【欧洲央行】宏观审慎措施如何影响抵押贷款标准？银行贷款调查的证据-2026

EUROPEANCENTRALBANK

EUROSYSTEM

MarkusBehn,MarcoLoDuca,CristianPerales

WorkingPaperSeries

Howdomacroprudentialmeasuresaffectmortgagelendingstandards?EvidencefromtheECB’sBank

LendingSurvey

No3190

Disclaimer:ThispapershouldnotbereportedasrepresentingtheviewsoftheEuropeanCentralBank(ECB).TheviewsexpressedarethoseoftheauthorsanddonotnecessarilyreflectthoseoftheECB.

ECBWorkingPaperSeriesNo31901

Abstract

UsinginformationfromtheECB’sBankLendingSurvey,weexaminehowtheimplemen-tationofborrower-basedmacroprudentialmeasures(BBMs)between2009-Q1and2023-Q3afectedmortgagelendingstandardsinasampleof15euroareacountries.WefindthatbanksgenerallytightenedcreditstandardsaroundtheimplementationofBBMs,withthestrongestefectoccurringcontemporaneously.SuchtighteningofcreditstandardsisobservedfordiferenttypesofBBMs,includinglimitsonloan-to-valueordebt-service-to-incomeratiosandmaturities.Wealsofindmildevidencethatlegallybindingmeasuresimplyastrongertighteningofcreditstandardsthanmeasuresintheformofnon-bindingrecommendations.Finally,thistighteningismorepronouncedincaseswheremortgageloangrowthorrealestatepricegrowthishigh,consistentwithBBMsefectivelysmoothingthecreditcycle.

Keywords:mortgages,creditstandards,macroprudentialpolicy,borrower-basedmeasures

JELclassification:G21,G28,G51

ECBWorkingPaperSeriesNo31902

Non-technicalsummary

Sincetheglobalfinancialcrisisof2008-09,manyeuroareacountrieshaveimplementedborrower-basedmacroprudentialmeasures,forexampleincludinglimitsonloan-to-value(LTV)ratios,debt-service-to-income(DSTI)ratios,orloanmaturities.Suchmeasuresaimtostrengthenborrowerresilienceandpreventexcessivelyriskylending,particularlyintheresidentialrealestatesector.Theyareoftencalibratedasstructuralbackstops,intendedtobenon-bindingfortheaverageborrowerbutconstrainingthemostriskypartofthemortgagedistribution.

Inthispaper,weexaminehowtheseborrower-basedmeasures(BBMs)haveafectedmortgagelendingstandardsandcreditterms&conditionsintheimplementingcountries.Forthispurpose,wemakeuseoftheEuropeanCentralBank’sBankLendingSurveyandacomprehensivedatasetcontainingdetailedinformationonBBMsin15euroareacountries.OuranalysisdiferentiatesbetweendiferenttypesofBBMs,toassesswhetherthereisheterogeneityacrossmeasures,andfurtherinvestigateswhethertheefectsdependoneconomicandbankingsectorconditions.

Wefindthatthenetpercentageofbanksreportingatighteningincreditstandardsorcreditterms&conditionsissignificantlyhigheraroundBBMimplementation,withthestrongestefectsoccurringcontemporaneously(i.e.,inthequarterofimplementation).ThetighteningefectstendtobemorepronouncedforpolicypackagesinvolvinglimitsonLTVratios,whicharealsothemostcommonintheeuroarea.Inlinewithintuition,wealsofindthatlegallybindingmeasurestendtoexertaslightlystrongerimpactoncreditstandardsandterms&conditionsthanmeasuresthatcomeintheformofrecommendationsfromsupervisoryormacroprudentialauthorities.

Finally,ouranalysisshowsthattighteningofcreditstandardsfollowingBBMimplementationtendstobemorepronouncedincaseswheremortgageorhousepricegrowthwashigh(above75thpercentile).Thediferentialefectsareconsistentwiththemacroprudentialobjectiveofsmooth-ingthecreditcycleandconfirmthatBBMscanhavearelativelystrongimpactonmortgagesupply,astheyimposedirectconstraintsoncertainborrowers.Atthesametime,moremutedefectsunderdepressedmarketconditionssuggestthat(properlycalibrated)BBMimplementa-tioncangoaheadevenundermorechallengingconditions.Areasonforthisisthatotherfactors(suchasmortgagedemandorinterestrates)tendtobemoreimportantthanBBMsinsuchtimes,whileconstrainingoverlyriskylendingremainsavalidpolicyobjectivefromafinancialstabilityperspective.

ECBWorkingPaperSeriesNo31903

1Introduction

Borrower-basedmeasures(BBMs)areanessentialpartofthemacroprudentialpolicytoolkitandamongthemostactivelyusedinstrumentsintheeuroarea.Theyinclude,forexample,limitsonloan-to-valueratios,debt-service-to-incomeratios,orloanmaturities,andareoftenemployedtoaddressrisksintheresidentialrealestatesector.Specifically,sincetheglobalfinancialcrisisof2008-09,manyEuropeancountrieshaveusedthesetoolstostrengthenborrowerresilienceandpreventexcessivelyriskylending.Indoingso,theyoftencalibratedthesemeasuresasstructuralbackstops,intendedtobenon-bindingfortheaverageborrowerbutconstrainingthemostriskypartofthemortgagedistribution(see,e.g.,

Tereanuetal.2022

or

Duranteetal.2025

).

Giventheirwidespreaduseinrecentyears,aclearunderstandingoftheimpactofBBMsonmortgagelendingisofvitalimportanceforpolicymakersandacademicsalike.Consideringtheircommonroleasstructuralbackstops,targetingonlythemostriskyborrowers,whetherandhowstronglyBBMimplementationafectsoverallcreditstandardsaswellascredittermsandconditionsintheimplementingcountriesisaprioriunclear.Atthesametime,itisplausiblethattheimpactdependsonmacro-financialconditionsatthetimeofimplementation,insofarasthemacro-financialenvironmenthasanimpactontheshareofriskymortgages.

1

Inthispaper,weaimtoshedlightontheseissuesbymakinguseoftheEuropeanCentralBank’s(ECB’s)BankLendingSurvey(BLS)andacomprehensivedatasetcontainingdetailedinformationonBBMsin15euroareacountries.WeemploythisdatatoassesswhetherandhowtheimplementationofBBMshasafectedbanklendingstandardsaswellascredittermsandconditions.Indoingso,wediferentiatebetweendiferenttypesofBBMs,toseewhetherthereisheterogeneityacrossmeasures,andinvestigatewhethertheefectsdependoneconomicandbankingsectorconditions.

WefindthatthenetpercentageofbanksreportingatighteningincreditstandardsinthethreequartersaroundBBMimplementationisabout23to25percentagepointshigherthanintheaveragequarter.Thestrongestefectoccurscontemporaneously,i.e.,inthequarterofBBMtighteningitself.Moreover,thenetpercentageofbanksreportingatighteninginoverallcreditterms&andconditionsis11to12percentagepointshigheraroundBBMimplementation,and

1Mortgagelendingstandardstypicallytendtoeaseduringrealestateboomperiods,asevidenced,forexample,bythetimeperiodbeforetheglobalfinancialcrisisof2008-09.Asaresult,theshareofriskyborrowersislikelytobehigherduringsuchtimes,whichmeansthattheimplementationofanidenticalBBMwillbemorebindingduringsuchtimes,inthesensethatitwillexcludealargershareofmortgageapplicantsfromthemarket.

ECBWorkingPaperSeriesNo31904

similarefectsareobservedforindividualsub-componentsofthelatter(i.e.,loan-to-valueratios,loanmaturities,andotherloansizelimits).TheseefectscorrespondtoroughlyonestandarddeviationoftherespectiveBLSvariables,suggestingthattheyaremeaningfulalsofromaneconomicperspective.

2

Thus,accordingtotheBLS,BBMsintheeuroareahadasizableimpactonlendingstandardsatthetimeofimplementationonaverage,despitetheirprominentroleasstructuralbackstopstargetingonlythemostriskypartofthemortgagedistribution.

DiferentiatingbetweendiferenttypesofBBMs,thetighteningefectstendtobestrongestforpolicypackagesinvolvinglimitsonloan-to-valueratios,whicharealsothemostcommonintheeuroarea.Thiscouldeithermeanthatlimitsonloan-to-valueratiosexertagenerallystrongerimpactoncreditstandardsthanlimitsonothermetricssuchasdebt-service-to-incomeratiosorloanmaturities,orthattheytendtobecalibratedmoretightlythanothertypesofmeasures(relativetotheexantedistributionoftheunderlyingratiosintherespectivecountries).Indeed,amonglimitsofloan-to-valueratios,wefindthattheefectstendtobesomewhatstrongerformoretightlycalibratedmeasures.Thereverseistrueforlimitsondebt-service-to-incomeratios,possiblyalsoduetodifficultiesinmeasuringthestringencyofsuchmeasureswithprecision.

3

Inlinewithintuition,wealsofindthatlegallybindingmeasurestendtoexertaslightlystrongerimpactoncreditstandardsandterms&conditionsthanmeasuresthatcomeintheformofrecommendationsfromsupervisoryormacroprudentialauthorities.

Finally,ouranalysisshowsthattighteningofcreditstandardsfollowingBBMimplemen-tationtendstobemorepronouncedincaseswheremortgageorhousepricegrowthwashigh(above75thpercentile).ThediferentialefectsareconsistentwiththemacroprudentialobjectiveofsmoothingthecreditcycleandconfirmthatBBMscanhavearelativelystrongimpactonmortgagesupply,astheyimposedirectconstraintsoncertainborrowers(

Tereanuetal.2022

).Atthesametime,moremutedefectsunderdepressedmarketconditionssuggestthat(prop-erlycalibrated)BBMimplementationcangoaheadevenundermorechallengingmacro-financialconditions.Areasonforthisisthatotherfactors(suchasmortgagedemandorinterestrates)tendtobemoreimportantthanBBMsinsuchtimes,whileconstrainingoverlyriskylending

2Unfortunately,assessingtheoveralleconomicrelevanceoftheefectsiscomplicatedbythedesignoftheBLS,whichrecordsonlywhetherornotaspecificbanktightensitscreditstandards,butnotbyhowmuch.

3Specifically,whilewehaveinformationontheapplicablequantitativelimits,welackgranulartimeseriesinformationonthedistributionoflendingstandardsineachcountry,whichwouldbeneededformeasuringthe“tightness”ofaspecificmeasurewithprecision.Theanalysisisfurthercomplicatedbydiferencesindefinitionsacrosscountries,andawidespreadapplicationofexemptionsfromthequantitativelimits,thecalibrationofwhichvariesacrosscountries(seeAppendixTable

B.1

foranoverviewandSection

2.2

forfurtherdiscussion).

ECBWorkingPaperSeriesNo31905

remainsavalidpolicyobjectivefromafinancialstabilityperspective.

Ourpapercontributestoagrowingliteratureontheefectsofborrower-basedmacropru-dentialpoliciesoncreditandhousingmarketsaswellasoveralleconomicoutcomes(forrecentsurveys,see

GalatiandMoessner2018

,

Biljanovskaetal.

2023

,or

Malovanáetal.2024

).Cross-countrystudiestypicallyrelyonaggregatedataandtendtofindmoderatenegativeefectsofthepoliciesoncreditandhousepricegrowth(

KuttnerandShim2016

,

AkinciandOlmstead-

Rumsey2018

,

Alametal.2019

,

Morganetal.

2019

,

Richteretal.2019

).Thesefindingsareconfirmedbystudieslookingatindividualcountriesinmoredetail(

IganandKang2011

,

Krznar

andMorsink2014

,

Defuscoetal.2019

,

Tzur-Ilan2023

),whichalsofounddistributionalefectsofBBMs(

Peydróetal.

2023

).Wecontributetothisliteraturebyexaminingwhetherandhowbanks’adjusttheircreditstandardsandcredittermsandconditionsinresponsetoBBMs,thussheddinglightonthetransmissionchannelsofpreviouslydocumentedefectsoncreditgrowth.Byrelyingonsurveydataaskingspecificallyaboutadjustmentsinbanks’behaviour,wecomple-mentotherrecentliteratureexaminingthetransmissionchannelswithgranular,loan-leveldata(

Acharyaetal.

2022

,

DirmaandKarmelavičius2023

,

Epureetal.2023

).

4

Besides,wealsoaddtotheliteratureonbanklendingstandards.Deteriorationofmortgagelendingstandardsintheearly2000’shasbeenidentifiedasoneoftherootcausesoftheglobalfinancialcrisisstartingin2008(

MianandSufi2009

,

Keysetal.

2010

,

Dell’Aricciaetal.2012

,

Adelinoetal.2016

).Moregenerally,banks’lendingstandardshavebeenfoundtobeimportantdeterminantsofbroadermacroeconomicoutcomesandfuturefinancialstability(

Dell’Ariccia

andMarquez2006

,

CarlosHatchondoetal.2015

).Giventhedifficultyindirectlyobservinglendingstandardsformortgageloans,severalpapersmakeuseofsurveydata,suchastheFederalReserve’sLoanOfficerOpinionSurvey(

Bassettetal.2014

,

Vojtechetal.

2020

).Weaddtothisliteraturebyprovidingfurtherevidencefromtheeuroarea,makinguseoftheEurosystem’sBLS,andputtingparticularfocusontheroleofBBMsindetermininglendingstandards.

Finally,wealsocontributetoabroaderempiricalliteratureonregulationandmortgagelend-ing.Startingwith

HancockandWilcox

(

1993

,

1994

),severalpapershaveexaminedtheimpactofbankcapital(requirements)onbanks’mortgagelendingbehaviour.Althoughgranulardataonmortgagelendingisscarcerthanforcorporatecredit,severalrecentstudieshaveusedloan-level

4Anotherrecentpaperrelyingonsurveydataistheoneby

FusterandZafar

(

2021

),whichuseshouseholdsurveydatatoexaminethesensitivityofhousingdemandtomortgageratesandavailableleverage.

ECBWorkingPaperSeriesNo31906

datafromindividualjurisdictionstoexaminetheefectsofchangesincapitalrequirementsonmortgagevolumesandriskiness(

Behncke2023

),interestrates(

Basten2019

),ortheoverallcom-positionofcredit(

Aueretal.2022

).Therearealsoanumberofrecentstudiesthathavelookedintotheimpactonmortgagelendingofcapitalreliefmeasuresprovidedduringthepandemic(

Dursun-deNeefetal.2023

,

Mathuretal.2023

),andintotheroleofpolicyuncertainty(

Gissler

etal.2016

,

KaraandYook2023

).Ourfindingsconfirmthatregulatoryfactorsareimportantdeterminantsofmortgagegrowth,e.g.viatheirimpactonlendingstandards.

Theremainderofthispaperisorganisedasfollows.Inthenextsection,wedescribeourdatasetandprovideanoverviewonBBMsimplementedintheBankingUnionsincetheglobalfinancialcrisis.Thereafter,wedescribeourestimationstrategyinSection

3

andpresenttheresultsinSection

4

.Finally,Section

5

concludes.

2Dataanddescriptivestatistics

2.1ECB’sBankLendingSurvey

OurfirstsourceofinformationistheEurosystem’sBankLendingSurvey(BLS).TheBLSisaquarterlysurveythatisconductedamongeuroareabankssince2003.Itprovidesatimelyassessmentofbanklendingconditionsintheeuroarea,thusinformingtheconductoftheECB’smonetarypolicy

(see

Bergetal.2005

or

Köhler-Ulbrichetal.2016

foradescription).

5

Thesurveyisaddressedtoseniorloanofficersatarepresentativesampleofaround150banksfromalleuroareacountries.Itincludesquestionsonthesupplyof,anddemandfor,loanstoenterprisesandhouseholds,andhasbeenfoundtobeasignificantleadingindicatorforeuroareabankcreditandrealGDPgrowth(see,e.g.,

deBondtetal.2010

,

VanderVeerandHoeberichts2016

).Thesurveyisusuallyconductedtowardstheendofaquarterandasksloanofficersaboutchangesinlendingconditionsinthepastthreemonths,andexpectationsforthesubsequentthreemonths.

OurprimaryinterestintheBLSisinthequestionsthatconcernfinancingconditionsformortgageloans(foradetaileddescription,seeAppendix

A

).Followingcommonpracticeforanalysesofthesurveyresponses,wecalculatethenetpercentageofbanksreportingatighteninginoverallcreditstandardsoroverallcredittermsandconditionsformortgageloansinaspecific

5Furtherinformationandthelatestresultsarealsoprovidedonthe

ECB,swebsite

.

ECBWorkingPaperSeriesNo31907

country-year.

6

Inaddition,wealsoobservethenetpercentageofbanksreportingatighteninginthetermsandconditionsforloan-to-valueratios,loanmaturities,andotherloansizelimits.Netpercentagesvarybetween-100percent(referringtoasituationwhereallbanksreportaneasing)and+100percent(referringtoasituationwhereallbanksreportatightening).

DescriptivestatisticsforthesenetpercentagesarereportedinTable

1

,PanelA.Averagevaluesareslightlypositiveforallvariables,inparticularoverallcreditstandardsandloan-to-valueratios.Thisindicatesaslighttendencyforbankstotightenmortgagelendingstandardsduringoursampleperiodfrom2009-Q1to2023-Q3,althoughthestatisticsforallvariablesexhibitconsiderablevariation.Showingtheevolutionofthevariablesovertime,Figure

1

confirmsaslighttighteningbias,butalsoillustratesthatoursampleperiodcomprisesbothperiodswithaneasingandperiodswithatighteningofcreditstandardsandcredittermsandconditions.Finally,PanelAofTable

2

reportscorrelationcoefficientsbetweenthediferentvariables.Notsurprisingly,thecoefficientsarepositiveinallcases,indicatingthatthedirectionoftighteningoreasingtendstobethesameacrossdiferenttypesofloanstandardsandterms&conditions.

2.2Borrower-basedmeasuresintheeuroarea

WecomplementthedatafromtheBLSwithdetailedinformationonborrower-basedmeasures(BBMs)intheeuroarea.Suchmeasuresareusuallyimplementedbyauthoritiestoimproveborrowerresilience,andtherebybankresilience.Specifically,income-basedBBMscanhelptoreducetheprobabilityofdefaultofmortgageloans,whilecollateral-basedBBMscanhelptocontainlossesgivendefault.

7

ThenumberofeuroareacountriesapplyingBBMsalmosttripledinthelasttenyears,illustratingthattheyhavebecomeanessentialpartofthemacroprudentialpolicytoolkit.Manycountriesapplytheminastructuralmanner,i.e.,theykeepthemeasuresinplaceovertheentirecycle,targetingthemostriskypartoftheborrowerdistribution,withlimitedadjustmentstoavoidunwarrantedbindingnesswhennecessary

(see

Duranteetal.2025

for

6Morespecifically,thenetpercentageiscalculatedasthediferencebetweenthesumofthepercentagesofbanksresponding“tightenedconsiderably”and“tightenedsomewhat”andthesumofthepercentagesofbanksresponding“easedsomewhat”and“easedconsiderably”.See,e.g.,

ECB(2024)

forthesametypeofapproach.

7ThefactthatBBMshelptoreducehouseholdriskiswell-establishedintheliterature(see,e.g.,thepapersby

GrossandPoblación2017

or

Giannoulakisetal.2023

andthereferencescitedtherein).

ECBWorkingPaperSeriesNo31908

furtherdiscussion).

8

ThedataissourcedfromECB-internaldatabasesandincludesinformationonallBBMsimplementedsince2009in15euroareacountries.ItcapturesvarioustypesofBBMs,includinglimitsonloan-to-value(LTV),debt-service-to-income(DSTI),anddebt-to-income(DTI)ratiosaswellaslimitsonloanmaturities(seeAppendixTable

B.1

foranoverviewofthemeasures,andFigure

2

fordistributionalcharacteristicsoftheircalibration).

BasedontheBBMdata,weconstructseveralindicatorvariablesthatwethenuseintheregressionanalysistogaugetheimpactofBBMimplementationonbanklendingstandards.Fordefiningthedummyvariables,wefocuseitheronallBBMs,diferentiatebytypeofmeasure(i.e.,LTV,DSTI,DTI,ormaturitylimits),ordiferentiatebytheirlegalstatus(i.e.,legallybindingmeasuresvs.non-bindingrecommendationsfromrelevantauthorities).TheindicatorvariablesaresettooneinthethreequartersaroundBBMimplementation(i.e.,fromthequarteraheaduntilthequarterafterimplementation),andtozerootherwise.Inthismanner,weaccountforpossibleanticipatoryorlaggedefects,sincethemeasuresareusuallyannouncedsometimeinadvanceandmayalsotakesometimetobecomefullyefective.

9

DescriptivestatisticsforthedummyvariablesareprovidedinTable

1

,PanelB.Theindi-catorD(BBM),capturingtheimplementationofanytypeofBBM,isequaltooneforaroung5.1percentoftheobservationsinthesample.Notsurprisingly,thevalueisabitlowerfortheremainingdummies,sincetheyarereferringtosubsetsoftheformer.Moreover,PanelBofTa-ble

2

showsthatthereisconsiderablecorrelationbetweendiferentdummyvariables,inlinewiththeobservationfromAppendixTable

B.1

thatmeasurestendtobeimplementedinpackages.

10

TogetafirstimpressionoftheimpactofBBMs,Figure

3

plotstheevolutionofthenetper-centageofbanksreportingatighteningincreditstandards(left)orcredittermsandconditions(right),aligningtheobservationsaroundthetimeofBBMimplementation.ThefigureclearlyshowsanupwardshiftinthewholedistributionoftherespectivevariablesaroundBBMimple-mentation.Forexample,themedianforthenetpercentageofbanksreportingatighteningincreditstandardsincreasesfromaround10percentinthequarteraheadofBBMimplementation

8Asnotedby

Duranteetal.

(

2025

),besidesitsfinancialstabilitybenefits,structuraluseofBBMscanalsohavesocialbenefits,asitcanhelpto“avoidasituationinwhichtoomanyborrowerssimultaneouslyfacerestrictedaccesstohousingcredit[whenBBMsareimplemented]duringupturns.”AswewillshowinSection

4.4

,theimpactofBBMimplementationindeeddependsonmacro-financialconditionsatthetimeofimplementation,andismoreconstrainingduringrealestateboomperiods,supportingthelineofargumentin

Duranteetal.

(

2025

).

9Notably,allourresultsarerobustwhendefiningthedummeissuchthattheyconsideronlycontemporaneousefects.Forfurtherdiscussionandanalysis,seeSection

4.1

.

10WeformallyexaminetheimplicationsofjointimplementationofmeasuresinSection

4.2

ofthepaper.

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toaround50percentinthequarterofimplementation,whilethemeanincreasesfromaround10percenttoaround40percent.Whileitisdifficulttomakestatementsabouttheeconomicimplicationsoftheseefects,giventhequalitativenatureofthesurveydata,thepatternssuggestameaningfulimpactofBBMsonbanks’lendingbehaviour.Tobeclear,fornowthisanaly-sisispurelydescriptiveanddoesnotcontrolforconfoundingfactorsthatcouldbedrivingtheevolutionoflendingstandards.OurregressionanalysisinSection

4

formallyaddressesthisissue.

Ofcourse,theimpactofBBMsonlendingstandardsislikelytodependonthe“tightness”ofthemeasures,i.e.,thenumberofborrowersafectedbythemeasuresandthedegreetowhichtheyareafected.However,measuringthetightnessofaspecificlimitonlendingstandardsiscomplicatedbyseveralpracticalchallenges.First,thedefinitionoflendingstandardsdiferssubstantiallyacrosscountries,sothatlimitsimposedontherespectivemetricsarenotdirectlycomparable(see,e.g.,

EuropeanCentralBank2022

).Second,alsothedesignofmeasuresdif-fersacrosscountries(see,e.g.,

Duranteetal.2025

),whereinparticularthediverginginterplaybetweenthelevelofthequantitativelimitsandtheuseofexemptionquotas(allowingbankstograntacertainfractionofloanswithlendingstandardsexceedingthelimit)makesitverydiffi-culttodirectlycomparethetightnessofdiferentmeasures.

11

Finally,thetightnessofmeasuresdependsnotonlyonthelevelofthequantitativelimits,butalsoonthecountry-specificdistri-butionoftheunderlyinglendingstandards,whichisagainveryheterogeneousacrosscountriesandnotavailableinacoherentdataset(see,e.g.,

Langetal.

2020

).

Takingnoteofallthesechallenges,andinlinewiththevastmajorityofempiricalstudies(see,e.g.,thecorrespondingdiscussioninthemetaanalysisby

Araujoetal.

2020

),ourbaselineempiricalanalysisreliesondummyvariablesreflectingtheintroductionofBBMs,ratherthancontinuousvariablescapturingalsothestrengthoftheimplementedmeasures.Still,incomple-mentaryanalysiswealsoemployanECB-ESRBinternaldatacollectiononlendingstandardstocalculatetheshareofnewlendingabovetherespectivelimitsimposedbyBBMs,thusobtaining

11Forexample,somecountriescouplerelativelylowquantitativelimitswithrelativelyhighexemptionquotas,whileothersimposerelativelyhighquantitativelimitscoupledwithrelativelylowornoexemptionquotas(seeTable

B.1

).Itisdifficulttosaywhichtypeofmeasureismoreconstrainingforbanksandborrowers.Otherrelevantdiferencesinthedesignofmeasuresrelatetotheuseofeithercurrentorstressedlendingstandardsforthedefinitionofthelimits,ortotheuseofdiferentiatedlimitsfordiferentborrowergroups(e.g.,first-timebuyers).Allthesedesignelementshaveanimpactonthetightnessofameasure.

ECBWorkingPaperSeriesNo3190