Udeagha, Maxwell Chukwudi; Ngepah, Nicholas
A icle
A oadmap o a g een economy in Sou h A ica: modelling
echnological inno a ion and ene gy consump ion in he no el
dynamic ARDL simula ions amewo k
Cogen Economics & Finance
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economy in Sou h A ica: modelling echnological inno a ion and ene gy consump ion in he no el
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A oadmap o a g een economy in Sou h A ica:
modelling echnological inno a ion and ene gy
consump ion in he no el dynamic ARDL
simula ions amewo k
Maxwell Chukwudi Udeagha & Nicholas Ngepah
To ci e his a icle: Maxwell Chukwudi Udeagha & Nicholas Ngepah (2024) A oadmap o a
g een economy in Sou h A ica: modelling echnological inno a ion and ene gy consump ion in
he no el dynamic ARDL simula ions amewo k, Cogen Economics & Finance, 12:1, 2295191,
DOI: 10.1080/23322039.2023.2295191
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G oup
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DEVELOPMENT ECONOMICS | RESEARCH ARTICLE
A oadmap o a g een economy in Sou h A ica: modelling
echnological inno a ion and ene gy consump ion in he no el
dynamic ARDL simula ions amewo k
Maxwell Chukwudi Udeagha and Nicholas Ngepah
School o Economics, College o Business and Economics, Uni e si y o Johannesbu g, Johannesbu g, Sou h A ica
ABSTRACT
Sou h A ica’s hea y eliance on ossil uels has posed signi ican challenges o en i -
onmen al sus ainabili y, p ima ily due o he associa ed clima e change conce ns. To
comba hese issues, he Sou h A ican go e nmen has u ned o echnological
inno a ion. Howe e , esea ch examining he combined impac o echnology and
ene gy use on en i onmen al quali y in he coun y emains sca ce. This s udy aims o
ill his gap by u ilizing a no el dynamic au o eg essi e dis ibu ed lag (DARDL) simu-
la ion amewo k o analyze he in luence o a ious ac o s on CO
2
emissions om
1960 o 2020. Key indings include ha echnological inno a ion con ibu es o CO
2
emission educ ion o e bo h sho and long e ms. The "scale e ec " exace ba es
emissions, while he " echnique e ec " mi iga es hem, aligning wi h he en i onmen-
al Kuzne s cu e (EKC) hypo hesis. Addi ionally, ene gy consump ion, o eign di ec
in es men , and indus ial alue-added ha e ad e se impac s on en i onmen al qual-
i y. Su p isingly, inc eased ade openness, despi e sho - e m bene i s, p o es de i-
men al o he en i onmen o e he long e m, suppo ing he pollu ion ha en
hypo hesis (PHH). In ligh o hese indings, he s udy emphasizes he i al ole o
echnological inno a ion in achie ing ene gy secu i y and ecological in eg i y. Sou h
A ica’s go e nmen and policymake s should conside his as a clean echnology
sou ce o add ess clima e change and bols e en i onmen al sus ainabili y.
ARTICLE HISTORY
Recei ed 26 June 2022
Re ised 2 No embe 2023
Accep ed 11 Decembe 2023
KEYWORDS
T ade openness; CO
2
emissions; dynamic ARDL
simula ions; ene gy
consump ion; EKC;
coin eg a ion; economic
g ow h; indus ial alue-
added; Sou h A ica
REVIEWING EDITOR
Ch is ian Nsiah, Baldwin
Wallace Uni e si y, USA
SUBJECTS
Technology; Economics;
En i onmen al Economics;
Indus y & Indus ial S udies
JEL CLASSIFICATIONS
F18; F13; Q56; O13; F1; F41
1. In oduc ion
The ideas o clima e change and global wa ming a e widely accep ed as he bigges isks o he exis ence
o all species on Ea h (Asi e al., 2023a,2023b,2023c; I an e al., 2021a). Since he dawn o his o y, eco-
nomic and en i onmen al en e p ises ha e coexis ed; ye , as human de elopmen has ad anced, i has
signi ican ly agg a a ed he en i onmen by inc easing ca bon dioxide emissions (CO
2
emissions) (Ali
e al., 2022; Udeagha & Ngepah, 2022a). The wo ld is p esen ly s uggling wi h he nega i e e ec s o eco-
logical exposu es and de e io a ion, which cause despai o he majo i y o people, wildli e, and ecosys-
ems e e ywhe e due o he absence o sui able go e nmen al ini ia i es (Ali e al., 2022). The e o e, by
conside ing a a ie y o impo an con ibu o s like enewable ene gy, echnological ad ancemen , expo
pe o mance, and p oduc i i y g ow h, educing CO
2
emissions as a means o c ea ing a sus ainable and
en i onmen ally iendly wo ld has eme ged as a wo hwhile pu sui o con empo a y esea che s (Islam
e al., 2022; Ali e al., 2022; Khalid e al., 2021). The Sus ainable De elopmen Goals (SDGs) ha he UN
has p oposed o be achie ed by 2030 also emphasize he need o a o dable and enewable echnolo-
gies, b oad-based and en i onmen ally iendly p oduc i i y expansion, and echnical inno a ion as ways
o immedia ely add ess global wa ming (Udeagha & Ngepah, 2022b). The 2021 Uni ed Na ions (UN)
CONTACT Maxwell Chukwudi Udeagha [email p o ec ed];[email p o ec ed] School o Economics, College o Business
and Economics, Uni e si y o Johannesbu g, P.O Box 524, Auckland Pa k, 2006 Johannesbu g, Sou h A ica.
ß2024 The Au ho (s). Published by In o ma UK Limi ed, ading as Taylo & F ancis G oup
This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License (h p://c ea i ecommons.o g/licenses/by/4.0/), which
pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed. The e ms on which his a icle has been
published allow he pos ing o he Accep ed Manusc ip in a eposi o y by he au ho (s) o wi h hei consen .
COGENT ECONOMICS & FINANCE
2024, VOL. 12, NO. 1, 2295191
h ps://doi.o g/10.1080/23322039.2023.2295191
Clima e Change Con e ence (COP26), held in Glasgow, Uni ed Kingdom, b ough oge he a numbe o
high- anking decision-make s om all o e he wo ld o discuss he majo p oblems b ough on by global
wa ming. In o de o gua an ee coope a ion o sus ained p og ess owa d he Pa is Ag eemen and UN
F amewo k Con en ion on Clima e Change, he con e ence’s decla ed aim is o limi he inc ease in global
empe a u es o 1.5 deg ees Celsius o e p e-indus ial le els (Uni ed Na ions Clima e Change, 2021).
Acco ding o he In e go e nmen al Panel on Clima e Change (IPCC), global emissions mus each ne
ze o by a leas 2050 o he e o con inue o be "high con idence" ha empe a u e inc eases would be
main ained o ole able le els. The e o e, minimizing CO
2
emissions as an app oach o achie ing a g een
and sus ainable wo ld has become a desi able a ge o mode n esea che s by aking in o accoun a
ange o con ibu ing ac o s including echnological inno a ion and enewable ene gy sou ces (Khalid &
Jalil, 2019; Khalid & Ozdese , 2021; Zheng e al., 2022).
The Wo ld Heal h O ganiza ion (WHO) decla ed a Public Heal h Eme gency o Global Signi icance o
he pneumonia epidemic igge ed by he newly disco e ed co ona i us (2019- nCoV) on Janua y 30,
2020. As an encapsula ed single-s anded RNA i us, i can cause e e y hing om modes (cold-like)
symp oms o se ious espi a o y, diges i e, hepa ic, and neu ological p oblems (I an e al., 2022a). The
exis ing e idence indica es ha he COVID-19 i us is p ima ily ansmi ed by espi a o y d ople s and
di ec con ac . COVID-19 can cause a a ie y o symp oms, including e e , b ea hing di icul ies, a d y
cough, and lung in ec ions ha sp ead o bo h lungs. Globally, COVID-19 is becoming mo e p e alen ,
which has majo e ec s on mac oeconomics as well as social p o ec ion o ce ain people, pa icula ly
in low-income na ions. The COVID-19 epidemic has been causing up oa and ea since 2020. When pan-
demics la e up, he e a e ypically many a ali ies and signi ican economic losses on a wo ldwide scale
(Yang e al., 2021a). Many na ions, including Sou h A ica, used "lockdown" s a egies o p e en i s as
sp ead in 2020. Global pa e ns o ene gy consump ion ha e been signi ican ly a ec ed by go e nmen
ac ions du ing he COVID-19 pandemic, including he closu e o in e na ional bo de s, he con inemen
o indi iduals o hei homes, and limi s on mo emen and ga he ing. The In e na ional Ene gy Agency
(IEA) de ails how economic un es , a el es ic ions, and lockdowns ha e an impac on he wo ld’s
ene gy consump ion in i s la es Global Ene gy Re iew 2020 publica ion (In e na ional Ene gy Agency,
2020). Despi e he ac ha he co ona i us (COVID-19) pandemic educed CO
2
emissions by 5.4% in
2020 as a esul o a el es ic ions, emissions a e expec ed o inc ease in he nea u u e as a esul o
escala ing globaliza ion, ising o eign di ec in es men (FDI), and he esul ing ise in ene gy consump-
ion in nume ous o me ly ene gy-poo geog aphic a eas (Udeagha & Muchapondwa, 2022a).
Ca bon emissions caused by ex ensi e ossil uel use since he indus ial e olu ion ha e se e ely dam-
aged en i onmen al quali y and wo sened he wo ld’s clima e. Ad ancemen s in echnology a e hough
o play a key ole in imp o ing ene gy e iciency, lowe ing ene gy use, and minimizing CO
2
emissions
(Tang e al., 2022). As Udeagha and Ngepah (2022c) ha e demons a ed, i o e s he na ion signi ican
possibili ies o mee he ene gy obliga ion by enabling he na ion o change om ossil- uelled based
ene gy esou ces o enewables; enables he na ion o each highe p oduc i i y le els wi h a easonable
le el o ene gy; and s imula es be e o e all inno a i e hinking p omo ing mo e en ep eneu ial en-
u es h ough enhanced ma ke access and g owing compe i ion. By expanding access o global com-
modi y ma ke s, echnological p og ess can a ac new capi al, inc ease p oduc ion, and boos
employmen and eal wages (Obobisa e al., 2022). Addi ionally, i p omo es wise esou ce managemen ,
which leads o g ea e p oduc i i y g ow h. The massi e accumula ion o esou ce ac o s, knowledge
spillo e s, and he sp ead o echnological b eak h ough may be he e en ual consequences (Udeagha &
Ngepah, 2022d). Enhancing he use o echnology is essen ial o p omo ing a g een economy and help-
ing o educe emissions o g owing CO
2
. Pollu ion and he consump ion o ossil uels a e educed by he
use o elec ic ehicles, hyb id echnologies, and enewable ene gy sou ces (I an e al., 2020;2021c; Lin &
Ma, 2022). As shown by I an e al. (2022b), e icien use o inclusi e g een inancing is essen ial o p o-
mo ing sus ainable economic de elopmen , s imula ing g een ini ia i es, and comba ing global wa ming.
The media ing e ec s show ha he main ansmission mechanisms h ough which g een inance a ec s
g een inno a ion a e economic g ow h, in es men in R&D, and indus ial s uc u e.
In ecen yea s, academics om all a ound he wo ld ha e been inc easingly in e es ed in how
echnological p og ess a ec s he en i onmen . Inno a i e ini ia i es migh include de eloping cu ing-
edge and supe io i ems (goods and se ices) o p ocesses, a no el ma ke ing plan, o a mode n
2 M. C. UDEAGHA AND N. NGEPAH
o ganiza ional app oach o co po a e go e nance, wo kplace design, o close connec ions. To quali y as
inno a i e, he manu ac u ing p ocess should be no el o echnologically sophis ica ed. This is because
inno a i e echnologies ha e been shown in se e al empi ical wo ks o imp o e ecological in eg i y.
Howe e , acco ding o some s udies, echnological de elopmen has sped up he a e o en i onmen al
de e io a ion (A su e al., 2021; Udeagha & Muchapondwa, 2023a). Acco ding o esea ch by he
In e go e nmen al Panel on Clima e Change (IPCC, 2018), ini ia i es o ad ance en i onmen al s anda ds
and echnological ad ancemen migh educe he quan i y o an h opogenic emissions eleased in o he
a mosphe e. Howe e , he mos common and imp o ed measu es a e esea ch and de elopmen (R&D)
engagemen s and pa en solu ions (Kuang e al., 2022). This dynamic in eg a ion, which may assis shi
ene gy supplies om non- enewable sou ces o ones ha a e mo e e ec i e and ecologically espon-
sible, hea ily depends on echnological imp o emen s (Rahman e al., 2022).
On he one hand, on Oc obe 29, 2010, he Technological Inno a ion Agency (TIA) o Sou h A ica
was ounded o help he coun y in championing and speeding up echnological p og ess so ha i
could be ad anced and deployed o imp o e he economy and he high quali y o li e o all Sou h
A icans (Van Zyl, 2011). The goal o he o ganiza ion is o spu inno a ion in o de o add ess he a y-
ing demands o Sou h A ica and he en i e A ican con inen , as he gene a ion o new, con ex -speci ic
knowledge is an essen ial elemen o echnology adop ion. A signi ican ac o in his uncommon si u-
a ion is Sou h A ica’s young popula ion, wi h a median age o abou 20 yea s. The in iguing p ospec
o ans o ma ion in he s uc u e and con en o pos seconda y educa ion and aining is o e ed by
his pa icula gene a ion. I also unde lines he alue o a combined echnical educa ion sys em ha is
led by he go e nmen and indus y. The no able appeal o Sou h A ica o ake pa he BRIC coun ies
con i med he g owing ela ions be ween ha coun y and B azil, China, Russia, and India. This mo e
signals ano he s ep o he na ion’s ad ancemen o echnology inno a ion and change. Addi ional con-
side a ions whe e home-g own echnological ad ance migh ha e a consequence include heal hca e
e o m, how socie al change in luences li elihood oppo uni ies, and how he inancial mel down in he
"ad anced economies" dis up s he wo ld ma ke and aid. These p oblems ha e been add essed in a i-
ous ways by Sou h A ica. The Depa men o Science and Technology i s de eloped he "Ten-Yea
Inno a ion Plan o Sou h A ica" in 2008 o "impac he o e all Sou h A ica’s p og ession owa ds a
knowledge-based wo k o ce, in which he manu ac u ing and di usion o in o ma ion leads o economic
bene i s and en iches all ields o human endea ou ." The 2007 Na ional Indus ial Policy F amewo k
Indus ial Policy Ac ion Plan, which also se he objec i e o hal ing unemploymen and po e y by
2014 wi h apid g ow h o a leas 6% s a ing in 2010, also ou lines he go e nmen ’s comp ehensi e
indus ializa ion s a egy. Sou h A ica’s Accele a ed and Sha ed G ow h Ini ia i e includes his s a egy.
Las bu no leas , one o he en s a egic p io i ies s ipula ed in he P esidency’s Medium-Te m
S a egic F amewo k, which was un eiled in July 2009, is he equi emen o boos economic g ow h
and es uc u e he economy o p oduce espec able employmen and highe quali y o li e." The TIA
could be iewed as a g oup ha helps he key knowledge p o ide s and he social and co po a e en e-
p eneu s communica e wi h one ano he . To b idge his gap, he agency will employ a ange o echni-
ques, as indica ed in i s ounding documen . The modi ica ion o human ingenui y, he exploi a ion o
local and in e na ional pa ne ships, and he de elopmen o he coun y’s dynamic capaci ies a e some
o hese ins umen s. Meanwhile, echnological ad ancemen s and p og ess in Sou h A ica ha e
subs an ially educed CO
2
emissions in he ollowing ways: (i) he c ea ion o ca bon-emission- educing
end- o-end pipeline a chi ec u es, (ii) he u iliza ion o ene gy-e icien p ocessing me hods, and (iii)
modi ica ions o uel mixing and oil combina ion mode niza ion. Th ough each o hese a enues, inno a-
i e echnology imp o es ene gy e iciency, which signi ican ly lowe s he na ion’s ca bon pollu ion.
Mo e c ucially, Sou h A ica’s sizeable in es men s in R&D and pace o inno a ion a e among he ac o s
ha ha e con ibu ed signi ican ly o he imp o emen o he na ion’s en i onmen al s ewa dship.
Addi ionally, he na ion has es ablished a numbe o policies o c ea e s ong echnologies ha a e
essen ial o educing he in ensi y o emissions om indus ial ac i i ies and o he comme cial sec o s
ha en ail high emissions as pa o a signi ican s a egy o comba en i onmen al damage. These cha -
ac e is ics make Sou h A ica an excellen choice o ou s udy, which looks a how echnological inno -
a ion and ene gy use join ly a ec ecological quali y.
COGENT ECONOMICS & FINANCE 3
Sou h A ica, on he o he hand, is a pa o he BRICS (B azil, Russia, India, and China) alliance and
one o he la ges eme ging ma ke s. E en hough i s e ia y se ice sec o s (including inancial se ices,
en al p ope ies, and p o essional se ices) ha e g own in p ominence, he coun y’s p ima y and sec-
onda y indus ies include mine al ex ac ion, indus ial p oduc ion, and anspo a ion—con inue o
make a majo con ibu ion o he GDP (S a is ics Sou h A ica, 2019). In con as o o he BRICS coun-
ies, Sou h A ica’s economy has gi en a lo o weigh on coal as an ene gy sou ce. Mo eo e 80% o
Sou h A ica’s elec ici y comes om coal, while only 7% comes om enewable sou ces (A ican
De elopmen Bank G oup, 2019; Udeagha & Ngepah, 2019). Despi e in e na ional o ganiza ions manda -
ing he use o enewable ene gy and a educ ion in coal mining, eplacing all o Sou h A ica’s coal- i ed
powe s a ions is inc edibly challenging. Re iewing ene gy policy in ligh o he p esen poli ical, social,
economic, and en i onmen al condi ions is ano he s ep in he e alua ion o an al e na e powe sou ce
(Udeagha & Ngepah, 2020). Howe e , a global compa ison o Sou h A ica’s g eenhouse gas (GHG) emis-
sions sugges s ha i has one o he mos ca bon-in ensi e economies globally. In ac uali y, Sou h A ica
is he mos ca bon-in ensi e de eloping coun y ha does no p oduce any oil, excluding island coun-
ies, based on pe capi a CO
2
equi alen emissions in 2010 (EIA, 2010). Fu he mo e, Sou h A ica is he
la ges emi e on he A ican con inen , p oducing 42% o o al GHG emissions. Sou h A ica p oduces
mo e CO
2
han he whole Sub-Saha an A ican (SSA) con inen (EIA, 2010). In 2000, Sou h A ica was
epo ed o ha e p oduced 461 million ons CO
2
equi alen o g eenhouse gas emissions, 83% o which
we e connec ed o ene gy supply and consump ion, 7% o indus ial ope a ions, 8% o ag icul u al, and
2% o was e. Since uel combus ion accoun s o 81 pe cen o he indus y’s emissions and ugi i e
emissions om uel accoun o he emaining 19%, he ene gy sec o is by a he la ges con ibu o o
emissions in he na ion wi h 380,988Gg CO
2
. One ac o ha signi ican ly con ibu ed o Sou h A ica’s
ex emely high ene gy- ela ed emission le els was he p e-democ a ic go e nmen ’s delibe a e p omo-
ion o in es men in ene gy-in ensi e sec o s o he economy, such as aluminium and o he non- e ous
me al bene icia ion ( he so-called "mine al-ene gy complex," iden i ied by Fine & Rus omjee, 1996), p io
o 1994. Ano he eason o Sou h A ica’s high emissions is he ca bon in ensi y o i s hea ily coal-based
elec ical gene a ion base, which accoun s o 90% o all emissions (Udeagha & Ngepah, 2021a). Sou h
A ica is he wo ld’s 14 h la ges emi e o GHGs, and a hea y eliance on coal is o blame o he
majo i y o he CO
2
emissions. Un eiling a d a powe plan, howe e , indica es a signi ican shi away
om he uel and owa d gas and enewable ene gy sou ces. Despi e he ac ha coal will con inue o
play a ole o decades, he plan calls o no new plan s o be buil a e 2030 and he shu down o
ou - i hs o he capaci y by 2050. The coun y has also ag eed o peak i s emissions be ween 2020 and
2025, allowing hem o s abilize o a ound en yea s be o e s a ing o d op. Du ing he Con e ence o
he Pa ies (COP26) in Glasgow, he US, UK, F ance, Ge many, and he EU p oposed o p o ide Sou h
A ica $8.5 billion o help he coun y educe i s eliance on coal. (h ps://www.bbc.com/news/wo ld-
a ica-59135169). This pa adigm-shi ing e en has he po en ial o aid he coun y in g adually shu ing
down i s coal- i ed powe acili ies and con e ing o enewable ene gy sou ces, which would educe
g eenhouse gas emissions. In ligh o he e idence p o ided abo e, Sou h A ica makes a s ong case o
conside a ion in sepa a e esea ch ha in es iga es he combined in luence o echnological inno a ion
and ene gy use on pollu an emissions.
The p esen s udy dis inguishes i sel om ea lie esea ch by add essing se e al c i ical limi a ions in
he exis ing body o knowledge ega ding he in e ac ions be ween echnological inno a ion, ene gy
usage, and hei impac s on en i onmen al quali y in he Sou h A ican con ex . This esea ch concen-
a es speci ically on Sou h A ica. Fi s , p io s udies o en gene alize indings o a global o egional
le el, po en ially o e looking he unique challenges and dynamics o indi idual coun ies. By explo ing
his ela ionship wi hin a Sou h A ican con ex , he s udy p o ides insigh s ha a e mo e ailo ed o he
na ion’s speci ic en i onmen al and economic ci cums ances. Second, unlike p io esea ch ha p edom-
inan ly employed con en ional ARDL amewo ks and o he coin eg a ion echniques, his s udy adop s
Jo dan and Philips (2018) dynamic ARDL simula ions app oach. This ad anced echnique enables
esea che s o model and o ecas posi i e and nega i e changes in he da a while assessing bo h sho -
e m and long- e m ela ionships be ween a iables. This me hodological inno a ion enhances he
obus ness o he analysis. The s udy in oduces a no el aspec by applying he equency domain caus-
ali y (FDC) app oach, as sugges ed by B ei ung and Candelon (2006). FDC is a mo e sophis ica ed and
4 M. C. UDEAGHA AND N. NGEPAH
comp ehensi e me hod o assessing causali y be ween a iables o e a ious ime scales, including
long, sho , and medium e ms. I p o ides a mo e comple e unde s anding o how echnological inno -
a ion and ene gy consump ion in luence en i onmen al quali y in di e en empo al dimensions. Also,
unlike ea lie wo ks, his s udy accoun s o s uc u al b eaks ha can in luence he ela ionships
be ween echnological ad ancemen , ene gy usage, and CO
2
emissions. S uc u al b eaks a e ch onic in
economic and en i onmen al da a, and igno ing hem can lead o un eliable and inconsis en esul s. By
add essing his issue, he esea ch con ibu es o mo e accu a e and eliable indings. This s udy del es
in o mul iple ac o s, including echnological inno a ion, ade openness, indus ial g ow h, o eign di -
ec in es men , echnique e ec , and scale e ec , o ho oughly unde s and hei e ec s on CO
2
emis-
sions in Sou h A ica. The comp ehensi e app oach o e s a nuanced pe spec i e on he complexi ies o
ansi ioning o a g een economy in he egion. In summa y, he s udy o e s an inno a i e pe spec i e
on how echnological inno a ion and ene gy consump ion in luence en i onmen al quali y in he Sou h
A ican con ex . I s unique geog aphical ocus, ad anced me hodology, conside a ion o s uc u al
b eaks, and comp ehensi e analysis o key ac o s con ibu e o a iche unde s anding o his complex
ela ionship, se ing i apa om ea lie esea ch in he ield.
Fu he mo e, p e ious s udies ha ha e explo ed he link be ween echnological inno a ion and CO
2
emissions, while conside ing ade openness, o en elied on a simpli ied ade p oxy, which has been
c i icized o i s limi ed ep esen a ion o he complex en i onmen al impac o ade openness.
Typically, hese s udies used ade in ensi y (TI), which is calcula ed as he a io o a coun y’s o al ade
(expo s plus impo s) o i s GDP, o measu e ade openness. Howe e , his measu e o ade openness
has signi ican limi a ions. I p ima ily e lec s a na ion’s ela i e ade pe o mance wi hin i s own econ-
omy bu ails o cap u e he ue ex en o a na ion’s engagemen in in e na ional ade o i s ecological
consequences. This esul s in an inaccu a e ep esen a ion o he en i onmen al e ec s o ade open-
ness. One no able issue wi h he TI-based measu e is i s endency o classi y la ge and mo e p ospe ous
economies as "closed" simply because hey ha e highe GDPs. Fo example, eme ging coun ies like
Sou h A ica, Japan, China, F ance, he Uni ed S a es, Ge many, and o he s a e un ai ly labeled as closed
economies. Meanwhile, less de eloped na ions wi h lowe GDPs, such as Togo, Nige ia, Ghana, Uganda,
Venezuela, Zambia, and Zimbabwe, a e inaccu a ely ca ego ized as open economies. This misclassi ica-
ion obscu es he eal en i onmen al impac o ade openness, as i penalizes economically success ul
coun ies o hei highe GDPs while alsely labeling economically challenged na ions as open.
Consequen ly, elying solely on TI o ep esen ade openness no only o e simpli ies he concep bu
also in oduces signi ican dis o ions in classi ying coun ies, pa icula ly in he con ex o en i onmen al
analysis. I is e iden ha he limi a ions o he TI-based measu e wa an a mo e comp ehensi e and
accu a e app oach o assessing ade openness and i s en i onmen al implica ions.
Taking in o conside a ion he a o emen ioned gaps in he li e a u e, his esea ch seeks o add ess
signi ican gaps in he exis ing li e a u e by sys ema ically examining he combined e ec s o echno-
logical inno a ion and ene gy consump ion on en i onmen al quali y in Sou h A ica om 1960 o 2020
wi hin he amewo k o he En i onmen al Kuzne s Cu e (EKC). The s udy makes se e al no able con i-
bu ions: i s , he esea ch con ibu es heo e ically by explo ing he exis ence o he EKC heo y when
conside ing he join in luence o echnological inno a ion and ene gy usage wi hin he Sou h A ican
con ex . This is a no el and essen ial addi ion o he li e a u e, as ea lie s udies o en ocused on indi-
idual componen s o neglec ed his speci ic combina ion. Second, he s udy in oduces a unique
app oach by employing he dynamic au o eg essi e dis ibu ed lag (DARDL) simula ions amewo k. This
me hodology allows o a comp ehensi e in es iga ion o he ela ionships be ween key a iables such
as echnological inno a ion, ene gy consump ion, and CO
2
emissions in Sou h A ica. This is a no able
depa u e om con en ional app oaches and opens he doo o a mo e nuanced unde s anding o he
dynamics in ol ed. This app oach also o e s he ad an age o isualizing and p edic ing posi i e and
nega i e da a a ia ions ins an ly. I also allows o an in-dep h examina ion o bo h sho - and long-
e m connec ions among he a iables being s udied. This is a signi ican imp o emen o e he con en-
ional ARDL echnique, add essing i s limi a ions and p o iding mo e eliable and objec i e esul s.
Thi d, while en i onmen al and economic s udies o en encompass a global o egional scope, his
esea ch concen a es speci ically on Sou h A ica. This in-dep h, localized analysis is c ucial because di -
e en coun ies may ha e dis inc challenges, p io i ies, and policy implica ions when ansi ioning o a
COGENT ECONOMICS & FINANCE 5
g een economy. The s udy explo es a ange o signi ican a iables, including echnological inno a ion,
ade openness, indus ial g ow h, o eign di ec in es men , and he echnique and scale e ec s. This
comp ehensi e app oach can o e a mo e comple e unde s anding o he ac o s in luencing CO
2
emis-
sions in Sou h A ica. Fou h, he s udy enhances me hodological schola ship by employing he FDC
s a egy. This app oach, ecommended by B ei ung and Candelon (2006), is pa icula ly e ec i e in
assessing sus ained causali y be ween a iables o e a ious ime ames, including sho , medium, and
long e ms. By conside ing bo h sho and long- e m e ec s, he esea ch akes in o accoun he ime
dimension o en i onmen al policies and echnological ansi ions. This p o ides mo e ealis ic and
nuanced insigh s in o he impac s o hese ac o s. The esea ch employs second-gene a ion econome -
ic me hodologies o accu a ely conside and cap u e he e ec s o s uc u al b eaks. P e ious s udies
o en igno ed his aspec . Recognizing hese s uc u al b eaks is c ucial, as hey a e known o ha e a
las ing impac on a ious mac oeconomic indica o s. The s udy conduc s s uc u al b eak uni oo es s,
ollowing Na ayan and Popp’s me hod, o ensu e he eliabili y o esul s. Finally, his esea ch in oduces
a no el and inno a i e measu e o ade openness based on he wo k o Squalli and Wilson (2011) o
in es iga e he ela ionship be ween echnological inno a ion and en i onmen al quali y while accoun -
ing o ade openness. Unlike p e ious s udies ha elied on he con en ional ade in ensi y measu e,
his app oach conside s wo dimensions o ade openness: he con ibu ion o ade o GDP and ade
size ela i e o o eign ma ke s. This mo e comp ehensi e measu e o e s a unique pe spec i e on he
impac o ade openness. In summa y, his esea ch p esen s a comp ehensi e and inno a i e app oach
o unde s anding he complex in e play be ween echnological inno a ion, ene gy consump ion, and
en i onmen al quali y. I s con ibu ions encompass heo e ical ad ancemen s, me hodological inno a-
ions, s uc u al b eak conside a ions, and a no el ade openness measu e, collec i ely enhancing he
schola ly landscape in his ield. Thus, he esea ch’s no el y lies in i s localized, comp ehensi e, and o -
wa d-looking app oach o unde s anding he g een ansi ion in Sou h A ica. I conside s a ious key
ac o s, examines bo h sho and long- e m impac s, and p o ides ac ionable policy ecommenda ions,
se ing i apa om o he s udies in he ield.
The emaining sec ions o he a icle a e a anged as ollows. The li e a u e on he ela ionship
be ween echnological ad ancemen and CO
2
emissions is e iewed in Sec ion 2. The ma e ial and
me hodology a e p esen ed in Sec ion 3; he indings a e co e ed in Sec ion 4.Sec ion 5 concludes wi h
policy implica ions.
2. Li e a u e e iew and summa izing knowledge gap
This pa is b oken up in o wo subsec ions in his in es iga ion. In he i s subsec ion, we explo e and
p o ide scien i ic in es iga ions on he connec ion be ween echnological ad ancemen and en i on-
men al quali y, and in he second subsec ion, we summa ize he gaps in he li e a u e.
2.1. Re iew o p e ious li e a u e
The in luence ha echnical inno a ion plays in imp o ing ecological in eg i y has only been he subjec
o a ew s udies globally. Howe e , he indings o hese s udies a e equen ly inconsis en and con a-
dic o y ac oss a ange o analy ic se ings and egions unde in es iga ion. While some s udies e ealed
ha echnological inno a ion may enhance he en i onmen in a numbe o ways, o he au ho s ha e
made he case ha ad ancing echnology wo sens he s a us o he en i onmen .
Fo an example, Ra ique e al. (2022) looked in o empi ical in e ela ions be ween he use o enew-
able ene gy, o eign di ec in es men , medium- and high- ech indus ies, economic complexi y, human
capi al, powe dis ance, unce ain y a oidance, and masculini y e sus eminini y in he sample o 76
Bel and Road economies. Using se ies spanning he yea s 1996 h ough 2019, a comple e amewo k
o econome ic es ing was de eloped ha made use o bo h he gene alized me hod o momen s and
he momen s quan ile eg ession me hodology. The au ho s’ini ial p edic ions ha medium and high-
ech indus ies, as opposed o FDI, in luenced he di usion o low-ca bon ene gy ac oss sec o s we e
co obo a ed by ela ed da a. The use o enewable ene gy is nega i ely impac ed by changes in human
capi al. To in eg a e hose esul s in o u u e ene gy planning, he au ho s p o ided a numbe o policy
6 M. C. UDEAGHA AND N. NGEPAH
ecommenda ions as well as a me hodological no e. Simila ly, Lin and Ma (2022) used in o ma ion on
264 p e ec u e-le el Chinese ci ies om 2006 o 2017 o examine he impac o he u ban inno a ion
en i onmen on he e ec o echnical ad ancemen s on CO
2
emissions. The empi ical esul s demon-
s a ed ha a ious ci y ypes a e impac ed by echnological imp o emen s in di e en ways. P io o
2010, he e ec on Chinese ci ies was negligible, howe e a e 2010, echnological de elopmen s may
con ibu e o a dec ease in CO
2
emissions. Second, echnical de elopmen s can indi ec ly educe CO
2
emissions by enhancing economic p ocesses. Thi dly, when he en i onmen o u ban inno a ion is
aken in o conside a ion, go e nmen expendi u e canno signi ican ly change he ma ginal impac o
echnological ad ancemen s. Simila o his, Obobisa e al. (2022), who iden i ied ins i u ional excellence
and echnological inno a ion as e ec i e app oaches o educe ca bon emissions and achie e sus ain-
able de elopmen , looked a how each con ibu ed o emissions educ ions in 25 A ican coun ies
be ween 2000 and 2018. The au ho s claim ha he usage o enewable ene gy and echnological
ad ancemen signi ican ly cu CO
2
emissions. On he o he hand, he e ec i eness o ins i u ions, he
g ow h o he economy, and he eliance on ossil uels as a sou ce o ene gy ha e a nega i e impac
on CO
2
emissions. The au ho s ecommended ha in o de o A ican coun ies o achie e hei objec-
i es o sus ainable de elopmen , hey inc ease hei in es men in echnical inno a ion and enewable
ene gy p ojec s. Addi ionally, Kuang e al. (2022) used panel da a o analyze he link be ween echnical
de elopmen , enewable ene gy, and CO
2
emissions in China om 1990 o 2018 and ound ha hese
ac o s had a long- e m, signi ican nega i e impac on CO
2
emissions. Fu he mo e, he e is li le p oo
ha echnical inno a ion and economic p og ess a e ela ed in he nea un. The applica ion o echnical
inno a ion has ad an ageous ex e nali ies, acco ding o he au ho s. Rahman e al. (2022) examined he
impo ance o con ibu ing a iables o CO
2
emissions dec ease in he 22 mos indus ialized na ions
globally h oughou he 1990–2018 da a pe iod. The esea che s disco e ed ha bo h expo -quali y and
enewable ene gy help o lowe CO
2
emissions. Con a y o he nega i e shocks o coun e incen i es o
hese a iables, which lead o an inc ease in CO
2
emissions, he posi i e s imuli o echnological inno -
a ion as measu ed by esea ch and de elopmen in es men and expo quali y index educe hese
emissions. Addi ionally, using da a om 1991 o 2018, Habiba e al. (2022) in es iga ed he impac s o
inancial ad ancemen , echnological ad ancemen , and he use o enewable ene gy on ca bon emis-
sions o he op wel e emi e s. Fu u e echnical ad ancemen s and he use o enewable ene gy sou -
ces will play a majo ole in educing CO
2
emissions, wi h he use o non- enewable ene gy sou ces
s eadily declining. The au ho s ecommended e o s o minimize CO
2
emissions in o de o achie e sus-
ainable de elopmen based on hei indings. Using second-gene a ion ime-se ies panel da a me hod-
ologies, Vi enu-Sackey and Acheampong (2022) in es iga ed he e ec s o economic policy unce ain y
(EPU) and echnological ad ancemen on CO
2
emissions in a panel o 18 indus ialized na ions om
2005 o 2018. To manage he e ogenei y, endogenei y, and simul anei y in he panels, he au ho s u i-
lized h ee eliable long- un es ima o s: wo-s age leas squa es (2SLS), panel gene alized me hod o
momen s (GMM), and gene alized leas squa es (GLS). They ound ha economic expansion signi ican ly
and a ou ably a ec ed CO
2
emissions, bu ha his e ec peaked a a ce ain a e o g ow h and hen
d opped, indica ing ha he sample had an in e ed U-shaped en i onmen al Kuzne s cu e (EKC) con-
nec ion. Second, di e en coun ies ha e di e en e ec s o EPU on CO
2
emissions. Fo ins ance,
whe eas high le els o EPU ha e a signi ican impac in high-pollu ion coun ies, hey ha e less e ec in
low-pollu ion na ions. Thi d, se e al ac o s, including u baniza ion, he use o enewable ene gy sou ces,
and esea ch and de elopmen (R&D), all ha e an impac on CO
2
emissions. The au ho s emphasized
ha e en in indus ialized na ions, he e is a a ied link be ween ca bon emissions and economic indica-
o s. The pollu ion halo e ec holds ue o low-pollu ion coun ies whe eas he pollu ion ha en
hypo hesis (PHH) holds ue in high-pollu ion ones. A one-size- i s-all s a egy o educing emissions,
acco ding o he s udy’s au ho s, is no he bes cou se o ac ion because, in he ace o e a ic eco-
nomic policies, no e e y coun y’s a e o u baniza ion, FDI in lows, R&D expendi u es, and use o
enewable ene gy di ec ly a ec CO
2
emissions.
Fu he mo e, Adebayo e al. (2022) employed cu ing-edge Mo le wa ele analysis o o e a esh
pe spec i e on he dynamic connec ion be ween CO
2
emissions and economic g ow h, he use o
enewable ene gy, ade openness, and echnological inno a ion in he Po uguese economy. The s udy
applied con inuous wa ele ans o m, wa ele co ela ion, mul iple and pa ial wa ele cohe ence, and
COGENT ECONOMICS & FINANCE 7
dynamic ARDL simula ions model has ecen ly been de eloped by Jo dan and Philips (2018) o add ess
he laws ha a e inhe en in he simple ARDL model. This model can e ec i ely and e icien ly esol e
he obs acles and esul in e p e a ions connec ed wi h he simple ARDL app oach. This ecen ly c ea ed
amewo k has he abili y o s imula e and plo o au oma ically o ecas g aphs o (posi i e and nega-
i e) changes in he a iables and es ima e he linkages o bo h he sho un and long un. The main
bene i o his amewo k is i s capaci y o an icipa e, simula e, and quickly depic p obabilis ic change
o ecas s on he dependen a iable in one explana o y a iable while main aining he cons an s o
o he eg esso s. The dynamic ARDL e o co ec ion echnique is used in his wo k, which bases i on
he mul i a ia e no mal dis ibu ion o he pa ame e ec o . We use he g aphs o in es iga e bo h he
explana o y a iable’s ac ual change and i s impac on he dependen a iable. Following is a p esen a-
ion o he unique dynamic ARDL simula ions model:
DInCO2 ¼a0þ 0InCO2 −1þu1DSE þq1SE −1þu2DTE þq2TE −1þu3DTECH þq3TECH −1þu4DEC
þq4EC −1þu5DFDI þq5FDI −1þu6DOPEN þq6OPEN −1þu7DIGDP þq7IGDP −1þe
(8)
3.7. F equency domain causali y es
The equency domain causali y (FDC) echnique, a eliable es ing ool p oposed by B ei ung and
Candelon (2006), is also used in his wo k o in es iga e he causal connec ions be ween he a iables
being s udied. FDC makes i possible o p edic he esponse a iable a a gi en ime equency, in con-
as o he adi ional G ange causali y app oach, which makes i nea ly impossible o do so. I also
makes i possible o cap u e pe manen causali y o he medium-, sho -, and long- e m among he a -
iables being s udied. In his s udy, a obus ness check is also conduc ed using his es .
4. Empi ical esul s and hei discussion
4.1 Summa y s a is ics
Fo a simple o e iew o he key in e es ing a iable s a is ics, please e e o Table 3. The mean, max-
imum, minimum, and s anda d de ia ion a e included in he se ies’summa y s a is ics. Based on yea ly
obse a ions o he annual ime se ies om 1960 o 2020, Table 3 p o ides he summa y s a is ics. The
cha ac e is ics and ai s o he s udied a iables used in his s udy a e p esen ed in Table 3.
Addi ionally, Table 3 demons a es ha echnique e ec (TE) has he g ea es mean alue (60.316),
whe eas CO
2
emission has he smalles mean alue (0.264). The g ea es maximum (80.717) and lowes
minimum (0.084) alues o TE and CO2 emissions, espec i ely, we e no ed. The ac ha i ually all o
he a iables’s anda d de ia ions we e lowe han hei mean alues shows ha all o he a iables pe -
o m well. Ku osis esul s show ha all a iables ha e pla yku ic dis ibu ions, meaning ha all es i-
ma ed pa ame e s ha e posi i e and ku osis alues unde h ee. Acco ding o he skewness indings,
Table 3. Desc ip i e s a is ics.
Va iables Mean Median Maximum Minimum S d. De Skewness Ku osis J-B S a P obabili y
CO
2
0.264 0.238 0.477 0.084 0.120 0.217 1.652 4.682 0.196
SE 7.706 7.959 8.984 6.073 0.843 −0.511 2.156 4.102 0.129
TE 60.316 63.754 80.717 36.880 12.663 −0.387 2.082 3.422 0.181
TECH 9.360 9.255 10.545 8.210 0.766 0.082 1.634 4.499 0.105
EC 4.220 4.422 4.840 3.177 0.527 −0.558 1.921 5.621 0.160
FDI 13.203 13.286 14.659 11.913 0.738 0.056 2.463 0.702 0.704
IGDP 3.513 3.580 3.813 3.258 0.161 −0.215 1.697 4.474 0.107
OPEN 6.060 6.512 7.665 2.745 1.329 0.636 2.077 5.757 0.156
Sou ce: Au ho s’calcula ions.
Desc ip i e s a is ics p o ide a concise summa y o da a, and help o condense la ge da ase s in o key measu es, making i easie o unde -
s and and wo k wi h he da a. They a e undamen al in making da a mo e manageable and comp ehensible. They a e o en he s a ing
poin o deepe da a analysis, in e p e a ion, and decision-making in a ious ields, including esea ch, business, and public policy.
CO
2
:CO
2
emissions; SE: Scale e ec ; TE: Technique e ec ; TECH: Technological inno a ion; EC: Ene gy consump ion; FDI: Fo eign di ec in es -
men ; IGDP: Indus y, alue added.
14 M. C. UDEAGHA AND N. NGEPAH
CO
2
, echnological inno a ion (TECH), o eign di ec in es men (FDI), and ade openness (OPEN) all
ha e long igh - ail dis ibu ions (posi i e skewness), whe eas he o he a iables ha e long le - ail dis i-
bu ions (nega i e skewness). The Ja que-Be a s a is ic e ealed ha all o he a iables had no mal dis i-
bu ions, cons an a iances, and ze o co a iance, indica ing ha he a iables we e app op ia e o
es ima ion.
4.2. O de o in eg a ion o he espec i e a iables
S a ing wi h he uni oo es s such as KPSS, ADF, PP, and DF-GLS, he empi ical s udy in es iga es he
s a iona i y cha ac e is ics o he a iables. Table 4 p o ides he ele an ou comes o he uni oo ana-
lysis. Acco ding o hese es s, he es s a is ics’s a is ical signi icance poin s o a mixed o de o a i-
able in eg a ion. The expe imen s show ha al hough all he a iables a e s a iona y a he i s
di e ence, some a e non-s a iona y a le el.
4.3. Lag leng h selec ion esul s
The in es iga ion o he ideal lag leng h, which depends on he numbe o lags selec ed, comes a e
he examina ion o he uni oo and o de o in eg a ion o he nomina ed model. The lags’selec ion
c i e ia a e displayed in Table 5. Since he model pe o ms be e a lag 1 han lag 0 o 4 based on SIC
alue o 19.094, he whole lag selec ion c i e ia ha e been employed o apply he ARDL bounds es in
his s udy (see Table 5).
Table 4. Uni oo analysis.
Va iable
Dickey-Fulle
GLS
Phillips-
Pe on
Augmen ed
Dickey-Fulle
Kwia kowski-Phillips-
Schmid -Shin Na ayan e al. (2010) Uni Roo Tes
(DF-GLS) (PP) (ADF) (KPSS) Model 1 Model 2
Le el Tes –S a is ics alue B eak-Yea ADF-s a B eak-Yea ADF-s a
InCO
2
−0.570 −0.464 −1.152 0.966 1982:1985 −3.132 1987:1994 −8.160
InSE −0.116 −0.079 −1.308 0.833 1979:1988 −2.914 1982:1990 −7.601
InTE −0.112−0.076 −1.268 0.848 1979:1990 −1.939 1982:1994 −6.791
InTECH −0.254 −0.284 −2.999 0.255 1995:2000 −4.318 2008:2011 −7.821
InEC −0.011 −0.014 −0.366 1.300 1982:1989 −4.372 1985:1991 −8.521
InFDI −0.032−0.001 −0.012 0.640 2001:2006 −2.021 2004:2010 −8.362
InOPEN −0.072 −0.082 −1.335 1.0801996:2001 −3.053 2003:2009 −7.318
InIGDP −0.046 −0.071−1.718 1.060 1972:1985 −3.815 1982:1991 −7.521
Fi s di e ence C i ical alue (1%, 5%, and 10%)
DInCO
2
−0.995 −0.996 −7.176 0.705 1999:2005 −4.801 1980:1991 −5.832
DInSE −0.695 −0.707 −5.319 0.585 1983:1997 −5.831 1985:1995 −6.831
DInTE −0.694 −0.707 −5.316 0.589 1991:2000 −8.531 1987:1996 −5.893
DInTECH −1.023 −1.034 −7.473 0.424 1999:2003 −4.841 2006:2010 −5.983
DInEC −1.105 −1.121 −8.142 0.586 1985:1993 −5.921 1989:1997 −7.942
DInFDI −0.207 −0.209 −6.443 0.609 2005:2008 −6.831 2001:2008 −6.973
DInOPEN −0.935 −0.938 −6.699 0.626 1996:2004 −6.842 2001:2007 −8.942
DInIGDP −0.799 −0.801 −5.878 0.431 1975:1990 −7.742 1988:1992 −7.892
Sou ce: Au ho s’calcula ions.
No e:, and deno e s a is ical signi icance a 10%, 5% and 1% le els, espec i ely. MacKinnon’s(1996) one-sided p- alues. Lag
Leng h based on SIC and AIC. P obabili y-based on Kwia kowski-Phillips-Schmid -Shin (1992). The c i ical alues o Na ayan-Popp uni oo
es wi h wo b eaks a e ollowed by Na ayan e al. (2010). All he a iables a e ended.
Table 5. Lag leng h c i e ia.
Lag LogL LR FPE AIC SC HQ
0 178.453 NA 3.2e-12 −6.594 −6.331 −6.493
1 607.095 857.28 1.5e-18 −21.195 −19.094−20.390
2 661.093 108 1.4e-18 −21.388 −17.448 −19.877
3 719.755 117.32 1.2e-18−21.759 −15.981 −19.544
4 784.113 128.721.3e-18 −22.350−14.733 −19.430
Sou ce: Au ho s’calcula ions.
No e:indica es lag o de selec ed by he c i e ion.
COGENT ECONOMICS & FINANCE 15
4.4. Coin eg a ion es esul s
The esul s o he coin eg a ion es a e p o ided in Table 6, which demons a e ha he null hypo hesis
ha he e is no coin eg a ion be ween he a iables is ejec ed since he F-s a and -s a c oss all uppe
bounda ies, indica ing s a is ical e idence o a long- e m link be ween he a iables. We compu ed he
long- and sho - un coe icien s o he a iables unde discussion a e achie ing a coin eg a ion connec-
ion be ween he a iables.
4.5. Diagnos ic s a is ics es s
The esea ch hus employs se e al diagnos ic s a is ical p ocedu es, and hei quan i a i e indings a e
p esen ed in Table 7, in o de o gua an ee ha ou selec ed model is us wo hy and accu a e. Gi en
ha he model in use clea ed all es ing p ocedu es, he empi ical indings imply ha i i s co ec ly.
The B eusch God ey LM es demons a es ha he model is no a ec ed by se ial co ela ion o au o-
co ela ion issues. E idence ob ained using he Ramsey RESET es demons a es ha he model is no
mis-speci ied. Bo h he B eusch-Pagan-God ey es and he ARCH es a e used o de e mine i he
model exhibi s he e oscedas ici y. Acco ding o he empi ical esul s, he e oscedas ici y is minimal and
no a conce n. Las bu no leas , he Ja que-Be a diagnos ic ou come indica es ha he esiduals a e
ha ing a no mal dis ibu ion.
4.6. Dynamic ARDL simula ions model esul s
Table 8 displays he ou comes om he dynamic ARDL simula ions amewo k. Ou indings show ha
he scale e ec (InSE) and echnique e ec (InTE) ha e a posi i e and nega i e in luence on CO2 emis-
sions, co espondingly. The scale e ec causes a educ ion in ecological heal h, whe eas he echnique
e ec bu e s he en i onmen . The EKC heo y is he e o e suppo ed by empi ical e idence in he case
o Sou h A ica, whe e eal income ises up o a ce ain h eshold bu CO2 emissions s a o decline.
Du ing he ini ial phases o economic g ow h, ecological condi ion in Sou h A ica alls; bu , a e he
na ion achie es i s op imum le el, i s a s o imp o e. This suppo s he in e ed U-shaped ela ionship
be ween economic g ow h and ecological quali y. The ou comes a e pe inen o Sou h A ica and a e
connec ed o he s uc u al change and echnological ad ancemen o he na ion. As people’s li ing
s anda ds inc ease, so does hei en i onmen al consciousness. Ecological egula ions a e he e o e
implemen ed o use ene gy-e icien echnologies o lessen con amina ion. These esul s suppo
Udeagha and B ei enbach (2021)’s asse ion ha he EKC heo y is ue o he Sou he n A ican
Table 6. ARDL bounds es analysis.
Tes s a is ics Value K H0H1
F-s a is ics 14.341 7 No le el ela ionship Rela ionship exis s
-s a is ics −8.752
K ip ganz &Schneide (2018) c i ical alues and app oxima e p- alues y
Signi icance F-s a is ics -s a is ics p- alue F
1(0) 1(1) 1(0) 1(1) 1(0) 1(1)
10% 2.12 3.23 −2.57 −4.04 0.000 0.000
5% 2.45 3.61 −2.86 −4.38 p- alue
1% 3.15 4.43 −3.43 −4.99 0.000 0.002
No e:, and espec i ely ep esen s a is ical signi icance a 10%, 5% and 1% le els. The espec i e signi icance le els sugges he
ejec ion o he null hypo hesis o no coin eg a ion. The op imal lag leng h on each a iable is chosen by he Schwa z’s Bayesian in o ma ion
c i e ion (SBIC).
Table 7. Diagnos ic s a is ics es s.
Diagnos ic s a is ics es s X2(P alues) Resul s
B eusch God ey LM es 0.3812 No p oblem o se ial co ela ions
B eusch-Pagan-God ey es 0.2610 No p oblem o he e oscedas ici y
ARCH es 0.6837 No p oblem o he e oscedas ici y
Ramsey RESET es 0.5183 Model is speci ied co ec ly
Ja que-Be a Tes 0.2715 Es ima ed esidual a e no mal
Sou ce: Au ho s’calcula ions.
16 M. C. UDEAGHA AND N. NGEPAH
De elopmen Communi y (SADC). Alha hi e al. (2021) a i ed a compa able conclusions showing ha
he EKC hypo hesis holds ue o he coun ies o he Middle Eas and No h A ica (MENA). Simila o
his, Bibi and Jamil (2021) disco e ed p oo suppo ing he EKC hypo hesis. Also, Udeagha and Ngepah
(2021b) claim ha Sou h A ica i s he EKC hypo hesis (2021b). Ou esul s suppo hose o Sun e al.
(2021) o China, Isik e al. (2021) o eigh OECD coun ies, and Mu shed (2021) o six Sou h Asian
coun ies. The ou comes disag ee wi h Minlah and Zhang (2021)’s obse a ion ha Ghana’s en i onmen-
al Kuzne s cu e o ca bon dioxide emissions is upwa d sloping. Thei obse a ion con lic s wi h he
s anda d En i onmen al Kuzne s Cu e p inciple, which sugges s an in e ed "U"-shaped connec ion
be ween economic p og ess and ecological decay. Mensah e al. (2018) epo ed da a ha a e simila
and show ha he EKC hypo hesis is alse.
In e ms o s a is ical signi icance, he calcula ed echnological inno a ion coe icien is bo h sho -
and long- e m nega i e. Ou empi ical esea ch demons a es ha , o e he long and sho e m,
espec i ely, a 1% inc ease in echnological inno a ion esul s in a educ ion in CO
2
emissions o 0.73%
and 0.22%. The educ ion o ca bon emissions in Sou h A ica is a esul o echnological ad ancemen s
ha p omo e e icien ene gy use and p oduce enewable ene gy sou ces a lowe cos s. Technological
inno a ion can be classi ied in o end-o -pipe inno a ions and cleane p oduc ion echnologies (Iqbal
e al., 2021). Sou h A ica has implemen ed a numbe o ene gy-sa ing and ene gy-e icien ini ia i es in
his a ea o educe ca bon emissions. The exac componen s o indus ies, he push o echnology, he
pull o he ma ke , and go e nmen al laws a e all pa o Sou h A ica’s en i onmen al pe ec ion goals,
which a e in luencing he end owa d pollu ion- ee socie y. Mo e speci ically, he bio uels indus y
looks o c ea i e ac i i ies in a a ie y o echnical s ages based on echnological capabili ies and en i -
onmen al condi ions. Fu he mo e, ca bon emissions a e educed, and global clima e change is ackled
owing o ca bon cap u e and s o age (CCS) echnology. Addi ionally, Sou h A ica is mo i a ed o in es
in en i onmen al inno a ion by ex e nali ies, ma ke impe ec ions, and R&D and inno a ion incen i es.
This aids he na ion in planning he geog aphic dis ibu ion o pollu ing businesses and enables en i on-
men al p o ec ion a minimal economic cos . Meanwhile, Sou h A ica’s conside able R&D expendi u es
and echnological ad ancemen s a e among he ac o s ha ha e signi ican ly imp o ed he na ion’s
en i onmen al quali y. As pa o he p ima y s a egy o educe he apidly inc easing le els o g een-
house gases emissions, Sou h A ica has also pu in place a numbe o policy ini ia i es aimed a c ea -
ing he wide ange o equipmen equi ed o educe he se e i y o pollu an s om manu ac u ing
ope a ions and o he sec o s o he economy associa ed wi h high le els o g eenhouse gas emissions.
Ou indings a e consis en wi h hose o Udeagha and Ngepah (2022a), who no ed ha echnological
inno a ion has inc eased ene gy e iciency h ough a numbe o means, such as al e ing he uel mix,
Table 8. Dynamic ARDL simula ions analysis.
Va iables Coe icien S . E o - alue
Cons −1.1814 1.2878 −0.92
InSE 0.2139 0.1829 4.56
DInSE 0.3962 0.2721 2.77
InTE −0.6657 0.8605 −2.34
DInTE −0.7441 0.1387 −1.79
InTECH −0.7358 0.5941 −3.24
DInTECH −0.2274 0.0738 −2.62
InEC 0.2713 0.1762 3.98
DInEC 0.59060.1719 1.98
InFDI 0.9064 0.0810 1.12
DInFDI 0.2846 0.2657 2.59
InOPEN 0.1883 0.0487 5.39
DInOPEN −0.3043 0.0570 −2.53
InIGDP 0.3429 0.1577 2.17
DInIGDP 0.5308 0.2309 0.23
ECT(-1) −0.8243 0.1396 −3.04
R-squa ed 0.7845
Adj R-squa ed 0.7693
N55
P al o F-s a 0.0000
Simula ions 1000
Sou ce: Au ho s’calcula ions.
No e:, and deno e s a is ical signi icance a 10%, 5% and 1% le els, espec i ely.
COGENT ECONOMICS & FINANCE 17
implemen ing ene gy-e icien indus ial p ac ices, and u ilizing end-o -pipe echnology, which esul s in
a dec ease in CO
2
emissions in he BRICS coun ies. Ou indings a e u he suppo ed by E dogan
(2021) and Guo e al. (2021), who highligh ed ha , o he BRICS coun ies and China, espec i ely,
echnological ad ancemen os e s an en i onmen ha encou ages a dec ease in ene gy consump ion,
an inc ease in ene gy e iciency, and ul ima ely a dec ease in g eenhouse gas emissions. These esul s
a e u he suppo ed by Anse e al. (2021) o EU coun ies. Ou indings, howe e , a e no consis en
wi h hose made by Dauda e al. (2021), who con end ha he de elopmen o echnology in Sub-
Saha an A ican na ions comp omises ecological in eg i y. Usman and Hamma (2021) ound equi alen
esul s o Asian coun ies.
When ade openness is inc eased by 1%, CO
2
emissions inc eased by 0.188% ce e is pa ibus acco d-
ing o he p edic ed coe icien o he long un on ade openness (InOPEN), which is de e mined o be
s a is ically signi ican and posi i e. Undispu edly, he long- e m ad e se e ec o openness on Sou h
A ica’s en i onmen al si ua ion ein o ces he opposi ion o economic libe aliza ion. Pa o he po en ial
explana ion o why ade openness ha ms Sou h A ica’s a mosphe e is he so o goods ha make up
he majo i y o i s expo s. Since Sou h A ica has a compe i i e edge in he ade and manu ac u ing o
i ems ha equi e a lo o na u al esou ces, such as imbe , a sena e, amekin, b ass, ce ium mine als,
ni a es, molybdenum, aluable mine als, p opane, ch omi e, mine al uels, nickel, coal, coppe and zinc,
gems ones, palladium, and doubloons, an inc ease in he p oduc ion o hese commodi ies will undoub -
edly agg a a e he coun y’s pollu ion le els. This is due o he ac ha he cons an ha es ing o hese
i ems o supply he expanding global ma ke s conside ably deg ades Sou h A ica’s ecological en i on-
men . Addi ionally, he L
opez (1994) concep ual model, which holds ha ca bon emissions is p ima ily
caused by ene gy-in ensi e ope a ions like p oduc ion and anspo a ion ha u ilize a lo o ene gy,
migh be used o jus i y ou obse a ions. Ou indings a e also in line wi h he pollu ion ha en hypo h-
esis (Taylo , 2004), which claims ha eme ging economies like Sou h A ica ha e a compa a i e ad an-
age in c ea ing commodi ies ha a e pollu an -hea y whe eas he indus ialized economies ha e a
compa a i e ad an age in making i ems ha a e clean (Wagne , 2010). Consequen ly, indus ialized
na ions equen ly use ade o sp ead ca bon emissions o hi d wo ld na ions (Cole, 2004; Wagne ,
2010). The indings o Khan and Oz u k (2021), which sugges ha eme ging economies ypically gene -
a e a high quan i y o emissions as a esul o eliance on unclean sec o s, a e consis en wi h and com-
plemen ou empi ical e idence. Ou indings a e in line wi h hose o Khan e al. (2022a), who claimed
ha ade openness is de imen al and signi ican ly wo sens Pakis an’s en i onmen al si ua ion. Ib ahim
and Ajide (2021a), who concluded ha ade openness led o inc eased CO
2
emissions in he G-7, p o-
ide mo e empi ical suppo o his conclusion. Same indings we e made by Van T an (2020), who
demons a ed ha ade openness e odes he s a e o he en i onmen in 66 eme ging ma ke s. The
ou comes om Aydin and Tu an (2020) and Ali e al. (2020), which e ealed ha ade has a de imen al
impac on ecological heal h by inc easing ca bon dioxide emissions, a e consis en wi h he ad e se pe -
cep ion o ecological epe cussions o ade openness. Ou esul s do no ag ee wi h hose o Ib ahim
and Ajide (2021b,2021c), and Ding e al. (2021), who showed ha mo e ade openness imp o es eco-
logical in eg i y in he G-20, 48 Sub-Saha an A ican na ions, and G-7 economies, espec i ely.
The compu ed coe icien s o he sho - and long- e m ene gy consump ion (InEC) a e s a is ically
signi ican and posi i e, indica ing ha ene gy usage makes an impo an con ibu ion o ising CO
2
emissions in Sou h A ica. Sou h A ica is he se en h-la ges na ion ha la gely elies on coal o sa is y
i s ene gy needs, and al hough his is necessa y o sus ain p oduc ion and u he economic g ow h, i
also signi ican ly con ibu es o he deg ada ion o en i onmen al quali y (Wo ld Bank, 2021). I can be
shown ha o e ime, a 1% ise in ene gy use esul s in a 0.2713% ise in CO
2
emissions. Sou h A ica is
signi ican ly elian on he ene gy indus y, whe e he p oduc ion p ocess is domina ed by he use o
coal. In Sou h A ica, coal ese es accoun o 93% o powe gene a ion and o e 77% o he coun y’s
p ima y ene gy sou ce (Udeagha & B ei enbach, 2021). Because o Sou h A ica’s consis en ly ising
ene gy consump ion, CO
2
emissions ha e d ama ically g own o e ime, ha ing se ious ad e se en i on-
men al e ec s, and playing a big ole in he global clima e change. Adebayo e al. (2021)’s indings ha
ene gy use causes CO
2
emissions in Sou h Ko ea a e consis en wi h ou empi ical indings. Simila ind-
ings a e made by Aslan e al. (2021), who disco e ha ene gy use deg ades ecological in eg i y in 17
Medi e anean na ions. Addi ionally, Do
ganla e al. (2021) no e ha Tu key’s ene gy usage inc eases
18 M. C. UDEAGHA AND N. NGEPAH
CO
2
emissions. Simila indings we e eached by Hongxing e al. (2021), who ound ha 81 BRI econo-
mies’ene gy usage esul s in highe ca bon emissions. Acco ding o esea ch by Hu e al. (2021),
Guangdong, China, expe iences a ise in ca bon emissions due o o e all ene gy usage. Simila indings
we e made by I an e al. (2021b), who looked a he ac o s a ec ing consume in en ion o use enew-
able ene gy. They disco e ed ha he d i ing ac o s, such as pe cep ion o one’s own e ec i eness,
awa eness, and pe cep ion o neighbou pa icipa ion, ha e signi ican and ad an ageous e ec s on con-
sume in en ion o use enewable ene gy. Ou indings con lic wi h hose made by Ponce and Khan
(2021), Khan e al. (2021c), He e al. (2021), Hao e al. (2021) and Baye e al. (2021), who claim ha
ene gy use enhances ecological in eg i y.
The es ima ed o eign di ec in es men (InFDI) coe icien o e he sho e m is ound o exace ba e
CO
2
emissions. Ou indings a e consis en wi h Sou h A ica’s "pollu ion ha e heo y." Due o i s com-
pe i i e po en ial in he expo and manu ac u ing o il hy goods, Sou h A ica has d awn signi ican
FDI in lows, which ha e signi ican ly wo sened he na ion’s pollu ion le el. The damaging impac o FDI
on Sou h A ica’s a mosphe e shows ha FDI in lows aid he na ion o u n in o one o he wo ld’s
"ha ens" o sec o s wi h high le els o pollu ion. Ou indings a e in acco dance wi h hose o Copeland
and Taylo (2013), who asse ed ha en i onmen ally ha m ul ac o ies ha gene a e di y p oduc s
ha e eloca ed o less indus ialized economies, he eby shi ing he pollu ions o he indus ialized
economies o hese poo coun ies. This has a signi ican nega i e impac on hese coun ies’al eady
decaying en i onmen al condi ions. Sou h A ica has also go en di ie as a esul o poo en i onmen al
egula ions and co up ins i u ions, since he na ion is known o p oducing di y commodi ies ha con-
side ably inc ease he a e o en i onmen al deg ada ion. FDI in lows ha e helped Sou h A ica become
a hea ily pollu ed in e na ional ac o y ha sends a la ge po ion o wha i manu ac u es back o in e -
na ional ma ke s. This ac ual da a e eals he eal cha ac e is ics o he Sou h A ican economy, which is
one o A ica’s as es -eme ging economies. The e o e, in o de o assu e e iciency in he manu ac u ing
p ocesses, au ho i ies and en i onmen alis s mus do mo e o gua an ee ha o e seas companies use
mode n, en i onmen ally iendly, and ene gy-e icien p oduc s o swi ch om non- enewable o enew-
able o less ca bon-in ensi e ene gy sou ces. Meanwhile, Sou h A ica’sCO
2
emissions will be signi i-
can ly educed by swi ching om non- enewable ene gy sou ces o al e na i es like sola powe . This
will e en ually encou age long- e m alue o GHG emission educ ions and con inuously assis he c e-
a ion o inno a i e solu ions ha imp o e Sou h A ica’s en i onmen al condi ion and p o ec he en i -
onmen wo ldwide. Ou indings a e suppo ed by Muhammad e al. (2021), who ound ha FDI
inc eases CO
2
emissions in BRICS and de eloping na ions om 1991 o 2018. Faheem e al. (2022), who
in es iga ed he ole o FDI in os e ing en i onmen al sus ainabili y in Malaysia, ound ha FDI has a
damaging e ec on he Malaysian en i onmen . Ou esul s suppo he conclusions o Abdouli and
Hammami (2017), who in he case o MENA coun ies achie ed a compa able ou come ha FDI has
g ea ly escala ed CO
2
emissions and concluded ha he e was clea indica ion o he pollu ion ha en
hypo hesis. Conclusions d awn by Adeel-Fa ooq e al. (2021) o 76 de eloped and de eloping coun ies,
and Ngepah and Udeagha (2018) o sub-Saha an A ica p o ide addi ional e idence in suppo o his
empi ical inding. Howe e , he esul s disag ee wi h hose o Mohan y and Se hi (2022), who ound ha
FDI helps o enhance g een echnologies ha imp o e en i onmen al quali y in BRICS coun ies.
Fo indus ial g ow h, we ound e idence ha he g ow h o he manu ac u ing indus y o e ime con-
side ably wo sens he ecological en i onmen o Sou h A ica. A ise in CO
2
emissions is mos ly caused by
Sou h A ica’s expanding indus ial sec o . Sou h A ica has implemen ed a a ie y o measu es h ough-
ou he yea s o pu sue economic change and indus ializa ion in o de o comba inequali y and encou -
age equi able dis ibu ion o income. To ensu e las ing economic de elopmen , employmen gene a ion,
and sus ainable de elopmen , he economy mus s uc u ally shi om low-p oduc i i y ag icul u al
o high-p oduc i i y indus ializa ion. Howe e , Sou h A ica’s expanding indus ial sec o has esul ed
in an inc ease in CO
2
emissions. Immense indus ializa ion, he esul ing en i onmen al e ec s, and
he e ec s on biodi e si y pu human su i al in dange since hey in e e e wi h undamen al needs, ec-
ea ional ac i i ies, and biological p ocesses. I is ecognized ha deg ada ion om a a ie y o sou ces,
no ably om comme cial en i ies, has a de imen al e ec on he ecosys em ha is pe manen in na u e
and leads o he ex inc ion o animal species, which esul s in he des uc ion o aluable and unique gen-
e ic esou ces. Ou esul s suppo he obse a ions made by Udemba (2022), who ound ha he
COGENT ECONOMICS & FINANCE 19
expanding manu ac u ing indus ies a e mos ly o blame o he inc eased end in CO
2
emissions
in Tu key. In addi ion, Tian e al. (2014) claimed ha domes ic CO
2
emissions a e mos ly caused by
hea y indus y. Che niwchan (2012) and Hossain (2011) a e mo e sou ces ha alida e ou indings. The
esul s, howe e , disag ee wi h hose o Lin e al. (2015), who a gued ha he e is no p oo ha Nige ia’s
apid indus ializa ion ac i i ies aises ca bon emissions. S udies like hose by Shahbaz e al. (2014b) and
Sha iei and Salim (2014) ound e idence ha indus ial sec o g ow h educes CO
2
emissions.
The s a is ically signi ican , nega i e e o co ec ion e m o -0.824, which also demons a es he
quick e u n o he long- un equilib ium, en enches he equilib ium connec ion be ween he a iables.
I u he cla i ies ha a e co ec ing he sho - un disequilib ium, ou model es o es o long- un equi-
lib ium a an 82% a e o adjus men .
Impulse esponse unc ions dynamically display and o ecas he u u e alue o a eg essed a iable
in esponse o an independen a iable in he dynamic ARDL model while main aining he cons an
alue o he o he p edic o a iable. In his in es iga ion, we p edic ed he change in CO2 emissions in
esponse o a 10% change in he explana o y ac o s, ei he posi i ely o nega i ely.
The expec ed ela ionship be ween scale e ec (economic g ow h) and CO
2
emissions is shown in
Figu e 1. Each 10% ise in scale e ec ine i ably deg ades he en i onmen in he sho e m. Howe e ,
o e ime, a ise in scale e ec causes mo e long- e m ha m o he ecosys em han i does sho - e m
ha m. On he o he side, e e y 10% dec ease in he scale e ec esul s in a long- e m dec ease in CO
2
emissions, and he en i onmen spon aneously epai s he ha m.
The impulse esponse o CO
2
emissions o posi i e o nega i e changes in echnique e ec is p e-
dic ed in Figu e 2. As demons a ed, a 10% inc ease o dec ease in echnique e ec causes signi ican
sho - and long- e m changes in en i onmen al heal h. Addi ionally, o e ime, e e y 10% inc ease in
echnique e ec esul s in con inued imp o emen o en i onmen al quali y. On he o he hand, any
dec ease in echnique e ec e en ually lowe s he quali y o he en i onmen .
Figu e 3 displays he impulse esponse unc ions o CO
2
emissions o changes in ade openness o
10%. A 10% ise in ade openness o decline esul s in a simila sho - e m cos o he en i onmen .
Howe e , o e ime, e e y inc ease in ade openness causes CO
2
emissions o ise, whe eas any 10%
dec ease in ade openness causes a g adual decline in CO
2
emissions. Howe e , as CO
2
emissions con-
inue o ise o e ime, he en i onmen canno eco e om his loss in ade openness.
Figu e 4 illus a es how a ia ions in CO
2
emissions in eac ion o ene gy consump ion. Thus any 10%
shi in ene gy usage esul s in a de ini e e ec in he en i onmen . Addi ionally, o e ime, e e y 10%
ise in ene gy use con inually wo sens he en i onmen by inc easing CO
2
emissions. Howe e , e e y
10% educ ion in ene gy usage esul s in an imp o emen in en i onmen al quali y. As a esul , ene gy
usage will con inue o exace ba e en i onmen al de e io a ion.
Figu e 1. The impulse esponse plo o scale e ec (economic g ow h) and CO
2
emissions.
I shows a 10% inc ease and a dec ease in scale e ec and i s in luence on CO
2
emissions whe e do s speci y a e age
p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al, espec i ely.
20 M. C. UDEAGHA AND N. NGEPAH
Figu e 3. The impulse esponse plo o ade openness and CO
2
emissions.
I shows a 10% inc ease and a dec ease in ade openness and i s in luence on CO
2
emissions whe e do s speci y a e -
age p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al,
espec i ely.
Figu e 4. The impulse esponse plo o ene gy consump ion and CO
2
emissions.
I shows a 10% inc ease and a dec ease in ene gy consump ion and i s in luence on CO
2
emissions whe e do s speci y
a e age p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al,
espec i ely.
Figu e 2. The impulse esponse plo o echnique e ec and CO2 emissions.
I shows a 10% inc ease and a dec ease in echnique e ec and i s in luence on CO
2
emissions whe e do s speci y a e -
age p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al,
espec i ely.
COGENT ECONOMICS & FINANCE 21
Acco ding o he indings, en i onmen al con amina ion in Sou h A ica inc eases wi h a þ10% shock
o o eign di ec in es men , bu dec eases wi h a -10% shock, as seen in Figu e 5. This means ha
boos ing o eign di ec in es men would inc ease CO
2
emissions in he na ion; ne e heless, lowe ing
o eign di ec in es men would imp o e Sou h A ica’s en i onmen al quali y.
The o ecas s in Figu e 6 show he ela ionship be ween en i onmen al quali y and echnological
ad ancemen . An equal and posi i e sho - e m shi in CO
2
emissions happens om each 10% inc ease
o dec ease in echnological inno a ion. In he long e m, en i onmen al quali y ends o inc ease wi h
each success ul echnological b eak h ough, bu any addi ional echnological delay esul s in mo e
se e e en i onmen al deg ada ion.
Figu e 7 shows ha a þ10% shock o u baniza ion causes en i onmen al de e io a ion in he na ion
whe eas a -10% shock o u baniza ion enhances he na ion’s ecological quali y. This means ha Sou h
A ica’s g owing u ban popula ion is no ecologically iendly.
This wo k also uses he equency domain causali y es p oposed by B ei ung and Candelon (2006)
o explo e he causali y be ween InSE, InTE, InTECH, InEC, InFDI, InOPEN, InIGDP and InCO
2
in Sou h
A ica. Table 9 shows ha InSE, InTE, InTECH, InEC, InFDI, InOPEN and InIGDP G ange -cause InCO
2
in he
sho , medium, and long un o equencies xi¼0:05, xi¼1:50, xi¼2:50:
Figu e 5. The impulse esponse plo o o eign di ec in es men and CO
2
emissions.
I shows a 10% inc ease and a dec ease in o eign di ec in es men and i s in luence on CO
2
emissions whe e do s
speci y a e age p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al,
espec i ely.
Figu e 6. The impulse esponse plo o echnological inno a ion and CO
2
emissions.
I shows a 10% inc ease and a dec ease in echnological inno a ion and i s in luence on CO
2
emissions whe e do s spe-
ci y a e age p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al,
espec i ely.
22 M. C. UDEAGHA AND N. NGEPAH
This implies ha InSE, InTE, InTECH, InEC, InFDI, InOPEN and InIGDP signi ican ly a ec CO
2
emissions
in sho , medium, and long e m in Sou h A ica. Ou empi ical e idence is compa ible wi h he indings
o Udeagha and Ngepah (2023a), and Udeagha and Muchapondwa (2022a).
Mo eo e , he s abili y o he model is con i med om he co esponding CUSUM and CUSUMSQ
cha s illus a ed in Figu es 8 and 9.
Figu e 7. The impulse esponse plo o u baniza ion and CO
2
emissions.
I shows a 10% inc ease and a dec ease in u baniza ion and i s in luence on CO
2
emissions whe e do s speci y a e age
p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al, espec i ely.
Table 9. F equency-domain causali y es .
Di ec ion o causali y Long- e m Medium- e m Sho - e m
xi¼0:05 xi¼1:50 xi¼2:50
InSE !InCO
2
<8.31><8.50><9.96>
(0.02) (0.00) (0.00)
InTE !InCO
2
<4.89><6.49><6.93>
(0.07)(0.03) (0.04)
InOPEN !InCO
2
<8.94><8.73><7.28>
(0.00) (0.00) (0.01)
InEC !InCO
2
<5.12><6.49><6.73>
(0.08)(0.04) (0.03)
InFDI !InCO
2
<8.20><8.08><8.62>
(0.01) (0.03) (0.00)
InTECH !InCO
2
<4.84><5.14><7.83>
(0.06)(0.04) (0.02)
InIGDP !InCO
2
<5.46><8.82><8.89>
(0.07)(0.00) (0.00)
Sou ce: Au ho s’calcula ions.
No e:, and deno e s a is ical signi icance a 10%, 5% and 1% le els, espec i ely.
Figu e 8. The impulse esponse plo o indus ial alue-added and CO
2
emissions.
I shows a 10% inc ease and a dec ease in indus ial alue-added and i s in luence on CO
2
emissions whe e do s speci y a e -
age p edic ion alue. Howe e , he da k blue o ligh blue line deno es 75, 90, and 95% con idence in e al, espec i ely.
COGENT ECONOMICS & FINANCE 23
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