framework Assessing macroprudential in OECD countries tools within acointegration Journal of Financial Stability

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Journal of Financial Stability

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Assessing macroprudential tools in OECD countries within a cointegration framework

OriolCarreras^a,E.PhilipDavis^a,b,∗,RebeccaPiggott^a

aNIESR,2DeanTrenchStreet,SmithSquare,London,SW1P3HE,UK

bDepartmentofEconomicsandFinance,BrunelUniversity,KingstonLane,Uxbridge,Middlesex,UB83PH,UK

a r t i c l e i n f o

Articlehistory:

Received26October2017

Receivedinrevisedform3April2018 Accepted5April2018

Availableonline7April2018 JELclassification:

E58 G28 Keywords:

Macroprudentialpolicy Houseprices Creditexpansion Panelestimation Robustness

a b s t r a c t

WhereasmacroprudentialpolicyhascometotheforesincetheGlobalFinancialCrisis,withmanyreg- ulatorsbeinggivenresponsibilityforsuchpolicy,theappropriatetoolsandtheeffectivenessofsuch toolsremainopenquestions.Wesuggestthatexistingworkoneffectivenessofmacroprudentialpolicy maybevulnerabletobiasduetoomissionoflongruncointegrationeffects.Thispaperseekstooffera freshbaselineforworkinthisareabyadoptingacointegrationframeworkwhichisrobusttoavariety ofalternativetechniquesandcomparesfavourablywithnon-cointegratedalternatives.Weassessthe impactoftypicalmacroprudentialpolicyinterventionsonhousepriceandhouseholdcreditgrowthin upto19OECDcountries,usingthreedatasetsfromtheIMFandBIS,thusgivingbothawiderrangeof controlvariablesandbroadercoverageofinstrumentsthaninmostextantwork.Wefindevidencethat macroprudentialpolicesremaineffectiveinbothshort-andlong-runatcurbinghousepriceandhouse- holdcreditgrowthevenwithinacointegrationframework,albeitsometoolsaremoreeffectivethan others.Theseinclude,inparticular,taxesonfinancialinstitutions,generalcapitalrequirements,strict loan-to-valueratiosanddebt-to-incomeratiolimits.

©2018TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/).

1. Introduction

Macroprudentialpolicyisfocusedonthefinancialsystemasa whole,withaviewtolimitingmacroeconomiccostsfromfinan- cialdistress(Crockett,2000),andriskistakenasendogenousto thebehaviourofthefinancialsystem.¹Whereassuchpolicieshave beenwidelyadoptedsince theGlobalFinancial Crisis,as noted byGalatiandMoessner(2014),“analysisisstillneededaboutthe appropriatemacroprudentialtools,theirtransmissionmechanism andtheireffect”.Theoreticalmodelsareintheirinfancyandempir- icalevidenceontheeffectsofmacroprudentialtoolsisstillscarce.

Norhasaprimaryinstrumentformacroprudentialpolicyemerged.

Meanwhile,anexaminationoftheempiricalliteratureshowsthat thecorrectmodellingofhousepricesandcreditatamacrolevel iscrucial,andexistingworkoneffectivenessofmacroprudential policymaybevulnerabletobiasduetoomissionoflongruncoin- tegrationeffects.

∗ Correspondingauthorat:DepartmentofEconomicsandFinance,BrunelUni- versity,KingstonLane,Uxbridge,Middlesex,UB83PH,UK.

E-mailaddresses:oriolcarreras1@gmail.com(O.Carreras), ephilipdavis@msn.com,philip.davis@brunel.ac.uk,pdavis@niesr.ac.uk (E.P.Davis),r.piggott@niesr.ac.uk(R.Piggott).

1 Recentoverviewsofmacroprudentialpolicyandinstrumentsareprovidedinter aliainBennanietal.(2014),Claessensetal.(2013)andDeNicolòetal.(2012).

Inthiscontext,ouraimistoadvancetheempiricalevidence onmacroprudentialtoolsfocusedonhousepricesandcreditby adoptingarigorouscointegrationframework,whichalsoallows estimationofmedium-andlongtermaswellasshorttermeffects oftypicalpolicyinterventions,thusaidingpolicymakersineval- uatingthetools’ effectiveness.Our focus onOECD countriesas opposedtoglobaloremergingmarketsamplesgivesusaccessto awiderrangeofcontrolvariablesthantheexistingliterature;we alsoincludeacrisisdummywhereappropriate.Alloftheseaspects shouldreduceomittedvariablesbiasandenhancetheaccuracyof ourresultsrelativetotheexistingliteraturethattendstoomitcoin- tegrationandemployaverysimplesetofcontrols.Furthermore,as arguedbyCeruttietal.(2017),OECDcountriesmaydiffermarkedly intermsoffinancialstructureandregulationfromEmergingMar- ketEconomiesandDevelopingCountries,makingglobalpooling asinmuchoftheexistingliteraturepotentiallyproblematic.²We alsoundertakearangeofrobustnesscheckswithacointegration

2Theycomment“emergingmarketshavereliedmoreonmacro-prudentialpoli- ciesthanadvancedeconomieshavedone.Second,advancedeconomiestendtohave moredevelopedfinancialsystemswhichoffervariousalternativesourcesoffinance andscopeforavoidance,makingitpossiblyharderformacroprudentialpoliciesto beeffective.Combinedthismeansthatemergingmarketsanddevelopingcoun- trieshavebeenabletousemacroprudentialpoliciesmoreeffectively.”Ceruttietal.

(2017)p.212.

https://doi.org/10.1016/j.jfs.2018.04.004

1572-3089/©2018TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).

approach,whichunderpinthemainresults,andthathavenot,to ourknowledge,beenundertakeninthisliteraturetodate.Andwe comparecointegratedtonon-cointegratedestimatesofthesame datasettoassessthedegreetowhichomittedvariablesmaybias results.

The paper is structured as follows: In Section 2 we survey keyrecentcontributionstotheempiricalliteratureontheeffec- tivenessofmacroprudentialpolicy.Thisthenformsbackground to ourown modelling exercisewhich begins in Section 3. We outlinethe advantages of our cointegra-basedapproach before estimating panel error correction models for house prices and householdsectorcredit.Wethenintroducethreeextantdatabases ofmacroprudentialtoolsbeforetestingtheadditionalimpactof macroprudentialpoliciesusingeachdatabaseinturn.Weprovide a“ready-reckoner”fortheestimatedeffectofpolicyoverdifferent times horizons which is relevant for regulators. Section 4 fea- turesrobustnesscheckswithinacointegrationframework;firsta Vector-Error-Correction(VECM)approach,secondusinglagsofthe macroprudentialtools,thirdwithfully-modifiedOLS(FMOLS)and laggeddynamicstobetterallowforendogeneityofregressors;and finallyweadoptaseeminglyunrelatedregression(SUR)procedure toaddressapotentialconcernofweakcointegrationunderpinning thepanelerrorcorrectionregressionsforhouseprices.³ InSec- tion5wecontrastourresultswithnon-cointegratedapproaches, includingcomparison ofourbaseline witha frameworktypical oftheexistingliteratureforglobaloremergingmarketsamples, whichincludemainlyeconomicgrowth,policyratesandvolatil- ityasindependentvariables andnolongruneffects,aswellas comparingtheVECMwithasimpleVARwhichomitscointegra- tion.Section6concludeswithasummaryofresultsandanumber ofsuggestionsforuseoftheestimatesbyregulators(forexample incalibratingmacroeconomicmodels)aswellassuggestionsfor furtherempiricalworkbyresearchersandpolicymakers.

2. Empiricalresearchpapersonmacroprudentialpolicy AsnotedinthereviewbyGalatiandMoessner(2014),empiri- calanalysisofmacroprudentialpolicyisdifficultbecauseoflackof establishedmodelsofrealandfinancialinteractions,lackofdata andtheneedforcareindistinguishingcorrelationandcausation.

Thisisamatterofconcernforpolicymakerswhoneedtoknow theimpactofpolicy.Anumberofapproachestoempiricalwork canbedistinguished(forarecent summary,seeCarrerasetal., 2016).Oneapproach is theevent studyas for example,Crowe etal.(2011)assesstheeffectsofpolicieslikeLTVsonrealestate marketvolatility.Asecondapproachisassessmentofauthorities oroutsideobserversoneffectivenessofmacroprudentialinstru- mentsasinBorioandShim(2007).Third,macrostresstestscanbe usedtoassessresponsesofthefinancialsystemtolargeshocks,see Drehmann(2009).Fourth,counterfactualanalysisseekstoassess whatwouldhavehappenedifmacroprudentialpolicieshadbeen appliedtopastevents(seeforexampleAntipaetal.,2010).

Afifthapproach,onwhichwefocus,isofreducedformregres- sions,generallyusingpaneldata.AppendixTableA1providesa summaryofrecentworkinthisarea.Here,theweaknessesarethat suchregressionsmaynotcapturewelltheinteractionofpolicy,real andfinancialsectors;thereislittleexperienceofmacroprudential policytoassesstheeffectandtransmissionmechanism;andthere isadifficultyinisolatingeffectsfromthoseofmonetarypolicy.

MostexistingstudiesusedynamicpanelGMMestimation.They alsogenerallyestimateovergroupsofemergingmarketeconomies

3Whilesuchacountry-by-countryapproachasSURtacklessuccessfullythecon- cernofweakcointegration,ithaslimitedscopeforeconometricinferenceasthe binarynatureofthedatasetsusedinthispaperbecomesamoretaxingfeature.

orglobalsampleswitha singledataset.Studiestypicallydonot allowforcointegration,andoftenarepurelyindifferencessodonot allowforalongruneffectofmacroprudentialpolicy.Theyalsooften usequiteasimplerangeofcontrolvariables,suchasGDPgrowth andshortrates.Threestudiesweconsiderofparticularinterest, andhencenoteinmoredetail,areasfollows:

KuttnerandShim(2016)assesstheeffectivenessofninenon- interestratepolicytools,includingmacro-prudentialmeasures,in stabilisinghousingmarketpricesandrelatedlendinginaglobal sampleof57countriesquarterlyover1980–2012,usingtheBIS databaseshowninAppendixTableA4anddescribedbelow.They usepanelregressionsforgrowthratesofhousingcreditandhouse prices,withcontrolsforlaggedgrowthofthedependentvariable, theleveloftheshortrate,thegrowthinrealGDPpercapitaand thecredit/GDPgap,aswellascountryfixedeffects.Thefinding thatcredit, houseprices andGDPpercapitaarenon-stationary whiletheirdifferencesarestationaryisconsideredtojustifythis formulationingrowthrates(andtheleveloftheinterestrateand thegapwhicharelevels-stationary)ratherthanallowingalsofor cointegrationbetweenthenon-stationaryvariables. Thereis no bankingcrisisdummy.Themacroprudentialtoolsaremeasured, asnoted inmore detail below,atpointsof tightening (+1)and easing(-1) over4 lags.Housing creditgrowthis slowedsignif- icantlybyadjustmentsinthemaximumdebt-service-to-income (DSTI)andhousing-relatedtaxes.Furthermore,onlyachangein housing-related taxes significantly affects house priceinflation.

Generalcreditpolicies(reserverequirements,liquidityandcredit growthlimits)werenotfoundtohaveasignificanteffectonhouse pricesorcreditgrowth.

AkinciandOlmstead-Rumsey(2015)constructaquarterlyindex ofdomesticmacroprudentialpoliciesin57advancedandemerging (EME)economiescovering2000–2013,partlyrelyingontheIMF surveyusedinCeruttietal.(2017)ascitedbelow.Effectiveness ofpoliciesincurbinggrowthinbankcredit andhousepricesis assessedusingadynamicpaneldatamodel,wherecontrolvariables besideslaggedgrowthratesofcreditandhousepricesincludereal GDPgrowth,thechangeinnominalmonetarypolicyratesandthe VIX,ameasureoftheimpliedvolatilityofS&P500indexoptions.

Therearenolevelsofnon-stationaryvariablesandaccordinglyno allowanceforpossiblecointegration.Thereisalsonobankingcrisis dummy.Findingsofthepaperarethatusageofmacroprudential policyhasbecomemoreactivesincetheglobalfinancialcrisis,in bothadvancedcountriesandEMEs;themaintargetisthehousing market,andtheyareoftenrelatedtobankreserverequirements, capitalcontrolsandmonetarypolicy.Macroprudentialtightening isassociatedwithlowerbankcreditgrowth,housingcreditgrowth, andhousepriceinflationandtargetedpoliciesaremoreeffective.

InEMEs,capitalinflowrestrictionstargetingthebankingsectorare alsoassociatedwithlowercreditgrowth,althoughportfolioflow restrictionsarenot.Withoutthemeasures,creditandassetprice growthwouldhavebeenmuchhigher.

Ceruttietal.(2017)usethefirstIMFdatabase(seeAppendix TableA2and thedescriptionbelow)ofannualmacroprudential measuresinaglobalsample⁴of119countries,withapanelGMM regressionformacroprudentialindicators.Independentvariables forcreditgrowthandhousepricegrowthincludeGDPgrowth,the policyratelevel,a dummyfor bankingcrisesandcountryfixed effectsaswellasthemacroprudentialvariables.Therearenolev- elsofnon-stationaryvariablesandallowanceforcointegration.An indexsummingalltypesofpolicyiscorrelatedwithlowercredit growth,especiallyinEMEs.Borrower-basedpolicieslikeLTVand DTIlimits,aswellasfinancial-institutionbasedpolicieslikelimits

4Theirsamplecovers31advancedcountries,64emergingmarketeconomiesand 24developingcountries.

onleverageand dynamicprovisioningareshowntobeparticu- larlyeffectiveinreducinggrowthinrealcreditandhouseprices.

Policiesworkbestintheupturnbut arelesseffectivein abust period.Macroprudentialpolicyisweakerinmoreopenandfinan- ciallydeepereconomies,suggestingthereisevasioncrossborder orinshadowbanking.Countrieswithmorecrossborderborrowing usemacroprudentialpoliciesmore.

AppendixTableA1summarisestheseandotherkeyrecentstud- ies.Whateverthecontext,itisclearthatthecorrectmodellingof housepricesandcreditatamacroleveliscrucialandislikelyto receiveincreasingattentionintheongoingwakeofthesub-prime crisisandrecentpolicydevelopments;itistothisissuethatwe turninthenextsection.

3. Modellingmacroprudentialpolicieswithina cointegrationframework

3.1. Specificationandestimationforhousepricesandhousehold credit

Ourstarting point is thatmany ofthereduced-form studies citedaboveandinAppendixTableA1haveadoptedarathersimple dynamicstructure⁵(generallygrowthratesofnon-stationaryvari- ablesandlevelsofstationaryones)whichmaybevulnerabletobias.

Sincevariablesemployedgenerallyshowatrend(theyarenon- stationary),itwouldbeappropriatetotestforcointegrationand includeitintheequationwherecointegrationisaccepted.Indeed, ifthereiscointegrationanditisomittedfromtheequation,weare losinginformationoverthelongrunperiod(Banerjeeetal.,1993).

Accordingly,amorecomplexdynamicstructurewithallowancefor cointegrationshouldimprovetheaccuracyoftheestimatesofthe macroprudentialtools.

Morespecifically,theGrangerrepresentationtheorem(Engle andGranger1987)statesthatifthelevelsarecointegratedthen thedatagenerationprocesscanberepresentedasanerrorcorrec- tionmodel(ECM).TheECMincludeslaggedlevelstermsaswellas differences.Incontrast,aregressionindifferences,asistypicalof theexistingliterature,omitsthelaggedlevelsterms.Omissionof cointegrationconstrainstheestimatedcoefficientsonthelagged levelstobezero(entailingbiasiftheyaresignificant)andunder mostcircumstanceswillalsoforcetheestimatedcoefficientson thedifferencedregressorsawayfromthevaluestheywouldtakeif themodelwerecorrectlyspecifiedasanECM(alsoentailingbias).

Thisinturnmayaffectthesizeandsignificanceofthedummyvari- ablesformacroprudentialpolicy,owingtotheomittedlongrun economiceffects.Weshowresultsconsistentwiththisargument inSection5below,wherewecompareaVECMwithaVAR(which omitscointegration),aswellascomparingourbaselineresultswith thesimplermodelstypicaloftheliteraturethatomitthepossibility ofcointegration.

Anadditionalbenefitofcointegrationisthatitallowsbothshort andlongruneffectsofmacroprudentialpolicytobediscerned,that isoftennotfeasiblewiththeexistingliterature.Furthermore,most existingstudieshavesoughttocoverglobaloremergingmarket samples,butatacostofhavingaratherlimitedsetofcontrolvari- ablesformacroprudentialtoolssuchasGDPgrowth,inflationand shortterminterestrates.WearefocusinghereonOECDcountries, notablyinEurope,andaccordinglycanuseabetterandmorepre- cisesetofcontrolssuchasrealpersonaldisposableincome(RPDI), therateof unemployment,the realstockof housingand gross householdfinancialwealth,thatshouldreducebias.Thisisinaddi- tiontoavoidingpotentialbiasesarisingfromglobalpoolingcitedin

5 AnexceptionisVandenbusscheetal.(2015)whoestimatedanerrorcorrection equationforhousepricesinagroupofEasternEuropeancountries.

theintroduction.Moreover,acrisisdummy,whichisonlyincluded inasubsetofexistingwork,ensuresthatcrisiseffectsarenotfalsely attributedtothemacroprudentialtools.

Ourchosentargetvariables,inlinewithmuchoftheliterature, arerealhousepricesandrealhouseholdsectorcredit.Themacro- prudentialinstrumentdatasetsusedarethefirstandsecondIMF datasetandtheBISdatasetasoutlinedbelow,thusofferingexten- sivescopeforcomparisonascomparedtoexistingstudiesfocused ononedataset.Accordingly,wecontendthatourresultsareof considerablerelevancetopolicymakers.

Typicalestimatesfordeterminationofhousepricesinadvanced countriesareindeedinerrorcorrectionformat.Thereisfirstacoin- tegratinglevelsequationwhichformsaninverteddemandfunction forhousingbutalsoincludesasupplyeffectsuchasthestockof housingwhich determinesthelong-runpriceofhousing(Meen (2002),Barrelletal.(2004, 2011),Adamsand Füss(2012),Igan andLoungini(2012),MuellbauerandMurphy(2008),Capozzaetal.

(2002)).Thisfirststageequationconstitutestherelationshipthat drivesthelong-runpropertiesofthedependentvariableandcan bewrittenforacountrycasthefollowingregressionequation:

Y^c=X^cˇ^c+ε^c (1)

WhereYisaTx1vectorcontainingthedependentvariableinlog levels,Tdenotesthetimeperiod,cisacountryindex,XisaTxN matrixofNregressorsinloglevelsincludingaconstant,␤isanNx1 vectorofcoefficientsand␧istheresidualterm.

Thisfirststageequationisincorporatedintoanexpandedequa- tionthat recognisesthat actualhouse pricesdeviate fromtheir fundamentalvaluesintheshort-runandtypicallyincludesaset ofcontrolsinfirstdifferencestoallowforthesedynamics,where theerrorcorrectiontermshowsthespeedofadjustmenttolong runequilibrium.Fortheerrorcorrectionequationtobemeaningful therehastobeacointegratingrelationshipbetweenthelong-run variables(thefirststageregressionstep)andtheelementscaptur- ingtheshort-termdynamicsmustbestationary.Thissetupallows theexaminationoffactorsthatdrivehousepricedynamics.The secondstagecanbewrittenas:

Y^c=˛^c+^c

Y^c−X^cˇ^c

(T−1)+^cZ^c+∈^c (2)

Where␣denotesaconstant,␭istheerrorcorrectioncoefficient, Zisasetofregressorsaimedatcapturingshort-termdynamics ofthedependentvariablewithcoefficientvector␥and isthe residualterm.Thetwostagesmaybecombined,asinourwork shownbelow,inasinglestageerrorcorrectionestimation.Asimilar approachisadoptedforhouseholdcredit.

Followingthisliterature,ourmodellingstartedfromthepanel error-correctionapproach ofDavis et al. (2011),alsoemployed inArmstrongandDavis(2014)usingestimatedgeneralisedleast squares(EGLS).Asisnormalforpanelestimation,thecoefficients in (1) and (2) are constrained to be identical for each coun- try, (althoughwevary thiswithcountry-specificcoefficients in theseemingly-unrelatedregressioninSection4).Weestimatean extendedhousepriceequationincludingrealhouseprices(LRPH), realpersonaldisposableincome(LRPDI)and thelong termreal interestrate(LRR)(proxyingtheusercostaswellasimpactedby monetarypolicy)⁶andalsotherateofunemployment(U),realgross householdfinancialwealth(LRGW)(asaportfoliobalanceeffect), realhousingcapitalstock(LRKH)(lagonly),realhouseholdcredit (LRLIABS)(lagonly)anddummiesforfinancialcrises.Weestimated

6Wenotethattheusercostisalsoaffectedbytaxdeductibilityinsomecoun- triesaswellasrecurrentpropertytaxes,andmortgagesarevariablerateinsome countries,butwecontendthatthereallongrateisanadequateproxy.