecteddescriptivestatisticsforthedependentandindepen- dent variablesare presented inTable 2.With respect to data availability,weexperience verylimitedinformationfor banks inSingapore. Wenotethat out of the 128 commercialbanks listedbyMonetaryAuthorityof Singapore(MAS),⁶ thereare lessthan10banknameslistedineitherOrbisorFitchConnect.

AccordingtoMAS,outofthe128commercialbanks,5arelocal banksand123areforeignbanks,withonly29ofthoseforeign banks(one-fifth)offerfullbankingservices.Giventhatdatafor foreignbanksubsidiaries/branches/representativeofficesarenot publiclyavailable,theavailabilityofdataisverylimitedforthe caseofSingaporeandtheanalysisisbasedonthissamplesize peryear.Nevertheless,thebanksincludedinthesampleaccount foralargestproportionofthetotalassetsofSingaporeanbanks, hencewetreatthissampleasarepresentativeone.⁷

3.2. Measuringbankcompetition:thePanzarandRosse model

To measure competition we use the Panzar and Rosse (1987) H-statistic.This statisticallowsdistinguishing among oligopolistic, competitive and monopolistically competitive markets.TheH-statistic isanon-structuraltest, asit assesses thecompetitivebehaviourofbankswithoutusinginformation onthestructureofthebankingmarket.Itiscalculatedusingthe followingreducedformrevenueestimations(runonapaneldata set)foreachcountry:

lnTR_it=β1lnP1,it+β2lnP2,it+β3lnP3,it+γ1

lnEQAST_it+γ2lnAST_it+γ3lnLOANAST_it +γ4lnCASHDEP_it+γ5lnOBSAST_it+ε_it

(1)

for t=1,...T, whereTis the numberof periods observedand i=1,...I,whereIisthe totalnumberofbanks.Thedependent

6 AsofJune2017.

7 Dataavailablearemostlyforthe5localSingaporebanks,namelyDBSBank Ltd.,Oversea-ChineseBankingCorporationLtd.,UnitedOverseasBankLtd., FarEasternBankLtd.,andBankofSingaporeLtd.,whicharethe5biggest banksinthecountry.Moreover,thefirst3banksaredeemedasthe3biggest banksinSoutheastAsia(i.e.ASEANregion)intermsofasset.

variableTRitistheratiooftotalrevenuetototalassets.Weuse threeinputs(labour,capitalanddeposits)todescribethepro- duction process of banks: lnP1 is the averagecost of labour (personnel expenses/total assets)⁸; lnP2is the average cost of deposits (interestexpenses/customerandshorttermfunding);

and finally lnP3 is the average cost of capital (total capital expenses/totalfixedassets).

Thismodelexaminestheeffectofthechangeinfactorinput prices(i.e.independentvariables)tothe revenues(i.e.dependent variables) earned by banks. In other words, it captures the elasticity of bank’s revenues to input prices. Essentially, all banks will experience an increase on their marginal cost givenanincreaseinfactorinputprices.However,thereaction of each banks towards that change will be different depend- ingonthetypeofmarketthatthosebanksarebelongin.Ina perfect competitionmarket,anincreaseininputprices, which raise the marginal costs, will force several firms to eventu- ally exit the market, resulting in an increase of demand for the remainingfirmswhichthen leadstoanincreased insell- ing priceandhencerevenuesbythesameamountas therise in costs.In a monopolisticmarket, the increase incosts will lead toan increaseof revenuesat arate slower thanthe rate of increase in the costs. Meanwhile, in a monopoly market, theconditionisexplainedbythetheorythatprofitmaximising firmsoperatesonaprice-elasticportionofmarketdemandfunc- tion(GoddardandWilson,2009).Hence,anincreaseininput priceswillincreasemarginalcosts,whichleadstoadecrease in the output, andconsequentlyresulted in adecline intotal revenues.

Weusetheintermediationapproachtoexplainthe production process of a bankgiven its mainfunction as a financial intermediary to transfer funds from the party with excess of funds to parties in need of funds.⁹ We use three inputs

8Duetolackofdataonthenumberofemployeesformanybanksinour sample,weusepersonnelexpensestototalassetsasanindicatorofunitlabour costs.

9Unliketheordinaryproductionapproachwhereabank’sproductionpro- cess involves transforming inputs which include labour and capital into outputs/productswhichincludesloansanddeposits,intermediationapproach considersdepositsasoneoftheinputsandtheloansasoneoftheoutputs.

(5)

Table2

Selecteddescriptivestatisticspercountry:min,max,mean,andstandarddeviationsfor2007–2016.^a Descriptivestatistics

ofdatasetpercountry forperiod2007–2016

Indonesia Malaysia Philippines

Min Max Mean SD Min Max Mean SD Min Max Mean SD

Dependentvariable TR=total revenue/totalasset

0.02 0.27 0.10 0.03 0.00 0.07 0.05 0.01 0.02 0.13 0.06 0.02

ROA*=1+returnon asset

0.83 1.10 1.01 0.02 1.02 1.01 0.01 0.01 0.93 1.04 1.01 0.01

Independentvariable P1=personnel expenses/totalassets

0.00 0.09 0.02 0.01 0.00 0.04 0.01 0.00 0.00 0.05 0.01 0.01

P2=interest expenses/customer&

short-termfunding

0.00 0.40 0.05 0.02 0.00 0.08 0.02 0.01 0.00 0.19 0.02 0.02

P3=totalcapital expenses/totalfixed assets

0.03 26.83 2.35 2.95 0.09 94.85 6.95 11.67 0.28 18.93 2.27 2.75

Bankspecificcontrol variables

EQAST=equity/total assets

0.00 0.86 0.14 0.08 0.03 0.96 0.13 0.11 0.01 0.65 0.13 0.07

AST=totalassets 18.57 71,747.60 4,177.04 9,779.66 103.64 129,487.70 14,015.80 21,972.42 17.13 43,946.18 7387.85 8560.98 LOANAST=total

loans/totalassets

0.05 0.89 0.65 0.11 0.00 1.16 0.52 0.21 0.00 0.70 0.44 0.14

CASHDEP=cashand duefrom

institutions/total deposits

0.00 0.69 0.09 0.06 0.00 4.14 0.29 0.36 0.01 0.44 0.13 0.11

OBSAST=OBS/total assets

0.00 3.21 0.13 0.17 0.00 13.52 0.78 1.50 0.00 3.00 0.20 0.41

Descriptivestatistics ofdatasetpercountry forperiod2007–2016

Singapore Thailand

Min Max Mean SD Min Max Mean SD

Dependentvariable TRit=total revenue/totalasset

0.01 0.06 0.03 0.01 0.01 0.10 0.05 0.02

ROA*=1+returnon asset

1.00 1.02 1.01 0.00 0.93 1.03 1.01 0.01

Independentvariable P1=personnel expenses/totalassets

0.00 0.02 0.01 0.00 0.00 0.03 0.01 0.00

P2=interest expenses/customer&

short-termfunding

0.00 0.03 0.01 0.01 0.01 0.12 0.02 0.01

P3=totalcapital expenses/totalfixed assets

0.27 30.12 5.87 7.17 0.32 22.62 2.40 3.07

Bankspecificcontrol variables

EQAST=equity/total assets

0.06 0.22 0.11 0.04 0.01 0.81 0.17 0.14

AST=totalassets 617.70 292,364.65 103,256.50 89,302.09 167.77 82,733.67 19,551.20 23,518.26 LOANAST=total

loans/totalassets

0.10 0.73 0.48 0.16 0.20 0.91 0.67 0.13

CASHDEP=cashand duefrom

institutions/total deposits

0.00 0.18 0.06 0.05 0.00 0.14 0.02 0.02

OBSAST=OBS/total assets

0.06 1.29 0.40 0.25 0.00 15.24 0.78 2.20

Sources:FitchConnectandAuthor’scalculation.

a AllfinancialvariablesmeasuredinUSDmillions.

(6)

(labour, capital anddeposits)to describethe production process of banks: lnP1 is the average cost of labour (personnel expenses/totalassets);lnP2istheaveragecostofdeposits(interestexpenses/customerandshorttermfunding);andfinallylnP3

istheaveragecostofcapital(totalcapitalexpenses/totalfixed assets).The dependent variableTRit is the ratio of totalrev- enuetototalassets.Unliketootherstudiesthat onlyconsider interestrevenue,wealsoincludebothinterestandnon-interest revenue(i.e.otheroperatingrevenue).Weviewthatthecurrent bankingmarketconditionhasforcedbankstobemoreinnova- tiveinexpandingtheir sourceof revenueincluding fromfee- and commission-based products and off-balance sheet activities. According to this view, in a competitive environment banksarecompeting inbothinterestandnon-interest income (Shaffer,1982;NathanandNeave,1989;DeBandtandDavis, 2000).Hence, distinction between the two become less rele- vant.

Severalbank-specificcontrolvariablesarealsoincludedin the regression formula to control for potential differences in costs,size,risk,structureandproductmix.Specifically,EQAST is theratio of equity to totalassets(tocontrol differences in riskpropensity);ASTisthelogarithmoftotalassets(tocontrol forpotentialsizeeffects);LOANASTistheratiooftotalloans tototal assets (tocontrol for asset composition);CASHDEP istheratio ofcashandduefrom institutionstototaldeposits (tocapturedifferencesinthedepositmix).Finally,OBSASTis equaltooffbalancesheetactivitiesovertotalassets(tocontrol for differences inthe business mix). Eq. (1) is estimated by runningapaneldatasetwithfixedeffects, controllingforthe bank-specificcomponenttoallowforheterogeneityacrossthe banks.TheH-statisticiscalculatedfromtheestimationof(1) as:

H=

3

j=1

β_j (2)

IftheH-statistictakesthevalueofzerooranegativevalue thenthecompetitivestructureiseitheramonopolyoraperfect colludingoligopoly.WhentheH-statisticisequalto1,itindi- catesperfectcompetitionwhereasavaluebetweenzeroandone indicates monopolisticcompetition. Therefore,the biggerthe valueoftheH-Statisticindicatesastrongerdegreeofcompeti- tioninamarketandthatthechangingpatternsofH-Statisticover timerepresentschangesinthedegreeofcompetitionthroughout thetime.Vesala(1995)andBikkerandHaaf(2002)suggestthat continuousinterpretationofH-Statisticaswellascomparison acrosscountriesorbankingmarketsandtimeperiodiscorrect understrongerassumptions,morespecifically theconstantor identicalpriceelasticityofdemandforthevariousmarkets.

Given that the PR model is only validif the market is in equilibrium, we also undertakethe tests onobservations that areinlong-runequilibrium.Theequilibriumtestisperformed byrecalculatingEq.(1)afterreplacingthedependentvariable (totalrevenueovertotalassets)withthenaturallogofreturns

onassets(ROA).Thus,weestimatethefollowingequationfor eachcountry:

lnROA_it=β1lnP1,it+β2lnP2,it+β3lnP3,it

+γ1lnEQAST_it+γ2lnAST_it+γ3lnLOANAST_it +γ4lnCASHDEPit+γ5lnOBSASTit+εit

(3)

Specifically, the dependent variable is computed as ROA=ln(1+ROA)inordertobeadjustedfor smallandneg- ative values dueto banks’ lossesin any year. Wedefine the equilibriumtestas:

E=

3

j=1

βj (4)

E-statisticmeasuresthesensitivityofprofitwithrespecttothe changesininputfactorpricesandiscalculatedasthesumofthe factorinputprices’coefficients.WethentestwhetherE-statistic isstatisticallyequaltozerousingtheF-teststatistic.¹⁰

Wefurthercarryoutasensitivityanalysisforrobustnessusing totestfordisequilibriumconditioninthemarket.Especiallyfor economiesthatareintransitional,theadjustmenttowardsequi- libriummightnothappeninstantly,leadingtoamarketcondition that is out of long-run equilibrium, which in turn can result in biased H-Statistic. Goddard andWilson (2009) propose a dynamicversion,asopposedtothenormalstaticversion,ofthe reducedrevenueequation.¹¹Thus,were-estimateEq.(1)as:

lnTR_it=β0TR_i,t−1+β1lnP1,it+β2lnP2,it

+β3lnP3,it+γ1lnEQAST_it+γ2lnAST_it +γ3lnLOANAST_it+γ4lnCASHDEP_it +γ5lnOBSAST_it+ε_it

(5)

Thisdynamicequationeliminatestherequirementforlong- runequilibriumassumptionsbecausethecoefficientestimates of thelaggeddependentvariablecanbeusedtodirectlyasses thespeedofadjustmenttowardsequilibrium.TheunbiasedH- Statisticcalculationisasfollows:

H =

₃

j=1βj

1−β0

(6)

3.3. Determinantofcompetition

To identifyfactorsthat canexplaindifferencesincompeti- tivenessacrossthe ASEASbakingmarket,weuseatwo-step approachandweregresstheH-Statistic(derivedfromEq.(1)) onanumberofcountryspecificcharacteristics.Specifically,we developamodelwherethecompetitionmeasureisregressedto

10AsClaessensandLaeven(2004)pointout,inequilibriumROAshouldnot berelatedtoinputprices.

11Oneofthetechniquestoproduceadynamicpanelestimatorthattheysuggest istheone-stepgeneralizedmethodofmoments(GMM)procedurebyArellano andBond(1991),whichintroducealaggeddependentvariableontheright-hand sideoftheequation.

(7)

thefollowingfactors:

H_i =α+α1lnDEPKM2+α2lnINTERM

+α3BANKSPOP+α4lnCRk+ε_i (7)

where,HiistheestimatedH-Statistic(derivedfromEq.(1))for countryI;DEPKM2isaproxyforthedensityofdemand(mea- suredastotaldepositsoversquarekmoflandarea);INTERM isthe intermediationratio (measured as loansoverdeposits);

BANKSPOPisthenumberofbankbranchesper100,000adults;

CRkistheconcentrationmeasure(measurebytheCRratio).

Weexpectapositivesignfor the DEPKM2 coefficientas anincreaseindensityofdemandwouldattractmorefirmsand hencemorecompetition.FortheintermediationratioINTERM, weexpectanegativecoefficientasthehighertheloanstodeposit ratio is the less deposit is required to produce loans, which indicatesalowcostofintermediationandisasignoflowcompe- tition.BANKSPOPcoefficient(aproxyfordensityofbanks)is expectedpositive,asthehigherthenumberofbanksinthepop- ulationis,themorecompetitivethemarketshouldbe.Finally, ifthetraditionalStructure-Conduct-Performancetheoryholds, theconcentrationratio(CRk)variableisexpectednegative,sug- gestingthatanincreaseinmarketconcentrationshouldrestrict market’scompetitiveness.

4. Empiricalresults

4.1. ThePanzarandRosseH-Statisticmeasure

BeforeapplyingthePanzarandRossemodeltotestformar- ketcompetitiveness,wefirstrunanequilibriumtesttoensure therequirementforlong-runequilibriuminthemarket.Table3 presentstheE-Statisticestimatesforthe wholesampleperiod between2007and2016alongwiththeresultoftheF-testwith anullhypothesisofE=0.

Theresultsshowthat,ontheASEAN-5level,theE-Statistic estimationisnotsignificantlydifferentfromzero.Thisisalso confirmed by the country level E-Statistic estimation values rangingfrom−0.006to0.008.Thissuggestthatwhenthemar- ketis inequilibrium, the increaseininput priceswillhave a minimumtonoeffectonbanks’profitability.Thisisalsocon- firmedbytheF-test,whichfailstorejectthenullhypothesisboth attheASEAN-5andatacountrylevel.Theaboveresultsimply thatthebankingmarketsareinlong-runequilibriumthroughout theobservedperiod.

Toensuretherobustnessofourresultaswellastocapture theevolutionandthedynamicofASEANbankingmarketcon- dition,wealsoconductedtheequilibriumtestonarollingbasis followingMatthewsetal.(2007).Therollingestimationiscon- ductedusinga5-yearwindowandisdonerepeatedlyforevery 1yeargap.Theresult,aspresentedinTable4.TheF-testresult failstorejectthenullhypothesisofE=0whichindicatesthat

theASEANbankingmarketisindeedinequilibriumthroughout theobservedperiod.¹²

Followingtheempirical literatureoncompetition,we esti- matethereducedformrevenuespecificationinEq.(1)apanel data framework. Table 5 reports the regression results. The estimatedH-Statisticis0.564attheASEANlevel,thusindicat- ingmonopolisticcompetition inthe ASEANbankingmarket.

The variety of H-Statistic estimates for each country shows the difference inlevel of competition ofeach country, which is inline withourexpectation. Asmentioned inSection3.2, we treatthe H-Statistic as acontinuousmeasure of competition,whichiscomparableacrosscountries.Therefore,wecan rank the countries’ banking market from the most competi- tiveonetotheleastone,i.e.Thailand(0.823)withthehighest H-Statisticfollowed byMalaysia,Philippines,Indonesia,and finallySingapore(0.438).Theseresultsareinlinewiththeresult frompreviousstudiesdonebyClaessensandLaeven(2004)and Liuetal.(2012)forIndonesia,Malaysia,andPhilippinesfor period1994–2001and1998–2008,respectively.

Bankingintegrationis expectednot onlytoincreasecom- petitionintheregion,butalsotoleadtoaconvergenceof the competitionlevelineachcountry.Banksincountrieswithhigher competitionlevelmaynotbeaffectedbytheincreasedcompe- titioncomparedtothesmaller ones.However,itmayalso be thecasethattheleadingbanksfromthelesscompetitivecoun- triesaretheonesdominatingtheregionalmarket.Forexample, Singaporehasthe lowestcompetition level,however its mar- ketisdominatedbythreelargebanks(namelyDBSBankLtd., OCBCLtd.,andUOBLtd.)withstrongpresenceattheASEAN regionmarket.Anotherinterestingpoint,ishowcountrieswith largenumberofbanksresultinlowerH-Statistic,comparedto countrieswithlessnumberofbanks.InSingaporeandIndonesia cases,thiscanbeexplainedbythefactthatthebiggestbanksin thecountry(intermsoftotalasset)tendtodominatethedomestic market interms ofcustomer base,market presence andfran- chise,benefitedfrommarketpower.Furthermore,asbefore,we apply therollingestimationtoexamine thetrendof competi- tionineachcountry’sbankingmarket.Theresultsarepresented in Table 6. In Appendix A (Graph A1), we also present the competitiontrend(H-Statisticrollingtrend)perASEAN-5coun- try throughouteach period window. Analysing two windows periodbeforeandaftertheendorsementofASEANFinancial Integration Framework (AFIF) andthe creation of the Bank- ingIntegrationFramework,weshowvariancesinthechangeof each country’sbankingcompetition landscape.Althoughit is notnecessarilyenoughtodepicttheactualchangesinthemar- ket,onecanarguethatthereisnoclearsignofconvergenceof thecompetitivenessacrosstheregion.

Following the announcement of the banking integration framework, banks in the ASEAN region has taken different approachedonrespondingtothecomingchanges.Countrieslike MalaysiaandSingapore,takeamoreoutward-lookingapproach

12Given these results, it is not necessary to perform the disequilibrium approach.However,forrobustnesspurposes,wealsocarryoutthedisequilibrium approachusingtheone-stepGMMdynamicpanelestimator.

(8)

Table3

EquilibriumtestonASEAN-5andcountrylevelfor2007–2016.

Dependentvariable:lnROA* ASEAN5 Indonesia Malaysia Philippines Singapore Thailand

lnP1 −0.002 −0.004 −0.002 0.003 0.008* 0.007

(0.317) (0.291) (0.171) (0.440) (0.091) (0.250)

lnP2 0.000 −0.002 0.004** −0.001 0.001 −0.003

(0.697) (0.421) (0.013) (0.381) (0.328) (0.278)

lnP3 0.001 0.002 0.000 −0.007** −0.001 −0.005

(0.634) (0.285) (0.711) (0.048) (0.192) (0.190)

lnEQAST 0.001 −0.003 0.001 0.002 −0.001 0.009***

(0.751) (0.201) (0.537) (0.482) (0.832) (0.004)

lnAST 0.000 0.000 0.001 0.002 0.001 0.003

(0.685) (0.929) (0.631) (0.470) (0.619) (0.310)

lnLOANAST 0.002* 0.001 0.004*** −0.002 −0.002 0.002

(0.087) (0.921) (0.000) (0.145) (0.491) (0.784)

lnCASHDEP −0.001* −0.001* 0.000 −0.001 −0.001 −0.002*

(0.057) (0.052) (0.422) (0.282) (0.479) (0.055)

lnOBSAST 0.000 0.001 0.000 0.000 −0.001 −0.001

(0.709) (0.728) (0.712) (0.465) (0.501) (0.167)

CONS −0.003 −0.020 0.013 0.002 0.044 0.020

(0.823) (0.404) (0.350) (0.940) (0.187) (0.210)

Estat(E) −0.002 −0.004 0.002 −0.006 0.008 0.000

Ftest(E=0) 0.52 0.60 2.47 0.92 2.05 0.00

Prob>F 0.471 0.440 0.124 0.348 0.212 0.953

*,**,***denotesignificanceat10%,5%,and1%levels,respectively.P-valuesareinparentheses.

Notes: lnROA*=1+Return on Asset; lnP1=personnel expenses/totalassets; lnP2=interest expenses/customer and short term funding;lnP3=total capital expenses/totalfixedassets;lnEQAST=equity/totalassets;lnAST=totalasset;lnLOANAST=totalloans/totalassets;lnCASHDEP=cashandduefrominstitutions/totaldeposits;lnOBSAST=off-balance-sheetactivities/totalassets.

Table4

RollingequilibriumtestonASEAN-5Levelfor2007–2016.

Dependentvariable:lnROA* 2007–2011 2008–2012 2009–2013 2010–2014 2011–2015 2012–2016

lnP1 −0.002 −0.001 −0.002 −0.002 0.000 0.004

(0.447) (0.826) (0.744) (0.711) (0.919) (0.260)

lnP2 0.001 0.002 0.001 0.001 −0.002 −0.07**

(0.393) (0.334) (0.508) (0.526) (0.371) (0.037)

lnP3 −0.003 0.000 0.001 0.002** 0.001 0.001

(0.147) (0.945) (0.470) (0.020) (0.579) (0.696)

lnEQAST 0.008*** 0.004* 0.002 0.000 0.000 −0.003

(0.008) (0.093) (0.488) (0.967) (0.984) (0.285)

lnAST 0.004** 0.005*** 0.004* 0.002 0.003 0.004

(0.034) (0.008) (0.100) (0.502) (0.369) (0.276)

lnLOANAST 0.001 0.002 0.002 0.003** 0.002 0.001

(0.518) (0.544) (0.218) (0.036) (0.234) (0.611)

lnCASHDEP 0.000 0.000 0.000 −0.001 −0.001*** −0.001***

(0.549) (0.634) (0.950) (0.139) (0.008) (0.003)

lnOBSAST 0.001 0.001 0.001 −0.001 0.000 0.000

(0.343) (0.315) (0.471) (0.278) (0.885) (0.842)

CONS −0.001 −0.010 −0.016 −0.008 −0.020 −0.036

(0.962) (0.694) (0.517) (0.631) (0.436) (0.307)

Estat(E) −0.003 0.001 0.000 0.001 −0.002 −0.002

Ftest(E=0) 1.17 0.06 0.01 0.17 0.23 0.20

Prob>F 0.2816 0.8078 0.9344 0.6801 0.6357 0.6522

Notes: lnROA*=1+Return on Asset; lnP1=personnel expenses/totalassets; lnP2=interest expenses/customer and short term funding;lnP3=total capital expenses/totalfixedassets;lnEQAST=equity/totalassets;lnAST=totalasset;lnLOANAST=totalloans/totalassets;lnCASHDEP=cashandduefrominstitutions/totaldeposits;lnOBSAST=off-balance-sheetactivities/totalassets.

focusing on strengthening their presence inregional market.

Other countries, like Indonesia and Philippines, take a more inward-lookingstrategyinordertoprotecttheirownlocalbanks’

domesticpresence.Usingmergerandacquisitionactivities,as

wellasincreasedrestrictionsonforeignownershipandactivi- ties,theyaimtoexpandtheirdomesticbusinesscapacityinorder tosurvivefromtheincomingforeigncompetition.Meanwhile, banksfromThailandtakeacombinationstrategyofstrengthen-

(9)

Table5

CompetitionattheASEAN-5Levelandatacountrylevelfor2007–2016.

Dependentvariable:lnTR ASEAN5 Indonesia Malaysia Philippines Singapore Thailand

lnP1 0.260*** 0.223*** 0.270*** 0.418*** 0.114 0.424***

(0.000) (0.000) (0.001) (0.001) (0.350) (0.000)

lnP2 0.289*** 0.241*** 0.401*** 0.219*** 0.336*** 0.343***

(0.000) (0.000) (0.000) (0.000) (0.001) (0.000)

lnP3 0.015 −0.001 0.062* −0.112 −0.012 0.056*

(0.293) (0.916) (0.056) (0.131) (0.672) (0.081)

lnEQAST 0.012 −0.046 0.094 −0.014 −0.149 0.008

(0.634) (0.126) (0.149) (0.760) (0.160) (0.884)

lnAST −0.042 −0.054** −0.026 −0.044 −0.199* −0.002

(0.107) (0.018) (0.658) (0.607) (0.070) (0.968)

lnLOANAST 0.158*** 0.215** 0.139*** 0.127*** 0.361** 0.227**

(0.000) (0.021) (0.000) (0.010) (0.016) (0.048)

lnCASHDEP 0.004 0.004 0.019 −0.026* 0.017 0.010

(0.527) (0.611) (0.222) (0.086) (0.490) (0.663)

lnOBSAST 0.000 0.007 −0.021 0.004 −0.002 0.014

(0.964) (0.389) (0.126) (0.677) (0.916) (0.206)

CONS −0.057 −0.292* 0.298 0.432 0.917 0.548**

(0.743) (0.077) (0.471) (0.293) (0.325) (0.037)

Hstat(H) 0.564 0.463 0.733 0.525 0.438 0.823

Ftest(H=0) 71.63*** 57.83*** 27.99*** 10.19*** 9.43** 103.69***

Prob>F 0.000 0.000 0.000 0.004 0.028 0.000

Ftest(H=1) 42.77*** 77.84*** 3.73* 8.33*** 15.50** 4.81**

Prob>F 0.000 0.000 0.061 0.009 0.011 0.040

Notes:TR=totalrevenue;lnP1=personnelexpenses/totalassets;lnP2=interestexpenses/customerandshorttermfunding;lnP3=totalcapitalexpenses/totalfixed assets;lnEQAST=equity/totalassets;lnAST=totalasset;lnLOANAST=totalloans/totalassets;lnCASHDEP=cashandduefrominstitutions/totaldeposits;

lnOBSAST=off-balance-sheetactivities/totalassets.

ingitsdomesticfoundationwhileatthesametimeenhancingits regionalpresence.Overall,thereisstillahighlevelofhetero- geneityamongthe ASEANbankingmarket andsurebanking integrationisachallengingobjectivefortheregion.Therefore, itremainscriticalforpolicymakerstocreateaplayinglevelfield inordertoimprovemarketenvironmentthoughharmonisation ofregulationandenhancementofcompetitionintheregion.

An analysis of the signand significance of the regression coefficients(Tables 5 and 6) indicate that the price of funds is always positiveand statistical significant for all countries.

Thepriceoflabourispositiveandstatisticalsignificantinmost countries(withtheexceptionofSingapore).Theimpactofthe costofcapitalseemstobeminimalcomparedtotheotherinput prices.Theseresultsareconsistentwithpreviousstudiesnotonly fortheASEANbankingmarketbutalsoforothercountries’and regions(Liuetal.,2012).

TovalidateourresultsweconducttheGoddardandWilson’s (2009)disequilibriumtestforrobustnesspurposes.Theresults fromthe one-step dynamic Generalized Method of Moments (GMM)estimationarepresentedinTable7.SimilartoLiuetal.

(2012),we do not find a positive andstatistically significant lagged-dependentvariableinallobservedcountries.Thevarying signandsignificanceindicatesthelackofnecessitytoincludea partialadjustmentmechanismtoproducethedynamicrevenue equation.Nonetheless,confirmingtheresultobtainedfromfixed effectestimators(aslaidoutinTables5and6),thepositiveand statisticallysignificantcoefficientforthepriceoffundsremain consistentforallcountriesandattheASEAN-5level.Further- more,theresultsforthecoefficientestimatesof theothertwo

inputpricesandthecontrolvariablesarebroadlyin-linewiththe resultsderivedfromthefixedeffectestimators.Table8presents thecomparisonbetweentheresultobtainedfromFEandGMM estimation.

Overall,theGMMmethodproduceshigherH-Statisticesti- matedcomparedtothefixedeffectsprocedure. Thisisinline with Goddard and Wilson(2009) and Liu et al.(2012) who suggest that the static H-Statistics produced by fixed effects hasthetendencytounderestimatethecompetitionlevel.More- over,in-linewiththeresultsfromthefixedeffectsprocedure, theGMM confirmsthattheASEANbankingmarketoperates undermonopolisticcompetitionthroughouttheobservedperiod (2007–2016).

4.2. Determinantsofcompetition

Thissection presents the results of the relationshipof the independentvariableswiththecompetitivenessmeasure.Table9 illustratestheresults.Theregressionwasrunusingtwodifferent proxiesforconcentration,CR3andCR5,whichgaveussimilar results and, for thepurpose of thispaper, we onlyreport the estimationresultbasedontheuseofCR3measure.¹³

Basedontheestimationresultabove,itcanbeseenthatthe factorssignificantlyaffectthe H-Statisticare theCR3 (proxy formarketconcentration)andDEPKM2(proxyfordensityof

13TheresultsforCR5arenotreportedinthetablesbutareavailableupon requestfromtheauthors.