Financial Structures, Bank Lending Rates and Transmission Mechanism

8/8/2019 Financial Structures, Bank Lending Rates and Transmission Mechanism

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Financial Structure, Bank Lending Rates, and the Transmission Mechanism of Monetary

PolicyAuthor(s): Carlo Cottarelli and Angeliki KourelisSource: Staff Papers - International Monetary Fund, Vol. 41, No. 4 (Dec., 1994), pp. 587-623Published by: Palgrave Macmillan Journals on behalf of the International Monetary FundStable URL: http://www.jstor.org/stable/3867521 .

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IMFStaffPapersVol.41, No. 4 (December1994) 1994InternationalMonetaryFund

FinancialStructure,Bank LendingRates, and the TransmissionMechanismof Monetary Policy

CARLO COTTARELLI and ANGELIKI KOURELIS*

The stickiness of bank lending rates with respectto money market rates isoften regarded as an obstacle to the smooth transmission of monetarypolicy impulses. Yet,no systematicmeasureof thedifferent degree of lend-ing ratestickiness across countries has been attempted.Thispaperprovidessuch a measure. It also relatesthedifferent degreeof lending ratestickinessto structural features of the financial system, such as the existence ofbarriersto competition, the degree of development of financial markets,and the ownership structure of the banking system. Thus, the paperprovides further evidence on the relationship between structuralfinan-cial policies and monetary policy, as well as on the relevance of creditmarkets for the monetary policy transmission mechanism. The role ofadministered discount rates in speeding up the adjustment of lending ratesis also discussed. [JEL: E43, E44, E52, E58]

T HE EFFECTIVENESSf monetary policy hinges on a set of crucialstructural parameters-not directly controlled by central banks-that reflect economic agents' reactions to policy impulses from money*CarloCottarelli s a DeputyDivisionChiefin the MonetaryandExchangePolicyAnalysisDivisionof theMonetary ndExchangeAffairsDepartment.Heis a graduateof the Universityof Sienaand holds a graduatedegreefrom theLondon Schoolof EconomicsandPoliticalScience.AngelekiKourelis s a Ph.D. studentat the Universityof Pennsylvania.Thispaperwas writtenduringher IMF summer ntershipat the Monetaryand Ex-changeAffairsDepartment.This paperbenefited from discussionswith Leonardo Bartolini and SeyedHosseinSamieiand fromcomments romWilliamAlexander,ErnestoFeldman,Sunil Sharma,and the participantsn a seminar held at the MonetaryandExchangeAffairsDepartment.Wethank heBankforInternational ettlementsfor providing ome of the data used in thispaper.

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CARLO COTTARELLIand ANGELIKI KOURELIS

markets.These structuralparameters(such as the elasticities of thedemandandsupplyof financialand realassetsto moneymarket nterestrates)are affectedby the structureof the financialsystem,that is, theexistenceanddegreeof developmentof financialmarkets, hedegreeofcompetition n these markets,and the availability f foreignsourcesoffinance. While economictheoryhasrecognized hisrelation,1 mpiricalevidenceon the subjecthas mainlyfocused on the effect of structuralchangesin financialmarketson the demandfor money (for example,Tsengand Corker(1991)).An aspectthathas been almostcompletelydisregarded2s the relationbetweenfinancial tructureand the speedofthe monetarypolicytransmission rocess.Thispapertakesupthis issueby focusingon how the financial tructure ffects he degreeof stickinessof bank endingrates,that s, thespeedat whichbank endingratesadjustto their long-runequilibriumvalue after a "shock"affectingmoneymarketrates.Recent economicliteraturehas stressedthat banks are not neutral"conveyors" f monetarypolicy mpulses BernankeandBlinder 1988),Bernankeand Gertler 1989),Bernanke 1993)).Consider, orexample,a monetarypolicytighteningreflected n an increase n moneymarketrates. Such a tighteningmay fail to containaggregatedemand or ex-changeratepressures f financial ntermediaries o not promptlyadjusttheir endingrates.3The reactionof financial ntermediariess, of course,moreimportantn developing ountries,wherethedirect inancial han-nelsbetweenprimaryendersandborrowers re imited,but it is farfromirrelevantnindustrial ountries. t is, forexample,notable hatbetweenJanuaryandSeptember1992,when mostEuropeancentralbankswerestriving o defend the exchangeratemechanism ERM)paritiesbyrais-ingmoneymarket ates,the differential etweenmoneymarketandbanklendingrates increased ubstantially by 100 basispointsin Sweden andthe United Kingdom,200 basispointsin DenmarkandItaly,and over300 basispoints n FinlandandNorway).Thissuggests hatlendingratesdid not fully adjustto the changes n moneymarketrates.Toanalyze he relationbetweenbank endingratestickinessandfinan-

'See, for example, Modiglianiand Papademos(1980), Vanhoose (1985),Kareken 1984),andFaig-Aumalle1987)).2An exception s Pelzman 1969).3It couldbeargued hat he behavior fthelending atebecomes ess mportantif the demand or bankdeposits s sufficiently lastic.An increasentreasury illrates will move depositsout of the bankingsystem, thus affectingaggregatedemandthroughthe availabilityof credit, ratherthan through ts cost. Thisargument,however,disregardshefact that nmanycountriesbankshave alargebuffer of governmentpaperthat can be sold to counterthe effect of depositchanges(Rodrigues 1993)).

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FINANCIAL TRUCTURE NDBANKLENDINGRATEScialstructure,we followa simpleapproach.First,we measure he speedof adjustmentof bank lending rates in 31 industrialand developingcountries,by regressing he lendingrateon a distributedag of moneymarketrates. Thisway,we estimate he effect on lendingrates of shocksin money marketrates, the so-called "multipliers,"when the shockoccurs,afterthreemonths,aftersixmonths,and nthelongrun.Second,weexplain hecross-country ifferencesn thesemultipliers yregressingthemon severalvariables elated o the structure f thefinancial ystem,suchas thedegreeof concentrationnthebanking ndustry, he existenceof constraints n capital lows andbarrierso entry,andthe sizeandtheefficiencyof themoneymarket.4We also examine he role ofadministra-tivelysetdiscountratesas instrumentshat"signal" hanges n thestanceof monetarypolicy, and their relation to banklendingratestickiness.Thepaper s organizedas follows.SectionI discusses everalchannelsthroughwhichthe financial tructure an affect the stickinessof lendingrates. Section II presentsthe model usedin the empiricalanalysisanddiscussessome econometricproblemsrelatedto its estimation.SectionIII summarizes he resultsof the time seriesregressionsused to measurethe degreeof stickinessof bank endingrates,whileSectionIV presentsestimatesof the cross-section quationexplaining he differencesn thedegreeof stickiness.Finally,SectionV summarizes he mainfindingsofthe paperand drawssome policyconclusions.

I. The Stickinessof BankLendingRatesand the FinancialStructureDefinitionof LendingRate Stickiness

The term "interestratestickiness"has takenon tworelated,but dis-tinct,meaningsnthebankingndustry.First, thasbeen used to indicatethat bankratesarerelativelynelasticwithrespect o shifts nthe demandfor bank loans and deposits.Second,it hasbeen used to meanthat, inthe presenceof a changeof moneymarketrates, bank rateschange bya smalleramount nthe shortrun(short-run tickiness),andpossiblyalso4 Thus, this paper is clearly related to the "bank structure-performance" liter-ature(see Heggestad 1979)andGilbert 1984)forsurveys,andShort 1979)fora cross-country nalysis).However,this literaturehas focusedon the relationbetweenfinancial tructure ndthe levelof bankratesor bankrate differentials.Whilethelevel is importantor the efficientallocationof resources, he dynamicpropertiesof the lendingrate are morerelevant orthe transmissionmechanismof monetarypolicy.

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CARLOCOTTARELLInd ANGELIKIKOURELIS

in the long run(long-runstickiness).In thispaperwe will refermainlyto the second definition.Morespecifically,we willfocuson the reasonsfor the existenceof "short-term"tickiness,an aspectthat we will showto be empiricallymore relevant hanits "long-run" quivalent.5Moneymarketrateswill be defined as rateson short-term inancialinstruments hat are not administrativelyontrolledbythe centralbank.We focus on these rates, ratherthan on administered hort-termrates(suchasdiscountrates),becausemarket-determinedatesare less likelyto be subjectto differentforms of "attrition" for example, politicalpressures) hat can delaytheiradjustment see also SectionII).The Relevance of the Financial Structure

The term "financial tructure"will be used fairly broadly o includesuch features as the degree of developmentof money and financialmarkets;the degree of competitionwithin the banking system, andbetweenbanksand otherintermediariesas affectedbyboth the regula-toryenvironmentandthe numberandsize of intermediaries);he exis-tenceof constraints n capitalmovements;and the ownership tructureof the financial ntermediaries.The relationbetweenthese featuresandbanklendingratestickinesscan be explained n fourdifferent,albeitrelated,ways.AdjustmentCostsand theElasticityof the Demand or Loans

The banking ndustry, ike anyindustry, acesadjustment osts whenprices (thatis, interestrates) change.The degreeto which these costsdelaythe adjustmentof lendingratesto changes n moneymarketratesdependson the elasticityof the demand or bankloans, which,in turn,dependson the structureof the financialsystem.Thisargumenthas been formalizedbyHannanandBerger(1991),onthe assumptionhat thebank oan market s characterized y monopolis-tic competition,that is, each bank faces a downward-slopingemandcurvefor its loans. In thiscase, a profit-maximizingank that does notface adjustment ostswillalways et the lendingrate at the pointwherethe marginalrevenueon loans is equalto an exogenouslygiven moneymarket nterestrate(Klein (1971)).Thus,the lendingrate wouldfollowmoneymarketrateswithoutdelay.6 n the presenceof fixedadjustment

5 As willbe shown, n most countriesendingratestend to adjustalmost ullyto moneymarketratechanges n the longrun.6However, n the monopolistic ompetitionmodel,the change n the lendingrate snotnecessarilyqual o thechangen themoneymarket ate(seeCottarelliand Kourelis 1994),p. 5).

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FINANCIAL STRUCTURE AND BANK LENDING RATES

costs, however,the lendingratewillchangeonlyif those costsare lowerthan the costs of maintaininga nonequilibriumate.If the demandfor loans is linear, the costs of preservinga nonequi-libriumrate are equal to 0.25g(Am)2,where Am is the changein themoneymarketrateandg is the derivativeof the demand or loans withrespect o the lendingrate(HannanandBerger (1989)).Thismeans thatthe greaterthe elasticityof demand for loans, the higherthe cost ofkeeping endingrates out of equilibrium. f we introducea time dimen-sion, the aboveargumentmpliesthat a bankwillprefernot to changeits lending rates if the discounted flow of lost profits arisingfrom anonequilibirumositionexceedsthe fixed costsof changing hoserates.Inincomplete inancialmarkets,demandelasticitys likelyto be lowerintheshortrunthan n the longrunbecause, nthelongrun,even inthinfinancialmarkets hereare alternative ourcesof financeto bankloans.But the differencebetween the short-andlong-runelasticitiesexplainswhylendingrates are stickier n the short run. If, in fact, the elasticityof demand ncreasesovertime, the cost of beingoutsidethe equilibriumin eachperiodandthe discountedvalueof the streamof lostprofitsalsorises overtime. A bank willdecideto raiselendingratesonlywhen thatpresentvalue exceeds the fixedcosts involved n changing hem;if theelasticityof demandis lower in the shortrun, the adjustmentwill bedelayed.Thus,the relationbetweenlendingrate stickinessand financial truc-ture is straightforward,s the financialstructureclearly nfluencestheelasticityof demand or loans.The demand or loans of each bank s lesselasticin markets hathave fewercompetitors,higherbarriers o entry,or no alternative inancesources(suchas other financialntermediaries,foreigncapitalmarkets,commercial aper,or bankers' cceptancesmar-kets). In such markets,lendingratesmay show a limitedresponsetochanges n moneymarketratesin the short run.AdjustmentCostsand Uncertaintybout FutureMoneyMarketChanges

In thepresenceof adjustment osts,bankswill notadjust heir endingratesif they perceivethat the changesin moneymarketratesare onlytemporary.The uncertainty egardinghe natureof moneymarket luc-tuationsprovidesan additional ink betweenlendingrate stickinessandfinancial structure. Interest rate movements in insufficientlyliquidmoneymarketswill be characterized yastrongrandomcomponentandwill not adequately ransmitmonetarypolicyimpulses,as policy signalswillbe lostin the noise of randommovements.As aresult, headjustmentof lendingrateswill be slower.

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Non-Profit-MaximizingehaviorThe conclusion hat banklendingratesadjustpromptly o changes nmoney marketrates is based on the hypothesisthat banksmaximizeprofit.However, heremaybe financial tructure onditionsunderwhichthis hypothesisdoes not hold. This may be the case, for example, inbanking ystemsdominatedbystate-ownedbanks, n which endingrateadjustmentsmaybe delayeddue to politicalpressuresor simpleineffi-ciency.In general,bankswill reactmorepromptly o changes n moneymarket onditionsfnon-profit-maximizingehavior spenalizedbymar-

ket forces. If market orces are weak(for example,becauseof barriersto entry,absenceof competition rom nonbank ntermediaries, r con-straints on internationalcapitalmovements),inefficiencywill not bepenalized,whichmayresult in lendingrate stickiness.OligopolisticCompetitionModels

Price stickinesshas often been considereda feature of oligopolisticmarkets,becauseof theunpredictableesponseof oligopolistic ompeti-tors to price changes, and/orthe fact that oligopolisticcollusionmaybreak down when pricesare changed.While there is not a monotonicrelation between the degreeof stickinessand the concentrationof thebanking ndustry, omestickinesswhen the marketdeviates romperfectcompetition,at least until a clear market leaderemerges, can be ex-plainedby this feature. It can also be argued hat, in oligopolisticmar-kets, the stickinesscan be reduced f the centralbank acts as a marketleader by signaling changesin the stance of monetarypolicy throughchanges n anadministered iscountrate,as the latterreduce he uncer-taintyabout competitors'responses.This argumenthas been used toexplain hestrongempirical elationbetweenthe discountrate andbanklendingratesobserved n manycountries.

II. The Empirical ModelModel Presentation

In orderto analyzethe relationbetweenlendingrate stickinessandfinancial tructure,ameasureof the degreeof stickinessn variouscoun-tries s necessary.To obtainsuch a measure,we beginwith thefollowingdynamicmodel for the lendingrate:

ii,t = i,O+ Pi,lii,t-1 + Pi,2mi,t + * + i,n+2mi,t-n + 3i,n+2+lAdi,t

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+ + Pi,n+3+jAdi,t_j-iUi,t, (1)


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FINANCIALTRUCTURE NDBANKLENDINGRATESwhere i,t,mitanddi,,are,respectively,helendingrate,themoneymarketrate, and the discount rate for country at time t. The index i rangesfrom1 to M, whereM is the numberof countriesncluded nthesample,while the time indext ranges rom 1 to Ti.7The firstdifferenceoperatoris signifiedby A, ui,ts an errorterm, and the pis areparameterswhosevalues vary across countries. Equation (1) reflects a fairly commonapproachto the modelingof the lending rate. Its steady state form(omittingthe errorterm) is:

ii = PO(1 - P1) + [(P2 + *' + Pn+2)/(1 - Pl)]m, (2)which s consistentwith themonopolistic ompetitionmodelrelating heloan rate to the moneymarket rate (that is, to the exogenouslygivenmarginal ieldof alternative ankassets,or to themarginal ost of funds).The fact thatno other variable s assumedto affect the lendingrate inthe longrunis of course a simplification.n a monopolistic ompetitionmodelof the bankingmarket, he lendingrate shouldalso be influencedbyshifts n the demand orloans, as well as by changes n the perceivedriskinessof loans. These variableswere omitted in order to keep theestimatedmodelsufficiently oncise.Thepossibleomissionof some vari-ablesexplainswhythe errortermin equation(1) cannotbe assumed obe seriallyuncorrelated.Wedo assume,however, hatuit suncorrelatedacross countries.8Thedynamic pecification eflectsapartialadjustmentmodel nwhich,alongwiththe laggeddependentvariable, he currentand severalof thelagged values of the money marketrate are included. In addition,apolynomialdistributed ag of the changein the discount rate is alsoincluded.Thisreflects hehypothesis,discussednSectionI, thatchangesin the discountrate speed up the adjustmentof lendingrates,with noeffect on theirlong-runequilibrium alue.Giventhe cross-country ifferencesn the 3s n (1), lendingrates willshow a differentdegree of stickiness n responseto shocks in moneymarketrates. The followingprocedurewas followedto derivesummarymeasuresof the degreeof stickiness.Fromequation(1) we derivedsetsof "multipliers"eflecting he adjustment f the lendingrateduring heperiodwhen themoneymarketratechanges impactmultipliers), nd at

7 Notice that the sample period varies across countries (see Section III).8This,of course,doesnot mean that the interestratesareuncorrelated crosscountries, but, rather, that the cross-country orrelationof interestrates istransmittedhroughmoneymarketrates.

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different imelags(interimmultipliers).Thesemultipliers re,ingeneral,deterministicnonlinear unctionsof the Bs:hi,e= 4([i), (3)

wherehieis the valueof the multiplierorcountry aftert periods; )(.)is a nonlinear unction(see Appendix);and i is a vectorof estimatedcoefficients or country . Weassumethat the valuetakenby the multi-pliers dependson the structuraleaturesof the financialsystem:hi,e= ZiYe+ vi,e, (4)

where Zi is a K-elementvector describingthe financialstructureofeconomy i and vi, is an errorterm uncorrelatedacrosscountries.Inmatrix ormequation(4) can be written,for different ags, as:ho = Zyo + vo; (5)he = Zye + ve; and (6)hL = ZYL+ VL, (7)

where ho is a vector of impact multipliers(t = 0); he is a vector of"interim"multipliers eflecting he adjustmentof the lendingrateafterf periods;andhL is a vector of long-termmultipliers eflecting he totaladjustment f lendingrates(all thesevectorshave M elements).Z is an(M x K) matrixof structural ariables,and the v vectors are (M x 1)vectors of homoscedasticresiduals,which are assumedto be indepen-dentlydistributednot only acrosscountries,but also across time lags.The mainfocus of thispaper s the estimationof the yvectorsdescrib-ing the relationbetween the structural ariablesand the h multipliers,that is, our measureof lendingrate stickiness. A two-stepestimationprocesswas followed. In the first step (Section III), equation(1) wasestimatedfor 31 countries.Then, by filteringthe estimatedP vectorsthroughequation (3), an estimatefor the h vectorswas derived. In thesecondstep (Section IV), the estimatedvectorswere regressedagainstthe structural ariables ncluded n Z.

Discussion of the ModelBeforemovingto the next section,some of the featuresof the aboveempiricalmodel must be discussed.

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Definitionof theMultipliersThe multipliersdefinedabove referto the effect of a changein themoneymarket ateforagivendiscount ate.Wefocusonthesemultipliersbecausethe stickinessof bank endingratesemergesmoreclearly n theabsenceof discountratechanges.Indeed,as arguedabove,oligopoliesare expectedto respondfairlyquicklyto changes n the discountrate.It could be arguedthat, from a policy perspective,the reaction oflendingrates to bothmoneymarketanddiscountrates shouldbe exam-ined, sincethey are both controlledby the monetaryauthorities.How-ever, the discountrateis often not a marketrate, but is set administra-tively. Unfortunately,administered atesmaythemselvesshow a highdegree of stickiness,as they may be subject to more direct politicalpressures,andoften requirecomplexadministrative rocedures.Thus,a transmissionmechanism enteredon discountratechangesmaybe lesseffectivethana transmissionmechanism elyingonlyon moneymarketchanges-hence the need to assessthe stickinessof lendingrates in theabsenceof changes n the discountrate.

The RelationBetween he 1 Coefficients nd the h MultipliersIn the abovemodel, the multipliersh, rather han the 13 oefficients,are modeledas a linear functionof the structural ariablesZ, becauseas discussedin Section I, there is a relation between the structuralvariablesandthe size of the adjustmentat different ags,whichis mea-suredby h. One couldbe temptedto assumea directrelationbetweenthe P3s ndthe Z matrixbut this wouldbe inappropriate.Consider,forexample,the followingdistributedagmodel(the i subscripts omitted,for simplicity):

it = PO+ f2mt + P3mt-1 + P4mt-2 + ut. (8)Supposethat the 13coefficientshad been modeleddirectlyas a linearfunctionof the variable ncluded n Z; for example:

33= Z4 + x. (9)Basedon the discussionn SectionI, we expectthat an increase n, say,variable Zkwill lead to a faster adjustment, that is, to a larger multiplierafter woperiods.Thisrequiresalarger um12+ 13withrespect o othercountriesbut it does not constrainthe value, or even the sign of thecoefficientof Zk in equation(9). An increase n Zkmay ead to a decreaseor an increase n 13,dependingon whether12 increasesby moreor lessthan 32 + P3. Since Zkaffects the sum of two coefficients, we cannot inferthe effect of Zk on one of the two.

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FINANCIALTRUCTURE ND BANKLENDINGRATESthe impactmultiplierho= 13owhosevariance s estimateddirectly romequation(1)), but is moreproblematicor the interimmultipliers, incethey are nonlinear functionsof the P coefficients.Consequently,thediscussionn SectionIV willfocusmainlyon the impactmultipliers,hatis, on the estimationof equation(5).NonlinearRelationbetweenh and Z

Equations(5)-(7) postulatea linear relationbetweenthe multipliershandthestructural ariablesZ. Oneproblemwiththisassumptionsthatfor certainvalues of the Z variables, he multipliers ouldbecomeneg-ative(implying hat the lendingrate declineswhenmoneymarketratesareraised).The standard olution to thisproblemwouldbe to imposeanonlinearrelationbetween h andZ, so that foranyvalueof Z, h wouldalwaysremainpositive.A simple wayof doingso is to assumethat therelationbetween h and Z is describedby a logisticfunction:h = c/[l + exp(-Zy)]. (10)

Thiswayh would be constrainedbetween0 and c (a fixedparameter).By takinglags, equation(10) couldbe linearized:

log(clh - 1) = -Zy (11)This approachwould not be problematicf h wereobserved,but, as itis not, the error term would enter equations(5)-(7) in a nonlinearfashion. The original inearformulationwas thereforemaintained.Aswill be shown,this does not seem to createproblems n the estimationof equation(5), as all fittedvalues remainedpositive.

III. Step One: Analysis of StickinessThe Data

Having aid out the schemeof the empiricalmodel,we canproceedtoits estimation. The estimation of equation(1) for differentcountriesrequiresmonthlyseriesof lendingrates,moneymarketrates, and dis-countrates.9These data mustbe available or a sufficiently ong periodduringwhichlendingrates were not administrativelyontrolledby the

9High frequencydata are needed because time aggregationmay bias theestimates. Moreover, for the purpose of policy analysis, monthly lags are cer-tainly more relevant than quarterly lags.

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centralbank10 nd no direct controls on the amountof credit were inplace.11This limitedthe samplesize to 31 countries,almostequallysplitbetweendevelopingand industrial ountries.It also limited the sampleperiod, sometimesto no more than two years.Three types of lendingrateswere used: posted primerates, postednonprimerates,andaverageratesactuallychargedon bank loans. Thefactthat these ratesmayshow differentdynamicpropertieswithrespectto money market rates was ignoredin the first step of the estimationprocess,butwas takeninto account n the secondstep(see SectionIV).The dataon moneymarketratesusuallyrefer to eithertreasurybill orinterbankrates. Discount rates referto interestrates on variousformsof last resortcredit fromthe centralbank.The stationarity f the above 93 series(threeseriesfor each of the 31sample countries)was assessed using augmentedDickey-Fuller ests.Sincealmostall theserieswere foundto benonstationary,he modelwasestimatednot only in levels but also in firstdifferences,which in mostcases wassufficient o removethe nonstationarity.12 e willrefer there-fore to two sets of results: "Model 1" results(estimates n levels), and"Model 2" results(estimates n firstdifferences).Estimation Results

Table1 shows the estimatedmultipliersof changes n moneymarketrates at different time lags for both Model 1 and Model 2. (Detailedresultsarepresented n Cottarelliand Kourelis 1994)).Withreferenceto Model1, columns1-4 report,respectively, he impactmultiplier, hemultiplierafterthree monthsand that aftersixmonths,andthe long-runmultiplier.Thesame nformationorModel2isreportedncolumns5-8.The lasttwo rows of the tablereportthe mean and the variation oeffi-

10n order o allowsome nitialadjustment f thelendingrateto itsequilibriumlevel after the removalof interestrate ceilings, the sample periodsused forestimate 1) incountrieshatexperienced eilings tartedatleast sixmonthsaftertheirremoval.n If directcontrolsareinplace,therelationbetween endingratesandmoneymarketrates is severed.This is because,in the absenceof creditrationing, helendingratewillbe determinedbytheintersection f thedemand orbank oansandthe administrativelyixed supplyof bankcredit. In this case, a changeinmoneymarketratesmaynot bringaboutanychange n the lendingrate.Thus,if the stickinessof lendingrateswereassessedduringperiodsof bindingdirectcontrols,the degreeof stickinesswouldprobablybe overestimated."2Theonlyexception s Poland,for which,due to the limitedsamplesize, itwasnotpossible oestimate hemodel nfirstdifferencesfirstdifferencesmodelsare likelyto require ongerdistributedags).

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CountryAustraliaBelgiumCanadaColombiaDenmarkFinlandGermanyGreeceHungaryIcelandIndonesiaIrelandIsraelItalyJamaica

Table1. Multipliers(Effect on the LendingRate of Changes n Money Mark

Model 1Impact 3-month 6-month Long-run Impact0.11 0.40 0.60 1.170.21 0.61 0.81 1.03 0.210.76 0.93 1.00 1.06 0.780.42 0.87 0.97 1.03 0.44

0.07 0.25 0.38 0.71 0.150.13 0.20 0.27 0.60 0.130.38 0.67 0.83 1.04 0.370.40 0.74 1.050.09 0.31 0.47 0.88 0.190.61 1.04 1.07 1.08 0.610.19 0.59 0.84 1.21 0.200.32 0.80 0.96 1.03 0.340.77 1.22 1.24 1.25 0.770.11 0.40 0.61 1.22 0.120.15 0.38 0.66 0.92 0.24


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Table 1. Multipliers concluded)(Effect on the LendingRate of Changesin Money Mark

Model 1Country Impact 3-inonth 6-month Long-run Impact

Japan 0.06 0.19 0.25 0.75 0.03Malaysia 0.16 0.29 0.39 0.91 0.13Mexico 0.83 1.40 1.34 1.29 0.72Netherlands 0.52 0.97 1.03 1.04 0.52New Zealand 0.09 0.48 0.60 0.67 0.11Philippines 0.27 0.75 0.81 0.87 0.24Polanda 0.04 0.15 0.24 0.59 -Portugal 0.28 0.77 0.97 1.12 0.47Singapore 0.27 0.71 0.83 1.00 0.27South Africa 0.61 0.79 0.88 0.99 0.73Spain 0.35 0.80 0.98 1.12 0.36Sri Lanka -0.22 0.28 0.30 -Swaziland 0.48 0.52 0.54 0.57 0.54UnitedKingdom 0.82 1.02 1.04 1.04 0.87United States 0.32 0.69 0.85 0.97 0.41Venezuela 0.38 1.03 1.30 1.48 0.24Mean 0.32 0.64 0.77 0.97 0.33Variation oefficient 0.79 0.51 0.40 0.25 0.78a Model 2 was not estimated or Poland.


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Table2. CorrelationetweenMultipliers(At different ags)

Model 1 Model 2ho h3 h6 hL ho h3 h6 hL

ho 1.00 0.89 0.77 0.46 1.00 0.80 0.70 0.63h3 1.00 0.96 0.67 1.00 0.92 0.88h6 1.00 0.80 1.00 0.93hL 1.00 1.00cient (that is, the ratio between standarddeviationandmean) of eachcolumn. The followingfeaturesare notable.ResultsRobustwithRespect o ModelSpecification

Models 1 and 2 yield very similarmeasuresof the multipliers.Thecorrelation oefficientbetween the impactmultipliers f Model1 and ofModel2 (thatis, betweenthe first and fifth columnsof Table1) is 0.97.The correlationcoefficientdeclinesslowlyat longerlags:it is 0.91 and0.86, respectively,orthree-and six-monthmultipliers ut remains airlyhigh(0.74)even for the long-runmultipliers.Thus,the resultsarerobustwith respectto differentmodel specifications.Degreeof StickinessHigh on Average

The degreeof stickiness s, on average,relativelyhigh.While, in thelongrun,thelendingrateseems to adjust ullyto themoneymarketrate(the long-runmultipliers, on average,0.97, andit falls within he rangeof 0.75-1.25 in threefourthsof all cases),the impactmultipliers onlyone-thirdof thelong-runmultiplier.13 roadly peaking, hisimplies hatin order to increase endingratesby 100 basispointsduring he monthof the moneymarketrateshock,the moneymarketratemust be raisedby 300 basis points. On average,after three months and six months,respectively,about one-third and one-fourthof the adjustmentre-mains to be completed. Moreover, the orderingof the countriesbydegreeof stickiness s not affectedmuchbythe lag at whichmultipliersare measured(see Table2).Strong Cross-CountryDifferences,Particularly t ShortLagsThere is muchcross-country ariationaroundthese averagevalues,particularlyorshorterags.Thestandard rror sabout80percentof themeanfor theimpactmultiplierbutdrops o 50percentafter hreemonthsand to 25 percentin the long run.Thus, countriesseem to differmore

13 Giventhe similarity f the resultsof the twomodels,we will commentonlyon the Model 1 estimates.

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CARLOCOITARELLInd ANGELIKIKOURELIS

in the short than in the long run. This has two implications. First, it sug-gests that the effect of different financial structurescan be better assessedby looking at short lags, rather than at long lags, a feature that will alsobe evident from the results of Section IV. Second, this result is consistentwith the fact that the strong short-run differences are due to adjustmentcosts or "inefficiencies," rather than long-rundifferences in loan demandelasticities. The effect of these adjustment costs and inefficiencies tendsto fade away in the long run.The differences among impact multipliers across countries cannoteasily be related to the degree of development of the economy. Focusingon the impact multipliers, the subsample of countries represented byhigher-than-averageperformers (that is, those with an impact coefficienthigher than 0.32) is almost equally split between industrial and develop-ing countries. The same is true for below-average performers. Clearly,an explanation of the cross-country differences must go beyond a simpleconsideration of the degree of overall development of the economy.Relevance of Discount Rate Changes

The effect of discount rate changes on lending rates for the countriesin which such a variable was significant is reported in Table 3. Thediscount rate appears to be a powerful instrument for speeding up theadjustment of the lending rate to money market shocks. The discountrate is significant in about one-half of the sample countries. Among theseTable 3. Effectof Changesn theDiscountRate

Impact0.200.681.250.450.230.250.360.630.070.691.030.190.150.320.49

Model 13 months

0.140.350.910.380.120.020.230.620.290.090.830.100.200.190.21

6 months0.110.170.660.320.070.010.070.460.260.010.660.060.050.110.09

Model2Impact 3 months 6 months0.27 -0.58 0.171.00 0.340.41 0.19-0.17 -

0.25 -0.51 0.19 0.060.09 0.33 0.180.51 -1.03 0.83 0.660.09 -0.19 --0.23-0.29 -Mean 0.47 0.31 0.21 0.40 0.34 0.30

CountryAustraliaBelgiumDenmarkFinlandGermanyIcelandIrelandItalyJapanNetherlandsPolandSouthAfricaSri LankaSwazilandUnited States

602

Mean 0.47 0.31 0.21 0.40 0.34 0.30


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countries, he average mpactmultiplierof a change n the discountrateis 0.47, and in some cases it is as high as 100 basispoints. When thediscount rate is changed,the percentagemultiplierrises to 89 percentfrom 26 percent, a threefold increasein the speed of adjustmentoflendingrates.One important eatureof the countries n which the discountrate issignificantmust be noted. In the absence of a discountrate change,lendingrates n thosecountries howa belowaverage esponse o moneymarketchanges. Their averageimpact multiplier s 0.26, against anaverageof 0.36for the othercountries,14hichsuggests hatthe stickinessof lendingratesandthe effectivenessof the discountratemaybe related.If a relationexists,it could beinterpretedn twoways.Onthe one hand,it couldbe argued hat, in the presenceof a weakfinancial tructure ndsticky lending rates, monetaryauthoritieshave to rely on publicizeddiscountratechangesto spurthe banking ystem.On the otherhand,itcouldbe claimed hat ncountrieswherethe centralbankhascustomarilyreliedon discountratesignals,bankshave become"addicted" o the useof thisinstrument,o theextent thatlendingratesarenotchangedunlessthe discountrate also changes.Both theseinterpretationsmplyanegativestatistical elationbetweenthe impact multipliersof moneymarketchangesand those of discountrate changes. The first interpretation,however,also implies that thestickinessof lendingratescan beexplainedpurelybylookingatstructuralvariables.If the financial tructure s responsible or boththe stickinessof lendingratesand the use of the discount rate as a monetarypolicysignal, t shouldbe possible o estimatea reduced ormequation nwhichthe money marketmultipliersare uniquelyrelated to the structuralvariables.However, his wouldnotbepossible f, inaddition o the effectof the financialstructure, he use of the discountrateas a policysignalfurtherreducesthe multipliers. n thiscase, a negativedummyequalto1whenthe discountrateis used asa "policysignaling"device shouldbesignificant,and with negative sign, in the regressionof SectionIV.

IV. StepTwo: Determinantsof the Stickinessof LendingRatesWenow focus on the factorsexplaining he cross-country ifferencesin the stickinessof lendingrates.

14Forthe countriesn which he discountrate is significant,here s a negativecorrelationbetweenthe sizeof the impactmultiplier f moneymarketratesandthose of the discountrate.

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StructuralVariablesSteptwo-the estimationof the relationbetweenmultipliers ndstruc-turalvariables-requiresthe identification nd measurement f the lat-ter. Based on the discussionin Section I, four groupsof structuralvariablesreflectinghedegreeof bankcompetition, he extentof moneymarketdevelopment ndtheopennessof theeconomy, hepublic/privatenatureof the banking ystem,andthe overalldegreeof developmentofthe financial ystem)havebeensingledout. Inaddition, t wasnecessaryto control for some additional factors affectingthe dynamicsof thelendingrates,such as the differentnflationarynvironment,he typeofthe lendingrate series usedin stepone, and the use of the discountrateas policysignal.Beforeproceeding,two caveats are necessary.First,whilethe rangeof structuralvariables ncludedis large (given the limitednumber ofobservationsavailable), t may not be exhaustive.Probably he mostimportantomission,due to insufficientdataavailability,s the absenceof variablesreflectingthe barriers o competitionbetween bank and

nonbank financial ntermediaries.This will have to be borne in mindwheninterpretinghe results.15Second,it must be stressedthat,while the followingvariablescanbedefinedas"structural,"heyarenot fixed over time. Thisdoes not createa problem n the majorityof casesin whichno majorstructural hange(suchas the removalof barriers o entry)occurred n the periodoverwhich hemultiplierswere measured.Thenthestructural ariables ouldbe measuredat anyperiodof time, and, indeed,were sometimesbasedon a singleannualobservation.However,when structural hangesoc-curredorwhenever nformation n the structural ariableswasavailableovertime,the structuralariableswerecomputedby usingaverage aluesoverthe sample period.16CompetitionwithintheBankingSystem

As in most studies of the relation between bankingstructureandperformance,he degreeof competitionwithinthe banking ystemwasproxiedbyvariablesmeasuringhe degreeof concentration f the bank-ingsystem,such asthe market hareof the largest ive banks(MARSH)

15Omittedariablesanbias heregressionesultsf theyarecorrelated iththeincluded ariables.Thismaybethecase,forexample,becauseregulatorsmayconstrain oththecompetitionwithin hebanking ystemand hatbetweenbanksandnonbanks.6See Cottarelliand Kourelis 1994)for furtherdiscussion,as well as for thevalue of the structural egressors.

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FINANCIALTRUCTURE NDBANKLENDINGRATES

and the numberof bankbranchesper 100,000 nhabitants NOBRA).Theexpectedsignis negative or the formervariableandpositiveforthelatter(the larger he concentration,he lowerthe degreeof competitionand therefore the lower the multipliers).17While thisis the standard pproach, hetheoryof contestablemarketsimplies hat marketconcentrationmeasuresare notgoodproxies ortheactualdegreeof competition.The reasonis thatconcentratedmarketscan behave ike competitivemarkets f firmsaresubjectto the threatofentryof newcompetitors.We havetherefore ncluded n the regressiona qualitativendexof the existenceof barrierso entry (ENTRY).Thisindex,ranging romzero(strongestbarriers o entry) o four(nobarriersto entry),reflects the legislationon the openingof new bankbranches(bothdomesticandforeign)existing neachcountry,andhas anexpectedpositive sign. Moreover, n some regression pecifications, he variableMARSHandNOBRA havebeen included n the followingform:MARSH*= (4 - ENTRY)*MARSH (12)NOBRA* = (4 - ENTRY)/NOBRA (13)

Equations(12) and (13) implythat the degreeof marketconcentrationbecomesrelevantonlyinthepresenceof barriers oentry.18 hestrongerthose barriers, he greaterthe impactof marketconcentrationon themultipliers.Extentof MoneyMarketDevelopment nd Opennessof theEconomy

The extentto which hemoneymarket sdevelopedhasbeen taken ntoaccount n twoways.First,avariablemeasuringhe sizeof the "randomcomponent"n themoneymarketrate series usedinthestepone regres-sorswasincluded(RANDO). The expectedsignof thisvariable s neg-ative: if the money market rate series are very "noisy,"the speed ofadjustment hould be lower.This is because,in the presenceof adjust-

17This s becauseof the lowerdemand lasticitynlesscompetitivemarkets ndthepresumedhigher tickiness foligopolisticprices.It hasbeen noted nSectionI that, while there are reasonsto arguethatoligopolisticpricesmaybe stickierthancompetitiveprices, hesameargumentmaynot holdformonopolistic rices(apartfrom the effect imputedto the lower demandelasticitycharacterizingmonopolies).Thus the relationbetweendegreeof stickinessand concentrationmay not be linear. To take this into account, absolute deviations from theMARSHsamplemeanhave beencalculated so thatveryconcentrated ndveryfragmentedmarkets would behave similarly).However,this has not yieldedsubstantially ifferentresultsfromthose reported n SectionIV.

18 Note that,in thisspecification,he expectedsignof NOBRA* is nownega-tive (as NOBRA appearsin the denominator),while the expected sign ofMARSH*continuesto be negative.

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mentcosts, bankswillonlyfollow interestratechanges hat arenot tooerratic.RANDO has been set equalto the standard rror(expressedasa percentageof the averagevalue of the money marketrate) of anARIMA model fitted on each moneymarket nterest rate series.19Thesecondaspectto be considered s the sizeof the market orshort-term negotiablefinancial nstruments ssuedby enterprises ENTMA)andotheragents(OTHMA),bothmeasurednrelation o eachcountry'sGDP.20The existenceof a market or short-term nstruments ssuedbyenterprises commercialpaperand bankers'acceptances)maybe rele-vant becauseit increases he elasticityof the demand or bank oans. Inthis case, if banksdo not adjustrapidlyto changesin money marketconditions, heymaybe disintermediated.The existenceof a market orothershort-termmarketable nstrumentsmainlycertificatesof deposit(CDs) andtreasurybills)mayalso be important.Theexistence of theseinstrumentsncreasesthe liquidityof enterpriseand householdport-folios, thus increasing he elasticityof demandfor loans. Moreover, fbanks raisea largeshareof their resources rom the issuance of CDs,whose interestratesrapidlyadjust o moneymarketconditions, heywillface largecosts if they delaythe adjustmentof theirlendingrates.An additionalvariable-CAPCO-has been introduced o capturethe barrierso foreigncompetition.Itsexpectedsignis negative; t takesthe value 1 in the presenceof constraintson capital lows andthe value0 otherwise.21BankingSystemOwnership

As more comprehensivemeasuresof the degree of public sectorownershipwere not readilyavailable,the public/privatenatureof thebankingsystem was measuredby a variable(PUBLI), equal to the19For simplicity, he same (2,1,2) ARIMAmodelwas fittedto all series.20 Toaccount orthepossibilityhatthesize of themoneymarket snotrelevantbeyonda certain evel, the abovevariableswere alsointroduced n the followingnonlinear orm:

OTHMA*= 1/(1 + )exp(-TrOTHMA)),thatis, througha logisticfunction.Thisspecificationmpliesthat,forveryhighas well as verylow levels of OTHMA,changes n the marketsize havelimitedeffect.The twoparameters andTrwereestimatedbyscanningi.e., byminimiz-ing the residual sum of squares). The estimated ( and ir implied a close linearrelationbetweenOTHMA*and OTHMA(for the actualvalues takenby thelatter nthecross-countryample),whichsuggestshatthe effectof OTHMAwasapproximatelyinear.21Noattempthas been made to differentiateby type of controlson capitalmovements. Annual information on this variable has been derived from Alesina,Grilli, and Milesi-Ferretti (1993).

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numberof the fivelargestbanks hatarepublic.Thisvariable sexpectedto be negativelyrelated to the impactmultipliers.Degree of Developmentof the FinancialSystem

In order to test the hypothesisthat lending rates adjust faster inmoresophisticated inancialenvironments,we includedvariablesmea-suringthe overall degree of developmentof the financialsystem. Astandard pproachwouldrequire aking he ratiobetweentotal financialassetsand GDP. Thismeasure,unfortunately,s notreadilyavailable orall countriesncludednthesample.We thereforeused threeproxies:percapitaGDP (GDPPC),whichusuallyexhibits a strongcorrelationwiththe ratio betweenfinancialassetsand GDP;22he ratio between broadmoneyand GDP (M2GDP),which is often used as a proxyfor the de-greeof financialdeepening e.g., De GregorioandGuidotti 1992));andthe ratiobetween broadand narrowmoney (M20M1), whichcapturesthe developmentof moresophisticateddepositinstruments.AdditionalVariables

Toidentify he effectof the abovefactors, t is necessary o control orthe existenceof other variables nfluencing he measuredmultipliers.First, wodummyvariableswere ntroducedo distinguish etween hetypeoflendingrateused nthesteponeregressions.The variablePRIMEtakesthe value1forposted primeratesandzero otherwise.It isexpectedto haveapositivesign,since ratesapplied o the best(i.e., higherdemandelasticity)customersarelikelyto react asterandbecause headjustmentcostsfor changingpostedrates are lower thanforchangingactualrates.The variablePOSTE akesthe value1 fornonprimepostedratesandzerootherwise.Its signis uncertainbecause the two factorsmentionedwithreferenceto the PRIME variablenow move in differentdirections.Second,adjustmentagsof nominalvariables nominalpricesor inter-est rates)arelikelyto be shorter n environmentsn which nflationhasbeenhighfor a numberof yearsand,consequently,ndexation s widelyused(Cecchetti 1986)).Structuralnflationwas measuredas the averageinflationrate during he 1980s(INFLA).Third,the variableEDISC was included o test thepossibility hatthe

multipliers lowerwhen the discount ate s used as asignalingdevice(thepossible "discount-rateaddiction"hypothesis noted in Section II).EDISC,which s defined as a dummyvariable akingthevalue1 forthe22 Forthe 32 countries onsideredbyWellons,Germidis,and Glavanis 1986),the correlation oefficientbetweenper capitaGDPandfinancialassets to GDPratiois 0.66.

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countriesin which the discountrate was significant n the step oneregressions,sexpected o haveanegative ign f the addictionhypothesisis true.Fourth,we also includedan additionaldummyvariable(DUSHO)equal to 1 for countriesin which the sample period of the step oneregressionwas shorter than two years. Thisvariablewas includedbe-cause, in the presenceof a laggeddependentvariable,OLSestimates,whileconsistent,are biased(theso-calledHurwiczbias).As discussednNickell(1981), hisbias slikelytoresult n anoverestimation f thespeed

of adjustment.Therefore,we expectthe signof DUSHO to be positive.Specification Search and Preferred EquationsImpactMultiplierEquation

Table 4 reportsthe estimates of equation(5), that is, the relationbetweenimpactmultipliersandthe structural ariables, or Model 1.23Followingthe "fromgeneral to specific"approach,the specificationsearch tartedwiththeinclusionof allexogenousvariablesistedabove.24The estimatesof the mostgeneralspecificationsarereportedas esti-mates(1)-(2) inTable4, referring, espectively,otheOLSandweightedleast squares(WLS)results.While the two estimatesare similar,it isconfirmedthat the use of OLS would have producedartificially owcoefficient standarderrors (and correspondinglyhigher t-statistics).However,evenestimate(2)presentsa remarkablyoodfit (theadjustedR2is 0.80, which is veryhighfor cross-sectionestimates)andlow stan-dard errors.25Of the 13 variablesincluded in the regression, onlyMARSH and GDPPChave a sign oppositeto whatwas expected.Ofthese, MARSH, whichmeasuresthe marketshare of the five largestbanks, sveryclose tozeroand snotsignificant,26eavingpercapitaGDPas the only significantvariablewiththe "wrong" ign.As recalled,this

23 See Cottarelliand Kourelis(1994)for the results obtainedusingModel 2estimates,which wereverysimilar.24However, iventhe limited numberof degreesof freedom,the alternativeproxiesfor the degree of financialdevelopment i.e., GDPPC,M2GDPandM20M1) were introduced ndividually.Table 4 only reportsthe resultsforGDPPC,as M2GDPandM2OM1wereneversignificant.TheDUSHOvariablewas also neversignificantand was dropped o savedegreesof freedom.25 Boththe adjustedR2 and the equationstandard rrorhave been expressedin terms of the originalresiduals, .e., those of the estimatenot adjustedforheteroscedasticitythe corresponding tatisticson the equationadjustedforheteroscedasticityook, of course,evenbetter).26For he givensamplesize, a 10 percentand a 5 percentsignificanceevelrequire -statisticsof 1.70 and2.04, respectively.

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Table4. Estimatesof Equation(5)(Dependent Variable: Impact Multipliers from Model

EstimationTechnique N Constant INFLA PRIME POSTE CAPCO RANDO ENTMA OTHMA PUBLI GDPPC MOLS 1 0.50 0.012 0.25 -0.34 -0.18 -0.031 -0.001 0.010 -0.056 -1.29

(4.09) (9.81) (4.63) (-5.69) (-3.49) (-5.73) (-0.09) (3.87) (-4.61) (-2.42) (WLS 2 0.51 0.013 0.22 -0.37 -0.21 -0.035 -0.003 0.013 -0.039 -1.50(4.35) (7.09) (3.22) (-3.93) (-3.07) (-5.45) (-0.43) (4.48) (-2.50) (-2.34) (WLS 3 0.30 0.012 0.22 -0.28 -0.15 -0.031 -0.002 0.011 -0.032 -(3.66) (6.18) (2.87) (-2.97) (-2.18) (-4.51) (-0.30) (3.57) (-1.90) - (WLS 4 0.30 0.012 0.25 -0.27 -0.12 -0.032 - 0.009 -0.022 - -(4.29) (6.85) (3.92) (-4.04) (-2.27) (-4.69) - (3.76) (-1.94) - -WLS 5 0.33 0.012 0.25 -0.27 -0.12 -0.032 - 0.009 -0.022 - -(5.17) (7.12) (5.01) (-4.04) (-2.13) (-5.93) - (4.05) (-1.77) -WLS 6 0.30 0.011 0.17 -0.29 -0.12 -0.025 - 0.013 -0.045 - -(4.07) (6.53) (3.50) (-3.86) (-2.01) (-4.28) - (5.48) (-5.04) - -OLS 7 0.31 0.011 0.20 -0.33 -0.18 -0.027 -0.002 0.011 -0.064 -0.54(1.98) (9.84) (4.58) (-5.24) (-3.36) (-4.97) (-0.27) (4.86) (-5.78) (-0.99) (WLS 8 0.45 0.012 0.15 -0.37 -0.21 -0.030 -0.002 0.015 -0.060 -1.33(2.60) (6.52) (2.38) (-3.44) (-2.78) (-4.72) (-0.27) (5.24) (-4.68) (-1.42) (WLS 9 0.26 0.011 0.15 -0.31 -0.15 -0.026 - 0.013 -0.046 -(3.41) (6.81) (2.97) (-4.21) (-2.45) (-4.60) - (5.76) (-5.26) - -

aIn estimates 7-9 this variable is adjusted for the existence of barriers to entry (see S


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variable acts as a proxy for the level of financial development, and thusis not important on its own. Therefore, it was dropped in estimate 3,without any major change in the other coefficients and t-statistics.In estimate (3), four variables (ENTMA, MARSH, NOBRA, andENTRY) are not significant. Therefore, ENTMA and MARSH (theleast significant of the group) are dropped in estimate (4), which raisesthe t-statistics for the remaining two variables. These, however, continueto be insignificant. It must be noted that NOBRA (the number of bankbranches) and ENTRY (reflecting the ease of opening bank branches)show a relatively high correlation,27 o that their lower significance, whenintroduced in tandem, may reflect problems of multicollinearity. Indeed,when the two variables are introduced separately in estimates (5) and (6),respectively, they each become significant at the 1 percent significancelevel. On account of the lower standard error and higher adjusted R2,estimate (6) will be considered the "preferred" equation.28In estimates (7)-(9), MARSH and NOBRA are replaced by theircorresponding values adjusted for the existence of barriersto entry (seeequations (12) and (13) above), but the resultsdo not change appreciably.ENTMA, MARSH* and NOBRA* remain insignificant. GDPPC is alsonot significant, while ENTRY is significant even in the most generalspecification. This confirms estimate (6) as the preferred equation.Interim and Long-Term Multiplier Equations

While the focus of this paper is on the impact multipliersfor the reasonsdiscussed in Section II, it is worthwhile to examine how the estimatedequations behave when applied to interim and long-term multipliers.29These estimates, reported in Table 5 (again, for Models 1 and 2)together with the preferred impact equations, show a much worse fit. Theadjusted R2 drops to 0.50 and 0.23), respectively, for the three- andsix-month multipliers, and becomes negative for the long-run multi-

27Theircorrelation oefficient s 0.52, meaning hat the numberof branchesis higher n countrieswithlower barriers o openingnewbranches.28It canbe notedthat the adjustedR2of estimate 6) is almostashighas thatof the overparameterizedstimate 2). This ndicates hat the significance f the"wrongly igned"GDPPCmayhave been spurious.29As noted in SectionII, the standarderrors of the estimated nterim andlong-termmultipliers re noteasilycomputable.Therefore, n the estimationofthe corresponding tep two equations,we adjusted or heteroscedasticitysingthestandard rrorsof theimpactmultipliers.This s not aproblemaslongas thestandarderrorsof the interimmultipliersare equal to those of the impactmultipliersup to a multiplicativeonstant.30Theuse of the adjustedR2, however,underestimates he portionof thedependentvariablevariance xplainedby the equation.Even forthe long-termmultiplier quation,the unadjustedR2remainsclose to 0.30.

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Table 5. Estimates of the Interim and Long-Term Multiplier(Dependent Variable: Multipliers from Model 1)

EstimationTechnique Multiplier Constant INFLA PRIME POSTE CAPCO RANDO OTHMAWLS Impact 0.30 0.011 0.17 -0.29 -0.12 -0.25 0.13(4.07) (6.53) (3.50) (-3.86) (-2.01) (-4.28) (5.48) (WLS 3-month 0.71 0.014 0.20 -0.24 -0.14 -0.036 0.021(5.66) (4.77) (2.29) (-1.90) (-1.33) (-3.60) (5.33) (WLS 6-month 0.80 0.012 0.18 -0.19 -0.13 -0.035 0.024(5.06) (3.34) (1.70) (-1.20) (-1.01) (-2.85) (4.80) (WLS Long-run 1.01 0.005 -0.02 -0.21 -0.23 -0.017 0.020(6.26) (1.43) (-0.19) (-1.27) (-1.71) (-1.35) (3.95)


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plier.30This is not surprising,as we noted that the variabilityof themultipliers crosscountries endsto fadeaway ntime,so that t becomesmore difficult(but also less relevant)to explainit. Nevertheless, t isnotablethat the signsand, to some extent, the significance f the coef-ficientsremainunchanged,particularly p to the six-monthmultiplierequation.Discussion of the Econometric Results

The above resultssupport he followingconclusions.Effectof InflationThe results indicatethat the speed of adjustmentof lendingrates ishigher ninflationarynvironments, result hatreplicateshatobtainedfor commoditypricesby Cecchetti(1986).In all of the abovespecifica-tions, the coefficient on INFLA is very significantand close to 0.01,indicatinghat anincrease n the structural ate of inflationby 10pointsraises heimpactmultiplierand ndeedthemultipliers pto sixmonths)by 10 basispoints.Typeof LendingRateThe resultsalso indicate hatthedynamics f theadjustment f lendingratesvary dependingon the type of lendingrate. Primeposted ratesadjustfasterthanactualrates(theirmultipliers almost20 basispointshigher,for up to sixmonths),whilepostednonprimeratesadjustmoreslowly,particularlyn the very short run (theirimpactmultiplier s 30basispointslower than for actualrates,and 20 basispointslowerafterthreemonths).Thisimpliesthat,whenassessing he effectivenessof thetransmissionmechanismof monetarypolicy, attentionmust be paidtothe type of lendingratefor which information s available.Onlyin thelong run do all rates tend to change by the same amount.Effectof FinancialStructure

Theeconometric esultsalso ndicate hatthestickiness f lendingratesis strongly nfluencedby the structure f the financial ystem,includingits regulatory nvironment.The effects of five structural ariableshavebeen identified(Table 6).31First,the stickinessof lendingrateshasbeen shownto be influenced31 Table6suggests hatthe effect of changesnthe different tructural ariablescanbe added.Whilethe estimatedmodel s, indeed,additive, t mustbe stressedthat additivityprobablydoes not hold for veryhighor verylow values of themultipliers see SectionII).

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Table 6. Effect of StructuralChangeson theLendingRateMultiplierStructuralChange Impact 3-month 6-monthRemovalof barriers o entry 0.14Privatization f the bankingsystem 0.23 0.34 0.27Removalof capitalcontrols 0.12Creationof a moneymarket(equalto 15 percentof GDP) 0.20 0.32 0.3650 percentreductionof "noise" on themoneymarketratea 0.13 0.18 0.18aReductionrom 10percent o 5percentnthe ratiobetween he standard rrorof the random omponentof themoneymarket ateseries and tsaveragevalue.

by the existence of constraints on competition among banks, and inparticular, by the existence of barriers to entry (measured here by con-straints in setting up new bank branches).32Based on the estimatedregression coefficients, a shift from a regime of ad hoc authorization inthe opening of branches to one of complete deregulation is estimated toincrease the impact multiplier by 14-19 basis points.33The actual degreeof concentration (measured by the market share of the five largest banks)seems to be less relevant. This is consistent with the view, stressed by thecontestable market school, that very concentrated markets behave likecompetitive markets as long as they are subject to entry threat.34Second, lending rates appear to be stickier in banking systemsdominated by state banks, which may reflect the relative inefficiency ofpublic banks or the existence of political constraints on interest rateschanges. Privatizinga publicly owned banking system would substantiallyincrease the flexibility of lending rates. The impact multiplier would beraised by over 20 basis points, and the effect would be even higher forthe three- and six-month multipliers.Third, capital controls reduce competitive pressures on the banking

32 As mentioned,similar esultshave been obtainedby usinga measureof theactualdiffusionof bankbranches.33 At higherorder ags,the effectsare essclearlydentified thecorrespondingt-statistics relow) although hesize of the estimated oefficientremainshighup

to the six-monthmultiplier.34 The existenceof barriers o interstatebranching, nd hence to competition,wouldbe one factorexplaininghe relativelyhigh degreeof stickinessof lendingrates n theUnitedStates(Table1),despitethe lowdegreeof marketconcentra-tion.The same conclusionholdsforItalyandJapan,which n thesampleperiodmaintainedstrongbarriers o the openingof new branches.In contrast,theCanadianbanking ystem,which s veryconcentrated ut characterized y rela-tively low entry barriers,exhibits a faster adjustment.For a more detaileddiscussionon the relationbetweenentrybarriers ndcompetitionn the UnitedStatesandCanada,see Shaffer(1993).

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system (arisingfrom foreign financialmarkets)and result in higherlendingratestickiness.The quantitative ffect of removingcapitalcon-trols,whilesignificant or the impactmultiplier, s relativelycontained(12 basispoints),and is statisticallynsignificant fterward.However, tmust be recalledthat the capitalcontrolvariablehas been measured na very impreciseway, whichmay explainthe relativelyhigh standarderror of the corresponding oefficient.35Fourth, he developmentof a market or short-termnstrumentspar-ticularlyCDs andtreasurybills)also enhancesthe flexibilityof lendingrates. Fora marketas largeas, say, 15percentof GDP, theeffect wouldbe between20 and 30basispointson allmultipliers pto sixmonths.Wewere unable to identify anyeffect of markets or short-termnegotiableinstruments ssued by enterprises.One possible interpretations thatthese instruments particularlyommercialpaper)are issuedmainlybyvery large enterprises,while in manycountries, he bulk of commercialbank loans is grantedto medium-sizedand small enterprisesand tohouseholds.

Fifth,quiteintuitively, endingratesdo not followmoneymarketratesthat moveveryerratically. f the ratio betweenthe standard rrorof therandom omponentof themoneymarket ateandtheaverageof the sameratedeclinesby5percentagepoints,themultipliersncrease ubstantially(10-20 basis points dependingon the lag and the model). Thus, thegrowthof the moneymarketcanspeed up the responseof the bankingsystem by reducing he volatilityof the moneymarketrate (undertheassumptionhatinterestratevolatility s, ceterisparibus, ower n largermarkets).In general, the transmissionmechanismwill benefit fromavoidingexcessive fluctuationsof moneymarketrates.Role of the Discount Rate

One featureof theregressionspresentednTables4-5 is thestatisticalsignificance,and the negativesign, of the coefficientreflecting he dis-countratepolicyof the centralbank. The estimatedcoefficient mpliesthat the use by the central bank of the discountrate as a monetarypolicysignalreducesthe responseof lendingrates to changes n moneymarket rates (when the discount rate is not moved) by 15-30 basispoints (dependingon the lag and model specification).The fact thatthis result has been obtained after controlling or a large number ofstructuralvariablesaffectingthe stickiness of lending rates supportsthe "discount-rateaddiction"hypothesis put forwardat the end ofSection III.35 ndeed,whilethe t-statistics f CAPCOfallafterthe impactmultiplier,heestimatedcoefficientremainshigh.

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T-able . UnitedKingdomand Canada:Estimatesof the Lendin(In percent)

Sampleperiod N Constant i m m- Ad dUnited Kingdom

72:10-78:03 1 0.72 0.63 0.77 -0.41 -0.01 ---(2.10) (6.68) (7.46) (-2.80) (-0.09) --78:04-81:02 2 0.10 0.99 -0.01 0.95 ---(0.73) (39.52) (0.11) (0.38) (32.73)78:04-81:02 3 0.98 0.03 --- 0.97(5.26) (0.15) - - (5.40)81:03-93:03a 4 0.87 0.38 0.86 -0.23 - ---(5.16) (6.04) (18.82) (-3.53) - --Canada

73:01-80:02 5 0.14 0.93 0.01 0.05 0.95 ---(1.28) (34.98) (0.09) (0.53) (8.58) -73:01-80:02 6 0.12 0.95 --- 0.93(1.20) (28.79) - - - (16.73)80:03-91:10 7 0.13 0.76 0.01 0.26 0.79 ---(1.45) (17.51) (0.14) (4.51) (13.11) -aA dummyvariable n January1985was also included(see AppendixIII in Cottarelli


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It could be argued hat,based on the estimatedcoefficienton EDISC,the stickinessattributedto discount-rateaddictions s relativelycon-tained,and thatit is a reasonablepriceto payforaneffective nstrumentsuchas an administrativelyontrolleddiscountrate. However,the dis-countrate san effective nstrument nlyinsofaras it canbeflexiblyused.But, asarguedabove,administered atesmaybe relatively ticky.More-over, the estimatedeffectof the discount-rate ddictionreportedabovereflects the average response of the bankingsystemsincluded in thesample,and it maythereforeunderestimate he effect in specificcoun-tries. Furtherevidence on this point can be derivedby reviewing heexperienceof two countries n which hediscountratewasused,butonlyfor some periods,as an administered ignalingdevice.Table7focuseson the relationbetween helendingrate,moneymarketrates, andthe discountrate in the United Kingdomand in Canada. Inthe UnitedKingdom,betweenOctober13, 1972,andApril11, 1978,thediscountrate(thatis, the MinimumLendingRate of the Bank of Eng-land,orMLR)wasset at 0.5 percentabove the average reasurybillrateat the most recent tender(Temperton 1991),p. 162),and thus did nothaveany independent ignalingeffect. As indicatedbythe firstestimateof the table, the lendingratein thisperiodwasprimarilynfluencedbythemoneymarketrate,with arelatively hortadjustmentag (theimpactmultipliers 0.77). The MLRwas administered etweenApril11, 1978,and August 20, 1981. Clearly,in this period, the relevanceof moneymarketratesdropped equation 2)), andthe MLRbecame he referencerate for banks. Indeed, the lendingrate adjuststo the MLR almostsimultaneouslyequation(3)). Whilethismaybe believedto be anidealconditionfor a centralbank, Temperton 1991)notes that:

Disenchantmentwith thisregimesoonset in. Changesn the official nterestrate onceagain ook ahighpoliticalprofileandthisledto problemswiththeconductof monetarypolicy.... On 20August,1981, twas stated hatMLRwould no longerbe announcedcontinuously:greaterreliance was to beplacedon market orcesin the determination f interestrates,... (p. 163).Equation(4) showsthat, after the suspensionof the MLR in August1981,moneymarketrates once againbecame the maindeterminantoflendingrates,withveryshortadjustment ags.3636 n the late 1980s, a new administered rate (the so-called Band One Stop Rate,which s the minimum ate at whichthe Bank of England s willingto discountbills of less than 14 daysmaturity)gradually mergedas a signalingdeviceofmonetary policy changes. This rate has been shown to affect money market andbankinterestratesquiterapidly Dale (1993)).The differences omparedwiththe MLR are that the changes in the Band One Stop Rate, while closely moni-tored by financial markets, do not receive the same attention by the media andhave a lower political impact, and therefore can be used more flexibly.

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Canada's xperiencewassimilar.Until March1980,the discountratewas set administrativelyndplayedthe role of signalingchanges n thestanceof monetarypolicy(FreedmanandDingle (1986), p. 28). Beforethatdate, moneymarketratesdid not appear o influence endingrates(equation(5)). Indeed, the level of the lendingrate appearedto berelateduniquelyto the level of the discountrate (equation(6)). In thefollowingperiod,thediscount atewas ndexed othe levelof thetreasurybillrate,thuslosingits role as a policysignal.As illustratedbyequation(7), during he 1980s,lendingrates were still statistically elated to thediscount ate,now to beinterpreted s aproxyof the mostrecent reasurybill auction rate (see CottarelliandKourelis(1994),Appendix III).These resultsconfirm he quantitative elevanceof the discount-rateaddictionhypothesis.When the discount rate is used as a signalingdevice, banks become less reactive to moneymarketchangesthat areunaccompanied y discountratechanges.37

V. Conclusionsand Policy ImplicationsThe stickinessof lendingrateswithrespect ochangesnmoneymarketrateshas often been seen as a serious mpediment o the smooth trans-missionof monetarypolicy impulses.Yet, no systematicattempthadpreviouslybeen made to measure the differentdegreeof stickinessoflendingratesacrosscountriesor to explain he observeddifferences.Thispaperhasattempted uch ameasurement nd,bydoingso, hasprovideda yardstickagainstwhichthe degreeof lendingrate stickiness n indi-vidual countriescan be assessed. It has shownthat the degreeof sticki-ness is quite differentacrosscountries,particularlyn the very short

run. The impactmultiplier definedas the changein the lendingrateobservedduring he month in whichthe moneymarketratechanges) sclose to unityin some countries(i.e., the adjustments completedinalmostone month)but as low as zero in others. Significantdifferencescan stillbe observedafter threeand six months,while, in the long run,the adjustment ends to be close to unityfor most countries.The paper has also documented the existence of a strongrelationbetweenthe degreeof interestrate stickinessand the structureof thefinancial ystem.Five structural eatureshavebeen singledout asbeingparticularlyelevant nincreasingendingrateflexibility:he existenceof37 Admittedly, heaboveresultsmayoverstate he loss of significance fmoneymarket ates n thepresenceof an administered iscount ate.Most ikely,bankswouldstopusing hediscount ateasareference ate f the latterweremaintainedexcessivelyout of line withrespectto moneymarketrates. In thisrespect, t isinteresting o note thatbetween1978and 1981,the Bank of EnglandkepttheMLRrelativelyclose to moneymarketrates(Spencer(pp. 55-57)).

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CARLO COTIARELLI and ANGELIKI KOURELIS

a marketfor negotiableshort-term nstruments particularlyCDs andtreasurybills);thecontainment f "unnecessary"rrandomluctuationsinmoneymarket ates; he absenceof constraints ninternationalapitalmovements; he absence of constraintson bank competition(particu-larly,barriers o entry);andprivateownershipof the bankingsystem.Market oncentration ndthe existenceofmarkets orinstrumentsssuedby enterprises forexample,commercialpaper)did not appear o affectloan rate stickiness.These results were obtainedaftercontrolling orstructuralnflation(whichtends to speedup the adjustmentof lendingrates)and for the type of lendingrates used (posted primeratesadjustfasterthan actualrates,which n turnreactfasterthannonprimepostedrates).These resultsadda newdimension o the relationbetweenregulationpoliciesandmonetarypolicy.Theanalysisof thisrelationhas,in thepast,focusedon the aspectof "soundness,"hatis, on the fact that the finan-cial systemmust be resilientenoughto sustainstrongmonetarypolicymeasures"until heybeginto bite"(Revell (1980),Gardener 1978)).Wefocusedprimarily nthe relationbetweencompetitionandefficiency,onthe one hand,andmonetarypolicy,on the other.Basedon ourresults,the transmissionmechanismof monetary policy can be enhancedbypoliciesaimedatenrichinghefinancial tructure f newmarkets partic-ularly or short-termmarketablenstruments), ndbyremovingbarriersto competition(such as barriersto entry and constraintson capitalmovements).Privatization oliciesalso appear o affect the responsive-nessof lendingratesto monetarypolicystimuli,possiblybecauseprivatebanksare more efficient,or becausethey are less subjectto politicalconstraints.

Policies aimed at reducingmarketconcentrationdo not appear o beuseful,possiblybecausecompetition s bestguaranteedby the threatofentry,both on local and nationalmarkets,rather hanby increasinghenumberof nationalcompetitors.Therefore,policies avoringbankmerg-ers, such as those implementedby some Europeancountries n the lastfew years,maynot be inconsistentwithcompetition.It hasbeen shownthatthe presenceof a highlevelof noise in moneymarket rates weakens their role as conveyersof monetarypolicy im-pulses, possiblybymaking t more difficult orbanksto identifydurablechangesninterestrates.Theremay hereforebe a caseforpoliciesaimedat smoothingmoneymarketrate fluctuations.38The above results also have implications or the shift from direct toindirectmonetarycontrols.Directcreditceilingswere common n many38These policies may include structural regulatory changes, such as reserveaveraging and lagged reserve requirements.

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FINANCIAL TRUCTURE ND BANKLENDINGRATES

industrial ountriesduring he 1960sand1970s,andarestillwidelyusedin developingcountries.As noted in a BIS reportof the early1970s:... quantitativereditceilings... areseen to have theadvantage f helpingto limit hegrowthofcreditandthemoneysupplymorequicklyandpreciselythan wouldbe possibleby the use of conventionalmonetary nstrumentsactingthroughbankliquidityandinterestrates(BIS (1971),p. 1).

Oneof the reasonsfor the system's imitedresponsivenesso changesin indirectmonetary nstruments s the stickinessof banklendingrates.However,asarguedabove,thisstickiness houldnotbe taken orgrantedas it is influencedbyfactors hat can be modifiedby structural eforms.Thus, before rulingout the possibilityof shiftingto indirectcontrols,consideration hould be givento structural eformsaimed at enhancingthe transmissionmechanismof indirectmonetary nstruments.Finally, hepaperalso hasimplicationsor the useof the discountrateas amonetarypolicy nstrument.Bysignalingundamentalhangesn themonetarypolicystance,administrativehanges nthe discountratestim-ulatetheresponseof lendingratesto moneymarketchanges.Therefore,in countries n whichlendingratesare stickydue to the weaknessesofthe financialstructure, here is a strongcase for usingan administereddiscountrateas partof the centralbankpolicyarsenal,untilthe effectof structuralinancial eformsgradually egins o bite.At the sametime,evidencehas been presentedsupportinghe so-calleddiscount-rate d-dictionhypothesis,namelythat the repeateduse of the discountrate asa policysignalweakensthe responseof banksto moneymarketchangesthat are not accompaniedby discount rate changes. This may be aproblem ormonetarypolicybecauseadministered iscount atesmaybemoreeasilysubjectto politicalpressuresof various orms,andpresentsome degree of stickiness.Thus, in countriesin which the structuralbarrierso lendingrateflexibilityhave been removed, hereis a caseforde-emphasizinghe discountrate aspolicysignal, orexample,bylinkingit to moneymarketrates.

APPENDIXRelationBetween the y Coefficientsat DifferentLags

As discussedin Section II, the y coefficients,expressingthe relationshipbetweenstructural ariablesand "multipliers" t different time lags, are notindependent cross ags.Toexplore hisrelationship,et usconsider hesimplestpartialadjustmentmodelfor the lendingrate:39i= lii_l + P2m (A.1)39All of the followingequationsshouldbe consideredas referringo a singlecountry; or simplicity he subscript used in SectionII has been dropped.

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CARLOCOTTARELLInd ANGELIKIKOURELISwhere is thelendingrate,andm is themoneymarket ate. Theimpactmultiplier(ho)andthe interimmultipliersup to lag2 (hl,h2) 40can be expressed n termsof p coefficientsas:

ho= P2 (A.2)hl= P2(1+ P1) (A.3)h2= P2(1+ P1+ P12). (A.4)

Consistentlywithequation(4) in SectionII, the multipliers re expressedas afunctionof the structural ariables twoin thisexample),denotedas zl andz2:ho= yolzl + 'o2Z2+ Eo (A.5)hi = yllZl + y12Z2 E1 (A.6)h2 = Y21Zl + Y22Z2 + E2, (A.7)

whereEo,El,andE2aretheerror erms.Bycombiningquations A.2)-(A.4) with(A.5)-(A.7) the relationbetweenthe p and the y coefficientscanbe writtenasfollows:P2 = YOlZ1+ Y02Z2+ Eo, (A.8)P2(1+ Pi) = yllZl + '12Z2+ El, and (A.9)P2(1+ P1+ P12)= Y21Zl '22Z2+ 62. (A.10)

Usingvectornotation,equations(A.8)-(A.10) can be rewrittenas:2 = Z'yo+ eo, (A.11)

P2(1+ Pi) = Z'yi + e1,and (A.12)P2(1+ P + P12)= Z'y2+e2, (A.13)

where yo= [YO1,Y02]', / = [y11,Y12]',Y2= [Y21,Y22]',nd Z' = [z1,z2].From equa-tions(A. 11)and(A. 12),thefollowing elationbetweenyoand / canbe derived:(Z'yo + Eo)(l + pi) = Z'yi + 61; (A.14)

and from(A.12), (A.13), and (A.14):(Z'yo + EO) (Z'yi + e1)+ [(Z'yi + el)2/(Z'yo + eo)] = Z'Y2+ E2. (A.15)

Equation A.15)showsthat the relationbetweenyo,yl, and Y2does not involveanyfurther nformation ntheps. However, heelementsof Y2annotbederivedfrom /yondyl becausethe constraint et by (A.15) is on linearcombinations fthe elements of the y vectors and not on the elements of the vectors.

REFERENCESAlesina, Alberto,VittorioGrilli,and GianMariaMilesi-Ferretti,ThePoliticalEconomyof CapitalControls,"CEPRWorkingPaperNo. 793 (London:Centrefor EconomicPolicyResearch,June1993).

40Westop at lag 2 for simplicity's ake. The algebrabecomesincreasinglycomplicatedat longer lags.

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, "Deposit,Credit,and InterestRate DeterminationUnder AlternativeBank ObjectiveFunctions," n MathematicalMethods n Investment ndFinance,ed. by G.E. Szergoand K. Shell (Amsterdam:North-Holland,1972), pp. 430-54.Nickell,Stephen,"Biases n DynamicModels with FixedEffects,"Economet-rica, Vol. 49 (November1981), pp. 1417-26.Pelzman,Sam,"TheBankingStructure nd the Transmission f MonetaryPol-icy,"Journalof Finance,Vol. 14 (June1969), pp. 387-411.Revell, Jack,"TheComplementary atureof Competitition ndRegulationntheFinancialSector," n CompetititionndRegulationn FinancialMarkets,ed. by A. VerheirstraetenLondon:Macmillan,1980).Rodrigues, Anthony, "GovernmentSecurities Investmentsof CommercialBanks," FederalReserveBank of New YorkQuarterlyReview,Vol. 18(Summer1993),pp. 39-53.Saxonhouse,GaryR., "EstimatedParameters sDependentVariables,"Amer-ican EconomicReview,Vol. 66 (March1976),pp. 178-83.

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Tseng,Wanda,and RobertCorker,FinancialLiberalization,MoneyDemand,and MonetaryPolicy in Asian Countries,IMF OccasionalPaperNo. 84(Washington:nternationalMonetaryFund,July 1991).

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Documents

Financial Structures, Bank Lending Rates and Transmission Mechanism