美联储金融账户报告-中央银行关于气候变化的沟通英

FinanceandEconomicsDiscussionSeries

FederalReserveBoard,Washington,D.C.

ISSN1936-2854(Print)

ISSN2767-3898(Online)

CentralBankCommunicationaboutClimateChange

DavidM.Arseneau,AlejandroDrexler,MitsuhiroOsada

2022-031

Pleasecitethispaperas:

Arseneau,DavidM.,AlejandroDrexler,andMitsuhiroOsada(2022).“Central

BankCommunicationaboutClimateChange,”FinanceandEconomicsDiscussionSe-

ries2022-031.Washington:BoardofGovernorsoftheFederalReserveSystem,

/10.17016/FEDS.2022.031

.

NOTE:StaffworkingpapersintheFinanceandEconomicsDiscussionSeries(FEDS)arepreliminary

materialscirculatedtostimulatediscussionandcriticalcomment.Theanalysisandconclusionssetforth

arethoseoftheauthorsanddonotindicateconcurrencebyothermembersoftheresearchstafforthe

BoardofGovernors.ReferencesinpublicationstotheFinanceandEconomicsDiscussionSeries(otherthan

acknowledgement)shouldbeclearedwiththeauthor(s)toprotectthetentativecharacterofthesepapers.

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CentralBankCommunication

aboutClimateChange*

DavidM.ArseneauFederalReserveBoard

AlejandroDrexlerFederalReserveBank

ofChicago

MitsuhiroOsada

BankofJapan

FederalReserveBoard

April15,2022

Abstract

Thispaperappliesnaturallanguageprocessingtoalargecorpusofcentralbankspeechestoiden-tifythoserelatedtoclimatechange.Weanalyzethesespeechestobetterunderstandhowcentralbankscommunicateaboutclimatechange.Byallaccounts,communicationaboutclimatechangehasacceler-atedsharplyinrecentyears.Thebreadthoftopicscoverediswide,rangingfromtheimpactofclimatechangeontheeconomytofinancialinnovation,sustainablefinance,monetarypolicy,andthecentralbankmandate.Financialstabilityconcernsaretouchedupon,butmacroprudentialpolicyisrarelymen-tioned.Directcentralbankactionlargelyrevolvesaroundidentifyingandmonitoringpotentialriskstothefinancialsystem.Finally,wefindthatcentralbankstendtousespeculativelanguagemorefrequentlywhentalkingaboutclimatechangerelativetoothertopics.

Keywords:Financialstability;Transparency;Centralbankmandate;Greenfinance;Naturallanguageprocessing;Centralbankspeeches

JELClassifications:E58;E61;Q54

*WethankAdeleMorris,RichardRosen,RicardoCorrea,andKojiNakamuraforvaluablecommentsandsuggestions.TheviewsexpressedinthispaperarethoseoftheauthorsanddonotnecessarilyrepresentthoseoftheFederalReserveBoardofGovernorsoranyoneintheFederalReserveSystem,nordotheyrepresenttheviewsoftheBankofJapan.

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1Introduction

Climatechangeisanimportantpriorityforcentralbanksaroundtheworld.Asevidence,membershipintheNetworkforGreeningtheFinancialSystem(NGFS)hasincreasedfromeightcentralbanksandsupervisorsatitsinceptioninlate-2017tooveronehundredasofearly-2022.InordertojointheNGFS,membersarerequiredtopubliclyacknowledgethatclimate-relatedrisksareapotentialsourceoffinancialinstability.

Assuch,thenumberofcentralbanksthathaveacknowledgedthatclimate-relatedrisksfallwithintheirsupervisoryandfinancialstabilitymandateshasexplodedduringashortfiveyearperiod.

Atthesametime,climatechangeisacomplextopicthatisoutsidethetraditionalareasofexpertiseforcentralbanks.Theinteractionbetweenclimateandeconomicactivityisnotwellunderstoodandoccursoveralongertimehorizonthancentralbankstypicallyconsider.Littleisknownaboutpropagationofclimate-relatedrisksthroughthefinancialsystem.Morefundamentally,therearesignificantdatagapswhichposechallengesforriskmanagementformicro-andmacroprudentialsupervisorsalikeinadditiontofinancialmarketparticipantsmoregenerally.Takentogether,thesecomplicationsputcentralbanksinadi伍cultposition.Howcantheyestablishcredibilityforbeingresponsivetoclimatechangewhenrelativelylittleisknownabouthowitinteractswiththerealandfinancialeconomy?

Oneapproachistobuildcredibilitythroughcommunication.Centralbankcommunicationisincreas-inglyimportantinachievingmonetarypolicyobjectives.

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Moreover,recentresearchhasshownthathowcentralbanksapproachcommunicationmattersgreatly,notonlyforachievingdesiredpolicyobjectivesbutalsoformanagingpublicperceptionabouttheinstitutionitself.Forexample,HaldaneandMcMahon(2018)andKryvtsovandPetersen(2021)showthatcommunicationismoreefectivewhencentralbanksusesim-ple,relatablelanguage.Bholat,etal.(2019)showsthatsimple,relatablecommunicationhelpstobuildpublictrustandimprovespeople’sperceptionofthecentralbank.Thisresearchsuggeststhathowcentralbanksapproachtalkingaboutclimatechangeiscruciallyimportantastheylearnmoreaboutitsefectsonfinancialmarketsandthebroadereconomy.Atthispoint,however,weknowverylittleabouthowcentralbanksapproachcommunicationaboutclimatechange.Thispapertakesafirststeptowardfillingthisgapintheliterature.Weapplynaturallanguageprocessingtechniquestoacorpusofover17,000centralbankspeechestoidentifythesubsetthatareclimate-related.Usingtheseclimate-relatedspeeches,weanalyzenotonlywhatcentralbankactuallytalkaboutwhentheytalkaboutclimatechange,butalsohowtheytalkaboutthetopic.Wepayparticularattentiontomacroprudentialtoolsinthecontextofthefinancialstabilityimplicationsofclimatechange,butanumberofothertopicsarecoveredaswell.Ouranalysiscanhelppro-motemoreefectivecommunicationaboutrisksassociatedwithclimatechangeandiscriticalforclarifyingtheroleofcentralbanksinaddressingtheissue.

Therearethreemainconclusions.First,byallaccountscentralbankcommunicationaboutclimatechangehasexpandedsharplyinrecentyears.Thisistrueattheextensivemargin(thenumberofspeechesfocusingonclimatechange)aswellastheintensivemargin(theextenttowhichclimate-relatedtopicsarecoveredwithinagivenspeech).Thesharpgrowthinclimate-relatedcommunicationappliestocentralbanks

1See,forexample,Blinder,etal.(2008)foranearlysurveyoftheliterature.Morerecently,anumberofpapershavestudiedtheefectofcentralbankcommunicationonmonetarypolicytransmission,includingGuthrieandWright(2000),Gürkaynak,etal.

(2005),NakamuraandSteinson(2018).

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inadvancedandemergingmarketeconomiesalike,pointingtotheglobalnatureoftheproblem.

Second,thebreadthofclimate-relatedtopicsaddressedbycentralbanksiswide,rangingfromtheim-pactofclimatechangeontheeconomytofinancialinnovation,sustainablefinance,monetarypolicy,andthecentralbankmandateamongothertopics.Financialstabilityconcernsaretouchedupon,butthespeechesrarelydiscussmacroprudentialpolicy.Atthispoint,publiccommunicationregardingdirectcentralbankac-tiontoaddressclimate-relatedfinancialstabilityriskscentersonidentifyingandmonitoringpotentialrisksnotonlyfrommacroprudentialperspectivebutalsoformicroprudentialsupervision.Climatescenarioanal-ysisorstresstestingisonesuchtooldiscussedinthiscontext,butcentralbanksalsotouchonotheractionsincludingsettingsupervisoryexpectationsonfinancialinstitutions’climateriskmanagementandenforcingmandatorydisclosureofexposuretoclimate-relatedrisks.Ahandfulofcentralbanksdiscussactionsre-latedtotheirowncarbonfootprint—eitherthecompositionofthebalancesheetorthroughresponsibilitiesassociatedwithmanagementofdomesticpensionfunds—–butnotinthecontextofmacroprudentialpolicy.

Finally,athirdconclusionrelatestothenatureofthelanguageusedbycentralbankstocommunicateaboutclimate.Wepresentstatisticalevidenceindicatingthatcentralbankstendtouse“speculativelan-guage”,orlanguagethatindicatesuncertainty,morefrequentlyinclimate-relatedspeechesrelativetootherspeeches.Giventhecomplexityofthetopicandthefactthatclimatechangeisnotanareaoftraditionalexpertiseforcentralbanks,somedegreeofambiguityaboutthetopicinpubliccommunicationseemsappro-priate.Nevertheless,previousstudiesofcentralbankcommunicationhaveshownthatclarityoflanguageinfluencesthecredibilityofthemessage.

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Goingforward,ascentralbanksdeepentheirknowledgeaboutclimate-relatedrisks,thelanguageusedinpubliccommunicationshouldevolvewiththegoalofprovid-ingsharpercommunicationwithmorepreciselanguage.Developingclimate-relatedcommunicationinthisdirectioncanhelpestablishcredibilitythatcentralbanksarebeingresponsivetoclimatechange.

Thispapercontributestoagrowingliteraturethatconsiderstherolethatcentralbanksinrespondingtoclimatechange.McKibbin,etal.(2021)arguesthatclimatechangeconsiderationsshouldbeincorporatedintomonetarypolicydecisions.Campiglio,etal.(2018)makesthecasethatthefinancialstabilityimplica-tionsofclimatechangeandthetransitiontoalow-carboneconomywarrantconsiderationinsettingfinancialregulationandcentralbankpolicies,moregenerally.Chenet,etal.(2021)goesonestepfurther.BuildingonWeitzman(2009),theseauthorsarguethattheseverityoffutureshocksduetoclimatechangearesopoten-tiallydevastatingthatstrongexantemacroprudentialpolicywhichprecludesinvestmentincarbon-intensiveassetsiswarranted.Incontrast,Hansen(2022)contendsthatinordertomaintaincredibility,centralbanksneedtobeclearabouttheirambitionsandexecutionandcanbestdosobyadheringnarrowlytotheirman-datedroles.

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Theauthormakesthecasethatbecausemostefectiveclimatepolicytoolsareinthefiscal,ratherthenthemonetary,toolkit.Assuch,ifcentralbankspursuepoliciestocombatclimatechangetheyriskunderminingtheirowncredibility.Finally,Bolton,etal.(2020)arguesthatcentralbanksneedtoworkproactivelywithotherpolicymakersandinstitutionstobetterunderstandandaddresstheincreasinguncer-

2InadditiontoHaldaneandMcMahon(2018),KryvtsovandPetersen(2021)andBholat,etal.(2019)discussedabove,seealsoMontesandNicolay(2017).

3DikauandVolz(2021)highlightsignificantdiferencesinhowclimateobjectivesdoanddonotfitwithincentralbanksmandatesacrossdiferentcountries.Forsomecountriesactivelyengaginginclimate-relatedpoliciesiswellwithinthemandatewhileforothersthecaseisnotsoclear.

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tainlyassociatedwithclimatechangetoensurelongrunfinancialandpricestability.Thispapercontributestothisliteraturebyfocusingonhowcentralbankscommunicateaboutclimatechangeregardlessofwhetherornottheyareactivelyconsideringpoliciestoaddressit.InkeepingwiththeconclusionsofbothHansen(2022)andBolton,etal.(2020),havingabetterunderstandingofhowcentralbanksapproachcommunica-tionaboutclimatewillhelptoimprovethequalityofthatcommunicationand,indoingso,makescentralbanksengagementmorecredibleandtransparent.

Thispaperalsorelatestoabodyofliterature,surveyedinBholat,etal.(2015),thatusesnaturallanguageprocessingtounderstandcentralbankcommunication.Anumberofstudiesfocusonextractinginformationfromspeeches,publications,orpolicystatementstoseeifthereareimplicationsforfinancialmarketactivity.Forexample,Born,etal.(2014)andCorrea,etal.(2021)bothanalyzehowinformationconveyedthroughFinancialStabilityReportsafectsfinancialmarkets.ShapiroandWilson(2021)usesentimentanalysistoestimatecentralbankpreferencesusingFOMCstatements.Kawamura,etal.(2019)findthatambiguityincentralbankcommunicationisrelatedtofinancialmarketvolatility.Thispaperdifersfromthesecontribu-tionsinthatwestudyaspecifictopic(climatechange)andtheuseoflanguageincommunicationfocusednarrowlyonthattopic.Withinthetextanalysisliterature,ourpaperisanapplicationoftopicdetectiontech-niques.Thereareahandfulofstudiesthatalsoapplytopicmodelingtocentralbankcommunication,buttopicmodelingisusedinthesepaperseitherfordimensionreduction(Hansen,etal.,2018,Hansen,etal.,2019,andHansson,2021)orforidentifyingthemainormostfrequenttopicsaddressedincommunication(forexample,MoschellaandPinto,2018,Armelius,etal.,2020,andBenchimol,etal,2021).Wecontributetothisliteraturebydevelopingamethodologytoidentifycentralbankscommunicationsaboutanarrowlydefinedtopic.Althoughweareparticularlyinterestedinclimatechange,themethodologydevelopedherecouldbeappliedtomorebroadly.

Theremainderofthispaperisorganizedasfollows.Thenextsectionofersdetailsonthefullsetofspeechesusedinouranalysis.InSection

3

wedescribeanovelmethodologyforidentifyingclimate-relatedspeeches.Section

4

analyzestheseclimate-relatedspeecheswithparticularattentionontheroleofmacroprudentialpolicyinaddressingclimate-relatedfinancialstabilityrisks.Section

5

analyzessomequalitativeaspectsofcentralbankcommunicationaboutclimatechange.Finally,Section

6

concludes

2CentralBankSpeechDataset

OurstartingpointisthesetofallcentralbankspeechesavailablefromtheBankofInternationalSettlements(BIS)overthetwenty-fiveyearperiodfromJanuary1997toDecember2021.

4

Table

1

presentssomesummarystatistics.Since1997,atotalof17,405speechesweredeliveredbyrepresentativesfrom108diferentcentralbanks.Roughly70percentweregivenbycentralbanksinad-vancedeconomieswithanaverageofabout17speechesperadvancedeconomycentralbankinanygivenyear.

5

Thatsaid,thereisconsiderabledispersioninfrequency.Forexample,largercentralbankssuchas

4TheBIScollectstranscriptsofspeechesinEnglishthatareavailablefromcentralbanks’websites.Forsomecentralbanks,thedatabaseonlycoversasubsetofthetotalnumberofspeechesavailableontheirwebsitesduetoselectedreportingfromtheirmediao伍ces.Thedatabaseisupdatedonadailybasisandisavailableat

/cbspeeches/

.

5OursplitbetweenadvancedandemergingmarketeconomiesisinformedbyIMFclassificationfortheirWorldEconomic

5

theEuropeanCentralBank(ECB)andtheFederalReserveSystem(Fed)tendtobemoreactive,giving

anaverageofcloseto90speechesperyear,whereassmalleradvancedeconomycentralbankssuchastheNationalBankofSlovakia,theBankofSlovenia,andtheCentralBankofCypruscommunicatelessfre-quently.

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Alltold,thefivemostactivecentralbanks—theECB(2,337speechestotal),theFed(2,073),the

DeutscheBundesbank(753),theBankofJapan(711),andtheBankofEngland(708)—accountforoverhalfthespeechesgivenbyadvancedeconomycentralbanksinourdataset.

Centralbanksinemergingmarketeconomiesaccounttheremaining30percentofallspeeches,withtheaverageemergingmarketeconomycentralbankgivingabout8peryear.ThemostactivearetheReserveBankofIndia(837speechestotal),theCentralBankofMalaysia(485),theCentralBankofthePhilippines(484),theSouthAfricanReserveBank(382),theBankofAlbania(281),andtheBankofThailand(219).Together,thesesixcentralbanksaccountforhalfofallspeechesgivenbyemergingmarketcentralbanks.

Table1:Summarystatistics,Allspeeches

Avg.#of

#of

#of

Avg.#ofSpeeches

Words

CentralBanks

Speeches

AnnuallyperBank

perSpeech

AdvancedEconomy37

12,016

16.8

1,037

EmergingMarketEconomy71

5,389

7.8

817

Total108

17,405

12.4

969

Source:Author’scalculations.

Communicationisskewedtowardadvancedeconomycentralbanksnotonlyinthenumberofspeeches(withovertwiceasmanyspeechesperbankannually),butalsointhelengthofthespeech.ThelastcolumnofTable1showsthatadvancedeconomycentralbankspeechesaverageabout1,000wordswhilespeechesbyemergingmarketcentralbanksaverage20%fewerwordsatjustunder800.

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Since2005,Figure

1

showsthenumberofadvancedeconomycentralbanksthathavegivenatleastonespeechinagivenyearaveragesabout30(redlineinthetopleftpanel).Foremergingmarkets(greenline)thenumberisslightlylowerdespitethefactthattherearenearlytwiceasmanyemergingmarketcentralbanks(71asopposedto37intheadvancedeconomies).Thetoprightpanelshowsthetotalnumberofspeechesforagivenyear.Foremergingmarketsthisnumberhasstayedroughlyconstantsince2005,butithassteadilyincreasedintheadvancedeconomies.Thisincreasereflectsaneardoublingoftheaveragenumberofspeechesperadvancedeconomycentralbankfromabout10toover20peryear(bottomleft

Outlook(see

/external/pubs/ft/weo/2021/01/weodata/groups.htm

).AcompletelistofcentralbankswithatleastonespeechinthedatasetisgiveninAppendixA.

6Smallercentralbanks(advancedandemergingmarketeconomiesalike)maybelesslikelytoreportspeechestotheBIS(translatingthespeechtoEnglishmaybecostly,smallcentralbanksmayhavefewerrepresentativesavailabletogivespeechesormaysimplychoosetomakefewerspeechesmadeavailableontheirwebsites,etc).Accordingly,somecross-bankcomparisonsneedtobeinterpretedwithcaution.

7Thenumberofwordsarecountedaftertherawtextispre-processed.Wefollowstandardpracticeinthetextanalysislit-eraturebydroppingextremelycommonwords(so-calledstopwords)andcreatingnoun-phrasesbyPart-of-Speech(POS)taggingtechniques.SeeAppendixB.1fordetails.

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panel)andisinkeepingwithaongoingtrendtowardgreatercentralbanktransparency.Finally,thelowerrightpanelshowsspeechlengthhasstayedroughlyconstantatabout1,000wordsforadvancedeconomycentralbanks,whilespeechesgivenbycentralbanksinemergingmarketeconomieshavegottenshorterovertime.

Figure1:Centralbankspeechesovertime,1997-2021

Source:Author’scalculations.

3IdentifyingClimate-relatedSpeeches

Usingthiscorpusofspeeches,weidentifythosethatare“climate-related”.A“climate-relatedspeech”isaspeechgivenbyarepresentativeofacentralbankthatdiscussestheimpactofclimatechangeontheeconomyand/orthefinancialsystem.Ideally,wewouldidentifythesespeechesusingof-the-shelftoolsfromthetextanalysisliteraturethatfocuson“classification”or“topicidentification”but,forreasonsdiscussedinthenextsubsection,thisisnotpractical.So,wedevelopourownmethodology.

3.1ExistingApproachesfor“TopicIdentification"

Therearethreeapproachescommonlyusedinthetextanalysisliteraturetoclassifytextonatopicalbasis.

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Thefirstistousewhatisknownasanunsupervisedtopicmodel.Thisapproachismostusefulwhenthetopicscontainedinthecorpusarelargelyunknowntotheresearcher.Inthiscase,unsupervisedtopicmodelsareefectiveatreducingalargequantityoftextdowntoamoremanageablesetofcategoriesina

8GrimmerandStewart(2013)andGentzkow,KellyandTaddy(2019)providesurveysofthisliterature.

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processknownasdimensionreduction.OneofthemostwidelyusedtopicmodelsistheLatentDirichlet

Allocation(LDA),introducedbyBlei,Ng,andJordan(2003).Owingtoitssimplestructure,LDAcanbeeasilyappliedasadimensionreductiontoolandhasbeenusedwithincreasingfrequencyintheeconomicsliterature.

9

However,LDA(andunsupervisedtopicmodels,moregenerally)doesnoteasilylenditselftoourtaskbecausetheobjectivehereistoidentifytextrelatedtoaveryspecific,andrelativelynew,topic.Unsupervisedmethodsofernoguaranteethatclimatechangewillbeoneofthetopicalcategoriesidentifiedthroughthedimensionreduction.Infact,giventhatclimatechangeisatopicthatcentralbankshaveonlyrecentlystartedtoaddress,itisunlikelythatunsupervisedmethodswouldbeefectiveatbeingabletoidentifyclimate-relatedspeeches.

10

Analternativeapproachistousesupervisedmachineleaningtechniquessuchastextregression,includ-inglinearandnon-lineartechniques,ortheNaiveBayesClassifier.

11

Incontrastwithunsupervisedtopicmodels,thisapproachisappropriatewhentheresearcherknowsthetopicsofinterestaheadoftimeandhasasmallsampleoftextsthataremeaningfullyrelatedtothetopicsofinterestreadilyavailable.

12

Inthiscase,thesampletextscanbeusedtotraincomputationalmodelstoe伍cientlyidentifytheseknowntopicsinthelargercorpus.Forourpurposes,whilewedoknowthetopicofinterestaheadoftime(climatechange),wedonothaveaninitialsetofspeechesthathavealreadybeenidentifiedasdefinitively“climate-related”toserveasatrainingset.

Thethirdapproachisknownasadictionaryapproachwhichinvolvesusingapre-establisheddictionary,orasetofkeywordsspecifiedbytheresearcher,toclassifytextsintoknowncategories.Thedictionaryapproachismostappropriatewhenthereisastrongandreliablepriorbeliefthatacertaintopicispresentinthetextbutinformationtoidentifythetopicislimited.Examplesincludecasesinwhichthetopicofinterestdoesnotmatchwiththefactorstructureofunsupervisedmethodsorwhenthereisnotrainingdataavailabletofitasupervisedmodel.Inprinciple,ourinterestinidentifyingclimate-relatedspeechesfitsneatlyintotheseexamples,sothedictionaryapproachseemspromising.

However,thechallengewefaceisthatitisnotclearwhatkeywordsarebesttousetoconstructthedictionarynecessarytoidentifyclimate-relatedspeeches.Existingstudiesineconomicsandfinancethatusethedictionaryapproachdonotfacethisproblem.Forexample,studiesontheimpactofsentimentoneconomicandfinancialoutcomesbenefitfrompre-determineddictionariesthatarewidelyavailabletoclassifytextbasedonsentiment.

13

Somestudiesthatbranchoutsideofsentimentanalysisdocreatecus-tomdictionaries.Awell-knownexampleistheEconomicPolicyUncertaintyIndexconstructedbyBaker,Bloom,andDavis(2016).

14

AnotherexampleisCorrea,etal.(2021),whichcreatesadictionarytailored

9ExamplesincludeArmelius,etal.(2020),Benchimol,etal.(2021),HansenandMcMahon(2016),Hansen,etal.(2018),andHansenetal.(2019),andLarsen,etal.(2021).

10ThereareavarietyofextensionsthatrelaxthestrongassumptionsofLDA,suchasthedynamictopicmodel(BleiandLaferty,2006),thecorrelatedtopicmodel(BleiandLaferty,2005),orthestructuraltopicmodel(Roberts,etal.,2013).Whilethesemethodsmayhelpwithourspecificapplication,theyallarestilllimitedbythefactthattheyareunsupervised.Unsupervisedmethodsofernoguaranteethatoneoftheidentifiedtopicswillbeclimate-related.Someformofsupervisionseemsnecessarytoachievethisobjective.

11LineartextregressionmethodsincludepenalizedlinearmodelssuchasLasso,Ridge,andElasticNetregressions.Non-linearmethodsincludegeneralizedlinearmodels(GLM),supportvectormachine(SVM),regressionstrees,anddeeplearning.

12GentzkowandShapiro(2010)andGentzkow,Shapiro,andTaddy(2019)areexamplesofpapersthatusethisapproach.

13See,Tetlock(2007),LoughranandMcDonald(2011),Bollen,etal.(2011),andWisniewskiandLambe(2013)amongothers.

14Thisindexisconstructedbycountingnewsarticlesthatcontainthefollowingtriple:“economic”or“economy”;“uncertain”

8

toafinancialstabilitycontext.AsnotedinGentzkow,Kelly,andTaddy(2019),creatingadictionaryfromscratchtypicallyinvolvesselectingkeywordsonanadhocbasis.Inthecaseofclimatechange,usinganadhocapproachcouldleadtomis-identification,somanualvalidationisrequiredtoensurethekeywordsactuallydeliverthetypesofspeechesinwhichweareinterested.Thisisprohibitivelytimeconsuminggiventhesizeofourcorpus.

3.2OurMethodology

Oursolutionistocomeupwithourownmethodologytoidentifyclimate-relatedspeechesusinganauto-matedapproachfortopicdetectionthroughkeywords.

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AdetaileddescriptionisprovidedinAppendixB,butthegeneralstrategyisasfollows.Startingwithasingleseedword,“climatechange”,weusethemethodofLaver,etal.(2003)andWatanabe(2018)tocreateascoreforallwords(afterpre-processing)inthecorpus.Thewordscoreisconstructedbycomparingthefrequencywitheachindividualwordshowsupinspeechesthatdoincludetheseedwordrelativetothefrequencywithwhichthewordshowsupinspeechesthatdonotincludetheseedword.Oncewehaveascoreforeverywordinthecorpusweusethesewordscorestoconstructameasureofthepropensityofagivenspeech(whichisjustacollectionofallthediferentwordsthatwescore)tobe“climate-related”bytakingaweightedaverageofwordfrequencyusingthewordscoresasweights.

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Wethenselectaminimumcutofofzeroandusethatasaninitialcriteriaforidentifyingwhatwecallanunrefinedsetofclimate-relatedspeeches.AsshowninPanelAofTable

2

,thisinitialstageidentifies2,337speechesthathaveaspeechscoregreaterthanzerothatarepotentially“climate-related”.

Inpractice,manyofthe