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2023

APR

Eye of the Storm: The

Impact of Climate

Shocks on Inflation

and Growth

Serhan Cevik and João Tovar Jalles

WP/23/87

IMF Working Paper

European Department

Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth

Prepared by Serhan Cevik and João Tovar Jalles1

Authorized for distribution by Bernardin Akitoby

April 2023

IMF Working Papers describe research in progress by the author(s) and are published to elicit comments

and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do

not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Abstract

What is the impact of climate change on inflation and growth dynamics? This is not a simple

question to answer as climate shocks tend to be ubiquitous, but with opposing effects

simultaneously on demand and supply. The extent of which climate-related shocks affect inflation

and economic growth also depends on long-run scarring in the economy and the country’s fiscal

and institutional capacity to support recovery. In this paper, we use the local projection method to

empirically investigate how climate shocks, as measured by climate-induced natural disasters,

influence inflation and economic growth in a large panel of countries over the period 1970–2020.

The results shows that both inflation and real GDP growth respond significantly but also differently

in terms of direction and magnitude to different types of disasters caused by climate change. We

split the full sample of countries into income groups—advanced economies and developing

countries—and find a striking contrast in the impact of climate shocks on inflation and growth

according to income level, state of the economy, and fiscal space when the shock hits.

JEL Classification Numbers:

E31; E32; E62; N10

Keywords:

Climate change; natural disasters; inflation; growth; local

projections; panel data

Author’s E-Mail Address:

scevik@imf.org; joaojalles@gmail.com

1 The authors would like to thank Helge Berger, Romain Duval, Gianluigi Ferrucci, Zeina Hasna, Florence

Jaumotte, Emanuele Massetti, Christine Richmond, Axel Schimmelpfennig, Glebs Starovoits, Alice Tianbo

Zhang, and the participants of a seminar at the European Department of the International Monetary Fund (IMF)

for helpful comments and suggestions.

I. INTRODUCTION

Climate change is a multifaceted and evolving phenomenon and a major source of uncertainty

for the global economy and financial markets.

The global surface temperature has already

jumped more than 1.1 degrees Celsius (°C) compared with the preindustrial average, escalating

the frequency and severity of weather-related natural disasters. Projections show that

accelerating climate change will elevate the risk of droughts, extreme temperatures, and severe

storms and cause greater damage to the environment, lives, and livelihoods, as the global mean

temperature increases by as much as 4°C over the next century (Stern 2007; IPCC 2007, 2014,

2019; 2021). Every country will experience the consequences of climate change, but the extent of

vulnerability depends on the size and composition of economies, the resilience of institutions

and physical infrastructure, and the capacity for mitigation and adaption to climate change.

What is the impact of climate change on inflation and growth dynamics? This is not a simple

question to answer as climate shocks tend to be ubiquitous, but with opposing effects

simultaneously on demand and supply. The magnitude and pattern of the impact on inflation

and growth also depends on long-run scarring in the economy and the country’s fiscal and

institutional capacity to support recovery. In this paper, we use the local projection (LP) method

proposed by Jordà (2005) to investigate how climate shocks—measured by a binary variable for

the occurrence of a climate-induced natural disaster or the number of deaths caused by such an

event per population in a given year—influence alternative measures of inflation and economic

growth in a large panel of 173 countries during the period 1970–2020. We also explore the

possibility of nonlinear effects of large-scale climate shocks on inflation and real GDP growth by

looking at two dimensions: (i) the position of a given economy in the business cycle and (ii) the

level of public debt as a proxy of fiscal space when a weather-related disaster occurs.

Using data on 173 countries over the period from 1970 to 2020, the empirical analysis shows that

inflation and growth respond significantly to disasters caused by climate change, but the impact

varies in terms of direction and magnitude. While extreme temperatures result in lower inflation,

droughts and storms lead to higher levels of inflation. We also develop a more granular analysis

by focusing on alternative measures of inflation and identify that the impact of weather-related

shocks on core and food inflation shows significant variation in magnitude and pattern across

country groups. With regards to economic growth, we find that the initial response is negative to

all types of climate shocks, but the magnitude and pattern of response show variation over the

long run. When we split the sample of countries by income group, we observe a striking contrast

in the impact of climate shocks on inflation and growth in advanced and developing countries.

Finally, we find that the impact of climate disasters on inflation and growth varies in a nonlinear

fashion depending on the state of the economy and the level of fiscal space when the shock hits.

These results suggest that climate-induced natural disaster have differential and opposing effects

on inflation and growth through multiple channels, such as (i) increasing or lowering agricultural

production and food prices (ii) dampening economic activity and lowering labor productivity, (iii)

Climate refers to a distribution of weather outcomes for a given location, and climate change describes

environmental shifts in the distribution of weather outcomes toward extremes.

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2023APREyeoftheStorm:TheImpactofClimateShocksonInflationandGrowthSerhanCevikandJoãoTovarJallesWP/23/87©2023InternationalMonetaryFundWP/23/87IMFWorkingPaperEuropeanDepartmentEyeoftheStorm:TheImpactofClimateShocksonInflationandGrowthPreparedbySerhanCevikandJoãoTovarJalles1AuthorizedfordistributionbyBernardinAkitobyApril2023IMFWorkingPapersdescriberesearchinprogressbytheauthor(s)andarepublishedtoelicitcommentsandtoencouragedebate.TheviewsexpressedinIMFWorkingPapersarethoseoftheauthor(s)anddonotnecessarilyrepresenttheviewsoftheIMF,itsExecutiveBoard,orIMFmanagement.AbstractWhatistheimpactofclimatechangeoninflationandgrowthdynamics?Thisisnotasimplequestiontoanswerasclimateshockstendtobeubiquitous,butwithopposingeffectssimultaneouslyondemandandsupply.Theextentofwhichclimate-relatedshocksaffectinflationandeconomicgrowthalsodependsonlong-runscarringintheeconomyandthecountry’sfiscalandinstitutionalcapacitytosupportrecovery.Inthispaper,weusethelocalprojectionmethodtoempiricallyinvestigatehowclimateshocks,asmeasuredbyclimate-inducednaturaldisasters,influenceinflationandeconomicgrowthinalargepanelofcountriesovertheperiod1970–2020.TheresultsshowsthatbothinflationandrealGDPgrowthrespondsignificantlybutalsodifferentlyintermsofdirectionandmagnitudetodifferenttypesofdisasterscausedbyclimatechange.Wesplitthefullsampleofcountriesintoincomegroups—advancedeconomiesanddevelopingcountries—andfindastrikingcontrastintheimpactofclimateshocksoninflationandgrowthaccordingtoincomelevel,stateoftheeconomy,andfiscalspacewhentheshockhits.JELClassificationNumbers:E31;E32;E62;N10Keywords:Climatechange;naturaldisasters;inflation;growth;localprojections;paneldataAuthor’sE-MailAddress:scevik@imf.org;joaojalles@gmail.com1TheauthorswouldliketothankHelgeBerger,RomainDuval,GianluigiFerrucci,ZeinaHasna,FlorenceJaumotte,EmanueleMassetti,ChristineRichmond,AxelSchimmelpfennig,GlebsStarovoits,AliceTianboZhang,andtheparticipantsofaseminarattheEuropeanDepartmentoftheInternationalMonetaryFund(IMF)forhelpfulcommentsandsuggestions.I.INTRODUCTIONClimatechangeisamultifacetedandevolvingphenomenonandamajorsourceofuncertaintyfortheglobaleconomyandfinancialmarkets.2Theglobalsurfacetemperaturehasalreadyjumpedmorethan1.1degreesCelsius(°C)comparedwiththepreindustrialaverage,escalatingthefrequencyandseverityofweather-relatednaturaldisasters.Projectionsshowthatacceleratingclimatechangewillelevatetheriskofdroughts,extremetemperatures,andseverestormsandcausegreaterdamagetotheenvironment,lives,andlivelihoods,astheglobalmeantemperatureincreasesbyasmuchas4°Coverthenextcentury(Stern2007;IPCC2007,2014,2019;2021).Everycountrywillexperiencetheconsequencesofclimatechange,buttheextentofvulnerabilitydependsonthesizeandcompositionofeconomies,theresilienceofinstitutionsandphysicalinfrastructure,andthecapacityformitigationandadaptiontoclimatechange.Whatistheimpactofclimatechangeoninflationandgrowthdynamics?Thisisnotasimplequestiontoanswerasclimateshockstendtobeubiquitous,butwithopposingeffectssimultaneouslyondemandandsupply.Themagnitudeandpatternoftheimpactoninflationandgrowthalsodependsonlong-runscarringintheeconomyandthecountry’sfiscalandinstitutionalcapacitytosupportrecovery.Inthispaper,weusethelocalprojection(LP)methodproposedbyJordà(2005)toinvestigatehowclimateshocks—measuredbyabinaryvariablefortheoccurrenceofaclimate-inducednaturaldisasterorthenumberofdeathscausedbysuchaneventperpopulationinagivenyear—influencealternativemeasuresofinflationandeconomicgrowthinalargepanelof173countriesduringtheperiod1970–2020.Wealsoexplorethepossibilityofnonlineareffectsoflarge-scaleclimateshocksoninflationandrealGDPgrowthbylookingattwodimensions:(i)thepositionofagiveneconomyinthebusinesscycleand(ii)thelevelofpublicdebtasaproxyoffiscalspacewhenaweather-relateddisasteroccurs.Usingdataon173countriesovertheperiodfrom1970to2020,theempiricalanalysisshowsthatinflationandgrowthrespondsignificantlytodisasterscausedbyclimatechange,buttheimpactvariesintermsofdirectionandmagnitude.Whileextremetemperaturesresultinlowerinflation,droughtsandstormsleadtohigherlevelsofinflation.Wealsodevelopamoregranularanalysisbyfocusingonalternativemeasuresofinflationandidentifythattheimpactofweather-relatedshocksoncoreandfoodinflationshowssignificantvariationinmagnitudeandpatternacrosscountrygroups.Withregardstoeconomicgrowth,wefindthattheinitialresponseisnegativetoalltypesofclimateshocks,butthemagnitudeandpatternofresponseshowvariationoverthelongrun.Whenwesplitthesampleofcountriesbyincomegroup,weobserveastrikingcontrastintheimpactofclimateshocksoninflationandgrowthinadvancedanddevelopingcountries.Finally,wefindthattheimpactofclimatedisastersoninflationandgrowthvariesinanonlinearfashiondependingonthestateoftheeconomyandtheleveloffiscalspacewhentheshockhits.Theseresultssuggestthatclimate-inducednaturaldisasterhavedifferentialandopposingeffectsoninflationandgrowththroughmultiplechannels,suchas(i)increasingorloweringagriculturalproductionandfoodprices(ii)dampeningeconomicactivityandloweringlaborproductivity,(iii)2Climatereferstoadistributionofweatheroutcomesforagivenlocation,andclimatechangedescribesenvironmentalshiftsinthedistributionofweatheroutcomestowardextremes.4reducingwealthandincomeandtherebyconsumptionandinvestment;(iv)affectingtransportationinfrastructureanddistributioncosts.Furthermore,thesetransmissionchannelsvarysignificantlywiththelevelofeconomicdevelopmentanddiversificationacrosscountries.Empiricalfindingspresentedinthispapershouldbetreatedasalowerboundontheimpactofweather-relateddisastersinthewakeofacceleratingclimatechange.Accordingly,thereareseveralimportantimplicationsforeconomicpolicy.First,thiswillmakeinflationandgrowthdynamicsmorevolatile,withpotentialfeedbackeffectsacrossallsectorsoftheeconomy.Second,thedifferingpatternsinhowinflationandgrowthresponsetoclimateshockswillleadtogreaterheterogeneityinthelevelofinflationandincomegrowthexperiencedbydifferentsegmentsofthesocietywithinacountry.Inotherwords,householdswhoseconsumptionbasketconsistsofgoodsandservicesthataremorelikelytoexperienceanincreaseininflationandlossofincomeintheaftermathofnaturaldisasterswillbemoreadverselyaffectedcomparedtohouseholdswhoseconsumptionisproportionatelylessdependentonsuchproductsandincomeisnotsubjecttoanegativeshock.Theseresults,inourview,reflectdemographicandstructuraldifferencesandweakerfiscalandinstitutionalcapacityindevelopingcountiestoadapttoandmitigatetheconsequencesofclimateshocks.Lookingforward,itisalsoimportantforpolicymakerstoconsiderhowthegreentransitionawayfromfossilfuels,asanimportantpartofclimatechangemitigationefforts,willaffectinflationandgrowthdynamics.Theremainderofthispaperisorganizedasfollows.SectionIIprovidesanoverviewoftherelatedliterature.SectionIIIdescribesthedatausedintheempiricalanalysis.SectionIVintroducesthesalientfeaturesofoureconometricstrategy.SectionVpresentstheempiricalresults,includingaseriesofrobustnesschecks.Finally,SectionVIoffersconcludingremarkswithpolicyimplications.II.ABRIEFOVERVIEWOFTHELITERATUREWepulltogetherdifferentstrandsoftheliteratureoninflation,growthandclimatechange.First,inflationisshowntobedeterminedbyarangeoffactorsincludingpolicypreferences(Rogoff,1985)macroeconomicdevelopmentssuchasthelevelofincome,tradeandfinancialopenness,andfiscaldeficits(Végh,1989;Romer,1993;CampilloandMiron,1997;Lane1997;GalíandGertler,1999;GrubenandMcLeod,2002;CataoandTerrones,2005;ClarkandMcCracken,2006;Gupta,2008,Badinger,2009;Binicietal.,2022),labormarketinstitutions(CukiermanandLippi,1999),exchangerateregimes(Levy-YeyatiandSturzenegger,2001;Husainetal.,2005),andinstitutionalandpoliticalfeatures(Cukierman,1992;AisenandVeiga,2007).Thereisalsoabroadcollectionofstudiesfocusingontherelationshipbetweencentralbankindependenceandinflation.BuildingonKydlandandPrescott(1977)andBarroandGordon(1993),thisstrandoftheliteraturedemonstratesthatgreatercentralbankindependencebringsaboutlowandstableinflation,butnotalwaysinaconsistentandstatisticallysignificantway(Cukiermanetal.,1992;AlesinaandSummers,1993;CampilloandMiron,1997;LouganiandSheets,1997;Cottarellietal.,1998;Posen,1998;Arnoneetal.,2006;Brumm,2006;Walsh,2008;CevikandZhu,2020).Second,thereissignificantvariationineconomicgrowthacrosscountriesandovertime,drivenbyaplethoraofcultural,demographic,economic,financial,institutional,politicalandsocial5factors.Neoclassicalandendogenousgrowththeoriesexplainthesedifferencesingrowthperformancemainlybytheaccumulationofphysicalandhumancapitalandtechnologicaladvancements(Solow,1956;Romer,1986,1990;Lucas,1988).Usingcross-countryanalysis,EasterlyandWetzel(1989),Barro(1991;2003),BarroandSala-i-Martin(1992),Mankiwetal.(1992),EasterlyandRebelo(1993),KingandLevine(1993),Islam(1995),KnackandKeefer(1995),EasterlyandLevine,(1997),SachsandWarner(1997),BurnsideandDollar(2000),Acemogluetal.(2002),Sala-i-Martinetal.(2004),amongothers,showthatthedifferencesinincomegrowthratesaresystematicallyrelatedtoasetofquantifiablevariables,includingtheinitiallevelofrealGDPpercapita,theamountofhumancapitalintermsofeducationalattainmentsandhealthconditions,publicandprivateinvestment,theextentofinternationalopennessandterms-of-tradeshocks,alongwiththeinfluenceofgeography,institutionsandpolitics.Otherstudiesreachsimilarresults,evenwithdifferentsamplesandmethodologies(CicconeandJarocinski,2010).Third,thereisafast-developingliteratureontheeconomicandfinancialeffectsofclimatechange.3StartingwithNordhaus(1991;1992)andCline(1992),aggregatedamagefunctionsarewidelyusedtoanalyzetheclimate-economynexus.Whiletheidentificationofmacroeconomiceffectsofannualvariationinclimaticconditionsisadifficultempiricalundertaking,Gallupetal.(1999),Nordhaus(2006),andDelletal.(2012)observethathighertemperaturesresultinasignificantreductionineconomicgrowthindevelopingcountries.Burkeetal.(2015)corroboratethisfindinganddeterminethathighertemperatureswouldhaveagreaterdamageincountriesthatareconcentratedingeographicareaswithhotterclimates.Usinglargedatasets,Acevedoetal.(2018),BurkeandTanutama(2019),Kahnetal.(2021),andAkyapi,Bellon,andMassetti(2022)showthatthelong-termeconomicimpactofweatheranomalies,suchaspersistentchangesinthetemperatureaboveorbelowthehistoricalnorm,isnothomogenousacrosscountriesandthateconomicgrowthrespondsnonlinearlytoextremetemperature.Furthermore,CevikandJalles(2023)findthatanincreaseinclimatechangevulnerabilityispositivelyassociatedwithrisingincomeinequality,especiallyindevelopingcountriesduelargelytoweakercapacityforclimatechangeadaptationandmitigation.Itisalsowelldocumentedthatincreasingfrequencyandseverityofclimate-relatednaturaldisastersaffecteconomicdevelopment(Loyazaetal.,2012;Noy,2009;Raddatz,2009;SkidmoreandToya,2002;Rasmussen,2004),reducetheaccumulationofhumancapital(Cuaresma,2010)andworsenexternalbalances(Gassebneretal.,2010).Morerecently,CevikandJalles(2020;2021;2022)showthatclimatechangevulnerabilityhassignificanteffectsongovernmentbondyieldsandspreads,theprobabilityofsovereigndebtdefaultandsovereigncreditratings,especiallyindevelopingcountries.Similarly,Bansaletal.(2016)andIMF(2020)findthatrisksassociatedwithclimatechange—asproxiedbytemperatureincreases—haveanegativeeffectonassetvaluations,whileBernsteinetal.(2019)showthatrealestateexposedtotheriskofsealevelriseispricedatadiscountrelativetootherwisesimilarunexposedhouses.FocusingontheU.S.,Painter(2020)findsthatcountiesmorelikelytobeaffectedbyclimatechangepaymorein3Tol(2018)providesarecentoverviewofthisexpandingliterature.6underwritingfeesandinitialyieldstoissuelong-termmunicipalbondscomparedtocountiesunlikelytobeaffectedbyclimatechange.Withregardstotheimpactofclimatechangeonconsumerpriceinflation,thereisasmallbutgrowingliterature.Afewstudieslookattheimpactofnaturalhazardsonprices(Parker,2018;Heinenetal.,2019),whilethereisalmostnoresearchontheeffectofextremeweathereventsincludingtemperaturedeviations,apartfromstudiesfocusingonspecificsectorsofactivity(DeWinneandPeersman,2018;2021).Inarecentpaper,Facciaetal.(2021)investigatehowextremetemperaturesaffectvariousmeasuresofinflationin48advancedandemergingeconomiesduringtheperiod1951–1980andfindthathighertemperaturesplayedanon-negligibleroleindrivingpricedevelopments,especiallyforemergingmarketeconomies.Similarly,Kabundietal.(2022)analyzehowclimateshocksaffectconsumerpricesandfindthattheimpactdependsonthetypeandintensityofshocks,countryincomelevel,andmonetarypolicyregime.III.DATAOVERVIEWWeconstructapaneldatasetofannualobservationscovering173countriesovertheperiod1970–2020.Ourdependentvariablesareconsumerpriceinflationandeconomicgrowth.Inflationiscomputedonanannualbasisastheyear-on-yearpercentagechangeintheCPIasfollows:𝜋𝑐,𝑡=(𝐶𝑃𝐼𝑐,𝑡𝐶𝑃𝐼𝑐,𝑡−12)∗100where𝜋𝑐,𝑡denotesinflationincountrycattimetbasedonheadlineCPI,coreCPIandfoodcomponentoftheCPI,drawnfromtheWorldBank’sglobaldatabaseofinflation(Haetal.,2021).WemeasureeconomicgrowthusingtheannualrateofchangeinrealGDP,whichisobtainedfromtheWorldBank’sWorldDevelopmentIndicatorsdatabase.Themainexplanatoryvariablesofinterestareclimateshocksasmeasuredbytheoccurrenceofweather-relatednaturaldisastersfromtheEmergencyEventsDatabase(EM-DAT).TheEM-DATdatabaseonnaturaldisasters—compiledbytheCentreforResearchontheEpidemiologyofDisasters(CRED)attheUniversitéCatholiquedeLouvaininBelgium—providesdataontheoccurrenceandeffectsofover22,000large-scalenaturaldisastersacrosstheworldsince1900andoffersinformationondifferentcategoriesfromwhichwefocusonclimate-inducedeventsincludingdroughts,extremetemperatures,andstorms.4TheEM-DATdefinesdroughtsas“anextendedperiodofunusuallylowprecipitationthatproducesashortageofwaterforpeople,animalsandplants”,extremetemperaturesas“ageneraltermfortemperaturevariationsabove(extremeheat)orbelow(extremecold)normalconditions”,andstormsasmeteorologicaleventsincludingextra-tropical,tropicalandconvectivestorms.Theseshockstakethevalueof1whenaclimate-relateddisasteroccursinacountryinagivenyearandzerootherwise.However,to4Thedifferencebetweenextremetemperaturesanddroughtsisthattheformeristheresultofashort-livedmeteorologicalhazard,whilethelatteristheresultofalong-livedclimatologicalhazard.7developamoregranularanalysis,wealsousetheintensityofclimate-relatednaturaldisastersasmeasuredbythenumberofdeathsscaledbypopulation.FollowingtheliteratureassummarizedinBotzenetal.(2019),weintroduceanumberofcontrolvariablesinourregressionanalysis,includingrealGDPpercapita,theoutputgap,tradeopenness(definedasthesumofexportsandimportsoverGDP),moneysupplygrowth,urbanization,theterms-of-tradeindex,theoutputgap5,broadmoneygrowth,andthefinancialopennessindexdevelopedbyChinnandIto(2006).6WeobtainthedataseriesfromtheIMFWorldEconomicOutlook,theWorldBank´sWorldDevelopmentIndicatorsandtheChinn-Itodatabases.AppendixTableA1reportssummarystatisticsacrossallcountriesinthesample.IV.ECONOMETRICMETHODOLOGYInthispaper,weapplytheLPmethodtoestimatetheimpactofclimateshocksoninflationandeconomicgrowthandderiveimpulseresponsefunctions(IRFs)inapanelsetting.Thisapproachestimatesasequenceofregressionsofthedependentvariableshiftedseveralperiodsaheadinsteadofrecursiveuseoftheinitialsetofestimatedcoefficients.Asaresult,theLPtechniquedoesnotconstraintheshapeofIRFsandthereforebecomelesssensitivetopotentialmisspecificationcomparedtoconventionalVARmodels(AuerbachandGorodnichenko,2013;JordàandTaylor,2016).Sinceitisespeciallyusefulinestimatingnonlineardynamicresponses,theLPframeworkiswidelyadoptedintherecentliteraturetoanalyzetheeffectsofmonetarypolicyshocks(Jeenas,2018)andfiscalpolicyshocks(RameyandZubairy,2018;RomerandRomer,2019).Accordingly,wedefinethebaselinespecificationinthefollowingform:𝑦𝑡+𝑘,𝑖−𝑦𝑡−1,𝑖=𝛼𝑖+𝜏𝑡+β𝑘𝐶𝑆𝑖,𝑡+𝜃𝑋𝑖,𝑡+ε𝑖,𝑡(1)where𝑦isameasureofconsumerpriceinflationoreconomicgrowth,whicharewinsorizedat5thand95thpercentilestomitigatetheeffectsofextremeoutliers;thecoefficients𝛼𝑖and𝜏𝑡arecountryandtimefixedeffects,respectively,accountingforcross-countryheterogeneityandglobalshocks;𝛽𝑘denotesthecumulativeresponseofinflationorgrowthineachkyearaftertheclimateshock;and𝐶𝑆𝑖,𝑡denotestheclimateshockvariable,whichismeasuredbyeitherabinaryvariableorthenumberofdeathsscaledbypopulationandtreatedasanexogenouseventthatcannotbeanticipatednorcorrelatedwithpastchangesineconomicactivity.Large-scaleclimateeventsfeaturedinouranalysisareconsideredtobecountry-wideshocksfortworeasons:eitherbecausetheshockitselfiswidespreadorbecauseeconomicrelationshipsrelatedtotradeand/ormarketintegrationeventuallypropagatetheshockthroughoutthecountry.𝑋𝑖,𝑡isasetaof5TheoutputgapforeachcountryisobtainedbyapplyingtheHodrick-Prescott(HP)filter.Alternatively,andforrobustness,theoutputgapisalsoobtainedusingtheapproachofHamilton(2018)todecomposetimeseries´trendandcycle.6TheChinn-Itoindexisnormalizedbetween0and1,withhighervaluesindicatingthatacountryismoreopentocross-bordercapitaltransactions.8controlvariablesincludinguptotwolagsofclimateshocks,oftherelevantdependentvariableandtwolagsoftheoutputgapobtainedviatheHPfilter.7Thisequationisestimatedforthreedifferentmeasuresofinflation—headlineCPI,coreCPI,andfoodprices—andrealGDPgrowth.Intermsofthemainvariableofinterest(𝐶𝑆𝑖,𝑡),weconsiderthreealternativeclimateshocks:drought,extremetemperatures,andstorms.Equation(1)isestimatedusingtheOrdinaryLeastSquares(OLS)methodwithSpatialCorrelationConsistent(SCC)standarderrorsasproposedbyDriscollandKraay(1998).8Impulseresponsefunctions(IRFs)arethenobtainedbyplottingtheestimated𝛽𝑘for𝑘=0,1,…,5with90(68)percentconfidencebandscomputedusingthestandarderrorsassociatedwiththeestimatedcoefficients𝛽𝑘overafive-yearperiod.9AccordingtoSimsandZha(1999),“theconventionalpointwisebandscommonintheliteratureshouldbesupplementedwithmeasuresofshapeuncertainty.”Hence,forcharacterizingthelikelihoodshape,bandsthatcorrespondtoa68percentposteriorprobability—oronestandarddeviationshock—provideamorepreciseestimateofthetrueprobability.10Wealsoexplorewhetherinitialmacro-fiscalconditionsatthetimeoftheshockinfluencetheimpactofclimateshocksoninflationandgrowth.TheLPestimationofnonlineareffectsissimilartothesmoothtransitionautoregressive(STAR)modelproposedbyGrangerandTerasvirta(1993).11Accordingly,theaugmentedLPmodeltakesthefollowingform:𝑦𝑖,𝑡+𝑘−𝑦𝑖,𝑡−1=𝛼𝑖+𝜏𝑡+𝛽𝑘𝐿𝐹(𝑧𝑖,𝑡)𝐶𝑆𝑖,𝑡+𝛽𝑘𝐻(1−𝐹(𝑧𝑖,𝑡))𝐶𝑆𝑖,𝑡+θ𝑋𝑖,𝑡+𝜀𝑖,𝑡(2)with𝐹(𝑧𝑖𝑡)=exp(−𝛾𝑧𝑖𝑡)1+exp(−𝛾𝑧𝑖𝑡),𝛾>0inwhich𝑧𝑖𝑡thestateoftheeconomyasmeasuredbytheoutputgaporthepublicdebt-to-GDPratiothatisnormalizedtohavezeromeanandunitvariance.12Thecoefficients𝛽𝐿𝑘and𝛽𝐻𝑘capturetheimpactofclimateshocksateachhorizonkincasesofrecessions(𝐹(𝑧𝑖𝑡)≈1whenzgoestominusinfinity)andexpansions(1−𝐹(𝑧𝑖𝑡)≈1whenzgoestoplusinfinity),respectively.7Alternatively,wealsoemployedtheoutputgapobtainedviaHamilton(2018)approachandresultshardlychange.8Thisisanonparametrictechniqueassumingtheerrorstructuretobeheteroskedastic,autocorrelateduptosomelag,andpossiblycorrelatedacrosscountries.9AnotheradvantageoftheLPmethodcomparedtovectorautoregression(autoregressivedistributedlag)specificationsisthatthecomputationofconfidencebandsdoesnotrequireMonteCarlosimulationsorasymptoticapproximations.Onelimitation,however,isthatconfidencebandsatlongerhorizonstendtobewiderthanthoseestimatedinvectorautoregressionspecifications.10OtherpapersthathaveemployedonestandarddeviationbandsincludeGiordanoetal.(2007),RomerandRomer(2010)andBachmannandSims(2012),amongothers.11UsingsuchaSTARfunctioninsuchempiricalsetupsisnotnew.AuerbachandGorodnichenko(2013)andAbiadetal.(2016)employedasimilarapproachtolookatnonlineareffectsofmonetaryandfiscalshocks.12Theweightsassignedtoeachregimevarybetween0and1accordingtotheweightingfunction𝐹(.),sothat𝐹(𝑧𝑖𝑡)canbeinterpretedastheprobabilityofbeinginagivenspacestate.9Wechoose𝛾=1.5.13ThisapproachpermitsadirecttestofwhethertheeffectofclimateshocksvariesacrossdifferentregimessuchasrecessionsandexpansionsandallowstheeffectofclimateshockstochangesmoothlybetweenrecessionsandexpansionsbyconsideringacontinuumofstatestocomputeIRFs,thusmakingtheresponsemorestableandprecise.Weusefiscalspaceasanalternativeconditioningvariabletoassesswhetheragovernment’sfiscalcapacitytorespondtoaclimateshockaffectsitsinflationaryimpact.V.EMPIRICALRESULTSA.ClimateShocksandInflationThestartingpointofourempiricalanalysisistheestimationoftheimpactofclimateshocksoninflationinthewholesampleof173countriesovertheperiod1970-2020.Figure1presentstheIRFsofheadlineinflationtothreetypesofclimate-relatednaturaldisastershocks,togetherwith90percentconfidenceintervals.Wefindthatheadlineinflationrespondssignificantlybutalsodifferentlyintermsofdirectionandmagnitudetoclimateshocksasmeasuredbyabinaryvariablefortheoccurrenceofalarge-scaleweather-relatednaturaldisasterinagivenyear.Whileextremetemperaturesresultinlowerinflation,droughtsandstormsleadtohigherinflation.Inthecaseofatemperatureshock,wefindthatheadlineinflationdeclinessignificantlybelowitsinitiallevelinthefirstyearandoverthelongrun.14Thisfallreachesitstroughafterabout4yearsFigure1.BaselineImpactofClimateShocksonHeadlineInflation:GlobalSampleNote:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,andthedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.13Ourresultshardlychangewhenusingalternativevaluesoftheparameter𝛾,between1and4.WealsoattemptedusingalternativelytheoutputgapcomputedviatheHamilton(2018)approach,whichyieldsqualitativelysimilarresults.14Theseresultsarebroadlyconsistentwiththosereportedinotherstudies,suchasParker(2018)andKabundietal.(2022).-6-4-20012345yeartemperatureshock-2024012345yeardroughtshock-2-1.5-1-.50.5012345yearstormshockImpactonHCPIfromalternativeshocks10sincetheshock,atwhichpointheadlineinflationis3.5percentagepointslowerthanifthetemperatureshockhadnothappened.Adroughtshock,ontheotherhand,resultsinanimmediateincreaseinheadlineinflationaboveitsinitiallevel,whichlastsoverthelongtermandamountstoabout1.5percentagepointscomparedtoiftheshockhadnotoccurred.Theimpactpatternofstorms,however,isdifferentthanotherweather-relateddisasters.Wefindthatheadlineinflationincreasesbyabout0.2percentagepointsinthefirstyearafterthestormshock,butthenendsup1percentagepointsloweroverthelongtermiftheshockhadnothappened.TableA2intheAppendixshowsallthecoefficientestimates,associatedstandarderrorsandbasicdiagnosticstatisticsbehindtheIRFsdepictedinFigure1.Wesplitthefullsampleofcountriesintoincomegroups—advancedeconomiesanddevelopingcountries—andpresenttheseIRFsinFigure2.Thisdisaggregationrevealsastrikingcontrastintheimpactofclimateshocksonheadlineinflationineconomieswithvaryinglevelsofeconomicdevelopment.Whileatemperatureshockleadstosustainedincreaseinheadlineinflationinadvancedeconomies,ithastheoppositeeffectindevelopingcountries.Inthecaseofadroughtshock,wefindthatheadlineinflationincreasesaboveitsinitiallevelacrossinthefirstyearandoverthelongrun,butthiseffectissmallanddissipatesfastinadvancedeconomiescomparedtodevelopingcountrieswhereitislong-lasting.Likewise,theinitialimpactofastormshockisdifferentinadvancedeconomies(lowerheadlineinflation)comparedtodevelopingcountries(higherheadlineinflation)butdoesnotpersistoverthelongruninbothincomegroups.Theseresultsmayreflectstructuralanddemographicdifferencesandweakerfiscalandinstitutionalcapacityindevelopingcountiestoadapttoandmitigatetheconsequencesofclimateshocks.WedevelopamoregranularanalysisbyfocusingonalternativemeasuresofinflationandpresenttheseIRFsofcoreandfoodinflationtoclimateshocksforthesub-samplesofadvancedeconomicanddevelopingcountriesinFigure3.Theimpactofweather-relatedshocksoncoreFigure2.ImpactofClimateShocksonHeadlineInflation:IncomeGroupAdvancedEconomiesDevelopingCountriesThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.01234012345yeartemperatureshock-4-202012345yeardroughtshock-1.5-1-.50.51012345yearstormshockImpactonHCPIfromalternativeshocks-15-10-50012345yeartemperatureshock-2024012345yeardroughtshock-2-101012345yearstormshockImpactonHCPIfromalternativeshocks11andfoodinflationshowssignificantvariationinmagnitudeandpatternacrosscountrygroups.Extremetemperaturesleadtohigherandmorevolatilecoreandfoodinflationinadvancedeconomies,whereasithastheoppositeandsustainedimpactindevelopingcountries.Adroughtshockappearstobedisinflationarywithavolatilepatterninadvancedeconomiesbutexhibitsasustainedinflationaryeffectindevelopingcountries.Theinflationaryimpactofdroughtsonfoodprices,however,issimilaracrossallcountrygroups,albeitsignificantlygreaterindevelopingcountries.Finally,astormshockleadstoasmallimmediateincreaseincoreinflationinadvancedeconomies,butthiseffectdissipatesoverthelongrun,whereasweobserveadownwardadjustmentincoreinflationinthefirstyearafterastormshockthatremainsintactoverthelongFigure3.ImpactofClimateShocksonInflation:CoreandFoodInflationAdvancedEconomiesDevelopingCountriesCoreInflationFoodInflationNote:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.-101234012345yeartemperatureshock-4-2024012345yeardroughtshock-1.5-1-.50.51012345yearstormshockImpactonCoreinflationfromalternativeshocks-8-6-4-202012345yeartemperatureshock-20246012345yeardroughtshock-6-4-20012345yearstormshockImpactonCoreinflationfromalternativeshocks012345012345yeartemperatureshock-20246012345yeardroughtshock-1.5-1-.50.51012345yearstormshockImpactonFoodinflationfromalternativeshocks-10-8-6-4-20012345yeartemperatureshock02468012345yeardroughtshock-2024012345yearstormshockImpactonFoodinflationfromalternativeshocks12runinthecaseofdevelopingcountries.Theimpactofstormsonfoodinflation,ontheotherhand,exhibitsanoppositepatterninadvancedeconomies(declining)anddevelopingcountries(increasing),butconvergestoinsignificanceoverthelongruninbothcountrygroups.Figure4.ImpactofClimateShocksonCoreInflation:RoleoftheBusinessCycleAdvancedEconomiesDevelopingCountriesNote:ThechartspresentIRFsbasedonEquation[2].x-axisinyears;t=0istheyearoftheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock;thedarkandlightgreyareadenotes90and68-percentconfidencebands,respectively,basedonstandarderrorsclusteredatcountrylevel;thedottedbluelinedenotestheunconditionalbaselineresultobtainedfromEquation[1].-50510012345yeardroughtshockinrecessions-15-10-505012345yeardroughtshockinexpansionsImpactonCCPI-5051015012345yeardroughtshockinrecessions-10-50510012345yeardroughtshockinexpansionsImpactonCCPI051015012345yeartemperatureshockinrecessions-505012345yeartemperatureshockinexpansionsImpactonHCPI-50510012345yeartemperatureshockinrecessions-20-15-10-505012345yeartemperatureshockinexpansionsImpactonHCPI-4-2024012345yearstormshockinrecessions-4-202012345yearstormshockinexpansionsImpactonHCPI-5051015012345yearstormshockinrecessions-20-15-10-50012345yearstormshockinexpansionsImpactonHCPI13Wealsoexplorethepossibilityofnonlineareffectsofclimateshocksoninflationbylookingattwoparticulardimensions:(i)thepositionofagiveneconomyinthebusinesscycleatthetimetheclimateshockhits;and(ii)thelevelofpublicdebtasaproxyoffiscalspacetocushiontheimpactofclimateshocks.First,aspresentedinFigure4,wefindthatthestateoftheeconomyFigure5.ImpactofClimateShocksonCoreInflation:RoleoftheFiscalSpaceAdvancedEconomiesDevelopingCountriesNote:ThechartspresentIRFsbasedonEquation[2].x-axisinyears;t=0istheyearoftheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock;thedarkandlightgreyareadenotes90and68-percentconfidencebands,respectively,basedonstandarderrorsclusteredatthecountrylevel;thedottedbluelinedenotestheunconditionalbaselineresultobtainedfromEquation[1].-5051015012345yeardroughtshock-lowdebt-8-6-4-202012345yeardroughtshock-highdebtImpactonHCPI-15-10-50510012345yeardroughtshock-lowdebt-505101520012345yeardroughtshock-highdebtImpactonHCPI-4-20246012345yeartemperatureshock-lowdebt-2024012345yeartemperatureshock-highdebtImpactonHCPI-50510012345yeartemperatureshock-lowdebt-20-15-10-50012345yeartemperatureshock-highdebtImpactonHCPI-6-4-2024012345yearstormshock-lowdebt-4-2024012345yearstormshock-highdebtImpactonHCPI-15-10-505012345yearstormshock-lowdebt-50510012345yearstormshock-highdebtImpactonHCPI14playsanimportantroleinshapingtheimpactofweather-relateddisastersoncoreinflation,butmagnitudeandlong-runpatterndependontheexactnatureoftheshock.Second,aspresentedinFigure5,wefindthatclimateshockshaveadifferentiatedeffectoncoreinflationdependingontheleveloffiscalspaceasmeasuredbylowlevelsofpublicdebtasaratioofGDP.Theinflationaryimpactofweather-relateddisastersinlowerincountrieswithgreaterfiscalspacecomparedtocountriesthatarefiscallyconstrained.Weconductseveralsensitivitycheckstoensuretherobustnessofourbaselineresults.First,wecontrolforthepotentialomittedvariablebiasbyincludinguptotwolagsofadditionalvariablesthatcouldcontributetoinflationdynamics,suchasameasureoffinancialopenness,theterms-of-tradeindex,urbanization,andmoneysupplygrowth.Second,weestimatethemodelsbyexcludingcountryfixedeffects,whichcouldbiastheresultssincetheerrortermmayhaveanon-zeroexpectedvalueduetotheinteractionoffixedeffectsandcountryspecificdevelopments(TeulingsandZubanov,2014).Third,wesplitthesampleintotwoperiods(1970–1995and1996–2020)toexaminewhethertheinflationaryimpactofclimateshockshasbecomemorepronouncedovertime.Theseestimations,presentedinFigure6-8,yieldsimilarresultswithnosignificantqualitativechange.Finally,todevelopamoregranularanalysis,weestimateameasureofdisasterintensity(thenumberofdeathsscaledbypopulation)andfindthattheimpactofclimateshocksoninflationbecomesmorepronouncedandturnspositiveeveninthecaseofextremetemperatures(Figure9).Figure6.ImpactofClimateShocksonHeadlineInflation:AdditionalControlsControlset1Controlset2Note:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.Controlset1includesinadditiontotheoutputgap(alsoincludedinthebaseline),tradeopennessandthelogofrealGDPpercapita.Control2includescontrol1variablesplusbroadmoneygrowth,financialopenness,urbanization,termsoftrade.-5-4-3-2-10012345yeartemperatureshock-101234012345yeardroughtshock-1012012345yearstormshockImpactonHCPIfromalternativeshocks15Figure7.ImpactofClimateShocksonHeadlineInflation:ExcludingCountryFixedEffectsNote:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.Figure8.ImpactofClimateShocksonHeadlineInflation:Sub-PeriodEstimations1970-19951996-2020Note:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.-8-6-4-20012345yeartemperatureshock0246012345yeardroughtshock-5-4-3-2-10012345yearstormshockImpactonHCPIfromalternativeshocks-10-505012345yeartemperatureshock-505012345yeardroughtshock-50510012345yearstormshockImpactonHCPIfromalternativeshocks-3-2-101012345yeartemperatureshock012345012345yeardroughtshock-2-1012012345yearstormshockImpactonHCPIfromalternativeshocks16Figure9.ImpactofClimateShocksonHeadlineInflation:DisasterIntensityNote:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.B.ClimateShocksandGrowthFigure10presentstheIRFsofrealGDPgrowthtothreetypesofweather-relatednaturaldisasters,togetherwith90percentconfidenceintervals.Wefindthattheinitialgrowthresponsetoalltypesofclimateshocksisnegative,butthemagnitudeandpatternofresponseshowvariationoverthelongrun.WhileatemperatureshockappearstoleadtoalastingreductioninrealGDPgrowth,theimpactofdroughtsandstormsismorevolatileandlesspersistentoverthelongrun.Inthecaseofatemperatureshock,thegrowthdecelerationreachesatthroughafter5yearssincetheshock,atwhichpointrealGDPgrowthisabout1.5percentagepointslowerthanifthetemperatureshockhadnothappened.Bothdroughtsandstormscauseasteeperfallingrowthinthefirstyearaftertheshock,butthemagnitudeoftheimpactisvolatileandlesspersistentovertime.TableA3intheAppendixshowsallthecoefficientestimates,associatedstandarderrorsandbasicdiagnosticstatisticsbehindtheIRFsdepictedinFigure10.Tobetterdiscernthegrowthimpactofclimateshocks,wesplitthefullsampleofcountriesintoincomegroups—advancedeconomiesanddevelopingcountries—andpresenttheseIRFsinFigure11.ThisdisaggregationconfirmsrevealsastrikingcontrastintheimpactofclimateshocksonrealGDPgrowthincountriesatdifferentlevelsofdevelopment.Whileweather-relatednaturaldisastersleadtoasignificantandpersistentdeclineineconomicgrowthindevelopingcountries,thereisnosuchimpactinadvancedeconomies.Nevertheless,whenweusetheintensityofclimateshocks(measuredbythenumberofdeathsscaledbypopulation)insteadofadummyvariablefordisasters,thegrowthimpactissignificantlynegativeforalltypesofclimateshocksacrossallcountriesinoursample(Figure12).-.50.51012345yeartemperatureshock-50510012345yeardroughtshock-3-2-101012345yearstormshockImpactonHCPIfromalternativeshocks17Wealsoexplorethenonlineareffectsofweather-relatednaturaldisastersoneconomicgrowthbytakingintoaccountthestateoftheeconomyandthelevelofpublicdebtasaproxyoffiscalspaceatthetimetheclimateshockhits.Theseresults,presentedinFigure13-14,showthatboththestateoftheeconomyandavailablefiscalspaceplaycriticalrolesindetermininghowclimateshocksaffecteconomicgrowthintermsofmagnitudeandpersistenceoverthelongrun,whichalsovarieswiththelevelofincomeacrosscountries.Theseresults,inourview,reflectdemographicandstructuraldifferencesandweakerfiscalandinstitutionalcapacityindevelopingcountiestoadapttoandmitigatetheconsequencesofclimateshocks.Inparticular,weshouldalsonotethattheoverallimpactofweather-relatednaturaldisastersonrealGDPgrowthislikelytoconcealsignificantdifferencesacrosssectors,asshownbythevaryinggrowthresponseinadvancedanddevelopingeconomies.Figure10.ImpactofClimateShocksonGrowth:GlobalSampleNote:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.-2.5-2-1.5-1-.50012345yeartemperatureshock-1-.50.51012345yeardroughtshock-1-.50.51012345yearstormshockImpactonrealGDPfromalternativeshocks18Figure11.ImpactofClimateShocksonGrowth:IncomeGroupAdvancedEconomiesDevelopingCountriesNote:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.Figure12.ImpactofClimateShocksonGrowth:DisasterIntensityNote:ThechartsshowIRFsusingtheLPmethod.x-axisinyears;t=0istheyearprecedingtheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock,thedarkgreyareadenotes90-percentconfidencebandsandthelightgreyareadenotes68-percentconfidencebandsbasedonstandarderrorsclusteredatthecountrylevel.-1-.8-.6-.4-.20012345yeartemperatureshock-8-6-4-20012345yeardroughtshock0.2.4.6012345yearstormshockImpactonrealGDPfromalternativeshocks-1-.50.51012345yeartemperatureshock-1-.50.511.5012345yeardroughtshock-1.5-1-.50.51012345yearstormshockImpactonrealGDPfromalternativeshocks-3-2-101012345yeartemperatureshock-1-.50.51012345yeardroughtshock-1-.50.51012345yearstormshockImpactonrealGDPfromalternativeshocks19Figure13.ImpactofClimateShocksonGrowth:RoleoftheBusinessCycleAdvancedEconomiesDevelopingCountriesNote:ThechartspresentIRFsbasedonEquation[2].x-axisinyears;t=0istheyearoftheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock;thedarkandlightgreyareadenotes90and68-percentconfidencebandsrespectivelybasedonstandarderrorsclusteredatcountrylevel;thedottedbluelinedenotestheunconditionalbaselineresultobtainedfromEquation[1].-3-2-1012012345yeardroughtshockinrecessions-3-2-1012012345yeardroughtshockinexpansionsImpactonrealGDP-2-10123012345yeardroughtshockinrecessions-2-1012012345yeardroughtshockinexpansionsImpactonrealGDP-1012012345yeartemperatureshockinrecessions-2-1012012345yeartemperatureshockinexpansionsImpactonrealGDP-6-4-202012345yeartemperatureshockinrecessions-4-2024012345yeartemperatureshockinexpansionsImpactonrealGDP-2-1012012345yearstormshockinrecessions-1-.50.511.5012345yearstormshockinexpansionsImpactonrealGDP-5-4-3-2-10012345yearstormshockinrecessions-20246012345yearstormshockinexpansionsImpactonrealGDP20Figure14.ImpactofClimateShocksonGrowth:RoleofFiscalSpaceAdvancedEconomiesDevelopingCountriesNote:ThechartspresentIRFsbasedonEquation[2].x-axisinyears;t=0istheyearoftheclimateshock;t=1isthefirstyearofimpact.Thesolidblacklinedenotestheresponsetoaclimateshock;thedarkandlightgreyareadenotes90and68-percentconfidencebandsrespectivelybasedonstandarderrorsclusteredatcountrylevel;thedottedbluelinedenotestheunconditionalbaselineresultobtainedfromEquation[1].-8-6-4-202012345yeardroughtshock-lowdebt02468012345yeardroughtshock-highdebtImpactonrealGDP-20246012345yeardroughtshock-lowdebt-6-4-202012345yeardroughtshock-highdebtImpactonrealGDP-2-1012012345yeartemperatureshock-lowdebt-1012012345yeartemperatureshock-highdebtImpactonrealGDP-6-4-202012345yeartemperatureshock-lowdebt-4-2024012345yeartemperatureshock-highdebtImpactonrealGDP-3-2-1012012345yearstormshock-lowdebt01234012345yearstormshock-highdebtImpactonrealGDP-3-2-1012012345yearstormshock-lowdebt-2-1012012345yearstormshock-highdebtImpactonrealGDP21VI.CONCLUSIONClimatechangeisthedefiningchallengeofourtime.Inthispaper,weempiricallyinvestigatetheimpactofweather-relatednaturaldisastersonconsumerpriceinflationandeconomicgrowth,usingalargepanelof173countriesduringtheperiod1970–2020.TheanalysisbasedontheLPmethodshowsthatinflationandgrowthrespondsignificantlybutalsodifferentlyintermsofdirectionandmagnitudetoclimateshocks.oTemperatureshocksresultinlowerinflation,butdroughtsandstormsleadtohigherinflation.Wesplitthefullsampleofcountriesintoincomegroups—advancedeconomiesanddevelopingcountries—andfindastrikingcontrastintheimpactofclimate-inducednaturaldisastersonheadlineinflationaccordingtothelevelofeconomicdevelopment.Wealsodevelopamoregranularanalysisbyfocusingonalternativemeasuresofinflationandidentifythattheimpactofweather-relatedshocksoncoreandfoodinflationshowssignificantvariationinmagnitudeandpatternacrosscountrygroups.Finally,wefindthattheinflationaryimpactofclimatedisastersvariesinanonlinearfashiondependingonthestateoftheeconomyandtheleveloffiscalspacewhentheshockhits.oAlltypesofclimateshockshaveanegativeimpactoneconomicgrowth,butthemagnitudeandpatternofresponseshowvariationoverthelongrun.WhileatemperatureshockappearstoleadtoalastingreductioninrealGDPgrowth,theimpactofdroughtsandstormsismorevolatileandlesspersistent.Tobetterdiscernthegrowthimpactofclimateshocks,wesplitthefullsampleofcountriesintoincomegroupsandfindastrikingcontrastintheimpactofclimateshocksonrealGDPgrowthincountriesatdifferentlevelsofdevelopment.Whileweather-relatednaturaldisastersleadtoasignificantandpersistentdeclineineconomicgrowthindevelopingcountries,thereisnosuchimpactinadvancedeconomies.Wealsoexplorethenonlineareffectsofweather-relatednaturaldisastersoneconomicgrowthandobservethatboththestateoftheeconomyandavailablefiscalspaceplaycriticalrolesindetermininghowclimateshocksaffectgrowthintermsofmagnitudeandpersistenceoverthelongrun,whichalsovarieswiththelevelofincomeacrosscountries.Overall,theempiricalanalysispresentedinthispaperindicatesthatclimate-inducednaturaldisastershavedifferentialandopposingeffectsoninflationandgrowththroughmultiplechannels,suchas(i)increasingorloweringagriculturalproductionandfoodprices(ii)dampeningeconomicactivityandloweringlaborproductivity,(iii)reducingwealthandincomeandtherebyconsumptionandinvestment;(iv)affectingtransportationinfrastructureanddistributioncosts.Furthermore,thesetransmissionchannelsvarysignificantlywiththelevelofeconomicdevelopmentanddiversificationacrosscountries.Theseresults,inourview,alsoreflectdemographicandstructuraldifferencesandweakerfiscalandinstitutionalcapacityindevelopingcountiestoadapttoandmitigatetheconsequencesofclimateshocks.Accordingly,thereareseveralimportantimplicationsforeconomicpolicyinthewakeofacceleratingclimatechange.First,thiswillmakeinflationandgrowthdynamicsmorevolatile,withpotentialfeedbackeffectsacrossallsectorsoftheeconomy.Second,thedifferingpatternsofinflationandgrowthresponsetoclimateshockswillleadtogreaterheterogeneityinthelevelofinflationandincomegrowthexperiencedbydifferentsegmentsofthesocietywithinacountry.Inotherwords,22householdswhoseconsumptionbasketconsistsofgoodsandservicesthataremorelikelytoexperienceanincreaseininflationandlossofincomeintheaftermathofnaturaldisasterswillbemoreadverselyaffectedcomparedtohouseholdswhoseconsumptionisproportionatelylessdependentonsuchproductsandincomeisnotsubjecttoanegativeshock.Lookingforward,itisalsoimportantforpolicymakerstoconsiderhowthegreentransitionawayfromfossilfuels,asanimportantpartofclimatechangemitigationefforts,willaffectinflationandgrowthdynamics.23REFERENCESAbiad,A.,D.Furceri,andP.Topalova,2016,”TheMacroeconomicEffectsofPublicInvestment:EvidencefromAdvancedEconomies,”JournalofMacroeconomics,Vol.50,pp.224–240.Acemoglu,D.,S.Johnson,andJ.Robinson,2002,“ReversalofFortune:GeographyandInstitutionsintheMakingoftheModernWorldIncomeDistribution,”QuarterlyJournalofEconomics,Vol.117,pp.1231–1294.Acevedo,S.,M.Mrkaic,N.Novta,E.Pugacheva,andP.Topalova,2018,“TheEffectsofWeatherShocksonEconomicActivity:WhatAretheChannelsofImpact?”IMFWorkingPaperNo.18/144(Washington,DC:InternationalMonetaryFund).Akyapi,B.,M.Bellon,andE.Massetti,2022,“EstimatingMacro-FiscalEffectsofClimateShocksFromBillionsofGeospatialWeatherObservations,”IMFWorkingPaperNo.22/156(Washington,DC:InternationalMonetaryFund).Aisen,A.,andF.Veiga,2006,“DoesPoliticalInstabilityLeadtoHigherInflation?APanelDataAnalysis,”JournalofMoneyCreditandBanking,Vol.38,pp.1379–1390.Aizenman,J.,M.Chinn,andH.Ito,2010,“TheEmergingGlobalFinancialArchitecture:TracingandEvaluatingtheNewPatternsoftheTrilemma’sConfigurations,”JournalofInternationalMoneyandFinance,Vol.29,pp.615–641.Aizenman,J.,M.Chinn,andH.Ito,2008,“AssessingtheEmergingGlobalFinancialArchitecture:MeasuringtheTrilemma’sConfigurationsOverTime,”NBERWorkingPaperNo.14533(Cambridge,MA:NationalBureauofEconomicResearch).Alesina,A.,andL.Summers,1993,“CentralBankIndependenceandMacroeconomicPerformance:SomeComparativeEvidence,”JournalofMoney,Credit,andBanking,Vol.25,pp.151–162.Arellano,M.,andS.Bond,1991,“SomeTestsofSpecificationforPanelData:MonteCarloEvidenceandAnApplicationtoEmploymentEquations,”ReviewofEconomicStudies,Vol.58,pp.277–297.Arellano,M.,andO.Bover,1995,“AnotherLookattheInstrumentalVariableEstimationofError-ComponentsModels,”JournalofEconometrics,Vol.68,pp.29–51.Arnone,M.,B.Laurens,andJ.Segalotto,2006,“MeasuresofCentralBankAutonomy:EmpiricalEvidenceforOECD,DevelopingCountries,andEmergingMarkets,”IMFWorkingPaperNo.06/228(Washington,DC:InternationalMonetaryFund).Auerbach,A.,andY.Gorodnichenko,2013,“OutputSpilloversfromFiscalPolicy,”AmericanEconomicReview,Vol.103,pp.141–146.Bachmann,R.,andE.Sims,2012,"ConfidenceandtheTransmissionofGovernmentSpendingShocks,"JournalofMonetaryEconomics,Vol.59,pp.235–249.Badinger,H.,2009,“Globalization,theOutput–InflationTradeoffandInflation,”EuropeanEconomicReview,Vol.53,pp.888–907.24Bansal,R.,D.Kiku,andM.Ochoa,2016,“PriceofLong-RunTemperatureShiftsinCapitalMarkets,”NBERWorkingPaperNo.22529(Cambridge,MA:NationalBureauofEconomicResearch).Barro,R.,1991,“EconomicGrowthinaCross-SectionofCountries,”QuarterlyJournalofEconomics,Vol.106,pp.407–443.Barro,R.,2003,“DeterminantsofEconomicGrowthinaPanelofCountries,”AnnalsofEconomicsandFinance,Vol.4,pp.231–274.Barro,R.,andX.Sala-i-Martin,1992,“PublicFinanceinModelsofEconomicGrowth,”ReviewofEconomicStudies,Vol.59,pp.645–661.Barro,R.,andD.Gordon,1993,“Rules,DiscretionandreputationinaModelofMonetaryPolicy,”JournalofMonetaryEconomics,Vol.12,pp.101–121.Baxter,M.,andR.King,1999,“MeasuringBusinessCycles:ApproximateBand-PassFiltersforEconomicTimeSeries,”ReviewofEconomicsandStatistics,Vol.81,pp.575–593.Bernstein,A.,M.Gustafson,andR.Lewis,2019,“DisasterontheHorizon:ThePriceEffectofSeaLevelRise,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)(0.008)(0.010)L2.shock-0.0004-0.0035-0.0058-0.0040-0.0152-0.00310.0012-0.00030.0034-0.00690.00060.00280.00530.00780.0102(0.002)(0.005)(0.008)(0.014)(0.014)(0.002)(0.004)(0.006)(0.009)(0.013)(0.002)(0.004)(0.008)(0.009)(0.010)L.hcpi10.14780.30180.46900.65940.79250.14760.30140.46880.65950.79320.14800.30200.46960.66000.7936(0.030)(0.047)(0.090)(0.147)(0.197)(0.030)(0.048)(0.090)(0.147)(0.198)(0.030)(0.047)(0.090)(0.147)(0.197)L2.hcpi10.01140.03350.06870.08840.09750.01150.03380.06880.08880.09810.01120.03320.06820.08830.0974(0.010)(0.025)(0.056)(0.079)(0.104)(0.010)(0.025)(0.055)(0.080)(0.105)(0.010)(0.025)(0.055)(0.079)(0.105)L.outputgap0.00000.00000.00000.00000.00000.00000.00000.00000.00000.0000-0.00000.00000.00000.00000.0000(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)L2.outputgap0.00000.00000.00000.00000.00000.00000.00000.00000.00000.00000.00000.00000.00000.00000.0000(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)Observations5,1805,0544,9164,7634,6065,1805,0544,9164,7634,6065,1805,0544,9164,7634,606R-squared0.36860.36040.35100.34360.30620.36890.36010.34970.34240.30490.36830.35970.34970.34250.3051Numberofcountries172172172172171172172172172171172172172172171Note:LPestimationofequation[1].Headlineinflationasdependentvariable.Standarderrorsinparenthesis.,,denotestatisticalsignificanceatthe10,5and1percentlevels,respectively.Constantomittedforreasonsofparsimony.33TableA3.CoefficientEstimatesunderlyingFigure10Horizonk(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)ShocktypeExtremetemperatureDroughtStormshock-0.0011-0.0026-0.0057-0.0108-0.0137-0.0025-0.0011-0.00160.00020.0012-0.00110.00160.0009-0.00030.0018(0.002)(0.003)(0.004)(0.005)(0.006)(0.002)(0.003)(0.003)(0.005)(0.006)(0.001)(0.003)(0.004)(0.004)(0.004)L.shock-0.0014-0.0058-0.0101-0.0130-0.01610.00380.00300.00630.00500.00370.00290.00240.00240.00240.0022(0.001)(0.003)(0.004)(0.005)(0.006)(0.002)(0.003)(0.004)(0.006)(0.007)(0.001)(0.003)(0.003)(0.004)(0.004)L2.shock-0.0040-0.0077-0.0106-0.0139-0.0142-0.00040.00180.0005-0.00040.0025-0.0016-0.0017-0.0021-0.0026-0.0013(0.001)(0.003)(0.003)(0.005)(0.005)(0.002)(0.003)(0.004)(0.006)(0.007)(0.001)(0.002)(0.003)(0.004)(0.004)L.gdp10.18140.20040.23910.23480.26360.18190.20110.24080.23730.26600.18230.20130.24100.23780.2663(0.043)(0.059)(0.070)(0.073)(0.073)(0.043)(0.059)(0.070)(0.073)(0.073)(0.043)(0.059)(0.070)(0.073)(0.073)L2.gdp10.03310.09300.08020.08340.00480.03340.09410.08160.08480.00640.03330.09330.08110.08460.0054(0.025)(0.053)(0.069)(0.070)(0.049)(0.026)(0.053)(0.069)(0.070)(0.049)(0.026)(0.053)(0.069)(0.070)(0.049)L.outputgap-0.0000-0.0000-0.0000-0.0001-0.0001-0.0000-0.0000-0.0000-0.0001-0.0001-0.0000-0.0000-0.0000-0.0001-0.0001(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)L2.outputgap-0.0000-0.0000-0.0000-0.0001-0.0001-0.0000-0.0000-0.0000-0.0001-0.0001-0.0000-0.0000-0.0000-0.0001-0.0001(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)Observations5,1055,0114,8844,7394,5865,1055,0114,8844,7394,5865,1055,0114,8844,7394,586R-squared0.16680.14900.13940.12960.11750.16710.14790.13780.12710.11480.16700.14810.13760.12710.1148Numberofcountries173173173173172173173173173172173173173173172Note:LPestimationofequation[1].Headlineinflationasdependentvariable.Standarderrorsinparenthesis.,,denotestatisticalsignificanceatthe10,5and1percentlevels,respectively.Constantomittedforreasonsofparsimony.

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