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2023-04-28 来源：爱问旅游网

Int.Fin.Markets,Inst.andMoney38(2015)42–64

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JournalofInternationalFinancialMarkets,Institutions&Money

journalhomepage:www.elsevier.com/locate/intfin

Doesstockmarketliquidityexplainrealeconomicactivity?NewevidencefromtwolargeEuropeanstockmarkets

NicholasApergisa,PanagiotisG.Artikisb,∗,DimitriosKyriazisc

abc

BusinessSchool,NorthumbriaUniversity,NewcastleuponTyneNE18ST,UK

DepartmentofBusinessAdministration,UniversityofPiraeus,80Karaoli&DimitriouStreet,18534Piraeus,Greece

DepartmentofBankingandFinancialManagement,UniversityofPiraeus,80Karaoli&DimitriouStreet,18534Piraeus,Greece

article

info

abstract

Articlehistory:

Received18December2013Accepted14May2015

Availableonline19May2015

Keywords:

StockmarketliquidityEconomicconditionsUKmarket

Germanymarket

Thispaperexaminestherelationshipbetweenstockmarketliquidity,whichproxiesfortheimplicitcostoftradingshares,withmacroeconomicconditions.WeprovideevidencethatstockmarketliquiditycontainsstrongandrobustinformationabouttheconditionoftheeconomyforboththeUKandGermanyinthepresenceofwell-establishedleadingindicators.Ourﬁndingsexemplifytheimportanceofsmallcapﬁrms’liquidityinexplainingthestateoftheeconomyandsupportthe“ﬂight-to-qualityargument”.Finally,theempiricalﬁndingsshowthatthereisnotanydifferentialroleofliquidityinexplainingthecourseofmacroeconomicvariablesbetweenacapitalmarketandabank-orientedeconomy.

1.Introduction

Theexistenceofanilliquidityriskpremiumiswelldocumentedintheliterature,inthesensethatilliquidstockscommandhigherexpectedreturnsthanliquidstocks(e.g.,AmihudandMendelson,1986;Amihud,2002;Chordiaetal.,2005;KempfandMayston,2008;PastorandStambaugh,2003;AcharyaandPedersen,2005;Papavassiliou,2013).Theliquidityshockhypothesisarguesthatsuddendropsinassetmarketsliquiditycauseequitypricestofallandthepriceofliquidassetstorise(KiyotakiandMoore,2008).Moreover,inaworldwhereﬁrmshavetocopewithﬁnancingconstraintsontheirinvestments,thisfallinequitypricesreducesthefundsforinvestmentsaﬁrmcanraisebyissuingequityand/orusingequityascollateralinborrowing.Asaresult,investmentsfall,outputfollowsandarecessionstarts.Theliquidityshockhypothesishasreceivedwideattentionbecauseofitsimmediatepolicyimplications.Ifunexpectedﬂuctuationsinequityliquidityarethecauseofeconomicgrowth,thenagovernmentcanattenuatetheeconomicperformancebymakingthesupplyofliquidassetscountercyclical.Attheonsetofarecession,agovernmentcanuseliquidassetstobuyupsomeoftheilliquidequitytopreventequitypricesfromfallingprecipitously.Theincreaseinthesupplyofliquidassetsrelaxesﬁrms’ﬁnancingconstraints,whilethestabilizationofequitypricesfurtherimprovesﬁrms’abilitytousetheequitymarkettoﬁnancetheirinvestmentprojectswithlowercostofcapital,thus,increasingthereturnontheprojectstheyadopt.ThesepolicyimplicationsseemtoprovideajustiﬁcationforthelargeandrepeatedinjectionsofliquiditybytheUSFederalReserveSystemaswellasothercentralbanksovertherecessionaryperiod2008–2009.

Thegoalofthisstudyistoinvestigatetheinformationcontentofstockmarketliquidity,basedonﬁrm-leveldata,toexplainthecourseofeconomicactivity,aftercontrollingforanumberofequity(i.e.,marketriskpremium,stockmarket

∗Correspondingauthor.Tel.:+302104142200.

E-mailaddresses:Nicholas.apergis@northumbria.ac.uk(N.Apergis),partikis@unipi.gr(P.G.Artikis),dkyr@unipi.gr(D.Kyriazis).

http://dx.doi.org/10.1016/j.intﬁn.2015.05.002

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

volatility)andnon-equity(i.e.,housingstarts,termspread,short-terminterestrates,defaultspread)factors.Indoingso,weapplyalternativeliquidityproxiestodifferentindicatorsofeconomicactivity,whileweutilizeasampleofstocksoriginatingfromtwoofthelargestEuropeanstockmarkets,i.e.theLondonStockExchangeandtheDeutscheBörse,spanningtheperiod1994to2011and1997to2011,respectively.

Therationaleforexaminingwhetherstockmarketliquiditycanactasaleadingindicatorforeconomicactivityisthreefold.First,accordingtothe“ﬂighttoquality”hypothesisputforwardbyLongstaff(2004),investorstendtoshifttheirportfoliostomoreliquidsecuritiesinturbulenttimesofeconomicactivity.Second,liquiditycanaffecteconomicactivitythroughcertaininvestmentchannels,sincealiquidsecondarymarketmayfacilitateinvestmentsinproductivelong-runprojects(Levine,1991).Third,BrunnermeierandPedersen(2009)showthatduringperiodsofeconomicdownturn,bothalackofassets’marketsliquidityandreducedﬁnancialintermediaries’fundingliquidityleadtoliquidityspirals.

TherelationshipbetweenstockmarketliquidityandeconomicactivityhasattractedlimitedattentionintheliteratureandcertainstudieshavefocusedeitheronUSdataoronsmallmarkets,suchasNorwayandSwitzerland.Beberetal.(2011)ﬁndthatanorderﬂowportfolio,basedoncross-sectormovements,canpredictthestateofthemacroeconomy.Inasimilarstudy,KaulandKayacetin(2009)showthattwoalternativeorderﬂowmeasurescanpredictGDPandindustrialproductiongrowth.Næsetal.(2011)usealternativeliquiditymeasures,bothfortheUSandNorway,anddocumentthatstockmarketliquiditycanserveasaleadingindicatorforthemacroeconomicvariables.Meichleetal.(2011)ﬁndthatstockmarketliquidityisthemainpredictorforeconomicactivityforSwitzerlandovertheperiod1990–2010.Morerecently,Florackisetal.(2014a)ﬁndthatstockmarketilliquiditycanbetterexplainandforecastthefutureUKGDPgrowththananyothervariableusuallyexamined(i.e.,termspread,short-terminterestratesandrealmoneysupply)andconﬁrmastatisticallysigniﬁcantnegativeassociationbetweenthesetwovariables.

Takingintoaccountthattheassociationbetweenstockmarketliquidityandmacrovariableshasattractedlimitedinterestintheliterature,furtherevidenceisneededintermsofmarketselection,methodologicalapproachesandthesampleperiod,inordertofullyunderstandthisassociation.Thepresentstudycontributestotheliteraturetowardsthisendinanumberofways.ItisclearfromtheabovediscussionthattherelationshipbetweenstockmarketliquidityandmacrovariableshasbeenexaminedmainlyinaUSsetting.Thus,weshedfurtherlightintheliteraturewiththeuse,fortheﬁrsttime,ofdatafromtwolargeEuropeanstockmarkets,theUKandGermany.TheLondonStockExchange(LSE)andtheGermanstockexchange(DeutscheBörse)areselectedonthegroundsthatalthoughtheyaremajormarketsofgreatinternationalimportanceandinterest,rankingamongtheworld’slargestintermsofnumberofﬁrmslistedandtotalmarketcapitalization,theyhavealargerliquidityeffectandhavenotbeencross-examinedinthepreviousempiricalliterature.

Anothersigniﬁcantnoveltyofthepresentpaperisthatfortheﬁrsttimeweprovideaninterestingcomparisonoftheinformationcontentofstockmarketliquidityforeconomicactivitybetweenacapitalmarketorientedeconomy(UK)andabankingorientedeconomy(Germany).Ithasbeenargued1thatthetypeoftheﬁnancialsystem(i.e.,marketvs.bankbased)inﬂuenceseconomicgrowth,whileanumberofempiricalworksshowthatthedistinctionisirrelevant,atleastforthecaseofdevelopedandmaturemarkets(BeckandLevine,2002).Theissueexaminedinourstudyiswhetherweshouldexpectthatstockmarketliquiditycouldbehavedifferentlyinabank-basedsystem,suchasinGermany,thaninamarket-basedsystem,suchasintheUK,basedonthefactthatliquidityisexplicitlyusedasthemainexplanatoryvariableofthemacroeconomicenvironment.Stockmarketsprovidedirectfundingtoinvestors,whilebanksandotherﬁnancialinstitutions,asintermediaries,provideindirectfundingtothem.Therefore,wecouldarguethatstockmarketsprovideaneasierandquickertransmissionofliquiditytoinvestorsandtotherealeconomythanbankswhentheeconomyisthriving,butanequallyfasternegativeadjustmentofliquiditywhentheeconomyisplungingintorecession.

Intermsofmethodologicalapproaches,thepresentstudydifferentiatesfrompreviousworksintheareabyexaminingalternativeliquidityproxies.Tothisend,thepapermakesuseofalternativesdeﬁnitionsofliquidityaswellastheInstru-mentalVariable(IV)methodologicalapproach,whichtakescaresofanyendogeneitybiasproblems.Thestudyfocusesonthesimplernon-sophisticatedliquidityproxies,which,however,aretheonesusedbypractitionersandinvestmentprofes-sionalsthatdonotrequirerestrictiveassumptionsasthemoresophisticatedproxiesdo.Moreover,thepresentstudydiffersfromthosebyNæsetal.(2011),Meichleetal.(2011)andFlorackisetal.(2014a)byexaminingtheinformationcontentoftwoliquiditymeasures,namely,theturnoverandthevolumeoftrading,toexplaineconomicactivityalongwiththerelativespreadandAmihud’silliquidityratiowhichhavebothbeenpreviouslyexamined.Weopttousedifferentliquidityproxiesinordertofullyexamineonhowvariousaspectsofliquidityaffecteconomicconditionsandtoproviderobustnesstoourresults.

Stiglitz(1985)andBhide(1993)claimthatstockmarketsdonotproducethesameimprovementinresourceallocationandcorporategovernanceasbanks.Thosewhofavourthemarket-basedsystemargueagainsttheroleofbanksforextractinginformationalrentsfromﬁrmsandreducingincentivestoundertakeriskyandinnovativebutproﬁtableprojects(e.g.,Rajan,1992;MorckandNakamura,1999).LaPortaetal.(2002)alsoargueagainsttheroleofstate-ownedbanksforhavingpoliticalgoalsintheprocessofsupplyingcredittorathertraditionallabourintensiveindustries,thantoinnovativeandtrulystrategicones.However,BootandThakor(1997)showthatbanksfacilitatebetterthegoalofeconomicgrowthinemergingﬁnancialsystemsandstockmarketsdobetterinmatureﬁnancialsystems.Inaddition,AllenandGale(2000)presentevidencethatbothbanksandmarketsprovidedifferentﬁnancialservices,whileeconomiesatdifferentstagesofeconomicdevelopmentrequiredifferentmixturesofﬁnancialservicestooperateeffectively.AsimilarﬁndingisprovidedbyTadesse(2002).BeckandLevine(2002)donotﬁndanyevidencethatthetypeofﬁnancialstructurereallymattersforindustrygrowthandtheefﬁcientallocationofcapitalacrossindustries.

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Forrobustnesspurposes,wehavealsoincludedfortheﬁrsttimeanadditionalcontrolvariable,i.e.,housingstarts,apartfromthetermspread,marketriskpremium,stockmarketvolatility,short-terminterestrateanddefaultspread,alreadyusedinpreviousstudies.Theimportanceofhousingstartsinexplainingmacroeconomicconditionshasbeendocumentedextensivelyintheliterature(Green,1997;CoulsonandKim,2000;HuiandYiu,2003;Iacoviello,2003).Ahousingstartisgenerallycountedastheexcavationofthefoundationandindicatesadvancedemandinthehousingsector.Housingstarts,ontopofbeingaleadingindicatorofstrengthintheconstructionindustry,arealsoanimportantleadingeconomicindicator,duetotheirextensivespilloverbeneﬁtstotheothersectors(i.e.,retail,manufacturing,utilities,labourmarkets),sincenewhomesneedtobeequippedandfurnishedfromscratch(Karamujic,2013).

Finally,asfarasthesampleperiodisconcerned,thepresentstudyisimplementedinaquiteuniqueandinterestingtimeframe,i.e.,1994–2011,sinceitcoversbothperiodsof“bull”and“bear”equitymarketsandperiodsofeconomicexpansion(1994–2002,2004–2008,2010–2011)andeconomicdownturn(2002–2004,2008–2010).Inparticular,thesecondperiodofrecessionwasquitesevere,followingtheburstoftherealestatebubbleintheUS,whichtriggeredtheglobalﬁnancialcrisisthatdrainedliquidityfromﬁnancialmarketsworldwide.Thus,ourempiricalmodelsaretestedacrossanumberofdifferenteconomicandstockmarketbackgroundsandtheimplicationsofourresultsmaybeofparticularinterestnotonlyforacademics,butalsoforinvestors(i.e.,retailandinstitutional),policymakersandregulators.

Toforeshadowtheresults,theyshowthatthereisastrongrelationshipbetweenstockmarketliquidityandthestateofthemacroeconomyinbothcountriesunderinvestigation.Whenthereisdrainageofstockmarketliquidityandtheimplicitcostsfortradingstocksincrease,theninvestorsshouldbeanticipatinglowerGDP,investmentsandconsumptionandhigherunemploymentrates.Finally,theliquidityofsmallstockcompaniesisfoundtohavealargerimpactonthemacrovariablesinvestigatedacrossbothcountries.ThisimportantresultcorroboratestheﬁndingsofAmihud(2002)andmorerecentlyofCakiciandTan(2014)andmayhaveseriousimplicationsforinvestorsandcentralbanks’policies,sincealargedropintheliquidityofsmallﬁrmsstocksgivesastrongsignalforthebeginningofarecessionaryperiod.Asinvestorsstartswitchingfromtheirpositionsonsmallcapstockstogovernmentbondsorlargecapstocks,centralbanksmayincreasepromptlythemoneysupplyaimingtostimulatetherealeconomy,avoidingplunginginadeepandprolongedrecession.

Theempiricalﬁndingsareexpectedtoshedfurtherlightontheroleofmarketliquidityinthegrowthprocess,especially,duringturbulentperiodsliketherecentrecession,sinceliquidityiscloselyassociatedwithboththemarketliquidityriskandthefundingliquidityrisk.Theﬁrsttypeofriskoccursasthemarketliquidityworsensandpotentialinvestorsneedtotrade,whilethesecondtypeistheriskwheretraderscannotfundtheirpositionsandareforcedtounwind.Thisperversesituationishavingsigniﬁcanteffectsontherealeconomy.

However,systematic(market)liquiditycanhaveseriousrepercussionsnotonlyfortheﬁnancialsystem,butalsofortherealeconomy,sinceanydisruptionscanleadtoﬁnancialcrises,whichdamageﬁnancialstability,resourcesallocationandhaveanegativeimpactontherealeconomy(Fergusonetal.,2007).Therefore,thepresenceofthisdownwardliquidityspiralrecommendsthatpolicymakershavetoimprovethefundingliquidityofinvestorsinthemarket,especiallythatofbankinginstitutions.

Therestofthepaperisorganizedasfollows.Section2presentsapertinentliteraturereview,whileSection3deﬁnestheliquidityproxiesalongwithanumberofothercontrolvariablesanddescribesthemethodologyemployed.Section4presentsanddiscussestheresultsobtainedfromtheempiricalanalysis.Finally,Section5concludesthepaper.

2.Literaturereview

Academicresearchhasextensivelyexaminedtherelationshipbetweenassetprices(e.g.,interestrates,termspreads,stockreturns,andexchangerates)andrealeconomicindicators.EstrellaandHardouvelis(1991)showthattheyieldcurvecanpredictfuturedevelopmentsinrealeconomicactivity,whileothershighlighttheroleofthetermspreads(i.e.,thedifferencebetweena10-yeargovernmentbondandanuncoveredshort-terminterestrate)inpredictingfutureturningpointsintheeconomy(EstrellaandMishkin,1998;RudebuschandWilliams,2009;Wright,2006).Therationaleofusingﬁnancialmarketvariablesasleadingindicatorsforeconomicactivityisthreefold:(a)investorsconveytheinformationaboutthefuturestateoftheeconomybytradingﬁnancialsecuritiesandchangingtheirrelativepriceovertime,basedonnewinformationarrivals(Beberetal.,2011),(b)theyareobservedandnotestimatedthroughatheoreticalmodel,and(c)theyareinstantlyandeasilyavailableatahighfrequencytoallmarketparticipantsandanalysts(Meichleetal.,2011).However,StockandWatson(2003),bycarryingouttheirempiricalstudyforsevenOECDcountriesspanningtheperiod1959–1999,concludethatthelinkbetweenﬁnancialmarketvariablesandrealeconomicactivityisnotuniformandstableacrossallcountriesandperiods.

Assetliquidity,whichistheabilitytosellaninvestmentinstantlyandatapriceclosetoitscurrentmarketprice,canbethoughtofasthechannelthroughwhichinformationaboutmacroeconomicvariablesisincorporatedintoassetprices.Anumberofresearchstudiesintheliteratureofmarketmicrostructurehavedocumentedapositivelinkbetweenasecurity’silliquidityanditsexpectedreturns,whichestablishesthepresenceofanilliquidityriskfactorandtheassociatedilliquid-ityriskpremium(AmihudandMendelson,1986;Amihud,2002;Jones,2002;PastorandStambaugh,2003;AcharyaandPedersen,2005;Guoetal.,2011).

Takingintoaccountononehandthatassetpricescanforecastrealeconomicindicatorsandontheotherthatassetliquiditycanexplainassetpriceschanges,thiscouldimplythatassetliquiditycontainsincrementalinformationaboutmacroeconomicconditions.Onepossibleexplanationcouldbetheroleofthe“ﬂighttoliquidity”or“ﬂighttoquality”,

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

putforwardbyLongstaff(2004)whoshowsthatinvestorsprefertoinvestinUSTreasurybondswhicharemoreliquidincomparisonwithRefcorp2bonds,althoughbothofthemcarrythesamecreditrisk.Infact,Longstaff(2004)discoversthatabout10%to15%ofT-Billpricescanbeattributedtotheirlargeliquiditypremia.LevineandZervos(1998)provideanexplanationbyshowinghowstockmarketliquidityaffectsrealeconomicactivityviacertaininvestmentchannels.Theyempiricallyestablishastatisticallysigniﬁcantpositiverelationshipbetweenstockmarketliquidityandcurrentandfutureratesofeconomicgrowthinseveralcountries,aftercontrollingforpoliticalandeconomicfactors.AdifferentexplanationisprovidedbyBrunnermeierandPedersen(2009)whodevelopamodelthatdescribesamutuallydependentrelationshipbetweenassetsmarketliquidityandﬁnancialintermediaries’fundingliquidity.Inparticular,themodelexplains,amongotherthings,howareducedfundingliquidityinperiodsofﬁnancialdownturnscanleadtoa“ﬂighttoquality”,i.e.,thatﬁnancialintermediarieschangetheirliquidityprovisiontostockswithlowmarginrequirements.AsimilarpathhasbeenfollowedbyRöschandKaserer(2012)whoprovideevidenceconsistentwiththetheoreticalmodelofBrunnermeierandPedersen(2009).

This“ﬂighttoquality”argumentmayalsobeassociatedwiththesizeofﬁrmsintermsofmarketvalue.Smallcapitalizationﬁrmssuffermorethanlargecapitalizationﬁrmsduringaneconomicdownturn,whiletheyprospermorewhentheeconomyisexpanding(Perez-QuirosandTimmermann,2000;Switzer,2010).Inaddition,smallcapstocksareusuallylessliquidthanlargecapstocks.Chordiaetal.(2004)witnessanincreaseinaggregatemarketliquidityovertime,whichhasbeenmorepronouncedforlargethanforsmallﬁrms.Duringarecession,investorsmoveoutmoreheavilyfromsmallcapstocksthatperformpoorlyandarelessliquidthanfromlargecapstocks.Chordiaetal.(2004)alsoestablishthataveragedailychangesinliquidityexertaheterogeneouseffectonstockreturns,dependingontheﬁrmsize,sincetheliquidityofsmallﬁrmsvariesmoreonadailybasisthanthatoflargeﬁrms.Thus,theliquidityvariationofsmallcapstocksislargerthanthevariationoflargecapstocks.Næsetal.(2011)document,usingUSdata,thattheliquidityofsmallcapﬁrmsismoreinformativeaboutfuturemacrofundamentalsthantheliquidityoflargecapﬁrms.Theyattributethiseffecttothetendencyofinvestorstomoveoutﬁrstfromsmallcapstocks,eitherbecauseofchangingexpectationsabouteconomicenvironmentorduetoincreasedfundingliquidityconstraints.Theyconﬁrmthisbyexhibitingamuchlargerdropintradingvolumeofsmallcapstocksbeforearecession,thanthatobservedforlargeﬁrmstocks.Inamorerecentstudy,CakiciandTan(2014),investigatingtheeffectofvalue3andmomentumvariablesin23developedinternationalmarkets,ﬁndthatvaluestockreturnsarelowerpriortoarecessionandthisisratherduetoadeteriorationoffundingliquidityandnotduetopoormarketliquidity.

Althoughtheliteratureprovidesanumberofdifferentexplanationsofwhystockmarketliquidityshouldberelatedtoeconomicgrowth,therelationshippersebetweenaggregatemarketliquidityandthefutureeconomicconditionshasattractedlessinterestfromacademicresearchers.First,anumberofstudies,closelyrelatedtoourwork,examinewhethermacroeconomicfactorsaffectstockmarketliquidity.Morespeciﬁcally,Fujimoto(2003)andSöderberg(2008)examinethein-sampleandout-ofsampleforecastingabilityofvariousmacroeconomicvariablesonliquidity,butdonotconsiderthatthisrelationshipcangointheoppositeway.LuandGlascock(2010)showthatthepricingcomponentofliquiditycanbesigniﬁcantlyaffectedbyanumberofmacroeconomicfactorsand,inparticular,thegrowthinindustrialproductionandwhentheeconomydigsdeeperintorecession.Inasomewhatdifferentapproach,GibsonandMougeot(2004)documentthatatime-varyingliquidityriskpremiumintheUSstockmarketcanbelinkedwitharecessionindex.

Inanotherstrandoftheliterature,therearestudiesthatexamineequity-marketorderﬂows,whicharecloselyrelatedtostockmarketliquidity.Speciﬁcally,KaulandKayacetin(2009)examinetheinformationcontentoftwodifferentmeasuresofaggregateequity-marketorderﬂowsforfuturemacroeconomicfundamentalsandexpectedstockmarketreturns.TheydiscoverthatbothcanpredictfuturegrowthratesofindustrialproductionandrealGDP,uptofourquartersahead,andthisresultisrobustevenaftercontrollingforvariablesassociatedwithcommonequitypricingfactors.Beberetal.(2011)addresshowtheissueoforderﬂowsmovementsbyinvestorsacrossequitysectorsisrelatedtocurrentandfutureeconomicconditions.Theirresultsshowthatlarge-sizedactiveorderﬂowsinthematerialssectorcanforecastanexpandingeconomy,whilelarge-sizedactiveorderﬂowsintoconsumerdiscretionary,ﬁnancials,andtelecommunicationsforecastacontractingeconomy.

Inthelightoftherecentglobalﬁnancialcrisis,thereducedfundingliquidityandthedecreasedorderﬂowmovementsfrommarketmakersareaddressedbythreepapersthatdirectlyexploretheissueofstockmarketliquidityandtherealeconomy.Næsetal.(2011)employUSandNorwegianstockmarketdataanddisplaythatstockmarketliquidity(intermsofthetradingcostsofequities)canbeusedasapowerful“leadingindicator”oftherealeconomy,evenaftercontrollingforthepresenceofothervariables,whichareextensivelyusedinpreviousrelevantempiricalstudiesforpredictingbusinesscycles.TheirstudymakesuseofalargeUSdatasetovertheperiod1947–2008alongwithauniquedatasetforNorwayspanningtheperiod1990–2006.TheauthorsalsodiscoveranimportantrelationshipbetweenthesizeoftheﬁrmsandtheinformationcontentofliquidityinpredictingGDPgrowth,aﬁndingthatisconsistentwiththe“ﬂight-to-quality”effect.

Meichleetal.(2011)claimthatforasmallopeneconomy,i.e.,theSwisseconomy,assetpricefactors,suchastermspreads,arenotentirelyappropriatetopredicteconomicgrowth,aslongastheyareseverelyaffectedbyexogenousfactors

RefcorpisagovernmentagencycreatedbytheFinancialInstitutionsReform,Recovery,andEnforcementActof1989(FIRREA).TheprincipalofthesebondsisfullycollateralizedbyTreasurybonds,whilefullpaymentofcouponsisguaranteedbytheTreasuryundertheprovisionsofFIRREA.3

Ithasbeenwellestablished(e.g.,FamaandFrench,1992,1996;Lakonishoketal.,1994)thatvaluestockswhicharedescribedasstockswithhighratiostofundamentals(e.g.,bookvalue,earningspershare,cashﬂows,etc)relativetostockpricetendtooverperformstockswithcorrespondinglylowratios.

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

(i.e.,co-movementsofinternationallong-terminterestrates).Theyalsoﬁndthatoverthelasttwodecades(1990–2010)stockmarketliquidityisabetterpredictorofeconomicactivitythantermspreads.However,thispictureisreversediftheentiresampleperiod(1975–2010)isconsidered,withtermspreadsgainingpredictivepower(RudebuschandWilliams,2009).ThisﬁndingalsoconﬁrmstheresultsbyStockandWatson(2003)abouttheerraticandtimevaryingbehaviourofassetpricesaspredictorsofrealeconomicactivity.

Finally,Florackisetal.(2014a)inastudy,whichfocusesonlyontheUKmarketandconsidersonlymacroeconomicactivityintermsofGDPgrowth,examinetheexplanatorypowerofstockmarketliquidityinforecastingtherealUK.GDPgrowthovertheperiod1989–2012.Byusingstandardlinearandnonlinearmodels,theyﬁndastatisticallysigniﬁcantnegativerelationshipbetweenstockmarketilliquidityandfuturegrowthinGDPofUK,evenafterincludingtheusualexplanatoryvariables(e.g.,termspreads,short-terminterestratesandrealmoneysupply/divisia).Theyalsoshowthatthattheeffectofbothmarketilliquidityanddivisiamoneybecomesstrongerduringperiodsofilliquidmarketconditionsandpooreconomicgrowth.Furthermore,throughanout-of-sampleforecastinganalysistheydiscoverthataregimeswitchingmodelofilliquidvs.liquidmarketconditionspredictsUKgrowthinGDPbetterthananyothermodel,eventheonepublishedbytheBankofEngland’sinﬂationreport.

3.Methodology

3.1.Liquidityproxiesandsampleﬁrms

Asfarastheliquiditymeasuresareconcerned,therearenumerousindicatorsdevelopedintheliteraturethatattempttomeasurestockmarketliquidity.Thehighfrequencyliquiditymeasuresrequireintradaydataonbid/askquotes,orderﬂows,volumeoftradesetc.,whicharenotavailableforalongperiodoftime.Thus,weadoptlowfrequencyliquiditymeasuresthatcanbeestimatedwithdailydata,whichareavailableforlongertimeperiods.Furthermore,sinceliquidityisanunobservablecharacteristicofanassetmarket,whichcannotbecapturedinasinglemeasure,itisdesirabletoexaminetheissuewiththeuseofavarietyofliquiditymeasures.

Weusefouralternativeliquiditymeasures:(a)theAmihud(2002)illiquidityratio(ILR),(b)therelativespread(RS),(c)turnover(TUR)and(d)thevolumeoftrading(VTR).AccordingtoGoyenkoandUkhov(2009)andGoyenkoetal.(2009),theﬁrsttwoliquidityproxiescapturethespreadcostandthepriceimpactwhenestimatedwithdailydata.Therationaleforusingturnoverandvolumeoftradingistwofold.First,theyaresimpleandstraightforwardtocalculateanddonotrequirealargeamountofdataorrestrictiveassumptionsasthemoresophisticatedproxies,suchastheLesmondetal.(1999)andRoll(1984)liquiditymeasures.Second,theyarethemostcommonlyusedliquiditymeasuresbypractitionersandinvestmentprofessionalsandhavebeenpreviouslyusedinthepertinentliteratureinotheraspectsofliquidity,suchasinassetpricing.Amihud’s(2002)illiquidityratio(ILR)istheratioofabsolutestockreturnstomonetaryvolumeonadailybasis,displayinghowmuchpricesmoveforeachmonetaryunitoftrades.Thecostassociatedwithlargertradesismoreaccuratelycapturedinthepriceimpactofatrade.Hasbrouck(2009)showsthattheILRisthebestavailableprice-impactproxyconstructedfromdailydata.Moreover,Amihud(2002)showsthattheILRispositivelyandsigniﬁcantlyrelatedtoboththepriceimpactandtheﬁxedcostcomponentestimatesdeﬁnedbyBrennanandSubrahmanyam(1996).TheILRcapturesthesensitivityofpricestotradingvolumes,sinceitisameasureoftheelasticitydimensionofliquidity.TheILRiscalculatedas:

ILRi,T=

󰀂󰀂T󰀂Ri,t󰀂󰀄1

t=1

VOLi,t

(1)

whereDTisthenumberofobservationswithinatimewindowT,|Ri,t|istheabsolutereturnatdaytforstocki,andVOLi,tis

thetradingvolumeinmonetaryvaluesatdaytforstocki.TheILRessentiallyprovidesanilliquiditymeasure,sinceahighvalueindicateslowliquidity(i.e.,ahighpriceimpactoftrades).Moreover,ahighpriceimpactsuggeststhatthemarketdepthislowandasmallervolumeisneededtomovethatprice.

Amarketparticipantwhowishestoﬁllhisorderimmediatelymustbewillingtopaytheaskpriceforabuyorderandcollectthebidpriceforasellorder.Thedifferencebetweenthetwopricesisthebid-askspread,whichreﬂectsthecostofimmediacy.Thus,thebid-askisaspreadcost,whichisobservedinbothdealerandlimitordermarkets.Inthepresentstudy,weestimateamarket-wideproportionalspreadmeasure,therelativebid/askspread(RS).Itisestimatedastheratioofthequotedspread(i.e.,thedifferencesbetweenthebestaskandbidquotes)overthemidpointprice(i.e.,theaveragesofthebestaskandbidquotes)onadailybasis:

RSi,T=

T1󰀄

󰀅󰀅ASK−PBIDPi,t

i,t

󰀁

(2)

t=1

ASK+PBID/2Pi,t

i,t

󰀁wherePASKi,tandPBIDi,taretheaskandbidprice,respectively,atdaytforstocki.TheRSprovidesarelativemeasureoftradingcostsandproxiesforapercentagetwo-waytransactioncost,i.e.,whatfractionofthepriceneedstobepaidto“cross”fromthebidtotheaskprice,orviceversa.SimilarlytothecaseoftheILR,theRSisanilliquiditymeasure,sinceahighspreadindicatesanilliquidmarketwheretheimplicitcostsoftradingarelarge.

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Table1

Descriptivestatistics,serialautocorrelationsandcorrelationcoefﬁcientsofliquidityproxies.

Mean

Median

Jarque–Berra

No.ﬁrms

No.Obs.

Section1:UKliquidityproxiesPanelA:descriptivestatisticsILRRSTURVTR

PanelB:serialautocorrelations

0.1389470.0656210.464037477,129,289

0.0978430.0627430.473530485,855,808

2.56(0.72)5.39(0.49)3.18(0.55)3.28(0.53)

6,4219,3457,5488,356

25,68437,38030,19233,424

Lags1

ILRRSTURVTR

PanelC:correlationcoefﬁcients

3.41(0.43)3.19(0.48)2.30(0.32)3.07(0.51)

3.93(0.29)3.74(0.37)2.58(0.24)3.30(0.39)

4.49(0.17)4.37(0.19)4.26(0.16)5.52(0.28)

RSTURVTR

Section2:GermanyliquidityproxiesPanelA:descriptivestatisticsILRRSTURVTR

PanelB:serialautocorrelations

ILR0.2330−0.3893−0.6569

TUR

−0.0375−0.5648

0.5692

0.6749500.0448760.3580196940,187

0.4655970.0434630.3684416311,968

2.29(0.77)4.51(0.58)3.62(0.39)3.35(0.49)

3,6984,5214,0893,897

14,79218,08416,35615,588

Lags1

ILRRSTURVTR

PanelC:correlationcoefﬁcients

3.03(0.50)3.14(0.56)2.61(0.31)2.68(0.62)

3.34(0.32)3.58(0.37)2.96(0.19)3.02(0.41)

3.85(0.20)3.83(0.24)4.19(0.12)5.17(0.22)

ILR

TUR

RSTURVTR

0.2956−0.3277−0.3153

−0.1470−0.4425

0.3711

PanelsA,BandCinSection1showdescriptivestatistics,serialautocorrelationsandcorrelationcoefﬁcientsrespectivelyfortheUKliquidityproxiesfrom1994to2011.TheliquiditymeasuresaretheAmihud’silliquidityratio(ILR),therelativebid–askspread(RS),theturnover(TUR)andthevolumetraded(VTR).Theliquidityproxiesarecalculatedforeachavailablestockineachquarter.PanelAshowsthemeanandmedianoftheliquiditymeasures,theJarque–Berrastatisticwithp-valuesinparenthesis,thenumberofsecuritiesusedandthetotalnumberofobservations(eachsecurityisobservedinseveralquarters).PanelBshowstheresultsoftheQtestforserialautocorrelationforlags1,4and12.PanelCshowscorrelationcoefﬁcientsbetweentheliquidityproxies.Thecorrelationsarecalculatedacrossallstocksandtime;theliquiditymeasuresarecalculatedforeachavailablestockineachquarterandthecorrelationsarepairwisecorrelationsbetweentheseliquiditymeasures.Section2showscorrespondingstatisticsfortheGermanliquidityproxiesfrom1999through2011.

Turnover(TUR)isacommonmeasureofactivityandiscalculatedasthetotalnumberofsharestradedduringatimeinterval,relativetothenumberofoutstandingsharesinthesecurity.Weexpressturnoverinpercentageterms,thus,measuringthepercentageoftheissuedsharesthatchangehandsduringatradingwindow(e.g.,day,month,quarter).Finally,thevolumeoftrading(VTR)inmonetarytermsiscalculatedbymultiplyingthenumberofsharestradedbytheconcurrentstockprice.BoththeTURandVTRareliquiditymeasures,asopposedtotheILRandRS,whichareilliquiditymeasures.Allfourliquidityproxiesareﬁrstestimatedforeachstockandforeachquarterandthentheequallyweightedcross-sectionalaverageforeachquarterisobtained.

ThesampleconsistsofallstockslistedontheLondonStockExchangeandtheDeutscheBörse.Inordertocalculatetheliquidityproxies,dataondailystocksprices,returns,thetradingvolumeandtotalnumberofshareslistedforeachcompanyinthesamplearesourcedfromBloombergandonlystockswithavailabledataareincludedintothesample.ThetimeperiodofthestudyfortheUKspansfrom31/12/1994to31/12/2011andforGermanyfrom31/3/1999to31/12/2011.Table1providessomedescriptivestatisticsaboutthefourliquidityproxies,bothfortheUKandGermanyandthecorrelationcoefﬁcientsamongthem.TheUKmarket,asexpected,isamoreliquidmarketthantheGermanstockmarket,sincethemean/medianvaluesoftheilliquidityproxies,namelytheILRandRS,fortheUKaremuchlowerfromthecorrespondingvaluesforGermany;asimilartrendcanalsobenoticedfortheliquidityproxies,namelytheTURandVTRmetrics,exhibitingmuchhighervaluesfortheUKthantheGermanstockmarket.

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

TheJarque–Berastatisticconﬁrmsacceptanceofthenullhypothesisofnormality,whiletheQtestforserialautocorre-lationforlags1,4and12hasbeenalsoimplementedforthefouralternativeliquidityindices.TheQ-statisticteststhenullhypothesisofnoautocorrelation.TheresultsforthelevelsoffourliquidityproxiesarealsoreportedinTable1alongwiththeircorrespondingp-values.Theﬁndingsprovidesupportiveevidenceoftheabsenceofanyautocorrelationatallthreelagstructuresunderstudy,implyingthatallfourseriesdisplaytheabsenceofaconsistentpatternofautocorrelation.Theresultsaresupportivetotheliteraturethatﬁndsminimalornilautocorrelationinﬁnancialseries,apieceofevidenceofmarketefﬁciency(Abrahametal.,2002;WorthingtonandHiggs,2004;Hamidetal.,2010;amongothers).

3.2.Macroandcontrolvariables

Tomeasureeconomicactivityweusethefollowingmacrovariables:a)realGDP(RGDP),realconsumption(RC),realinvestment(RI)andtheunemploymentrate(UnR).AllseriesaresourcedfromtheOECDdatabaseonaquarterlybasis,arechainedvolumeestimatesandseasonallyadjusted.

Inordertoaccountfortheotherﬁnancialvariablesthathavebeenidentiﬁedintheliteraturethatcanexplaineconomicactivity,weuseanumberofequityandnon-equitycontrolvariablesinourmodelspeciﬁcations.Speciﬁcally,weusehousingstarts(HS),thetermspread(TS),themarketriskpremium(MRP),stockmarketvolatility(V),short-terminterestrates(SR)andthedefaultspread(DS).ThecontrolvariablesaresourcedfromBloombergandThompsonReuters.Thetermspreadiscalculatedasthedifferencebetweentheyieldofthe10-yeargovernmentbondandtheyieldofthe3-monthTreasurybill,theshort-terminterestrateisproxiedbythe3-monthTreasurybillandthedefaultspreadisthedifferencebetweentheyieldofabondindexconsistingofcorporatebondsandtheyieldofthe30-yeargovernmentbond.ThemarketriskpremiumistheexcessreturnoftheFTSE100fortheUKandtheDAXforGermanyovertheyieldoftherespective3-monthTreasurybill.Thestockmarketvolatilityismeasuredasthecrosssectionaveragestandarddeviationofdailyreturnsofthesamplestocksoverthequarter.

Housingstarts(HS)isaleadingeconomicindicatorthatreﬂectsthenumberofprivatelyownednewhousesonwhichconstructionhasbeenstartedoveragivenperiod.Itincludesanumberofnewsingleormulti-familyhousesasdeterminedfromthenumberofpermitsissuedforconstructionofresidentialbuildings.Realestateinvestmentsareagoodmeasureofexpecteddemandforrealestate.SinceeconomicperformanceisreﬂectedontoGDP,ifthereisaleadingrelationshipbetweenGDPandrealestateinvestments,therealestatesectorwillbealeadingsectorofeconomicperformance.Therefore,realestateinvestmentsaregoodmeasuresforreﬂectingexpectedrealestatedemandandserveasgoodpredictorsofeconomicperformance.Green(1997)makesuseofcausalityteststoexaminetheeffectofhousingstartsonGDP.Heﬁndsthatresidentialinvestmentscause(lead)GDP,whileinvestmentsinequipmentandmachinerydonot.CoulsonandKim(2000)alsoconﬁrmthatGDP’sresponsetoashockinresidentialinvestmentisseveraltimesthemagnitudeofaresponsetoashockininvestmentinequipmentandmachinery.TheysuggestthatresidentialshocksexplainbyfarthevariationinGDPthandoesashockinequipmentandmachinery.HuiandYiu(2003)usecausalityteststoempiricallyexaminethemarketfundamentaldynamicsofprivateresidentialrealestateprices.TheyshowthatresidentialinvestmentsleadGDP,becauseGDPisregardedasoneofthemarketfundamentalsthataffectdemandforprivateresidentialrealestate,whileitisaffectedbysomemarketfundamentals.Iacoviello(2003)inhisstudyofconsumption,housingprices,andcollateralconstraints,alsoﬁndsadirecteffectfromhousingpricestoconsumption,which,inturn,inﬂuencesthecourseofeconomicgrowth.

3.3.Modellinghypothesismethodology

Thebaselineempiricalmodelforanalyzingtherelationshipbetweeneconomicactivityandtheliquiditymeasuresisthefollowing:

󰀅yt+1=

LIQ

˛+ˇiXLIQt

+ˇiHSt

+ˇiTSt

MRP

+ˇiMRPt

+ˇiVt

+ˇiSRt

+ˇiDSt

󰀅y

+ˇi

p󰀄i=0

󰀅yt−i+et

(3)

where󰀅yt+1isthegrowthrateofthemacrovariable(RGDPorRCorRIorUnR)ofinterest,XLIQtisavectoroftheliquiditymeasures(ILRorRSorTURorVTR),HStistheleadingindicatorofhousingstarts,TStisthetermspread,MRPtisthemarket

LIQ,ˇHS,riskpremium,Vtdenotesstockmarketvolatility,SRtistheshort-terminterestrate,DStisthedefaultspread,andˇ󰀃

󰀅yt−iˇTS,ˇMRP,ˇV,ˇSR,andˇDSarethecoefﬁcientsestimatesoftheaboveregressionvariables,respectively.Finally,

displaysanumberoflagsforthedependentvariable.Thenumberoflagshasbeendeterminedthroughtheﬁnalpredictionerror(FPE)criterion,recommendedbyAkaike(1969)anddeﬁnedastheminimizationofFPEp=󰀃p2(T−p)−1(T+p),where󰀃p2indicatestheestimatederrorvariance,tindicatesthenumberofobservations,andpisthesizeofthelaglength.Finally,thedynamicpropertiesofGDPserieshavebeenthesubjectofalongdebate(NelsonandPlosser,1982;KimandPerron,2009).Inparticular,anumberofstudiesindicatethatGDPdisplayshighlypersistentchangesacrosstime,whileCampbellandMankiw(1989)addressthisissuebyprovidingsupportiveevidencethatshockstooutputarelargelypermanentandthatsubstantialpersistenceofoutputshocksisanimportantfeatureofpost-wareconomictimeseries.Tothisend,wemakeuseoftheHodrickandPrescott(1997)toobtainthecyclicalcomponentofrealGDP.

Totesttheimpactofliquidityoneconomicgrowth,wemakeuseoftheInstrumentalVariable(IV)methodologicalapproach,whichtakescaresofanyendogeneitybiasissues.Eq.(3)cannotbeestimatedconsistentlyusingsimpleordinary

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

leastsquare(OLS)duetopotentialendogeneitybetweeneconomicgrowthandanyoftheexplanatoryvariables,sowemaybecapturingreversecausality.Usinginstrumentsisthebestoptiontotakecareofanypossibleproblemsofreversecausationrunningfromeconomicgrowthtotheexplanatoryvariables.Duetothelackofproperinstrumentsforthoseexplanatoryvariables,leadsusnottochoosetwo-stageleastsquares(2SLS).Instead,weuseweakmethodsofcontrollingendogeneity,byusinglagsoftheexplanatoryvariablesastheappropriateinstruments.

Next,inordertotakeintoaccounttheliquidityvariationbetweensmallandlargesizedﬁrms,wealsoconstructtwoversionsofeachliquidityvariable,oneforsmallcapﬁrmsandoneforlargecapﬁrms.Allsamplestocksaresortedonmarketcapitalizationandallocatedintosizequartiles.Thefourliquiditymeasuresaresubsequentlycalculatedforthe25%smallestﬁrms(LIQS)andthe25%largestﬁrms(LIQL).Then,werunthefollowingregressionmodelthatcapturestheinformationcontentofsmallandlargecapﬁrmsseparately:

󰀅yt+1=

LIQ

˛+ˇiSXLIQst

LIQ

+ˇiLXLIOLt

+ˇiHSt

+ˇiTSt

MRP

+ˇiMRPt

+ˇiVt

+ˇiSRt

+ˇiDSt

+ˇi

p󰀄i=0

yt−1+et

(4)

Theabovemodelisestimatedwithandwithoutliquiditymeasures.

Table2providessomedescriptivestatisticsaboutthefourliquidityproxiesforthesmallandlargecapﬁrmsandthecorrelationcoefﬁcientsamongthem.Forbothcountries,asexpected,largecapﬁrmsexhibithigherliquiditylevelsintermsoflowerILRandRSandhigherTURandVTRaswell.Furthermore,thecorrelationcoefﬁcientbetweentheILRandRSispositiveacrossallcases,sincebothproxiesmeasureilliquidity,whilethereisapositiverelationshipbetweenthetwoliquiditymeasuresTURandVTR.Onceagain,thestatisticsconﬁrmthepresenceofnormality(i.e.,throughtheJarque–Berastatistic)andtheabsenceofserialautocorrelationacrossthethreelagsaswellasacrossallfourliquidityvariables.

3.4.Causalitytests

Simsetal.(1990)andTodaandPhillips(1993)arguethatWaldteststatisticsfornon-causalityinanunrestrictedVARcouldhaveanonstandardlimitdistribution.TodaandYamamoto(1995)suggestanalternativeapproachtocausalitytesting.Thebasicideaistoartiﬁciallyaugmentthecorrectorder,K,oftheVARbythemaximalorderofintegration,sayTmax.TheaugmentedVARisthenestimatedandWaldtestsforlinearornonlinearrestrictionsarecarriedoutontheﬁrstKcoefﬁcientmatrix(Caporaleetal.,2004).

WeuseToda-Yamamotocausalitytestsfortestingstatisticalcausalitybetweenstockmarketliquiditymeasuresandvariousproxiesforeconomicgrowth.Thenullhypothesisofinterestis:H0:stockmarketliquiditydoesnotGranger-causeeconomicgrowth.TheWaldstatisticconvergesindistributiontoarandomvariablewithmdegreesoffreedom,regardlessofwhethertheprocessisstationary,I(1),I(2),possiblyaroundalineartrendorwhetheritisco-integrated.Inaddition,theirmethodologyrequiressomepretestinginordertodeterminethelaglengthoftheprocess.Simsetal.(1990)showthatlagselectionprocedures,commonlyemployedforstationaryVARs,whicharebasedontestingthesigniﬁcanceoflaggedvectorsbymeansoftheWald(orLMorLR)tests,arealsovalidforVARswithI(1)processes,whichmightexhibitcointegration.WeaugmentthebivariateVARbythemaximumorderofintegrationintheseries.InthiscasethevariablesturnouttobeI(1).Therefore,weaugmentthebivariateVARbyonelagandtestfornon-causalityzerorestrictionsontheparametersoftheoriginalVARbycarryingoutWaldtestsontheﬁrstKcoefﬁcientmatrix(TodaandYamamoto,1995).

4.Resultsanddiscussion

4.1.Baselineestimates

Table3presentstheIVestimates.ThedependentvariableintheseestimatesiseitherrealGDP(RGDP),orrealconsumption(RC),orrealinvestment(RI),ortheunemploymentrate(UnR).Sections1–4reportstheresultsfromtheAmihudilliquidityratio(ILR),Relativespread(RS),Turnover(TUR)andVolumetraded(VTR),respectively,whiletheresultsfromtheUKandGermanyarereportedinPanelAandB,respectively.ThelastthreecolumnsshowtheR2withtheinclusion/exclusionoftheliquidityvariableandtheF-testwhichteststhenullhypothesisthatacceptstherestrictedmodel(whentheLiquidityvariableisexcluded)andisbasedonthestatisticF=(RU2−RR2)/(1−RU2)×df1/(df0−df1),withRU2beingtheunrestrictedR2,RR2beingtherestrictedR2,withdf1=(N−k)degreesoffreedomanddf0=(N−k0)degreesoffreedom,respectively.

Theoverallpictureoftheempiricalresultscanbecharacterizedbythreefacts:First,thevastmajorityoftheexplanatoryvariablesarehighlystatisticallysigniﬁcant(atthe1%signiﬁcancelevel)withtheexpectedsignsremainingstable,irrespec-tivelyoftheliquiditymeasureorthemarketunderinvestigation.Second,theexplanatorypowerofthemodelisquitehigh,rangingfrom37%(ILRfortheUKwhenUnRisthedependentvariable)to64%(RCfortheUKwhenVTRisthedependentvariable).Third,theincrementalinformationalcontentofthevariablerepresentingtheliquidityproxy(ILR,RS,TURandVTR)canbeestablished,judgingfromtherejectionoftherestrictedmodel(i.e.,theoneinwhichtheliquidityvariableisexcluded)acrossallcases,implyingthesubstantialroleofliquidityinexplainingthebehaviourofeconomicactivity.Thiscan

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Table2

Descriptivestatisticsoflargeandsmallcapsliquidityproxies.

Mean

Median

Jarque–Berra

Section1:UKlargecapsliquidityproxiesPanelA:descriptivestatisticsILR0.062320.023202.74(0.42)RS0.025800.023335.82(0.33)TUR0.50706

0.53318

3.71(0.45)VTR

1,506,398,386

1,580,166,192

6.01(0.14)

PanelB:serialautocorrelations

Lags1

ILR2.48(0.48)2.94(0.29)3.37(0.17)RS2.70(0.43)2.63(0.38)3.48(0.15)TUR2.64(0.50)2.59(0.35)3.30(0.21)VTR

2.39(0.56)

2.44(0.42)

2.96(0.29)

PanelC:correlationcoefﬁcientsRS0.48108TUR−0.57706−0.30692VTR

−0.28798

−0.20230

0.66781

Section2:UKsmallcapsliquidityproxiesPanelA:descriptivestatisticsILR0.251420.195102.18(0.64)RS0.131040.122424.29(0.50)TUR0.511130.503403.36(0.48)VTR

72,728,154

49,659,454

3.09(0.57)

PanelB:serialautocorrelations

Lags1

ILR2.64(0.38)2.81(0.24)3.11(0.16)RS2.47(0.46)2.73(0.35)3.02(0.20)TUR2.36(0.52)2.88(0.21)3.24(0.11)VTR

2.29(0.57)

2.64(0.39)

2.89(0.28)

PanelC:correlationcoefﬁcients

ILR

TUR

RS0.01314

TUR

−0.34143−0.05217VTR−0.20001−0.30034

0.08426

Section3:GermanylargecapsliquidityproxiesPanelA:descriptivestatisticsILR13.65080

9.380153.74(0.30)RS

0.017440.016644.66(0.13)TUR

0.412490.390373.67(0.33)VTR

25,930,67122,062,306

3.84(0.28)

PanelB:serialautocorrelations

Lags

ILR2.59(0.42)2.85(0.28)3.36(0.14)RS2.84(0.36)3.01(0.23)3.40(0.12)TUR2.66(0.38)2.95(0.29)3.32(0.17)VTR

2.82(0.39)

3.24(0.19)

3.68(0.11)

PanelC:correlationcoefﬁcients

ILR

TUR

RS0.26203

TUR

−0.19579−0.39028

VTR

−0.06852−0.40239

0.46739

Section4:GermansmallcapsliquidityproxiesPanelA:descriptivestatistics

ILR

18.3646912.223802.90(0.34)RS

0.090500.080735.11(0.16)TUR

0.449210.401524.64(0.27)VTR

2,081,5232,605,287

3.59(0.30)

No.ﬁrms

No.Obs.

1,6056,4212,3369,3451,8877,5482,089

8,356

1,6056,4212,3369,3451,8877,5482,089

8,356

9243,6981,1304,5211,0224,089974

3897

9243,6981,1304,5211,0224,089974

3,897

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Table2(Continued)

PanelB:serialautocorrelations

Lags1

ILRRSTURVTR

PanelC:correlationcoefﬁcientsofGermansmallcapsproxies

2.48(0.49)2.67(0.41)2.51(0.46)2.39(0.55)

2.80(0.29)2.96(0.27)2.99(0.26)2.84(0.35)

3.38(0.16)3.29(0.17)3.42(0.14)3.30(0.20)

ILR

TUR

RSTURVTR

0.32748−0.14907−0.25010

−0.01489−0.09497

0.04685

Section1showsdescriptivestatistics,serialautocorrelationsandcorrelationcoefﬁcientsfortheUKlargecapsliquidityproxiesfrom1994to2011.TheliquiditymeasuresaretheAmihud’silliquidityratio(ILR),therelativebid–askspread(RS),theturnover(TUR)andthevolumetraded(VTR).Theliquidityproxiesarecalculatedforeachavailablestockineachquarter.PanelAshowsthemeanandmedianoftheliquiditymeasures,theJarque–Berrastatisticwithp-valuesinparenthesis,thenumberofsecuritiesusedandthetotalnumberofobservations(eachsecurityisobservedinseveralquarters).PanelBshowstheresultsoftheQtestforserialautocorrelationforlags1,4and12.PanelCshowscorrelationcoefﬁcientsbetweentheliquidityproxies.Thecorrelationsarecalculatedacrossallstocksandtime;theliquiditymeasuresarecalculatedforeachavailablestockineachquarterandthecorrelationsarepairwisecorrelationsbetweentheseliquiditymeasures.Section2showscorrespondingstatisticsfortheUKsmallcapsliquidityproxies,whereasSections3and4showscorrespondingstatisticsfortheGermanlargecapsandsmallcapsliquidityproxiesrespectivelyfrom1999through2011.

beclearlydiscernedbyobservingthemuchhighervaluesofR2producedwhenweincludetheliquidityproxyincomparisonwiththecorrespondingvaluesofR2generatedwhenweexcludeit.

AﬁnalremarkcanbemadeonthebasisofthevaluesofR2ingeneral,whenwecompareourﬁndingsbetweenliquidityproxiesandmacrovariables.ThemodelsthatinvolvetheVTRhaveonaveragealargerR2fortheUKthanthemodelswiththeotherliquidityproxies,whereasforGermanythemodelswiththelargerR2aretheonesinvolvingtheRS.Finally,itshouldbenotedthatthebestﬁtofthedataforbothcountriesisfoundinmostcaseswhenRGDPisusedasthedependentvariable.

Inmoredetails,wecanclearlyseethattheILRandRSilliquidityproxieshaveastatisticallysigniﬁcantnegativelinkwithGDP,consumptionandinvestmentandasigniﬁcantpositiveassociationwiththeunemploymentrateinbothcountries.Thisbehaviourofthetwoilliquidityproxiesisexpectedsincetheirincreaseindicatesafallinmarketliquidityandconsequentlyitshouldbenegativelyrelatedwitheconomicgrowth.Whenweusetheothertwoliquidityproxies,namelytheTURandVTR,theirfactorloadingsshowastrongandstatisticalsigniﬁcantpositiverelationshipwithRGDP,consumptionandinvestmentandanegativerelationshipwiththeunemploymentrate.Thus,theresultsindicatethatinbothcountrieswhenbothTURandVTRincrease,implyingthatstocksaremoreliquidandmoreeasilytraded,weanticipatefavourablemacroeconomicconditionsintermsofhigherGDP,consumptionandinvestmentandalowerunemploymentrate.

TheHousingStarts(HS)controlvariableisdisplayedtobesigniﬁcantlypositivelyrelatedacrosstheRGDP,RC,RIeconomicvariablesandnegativelyrelatedwiththeUnRvariable.Thepositiverelationshipbetweenthehousingstartsvariableandtherealmacrovariables(i.e.,RGDP,RCandRI)isexpectedaccordingtotheoreticaljustiﬁcations.However,therelationshipbetweenhousingstartsandunemploymentcanbeambiguous.Recentworkintheareahasnotconcludedaboutthesignoftherelationshipbetweenhousingstartsandlabourmarketeffects.BlanchﬂowerandOswald(2013)establishthatrisesinhome-ownershipintheUSareaprecursortoeventualsharprisesinunemploymentduetoreasonsoflowerlevelsoflabourmobilityandtofewernewbusinesses.Theirevidencesuggeststhatthehousingmarketcanproducenegative‘externalities’uponthelabourmarket.

Theothernon-equityandequityorientedcontrolvariableshaveastatisticallysigniﬁcantrelationshipwitheconomicactivity.Speciﬁcally,thetermspread(TS)andMRP(marketriskpremium)arepositivelyrelatedwithRGDP,RCandRI,whilebeingnegativelyrelatedwithUnR.Ontheotherhand,marketvolatility(V),short-terminterestrates(SR)andthedefaultspread(DS)aresigniﬁcantandnegativelyrelatedwithRGDP,RCandRIandpositivelywithUnR.Theseresultsholdinbothcountriesandacrossallliquidityproxies,whiletheyareasexpectedbytheoreticalargumentsandconsistentwiththepreviousempiricalevidence(EstrellaandMishkin,1998;RudebuschandWilliams,2009;Wright,2006;Meichleetal.,2011;Næsetal.,2011).

Overall,theresultsshowthatalthoughtheequityandnon-equitycontrolvariablesprovedtobeusefulinexplainingeconomicactivity,theliquidityproxiesofferimportantincrementalinformationandcouldnotbeomittedfromtheanalysis.Marketliquidityisshowntobeastrongleadingindicatorforeconomicconditionsforbothcountriesunderquestion,eventhoughtheUKisacapitalmarket-basedeconomyandGermanyisabank-basedeconomy.

Thiscanbeexplainedbythefactthatinterbankmarketsforliquidityareindirectlyconnectedtooneanotherthroughvariouschannelswiththeliquidityofstockmarkets,asNyborgandÖstberg(2014)recentlypointedout.Theyshowthatanincreaseintightness(e.g.,higherinterestrates)intheinterbankmarketforliquidityleadstopull-back(i.e.,the‘liquiditypull-backhypothesis’),whichinvolvessellingﬁnancialassets(themostliquidones)eitherdirectlybybanksorthroughleveragedinvestorswhoselltheirmostliquidassetstheyown(i.e.,portfoliorebalancing)tomeettheincreasedmargins’requirementsthatbanksimposeonthem.Ahugedropinliquidityintheinterbankmarketwasthecaseinthelastﬁnancial

52Table3

IVEstimateswithliquidityproxies.

ˇLIQˇHSˇTSˇMRPˇVˇSRˇDSˇ1󰀅y

R2Adj.

F-test

ex.LIQ

in.LIQ

Section1:Amihudilliquidityratio(ILR)PanelA:UK

RGDP

0.758

(3.47)*

Lags=8

0.761

(3.02)*

Lags=9

0.862

(3.25)*

Lags=8

UnR

0.773

(3.28)*

Lags=8

PanelB:Germany

RGDP

0.874

(3.49)*

Lags=9

0.741

(4.35)*

Lags=9

0.873

(4.36)*

Lags=10

UnR

0.742

(4.35)*

Lags=8

Section2:relativespread(RS)PanelA:UK

RGDP

0.764

(4.14)*

Lags=8

0.769

(3.24)*

Lags=9

0.674

(3.87)*

Lags=8

UnR

0.761

−4.0180.436(−5.62)*

(4.49)*

−3.3720.365(−5.64)*

(5.26)*

−2.3250.238(−5.51)*

(5.14)*

0.429−0.238(6.12)*

(−5.46)*

−0.4670.403(−5.46)*

(5.24)*

−0.4480.386(−5.73)*

(5.25)*

−0.2580.325(−5.36)*

(5.31)*

0.417−0.157(5.42)*

(−5.26)*

−0.3950.465(−5.49)*

(5.52)*

−0.4250.435(−6.26)*

(5.18)*

−0.2630.338(−5.26)*

(5.20)*

0.282

−0.204

0.3310.149(4.18)*

(5.27)*

0.2530.119(4.61)*

(5.36)*

0.3420.255(5.30)*

(5.26)*

−0.384−0.118(−5.30)*

(−5.26)*

0.2940.163(5.18)*

(5.30)*

0.2580.214(5.12)*

(4.28)*

0.4640.230(5.02)*

(4.96)*

−0.264−0.183(−4.25)*

(−4.21)*

0.3360.153(5.31)*

(5.42)*

0.2650.248(4.85)*

(5.42)*

0.3950.285(5.04)*

(5.32)*

−0.426

−0.178

−0.135−0.248(−4.48)*

(−5.26)*

−0.142−0.249(−5.04)*

(−5.93)*

−0.141−0.429(−5.23)*

(−5.06)*

0.1240.461(4.15)*

(6.48)*

−0.138−0.219(−5.28)*

(−5.03)*

−0.159−0.286(−5.36)*

(−6.27)*

−0.153−0.438(−5.47)*

(−5.39)*

0.1350.415(4.26)*

(5.74)*

−0.257−0.286(−5.38)*

(−5.11)*

−0.192−0.326(−5.41)*

(−6.09)*

−0.163−0.508(−5.16)*

(−6.19)*

0.147

0.406

−0.1850.439(−4.34)*

(6.48)*

−0.2320.486(−5.14)*

(6.17)*

−0.3450.476(−5.28)*

(6.15)*

0.227−0.387(5.39)*

(−6.14)*

−0.2130.485(−5.16)*

(6.39)*

−0.2550.548(−4.96)*

(5.81)*

−0.3310.482(−5.05)*

(5.86)*

0.232−0.411(4.87)*

(−6.15)*

−0.2280.484(−5.19)*

(6.05)*

−0.3280.537(−5.03)*

(5.42)*

−0.3250.517(−5.26)*

(6.27)*

0.285

−0.434

0.60

0.34

0.53

0.28

0.57

0.30

0.37

0.24

0.61

0.34

0.56

0.31

0.56

0.29

0.54

0.28

0.63

0.38

0.58

0.27

0.56

0.30

0.46

0.26

39.47[0.00]35.46[0.00]N.40.52[0.00]

Apergisetal.32.85/[0.00]

Int.Fin.33.92[0.00]Markets,37.58Inst.[0.00]and39.62[0.00]Money3836.64[0.00]

(2015)42–6430.57[0.00]17.93[0.00]28.48[0.00]

27.69

Table3(Continued)

(4.35)*

Lags=8

PanelB:Germany

RGDP0.752(3.38)*

Lags=10

RC0.732(3.80)*

Lags=9

RI1.328(4.25)*

Lags=9

UnR0.815(4.09)*

Lags=10

Section3:Turnover(TUR)PanelA:UK

RGDP0.683(4.27)*

Lags=10

RC0.655(4.18)*Lags=8

RI0.729(4.14)*

Lags=9UnR

0.835(5.15)*

Lags=9

PanelB:Germany

RGDP0.652(4.11)*Lags=8

RC0.612(4.51)*

Lags=9

RI0.625(3.86)*

Lags=9

UnR

0.753

ˇLIQˇHS(5.36)*(−5.12)*−0.4520.418(−5.49)*

(5.26)*

−0.4140.392(−5.32)*

(5.26)*

−0.2550.346(−5.41)*

(5.37)*

0.336−0.243(5.27)*

(−5.14)*

0.3590.413(5.38)*

(4.85)*

0.4170.463(5.22)*(5.40)*

0.3250.409(4.81)*

(5.36)*

−0.246−0.216(−4.88)*

(−4.84)*

0.4160.464(5.25)*(5.38)*0.4060.438(5.71)*

(4.91)*

0.2390.364(5.21)*

(5.48)*

−0.325

−0.339

ˇTSˇMRP(−4.30)*(−4.26)*0.3270.259(4.40)*

(5.25)*

0.2580.237(4.63)*

(5.02)*

0.4860.285(5.26)*

(5.03)*

−0.228−0.152(−5.08)*

(−4.81)*

0.3140.163(5.02)*

(5.29)*

0.2840.228(5.37)*

(4.82)*

0.3520.287(5.04)*

(5.25)*

−0.405−0.224(−5.35)*

(−4.30)*

0.3520.227(5.19)*(5.38)*0.3500.265(5.26)*

(5.28)*

0.4360.249(5.38)*

(5.15)*

−0.349

−0.147

ˇVˇSR(5.42)*(5.53)*−0.146−0.327(−5.18)*

(−5.29)*

−0.124−0.313(−4.97)*

(−6.06)*

−0.145−0.479(−5.18)*

(−5.40)*

0.1360.411(5.13)*

(4.81)*

−0.255−0.351(−5.34)*

(−5.28)*

−0.218−0.353(−5.25)*

(−5.36)*

−0.169−0.451(−5.36)*

(−5.52)*

0.1620.433(5.17)*

(5.74)*

−0.161−0.356(−5.30)*(−5.18)*−0.162−0.325(−5.20)*

(−5.51)*

−0.142−0.424(−5.06)*

(−4.98)*

0.418

0.279

ˇDSˇ1󰀅y

(5.10)*(−5.71)*−0.2970.510(−5.49)*

(6.39)*

−0.2960.530(−5.35)*

(5.92)*

−0.3470.526(−5.31)*

(5.71)*

0.325−0.463(5.24)*

(−4.96)*

−0.3020.549(−5.14)*

(6.10)*

−0.2550.537(−4.81)*

(5.39)*

−0.3640.520(−5.14)*

(5.92)*

0.259−0.482(4.72)*

(−5.92)*

−0.3020.479(−5.27)*(5.83)*

−0.3030.486(−5.04)*

(5.82)*

−0.3580.486(−5.14)*

(6.15)*

0.549

−0.415

R2Adj.

in.LIQ

ex.LIQ

0.63

0.40

0.57

0.28

0.55

0.22

0.52

0.29

0.63

0.34

0.55

0.31

0.57

0.33

0.48

0.24

0.60

0.37

0.58

0.30

0.54

0.23

0.52

0.31

F-test

[0.00]

33.48[0.00]

32.78[0.00]N.37.85[0.00]Apergisetal.35.23/[0.00]

Int.Fin.33.81Markets,[0.00]Inst.29.82and[0.00]Money30.6238[0.00]28.09(2015)[0.00]

42–6428.26[0.00]32.47[0.00]

37.13[0.00]32.59

53Table3(Continued)

ˇLIQˇHSˇTSˇMRPˇVˇSRˇDSˇ1󰀅y

R2Adj.

F-test

in.LIQ

ex.LIQ

(4.14)*

(−5.26)*(−5.16)*(−5.25)*(−5.16)*(5.07)*(5.72)*(5.24)*(−4.63)*[0.00]

Lags=8

Section4:Volume(VTR)PanelA:UK

RGDP0.7730.3630.4360.3290.209−0.262−0.330−0.2970.5360.61

0.38

30.06(4.25)*

(5.29)*

(5.14)*

(5.29)*

(5.24)*

(−5.28)*

(−5.03)*

(−5.25)*

(5.91)*

[0.00]Lags=10

RC0.7140.4420.4830.2750.246−0.240−0.321−0.2650.5270.64

0.30

32.94(4.06)*

(5.15)*

(5.39)*

(5.25)*

(−5.24)*

(−5.10)*

(−5.13)*

(5.86)*

[0.00]

Lags=8

RI0.8190.3620.4340.3470.238−0.180−0.531−0.3140.5080.60

0.36

30.13(5.02)*

(5.09)*

(4.92)*

(5.26)*

(5.18)*

(−5.45)*

(−5.32)*

(−5.29)*

(5.89)*

[0.00]Lags=8

UnR

0.674−0.244−0.248−0.386−0.2490.1640.4260.285−0.5370.48

0.25

34.18(5.36)*

(5.02)*

(−5.25)*

(−5.35)*

(−5.12)*

(5.42)*

(5.30)*

(5.16)*

(−5.79)*

[0.00]

Lags=9

PanelB:Germany

RGDP0.7140.4150.4290.3590.264−0.148−0.329−0.2360.5150.55

0.33

32.79(4.28)*

(5.48)*

(4.83)*

(5.23)*

(5.26)*

(−4.85)*

(−5.04)*

(−4.87)*

(5.40)*

[0.00]Lags=9

RC0.6940.4370.4050.3260.284−0.146−0.329−0.2270.5230.58

0.31

33.76(3.48)*

(4.92)*

(4.81)*

(5.37)*

(5.14)*

(−5.25)*

(−5.29)*

(−5.19)*

(5.61)*

[0.00]Lags=9

RI0.6580.2480.4110.4030.215−0.130−0.416−0.3820.5460.53

0.26

37.94(4.29)*

(4.82)*

(5.20)*

(5.26)*

(4.88)*

(−4.82)*

(−4.67)*

(−5.38)*

(5.52)*

[0.00]Lags=9

UnR0.652−0.234−0.335−0.352−0.2360.1380.4280.242−0.5450.50

0.26

35.13(4.27)*

(−5.21)*

(−5.03)*

(−5.27)*

(−4.25)*

(5.25)*

(4.79)*

(5.18)*

(−5.39)*

[0.00]

Lags=8

Thetablereportstheresultswhenweregresseachmacrovariable(RealGDP,RealConsumption,RealInvestment,Unemploymentrate),againsttheAmihudilliquidityratio(ILR)inSection1,therelativespread(RS)inSection2,theturnover(TUR)inSection3,volumetraded(VTR)inSection4andsixcontrolvariables(HS,TS,MRP,V,SR,DS)forUK(PanelA)andGermany(PanelB).Thecross-sectionalliquiditymeasuresarecalculatedasequallyweightedaveragesacrossstocks.Figuresinparenthesesdenotet-statistics.Thecolumnlabelled“R2in.LIQ”givestheadjustedR2foramodelwiththeliquidityproxy(LIQ)andthecolumnlabeled“R2ex.LIQ”givestheadjustedR2foramodelwithouttheliquidityproxy(LIQ).F-testdenotesthetestonthenullhypothesisthatacceptstherestrictedmodel(whentheLiquidityvariableisexcluded)andisbasedonthestatisticF=(RU2−RR2)/(1−RU2)×df1/(df0−df1),withRU2beingtheunrestrictedR2,RR2beingtherestrictedR2,df1=(N−k)degreesoffreedomanddf0=(N−k0)degreesoffreedom.Lags=showsthenumberoflagsofthedependentvariablesusedastheinstrumentsintheregression.*

Denotesstatisticalsigniﬁcanceatthe1%signiﬁcancelevel,whileﬁguresinbracketsdenotep-values.

54N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64Table4

IVEstimateswithliquidityproxiesforbothsmall-andlarge-capﬁrms.

ˇLIQSˇLIQLˇHSˇTSˇMRPˇVˇSRˇDSˇ󰀅y

R2adjusted

F-test

ex.LIQ

in.LIQ

Section1:Amihudilliquidityratio(ILR)PanelA:UK

RGDP

0.763(3.28)*

Lags=8

0.722(3.81)*

Lags=10

RI0.784(3.28)*

Lags=9

UnR

0.613(3.93)*Lags=10

PanelB:Germany

RGDP

0.589

(3.41)*

Lags=9

0.648(4.23)*

Lags=10

0.855(4.26)*

Lags=9

UnR

0.614(4.25)*

Lags=10

Section2:relativespread(RS)PanelA:UK

RGDP

0.682

(3.86)*

Lags=10

0.584

(4.38)*

Lags=9

0.685

(3.28)*

Lags=8

UnR

0.709

−0.159

−0.126(−5.28)*(−5.19)*

−0.236

−0.215(−5.20)*(−4.87)*

−0.236

−0.214(−5.38)*

(−5.29)*

0.242

0.214(5.37)*

(4.96)*

−0.134−0.118(−4.86)*(−4.71)*

−0.264

−0.216(−5.27)*(−5.38)*−0.246

−0.214(−5.18)*(−5.09)*

0.239

0.226(5.36)*(5.14)*

−0.174−0.125(−5.28)*(−5.48)*−0.139−0.148(−5.01)*

(−5.26)*

−0.236−0.225(−4.79)*

(−5.19)*

0.139

0.126

0.3140.168(5.92)*

(5.23)*

0.3250.132(5.16)*

(5.27)*

0.2880.337(4.82)*

(5.41)*

−0.248−0.329(−5.36)*

(−5.02)*

0.3280.213(4.52)*

(4.83)*

0.3420.147(5.28)*(5.16)*

0.3570.250(5.39)*

(5.26)*

−0.328−0.314(−5.30)*

(−5.28)*

0.4420.173(5.39)*(5.14)*0.3390.142(5.13)*

(5.06)*

0.3380.329(−5.41)*

(4.59)*

0.236

−0.338

0.139−0.147(5.42)*

(−5.28)*

0.245−0.156(5.19)*

(−5.24)*

0.226−0.136(5.38)*

(−5.10)*

−0.2350.149(−5.41)*

(5.14)*

0.125−0.128(4.94)*

(−5.03)*

0.249−0.135(5.36)*

(−5.17)*

0.242−0.141(5.37)*

(−5.17)*

−0.2270.135(−5.28)*

(5.19)*

0.142−0.248(5.14)*

(−5.19)*

0.248−0.215(5.30)*

(−4.84)*

0.253−0.246(5.12)*

(−5.15)*

−0.225

0.142

−0.245−0.249(−5.02)*

(−4.86)*

−0.329−0.248(−5.16)*

(−4.82)*

−0.412−0.312(−5.65)*

(−5.01)*

0.3270.226(5.25)*

(5.78)*

−0.256−0.214(−4.87)*

(−4.53)*

−0.329−0.226(−5.18)*

(−5.35)*

−0.329−0.324(−5.36)*

(−5.11)*

0.3240.285(5.07)*

(5.75)*

−0.284−0.265(−5.40)*

(−5.21)*

−0.352−0.254(−5.18)*

(−5.36)*

−0.428−0.240(−5.81)*

(−4.94)*

0.352

0.263

0.4350.60

(6.06)*

0.4260.55

(6.61)*

0.5140.51

(6.13)*

−0.4290.44

(−6.11)*

0.4290.53

(5.37)*

0.4300.56

(5.82)*

0.5140.50

(5.27)*

−0.3790.52

(−5.49)*

0.4680.58

(5.41)*

0.4390.52

(5.71)*

0.5160.52

(6.05)*

0.462

0.45

0.29

35.48[0.00]0.26

38.37[0.00]0.26

36.29[0.00]0.22

36.71[0.00]

0.31

31.75[0.00]0.30

33.32[0.00]0.30

30.48[0.00]

0.25

36.73[0.00]

0.34

33.29[0.00]0.28

34.21[0.00]0.26

28.26[0.00]0.23

28.33

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–645556Table4(Continued)

ˇLIQSˇLIQLˇHSˇTSˇMRPˇVˇSRˇDSˇ󰀅y

R2adjusted

F-test

(4.17)*

Lags=9

PanelB:Germany

RGDP0.685(3.16)*

Lags=8

RC0.652(4.19)*

Lags=8

RI0.840(4.27)*

Lags=10

UnR0.612(4.09)*Lags=9

Section3:turnover(TUR)PanelA:UK

RGDP0.736(3.95)*

Lags=9

RC0.714(4.21)*

Lags=9

RI0.724(4.25)*Lags=9

UnR

0.682(4.12)*

Lags=9

PanelB:GermanyRGDP0.583(4.32)*Lags=9

RC0.572(4.31)*

Lags=9

RI0.761(3.75)*

Lags=8

UnR

0.572

(5.11)*(5.30)*−0.168−0.155(−5.04)*

(−5.37)*

−0.225−0.159(−5.17)*

(−5.24)*

−0.268−0.224(−5.35)*

(−5.16)*

0.1980.157(5.10)*(5.13)*

0.1680.128(5.41)*

(5.04)*

0.2370.177(5.35)*

(5.21)*

0.1530.128(5.15)*(5.36)*−0.239−0.157(−5.46)*

(−5.39)*

0.1460.117(4.28)*(5.25)*0.2490.225(5.02)*

(5.01)*

0.1460.133(5.28)*

(5.19)*

−0.247

−0.227

(4.83)*(−4.88)*0.3530.245(5.01)*

(5.48)*

0.3280.158(4.92)*

(5.14)*

0.3300.268(5.17)*

(5.07)*

−0.329−0.325(−4.74)*

(−5.31)*

0.4280.217(5.00)*

(5.16)*

0.3410.135(5.38)*

(5.11)*

0.3210.325(5.19)*(5.26)*0.258−0.339(5.26)*

(−5.12)*

0.3740.285(5.06)*(4.96)*

0.4090.160(5.16)*

(5.08)*

0.3250.342(5.14)*

(5.21)*

0.345

−0.152

(−5.17)*(5.13)*0.146−0.247(5.15)*

(−5.20)*

0.244−0.262(5.15)*

(−5.07)*

0.255−0.152(5.21)*

(−5.29)*

−0.1620.149(−5.24)*

(5.20)*

0.236−0.253(5.14)*

(−4.88)*

0.249−0.224(5.26)*

(−5.19)*

0.239−0.238(5.36)*

(−5.51)*

−0.1600.145(−4.86)*

(5.24)*

0.238−0.229(4.87)*

(−5.14)*

0.225−0.234(5.24)*

(−5.26)*

0.249−0.237(4.86)*

(−5.02)*

0.158

0.416

(5.26)*(5.90)*−0.313−0.228(−5.25)*

(−5.19)*

−0.325−0.249(−5.16)*

(−5.04)*

−0.328−0.241(−5.82)*

(−4.80)*

0.3470.286(5.19)*

(6.25)*

−0.296−0.238(−4.74)*

(−5.29)*

−0.335−0.226(−4.92)*

(−5.15)*

−0.324−0.255(−5.29)*

(−5.07)*

0.3320.253(4.91)*

(5.85)*

−0.316−0.214(−4.78)*

(−5.24)*

−0.349−0.215(−5.26)*

(−5.26)*

−0.413−0.238(−5.63)*

(−4.86)*

0.238

0.485

in.LIQ

(5.97)*0.5070.60

(6.36)*

0.4180.54

(5.86)*

0.4810.52

(6.14)*

−0.4180.54

(−5.44)*

0.4290.61

(6.15)*

0.4360.50

(5.84)*

0.4720.52

(6.10)*

0.4460.47

(6.17)*

0.4290.55

(5.06)*

0.4060.52

(5.82)*

0.4150.57

(5.26)*

−0.252

0.58

ex.LIQ

[0.00]

0.31

36.18[0.00]0.29

38.33[0.00]0.27

31.08[0.00]0.24

35.89[0.00]

0.32

34.27[0.00]0.24

34.19[0.00]0.28

33.64[0.00]0.24

34.63[0.00]

0.32

29.78[0.00]0.30

36.15[0.00]

0.29

32.16[0.00]0.27

34.83

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64Table4(Continued)

ˇLIQSˇLIQLˇHSˇTSˇMRPˇVˇSRˇDSˇ󰀅y

R2adjusted

F-test

in.LIQ

ex.LIQ

(4.11)*

(−4.92)*(−5.39)*(5.25)*(−5.19)*(5.32)*(5.74)*(5.29)*(5.82)*(−4.37)*[0.00]

Lags=10

Section4:Volume(VTR)PanelA:UK

RGDP0.6580.2270.1460.3500.2150.159−0.246−0.342−0.2360.4480.60

0.35

33.29(4.12)*

(5.25)*

(5.03)*

(5.27)*

(5.37)*

(5.36)*

(−5.10)*

(−5.84)*

(−5.15)*

(5.33)*

[0.00]Lags=9

RC0.5140.1390.1260.3140.1450.237−0.214−0.324−0.2360.4350.54

0.26

33.95(4.20)*

(5.05)*

(5.30)*

(5.08)*

(5.20)*

(5.31)*

(−5.02)*

(−4.84)*

(−4.79)*

(5.91)*

[0.00]Lags=10

RI0.6720.2360.2270.3840.2850.242−0.213−0.427−0.2250.4620.54

0.30

36.15(4.32)*

(5.13)*

(4.81)*

(5.25)*

(5.12)*

(5.36)*

(−5.21)*

(−5.89)*

(−5.26)*

(5.36)*

[0.00]

Lags=10

UnR

0.732−0.232−0.148−0.305−0.249−0.2360.2060.3920.2640.4270.48

0.26

35.19(4.10)*

(−5.14)*

(−5.13)*

(−5.20)*

(−5.31)*

(−5.12)*

(5.15)*

(5.11)*

(5.72)*

(5.24)*

[0.00]

Lags=10

PanelB:Germany

RGDP0.6070.1850.1550.4420.2480.174−0.310−0.326−0.2510.5120.59

0.33

34.16(3.78)*

(5.16)*

(5.26)*

(5.37)*

(5.05)*

(5.28)*

(−5.42)*

(−5.24)*

(−5.39)*

(6.08)*

[0.00]Lags=8

RC0.6250.1920.1490.3510.2090.254−0.158−0.339−0.2260.4360.57

0.33

33.85(3.91)*

(5.04)*

(5.24)*

(5.16)*

(5.25)*

(5.17)*

(−4.93)*

(−5.18)*

(−4.85)*

(5.94)*

[0.00]Lags=19

RI0.4830.2360.2180.3490.2470.240−0.247−0.429−0.2180.5460.61

0.29

36.42(3.39)*

(5.25)*

(5.26)*

(5.07)*

(5.12)*

(5.21)*

(−5.37)*

(−6.13)*

(−5.03)*

(5.72)*

[0.00]Lags=10

UnR0.606−0.223−0.158−0.327−0.239−0.4290.3050.4580.224−0.3370.55

0.27

31.64(4.15)*

(−5.19)*

(−4.84)*

(−5.13)*

(−5.36)*

(−5.17)*

(6.14)*

(5.92)*

(4.54)*

(−4.83)*

[0.00]

Lags=11

Thetablereportstheresultswhenweregresseachmacrovariable(RealGDP,RealConsumption,RealInvestment,Unemploymentrate),againsttheAmihudilliquidityratio(ILR)inSection1,therelativespread(RS)inSection2,theturnover(TUR)inSection3,Volumetraded(VTR)inSection4,forsmall-cap(LIQS)andlarge-cap(LIQL)ﬁrms,andsixcontrolvariables(HS,TS,MRP,V,SR,DS)forUK(PanelA)andGermany(PanelB).Thet-statisticsarereportedinparentheses.Thecolumnlabeled“R2in.LIQ”givestheadjustedR2foramodelwithbothilliquidityratiosandthecolumnlabeled“R2ex.LIQ”givestheadjustedR2foramodelwithoutanyilliquidityratios.F-testdenotesthetestofthenullhypothesisthatacceptstherestrictedmodel(whentheLiquidityvariableisexcluded)andisbasedonthestatisticF=(RU2−RR2)/(1−RU2)xdf1/(df0−df1),withRU2beingtheunrestrictedR2,RR2beingtherestrictedR2,df1=(N−k)degreesoffreedomanddf0=(N−k0)degreesoffreedom.Lags=showsthenumberoflagsofthedependentvariablesusedastheinstrumentsintheregression.*

Denotesstatisticalsigniﬁcanceatthe1%signiﬁcancelevel,whileﬁguresinbracketsdenotep-values.

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–645758

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Table5

Waldtestsforsmall-andlarge-capﬁrms.

UKvariables

Germanyvariables

RGDP

UnR

RGDP

UnR

PanelA:H0:ˇLIQS−ˇLIQL=0Illiquidityratio(ILR)H0:ˇILRS−ˇILRL=0Relativespread(RS)H0:ˇRSS−ˇRSL=0Turnover(TUR)

H0:ˇTURS−ˇTURL=0Volume(VTR)

H0:ˇVTRS−ˇVTRL=0PanelB:H0:ˇLIQS−ˇLIQL>0Illiquidityratio(ILR)H0:ˇILRS−ˇILRL>0Relativespread(RS)H0:ˇRSS−ˇRSL>0Turnover(TUR)

H0:ˇTURS−ˇTURL>0Volume(VTR)

H0:ˇVTRS−ˇVTRL>0

(0.01)

(0.00)

(0.01)

(0.00)

(0.01)

(0.00)

(0.01)

(0.00)(0.00)(0.00)(0.00)

(0.00)

(0.01)

(0.00)

(0.01)

(0.00)

(0.01)

(0.00)

(0.01)

(0.00)

(0.01)

(0.00)

(0.01)

(0.23)

(0.24)

(0.20)

(0.16)

(0.26)

(0.22)

(0.21)

(0.19)(0.22)(0.20)(0.26)

(0.20)

(0.18)

(0.14)

(0.12)

(0.21)

(0.28)

(0.22)

(0.16)

(0.12)

(0.24)

(0.32)

(0.25)

(0.22)

(0.31)

(0.27)

(0.21)

(0.29)

(0.35)

(0.28)

ThetableshowsWaldtestsbetweenthecoefﬁcientsoftheliquidityproxiesforbothsmall-andlarge-capﬁrms.ThetestisperformedforthewholesampleperiodfortheUKfrom1994to2011andforGermanyfrom1999to2011.Foreachmeasure,inPanelAwetestthenullhypothesisthatthedifferencebetweentheilliquiditymeasureforsmall-andlarge-capﬁrmsisequaltozeroandsecondinPanelBwetestthenullhypothesisthatthedifferencebetweentheilliquiditymeasureforsmall-andlarge-capﬁrmsisgreaterthanzero.Wereportp-valuesinparenthesesforeachtest.

Table6

CausalityresultsforUK&Germany(bothsmallandlargeﬁrms).

UKvariables

Germanyvariables

RGDP

UnR

RGDP

UnR(+)17.81(0.00)*0.21(0.59)(+)23.18(0.00)*1.03(0.67)(−)18.14(0.00)*1.24(0.56)(−)19.85(0.00)*1.27(0.36)

Illiquidityratio

H0:󰀅ILR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅ILR󰀄2-testp-Value

Relativespread(RS)H0:󰀅RS󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅RS󰀄2-testp-ValueTurnover(TUR)

H0:󰀅TUR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅TUR󰀄2-testp-ValueVolume(VTR)

H0:󰀅VTR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅VTR󰀄2-testp-Value

(−)19.74(0.00)*

(−)18.36(0.00)*

(−)17.34(0.00)*

(+)15.92(0.00)*

(−)18.28(0.00)*

(−)16.15(0.00)*

(−)24.66(0.00)*

0.36(0.58)

0.06(0.78)

0.09(0.78)

0.22(0.61)

0.58(0.47)

0.03(0.88)

0.00(0.94)

(−)16.59(0.00)*

(−)17.82(0.00)*

(−)20.53(0.00)*

(+)20.29(0.00)*

(−)15.24(0.00)*

(−)28.16(0.00)*

(−)20.53(0.00)*

0.57(0.49)

0.12(0.79)

0.00(0.99)

0.01(0.99)

2.04(0.31)

0.75(0.50)

0.84(0.71)

(+)18.64(0.00)*

(+)15.43(0.00)*

(+)19.61(0.00)*

(−)15.14(0.00)*

(+)20.47(0.00)*

(+)15.42(0.00)*

(+)22.36(0.00)*

15.52(0.00)*

22.71(0.00)*

1.05(0.45)

1.12(0.59)

18.93(0.00)*

24.22(0.00)*

0.00(0.99)

(+)18.49(0.00)*

(+)16.45(0.00)*

(+)20.73(0.00)*

(−)19.37(0.00)*

(+)17.21(0.00)*

(+)20.53(0.00)*

(+)22.90(0.00)*

17.54(0.00)*

22.62(0.00)*

0.38(0.64)

0.52(0.49)

19.82(0.00)*

16.35(0.00)*

0.00(0.99)

ThetableshowsGrangercausalitytestsbetween󰀅MACRO:(a)realGDPgrowth,(b)realconsumption,(c)realinvestment,(d)theunemploymentrateand(a)theAmihudILR,(b)therelativespread(RS),(c)turnover(TUR)and(d)volumetraded(VTR).Thecross-sectionalliquiditymeasuresarecalculatedasequallyweightedaveragesacrossstocks.ThetestisperformedforthewholesampleperiodfortheUKfrom1994to2011andforGermanyfrom1999to2011.Foreachmeasure,weﬁrsttestthenullhypothesisthatmacrovariabledoesnotGrangercausemarketilliquidityandwhethermarketilliquiditydoesnotGrangercausethemacrovariable.Theresultsinparenthesesdenotethesignoftheassociationbetweenthevariablesunderinvestigation.WereportF-testvaluesandcorrespondingp-values(inparentheses)foreachtest.*

Denotesarejectionofthenullhypothesisofcausalityatthe1%level.

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Table7

CausalityresultsforUK&Germany(smallﬁrms).

UKvariables

Germanyvariables

RGDP

UnR

RGDP

UnR(+)32.53(0.00)*6.36(0.12)(+)28.93(0.00)*15.93(0.00)*(−)25.52(0.00)*25.26(0.00)*(−)25.31(0.00)*23.09(0.00)*

Illiquidityratio

H0:󰀅ILR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅ILR󰀄2-testp-Value

Relativespread(RS)H0:󰀅RS󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅RS󰀄2-testp-ValueTurnover(TUR)

H0:󰀅TUR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅TUR󰀄2-testp-ValueVolume(VTR)

H0:󰀅VTR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅VTR󰀄2-testp-Value

(−)37.61(0.00)*

(−)32.19(0.00)*

(−)25.62(0.00)*

(+)17.06(0.00)*

(−)29.17(0.00)*

(−)32.53(0.00)*

(−)30.88(0.00)*

7.16(0.11)

7.81(0.11)

6.42(0.14)

9.72(0.10)***

8.05(0.11)

4.91(0.18)

10.52(0.09)***

(−)30.15(0.00)*

(−)28.45(0.00)*

(−)27.55(0.00)*

(+)26.27(0.00)*

(−)34.02(0.00)*

(−)29.62(0.00)*

(−)25.16(0.00)*

16.13(0.00)*

12.35(0.02)**

13.52(0.01)*

15.41(0.01)*

17.54(0.00)*

15.31(0.01)*

11.37(0.03)**

(+)31.25(0.00)*

(+)24.18(0.00)*

(+)26.48(0.00)*

(−)23.92(0.00)*

(+)33.84(0.00)*

(+)24.02(0.00)*

(+)33.16(0.00)*

21.46(0.00)*

33.17(0.00)*

25.09(0.00)*

29.66(0.00)*

36.03(0.00)*

32.45(0.00)*

25.16(0.00)*

(+)31.16(0.00)*

(+)22.63(0.00)*

(+)29.71(0.00)*

(−)22.45(0.00)*

(+)26.15(0.00)*

(+)28.73(0.00)*

(+)26.26(0.00)*

34.32(0.00)*

35.16(0.00)*

27.94(0.00)*

25.86(0.00)*

33.15(0.00)*

27.38(0.00)*

25.17(0.00)*

ThetableshowsGrangercausalitytestsbetween󰀅MACRO:(a)realGDPgrowth,(b)realconsumption,(c)realinvestment,(d)theunemploymentrateand(a)theAmihudILR,(b)therelativespread(RS),(c)turnover(TUR)and(d)volumetraded(VTR).Thecross-sectionalliquiditymeasuresarecalculatedasequallyweightedaveragesacrossthe25%smallcapﬁrms(LIQS).ThetestisperformedforthewholesampleperiodfortheUKfrom1994to2011andforGermanyfrom1999to2011.Foreachmeasure,weﬁrsttestthenullhypothesisthatmacrovariabledoesnotGrangercausemarketilliquidityandwhethermarketilliquiditydoesnotGrangercausethemacrovariable.Theresultsinparenthesesdenotethesignoftheassociationbetweenthevariablesunderinvestigation.WereportF-testvaluesandcorrespondingp-values(inparentheses)foreachtest.******,,Denotetherejectionofthenullhypothesisofcausalityatthe1%,5%,10%levels,respectively.

crisis(Cassolaetal.,2009).Insuchasituation,bankscannotattractadditionaldepositseasilyandwithoutasigniﬁcantcostofdeposits,i.e.,higherinterestrates.Moreover,AllenandCarletti(2008)emphasizethepositiveroleofbanksforbettermonitoringoflendingandtheirrisksharingroleinincompletemarketsandpointoutthatbanksarealsoexposedtodeposits’withdrawalsordry-upofliquidityintheshort-termcapitalmarkets;inthatsense,theycanspreadthecrisestotherealeconomy.AsNyborgandÖstberg(2014)document,theliquiditypull-backhypothesisisvalidevenforthepre-crisisperiod,whileitseffectissubstantiallystrongerfortheUSmarketoverthepre-crisisperiod,thanoverthecrisisperiodduetotheimmediateresponseoftheUSFedwithaloosemonetarypolicy(e.g.,TAFandQuantitativeEasingmeasures)whichhelpedthebankstocurtailtheirneedsforaliquiditypull-back.

Theresultsregardingthestrongexplanatorypoweroftheliquidityproxiesforeconomicactivityareverysimilartothosereportedbypreviousempiricalstudiesfollowingasimilarapproach(Meichleetal.,2011;Næsetal.,2011;Florackisetal.,2014a).Inparticular,ifwecompareourﬁndingswiththosebyNæsetal.(2011),weconcludethatwegetevenstrongerresults(i.e.,higherR2valuesinourcase),whichpointtothesamedirection.Thisconclusioncanalsobedocumentedbythefactthatweobtainstatisticalsigniﬁcanceconsistentlyacrossallindependentvariables(includingthecontrolvariables)andacrossallequationsused,withoutlosingtheincrementalinformationalcontentoftheilliquidity/liquidityproxies.Incontrast,inthestudyofNæsetal.(2011)whenthedependentvariableiseithertheinvestmentortheconsumptionvariable,whiletheyaddbothexcessmarketreturnsandvolatility,thecoefﬁcientoftheILRproxyturnsouttobestatisticallyinsigniﬁcant,alongwithinsigniﬁcantcoefﬁcientsofthevolatilitymeasure.

Finally,Table4showstheestimationresultsfortheUKandGermany,whentheliquidityratioproxy(ILR,RS,TURandVTR)isappliedforbothsmallandlargecapﬁrms.ThelastthreecolumnsinTable4showthevaluesoftheR2again,undertwooptions:withtheliquidityproxyofbothsmallandlargecapﬁrmsandwithouttheliquidityproxyforbothﬁrmsandtheF-test,whichteststhenullhypothesisthatacceptstherestrictedmodel(whenbothliquidityvariablesareexcluded).Wecanobservethatthecoefﬁcientacrossallliquidityproxies(ILR,RS,TURandVTR)regardingsmallﬁrmsishigherthanthecorrespondingliquiditycoefﬁcientforlargeﬁrms.Thisdifferenceremainsconsistentacrossalldifferentapplicationsofdependentvariables(RGDP,RC,RIandUnR)andinbothcountries.Thisﬁndingimpliesthattheimpactoftheliquidityproxyoneconomicactivityismorepronouncedinthecaseofsmallcapﬁrms,asitwasexpected.Forbothcountriesandacrossall

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Table8

CausalityresultsforUK&Germany(largeﬁrms).

UKvariables

Germanyvariables

RGDP

UnR

RGDP

UnR(+)24.84(0.00)*0.54(0.58)(+)30.43(0.00)*1.16(0.64)(−)25.94(0.00)*1.38(0.40)(−)25.19(0.00)*1.16(0.45)

Illiquidityratio

H0:󰀅ILR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅ILR󰀄2-testp-Value

Relativespread(RS)H0:󰀅RS󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅RS󰀄2-testp-ValueTurnover(TUR)

H0:󰀅TUR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅TUR󰀄2-testp-ValueVolume(VTR)

H0:󰀅VTR󰀁󰀅MACRO󰀄2-testp-Value

H0:󰀅MACRO󰀁󰀅VTR󰀄2-testp-Value

(−)28.59(0.00)*

(−)30.26(0.00)*

(−)23.92(0.00)*

(+)25.14(0.00)*

(−)23.82(0.00)*

(−)22.61(0.00)*

(−)32.19(0.00)*

1.17(0.42)

0.36(0.75)

0.58(0.69)

0.41(0.63)

1.45(0.33)

0.24(0.81)

0.25(0.85)

(−)27.25(0.00)*

(−)22.17(0.00)*

(−)28.03(0.00)*

(+)30.48(0.00)*

(−)26.13(0.00)*

(−)28.27(0.00)*

(−)26.92(0.00)*

2.24(0.30)

0.38(0.72)

0.24(0.79)

0.52(0.83)

2.26(0.20)

1.24(0.33)

1.39(0.73)

(+)31.26(0.00)*

(+)23.29(0.00)*

(+)21.08(0.00)*

(−)22.36(0.00)*

(+)34.22(0.00)*

(+)23.19(0.00)*

(+)32.14(0.00)*

2.03(0.29)

1.46(0.48)

1.15(0.50)

1.29(0.48)

2.12(0.30)

1.24(0.49)

0.37(0.78)

(+)28.01(0.00)*

(+)22.36(0.00)*

(+)29.32(0.00)*

(−)23.16(0.00)*

(+)28.13(0.00)*

(+)27.14(0.00)*

(+)30.35(0.00)*

1.25(0.39)

1.72(0.35)

0.58(0.40)

0.68(0.43)

1.09(0.32)

0.71(0.41)

0.28(0.76)

ThetableshowsGrangercausalitytestsbetween󰀅MACRO:(a)realGDPgrowth,(b)realconsumption,(c)realinvestment,(d)theunemploymentrateand(a)theAmihudILR,(b)therelativespread(RS),(c)turnover(TUR)and(d)volumetraded(VTR).Thecross-sectionalliquiditymeasuresarecalculatedasequallyweightedaveragesacrossthe25%largecapﬁrms(LIQL).ThetestisperformedforthewholesampleperiodfortheUKfrom1994to2011andforGermanyfrom1999to2011.Foreachmeasure,weﬁrsttestthenullhypothesisthatmacrovariabledoesnotGrangercausemarketilliquidityandwhethermarketilliquiditydoesnotGrangercausethemacrovariable.Theresultsinparenthesesdenotethesignoftheassociationbetweenthevariablesunderinvestigation.WereportF-testvaluesandcorrespondingp-values(inparentheses)foreachtest.*

Denotesarejectionofthenullhypothesisofcausalityatthe1%level.

macrovariables,whenweincludeboththeliquidityproxiestheR2turnsouttobehigherthanthatobtainedbyexcludingthem.Forexample,inSection1(ILR)intheequationofRGDPfortheUK,theR2intheﬁrstcaseisupto60%,whileinthelattercaseitgoesdownto29%.AsimilareffectisfoundinthecaseofGermany(sameSection1,ILR),whentheR2goesupfrom31%to53%,whenILRisincluded.

Toenhancetherobustnessoftheseﬁndings,wefurthertestwhetherthereisadifferencebetweenthecoefﬁcientsoftheliquidityproxiesforsmall-capandlarge-capﬁrmsbyperformingtheWaldtestsinTable5.Foreachmeasure,weﬁrsttestthenullhypothesisthatthedifferencebetweentheliquidityproxyforsmall-andlarge-capﬁrmsisequaltozero(PanelA)andthentestthenullhypothesisthatthedifferencebetweentheilliquiditymeasureforsmall-andlarge-capﬁrmsisgreaterthanzero(PanelB).Theresultsobtainedindicatethatinbothcountriesandacrossallmacrovariables,theliquiditycoefﬁcientofthesmall-capﬁrmsisstatisticallysigniﬁcantdifferentfromtheliquiditycoefﬁcientofthelarge-capﬁrmsandthattheliquiditycoefﬁcientofthesmall-capﬁrmsisstatisticallysigniﬁcantlargerthattheliquiditycoefﬁcientofthelarge-capﬁrms,indicatingthelargereffectofsmall-capﬁrmliquidityinexplainingeconomicactivity.Thisﬁndingisinagreementwithanumberofpreviousstudies(e.g.,Amihud,2002;Næsetal.,2011;CakiciandTan,2014).Thus,itisimportantforinvestorsandcentralbankauthoritiestowatchcloselyforalargedropintheliquidityofsmallﬁrmsstocks,aslongasitgivesastrongsignalforthebeginningofarecessionaryperiod.Asinvestorsmaystartswitchingfromtheirpositionsonsmallcapstockstogovernmentbondsorlargecapstocks,centralbanksmayincreasepromptlythemoneysupplyaimingtostimulatetherealeconomyandhencetoavoidplunginginadeepandprolongedrecession.

4.2.Causalitytests

Thecausalityresults,reportedinTable6,displaythatinboththeUKandtheGermanstockmarketsthereexistsaone-waycausalityrunningfromboththeilliquidityratio(ILR)andtherelativespread(RS)toallfouralternativemacroeconomicvariables(󰀅MACRO).Theseﬁndingsarecompatiblewiththeforward-lookingnatureofliquidityrelatedtothestockmarketasdocumentedbyFama(1991).Inaddition,itrecognizestheimportanceofmarketliquidityasacomponentoftheﬁnancialsystemintheprocessofeconomicgrowth,gainingfurthersupportbytheargumentputforwardbyLevineandZervos(1998).

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

Table9

CausalityresultsforUK&Germanybetweensmallandlargeﬁrms’liquiditymeasures.

Germany(+)19.64*(0.00)(+)3.92(0.16)(+)20.75*(0.00)(+)3.38(0.24)(+)29.07*(0.00)(+)3.75*(0.18)(+)36.83*(0.00)(+)3.62(0.20)

Illiquidityratio

H0:󰀅ILRS󰀁󰀅ILRL󰀄2-testp-Value

H0:󰀅ILRL󰀁󰀅ILRS󰀄2-testp-Value

Relativespread(RS)H0:󰀅RSS󰀁󰀅RSL󰀄2-testp-Value

H0:󰀅RSL󰀁󰀅RSS󰀄2-testp-ValueTurnover(TUR)

H0:󰀅TURS󰀁󰀅TURL󰀄2-testp-Value

(+)24.93*(0.00)(+)3.51(0.19)

(+)23.63*(0.00)(+)2.74(0.35)

(+)26.93*(0.00)

H0:󰀅TURL󰀁󰀅TURS󰀄2-testp-ValueVolume(VTR)

H0:󰀅VTRS󰀁󰀅VTRL󰀄2-testp-Value

H0:󰀅VTRL󰀁󰀅VTRS󰀄2-testp-Value

(+)2.16(0.41)

(+)30.17*(0.00)(+)2.27(0.37)

ThetableshowsGrangercausalitytestsbetweenthe(a)AmihudILRofsmallandlargeﬁrms,(b)relativespread(RS)ofsmallandlargeﬁrms,(c)turnover(TUR)ofsmallandlargeﬁrms,and(d)volumetraded(VTR)ofsmallandlargeﬁrms.Thecross-sectionalliquiditymeasuresarecalculatedasequallyweightedaveragesacrossstocks.ThetestisperformedforthewholesampleperiodfortheUKfrom1994to2011andforGermanyfrom1999to2011.Foreachmeasure,weﬁrsttestthenullhypothesisthattheliquiditymeasureforsmallﬁrmsdoesnotGrangercauseliquidityforlargeﬁrmsandwhetherliquidityforlargeﬁrmsdoesnotGrangercauseliquidityforsmallﬁrms.Theresultsinparenthesesdenotethesignoftheassociationbetweenthevariablesunderinvestigation.WereportF-testvaluesandcorrespondingp-values(inparentheses)foreachtest.*

Denotesarejectionofthenullhypothesisofcausalityatthe1%level.

Inparticular,marketliquidityisimportanttorestoretheconﬁdenceofinvestorsinthevalueofinformationassociatedwithtrading.Therefore,investors,inthecaseofincreasesinmarketliquidity,areencouragedtoinvestmoreheavily,increasingtheﬂowofcapital,leadingtofurtherincreasesineconomicactivity.

Bycontrast,fortheturnoverandthetradingvolumeliquidityindicesthisone-waycausalityholdsonlyinthecasesofinvestmentandtheunemploymentrateinbothcountries.Thepresenceoftwo-waycausalitydenotesthatthegrowthprocessitselfnurturesthegrowthofﬁrmsand,consequently,increasesthereturnstothosebusinesses;asaresult,highergrowthlevelsprovideaboostbothtothestockmarketandtotheliquiditymeasuresassociatedwithit.

OurﬁndingstendtobeconsistentwiththeﬁndingsbyNæsetal.(2011)whodocumentthatforthewholesampleperiodthereisfullsupportforGrangerone-waycausalityfrommarketilliquidity/liquidityproxies(ILR,implicitspreadestimatorofRoll,theLOTmeasure)toGDP,whilenoreversecausalityfromGDPtotheseproxiesispresent.

TheseresultsarealsoconsistentwiththeargumentputforwardbyLevineandZervos(1998)andRousseauandWachtel(2000),accordingtowhich,marketliquidityisrelatedtoeconomicgrowth.Asinvestorsareencouragedbyhighmarketliquiditytoinvestinequitiesandincreasetheﬂowofcapital,suchmoveswouldefﬁcientlyallocateresourcesand,hence,enhanceeconomicgrowthinthelongrun.Thecausalityempiricalﬁndingsdisplaythatstockmarketscaneffectivelymobilizefundsthathavebeennotfullyabsorbedbyﬁnancialintermediariesintoproductiveinvestmentsand,hence,spureconomicgrowth.

ThecausalitytestswerealsoperformedseparatelyforsmallandlargesizedcompaniesandtheresultsarereportedinTables7and8,respectively.Ourinitialﬁndingsconcerningtheonewaycausalityrunningfromtheilliquidityratio(ILR)andtherelativespread(RS)toallfourmacroeconomicvariablesarevalidatedfromtheanalysisofsmallcapﬁrmsonlyforthecaseofILR.

Weconsiderthatthisﬁndingmaybejustiﬁedonthebasisoftheargumentthatsmallﬁrmsaremorevulnerabletonegativemacroeconomicshocksthanlargeﬁrmsandthustheirliquidityisﬁrstlyaffectedbyadversemacroeconomicconditions,eveniftheirdropinliquidityhasmorepredictivepowerfortheoncomingrecessionthanthatofthelargeﬁrms.ThisisconsistentwiththeﬁndingsprovidedbyGertlerandGilchrist(1994)whoreportthatsmallﬁrmsaremoresensitivethanlargeﬁrmstonegativechangesinthemacroeconomicenvironment(e.g.,theirsalesdeclinefasterfollowingacontractioninbanklendingaswellasafallinGDP).Thisimpactisstrongerforsmallﬁrmsandisconsummatedthroughboththebank

N.Apergisetal./Int.Fin.Markets,Inst.andMoney38(2015)42–64

lendingandborrowingchannels,asKhwajaandMian(2008)showexaminingthecaseofabankliquiditycrisisinPakistanin1998.Therefore,smallﬁrmswouldbetheﬁrstwhowillexperiencetheeffectsofacreditcrunchandacontractionaryeconomy.

Lookingatthecausalitytestsresultsobtainedforthesampleofonlylargeﬁrms(Table8)wecanobservethataclearone-waycausalitylinkexistsforallliquidityandmacroeconomicvariablesexaminedacrossboththeUKandGermany.Thus,itseemsthattheone-waycausality,whichisprevalentinthesampleoflargeﬁrms,dominatesthemarginaltwo-waycausalityrelationshipobservedinthesampleofthesmallﬁrms.

Finally,asrobustnesstestsweperformedGrangercausalitytestsbetweensmallandlargecapliquidityproxies(whenbothvariableshavebeenexplicitlyusedintheregressions)acrossallfourliquiditymeasuresandtheresultsarereportedinTable9.Wefocusonlyonthecausalityresultsacrossthetwotypesofﬁrmsandtheﬁndingsdocumentthatacrossbotheconomiesandacrossliquiditymeasures,thereexistsaunivariatecausalityrunningfromtheliquidityofsmallﬁrmstothatoflargeﬁrms.Inotherwords,liquidityinnovationsinsmallﬁrmsareinformativeinpredictingliquidityshiftsinlargeﬁrms,whiletheotherwayarounddoesnotseemtohold.Thisasymmetrysuggeststhatincaseofstressfulmacroeconomicenvironmentsthereexistsrelativelyamoreactiveroleofthesmallcapsectorinpropagatingmarket-wideshocks.Transac-tionsinresponsetoeconomiceventsoccurﬁrstinsmallstocks,andthenspilloverovertolargestocks.Inthatcase,marketparticipants/investorschoosetoexploitanyinformationaladvantagetheyareholdinginthesmall-capsector,whichmaydriveliquidity/orilliquiditymeasuresandmaycauselargeﬁrms’liquiditytolagtothatofsmallﬁrms.

5.Conclusions

Thepresentresearchstudiedtheinformationcontentofstockmarketliquidityoneconomicconditionsintwohighlycapitaldevelopedcountries,theUKandGermany.Theempiricalresultssuggestedthatstockmarketliquidityandeconomicindicatorswerestronglyassociatedacrossbotheconomies,eventhoughtheUKisacapitalmarket-basedeconomyandGermanyabank-basedeconomy.Theseﬁndingshighlightthatthemechanismofchannellingfundstotheeconomy(viamarketsorviabanks)doesnotmatter,atleastformaturemarkets,whilethereisnotanydifferentialroleofliquidityinexplainingthecourseofmacroeconomicvariables.However,theliquidityofsmall-capﬁrmsprovedtobemoreimportantthanlarge-capﬁrmliquidity,inbothcountries,revealingthatinvestorsreallocatetheirportfoliosfromilliquidsmall-capriskystockstolessriskylarge-capstocks(the“ﬂighttoquality”effect)withhigherliquidity,whentheexpectationsforthefuturestateoftheeconomychange.

Ourresultscouldhelppolicymakersandcorporatemanagersimproveresourceallocation,sincetheybothcanbeconﬁ-dentenoughinmakinguseofstockmarketliquiditytoreachdecisionsthatrelyheavilyuponeconomicactivity.Inaddition,providingmorestrengthtotheliquidityproﬁleofacapitalmarketisexpectedtoreducetheriskassociatedwithinvestments,asthiswillallowsaverstoacquireequitiesandsellthemreallyfastandwithoutincurringhighcostsiftheyneedtomakechangesintheirportfolios.Anenhancedmodeofstockmarketliquiditywillalsoimprovecapitalallocations,thus,leadingtofurtherinvestments.Furthermore,ﬁrmswithilliquidmarketsfortheirequitytendtobemoreexposedtoanumberofexternaltothemshocks.Therefore,byprovidingliquiditytothestockmarketisexpectedtosubstantiallyreduceliquidityrisksfacedbyinvestorsand,moreover,thiswillleadtoequitycapitalcostreductionsinfuturefundraisingandfutureeconomicgrowth(Levine,1991;LernerandSchoar,2004).

Whatshouldpolicymakersdoinordertopushstockmarketliquidity?Theyshouldremoveanypotentialimpediments,suchastax,legalandregulatorybarrierstostockmarketdevelopment.Duringacrisiseventwecannotignoretheroleofmonetaryauthoritiesintheprocessofimplementinganefﬁcientmonetarypolicywithrespecttomaintainingstableﬁnancialmarkets,giventhatduringacrisis,stockmarketsarehighlyilliquid.Therefore,theroleofthecentralbanktomaintaintherequiredliquiditylevelsisamajoronebyprovidingliquiditytothosemarketsanddirectlytolargeinvestorsthatholdlongpositionsinstocks.However,asarecentstudybyFlorackisetal.(2014b)showed,traditionaltoolsofmonetarypolicy(e.g.,cutsininterestrates)maynotbeeffective,atleastintheUK,sincetheywereperceivedbythemarketparticipantsasasignalofdeterioratingeconomicprospectsandinfactaggravatedthe“ﬂighttosafety”effect,tradingeitherfromstockstogovernmentbondsorfromlessliquid(e.g.,smallcap)stockstomoreliquidones(largecapstocks).

Theneedforfurtherresearchisobviousbyincludingmorecountrieswithdevelopedcapitalmarkets,and/orcountrieswithlessdevelopedcapitalmarketsaroundtheglobeinordertoobtainmoreevidenceontheactualrelationshipbetweenstockmarketliquidityandeconomicconditions.Moreover,futureresearchattemptscouldidentifythosefactorsthataffectdirectlystockmarketliquidityand,therefore,indirectlymacroeconomicactivity,suchas,legal,regulatory,accounting,tax,political,andmacroeconomicfactors.Forexampleoneofthesefactorsmaybetheanalysts’forecasterrorsandfutureresearchcanexamineitsrelationshipwithbothmarketliquidityandthemacroeconomicenvironment.

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