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EUROPEANCENTRALBANK
EUROSYSTEM
LorenzEmter,AfonsoS.Moura,RalphSetzer,NicoZorell
WorkingPaperSeries
Monetarypolicyandgrowth-at-risk:theroleofinstitutionalquality
No2989
Disclaimer:ThispapershouldnotbereportedasrepresentingtheviewsoftheEuropeanCentralBank(ECB).TheviewsexpressedarethoseoftheauthorsanddonotnecessarilyreflectthoseoftheECB.
ECBWorkingPaperSeriesNo29891
Abstract
Thispaperanalyseshowcountry-speci?cinstitutionalqualityshapestheimpactofmon-
etarypolicyondownsideriskstoGDPgrowthintheeuroarea.Usingidenti?edhigh-frequencyshocksinagrowth-at-riskframework,weshowthatmonetarypolicyhasahigherimpactondownsiderisksintheshorttermthaninthemediumterm.However,thisresultfortheeuroareaaveragehidessigni?cantheterogeneityacrosscountries.Ineconomieswithweakinstitutionalquality,medium-termgrowthrisksincreasesubstan-tiallyfollowingcontractionarymonetarypolicyshocks.Incontrast,theserisksremainrelativelystableincountrieswithhighinstitutionalquality.Thissuggeststhatimprove-mentsininstitutionalqualitycouldsigni?cantlyenhanceeuroareacountries’economicresilienceandsupportthesmoothtransmissionofmonetarypolicy.
Keywords:Euroarea,growth-at-risk,institutionalquality,monetarypolicytransmissionJELClassi?cation:C23,E52,F45,G28,O43
ECBWorkingPaperSeriesNo29892
Non-technicalsummary
25yearsaftertheintroductionoftheeuro,theeuroareacountriesarestillheterogeneousintermsofeconomicstructures.Thisisparticularlyevidentinstandardindicatorsofinstitu-tionalquality,suchastheWorldBank’sWorldGovernanceIndicators.Whilesomeeuroareacountriesareclosetotheglobalfrontier,othersarelagging.
Itiswidelyrecognisedthatcross-countrydifferencesininstitutionsandothereconomicstructureshaveimportantimplicationsforthetransmissionoftheECB’smonetarypolicy.Inparticular,structuralheterogeneitycancontributetocross-countrydifferencesintheresponsesofoutputandin?ationtomonetarypolicychanges.This,inturn,maycontributetorealornominaldivergences,makingitlesslikelythatthecommonmonetarypolicyisalignedwitheconomicconditionsineachindividualeuroareacountry.
Inthispaper,weexploreifdifferencesininstitutionalqualityacrosseuroareacountriesalsomatterfortailrisksintheaftermathofmonetarypolicyshocks.Whenpolicymakersconsidertheimpactofmonetarypolicychangesonfutureeconomicactivity,theytypicallyfocusonthemostlikelyscenario,i.e.themeanofthe(conditional)distributionoffutureGDPgrowth.However,centralbanksalsoincreasinglyanalysetherisksaroundthecentralprojectioninquantitativeterms.Againstthisbackdrop,ourpaperaimstoshedlightontheroleofinstitutionalfactorsinshapingdownsideriskstoGDPgrowthintheaftermathofmonetarypolicyshocksinaheterogeneousmonetaryunion.
Weusethegrowth-at-riskframeworkproposedby
Adrian,BoyarchenkoandGiannone
(2019)toestimatedownsideriskstofutureGDPgrowthwithpanelquantileregressions
.Inlinewiththeliterature,wede?negrowth-at-riskasthelowestdecileofthedistributionofpredictedGDPgrowth.Toestimatetheimpactofmonetarypolicyshocksongrowth-at-risk,wefollowthemethodproposedby
Loria,MatthesandZhang
(2024)
.Wesplitoursampleintoeuroareacountrieswithhigherandlowerinstitutionalquality,respectively,asmeasuredbytheWorldGovernanceIndicators.
We?ndthatmonetarypolicyhasahigherimpactondownsideriskstoGDPgrowthintheshorttermthaninthemediumterm.However,thishidessigni?cantheterogeneityacrosscountries.Ineconomieswithweakinstitutionalquality,medium-termgrowthrisksincreasesubstantiallyfollowingcontractionarymonetarypolicyshocks.Incontrast,theserisksremainrelativelystableincountrieswithhighinstitutionalquality.Interestingly,expansionarymon-etarypolicyshockshaveamilderandmoresymmetricimpactthancontractionaryshocks,bothacrosscountriesandquantilesoftheconditionalgrowthdistribution.Wheninspectingthetransmissionchannels,we?ndthatmedium-termrisksincreasethroughtheimpactofmonetarypolicyshocksonmacro-?nancialvulnerabilities,inparticularincountrieswithlowinstitutionalquality.
Theseresultshaveimportantpolicyimplications.First,ourempirical?ndingssuggestthatimprovinginstitutionalqualitycanstrengthentheeconomicresilienceofeuroareacoun-tries.Insofar,wecomplementexistingstudiesthatemphasisetheroleofbankcapitalisation,macroprudentialmeasuresormonetarypolicyinstrumentsinsteeringgrowth-at-risk.Sec-ond,our?ndingsindicatethatupwardinstitutionalconvergencewouldsupportthesmooth
ECBWorkingPaperSeriesNo29893
transmissionofmonetarypolicyintheeuroareabyensuringalesspronouncedandmorehomogeneousresponseofmedium-termgrowth-at-risktomonetarypolicytightening.
ECBWorkingPaperSeriesNo29894
1Introduction
25yearsaftertheintroductionoftheeuro,theeuroareacountriesarestillheterogeneousintermsofeconomicstructures.Thisisparticularlyevidentinstandardindicatorsofinsti-tutionalquality,suchastheWorldBank’sWorldGovernanceIndicators(WGI).Whilesomeeuroareacountriesareclosetotheglobalfrontier,othersarelagging.
Itiswidelyrecognisedthatcross-countrydifferencesininstitutionsandothereconomicstructureshaveimportantimplicationsforthetransmissionoftheECB’smonetarypolicy.Inparticular,structuralheterogeneitycancontributetocross-countrydifferencesinthere-sponsesofoutputandin?ationtomonetarypolicydecisions(
Barigozzi,ContiandLuciani,
2014;
Ciccarelli,MaddaloniandPeydró,
2013;
Corsetti,DuarteandMann,
2022;
Slacalek,Tris-
taniandViolante,
2020
)
.1
Forinstance,economieswithstronginstitutionalqualityarelikelytobelessdependentonshort-term?nancialin?owsfromabroadandmaythereforebelessvulnerabletotightening?nancialconditionsthancountrieswithweakerinstitutionalback-grounds.Suchcross-countryheterogeneitymaycontributetorealornominaldivergences,makingitlesslikelythatthecommonmonetarypolicyisalignedwitheconomicconditionsineachindividualeuroareacountry.
Inthispaper,weexploreifdifferencesininstitutionalqualityacrosseuroareacountriesalsomatterfortailrisksintheaftermathofmonetarypolicyshocks.Whenpolicymakersconsidertheimpactofmonetarypolicychangesonfutureeconomicactivity,theytypicallyfocusonthemostlikelyscenario,i.e.themeanofthe(conditional)distributionoffutureGDPgrowth.However,centralbanksalsoincreasinglyanalysetherisksaroundthecentralprojectioninquantitativeterms.Againstthisbackdrop,ourpaperaimstoshedlightontheroleofinstitutionalfactorsinshapingdownsideriskstoGDPgrowthintheaftermathofmonetarypolicyshocksinaheterogeneousmonetaryunion.
TocapturedownsideriskstofutureGDPgrowth,weusethegrowth-at-risk(GaR)frame-workproposedby
Adrian,BoyarchenkoandGiannone
(2019)
.Inlinewiththeliterature(see,e.g.,
FigueresandJaroci′nski
(2020)and
G?chter,GeigerandHasler
(2023)),wede?neGaRas
thelowestdecileofthedistributionofpredictedGDPgrowth,foragiventimehorizon,con-ditionalonasetofcurrenteconomicand?nancialconditions.OurGaRmeasureisderivedfromapanelquantileregression,usingtheestimatordevelopedby
MachadoandSantosSilva
(2019)
.Thesamplecoversall20euroareacountriesovertheperiod1999Q1-2019Q4.
Inasecondstep,weestimatethecausalimpactofmonetarypolicyshocksonGaRfol-lowingthemethodproposedby
Loria,MatthesandZhang
(2024)
.2
Monetarypolicyshocksareconstructedbasedonhigh-frequencymovementsinassetpricesaroundECBpolicyan-nouncementsandcleanedfromcentralbankinformationeffects(
Gürkaynak,SackandSwan-
1Takingabroaderperspective,Sondermann(2018)showsthattheoutputlosssufferedbyeuroareacountries
withweakereconomicstructuresinresponsetoacommonshock(notnecessarilyamonetarypolicyshock)ison
averagetwiceaslargeastheoutputlossofthebestperformers.
2WhiletheGaRliteraturetypicallydoesnotidentifythecausalimpactofstructuralshocksonGaR,Loria,
MatthesandZhang(2024)showthatcontractionaryUSmonetarypolicyshocksareamongthestructuralshocks
whichdisproportionatelyincreasetheriskoflargedownturnsintheUnitedStates.Beuteletal.(2022)showthat
theseshockscauseelevateddownsideriskstogrowtharoundtheworld.Wefollowthisapproachandestablish
causalitybetweenmonetarypolicyshocksandGaRintheeuroarea.
ECBWorkingPaperSeriesNo29895
son
(2005);
Altavillaetal.
(2019);
Jaroci′nskiandKaradi
(2020))
.WeusetheWorldBank’sWGIdata(
KaufmannandKraay,
2023)tosplitthesampleintoeuroareacountrieswithweakerand
strongerinstitutionalquality,respectively.ThisallowsustostudydifferencesintheimpulseresponsesofGaRtomonetarypolicyshocksbetweenthesetwocountrygroups.
We?ndthatmonetarypolicyhasahigherimpactondownsideriskstoGDPgrowthintheshorttermthaninthemediumterm.However,thisaggregateresulthidessigni?canthetero-geneityacrosscountries.Ineconomieswithweakinstitutionalquality,medium-termgrowthrisksincreasesubstantiallyfollowingcontractionarymonetarypolicyshocks.Incontrast,theserisksremainrelativelystableincountrieswithhighinstitutionalquality.Interestingly,expansionarymonetarypolicyshockshaveamoresymmetricimpactthancontractionaryshocks,bothacrosscountriesandquantilesoftheconditionalgrowthdistribution.
Inspectingthetransmissionchannels,we?ndthatmedium-termrisksincreasethroughtheimpactthatmonetarypolicyshockshaveonvariablescapturingmacro-?nancialvulner-abilities—andthischannelismuchmorepronouncedforcountrieswithlowinstitutionalquality.Ourmainresultsarerobustto(i)usingdifferentindicatorscapturingmedium-termriskstoGDPgrowthwhenestimatingGaR,(ii)employingdifferentindicatorsofinstitutionalquality,(iii)accountingforcross-countrydifferencesinincomelevelsand(iv)alteringeitherthecountriesorthetimeperiodcoveredinthesample.
Ourresultshaveimportantpolicyimplications.First,ourempirical?ndingssuggestthatimprovinginstitutionalqualitycanstrengthentheeconomicresilienceofeuroareacountries.Insofar,wecomplementexistingstudiesthatemphasisetheroleofbankcapitalisation(
Aik-
manetal.,
2021),macroprudentialmeasuresormonetarypolicyinstruments(Galán,
2024)
insteeringGaR.Second,our?ndingsindicatethatinstitutionalconvergencewouldsupportthesmoothtransmissionofmonetarypolicybyensuringamorehomogeneousresponseofthetailofthemedium-termgrowthdistributiontomonetarypolicytightening.Thisaddsanimportantdimensiontothediscussionof?nancialstabilityconsiderationsintheconductofmonetarypolicy(
Bochmannetal.,
2023
).
Theremainderofthepaperisstructuredasfollows.Section
2
outlinesthemethodologyemployedtoestimateGaRandpresentstheresultingestimates.InSection
3
,wecomputeimpulseresponsesoftheGaRmeasurestomonetarypolicyshocksandexploretheroleofinstitutionalqualityinexplainingthecross-countryheterogeneityintheseimpulseresponses.Section
4
providesanoverviewofourrobustnesschecksandSection
5
concludes.
2Growth-at-riskandmacro-?nancialvulnerabilities
WestartouranalysisbyestimatingGaRoverdifferenttimehorizonsinasampleofeuroareacountries.Thisexerciseillustratestherelativeimportanceofdifferentmacro-?nancialvariablesfordownsideriskstogrowth,dependingonthetimehorizonconsidered.Weshowthatshort-termGaRestimatesforeuroareacountriesaremostlyassociatedwith?nancialstressindicators,whilemedium-termriskstogrowtharenotstronglycorrelatedwithcurrent?nancialstress.Instead,onlymacrovulnerabilitiesmatterformedium-termGaR.Our?nd-ingsthuspointtotwodifferentchannelsthroughwhichdownsideriskstoGDPgrowthmay
ECBWorkingPaperSeriesNo29896
materialise.
Buildingonour?rst-stageregression,Section
3
willexploretheroleofinstitutionalqualityindeterminingtheresponseofGaRtomonetarypolicyshocks.Thistwo-stepapproach,asfurtherexplainedinmoredetailinSection
3
,enablesustofocusontheeffectsofmonetarypolicythataretransmittedviatheconditioningvariablesinour?rst-stageregression.ThemethodologytherebyallowsustoidentifythechannelsthroughwhichinstitutionalfactorsshapetheimpactofmonetarypolicyonGaR.
2.1Methodologyanddata
Following
Adrianetal.
(2022),weestimatepanelquantileregressionsmakinguseoflocal
projectionmethods(
Jordà,
2005)sothatweareabletoestimatetheconditionalforecastof
GDPgrowthbothfortheshortterm(de?nedas4quartersahead)andthemediumandlongerterm(8and12quartersahead,respectively).Toestimateourmodel,wefollow
Machadoand
SantosSilva
(2019)whoderiveanestimatorofconditionalquantilesfromthecombinationof
alocationandascalefunction,whichisparticularlyusefulinapanelsettingwithcountry?xedeffects
.3
Following
MachadoandSantosSilva
(2019),theconditionalpredicteddistributionoffu
-tureGDPgrowth,foragivenquantileofDyi,t+h,willbegivenby
q,t,τ=(Dyi,t+hjxi,t)=i,τ+xi,t,τ∈(0,1).(1)
Inlinewithpreviousstudies(see,e.g.,
FigueresandJaroci′nski
(2020)and
G?chter,Geiger
andHasler
(2023)),weconsiderthe10thpercentileofpredictedGDPgrowthtobeourGaR
measure.Wede?neDyit+hastheannualisedaveragegrowthrateofGDPbetweenquarterst
andt+h:Dyi,t+h=
Thevariablesincludedinxi,treferto?nancialstressindicatorsandmacro-?nancialvulner-abilities,whichhavebeenshowntocontainthemostrelevantinformationformedium-termGaRintheeuroarea(
Lang,RusnákandGreiwe,
2023)
.FinancialstressiscapturedbytheCountryLevelIndexofFinancialStress(CLIFS),introducedby
Duprey,KlausandPeltonen
(2017)basedon
Hollo,KremerandLoDuca
(2012)
.TheCLIFScoversmeasuresofstressinequity,bondandforeignexchangemarketsandtakesco-movementsinthesemarketsegmentsintoaccount.Turningtoindicatorsofmacro-?nancialvulnerabilities,andascommonintheGaRliterature,weincludeameasureofexcessivecreditgrowthoverthepasttwoyears.ForthatwerelyontheBIScredit-to-GDPgapandcalculateitscumulativedeviationoverthepre-vious8quartersfromitslong-runtrend.BoththeCLIFSandthecumulativedeviationfromthetrendofthecredit-to-GDPgaparestandardisedbytheircountry-speci?cstandarddevia-tions.Wealsoincludethegrowthrateinhousepricesoverthepast8quarters.Inaddition,tocapturebothpublicandexternalsectorvulnerabilitiesweincludethecyclically-adjustedbud-
3Thisapproachallowsthecountry?xedeffectstovaryacrossquantiles,suchthatαi,τ三αi+δiq(τ).Thiscontrasts,forexample,withthemethodproposedby
Canay
(2011)whichrestrictscountry?xedeffectstobe
invariantacrossquantiles.
4ForIreland,weusethemodi?eddomesticdemandindicatorreleasedbythenationalstatisticalauthority.ComparedtoGDP,itislessaffectedbydatadistortionsarisingfromtheactivitiesofmultinationalenterprises.
ECBWorkingPaperSeriesNo29897
getbalanceandtheseasonally-adjustedcurrentaccountbalance.Finally,theeffectofoverallcurrenteconomicconditionsonfuturedownsiderisksiscapturedbyincludingeachcountry’sGDPasacontrolvariable,asiscommonintheliterature.
Oursamplecoversalleuroareacountriesinthetimeperiodfrom1999Q1to2019Q4,al-thoughsomevariablesarenotavailableforthefullobservationperiod
.5
GDPgrowthratesarehighlyleft-skewedduringthisperiodacrosscountriesasshowninAppendix
A.1.
Moreover,theunconditionallowerpercentilesofGDPgrowthshowsubstantialheterogeneityacrosscountries,muchmoresothanthemedianoftheunconditionalGDPgrowthdistribution(Fig-ure
8
).Inotherwords,someeuroareacountriesappeartobemoresusceptibletoweakgrowthoutcomesthanothers.Thisisdespitethefactthattheeuroareacountrieshavebeensubjecttoanumberofcommonshocksoverthisperiod.Thecross-countryheterogeneitythussuggestsaroleforcountrycharacteristicsinexacerbatingdownsideriskstogrowth.
2.2GaRestimates
WestartdocumentingourresultsbyshowingGaRestimatesfordifferenttimehorizons,to-getherwiththetimeseriesoftheircross-countryaverages
.6
Figure
1
suggeststhat,inlinewith
Adrian,BoyarchenkoandGiannone
(2019)and
Adrianetal.
(2022),thepredictedlower
tailofthegrowthdistributionismuchmorevolatilethanhigherquantiles
.7
Thismeansthatdownsideriskstogrowthvarymuchmoreovertimethanupsiderisks.Ourframeworkalsoappearstogiveanearlypredictionofthedownturnsandtroughsoftheglobal?nancialcri-sisin2008.Althoughthe4-quarter-aheadGaRmeasuredoesabetterjobinthisregard(seeAppendix
A.3
),itisstillinterestingthatthemedium-termmodelcansignaltheincreasingprobabilityofadownturnaroundtwoyearsbeforeitmaterialised.
Table
1
presentstheestimatedcoef?cientsforthequantileregression,fordifferenttimehorizons
.8
Asnotedabove,ourpreferredmeasureofGaRisthe10thpercentileofpredictedGDPgrowth.Thereisastrongassociationbetween?nancialconditionsandshort-termriskstogrowth.Atighteningof?nancialconditions,re?ectedinanincreaseintheCLIFS,isasigni?cantpredictoroflargemacroeconomicdownturnsoverafour-quarterhorizon.Thein-formationcontentof?nancialstressregardingriskstogrowthdecreasesoverlongerhorizons(eightandtwelvequarters)re?ectingthefactthat?nancialconditionsmayremainbuoyantuntilshortlybeforerisksmaterialise(
IMF,
2017
).Incontrast,incorporatinginformationonthecredit-to-GDPgapdoesnotaddexplanatorypowertoGaRintheshorttermbuthelpstocaptureriskstogrowthoverthemedium-andlonger-term(eightandtwelvequarters).Strongrisesinhouseprices,negativebudgetbalancesandnegativecurrentaccountbalancesalsosignalheightenedtailriskstogrowth,especiallyoverthelongerterm(or,atleast,insim-ilarmagnitudesforshorterandlongerhorizons,asopposedtoCLIFS).These?ndingsonthe
5InAppendix
A.4.2
weshowthatthecoef?cientsdonotsigni?cantlychangeifweextendthesampletoincludetheCOVID-19periodandthesubsequentyears.
6SeethefootnoteofFigure
1
foranexplanationofhowweobtainthisseries.
7Sinceweareinterestedincross-countryheterogeneityandtheroleofinstitutionalcharacteristicsinthetransmissionofmonetarypolicy,wefocusonmedium-termGaR.Figure
1
showsthecross-countryaverageof8-quarter-aheadGaR.InAppendix
A.3
weshowthesame?gureforothertimehorizons.
8Inappendix
A.4
weshowthatthesecoef?cientsareverysimilaracrossasetofdifferentspeci?cations.Additionally,inappendix
A.2
weshowthecoef?cientsforotherquantilesofthedistribution.
ECBWorkingPaperSeriesNo29898
Figure1:Predicted10thpercentile(GaR),medianand90thpercentileof8-quarter-aheadGDPgrowthandrealisedGDPgrowth
%
8
6
4
2
0
-2
-4
-6
-8
-10
-12
10thQuantile50thQuantile90thQuantileRealized
Mean
SD
10thperc.(GaR)-1.081.54Median1.770.88
90thperc.3.900.50
Realized1.932.48
2000q12005q12010q12015q12020q1
Quarter
Notes:Thepredicted8-quarter-ahead10thpercentile,medianand90thpercentileoftheannualisedaveragegrowthrateofGDParethecross-countryaveragesofeachcountryprediction(countryspeci?cpredictionsareobtainedwiththeestimatesofthepanelmodelofequation
1)
.Onceaveragedbyquarter,theseseriesareshiftedforwardby8quarterssuchthatthetimingofthepredictedgrowthrateandtherealisedoneforagivenquartermatch.
termstructureofGaRareinlinewithprevious?ndingsintheliterature,suchas
Adrianetal.
(2022)andinparticular
Lang,RusnákandGreiwe
(2023)whoshowthatonlymacro-?nancial
vulnerabilityindicatorsre?ectingcreditandassetpriceimbalancescontaininformationaboutmedium-termGaRintheeuroarea.Therefore,weinterpretthis?ndingasevidenceoftwokeychannelsbehindshort-termandmedium-termGaR:ashort-termchannelconnectedwith?nancialstressandamedium-termchannellinkedtomacro-?nancialvulnerabilities.
Itisalsointerestingtoanalysethetimevariationinthecontributionstodownsiderisksfromeachexplanatoryvariable.Figure
2
presentsthecontributionstoGaRfordifferenthori-zons.Figure
2a
illustratesthatweak?nancialandeconomicconditionsmakethelargestcontributiontodownsiderisksintheshort-term.Thereisasigni?cantcontributionofCLIFSaroundtheglobal?nancialcrisis,asonewouldexpect.However,Figure
2b
showsthatmacroe-conomicvulnerabilitiesweighstronglyonthepredictionofGaRoverlongerhorizons.Inpar-ticular,weakpublic?nancescontributedstronglytothelower10thpercentileofconditionalgrowtharoundthesovereigndebtcrisis.Figure
2c
con?rmstheimportanceofmacro-?nancialvulnerabilitiesforGaRinthelongertermalsooverahorizonof12quarters.Atthesametime,thecontributionof?nancialstresstolonger-termriskstogrowthisnegligible.
ECBWorkingPaperSeriesNo29899
Figure2:AveragecontributionstoGaRforecast,h=4,h=8andh=12quartersahead
PercentagePoints
2
0
-2
-4
-6
-8
2000q12005q12010q12015q12020q1
(a)h=4
PercentagePoints
2
0
-2
-4
2005q1
2000q1
2010q1
2015q1
2020q1
(b)h=8
PercentagePoints
2
0
-2
-4
2000q1
2005q1
2010q1
2015q1
2020q1
二GDP
二CurrentAccount
Credit-to-GDPGapHousePrices
GaR
二CLIFS
BudgetBalance
(c)h=12
Notes:GaRreferstothe10thpercentileofpredictedGDPgrowth.ThepredictedGaRmeasuresplottedarethecross-countryaveragesoftheindividualcountrypredictions(thatwereobtainedusingmodel
1
),netofthecountry?xedeffectandthecoef?cientofthedummyforwhenthecountryadoptedtheeuro.
ECBWorkingPaperSeriesNo298910
Table1:Quantileregressioncoef?cientsfordifferenthorizonsofGaR
h=4
h=8
h=12
CLIFS
-0.780***
-0.331
-0.176*
(0.339)
(0.429)
(0.136)
GDP
0.318***
0.049
-0.004
(0.158)
(0.195)
(0.054)
Credit-to-GDPGap
-0.255
-0.525*
-0.435***
(0.316)
(0.497)
(0.164)
HousePrices
-0.040*
-0.039
-0.031***
(0.035)
(0.050)
(0.015)
BudgetBalance
0.441***
0.438**
0.314***
(0.175)
(0.262)
(0.088)
CurrentAccount
0.279***
0.228*
0.247***
(0.094)
(0.142)
(0.048)
Observations
1179
1103
1027
Notes:GaRreferstothe10thpercentileofpredictedGDPgrowth.Standarderrorsinparenthesis.Quantileregressionwithcountry?xedeffectsandcontrollingforthetimingofeuroadoption.Starsindicatesigni?canceat*p<0.32,**p<0.10,***p<0.05.
3Impactofmonetarypolicyshocksongrowth-at-risk
ThissectionlooksattheimpactofmonetarypolicyshocksonGaRinaheterogeneousmon-etaryunion.Morespeci?cally,weanalysetheextenttowhichcross-countrydifferencesininstitutionalqualityaffecttheresponseofGaRtoamonetarypolicyshockintheeuroarea.Indoingso,wetrytodisentangletherelevanceof?nancialconditionsandmacroeconomicvulnerabilities,respectively,astransmissionchannels.Inaddition,weexplorepossiblenon-linearitiesinthesetransmissionchannelsdependingonwhetherthemonetarypolicyshockiscontractionaryorexpansionary.
3.1Methodologyanddata
Following
Loria,MatthesandZhang
(2024),weassesstheresponseoftheGaRvaluespre
-
dictedinthe?rst-stageregression(seeSection
2.1
)tomonetarypolicyshocks.De?ningq,t+s,τ
as
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