CarloAltavilla(ECB)
MiguelBoucinha(ECB)
MarcoPagano(UniversityofNaplesFedericoII)
AndreaPolo(LuissUniversity)
19April2024
“Navigatingthepathtonetzero–theinterplayofclimate,monetaryand financialpolicies”
ECB–OECDWorkshop
Theopinionsinthispresentationarethoseoftheauthorsanddonotnecessarily reflecttheviewsoftheEuropeanCentralBankandtheEurosystem
1 Dobankspricefirms’climateriskoverandabovecreditrisk,when grantingloans?E.g.,becausebanks’IRMsdonotfullyaccountforclimate riskorbankshavereputationalconcerns
inassessingclimaterisk,dotheytakeintoaccountfirms’ plans toreduce emissions(inadditiontocurrentemissions)?
dobanks committed toenvironmentalprotectionchargeahigherlending premiumonclimaterisk?
2 Doesmonetarypolicyaffectbanks’pricingofclimateriskand,ifso, how? Twoalternativeviews,withoppositepredictions:
financialfrictionschannel:aslow-emissionfirmshavefewertangibleassets, hencelesscollateral,monetarytighteningdiscouragesmorelendingtothem
→ promptsbanksto raiserates moretofirms lessexposedtoclimaterisk
risk-takingchannel:monetarytighteningdiscouragesbanks’risk-taking
→ promptsbanksto raiserates moretofirms moreexposedtoclimaterisk
1 Dobankspricefirms’climateriskoverandabovecreditrisk,when grantingloans?YES
bankschargehigherinterestratestofirmswithgreatercarbonemissions, controllingforfirms’probabilityofdefault theyalsochargelowerratestofirmsthatcommittoloweremissions botheffectsarelargerforbankscommittedtodecarbonization
2 Doesmonetarypolicyaffectbanks’pricingofclimaterisk? YES
consistentlywitha“climaterisk-takingchannelofmonetarypolicy”,tighter policyinducesbankstoincreasebothcreditriskpremiaandcarbonemission premia → morepenalizingformorepollutingfirms
comparativestatement:restrictivemonetarypolicyincreasesthecostofcredit toallfirms,butitscontractionaryeffectismilderfor(i)firmswithlow emissionsthanforthosewithhighemissionsand(ii)forthosethatcommitto decarbonizationthanforthosethatdon’t
3 Results
4 Conclusions
Evidencethat securitymarkets priceclimate(esp.transition)risk:
stockmarket:BoltonandKacperczyk(2021,2022),Hsu,LiandTsu(2023)
optionmarkets:Ilhan,SautnerandVilkov(2020)
bondmarkets:HuynandXia(2021),Bakeretal(2021)
For creditmarkets theevidence(limitedtosyndicatedloans)isambiguous:
NO:Beyen,DeGreiff,DelisandOngena(2021)
YES,afterthe2015ParisAgreement:EhlersandDeGreiff(2021)
Also,noconsensusonwhether bankscommittedtoenvironmental policies lendpreferentiallytolow-emissionfirms:
NO:EhlersandDeGreiff(2021)andGiannetti,Jasova,Loumiotiand Mendicino(2023)
YES:Degryse,Goncharenki,TheuniszandVadasz(2020)andKacperczykand Peydr`o(2021)
Noevidenceonthe impactofMP impactofMPonthepricingofclimate risk
Literatureonfinancialfrictionschannelofmonetarypolicy
BernankeandGertler’s(1989,1995)ideathatmonetarypolicyhasdifferent effectonfirmsdependingontheircollateralcapacity:
inthepresenceofincentiveproblems,banksprovidelesscredittofirmswith lowerratiooftangibleassetstofuturecashflow
restrictivemonetarypolicyworsensproblem:banksrestrictcreditrelatively moretocollateral-poorfirmsthantocollateral-richones
Iovino,MartinandSauvagnat(2021):firmswithlowcarbonemissionshavea lowerfractionoftangibleassets,hencecanofferlesscollateral
Combiningthisfactwiththeroleoffinancialfrictionsinmonetarypolicy: monetaryexpansion → looserlendingstandards,esp.forlow-emissionfirms monetaryrestriction → tighterlendingstandards,esp.forlow-emissionfirms
Prediction: monetarypolicytighteningmorerestrictiveforGREEN firmsthanforbrownones
Ideaisthatmonetarypolicyaffectsbanks’yield-seekingincentives: monetaryexpansion → looserlendingstandards,esp.forriskierfirms monetarytightening → tighterlendingstandards,esp.forriskierfirms
Duetointeractionbetweenmonetarypolicyandbanks’informationalissues:
AcharyaandNaqvi(2012):toelicitloanofficers’effort,theirpayistiedto loanvolume → abundantliquidityinducesmorerisktaking
Dell’Ariccia,LaevenandMarquez(2014):costlymonitoringofloanportfolio → dropinrisk-freerateinducesbankstocutmonitoring → takemorerisk
Dell’Ariccia,LaevenandSuarez(2017):U.S.bankslowertheirinternalrisk ratingofnewloanswhenshort-terminterestratesrise
Jim´enez,Ongena,Peydr`oandSaurina(2014):asovernightratesdrop,less capitalizedSpanishbanksrelaxlendingstandardstoriskyfirms
AndersonandCesa-Bianchi(2023):amonetarytighteningtriggersalargerrise increditspreadsforhigh-leveragefirms,mainlyduetoahigherriskpremium
Prediction: monetarypolicytighteningmorerestrictiveforBROWN firmsthanforgreenones
4 Conclusions
Wedrawmonthlyloan-leveldatafromSeptember2018toDecember2022 fromtheAnaCreditdatabase,coveringalleuro-areacountries Foreachcreditinstrument,wehavedatafor:
theinterestratechargedbytheissuingbank
itsestimateoftheprobabilityofdefault(PD)
Forlistedfirms,wemergethesedatawithRefinitivdatafor
firm-levelcurrentcarbon(CO2andCO2equivalent)Scope1andScope2 emissiondata(inthousandtonnespermillionUSDofnetrevenues)
thefirm’scommitmenttoreducefutureemissions,namely,adummy indicatingifthefirmhasdisclosedanemissionreductiontarget Firmcommitmentisassociatedwithcarbonemissionsreductionaccordingto Carboneetal.(2022)andBoltonandKacperczyk(2023).Theyalsofind greatersign-upinEuropebyhighemittersthaninNorthAmericaandAsia
Wecomplementthesedatawith:
informationaboutbanks’environmentalcommitment,byidentifying signatoriesofacommitmentletterinthecontextoftheScienceBasedTargets initiative(SBTi),whichpromotesnet-zeroclimatetargets(following KacperczykandPeydr`o,2021)
amonthlytimeseriesofhigh-frequencymonetarypolicysurprisesfromthe EuroAreaMonetaryPolicyEvent-StudyDatabase(EA-MPD)developedby Altavillaetal.(2019)
interestratechangesina30-minutewindowaroundECBpressconferences, expressedonamonthlybasis asinGurkaynak,SackandSwanson(2005),Jaroc`ınskiandKaradi(2020)and AndersonandCesa-Bianchi(2023)
VariablesObservationsMeanSt.Dev.p5p10p25p50p75p90p95
(b.p.)453,2311.095.56-1.53-1.20-0.530.000.064.2114.14
4 Conclusions
(1)(2)(3)(4)(5)(6)(7)
PDf ,t 0.024***0.017***0.017***0.026***0.026***0.005***0.005*** (0.0005)(0.0006)(0.0006)(0.0008)(0.0008)(0.0006)(0.0006)
Carbonf ,t 0.071***0.020***0.043***0.019***0.090***0.033**0.086*** (0.0026)(0.0061)(0.0088)(0.0066)(0.0118)(0.0169)(0.0201)
Targetf ,t -0.103***-0.067***-0.068***-0.067***-0.078***-0.034***-0.034*** (0.0024)(0.0025)(0.0026)(0.0028)(0.0032)(0.0034)(0.0034)
Carbonf ,t × -0.032***-0.103***-0.045***
Targetf ,t (0.008)(0.0139)(0.0086)
FixedEffects:
BankYesYesYesYesYesYesYes
Economicsignificance,basedonColumn1:
4bppremium(5%ofSD)forfirmswithhighemissions(90th percentile)
10bpdiscount(13%ofSD)forfirmscommittedtoreduceemissions
3bppremium(4%ofSD)onfirmswithhighPD(90th percentile)
Concern:whatifPDalreadyincorporatesclimateriskconsiderations?
Theoretically:
Differenthorizons
NoincentivestoincorporateclimateriskinPD
Maybedifficulttoincorporateininternalmodels
Empirically
Zerocorrelationofthetwovariables
Robustnesstest:wefindsameresultsonclimateriskvariablesifweremove PDandaddlistoffirmobservables
Bankcommitment&climateriskpricing:panelestimates (1)(2)(3)(4)(5)
PDf ,t 0.0248***0.0176***0.0270***0.00512*** (0.000566)(0.000627)(0.000794)(0.000660)
Carbonf ,t 0.0414***0.0313***0.0815***0.0823*** (0.00730)(0.00907)(0.0121)(0.0200)
Targetf ,t -0.0913***-0.0591***-0.0750***-0.0238*** (0.00267)(0.00267)(0.00331)(0.00340)
Commitb,t 0.241***0.207***0.01750.213***0.0133 (0.0247)(0.0235)(0.0223)(0.0234)(0.0210)
Carbonf ,t × Targetf ,t 0.0328***-0.0229***-0.0999***-0.0394*** (0.00767)(0.00796)(0.0139)(0.00852)
Commitb,t × PDf ,t -0.00669***-0.00744***-0.00772***0.0004380.00500*** (0.00174)(0.00151)(0.00152)(0.00149)(0.00144)
Commitb,t × Carbonf ,t 0.0336***0.0339***0.0310***0.001580.00907 (0.0115)(0.0115)(0.00936)(0.0124)(0.0100)
Commitb,t × Targetf ,t -0.166***-0.157***-0.0572***-0.163***-0.0431*** (0.0194)(0.0203)(0.0154)(0.0205)(0.0146)
BankFixedEffectsYesYesYesYesYes
TimeFixedEffectsYesYes-Yes-
ILSFixedEffects-Yes---
ILS × TimeEffects--Yes--
FirmFixedEffects---Yes-
Firm × TimeEffects----Yes
Observations306871306788305401306864303466
R-squared0.4690.5510.6030.6180.694
Economicsignificance,basedonColumn2:committedbankscharge
16bp(21%ofSD)lessthanuncommittedbanksinlendingtofirmswithtarget
2bp(3%ofSD)moretofirmswithhighemissions(90
percentile)
PDf ,t 0.00777***0.0242***0.0168***0.0261***0.00540*** (0.000724)(0.000546)(0.000593)(0.000769)(0.000643)
Carbonf ,t 0.0506***0.0425***0.0893***0.0856*** (0.00758)(0.00885)(0.0118)(0.0201)
Targetf ,t -0.103***-0.0688***-0.0780***-0.0349*** (0.00252)(0.00260)(0.00323)(0.00340)
Carbonf ,t × Targetf ,t -0.0260***-0.0308***-0.102***-0.0443*** (0.00788)(0.00806)(0.0139)(0.00862)
MPt 0.0150***
(0.000876)
MPt × PD f ,t 0.000263**0.000399***0.000348***0.000340**0.000274*** (0.000118)(0.000110)(0.000105)(0.000154)(0.0000914)
MPt × Carbonf ,t 0.00111*0.00107*0.00233*0.000990* (0.000673)(0.000587)(0.00138)(0.000585)
MPt × Targetf ,t -0.00329***-0.00205***-0.000509-0.00162*** (0.000575)(0.000554)(0.000686)(0.000528)
BankFixedEffectsYesYesYesYesYes
TimeFixedEffects-YesYes-Yes
ILSFixedEffects--Yes-ILS × TimeFixedEffects---Yes-
FirmFixedEffectsYes---Yes
Observations321331306871306788305401306864 R-squared0.3660.4680.5500.6030.617
Note:themonetarypolicyshockisdefinedasanunexpected increase inthe policyrate(asproxiedbytheOIS),i.e.,atightening
Column1:a25bpsurpriseincreaseinthepolicyrateresultsina35bp increaseinbanks’creditspreads
Subsequentcolumns:baselineimpactabsorbedbytimeeffects,butwecan stillestimatethedifferentialimpactonpremiaacrossfirms
Column3(withbank,timeandILSeffects):a25bpsurpriseincreaseinthe policyrateresultsin
1.4additionalriseinpremiaforhighemitters(90th percentile)
5bpsmallerriseinpremiaforfirmscommittedtoloweremissions
Butmonetarypolicyactswith“longandvariablelags”...
Creditsupply:banksmaytaketimetoadjusttheirlendingpoliciesto changesinmonetarypolicy
Creditdemand:firmsmaytaketimetoadjusttheirinvestment,hiringand productiondecisions–hencetheirdemandforloans–tochangesinthecost ofcredit
Uselocalprojectionestimatestocapturethesedynamiceffects: yb,f ,t+h = λ1hMPt + λ2hMPt × Carbonf ,t + λ3hMPt × Targetf ,t + θb + ϵf ,b,t+h , wheretheoutcomevariable yb,f ,t+h iseitherthelendingspreadorthe (logarithmofthe)loangivenbybank b tofirm f betweenmonth t and month t + h; MPt isthemonetarypolicyshock; θb arebankfixedeffects.
Localprojectioncoefficientestimatesatmonth0,3,9and12 Monetarytighteninghasinitiallysmallbutgraduallyincreasingeffecton premia,slightlygreaterforhigh-emissionfirms,lesssoforcommittedones:
1st figure:25bpsurprisetightening → 39bpriseinpremiaafter12months
2nd figure:additional2bpforhighemitters(90th percentile)
3rd figure:5bpmitigationeffectforcommittedfirms,9bpafter12months
Localprojectionestimatesaremirrorimagesofthoseinpreviousslide Monetarytighteninggraduallyreduceslending,moresoforhigh-emission firms,lesssoforcommittedones:
1st figure:25bpsurprisetightening → negligibleimpacteffect,gradualdrop inlendingby2.5%after12months
2nd figure:additional2.7%dropforhighemittersafter12months
3rd figure:1.5%mitigationeffectforcommittedfirmsafter12months
Similarresultsifweadoptadiff-in-diffstrategyaroundtwoepisodes
December2021:endofnetpurchasesunderPEPPandreductionofAPPnet purchases
July2022:firstratehike
July2023BLSaskedbanksifinthepreviousyeartheychangedtheirlending policiesdifferentlyfor“brown”firms,“green”firmsandfirms“intransition”
Note:previousyearhadseenalargeandpersistentmonetarytightening
3 Results
4 Conclusions
Euroarea bankspriceclimaterisk:theycharge higherratestofirmswith largeremissions,and lowerratestofirmsthatcommittogreen transition
Banks’ commitmentmatters:Committedbanks provide cheaperloansto firmsthatcommit todecarbonizationand penalize more pollutingfirms
Climaterisk-takingchannelofmonetarypolicy: contractionarymonetary policy shocksleadto
higherpremiaandlowervolumes tohighemissionfirms
mitigating effectsfor firmscommitted todecarbonization
Bottomline:
restrictivemonetarypolicyincreasesthecostofcredittoallfirms... ...butitscontractionaryeffectismilderforfirmswithlowemissionsandthose committedtoreducingthem