A ílio, Luccas Assis
A icle
T ansmission and impac o s ock ma ke shocks on he
wo ld economy
Cen al Bank Re iew (CBR)
P o ided in Coope a ion wi h:
Cen al Bank o The Republic o Tu key, Anka a
Sugges ed Ci a ion: A ílio, Luccas Assis (2024) : T ansmission and impac o s ock ma ke shocks on
he wo ld economy, Cen al Bank Re iew (CBR), ISSN 1303-0701, Else ie , Ams e dam, Vol. 24, Iss.
1, pp. 1-24,
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T ansmission and impac o s ock ma ke shocks on he wo ld economy
Luccas Assis A ílio
Fede al Uni e si y o Ou o P e o, Rua do Ca e e, 166, Cen o, Ma iana, MG, B azil
ARTICLE INFO
JEL classi ica ion:
G17
E32
E44
F37
Keywo ds:
S ock ma ke
Fluc ua ion
Eme ging economies
Ad anced economies
Bila e al ade
ABSTRACT
In his s udy, we examine s ock ma ke shocks using a Global Vec o Au o eg essi e (GVAR) model encompassing
26 coun ies om Janua y 1999 o June 2022. Ou indings e eal ha i) shocks o igina ing om ad anced
economies (AD) exhibi g ea e pe sis ence in gene a ing luc ua ions compa ed o shocks om eme ging ma ke
economies (EME); ii) nega i e s ock ma ke shocks a e associa ed wi h de alua ions o domes ic cu encies,
endogenous esponses o mone a y policy, and global ecession. Ou es ima es sugges ha s ock ma ke luc-
ua ions ha e signi ican po en ial o des abilize in e na ional ma ke s, wi h con agion sp eading apidly. Ou
app oach con ibu es o exis ing li e a u e by cons uc ing a comp ehensi e model o he wo ld economy,
simula ing agg ega e shocks, and assessing he ele ance o global shocks based on he le el o economic
de elopmen .
1. In oduc ion
In he cu en cen u y, wo cha ac e is ics o ma ke economies s and
ou : he i s is a signi ican ade and inancial in e dependence be-
ween economies; he second, pa icula ly e iden du ing c i ical e en s
such as inancial c ises, is ha domes ic shocks in majo economies can
lead o p o ound luc ua ions in he wo ld economy. The challenges ha
a ise in ol e modeling he in e dependences be ween economies, un-
de s anding spillo e e ec s, examining he domes ic esponses o in-
di idual economies, and dis inguishing pa e ns acco ding o he le el o
economic de elopmen .
The aim o his a icle is o con ibu e o his esea ch a ea. We
examine he dissemina ion o s ock ma ke shocks om ad anced
economies and eme ging economies in a sys em o 26 economies. We
analyze he ansmission channels h ough which hese shocks p opa-
ga e and examine domes ic esponses o hem.
We employ he GVAR model o add ess ou objec i es. This model
enables us o cons uc a sys em encompassing economies a a ious
le els o de elopmen . By using an explici economic in eg a ion a i-
able o connec egions, he GVAR inco po a es spillo e e ec s and
cons uc s p oxies o he in e na ional economy h ough domes ic
a iables. Thus, he GVAR inco po a es ea u es ha allow us o cap u e
spillo e e ec s, o mula e agg ega e shocks, and ind he e ogenei ies in
he esul s.
Gi en ha ou sample comp ises se e al economies, an al e na i e
model is he Panel Vec o Au o eg essi e (PVAR). Howe e , he PVAR
o e s a gene al esponse o shocks, lacking he abili y o show indi-
idual esponses. Consequen ly, he e ogenei ies in he esul s would be
absen . Ano he limi a ion lies in cap u ing spillo e e ec s. In he
GVAR, we cons uc a Vec o Au o eg essi e wi h Exogenous Va iable
(VARX) o each economy. This app oach allows economies o eac o
shocks, gene a ing eedback e ec s ha in luence o he economies.
While he class o VAR models was an op ion, VAR models ypically
ocus on a single economy, elying on p oxies o ep esen he wo ld
economy. Consequen ly, hese models may mispeci y spillo e e ec s. In
con as , GVAR, by cons uc ing he domes ic dynamics o each econ-
omy, cap u es spillo e e ec s h ough eedback mechanisms and in-
e ac ions be ween domes ic and o eign a iables.
The esul s indica e ha nega i e s ock ma ke shocks om AD
pe sis en ly impac he domes ic ma ke s o all economies. The alues o
domes ic s ock ma ke s dec ease o wo yea s ollowing he shock,
ma ked by capi al ou lows causing dep ecia ions o domes ic cu encies
and a g adual decline in sho - e m in e es a es. Consequen ly, he
es ima es depic episodes o ecession, accompanied by a widesp ead
decline in GDP. Al hough we obse e simila luc ua ions when shocks
o igina e om EME, hey a e sho -li ed, wi h s ock ma ke s showing
s a is ically signi ican esponses o only ou mon hs. Thus, we ind
e idence ha shocks om AD lead o meaning ul and endu ing luc u-
a ions compa ed o EME shocks.
The li e a u e on s ock ma ke shocks, o ecas s, and ansmission
Pee e iew unde esponsibili y o he Cen al Bank o he Republic o Tu key.
E-mail add ess: [email p o ec ed].
Con en s lis s a ailable a ScienceDi ec
Cen al Bank Re iew
jou nal homepage: www.jou nals.else ie .com/cen al-bank- e iew/
h ps://doi.o g/10.1016/j.cb e .2024.100149
Recei ed 22 June 2023; Recei ed in e ised o m 1 Decembe 2023; Accep ed 28 Feb ua y 2024
Cen al Bank Re iew 24 (2024) 100149
2
channels ypically employs Gene alized Au o Reg essi e Condi ional
He e oskedas ici y (GARCH), GARCH-MIDAS, Vec o Au o eg essi e
(VAR), and panel da a models (F anses and Dijk, 1996; Soydemi , 2000;
Cuad o-S´
aez e al., 2009; Song e al., 2022). As men ioned ea lie , we
op o he GVAR, which inco po a es ea u es acili a ing he c ea ion o
a ich and cohe en scena io, encompassing spillo e e ec s, domes ic
adjus men s, and agg ega e analysis in acco dance wi h he esea che s’
c i e ia.
One o he a icles ha inspi ed ou esea ch was Soydemi (2000).
In his s udy, he au ho employed a VAR wi h ou a iables, ep e-
sen ing a de eloped economy ( he U.S.) and h ee EMEs (B azil,
A gen ina, and Mexico), o examine s ock ma ke mo emen s in bo h
de eloped and eme ging economies. We ex end his esea ch by wo king
wi h a sample o 26 economies, inco po a ing ansmission channels
(exchange a e and in e es a e) and eal sec o a iables (GDP). In
con as , Soydemi (2000) did no include any channels o eal sec o
a iables. Addi ionally, while Soydemi a ibu es a signi ican ole o
ade in explaining his esul s, VAR models do no accoun o ade in
hei es ima es. To add ess his, we use he GVAR, which inco po a es
bila e al ade o connec egions.
Pesa an e al. (2004) examined U.S. s ock ma ke shocks using a
GVAR model encompassing 25 economies o e he pe iod om 1979Q1
o 1999Q1. The au ho s ocused hei analysis on nine egions: he U.S.,
he U.K., Ge many, F ance, I aly, Wes e n Eu ope, Sou heas Asia,
Japan, and La in Ame ica. We complemen his s udy by i) upda ing he
analysis pe iod om 1999 o 2022, ii) using mon hly da a ins ead o
qua e ly da a, iii) indi idually analyzing he esponses o each econ-
omy, p o iding mo e de ailed insigh s in o he eac ions o s ock ma ke
shocks and cap u ing he e ogenei ies, i ) es ing bila e al inancial lows
o connec he economies (Pesa an e al. (2004) adop ed bila e al ade),
and ) e alua ing he impac o s ock ma ke shocks based on he le el o
economic de elopmen .
A icles on business cycles and luc ua ions ypically ocus on speci ic
coun ies, egions, o g oups o economies (Dees e al., 2007; Gup a and
Kabundi, 2010; Bou i e al., 2020; Camacho and Palmie i, 2021). In ou
s udy, we in es iga e shocks om de elopmen g oups (ADs and EMEs)
and depic esponses om all egions, p o iding a comp ehensi e iew o
domes ic ma ke eac ions o hese shocks. While Papanyan (2010)
concen a ed on ansmission shocks om he U.S., Eu ope, and Japan,
and Dees e al. (2007) explo ed he consequences o U.S. shocks on he
Eu ozone, we ad ance bo h s udies by inc easing he numbe o shock
sou ces and illus a ing domes ic adjus men s om 19 egions. Ou
app oach and s a egy enable us o de ec idiosync a ic mo emen s based
on he geog aphy o he shock, ansmission channels, and he in luence
o bila e al ade (and inancial low), enhancing ou unde s anding o
domes ic esponses.
We o ganize he a icle as ollows: Sec ion 2 p o ides he li e a u e
e iew. Sec ion 3 ou lines he GVAR and da a. Sec ion 4 p esen s he
econome ic esul s. Finally, Sec ion 5 concludes he a icle wi h addi-
ional commen s.
2. Li e a u e e iew
Balcila e al. (2020) analyzed he impac o egional and global s ock
ma ke shocks on sa e-ha en asse s using a wo- ac o , egime-based
ola ili y spillo e model. An ad an age o his s udy is i s inco po a ion
o he domes ic dynamics o each economy, p o iding domes ic e-
sponses o s ock ma ke shocks. The esul s indica ed ha s ock ma ke
shocks p omo e changes in po olios and di e si ica ion. Fu he mo e,
he au ho s emphasized he signi icance o adop ing dynamic models, as
s a ic models migh lead o biased esponses.
Chudik and F a zsche (2011) explo ed he ansmission channels o
he 2008 inancial c isis in a GVAR. The au ho s included inancial
a iables such as money ma ke a es, s ock ma ke s, he VIX index, and
he TED sp ead. In hei GVAR model encompassing 26 economies, hei
econome ic s a egy allowed hem o assess he impo ance o liquidi y
and isk in comp ehending he impac o he inancial c isis on bo h
ad anced and eme ging economies. Simila o he indings o Balcila
e al. (2020), he esul s depic ed he e ogenei ies: o ad anced econo-
mies, he liquidi y channel explained he ansmission o he c isis, while
o eme ging economies, he eal side o he economy played a mo e
signi ican ole.
Ano he GVAR app oach o explo e he impac o s ock ma ke
shocks is p esen ed by Dees e al. (2007). The au ho s s udied how a
nega i e U.S. s ock ma ke shock a ec s bo h he U.S. and he Eu ozone.
The esul s indica ed esponses in c edi ma ke s, cu ency ma ke s,
s ock ma ke s, and he eal sec o o his shock. Consequen ly, Dees e al.
(2007) a gued ha hese indings sugges linkages be ween hese
economies, a concep he model inco po a es by adop ing bila e al ade
o connec economies. Bila e al ade also aids in cons uc ing he
ulne abili y be ween economies, wi h he o eign a iables (as
desc ibed in Sec ion 3) playing a c ucial ole.
Building upon hese s udies, we expand ou scope by inco po a ing
se e al coun ies o simula e he wo ld economy. We include p oxies o
bo h he inancial and eal sec o s o ho oughly in es iga e he impac
o s ock ma ke shocks. Simila o Dees e al. (2007), we adop bila e al
ade as a connec ing a iable. Howe e , we go a s ep u he by es ing
ou main esul s using bila e al inancial low o link economies.
While Chudik and F a zsche (2011) and Dees e al. (2007) did no
dis inguish be ween he esponses o coun ies based on economic
de elopmen , we add ess his aspec by implemen ing wo shocks: one
o igina ing om ad anced economies and ano he om eme ging
economies. This app oach enables us o explo e how economies espond
acco ding o he sou ce o he shock.
Typically, GVAR s udies u ilize he Gene alized Impulse Response
Func ion (GIRF) o examine he impac o local shocks on he sys em.
Dees e al. (2007) highligh ed he challenge o iden i ying shocks in
GVAR due o he inclusion o nume ous economies and a iables. To
add ess his issue, GIRFs do no iden i y shocks bu ins ead o e ans-
mission channels o hem. Chudik and F a zsche (2011) employed
GIRFs in hei in es iga ion, and we also adop GIRFs in ou s udy.
Howe e , we enhance ou analysis by es ing ou esul s using he
S uc u al Gene alized Impulse Response Func ion (SGIRF). SGIRF
iden i ies shocks in one economy, usually he sou ce o he local shock,
he eby mi iga ing he iden i ica ion challenge associa ed wi h GIRFs.
S ock ma ke s a e also sensi i e o shocks. Lu e al. (2021) demon-
s a ed he impac o oil shocks on domes ic s ock ma ke s. Ha jo o e al.
(2021) iden i ied he nega i e e ec s o Co id-19 on global s ock ma -
ke s, pa icula ly impac ing eme ging ma ke economies. Addi ionally,
Ca aiani and Calin (2020) in es iga ed he impac o a mone a y policy
shock on ma ke bubbles in OECD economies using a ime- a ying
Bayesian Vec o Au o eg essi e (BVAR).
One limi a ion o hese s udies is hei adop ion o app oaches ha
ea economies as closed economies. Fo ins ance, Ca aiani and Calin
(2020) employed a BVAR, a me hod ha concen a es on one economy
and uses p oxies o ele an a iables o ep esen he wo ld economy.
The class o VAR models can mis ep esen spillo e e ec s because hey
do no accoun o he domes ic dynamics o indi idual economies o
employ in eg a ion a iables o link economies. In ou s udy, we po ay
he esponses o 19 egions o s ock ma ke shocks, including he e-
ac ions o domes ic s ock ma ke s. In con as o Dees e al. (2007), who
ocused on wo egions, we depic he esponses o all egions.
Wu (2020) and Qiu e al. (2022) conduc ed analyses on he in e-
g a ion o s ock ma ke s. In he o me pape , a VAR was employed o
ad ance he s udy, demons a ing ha common global ac o s a e he
p ima y d i e s o ma ke in eg a ion in Asian economies. In con as ,
he la e , unlike all s udies discussed in his sec ion, adop ed panel da a
co e ing he pe iod 1990–2017. Panel da a o e s ad an ages, such as
he inclusion o se e al economies and a iables (due o he annual
ime- equency), he abili y o handle samples wi h a long- ime span,
and he p o ision o gene al esponses o shocks. Howe e , akin o
c i icisms conce ning VAR models, panel da a does no accu a ely model
L.A. A ílio
Cen al Bank Re iew 24 (2024) 100149
3
spillo e e ec s. Ano he conce n ela es o gene al esponses o shocks.
In his case, he esul s do no indica e he e ogenei ies. In o he wo ds,
he au ho s canno dis inguish whe he he esponse o a shock is
a ibu able o a sizable economy o o se e al economies.
GVAR o e s ad an ages compa ed o panel da a because i allows us
o po ay indi idual esponses o shocks. This cha ac e is ic was
explo ed by Chudik and F a zsche (2011), al hough hey ocused solely
on inancial a iables wi hou including he eal sec o . In a simila ein,
Dees e al. (2007) concen a ed on he U.S. and Eu ozone. Ou s udy
akes a b oade pe spec i e by po aying he esponses o all egions,
ex ending he wo k o Chudik and F a zsche (2011) by inco po a ing
bo h inancial and eal a iables. Addi ionally, we go beyond by es ing
ade and inancial in eg a ion a iables, and compa ing he esul s o
GIRFs and SGIRFs. Mo eo e , we in oduce an inno a i e app oach by
cons uc ing shocks based on he le el o economic de elopmen . This
allows us o e alua e spillo e e ec s, inancial in eg a ion, and indi-
idual esponses o shocks based on economic de elopmen
cha ac e is ics.
3. Model and da a
The GVAR is a se o VARX connec ed by an economic in eg a ion
a iable, commonly bila e al ade. By u ilizing bila e al ade, he
GVAR can cons uc p oxies o he ex e nal en i onmen , ea ing each
egion as a small-open economy (A ílio e al., 2023). I is wo h no ing
ha no ably indus ialized economies, such as he U.S., ecei e a dis inc
ea men - a opic we del e in o la e in he a icle.
Ou p esen a ion is based on Pesa an e al. (2004). Equa ion (1)
p esen s a VARX (1,1) o a egion i in ime . The subsc ip i a ies om
0 o N+1 and om 1 o T. The ec o xi ep esen s he domes ic a -
iables o egion i; x∗
i is he ec o o o eign a iables o he egion i, he
p oxies o he ex e nal en i onmen ; ai0 is he cons an o egion i; ai1 is
he end e m;
ε
i is he ec o o idiosync a ic shocks.
xi =ai0+ai1 +Φixi, −1+Λi0x∗
i +Λi1x∗
i, −1+
ε
i .(1)
To calcula e he o eign a iables, we use wij, which ep esen s he
bila e al ade be ween egions i and j (as shown in Equa ion (2)). The
bila e al ade da a (sum o expo s and impo s) we e ob ained om
Mohaddes and Raissi (2020). Consequen ly, each VARX includes i s
co esponding o eign a iables, weigh ed by bila e al ade.
x∗
i =∑
N
j=0
wijxj .(2)
Equa ion (2) illus a es he economic in eg a ion be ween he e-
gions o he sys em. Pa icula ly, we use Equa ion (2) o build h ee
p oxies o he wo ld economy: o eign s ock ma ke , o eign in e es
a e, and o eign GDP. Equa ion (3) displays he ec o s o domes ic and
o eign a iables o egion i:
xi = (qi ,yi ,ei , i )
′
x∗
i =(q∗
i ,y∗
i , ∗
i )
′
.
(3)
In Equa ion (3), qi is he s ock ma ke , yi is GDP, ei is he exchange a e,
and i is he sho - e m in e es a e. The second ec o o Equa ion (3)
ep esen s o eign a iables (wo ld economy). The exchange a e is he
a io o he domes ic cu ency o he U.S. dolla ; he e o e, when
ega ding he U.S., he exchange a e only en e s he o eign a iable
ec o . This deno es ano he pa icula i y conce ning he U.S.; i would
be inco ec o ea he U.S. as a small open economy, so we ake a
pa simony app oach by including o eign a iables in i s ec o . Equa-
ion (4) illus a es he ea men o he U.S.:
xi = (qi ,yi , i )
′
x∗
i =(e∗
i )
′
.(4)
This adap a ion o he U.S. is a commonly applied p ac ice in GVAR
s udies (see Pesa an e al., 2004; Dees e al., 2007). In addi ion o ep-
esen ing he in e na ional economy, o eign a iables also con ibu e o
he long- e m s abiliza ion o he model. While he GVAR conside s he
sho - e m impac o domes ic a iables on o eign a iables, i aligns
wi h he a ibu es o small open economies whe e domes ic a iables
exhibi no long- e m in luence on o eign a iables. Howe e , omi ing
he long- e m e ec s o domes ic a iables en i ely is a s ong p oposi-
ion o in e na ionally ele an economies, such as he U.S. (A ílio
e al., 2023).
Rega ding ou da a sou ces, we ob ain he s ock ma ke index and
in la ion index – which we use o de la e some se ies – om he O ga-
niza ion o Economic Coope a ion and De elopmen (OECD). Exchange
a es we e sou ced om he In e na ional Financial S a is ics (IFS)/In-
e na ional Mone a y Fund (IMF), and GDP and sho - e m in e es a es
we e collec ed om he Fede al Rese e Bank o S . Louis (FRED). Ou
da a se comp ises 26 coun ies, co e ing he pe iod om Janua y 1999
o June 2022.
Fo seasonal adjus men , we use he X-11 me hod on he eal s ock
ma ke s, eal exchange a es, and GDP. De la ion o he s ock ma ke
was pe o med using he domes ic Consume P ice Index (CPI), 2015 =
100. Gi en ha he exchange a e ep esen s he a io o he domes ic
cu ency pe U.S. dolla , we employ he CPI o he domes ic coun y and
ha o he U.S. o de la e he ime se ies. All a iables, excep in e es
a es, we e loga i hmized.
We c ea e he Eu ozone by agg ega ing eigh economies (Aus ia,
Belgium, Finland, F ance, Ge many, I aly, he Ne he lands, and Spain)
based on he a e age GDP in PPP om 2014 o 2016. Consequen ly, ou
sys em includes 19 egions (18 coun ies and he Eu ozone). Table A in
he appendices p esen s he coun ies and egions o he model.
To de i e he GVAR, we c ea e wo new ec o s: zi = (xi ,x∗
i )
′
and
x = (x
′
0 ,x
′
1 ,x
′
2 ,x
′
3 ,…,x
′
N )
′
; he i s con ains domes ic and o eign
a iables, while he second is a domes ic global ec o in which each
e m deno es all domes ic a iables o each egion. Wi h hese ec o s,
we w i e he iden i y: zi =Wix . The ma ix Wi has he sha es o
bila e al ade be ween he egions o he sys em. We inse hese e ms
in o Equa ion (1) as ollows:
Gx =a0+a1 +Hx −1+
ε
,
whe e: a0=
⎛
⎜
⎜
⎜
⎜
⎝
a00
a10
a20
…
aN0
⎞
⎟
⎟
⎟
⎟
⎠
,a1=
⎛
⎜
⎜
⎜
⎜
⎝
a01
a11
a21
…
aN1
⎞
⎟
⎟
⎟
⎟
⎠
,
ε
=
⎛
⎜
⎜
⎜
⎜
⎝
ε
0
ε
1
ε
2
…
ε
N
⎞
⎟
⎟
⎟
⎟
⎠
,G=
⎛
⎜
⎜
⎜
⎜
⎝
A0W0
A1W1
A2W2
…
ANWN
⎞
⎟
⎟
⎟
⎟
⎠
,H=
⎛
⎜
⎜
⎜
⎜
⎝
B0W0
B1W1
B2W2
…
BNWN
⎞
⎟
⎟
⎟
⎟
⎠
,
Ai= [Iki,−Λi0],and Bi= [Φi,Λi1].(5)
We mul iply Equa ion (5) by he in e se o ma ix G, which is
gene ally a non-singula ma ix. This ep esen a ion gene a es Equa ion
(6):
x =G−1a0+G−1a1 +G−1Hx −1+G−1
ε
.(6)
Equa ion (6) ep esen s he basic o m o he GVAR. Addi ional
de i a ions, including Equa ion (7) (when ime se ies a e
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nons a iona y), a e desc ibed by Pesa an e al. (2004). Howe e , o his
a icle, we use he model in he e o co ec ion o m. In he appendices,
Tables B, C and D p esen he uni oo es s o domes ic and o eign
a iables, he o de o each VARX, and he numbe o coin eg a ing
ela ionships. The esul s indica e he p esence o uni oo s in mos o
he ime se ies, bu we also de ec coin eg a ing ela ionships.
1
Following Dees e al. (2007), we employ he Weigh ed Symme ic
(WS) es . The esul s indica e ha he a iables a e nons a iona y in
le els, bu hey become s a iona y in di e ences. The nex s ep in ol es
e alua ing coin eg a ing ela ionships, and Table C demons a es he
exis ence o long- e m ela ionships be ween he a iables. Conse-
quen ly, we adop he GVAR in he e o co ec ion o m, as ou lined by
Pesa an e al. (2004).
Δxi =ai0+ai1 +Πi i, −1+Λi0Δx∗
i +
ψ
i0Δd +
ε
i ,
whe e Πi= (Ai−Bi,−
ψ
i0−
ψ
i1), i −1=(zi, −1
d −1),and d is a global ec o .
(7)
Sec ion 4 p esen s he econome ic esul s o he dynamic analysis
using he GIRF and he Gene alized Fo ecas E o Va iance Decompo-
si ion (GFEVD). The GIRF illus a es how a shock sp eads and impac s
he egions o he sys em, while he GFEVD p o ides in o ma ion abou
he ex en o which a speci ic luc ua ion o a gi en a iable occu ed
due o o he a iables.
Kim (2013) a gued ha GIRFs can lead o misleading in e ences
since hey a e based on ex eme in e ences. A no able limi a ion o
GIRFs is hei inabili y o iden i y shocks. To add ess his, Khan (2020)
and A ílio (2023) employed he SGIRF o ein o ce hei esul s. SGIRF
allows o he iden i ica ion o shocks in one economy. Consequen ly, we
p esen he esponses o bo h GIRFs and SGIRFs in ou esul s.
In he empi ical sec ion, we analyze wo shocks: one o igina ing om
ad anced economies and ano he om eme ging ma ke economies. We
simula e a global shock using Aus alia, Canada, he Eu ozone, Japan,
Ko ea, No way, New Zealand, Sweden, Swi ze land, he U.K., and he U.
S. (AD shock). Fo he eme ging g oup, a shock is simula ed using B azil,
Chile, China, India, Indonesia, Mexico, Sou h A ica, and Tu key (EME
shock). Consequen ly, an AD shock (o EME shock) ep esen s shocks in
all domes ic s ock ma ke s o he economies in his g oup. The GIRF and
SGIRF p esen he esponses o all economies o hese global shocks
based on economic de elopmen .
4. Resul s
4.1. AD and EME shocks
Figs. 1-4 illus a e he domes ic esponses o all economies o a
nega i e shock in he s ock ma ke s o ad anced economies. In he i s
pa o his subsec ion, we simula e a shock on ad anced economies, and
simila ly, we adop he same wi h eme ging economies in he second
pa . This app oach enables us o examine how economies eac o
shocks based on he le el o economic de elopmen . The alues in he
GIRF a e p esen ed in pe cen ages, wi h he dashed lines ep esen ing a
90% con idence in e al ob ained by boo s ap. The solu ion o he
GVAR was based on he a e age bila e al ade in 2014–16.
In Fig. 1, we obse e ha he AD shock induces luc ua ions in all
s ock ma ke s, wi h all esponses being s a is ically signi ican and
p esen ing nega i e alues. In gene al, domes ic s ock ma ke s exhibi
a ia ions be ween 1 and 2%.
Fig. 2 explo es how mo emen s in he domes ic s ock ma ke impac
GDP. Two obse a ions can be made: hese luc ua ions ha e a nega i e
e ec on GDP, and GDP esponses a e ansi o y in some economies. In
all La in Ame ican coun ies (BRA, CHL, and MEX), GDP expe iences a
all o e wo yea s. Howe e , he same esponse is no obse ed in Asian
economies. GDP did no all in China and India (Chinese GDP inc eased
in he i s mon hs), while he GDP o Indonesia and Japan declined.
Addi ionally, we did no de ec any pe sis en di e ences be ween
ad anced and eme ging economies. In sho , he es ima es illus a e ha
nega i e s ock ma ke shocks a e ela ed o a global ecession, leading o
a dec ease in GDP.
Figs. 3 and 4 help in unde s anding he ansmission o he shock,
ocusing on wo inancial channels: exchange a es and in e es a es.
Based on he es ima es o domes ic cu encies, we obse e e en s
known as “ ligh o quali y”, whe e capi al lows o sa e ha ens,
esul ing in he dep ecia ion o he domes ic cu ency. Howe e , no
dis inc pa e n o his p ocess eme ged when compa ing ad anced and
eme ging economies, as bo h expe ienced dep ecia ions. Addi ionally,
some cu encies, such as hose o Aus alia, India, and Sou h A ica,
app ecia ed.
Examining c edi ma ke s in Fig. 4, we obse e ha mos eac
nega i ely o he shock. While one migh an icipa e posi i e in e es a e
alues due o po en ial con ac iona y mone a y policies implemen ed
by cen al banks o cu b he ou low o capi al, as obse ed in Bha a ai
e al. (2020), ou es ima es did no con i m his esponse.
F om his, we can d aw he ollowing p elimina y conclusions: he
nega i e shock om AD s ock ma ke gene a es pe sis en and signi i-
can e ec s in all economies, mani es ed in declines in bo h domes ic
s ock ma ke s and in e es a es, as well as episodes o “ ligh o quali y”.
In his con ex , ou esul s align wi h he indings o Aguia and Gopi-
na h (2007), who demons a ed ha he business cycle o eme ging
economies is in luenced by de eloped economies. Impo an ly, ou es-
ima es unde sco e he endu ing in luence o ad anced economies on
he business cycle o eme ging economies, which con adic s he ind-
ings o Kose e al. (2012) and Abiad e al. (2015). These s udies a gued
ha de eloping economies ha e become mo e esis an o ex e nal
shocks. Figs. 1-4 highligh ha AD shocks a e a p ominen sou ce o
luc ua ions in eme ging ma ke s.
Following he same s uc u e as be o e, he second pa o his sub-
sec ion po ays a nega i e shock on he agg ega e EME s ock ma ke .
Figs. 5-8 display he domes ic esponses o all economies. The mos
appa en di e ence om he p e ious igu es is he ansi o y na u e o
he EME shock. Fo example, in Fig. 5, he nega i e shock akes a ound
ou o i e mon hs o lose s a is ical signi icance. In many economies,
his shock was no able o p oduce s a is ically signi ican esponses.
This limi ed impac is e lec ed in o he ma ke s wi h mode a e domes ic
esponses. Once again, we de ec ed he same endency: EME shocks a e
ansi o y and sho -li ed. E en in one o he mos sensi i e ma ke s, he
exchange a e showed only sho -li ed episodes o “ ligh o quali y."
In sho , he es ima es in Figs. 1-8 sugges ha ad anced economies
exe a meaning ul and pe sis en in luence on domes ic luc ua ions,
leading o endu ing e ec s on s ock, exchange, c edi ma ke s, and GDP.
Con e sely, when we in es iga e a shock o igina ing om eme ging
economies, i has only sho -li ed e ec s. Using a GVAR o s udy he
sp ead o he 2008 inancial c isis, Chudik and F a zsche (2011)
concluded ha bo h ad anced and eme ging economies we e nega i ely
in luenced by he un olding o his e en . In his case, ou esul s show a
simila scena io in which shocks om ad anced economies cause s ong
luc ua ions in all economies.
The luc ua ions depic ed in Figs. 1-8 sugges ha s ock ma ke
shocks igge mo emen s in he cu ency and c edi ma ke s. One hy-
po hesis is ha hese shocks impac exchange a es, leading o he
dep ecia ion o domes ic cu encies. Subsequen ly, cen al banks eac .
Gi en he nega i e na u e o he shock and he impending ecession,
mone a y au ho i ies accommoda e he nega i e s ock ma ke shock.
1
The coin eg a ion es indica ed ha i e economies (Canada, Chile, No -
way, New Zealand, and Sweden) do no ha e coin eg a ing ela ionships.
Despi e he absence o coin eg a ing ec o s o hese economies, hei inclusion
did no comp omise he s abili y o he model. Consequen ly, we decided o
e ain hese economies o ensu e a ep esen a i e po ayal o he wo ld
economy.
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Finally, he s ock ma ke shock co esponds o declines in GDP (we use
SGIRFs in Sec ion 4.2 o iden i y s ock ma ke shocks and ein o ce his
hypo hesis).
These igu es also indica e he e ogenei ies in he esul s. One o he
main di e ences be ween he shocks is he esponses o he Chinese
economy. Rega ding he AD shock, he s ock ma ke and in e es a es
dec ease, GDP inc eases, and he domes ic cu ency app ecia es. In he
case o he EME shock, he s ock ma ke dec eases, and he domes ic
cu ency dep ecia es ( he o he a iables a e no s a is ically signi i-
can ). In his sense, China shows a dis inc pa e n o esponses o hese
Fig. 1. GIRF o a nega i e shock on he s ock ma ke o AD and domes ic esponses o domes ic s ock ma ke s.
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wo shocks compa ed o he o he economies.
We o e he ollowing explana ion o hese dis inc esponses o he
Chinese economy. Pe haps he nega i e ex e nal shock inc eases un-
ce ain y in he Chinese economy, p o oking s ess eac ions in he
inancial ma ke s, such as declining alues in s ocks. The Chinese cen al
bank eac ed by dec easing in e es a es, a mo e ha could p e en a
po en ial economic ecession. As he cos o capi al dec eases, com-
panies can bo ow capi al and in es in new plans and p ojec s, he eby
inc easing p oduc ion. This economic boom in China may a ac
ex e nal capi al, esul ing in he app ecia ion o he domes ic cu ency.
Fig. 2. GIRF o a nega i e shock on he s ock ma ke o AD and domes ic esponses o he GDP.
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An implici assump ion in his a ionale is ha he Chinese cen al bank
manages o a e a po en ial ecession s emming om an ex e nal
nega i e shock.
Rega ding he nega i e s ock ma ke impac om he EME, i ’s
impo an o no e ha he Chinese s ock ma ke is included in his shock.
Thus, o a ce ain deg ee, his cons i u es a domes ic nega i e shock on
he s ock ma ke . This ma ke loses alue, leading o an ou low o
capi al. Subsequen ly, he domes ic cu ency expe iences dep ecia ion.
Because he esponse o he s ock ma ke loses s a is ical signi icance in
he i s yea , we can suppose ha hese e ec s a e sho -li ed, which
Fig. 3. GIRF o a nega i e shock on he s ock ma ke o AD and domes ic esponses o he exchange a es.
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explains he lack o esponse in GDP. Na u ally, hese a e supposi ions.
Fo a o mal e alua ion o he esponses o he Chinese economy, we
should iden i y i s shock, which is no he goal o ou in es iga ion.
Ano he he e ogenei y conce ns he esponses o he domes ic cu -
encies. In Fig. 3, ele en cu encies dep ecia e (B azil, Canada, Chile,
Indonesia, Ko ea, Mexico, No way, Sou h A ica, Sweden, Tu key, and
he U.K.) o he shock, while se en cu encies (Aus alia, China, he
Eu ozone, India, Japan, New Zealand, and Swi ze land) app ecia e.
These es ima es highligh he impo ance o domes ic ac o s, such as
ins i u ional a angemen s and ulne abili y o shocks, in
Fig. 4. GIRF o a nega i e shock on he s ock ma ke o AD and domes ic esponses o he in e es a es.
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Fig. 10. SGIRF o a nega i e AD s ock ma ke shock and esponses o GDP.
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Fig. 11. SGIRF o a nega i e EME s ock ma ke shock and esponses o s ock ma ke s.
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Fig. 12. SGIRF o a nega i e EME s ock ma ke shock and esponses o GDP.
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Fig. 13. GIRF o a nega i e AD s ock ma ke shock and esponses o s ock ma ke s ( inancial low).
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Fig. 14. GIRF o a nega i e AD s ock ma ke shock and esponses o GDP ( inancial low).
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Fig. 15. GIRF o a nega i e EME s ock ma ke shock and esponses o s ock ma ke s ( inancial low).
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Fig. 16. GIRF o a nega i e EME s ock ma ke shock and esponses o GDP ( inancial low).
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main esul s did no change ( esul s a e a ailable upon eques ).
5. Conclusion
We con ibu e o he li e a u e by p o iding a gene al analysis
encompassing EMEs and ADs in a sys em connec ed by bila e al ade
(and inancial low). GVAR pe mi s us o compa e shocks om di e en
egions and he domes ic esponses o all economies. Howe e , ou
app oach does no add ess idiosync a ic domes ic ac o s, which a e
c ucial o unde s anding speci ic esponses. To his end, a case s udy is a
ecommendable nex s ep in ou in es iga ion. The challenge is o model
he in e na ional economy while explici ly inco po a ing ade/ inan-
cial low. We p opose ha a modi ied GVAR ocused on one coun y
could add ess hese conside a ions.
Finally, ou esul s e idence he economic in e dependence and
in eg a ion be ween economies, showing how inancial episodes can
sp ead h oughou he sys em, causing pe sis en luc ua ions in do-
mes ic ma ke s. Al hough exchange a es abso b pa o he shock, hey
do no comple ely shield he coun y. The e o e, we asse ha ou pape
highligh s how ex e nal inancial shocks can p oduce luc ua ions in
EMEs and ADs, d awing he a en ion o policymake s o ools and
s uc u al e o ms ha can imp o e he esilience o economies.
Decla a ions
The au ho s epo he e a e no compe ing in e es s o decla e.This
esea ch did no ecei e any speci ic g an s om public, comme cial, o
non-p o i agencies.The da a suppo ing he indings o his s udy a e
a ailable om he co esponding au ho upon easonable eques .
Appendices.
Table A
Coun ies and egions
AUS Aus ia NOR No way EUR
BRA B azil NZL New Zealand (AUT) Aus ia
CAN Canada SOU Sou h A ica (BEL) Belgium
CHN China SWE Sweden (FIN) Finland
CHL Chile SWI Swi ze land (FRA) F ance
IND India TUR Tu key (GER) Ge many
IDN Indonesia UK Uni ed Kingdom (ITA) I aly
JPN Japan US Uni ed S a es (NTH) Ne he land
KOR Sou h Ko ean EUR Eu ozone (SPA) Spain
MEX Mexico
No e: The las column shows he agg ega ion o he Eu ozone. In b acke s a e he coun ies ha makeup pa o i .
Table B
Uni Roo Tes o Domes ic Va iables a 5% o s a is ical signi icance
C i ical Value AUS BRA CAN CHN CHL EUR IND IDN JPN KOR
q (wi h end) −3.24 −2.67 −1.57 −3.69 −3.89 −1.43 −2.65 −2.90 −2.16 −2.25 −3.26
q (no end) −2.55 −0.54 0.78 −0.89 −2.51 0.99 −2.28 0.28 0.16 −1.88 −0.83
Dq −2.55 −7.07 −7.95 −7.27 −5.89 −7.79 −10.71 −6.77 −6.97 −9.61 −7.34
y (wi h end) −3.24 −5.76 −4.27 −4.58 −3.98 −4.37 −4.05 −5.04 −1.35 −4.19 −2.35
y (no end) −2.55 −5.54 −4.27 −4.24 −3.99 −4.38 −3.80 −4.82 −1.14 −4.20 −2.38
Dy −2.55 −9.51 −9.92 −8.36 −14.90 −6.43 −12.27 −14.04 −9.29 −6.55 −4.72
e (wi h end) −3.24 −1.84 −1.85 −1.47 −1.56 −1.83 −1.84 0.17 −1.44 −1.71 −2.64
e (no end) −2.55 −1.24 −1.77 −0.02 0.07 −1.56 −1.25 −1.18 0.15 −1.89 −1.00
De −2.55 −11.35 −8.67 −10.47 −5.73 −9.91 −10.34 −2.16 −8.91 −9.38 −6.96
(wi h end) −3.24 −2.46 −3.37 −2.73 −2.66 −3.25 −2.52 −1.37 −3.34 −2.21 −2.89
(no end) −2.55 −1.92 −2.38 −2.09 −2.25 −2.88 −1.42 −0.83 −0.45 −2.23 −0.38
D −2.55 −3.74 −4.49 −6.34 −11.52 −6.33 −4.88 −12.52 −6.42 −10.32 −9.38
MEX NOR NZL SOU SWE SWI TUR UK US
q (wi h end) −3.24 −0.79 −2.77 −1.78 −1.95 −2.94 −2.57 −1.04 −2.50 −2.81
q (no end) −2.55 1.03 0.34 −0.46 0.95 −0.86 −1.72 2.12 −1.99 −0.88
Dq −2.55 −8.13 −10.13 −6.94 −7.95 −7.35 −7.53 −6.93 −9.01 −10.92
y (wi h end) −3.24 −3.95 −3.56 −5.15 −3.65 −3.36 −3.48 −5.01 −4.33
y (no end) −2.55 −3.78 −3.58 −5.05 −3.56 −3.37 −3.48 −4.77 −4.16
Dy −2.55 −9.67 −11.31 −8.60 −9.19 −11.54 −5.82 −10.27 −7.78
e (wi h end) −3.24 −1.96 −1.77 −2.47 −2.50 −2.24 −1.88 −0.93 −2.19
e (no end) −2.55 −1.55 −1.48 −1.70 −2.26 −2.09 −0.74 −0.97 −1.68
De −2.55 −11.92 −10.38 −10.26 −10.44 −7.31 −11.43 −11.79 −10.13
(wi h end) −3.24 −0.45 −2.83 −2.14 −2.97 −1.79 −2.33 −1.57 −2.39 −2.06
(no end) −2.55 0.22 −1.49 −1.87 −1.26 −1.48 −1.29 −0.56 −1.55 −1.93
D −2.55 −4.69 −7.62 −6.19 −6.59 −7.24 −18.32 −11.68 −4.58 −5.05
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Table C
Uni Roo Tes o Fo eign Va iables a 5% o s as is ical signi icance
C i ical Value AUS BRA CAN CHN CHL EUR IND IDN JPN KOR
q* (wi h end) −3.24 −3.86 −3.73 −3.58 −3.27 −3.75 −3.62 −3.65 −3.69 −3.86 −3.86
q* (no end) −2.55 −0.98 −0.86 −0.77 −0.69 −0.71 −0.34 −0.66 −0.97 −0.78 −0.86
Dq* −2.55 −8.97 −7.44 −10.49 −7.94 −7.43 −7.56 −7.47 −7.31 −9.22 −9.04
y* (wi h end) −3.24 −5.08 −3.40 −5.16 −4.77 −4.13 −3.52 −3.34 −4.16 −4.60 −5.17
y* (no end) −2.55 −4.83 −3.32 −4.98 −4.62 −4.06 −3.47 −3.30 −4.10 −4.52 −5.10
Dy* −2.55 −7.45 −8.35 −8.09 −8.07 −9.25 −7.33 −6.92 −8.72 −9.08 −8.30
e* (wi h end) −3.24 0.34 −0.12 −0.61 −0.13 −0.14 −0.34 −1.45 0.86 −0.39 0.22
e* (no end) −2.55 −1.05 −1.09 −0.85 −1.15 −0.96 −0.94 −0.43 −1.08 −0.62 −1.06
De* −2.55 −4.11 −5.75 −7.61 −6.33 −6.54 −7.22 −10.24 −1.85 −7.45 −4.23
* (wi h end) −3.24 −2.57 −2.38 −2.10 −2.45 −2.37 −2.11 −2.59 −2.71 −2.41 −2.29
* (no end) −2.55 −1.17 −1.34 −1.82 −1.49 −1.31 −1.13 −1.23 −1.36 −1.33 −1.26
D * −2.55 −6.75 −5.80 −4.83 −5.41 −5.72 −6.56 −5.61 −6.15 −6.21 −6.53
MEX NOR NZL SOU SWE SWI TUR UK US
q* (wi h end) −3.24 −3.56 −3.08 −3.74 −3.59 −2.83 −3.14 −3.21 −3.16 −3.01
q* (no end) −2.55 −0.86 −1.47 −0.90 −0.99 −1.25 −1.32 −1.37 −1.21 −0.48
Dq* −2.55 −10.41 −7.93 −7.38 −7.44 −7.99 −7.91 −7.71 −7.78 −7.39
y* (wi h end) −3.24 −5.03 −4.41 −3.99 −3.47 −3.98 −4.40 −4.52 −4.12 −3.56
y* (no end) −2.55 −4.85 −4.19 −3.91 −3.36 −3.81 −4.16 −4.30 −3.93 −3.45
Dy* −2.55 −7.32 −8.03 −9.12 −6.90 −9.43 −8.30 −7.66 −8.70 −7.18
e* (wi h end) −3.24 −0.25 −1.84 −0.24 0.30 −1.58 −0.56 −0.85 −1.23 −0.92
e* (no end) −2.55 −0.89 −1.30 −0.98 −1.13 −1.24 −1.23 −1.22 −1.16 −0.60
De* −2.55 −6.61 −7.64 −6.46 −3.44 −9.81 −6.48 −7.54 −9.25 −9.03
* (wi h end) −3.24 −2.16 −2.55 −2.80 −2.72 −2.92 −2.88 −2.64 −2.65 −2.70
* (no end) −2.55 −1.87 −1.51 −1.48 −1.34 −1.46 −1.49 −1.38 −1.41 −1.23
D * −2.55 −4.87 −4.41 −5.11 −5.59 −4.57 −4.57 −4.99 −4.96 −3.63
Table D
VARX o de and numbe o coin eg a ing ela ionships
VARX (p,q) Coin eg a ing ela ionships
p q
AUS 2 1 1
BRA 2 2 1
CAN 2 2 0
CHN 2 2 3
CHL 2 2 0
EUR 2 2 1
IND 2 2 1
IDN 2 2 1
JPN 2 2 1
KOR 2 2 1
MEX 2 2 1
NOR 2 2 0
NZL 2 1 0
SOU 2 2 2
SWE 2 2 0
SWI 2 2 1
TUR 2 2 1
UK 2 2 1
US 2 2 1
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