Abdelsalam, Mamdouh Abdelmoula Mohamed
A icle
Oil p ice luc ua ions and economic g ow h: The case o
MENA coun ies
Re iew o Economics and Poli ical Science (REPS)
P o ided in Coope a ion wi h:
Cai o Uni e si y, Cai o
Sugges ed Ci a ion: Abdelsalam, Mamdouh Abdelmoula Mohamed (2023) : Oil p ice luc ua ions and
economic g ow h: The case o MENA coun ies, Re iew o Economics and Poli ical Science (REPS),
ISSN 2631-3561, Eme ald, Bingley, Vol. 8, Iss. 5, pp. 353-379,
h ps://doi.o g/10.1108/REPS-12-2019-0162
This Ve sion is a ailable a :
h ps://hdl.handle.ne /10419/316087
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Oil p ice fluc ua ions and
economic g ow h: he case o
MENA coun ies
Mamdouh Abdelmoula Mohamed Abdelsalam
Depa men o Economics, Minufiya Uni e si y, Shebin El-Kom, Egyp
Abs ac
Pu pose –This pape aims o explo e he ex eme e ec o c ude oil p ice fluc ua ions and i s ola ili y on
he economic g ow h o Middle Eas and No h A ica (MENA) coun ies. I also in es iga es he asymme ic
and dynamic ela ionship be ween oil p ice and economic g ow h. Fu he , a sepa a e analysis o each
MENA oil-expo and oil-impo coun ies is conduc ed. Fu he mo e, i s udies o wha ex en he quali y o
ins i u ions will change he e ec o oil p ice fluc ua ions on economic g ow h.
Design/me hodology/app oach –As he e ec o oil p ice fluc ua ions is no he same o e di e en
business cycles o oil p ice le els, he pape uses a panel quan ile eg ession app oach wi h o he linea
models such as fixed e ec s, andom e ec s and panel gene alized me hod o momen s. The panel quan ile
me hodology is an ex ension o adi ional linea models and i has he ad an age o explo ing he
ela ionship o e he di e en quan iles o he whole dis ibu ion.
Findings –The pape can summa ize esul s as ollowing: changes in oil p ice and i s ola ili y ha e an
opposi e e ec o each oil-expo and oil-impo coun ies; o he o me , changes in oil p ices ha e a posi i e
impac bu he ola ili y a nega i e e ec . While o he la e , changes in oil p ices ha e a nega i e e ec bu
ola ili y a posi i e e ec . Fu he , he impac o oil p ice changes and hei unce ain y a e di e en ac oss
di e en quan iles. Fu he mo e, he e is e idence abou he asymme ic e ec o he oil p ice changes on
economic g ow h. Finally, accoun ing o ins i u ional quali y led o a educ ion in he impac o oil p ice
changes on economic g ow h.
O iginali y/ alue –The s udy concludes mo e de ailed esul s on he impac o oil p ices on g oss
domes ic p oduc g ow h. Thus, i can be used as a decision-suppo ool o policymake s.
Keywo ds Economic g ow h, C ude oil p ice, Asymme ic e ec , Ex eme e ec ,
Panel quan ile eg ession
Pape ype Resea ch pape
1. In oduc ion
Ene gy plays he mos c i ical ole in he global economy. Despi e he inc easing deba e
a ound he ole o al e na e enewable sou ces o ene gy such as wa e , sola and nuclea
powe , oil s ill has a cen al ole o a as po ion o he wo ld’s coun ies. Hence, oil p ice
shocks migh ha e conside able mac oeconomic consequences o bo h impo ing and
expo ing coun ies. As o he o me ca ego y, oil is a majo de e minan o p oduc ion cos
and o he la e , i is he p ima y sou ce o go e nmen e enue. Fu he , fluc ua ions in oil
© Mamdouh Abdelmoula Mohamed Abdelsalam. Published in Re iew o Economics and Poli ical
Science. Published by Eme ald Publishing Limi ed. This a icle is published unde he C ea i e
Commons A ibu ion (CC BY 4.0) licence. Anyone may ep oduce, dis ibu e, ansla e and c ea e
de i a i e wo ks o his a icle ( o bo h comme cial and non-comme cial pu poses), subjec o ull
a ibu ion o he o iginal publica ion and au ho s. The ull e ms o his licence maybe seen a h p://
c ea i ecommons.o g/licences/by/4.0/legalcode
JEL classifica ion –E32, Q43, C3
Oil p ice
fluc ua ions
and economic
g ow h
353
Recei ed 21 Decembe 2019
Re ised 7 Sep embe 2020
26 Oc obe 2020
Accep ed 27 Oc obe 2020
Re iew o Economics and Poli ical
Science
Vol. 8 No. 5, 2023
pp. 353-379
Eme ald Publishing Limi ed
e-ISSN: 2631-3561
p-ISSN: 2356-9980
DOI 10.1108/REPS-12-2019-0162
The cu en issue and ull ex a chi e o his jou nal is a ailable on Eme ald Insigh a :
h ps://www.eme ald.com/insigh /2631-3561.h m
p ices a ec p oduc ion cos s, hea ing bills and anspo a ion cos s. This gene a es
unce ain y abou he u u e o he wo ld economy. This may also encou age in es o s o
delay hei p oducing decisions and ealloca e labo and capi al om in ensi e pe oleum
sec o s o non-in ensi e pe oleum sec o s (Sill, 2007). I is a gued ha oil p ice fluc ua ions
ha e caused ins abili y o many mac oeconomic agg ega es in bo h oil-expo e s and
impo e s coun ies (B inin e al., 2016). Consequen ly, because o his double impo ance o
oil, i has been a gued ha i s p ice is highly ola ile han ha o any o he commodi y and i
is almos unp edic able (Dehn, 2001).
Howe e , he e ec o changes in he oil p ice is di e en o expo ing and impo ing
coun ies. Expo ing coun ies massi ely depend on oil e enue. Then, a ise in oil p ices
means inc easing he amoun o money a ailable o unding de elopmen p ojec s.
The e o e, mone a y and fiscal policies unc ion is conside ably a ec ed by oil p ice
fluc ua ions (Saddiqui e al.,2018). Howe e , he ad e se e ec makes he financial and eal
agg ega es mo e unce ain due o he oil p ice ola ili y, pa icula ly in he case o impe ec
capi al ma ke s (Hausmann and Rigobon, 2003). On he con a y, when he oil p ice is
alling, go e nmen s canno immedia ely cu hei expendi u es and hen ace a massi e
budge defici . As changes in oil p ices ha e a conside able e ec on mac oeconomic
pe o mance in bo h expo ing and impo ing coun ies, analyzing his e ec and p edic ing
o wha ex en g oss domes ic p oduc (GDP) in di e en coun ies is sensi i e o hese
a ia ions a e c ucial
Howe e , he dependence be ween oil p ice and economic g ow h is no he same o e
di e en business cycles o oil p ice le els (Kilian and Vig usson, 2011;Das e al.,2018).
The e o e, his s udy explo es he ex eme dependence be ween oil p ice fluc ua ions and
economic g ow h in Middle Eas and No h A ica (MENA) coun ies using quan ile
eg ession (Q.R.) in addi ion o he o he ou linea models. To ou knowledge, he e a e no
s udies ha explo ed he ex eme e ec o he oil p ices on he economic g ow h o MENA
coun ies. Q.R.’s app oach was p esen ed by Koenke and Basse (1978). I a ge s he
assessmen o he unde lying ela ionship based on each quan ile
(Bau , 2013). Unlike
he o dina y leas squa es (OLS) and o he adi ional models, which assess he e ec o he
explana o y a iable on he dependen a iable on a e age. The Q.R. me hodology is an
ex ension o adi ional linea models and i has he ad an age o explo ing he whole
ela ionship abou he impac o oil p ice changes on economic g ow h. Fu he , oil p ice
changes a e cha ac e ized by hea y ails and sha p peaks. As quan ile eg ession is obus
o skewness, ku osis and he e oscedas ici y, Q.R. can be used o o e come hese
phenomena (Koenke , 2004;Chuang e al., 2009;Lin, 2013;Mensi e al.,2014). The s udy aims
a explo ing how economic g ow h is a ec ed by he fluc ua ions and he ola ili y o c ude
oil p ices, as well as he asymme y o c ude oil p ice changes in he MENA egion. In
addi ion, i in es iga es how augmen ing he quali y o ins i u ions will a ec he p e ious
ela ionship. Thus, he pape ies o answe he ollowing ou ques ions: wha he expec ed
ex eme e ec o he fluc ua ions in c ude oil p ices on di e en MENA coun ies? How do
he changes in oil p ice and ola ili y o oil p ice impac he MENA economies? To wha
ex en should changes in oil p ice and oil p ice ola ili y be aken in o conside a ion when
es ima ing o o ecas ing he economic g ow h o MENA coun ies? (4) Does he exis ence o
mo e qualified and e ec i e ins i u ions a ec he ela ionship be ween oil p ice fluc ua ions
and GDP g ow h?
This pape con ibu es o p e ious s udies in di e en aspec s. Fi s , i explo es he
ex eme impac o bo h oil p ice and unce ain y o oil p ice on he eal p oduc ; o ou
knowledge, no p e ious s udy conside ed his poin be o e. Second, i explo es o wha
ex en he e ec o oil p ices is asymme ic. The analysis o his pape is used as a decision-
REPS
8,5
354
suppo ool o policymake s as i a emp s o in es iga e o wha ex en oil p ices and oil
p ices ola ili y should be aken in o conside a ion when calcula ing and p edic ing
economic g ow h. All ou linea models gi e obus analysis such as ha : changes in oil
p ice fluc ua ions ha e a significan posi i e impac on economic g ow h while he ola ili y
o oil p ice has an insignifican posi i e e ec . In addi ion, he e is e idence abou he
asymme ic e ec o oil p ice changes on economic g ow h. Fu he , Q.R. emphasizes he
impo ance o analyzing he ex eme e ec o oil p ice changes and unce ain y o oil p ice
on economic g ow h as he e ec o hose a iables is mo e significan in uppe quan iles
han middle o lowe ones. Fu he mo e, he quali y o ins i u ions has a significan posi i e
e ec on GDP g ow h. Also, augmen ing he quali y o ins i u ions in he analysis esul ed
in lowe ing he impac o c ude oil changes on economic g ow h, and he e ec o he
ola ili y becomes insignifican in all models. Mo eo e , a sepa a e analysis o each MENA
oil-expo coun y and MENA oil-impo coun ies is conduc ed and esul s show ha o
oil-expo coun ies, changes in oil p ices ha e a significan posi i e impac bu he ola ili y
has a nega i e e ec . Whe eas o oil impo coun ies, changes in oil p ices ha e a
significan nega i e e ec bu ola ili y a posi i e significan e ec . This pape is s uc u ed
as ollows. Sec ion 2 highligh s he ela i e exis ing li e a u e. Sec ion 3 illus a es he
me hodology and empi ical analysis. Sec ion 4 p esen s he da a and empi ical esul s.
Finally, in Sec ion 5 he conclusion and policy ecommenda ions a e p o ided.
2. Li e a u e e iew
The ela ionship be ween oil p ice and economic g ow h has a ac ed many esea che s
a e he pionee ing wo k o Hamil on (1983), who concludes ha he e is a nega i e e ec o
oil p ice on he eal p oduc . In his ins ance, i is a gued ha oil p ice fluc ua ions ha e a
conside able impac on indi iduals’wel a e o e he globe (Mgbame e al., 2015). Howe e ,
o he wo ks claim ha he ac ions o economic policies can abso b he e ec o oil p ice
shocks on he eal p oduc (Vespignani e al., 2019;Ge shon e al.,2019). Fu he , Odhiambo
(2020) e iews he li e a u e abou he e ec o oil p ice fluc ua ions on economic g ow h and
he s a es ha he e ec a ies o di e en coun ies o di e en samples.
The e is a con inuous deba e in he li e a u e abou he di ec ion o oil p ice e ec on
economic g ow h. Whe eas some s udies a gue ha o expo ing coun ies, oil p ice
inc eases lead o enhancing he le el o income and hen consequen ly bo h in es men and
consump ion incomes g ow, which means highe le els o GDP g ow h; indeed, highe oil
p ices lead o highe ea nings, which imply highe incomes in oil-expo ing-na ions
(Akpan,2009;Foudeh,2017;Jahangi and Du al, 2018;Dabachi e al.,2020). Howe e , some
empi ical s udies conclude ha he e is a nega i e e ec o oil p ice changes on GDP g ow h,
pa icula ly in impo ing coun ies whe e he oil p ice is conside ed one o he mos c i ical
ac o s o p oduc ion (A ou i and Nguyen, 2010;Filis e al.,2011;Mu shed and Tanha, 2020;
Rahman and Majumde ,2020). Acco ding o his iew, a ise in wo ld oil p ices lowe s
incomes o oil-impo ing coun ies. In his ega d, his educ ion in income depends on he
deg ee o oil p ice elas ici y and he pe sis en change in he oil p ice (Ghalayini, 2011).
Fu he , cen al banks migh adop con adic o y policies o lessen he domes ic p ice
inc eases and his also b ings mo e es ic ions on he eal p oduc ion side. Papape ou
(2001) and Miguel e al. (2003) ound a nega i e e ec o changes in oil p ices on GDP g ow h
in G eece and Spain, espec i ely. Bouzid (2012) explo ed he Tunisian case and concluded
ha a 10% highe inc ease in he global oil p ice causes a 3.4% decline in GDP g ow h.
The ola ili y o oil p ices is also gi en conside able a en ion in he li e a u e. Okonju
(2009) a gued ha oil p ices ha e highe ola ili y mo e han any o he p oduc s, which b ings
undesi ables nega i e impac s on he eal p oduc side. Amany El-Anshasy e al. (2017)
Oil p ice
fluc ua ions
and economic
g ow h
355
conclude ha he ola ili y o oil e enue has a significan nega i e impac on GDP g ow h.
Howe e , his e ec becomes less wi h he exis ence o ma u e ins i u ions as a mo e qualified
fiscal egime. Van Eyden e al. (2019) ound a significan nega i e e ec on oil p ice ola ili y on
GDP g ow h. Howe e , o he s udies confi med a posi i e impac on oil p ice ola ili y on GDP
g ow h such as Bjo nland (2000) o No way economy and Akinlo and Tolulope Apanisile
(2010) o 20 Sub-Saha an A ican coun ies. In addi ion, Ca alcan i e al. (2015) explo e he
e ec o ola ili y and le el o he commodi y o ade e ms on GDP and hey conclude ha
ola ili y is he main de e minan o he “ esou ce cu se.”Some s udies ound he e ec o oil
p ice ola ili y can be mode a ed; o example, Ja e e al. (2018) ound ha he financial
ins i u ions can decline he possible impac s o oil p ice ola ili y on some oil-p oducing
coun ies.
The asymme ic e ec o oil p ice on economic g ow h, whe he posi i e and nega i e oil
p ice shocks ha e di e en impac s is ano he impo an opic o ecen li e a u e. The
likely asymme ic e ec o oil p ice could be jus ified using h ee jus ifica ions: unce ain y,
sec o al e ec s and coun e infla iona y mone a y ac ions (Kilian and Vig usson, 2011;
Raheem,2017;Akinsola and Nicholas, 2020). Fo ins ance, Hamil on (2008) a gues ha oil
p ice shocks migh push cus ome s in in ensi e ene gy sec o s o educe hei demands
while o he sec o s which do no in ensi ely depend on ene gy migh be mo e cos ly o pay
he cos o shi ing o labo and capi al inpu s ac oss sec o s due o aining cos s and o he
mobili y cos s. S udies such as (Hamil on, 2003) conclude ha posi i e changes in wo ld oil
p ices ha e a s onge e ec on economic pe o mance han nega i e ones. Jiménez-
Rod íguez and Sanchez (2005) find ising in he oil p ice has mo e e ec on GDP g ow h
han i s all in he selec ed The O ganisa ion o Economic Co-ope a ion and De elopmen
(OECD) coun ies. Simila ly, Maalel and Mahmood (2018) find oil p ice shocks ha e an
asymme ic impac on The Gul Coope a ion Council (GCC) economies.
Al hough he main body o he li e a u e conside ed he case o de eloped economies,
o he wo ks explo e he case o eme ging and de eloping coun ies. Fo ins ance, Anashasy
e al. (2005) find a significan associa ion be ween oil p ice fluc ua ions and some economic
agg ega es o Venezuela such as GDP, go e nmen e enues, go e nmen consump ion
and in es men . Fa zanegan and Ma kwa d (2009) s udied he e ec o I an; Gba u e al.
(2017) o Libe ia; Kousa e al. (2019) o Pakis an and Wida jono e al. (2020) o Indonesia.
O he s udies such as Saban e al. (2019) compa ed di e en coun ies by explo ing he e ec
o each coun y indi idually. Rega ding he MENA coun ies; Meh a a and Oskui (2007)
p o ide e idence ha oil p ice fluc ua ions a e he p ima y sou ce o ins abili y o he
mac oeconomic agg ega es in Saudi A abis. Be umen e al. (2010) conclude ha he impac
o changes in oil p ice on economic g ow h is significan o some MENA coun ies while i
is insignifican o o he s. Selim and Zaki (2014) find ha ins i u ional quali y is a leading
cause o esou ce cu se in A abian coun ies. Cashin e al. (2016) used a global ec o
au o eg ession (GVAR) model o es ima e he expec ed e ec s o mac oeconomic shocks in
he main economies (US, Eu ope and China) on he MENA economies. They conclude ha
shocks in he Chinese economy ha e a conside able influence on MENA coun ies.
Mahmood and Zamil (2019) conclude fluc ua ions in oil p ices ha e a conside able e ec on
Saudi A abia GDP ia he e ec on he budge defici . Simila esul s a e concluded o GCC
coun ies by Voh a (2017) and o Bah ain by Abou Elseoud and K eishan (2020).
3. Model and me hodology
The pape aims a examining he impac o changes in oil p ices and hei ola ili ies on he
GDP o he MENA coun ies. Fu he , i explo es how he inclusion o ins i u ional quali y
can a ec his ela ionship. The s udy uses he base model o Mankiw e al. (1992), gi en
REPS
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356

ha i allows augmen ing o he a iables such as he human capi al and ins i u ional
quali y inside he adi ional classic model o Solow (1956). The model can be o mula ed as
ollows:
Yi ¼A0H
b
i GFC
a
i ALD
d
i (1)
Whe e, Yi ep esen s he eal GDP g ow h o coun y i in he yea ;A0 ep esen s a scaling
coe ficien ; and Hi ;GFCi ;and ALDi embody human capi al, physical capi al and land,
espec i ely. The abo e equa ion ep esen s a Cobb-Douglas p oduc ion unc ion, which can
be ans o med in o a log-linea equa ion. Wi h augmen ing o he a iables can, equa ion (1)
can be ew i en as ollows:
Yi ¼
b
0þCOP þVCOP þD þ
b
ln Hi
ðÞ
þ
a
ln GFCi
ðÞ
þ
d
ln ALDi
ðÞ
þXi
þ
«
i
(2)
In mo e de ails can be w i en as ollows:
Yi ¼
b
0þ%COP þ
VCOP þ
w
AsDum þ
b
ln Hi
ðÞ
þ
a
ln GFCi
ðÞ
þ
d
ln ALDi
ðÞ
þ#Xi þ
«
i
(3)
Whe e, Yi is he g ow h in he eal domes ic p oduc (GDP); COP is he change in C ude oil
p ices; VCOP is he ola ili y o c ude oil p ices; and AsDum ep esen s he dummy a iable
ha cap u es he asymme y in he unde lying ela ion (i.e. whe he he changes in oil p ices
a e posi i e o nega i e). The seconda y en ollmen pe cen age (SSEi Þand popula ion g ow h
(PGi Þa e used o app oxima e he human capi al. Whe eas he alue o a eal in es men in
o de app oxima e he physical capi al (GFCi Þ,A ablelandinhec a es(ALDi Þ. In addi ion, Xi
is he included con ol a iables, which include he ini ial ILGDPi (ini ial GDP) o con ol o
he likely condi ional con e gence, ERDi ep esen s he exchange a e de ia ion om he long-
un exchange a e le el. Fu he , ne expo s o GDP (EPGi Þis used o examine he ex en o
which eal ou pu g ow h is a ec ed by ade openness. Fu he mo e, OED is a dummy
a iable which akes 1 o oil expo coun ies and 0 o o he impo coun ies and finally,
INSi is used o accoun o he ins i u ion’s quali y index. In he case o he dynamic panel
app oach, Xi also includes he lag o he dependen a iable (Yi 1).
To be in ol ed in he ongoing deba e a ound he e ec o oil p ice unce ain y on
di e en economic ac i i ies, we will use an app oxima ion o he a iabili y o c ude oil
p ices. The condi ional a iance o oil p ice shocks is calcula ed by using a gene alized
au o eg essi e condi ional he e oskedas ici y (GARCH) model which is based on mon hly-
da a o he oil p ice. Then, he annual condi ional ola ili y is cap u ed by aking he
a e age o he 12-mon h ola ili y.
The e ec o oil p ice changes, he ola ili y o oil p ice and he asymme ic e ec o oil
p ice on economic g ow h a e explo ed based on he specifica ion o equa ion (3). The
coe ficien s o he equa ion (3) a e es ima ed using ou di e en linea app oaches: Pooled
OLS, Fixed e ec es ima ion, Random e ec es ima ion and gene alized me hod o momen s
(GMM). Fu he , o accoun o he whole dis ibu ion o he ela ionship, we also use he
panel quan ile app oach.
Oil p ice
fluc ua ions
and economic
g ow h
357
Rega ding linea models, pooled OLS does no accoun o he e ogenei y be ween he
c oss-sec ions in he model, while he fixed-e ec app oach and he andom e ec app oach
conside he e ogenei y be ween c oss-sec ions. Howe e , all he p e ious h ee app oaches
igno e he endogenei y p oblem when adding he lag o he dependen a iable.
The sys em o he GMM me hod o e comes he likely endogenei y p oblem ha comes
om augmen ing he lag o he dependen a iable inside he explana o y a iable. The
sys em GMM me hod depends on adding lags o independen a iables as ins umen s. The
es ima ion based on GMM has he ad an ages ha i gi es a consis en es ima ion o
coe ficien s wi h an asymp o ically no mal dis ibu ion (Ziliak, 1997). The sys em GMM is
widely used and is hea ily ecommended in he g ow h li e a u e. Bond e al. (2001) and
Hauk and Waczia g (2009) s a e ha he GMM app oach is p e e ed o g ow h models o
ge consis en and e ficien coe ficien s.
Q.R. is ini ially inno a ed by Koenke and Basse (1978), and i ac s as he gene al o m o
O dina y Leas Squa es (OLS); i p o ides mo e p ecise es ima es o he condi ional
dis ibu ion. Q.R. app oach assumes ha he alue o he e o e m is condi ional on he
included explana o y a iables a
h quan ile equal o 0. Thus, he Q.R. o y as a dependen
a iable and x as an independen a iable can be ep esen ed in he ollowing o m:
Qyjx
ðÞ
¼in bjFyjxb
ðÞ

no
¼x0
b
ðÞ (4)
Whe e Qyjx
ðÞ
deno es he condi ional quan ile o he dependen a iable y, 0 <
<1 and
b
ðÞ
is he deg ee o e ec o x on y in he
h quan ile which can be es ima ed as:
^
b
ðÞ
¼a gmin
b
ðÞ
X
n
i¼1
yix0
b
ðÞ
 (5)
I
«
iis he andom e o e m, hus he loss unc ion o he quan ile eg ession can be
w i en as ollows:
«
i
ðÞ
¼
«
i
I
«
i<0
ðÞ½ (6)
Whe e I(.) deno es he indica o unc ion and
«
i
ðÞ
deno es he check unc ion which
weighs in an asymme ic way he nega i e and posi i e alues.
To check o he assump ion o symme y, we use Newey and Powell (1987) es . I he
dis ibu ion o Y based on X is symme ic, hen:
b
ðÞ
þ
b
1
ðÞ
2¼
b
1
2
 (7)
Thus, we can use he Wald es on he quan ile p ocess o e alua e he p e ious es ic ion.
I we assume we ha e an odd numbe , K, o a se o es ima ed pa ame e s which o de ed
k,
hen he middle alue which
kþ1
ðÞ
=2 should be 0.5. Thus, he unde lying unc ion is
symme ic a ound 0.5, and he assumed null hypo hesis is as ollows:
u
j
ðÞ
þ
u
kj1
ðÞ
2¼
u
1=2
ðÞ
o j ¼1;...;K1
2(8)
REPS
8,5
358
The Wald es is designed wi h he null hypo hesis o he symme ic e ec , and i ollows
x
2
K1
ðÞ
=2. Indeed, e using he null hypo hesis o Newey and Powell (1987) es means
e using he assump ion o symme ic alues o he ela ionship o e di e en quan iles.
Rega ding he gene a ing o oil p ice ola ili y, as i is men ioned be o e, i will be
cap u ed based on he GARCH model. The ini ial o m o GARCH was in oduced by
Bolle sle in 1986. In he con ex o he p e ious model, he mean equa ion will be modeled
as a unc ion in i s lags. In addi ion, he condi ional a iance is a unc ion in he lag o
squa ed esiduals and he lag o he condi ional a iance. I we assume ha he condi ional
a iance is h and he squa ed e o s is
«
2
, hen we can exp ess he GARCH(1,1)
ep esen a ion as ollows:
h ¼
l
0þ
l
1
«
2
1þ
l
2h 1(9)
The coe ficien
l
2measu es he pe sis ence inside he condi ional a iance equa ion which
implies ha when
l
2is close o 0, he pe sis ence is lowe whe eas he pe sis ence is highe
when
l
2close o one. Fu he , he a iance should be s ic ly posi i e, and he coe ficien s
mus no be nega i e;
l
00;
l
10;
l
20. Fu he mo e, he s a iona i y condi ion
should be alid o he condi ional ola ili y equa ion;
l
1þ
l
2<1
ðÞ
.
4. Da a, desc ip i e analysis and esul s
4.1 Da a
The s udy uses annual da a o a panel o 17 MENA coun ies, which include: Alge ia,
Bah ain, Egyp , Is ael, Jo dan, Kuwai , Lebanon, Libya, Mo occo, Oman, Qa a , Saudi
A abia, Sudan, Tunisia, Tu key, Uni ed A ab Emi a es and Yemen. The sample span
co e s he pe iod (1970–2018) o cap u e he su ge in oil p ices in he 1970s. The da a se
includes he g ow h in he Real G oss Domes ic P oduc (cons an 2010 USD), C ude oil
p ice, he seconda y school en ollmen pe cen age, he popula ion g ow h pe cen age, g oss
fixed capi al o ma ion (cons an 2010 US$), a able land in hec a es, he exchange a e
de ia ion om he long- un exchange a e le el calcula ed as he de ia ion om he long-
un end which es ima ed by “Hod ick-P esco Fil e me hod,”ne expo s o GDP ( he
expo s o goods and se ices minus impo s o goods and se ices as a pe cen age o GDP).
The ins i u ion quali y index embodies he a e age o he sub-indices such as go e nmen
s abili y, socioeconomic condi ions, in es men p ofile, in e nal conflic , ex e nal conflic ,
co up ion, mili a y in e en ion in poli ics, eligious ensions, law and o de en o cemen ,
e hnic ensions, democ a ic accoun abili y and bu eauc acy quali y. The da a o he
a iables a e cap u ed om he wo ld bank da abase. Fu he , he da a o he c ude oil p ice
is ep esen ed by he Wes Texas In e media e (WTI) c ude oil spo p ices, which
a e collec ed om he In e na ional Ene gy Agency. Finally, da a abou ins i u ion quali y
a e cap u ed om “Poli ical Risk Se ices G oup da abases.”All eg ession a iables a e
implemen ed wi h logs o he a iables.
4.2 Desc ip i e analysis
Figu e A1 depic s he de elopmen o he index o c ude oil p ice. As shown in he figu e, he
oil p ice is highly ola ile du ing he pe iod o he s udy. Thus, he e was a significan
inc ease in oil p ices s a ing om 1973 due o he poli ical p essu e and wa in he MENA
egion. Howe e , wi h he 1980s and he economic slowdown in many de eloped coun ies,
he oil demand d opped again. The p ice ended o inc ease om he beginning o he 2000s
Oil p ice
fluc ua ions
and economic
g ow h
359
un il he las global c isis in 2008. Ano he episode o oil p ice inc eases s a ed a e he
eco e y o he financial c isis un il s a ing o all in 2014.
Table A1 displays he desc ip i e s a is ics o he included a iables in he panel o m.
Fo mo e de ails, analysis o each oil-expo and oil-impo is going o be sepa a ed.
Table A2 shows he co ela ion ma ix o MENA expo ing coun ies. As shown in he
able, he e is a posi i e co ela ion be ween GDP g ow h on one side and c ude oil p ice
changes, ins i u ional quali y, Seconda y school en olmen pe cen age and popula ion
g ow h on he o he side. In con as , he co ela ion be ween GDP g ow h and oil p ice
ola ili y is nega i e.
Figu e A2 shows he e olu ion o c ude oil p ices and GDP g ow h o he MENA oil-
expo ing coun ies. I could be obse ed ha he e is a posi i e associa ion be ween bo h
a iables. Howe e , he linkage be ween bo h a iables was s onge o mos oil-expo ing
coun ies a he beginning o he sample: hen, i has been weakened in he pas 10 yea s.
This could be explained by he economic di e sifica ion s a egy ha has been applied in
many oil-expo ing coun ies such as Saudi A abia and Emi a es. On he o he hand, he
ela ion be ween oil p ice ola ili y and GDP g ow h o MENA oil-expo ing coun ies is
nega i e o long pe iods and many coun ies a e depic ed in Figu e A3.
Table A3 shows he co ela ion ma ix o he MENA oil-impo ing coun ies. I can be
obse ed ha he GDP g ow h is nega i ely co ela ed wi h c ude oil p ice changes and
popula ion g ow h. While i is posi i ely co ela ed wi h he ola ili y o c ude oil p ice, he
ins i u ion quali y and pe cen age numbe o seconda y schooling. The e olu ion o bo h
c ude oil p ices and GDP g ow h a es o oil-impo ing na ions in he MENA egion is
p esen ed in Figu e A4, whe e i can be obse ed ha a nega i e associa ion be ween he
wo a iables. In addi ion, Figu e A5 depic s he e olu ion o oil ola ili y and GDP g ow h
in he oil-impo ing coun ies in he MENA egions, whe e i can be obse ed i is sligh ly
posi i e o some coun ies.
4.3 Resul s
To check o s a iona i y o he included a iables, The Phillip Pe on (PP) es and he
Augmen ed Dickey-Fulle (ADF) es s a e applied. Table A4 depic s he esul s o hese uni
oo es s. As shown in he able, he p obabili ies o he wo used es s indica e ha we
should ejec he null hypo hesis o he uni oo o all he used a iables.
Table A5 e eals he esul s o he GARCH model. I shows ha in he mean equa ion
bo h he fi s leg and he second lag a e significan . In he a iance equa ion, bo h he
squa ed o p e ious esidual and lag o he GARCH a e significan . Also, he summa ion o
he las wo coe ficien s is less han one, which is a equi ed assump ion o he s a iona i y
o he GARCH model. Figu e A6 plo s he ola ili y o oil p ices o e he pe iod unde s udy.
Table A6 shows he es ima es using he pooled OLS, fixed e ec , andom e ec and he
sys em GMM, espec i ely. Acco ding o he esul s o he pooled OLS model, changes in oil
p ices ha e a significan posi i e e ec on ou pu g ow h whe eas ola ili y o oil p ice has a
posi i e e ec bu insignifican . In addi ion, he dummy a iable o he asymme ic e ec o
oil p ice changes is significan and posi i e. Fu he , capi al o ma ion pe cen age has a
significan and posi i e e ec , popula ion g ow h has a nega i e and significan e ec and
he dummy a iable o oil-expo ing coun ies has a significan posi i e e ec .
Rega ding he esul s o he fixed e ec me hod, Table A6 shows changes in oil p ices
ha e a significan posi i e e ec whe eas he ola ili y o oil p ice has an insignifican
posi i e e ec . Fu he , he e is e idence ha he e ec o oil p ice changes on economic
g ow h is asymme ic and he popula ion g ow h has a nega i e significan e ec . Howe e ,
he exchange a e de ia ion does no ha e a significan e ec on ou pu g ow h. Fo he
REPS
8,5
360
Kao, C. (1999), “Spu ious eg ession and esidual-based es s o coin eg a ion in panel da a”,Jou nal o
Econome ics, Vol. 90 No. 1, pp. 1-44, doi: 10.1016/S0304-4076(98)00023.
Lee, K., Lee, B. and Ra i, R. (2001), “Mone a y policy, oil p ice shocks, and he Japanese economy”,
Japan and he Wo ld Economy, Vol. 13 No. 3, pp. 321-349.
Le in, A., Lin, C.F. and Chu, C.S.J. (2002), “Uni oo es s in panel da a: asymp o ic and fini e sample
p ope ies”,Jou nal o Econome ics, Vol. 108 No. 1, pp. 1-24, a ailable a : h ps://doi.o g/
10.1016/S0304-4076(01)00098-7
Odhiambo, N.M. (2020), “Oil p ice and economic g ow h o oil-impo ing coun ies: a e iew o
in e na ional li e a u e, Applied Econome ics and In e na ional De elopmen ,Vol.20.
Vespignani,J.M.andRagha an,M.K.(2019),“Oil cu se, economic g ow h and ade openness”,
Globaliza ion Ins i u e Wo king Pape , Vol. 2019, a ailable a : h ps://doi.o g/10.24149/
gwp370.
Wida jono, A. and Susan un, I. (2020), “Oil and ood p ices o a ne oil impo ing-coun y: how a e
ela ed in Indonesia?”,In e na ional Jou nal o Ene gy Economics and Policy, Vol. 10 No. 5,
pp. 255-263.
Oil p ice
fluc ua ions
and economic
g ow h
367

Appendix
Figu e A1.
De elopmen o oil
p ices o e he s udy
pe iod
0
20
40
60
80
100
120
140
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
USD
Sou ce: The In e na ional Ene gy Annual da abase
REPS
8,5
368
Figu e A2.
The de elopmen o
c ude oil p ice and
GDP g ow h o
MENA oil-expo
coun ies
–2
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Alge ia
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Bah ain
–8
–4
0
4
8
12
70 75 80 85 90 95 00 05 10 15
Kuwai
–15
–10
–5
0
5
10
70 75 80 85 90 95 00 05 10 15
Libyia
–2
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Oman
–4
–2
0
2
4
6
70 75 80 85 90 95 00 05 10 15
Qa a
–4
–2
0
2
4
6
70 75 80 85 90 95 00 05 10 15
Saudi A abia
–4
0
4
8
12
16
70 75 80 85 90 95 00 05 10 15
GLGDP COP
UAE
Sou ce: C ea ed by he au ho
Oil p ice
fluc ua ions
and economic
g ow h
369
Figu e A3.
The de elopmen o
c ude oil p ice
ola ili y and GDP
o MENA oil-expo
coun ies
–0.2
–0.1
0.0
0.1
0.2
0.3
0.4
70 75 80 85 90 95 00 05 10 15
Alge ia
–0.1
0.0
0.1
0.2
0.3
0.4
0.5
70 75 80 85 90 95 00 05 10 15
Bah ain
–0.8
–0.4
0.0
0.4
0.8
1.2
70 75 80 85 90 95 00 05 10 15
Kuwai
–1.5
–1.0
–0.5
0.0
0.5
1.0
70 75 80 85 90 95 00 05 10 15
Libyia
–0.2
–0.1
0.0
0.1
0.2
0.3
0.4
70 75 80 85 90 95 00 05 10 15
Oman
–0.4
–0.2
0.0
0.2
0.4
0.6
70 75 80 85 90 95 00 05 10 15
Qa a
–0.3
–0.2
–0.1
0.0
0.1
0.2
0.3
0.4
70 75 80 85 90 95 00 05 10 15
Saudi A abia
–0.4
0.0
0.4
0.8
1.2
1.6
70 75 80 85 90 95 00 05 10 15
GLGDP VCOP
UAE
Sou ce: C ea ed by he au ho
REPS
8,5
370
Figu e A4.
The de elopmen o
c ude oil p ice and
GDP o MENA oil-
impo coun ies
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Egy p
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Is ae l
–2
0
2
4
6
70 75 80 85 90 95 00 05 10 15
Jo dan
–
10
–5
0
5
10
70 75 80 85 90 95 00 05 10 15
Lebanon
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Mo o c o
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Sudan
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Tunisia
–1
0
1
2
3
4
5
70 75 80 85 90 95 00 05 10 15
Tu key
–15
–10
–5
0
5
70 75 80 85 90 95 00 05 10 15
GLGDP COP
Yiemen
Sou ce: C ea ed by he au ho
Oil p ice
fluc ua ions
and economic
g ow h
371
Figu e A5.
The de elopmen o
c ude oil p ice
ola ili y and GDP
o MENA oil-impo
coun ies
0.00
0.04
0.08
0.12
0.16
70 75 80 85 90 95 00 05 10 15
Egy p
–0.04
0.00
0.04
0.08
0.12
70 75 80 85 90 95 00 05 10 15
Is ae l
–0.2
–0.1
0.0
0.1
0.2
0.3
70 75 80 85 90 95 00 05 10 15
Jo dan
–
1.0
–
0.5
0.0
0.5
1.0
70 75 80 85 90 95 00 05 10 15
Lebanon
–0.08
–0.04
0.00
0.04
0.08
0.12
70 75 80 85 90 95 00 05 10 15
Mo o c o
–0.08
–0.04
0.00
0.04
0.08
0.12
0.16
70 75 80 85 90 95 00 05 10 15
Sudan
-0.05
0.00
0.05
0.10
0.15
0.20
70 75 80 85 90 95 00 05 10 15
Tunisia
–0.08
–0.04
0.00
0.04
0.08
0.12
70 75 80 85 90 95 00 05 10 15
Tu key
–1.6
–1.2
–0.8
–0.4
0.0
0.4
70 75 80 85 90 95 00 05 10 15
GLGDP VCOP
Yiemen
Sou ce: C ea ed by he au ho
REPS
8,5
372

Figu e A6.
The ola ili y o oil
p ice o e he pe iod
o s udy
0.000
0.002
0.004
0.006
0.008
0.010
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Sou ce: C ea ed by he au ho
Oil p ice
fluc ua ions
and economic
g ow h
373
Figu e A7.
Di e en kinds o oil
p ice ola ili y
0.000
0.002
0.004
0.006
0.008
0.010
0.012
1975 1980 1985 1990 1995 2000 2005 2010 2015
SVCOP VCOP
Sou ce: Calcula ed by he au ho
REPS
8,5
374
Table A1.
Desc ip i e s a is ics
Measu e Y COP VCOP ERD ALD GFC PG SSE INS
Mean 0.055 0.064 0.0007 0.0001 12.930 23.242 3.35 65.92 4.970
Median 0.046 0.049 0.0003 0.0030 14.125 23.128 2.58 70.26 5.200
Maxi 0.897 1.11 0.0103 1.1003 17.0650 26.590 17.63 98.46 6.610
Min 1.331 0.65 0.00006 0.7378 6.90775 19.406 3.10 0.000 0.710
S d.
de . 0.155 0.31 0.00150 0.1297 2.9712 1.366 2.62 27.29 1.086
Ja que
2,035
(0.00)
206
(0.00)
3,9362.4
(0.00)
8,977.66
(0.00)
61.678
(0.00)
9.12
(0.01)
3,630.0
(0.000)
30.58
(0.00)
120
(0.00)
Sou ce: C ea ed by he au ho
Table A2.
Co ela ion ma ix
o MENA oil-expo
coun ies
Va iable Y COP VCOP EPG ERD GFC PG SSE INS
Y1.000 0.270 0.376 0.207 0.078 0.028 0.081 0.151 0.241
COP 0.270 1.000 0.214 0.268 0.075 0.461 0.551 0.286 0.497
VCOP 0.376 0.214 1.000 0.051 0.029 0.010 0.075 0.051 0.119
EPG 0.207 0.268 0.051 1.000 0.042 0.315 0.023 0.512 0.568
ERD 0.078 0.075 0.029 0.042 1.000 0.136 0.013 0.125 0.079
GFC 0.028 0.461 0.010 0.315 0.136 1.000 0.566 0.324 0.326
PG 0.081 0.551 0.075 0.023 0.013 0.566 1.000 0.310 0.493
SSE 0.151 0.286 0.051 0.512 0.125 0.324 0.310 1.000 0.360
INS 0.241 0.497 0.119 0.568 0.079 0.326 0.493 0.360 1.000
Sou ce: Calcula ed by he au ho
Table A3.
Co ela ion ma ix
o MENA oil-impo
coun ies
Va iable GLGDP COP VCOP EPG ERD GFC PG SSE INS
GLGDP 1.000 0.022 0.038 0.192 0.023 0.003 0.143 0.058 0.172
COP 0.022 1.000 0.144 0.102 0.034 0.098 0.175 0.042 0.275
VCOP 0.038 0.144 1.000 0.015 0.146 0.045 0.015 0.009 0.133
EPG 0.192 0.102 0.015 1.000 0.041 0.556 0.594 0.063 0.046
ERD 0.023 0.034 0.146 0.041 1.000 0.038 0.084 0.002 0.171
GFC 0.003 0.098 0.045 0.556 0.038 1.000 0.351 0.520 0.441
PG 0.143 0.175 0.015 0.594 0.084 0.351 1.000 0.054 0.153
SSE 0.058 0.042 0.009 0.063 0.002 0.520 0.054 1.000 0.278
INS 0.172 0.275 0.133 0.046 0.171 0.441 0.153 0.278 1.000
Sou ce: Calcula ed by he au ho
Oil p ice
fluc ua ions
and economic
g ow h
375
Table A4.
Uni oo s a is ics
Va iable ADF PP
COP 13.80 (0.0000)*** 13.792 (0.0000)***
VCOP 4.564 (0.0002)*** 4.575 (0.0002)***
Y217.306 (0.000)*** 365.723 (0.000)***
ER 229.899 (0.000)*** 131.014 (0.000)**
ALD 77.1695 (0.000)*** 99.048 (0.000)**
EPG 61.86 (0.002)*** 66.54 (0.000)***
GFC 12.583 (0.05)* 57.62 (0.000)***
PG 107.05 (0.000)*** 56.2 (0.000)***
SSE 12.27 (0.05)* 42.29 (0.04)**
INS 87.09 (0.000)*** 46.44 (0.047)**
No es: ***Means he coe ficien is significan wi h 1, 5 and 10%; **indica e he coe ficien is significan
wi h p obabili y 5 and 10%; *indica es significan wi h p obabili y 10%
Sou ce: Calcula ed by he au ho
Table A5.
Vola ili y o oil p ices
gene a ed om he
GARCH model
Va iable Coe icien P obabili y
COP(1) 1.179471 0.0000
COP(2) 0.179295 0.0000
Va iance equa ion
C0.00488 0.2825
RESID(1)^2 0.169321 0.0000
GARCH(1) 0.596515 0.0000
T-DIST. DOF 2.967606 0.0000
R-squa ed 0.995065
Adjus ed R
2
0.995057
Du bin-Wa son s a 1.974966
Sou ce: Calcula ed by he au ho
REPS
8,5
376