Kwilinski, Aleksy; Lyulyo , Oleksii; Pimonenko, Te yana
A icle
The ole o g een inance in a aining en i onmen al
sus ainabili y wi hin a coun y's ESG pe o mance
Jou nal o Inno a ion & Knowledge (JIK)
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Sugges ed Ci a ion: Kwilinski, Aleksy; Lyulyo , Oleksii; Pimonenko, Te yana (2025) : The ole o g een
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Inno a ion & Knowledge (JIK), ISSN 2444-569X, Else ie , Ams e dam, Vol. 10, Iss. 2, pp. 1-13,
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The ole o g een inance in a aining en i onmen al sus ainabili y wi hin a
coun y’s ESG pe o mance
Aleksy Kwilinski
a,b,c,*
, Oleksii Lyulyo
a,c
, Te yana Pimonenko
a,c
a
Depa men o Ma ke ing, Sumy S a e Uni e si y, 40007 Sumy, Uk aine
b
The London Academy o Science and Business, 120 Bake S ., London W1U 6TU, UK
c
Depa men o Managemen , Facul y o Applied Sciences, WSB Uni e si y, 41-300 Dab owa Go nicza, Poland
ARTICLE INFO
JEL Classi ica ion:
F64
F65
O36
Q01
Q56
Keywo ds:
G een in es men
Sus ainable de elopmen
Inclusi e economic g ow h
G een g ow h
ABSTRACT
The ongoing issues ha ollow clima e change equi e he implemen a ion o ele an s a egies and ins umen s
o accele a e coun ies’ e o s owa d en i onmen al sus ainabili y. Thus, he pu sui o en i onmen al sus-
ainabili y has become a global impe a i e as coun ies inc easingly adop measu es o enhance hei en i on-
men al, social, and go e nance (ESG) pe o mance. Mo eo e , an e ec i e sys em o inancial suppo is needed.
This pape aims o assess he impac o g een inance on he en i onmen al dimension o ESG pe o mance in
Eu opean Union (EU) coun ies om 2008 o 2020. The s udy applies he ollowing me hods: (1) a spa ial Du bin
model o examine he ela ionship be ween g een inance and en i onmen al pe o mance wi hin he EU con ex
and (2) en opy me hods o assess he en i onmen al dimension o ESG pe o mance. The indings e eal ha
g een inance ini ia i es play a signi ican ole in d i ing posi i e en i onmen al ou comes wi hin a coun y’s
ESG pe o mance. By channeling inancial esou ces owa d en i onmen ally iendly p ojec s and businesses,
g een inance acili a es he ansi ion o a low-ca bon and esou ce-e icien economy. I enables he imple-
men a ion o enewable ene gy p ojec s, ene gy e iciency imp o emen s, sus ainable in as uc u e de elop-
men , and ecosys em p ese a ion e o s. These ini ia i es con ibu e o educing g eenhouse gas emissions,
mi iga ing clima e change isks, conse ing na u al esou ces, and p o ec ing biodi e si y.
In oduc ion
In he ace o ongoing clima e change and i s accompanying chal-
lenges, coun ies wo ldwide a e inc easingly ecognizing he u gen
need o s a egies and mechanisms o p opel hei way owa d en i-
onmen al sus ainabili y (Ones & Dilche , 2012; Kha azish ili e al.,
2020; Hamid e al., 2021; Opoku e al., 2022; Ahmed e al., 2022;
Le uno ska e al., 2022; Zeeshan Za a e al., 2023; Pud yk e al., 2023;
Chen e al., 2023; Dzwigol e al., 2023a). Schola s (Chen e al., 2021;
A e ie a e al., 2021; Mi´
skiewicz e al., 2022; Kwilinski e al., 2023e;
Kwilinski, 2023; 2024a; 2024b) emphasize ha hese coun ies a e
p og essi ely adop ing measu es aimed a enhancing hei en i on-
men al, social, and go e nance (ESG) pe o mance, acknowledging ha
en i onmen al s ewa dship is a c i ical componen o o e all sus ain-
abili y. Ne e heless, o e ec i ely bols e hese aspi a ions, a obus
inancial sys em ha suppo s g een ini ia i es is essen ial. Conside ing
hese s udies (Fo manko aа e al., 2018; Chyg yn e al., 2020; Moska-
lenko e al., 2022a; Kwilinski e al., 2023g), g een inance (Chien e al.,
2022; Lu e al., 2023; Liu e al., 2022), as a mul i ace ed and dynamic
ool, is designed o channel inancial esou ces owa d p ojec s and
businesses commi ed o en i onmen ally sus ainable p ac ices (Xue
e al., 2022). I se es as a ca alys o ansi ioning economies owa d a
low-ca bon and esou ce-e icien u u e. The ini ia i es i suppo s
encompass a b oad spec um o enewable ene gy p ojec s (D´
zwigol
e al., 2019; B ych e al., 2021; Dzwigol, 2022a; Kwilinski e al., 2022a;
2022c), imp o emen s in ene gy e iciency (Kwilinski e al., 2022b;
Ziabina & Na ickas, 2022; Chyg yn e al., 2022; Gha a & Sa da ,
2023), sus ainable in as uc u e de elopmen (O ali e al., 2022; Raz-
zaq e al., 2022; Baloch e al., 2023; Akbas & Iyisan, 2023; B odny &
Tu ak, 2023; Baloch, 2023; Sabba , 2023), and conce ed e o s o
p ese e ecosys ems (Dzwigol e al., 2019a; 2020b; 2021; Dzwigol &
Dzwigol-Ba osz, 2020). These ini ia i es, collec i ely, yield mani old
bene i s, including he educ ion o g eenhouse gas emissions, he
mi iga ion o clima e change isks (Polcyn e al., 2022; Taghiza-
deh-Hesa y e al., 2022; Kwilinski e al., 2023a; 2023b), and he con-
se a ion o i al na u al esou ces. D’O azio (2023) examined he
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (A. Kwilinski).
Con en s lis s a ailable a ScienceDi ec
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Recei ed 1 Decembe 2023; Accep ed 10 Feb ua y 2025
Jou nal o Inno a ion & Knowledge 10 (2025) 100674
A ailable online 17 Feb ua y 2025
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e ec s o clima e inance policies (such as he Pa is Ag eemen
(Sa a esi, 2016) and he EU’s Sus ainable Finance Ac ion Plan (Moslein
& So ensen, 2018)) on inancial ma ke s, pa icula ly he expansion o
he g een bond ma ke . ˇ
S eimikien˙
e e al. (2023) emphasized he need
o imp o emen s in se e al policy a eas, including s anda dizing
disclosu e ules, es ablishing in e na ional economic ac i i y classi ica-
ions, and encou aging he use o clima e-aligned inancial me ics.
P og ess in hese a eas equi es bo h in e na ional coope a ion and ac-
ions a he na ional le el o acili a e a ansi ion o a low-ca bon
economy. Ha ne e al. (2020) ou lined he co ela ion be ween sus-
ainable de elopmen and inance o EU coun ies, concluding ha
in es men s made h ough g een inance a e mo e likely o con ibu e o
long- e m economic esilience. By ocusing on sus ainabili y, EU coun-
ies educe hei ulne abili y o he ola ili y o non- enewable e-
sou ces and en i onmen al disas e s (Ca o a e al., 2022; ˇ
Za ko i´
c
e al., 2022). This app oach enhances o e all economic s abili y and
p epa edness o u u e challenges. Se e al s udies (Flanne y & May,
2000; Shka le e al., 2019; Dacko-Pikiewicz, 2019; Bu ko e al., 2019;
Mi´
skiewicz, 2019; T ushkina e al., 2020; Dzwigol, 2020a; 2023; Ade-
doyin e al., 2021; T zeciak e al., 2022; Zhanibek e al., 2022; Dzwigol
e al., 2023b; Le uno ska e al., 2023) ha e shown ha knowledge and
digi aliza ion play pi o al oles in b idging he gap be ween g een
inance and ESG pe o mance a he coun y le el. The in eg a ion o
digi al echnologies enables he e icien moni o ing, epo ing, and
assessmen o en i onmen al ini ia i es and ESG pe o mance me ics.
Knowledge dissemina ion (Dzwigol e al., 2019c; Kwilinski e al., 2020a;
2022b; Szos ek, 2021; Dzwigol-Ba osz & Dzwigol, 2021; Kha azish ili &
Kwilinski, 2022; Ka nowski & Rzo´
nca, 2023), pa icula ly in he o m o
sus ainable p ac ices and eco- iendly echnologies, uels inno a ion and
os e s a deepe unde s anding o he in e connec edness be ween
inancial decisions and en i onmen al consequences (Flanne y & May,
2000; Dzwigol e al., 2019b; Kwilinski e al., 2020b; 2022b; Dzwi-
gol-Ba osz & Dzwigol, 2021; Adedoyin e al., 2021; Kha azish ili &
Kwilinski, 2022; Ka nowski & Rzo´
nca, 2023).
The Eu opean Union s ands a he o e on o he global sus ain-
abili y discou se, d i en by i s ad anced g een inance ma ke s and
s ingen en i onmen al policies. Unde s anding how g een inance
con ibu es o hese goals can shed ligh on e ec i e p ac ices and guide
u u e e o s. This s udy del es in o he in e sec ion o inance and
sus ainabili y, a key a ea o achie ing long- e m en i onmen al goals.
By ocusing on he EU, a leade in sus ainabili y ini ia i es, he esea ch
p o ides a benchma k o o he egions aiming o enhance hei g een
inance s a egies. Addi ionally, he s udy’s ou comes in luence global
discussions and policies on en i onmen al sus ainabili y. Resea ch in
his a ea is essen ial o b idge he knowledge gap ega ding he e ec-
i eness o g een inance in achie ing angible en i onmen al bene i s.
The EU’s ambi ious a ge s o educing ca bon emissions and p omo -
ing sus ainable de elopmen equi e obus e idence on he impac o
g een inancial ins umen s. This esea ch alida es he ole o g een
inance in mee ing hese a ge s and sugges s imp o emen s whe e
needed. This s udy con ibu es o he exis ing li e a u e by o e ing
empi ical e idence on he impac o g een inance on en i onmen al
ou comes wi hin he EU con ex . I en iches he academic discou se wi h
da a-d i en insigh s and expands ou unde s anding o how inancial
mechanisms can suppo sus ainabili y. This con ibu ion is pa icula ly
signi ican gi en he dynamic na u e o g een inance and he e ol ing
egula o y landscape.
The o iginali y o his esea ch lies in i s comp ehensi e app oach o
assessing he impac o g een inance using empi ical econome ic
models. Unlike p e ious s udies ha may ha e ocused on heo e ical
amewo ks o case s udies, his esea ch employs obus quan i a i e
me hods o p o ide conc e e e idence o g een inance’s e icacy.
Mo eo e , i conside s egional speci ici ies wi hin he EU, o e ing a
nuanced pe spec i e ha accoun s o di e se economic and en i on-
men al condi ions. P elimina y indings sugges ha g een inance
signi ican ly enhances en i onmen al sus ainabili y and ESG
pe o mance. G een bonds and o he inancial ins umen s a e e ec i e
in mobilizing capi al owa ds sus ainable p ojec s, esul ing in measu -
able en i onmen al imp o emen s. The s udy also highligh s he
impo ance o policy suppo and egula o y amewo ks in maximizing
he impac o g een inance.
The indings o his esea ch ha e p o ound policy implica ions.
Policymake s can le e age he insigh s o e ine and enhance g een
inance ini ia i es, ensu ing hey a e aligned wi h sus ainabili y goals.
The s udy unde sco es he need o suppo i e egula o y en i onmen s
and incen i es o os e he g ow h o g een inance ma ke s. Addi-
ionally, i sugges s ha egional speci ici ies should be conside ed in
policy o mula ion, ad oca ing o ailo ed s a egies ha add ess
unique economic and en i onmen al con ex s wi hin he EU. In
conclusion, his esea ch no only unde sco es he c i ical ole o g een
inance in ad ancing sus ainabili y bu also p o ides ac ionable insigh s
o policymake s. By demons a ing he angible bene i s o g een
inancial mechanisms, i lays he g oundwo k o mo e e ec i e and
a ge ed sus ainabili y policies wi hin he EU and beyond. Thus, his
pape aims o explo e he ela ionships be ween g een inance, en i-
onmen al sus ainabili y, and ESG pe o mance, o e ing a deepe un-
de s anding o he ans o ma i e po en ial o inancial mechanisms in
shaping a mo e sus ainable u u e o coun ies wi hin he EU and, by
ex ension, o he global communi y. Thus, his s udy ills he heo e ical
gap in he de elopmen o an app oach o explo ing he pi o al ole o
g een inance in in luencing he en i onmen al dimension o ESG pe -
o mance in Eu opean Union (EU) coun ies by employing a combina-
ion o spa ial Du bin modeling ( o examine he ela ionship be ween
g een inance and en i onmen al pe o mance) and en opy ( o assess
he en i onmen al dimension o ESG pe o mance) me hods.
The pape has he ollowing s uc u e: a li e a u e e iew explo ing
he ela ionship be ween g een inance and he en i onmen al dimen-
sion o ESG pe o mance; a ma e ials and me hods sec ion ou lining he
me hods, a iables, and sou ces used o es he esea ch hypo hesis
linking g een inance and he en i onmen al dimension o ESG pe o -
mance; a esul s sec ion explaining he empi ical indings on es ing he
esea ch hypo hesis; a discussion compa ing he ob ained indings wi h
hose o p e ious in es iga ions; and a conclusion summa izing he
esea ch indings, policy implica ions, limi a ions, and di ec ions o
u u e in es iga ions.
Li e a u e e iew
Theo e ical s udies on g een inance and ESG pe o mance
The heo e ical unde pinning o he ela ionship be ween g een
inance and ESG pe o mance is s ongly suppo ed by schola s such as
Panchenko e al. (2020), Dzwigol (2021; 2022b), Ka nowski &
Mi´
skiewicz (2021), and Moskalenko e al. (2022b). These s udies
collec i ely emphasize ha a na ion’s ESG pe o mance is undamen-
ally con ingen on a subs an ial alloca ion o g een inance, which is
ins umen al in os e ing g een in as uc u e, p og essi e echnologies,
and ene gy-e icien p ojec s. Roy (2023) u he ein o ced his na a-
i e by asse ing he g owing p ominence o ESG measu es as indis-
pensable componen s o sus ainable in es men ha a e c ucial o he
ealiza ion o sus ainable de elopmen goals. This heo e ical s ance is
complemen ed by he insigh s o Macchia ello and Si i (2022), who
ad oca ed o a syne gis ic app oach by me ging he EU’s Digi al
Finance/Fin ech Ac ion Plan wi h he Sus ainable Finance S a egy.
Such an in eg a ion, hey a gue, is po en in add essing he dual chal-
lenges o sus ainabili y and ESG disclosu e, a need s a kly highligh ed by
he economic pe u ba ions induced by he COVID-19 pandemic. This
body o heo e ical wo k collec i ely posi s ha g een inance is no only
a inancial condui bu also a mul i ace ed ca alys ha p opels na ions
owa d comp ehensi e ESG pe o mance. Khan e al. (2022), ocusing
on i e egions (Sou h Asia, Sou heas Asia, China, Middle Eas e n
coun ies, and Eu opean coun ies), assessed he impac o g een inance
A. Kwilinski e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100674
2
on en i onmen al sus ainabili y, paying speci ic a en ion o ac o s
such as egional GDP, inno a ion le els, and ai quali y. This e eals
ha he de elopmen o g een inance exhibi s egional a ia ions,
emphasizing he signi icance o hese egional ac o s in in luencing
g een inance. Khan e al. (2022) emphasized he impo ance o
inc easing g een inance in enewable ene gy sou ces, esea ch and
de elopmen , and public‒p i a e pa ne ships o educe CO2 emissions
and p omo e en i onmen al sus ainabili y, ul ima ely ad oca ing o
c oss-bo de ade in enewable ene gy o mi iga e global CO2
emissions.
Schola s (Waddell & B own, 1997; Hamann & Acu , 2003; Cla k
e al., 2018; Muhammad e al., 2023) ha e emphasized ha g een
inance o en in ol es collabo a ion among a ious s akeholde s,
including go e nmen s, inancial ins i u ions, businesses, and ci il so-
cie y. These pa ne ships os e a mo e holis ic and in eg a ed app oach
o add essing en i onmen al challenges (Waddell & B own, 1997;
Hamann & Acu , 2003; Cla k e al., 2018; Muhammad e al., 2023).
Public‒p i a e pa ne ships, o ins ance, can mobilize signi ican e-
sou ces o la ge-scale sus ainable in as uc u e p ojec s (Waddell &
B own, 1997; Hamann & Acu , 2003; Cla k e al., 2018; Muhammad
e al., 2023). Using da a om 2001 o 2019, Wu (2023) employed
ad anced modeling echniques o highligh he signi ican and posi i e
e ec s o g een inance on he economic pe o mance (measu ed by
g oss domes ic p oduc (GDP)) o selec ed OECD economies.
Empi ical wo ks linking g een inance o ESG pe o mance
Roy (2023) p oposed an ESG-based c edi a ing model ha employs
he uzzy BWM and uzzy TOPSIS-So ing me hods o e alua e i ms,
wi h inancial ac o s ca ying he mos weigh (43%), ollowed by
en i onmen al ac o s (24%), social ac o s (19%), and go e nance
ac o s (14%). This model, wi h an 84.31% accu acy a e and 87.5% ue
posi i e a e, o e s a aluable ool o na ional inancial ins i u ions and
egula o s o p omo e sus ainable in es men s. Empi ical s udies sub-
s an ia e he heo e ical amewo ks wi h conc e e da a and analysis. Ma
e al. (2023) explo ed he in ica e dynamics be ween g een inance,
enewable ene gy in es men , g een economic eco e y, and en i on-
men al pe o mance. The au ho s ound ha coun ies, pa icula ly
noneme ging coun ies equipped wi h ad anced echnologies o obus
sus ainabili y s a egies, exhibi ma kedly enhanced en i onmen al
pe o mance. This empi ical e idence unde sco es he pi o al ole o
g een inance in s ee ing na ions owa d sus ainable g ow h and en i-
onmen al s ewa dship. Simila ly, using da a om 30 Chinese p o inces
o e he pe iod 2004–2019, Deng & Zhang (2023) examined he impac
o en i onmen al egula ion in ensi y and g een inance de elopmen on
egional en i onmen al sus ainabili y. They e eal a pa e n o spa ial
clus e ing in sus ainabili y and posi ha mo e s ingen en i onmen al
egula ions, coupled wi h obus g een inance, exe posi i e e ec s a
bo h he na ional and p o incial le els, wi h he wes e n egion o China
expe iencing he mos p o ound impac . A shan e al. (2023) in oduced
a nuanced app oach, employing he quan ile au o eg essi e dis ibu ed
lag (QARDL) model, o dissec he in luence o g een inance,
eco-inno a ion, and s ic en i onmen al policies on China’s ecological
oo p in . The indings depic a complex, quan ile-dependen associa ion
be ween hese a iables, o e ing ich insigh s o policy o mula ion.
Qad i e al. (2023) del ed in o he complex in e play be ween g een
inance, ade openness, o eign di ec in es men , and en i onmen al
sus ainabili y in Pakis an, unco e ing di e se and nonlinea connec ions
among hese ac o s. Based on ime-se ies da a o 1986 o 2018, T an
(2022) con i med he long- e m ela ionships (coin eg a ion) among
g een inance, economic g ow h, enewable ene gy consump ion, en-
e gy impo s, and CO2 emissions and sugges ed unidi ec ional causali y
om enewable ene gy consump ion and g een in es men o CO2
emissions. Kem e & Schmalz (2019) highligh ed he ole o na ional
and Eu opean policy amewo ks, including public ins i u ion in-
es men s and di es men s a egies, in p omo ing g een inance, which
a ec s GDP. Schola s (Lee, 2020; Tolli e e al., 2021; Uma & Sa i,
2023) ha e highligh ed he c i ical ole o g een inance and R&D
(which a e measu ed by g een inno a ion) in achie ing sus ainable
de elopmen and educing en i onmen al pollu ion. Thei indings (Lee,
2020; Tolli e e al., 2021; Uma & Sa i, 2023) demons a ed a
long- e m ela ionship among g een inance, R&D, en i onmen al pol-
icy s ingency, GDP, expo s, impo s, and ca bon emissions, wi h g een
inance and inno a ion signi ican ly educing ca bon emissions. Kwi-
linski e al. (2023a) con i med ha as u baniza ion a es ise and ade
openness inc eases, he need o e ec i e en i onmen al policies be-
comes e iden . G een inance could be di ec ed owa d eco- iendly
u ban de elopmen and sus ainable ade p ac ices, ul ima ely impac -
ing he en i onmen al dimension o ESG pe o mance. EU coun ies a e
inc easingly ecognizing ha sus ainable u baniza ion and ade,
unde pinned by g een inance, a e c ucial componen s in hei pu sui o
en i onmen al goals and holis ic ESG pe o mance. Udeagha & B ei-
enbach (2021) analyzed he impac o ade openness on CO2 emissions
in he Sou he n A ican De elopmen Communi y om 1960 o 2014
and ound ha while ade openness imp o es en i onmen al quali y
h ough echnology and economic es uc u ing, i can also heigh en
emissions due o indus ial and ene gy ac o s. I ad oca es o ha mo-
nizing ade policies wi h en i onmen al and echnological ini ia i es o
enhance he egion’s en i onmen al sus ainabili y. Lagoa de-Sego
(2020) and La To e e al. (2021) discussed how he EU’s g een bond
ma ke , an essen ial componen o g een inance, has signi ican ly
con ibu ed o unding sus ainable p ojec s ac oss membe s a es. This
aligns wi h he EU’s Ac ion Plan on Sus ainable Finance, which aims o
eo ien capi al lows owa d sus ainable in es men o achie e sus-
ainable and inclusi e g ow h. Baue (2022) examined he e olu ion o
esponsible in es ing, emphasizing i s ans o ma ion om a niche o a
mains eam in es men solu ion p opelled by bo h ma ke dynamics and
a genuine shi owa d ecognizing en i onmen al and social isks.
Baue (2022) unde sco ed he complexi y o balancing inancial and
non inancial objec i es wi hin he EU’s legal and egula o y ame-
wo ks, pa icula ly highligh ing he challenges o in eg a ing sus ain-
abili y in o in es men s a egies while managing inhe en ade-o s.
Baue ad oca ed o au hen ici y in he esponsible in es men sec o ,
u ging a anspa en and since e app oach o aligning inancial se ices
wi h sus ainabili y objec i es, in line wi h e ol ing EU egula ions and
socie al expec a ions. Schoenmake (2021) analyzed he in eg a ion o
en i onmen al sus ainabili y in o he Eu opean Cen al Bank’s (ECB)
inancial ope a ions, aligning wi h he b oade EU objec i es o
enhancing ESG pe o mance. I p oposes a ‘medium il ing’ s a egy o
he ECB’s asse and colla e al amewo k o pi o owa d low-ca bon
asse s, e ec i ely add essing he inhe en ma ke bias owa d
ca bon-in ensi e i ms. This app oach no only aims o educe ca bon
emissions in he ECB’s po olio by mo e han 50% bu also s a egically
aligns wi h he EU’s commi men o en i onmen al sus ainabili y by
incen i izing ca bon-in ensi e companies o adop g eene echnolo-
gies. This shi can po en ially ans o m he inancial landscape by
in eg a ing ESG conside a ions in o mone a y policy, e lec ing he EU’s
dedica ion o os e ing a sus ainable, low-ca bon economy.
Li e a u e gaps and u u e esea ch di ec ions
Despi e he comp ehensi e insigh s p o ided by heo e ical and
empi ical s udies, he e a e s ill signi ican gaps in he li e a u e ha
o e e ile g ound o u u e esea ch. Al hough ex ensi e, he exis ing
s udies o en lack a uni ied amewo k ha cohesi ely in eg a es heo-
e ical insigh s wi h empi ical indings ac oss a ious egional and
economic con ex s. Mo eo e , he apidly e ol ing landscape o inan-
cial echnologies and g een inance s a egies p esen s an oppo uni y
o no el esea ch a enues. Fu u e s udies could ocus on how hese
ad ancemen s can be le e aged o u he op imize ESG pe o mance
and add ess he nuanced in e ac ions be ween g een inance and
di e en sec o s o he economy. Addi ionally, longi udinal s udies ha
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3
ack he e olu ion o hese ela ionships o e ime, especially in
esponse o changing en i onmen al policies, economic condi ions, and
echnological ad ancemen s, a e needed. Add essing hese gaps will no
only enhance he academic discou se bu also p o ide ac ionable in-
sigh s o policymake s and indus y s akeholde s, guiding he global
economy owa d a mo e sus ainable, esilien , and en i onmen ally
conscious u u e.
Based on he abo emen ioned indings, his s udy es s he ollowing
hypo hesis:
H1.G een inance has a s a is ically signi ican impac on he en i on-
men al dimension o ESG pe o mance in EU coun ies.
Ma e ials and me hods
Theo e ical backg ound and model speci ica ion
Acco ding o he li e a u e e iew, he in e play be ween g een
inance and en i onmen al sus ainabili y has eme ged as a pi o al a ea
in con empo a y economic esea ch. G een inance, cha ac e ized by
in es men s in sus ainable, en i onmen ally iendly p ojec s and
echnologies, plays a c ucial ole in s ee ing economies owa d sus-
ainable g ow h ajec o ies. This shi is pi o al o add essing global
challenges such as clima e change and esou ce deple ion. The en i-
onmen al, social, and go e nance (ESG) c i e ia se e as a comp e-
hensi e amewo k o assessing he sus ainabili y and socie al impac o
an in es men in a company o business. The ela ionship be ween g een
inance and he en i onmen al dimension o ESG pe o mance is sig-
ni ican o policymake s and in es o s alike, as i unde sco es he po-
en ial o g een inance as a ool o en i onmen al imp o emen . To
empi ically in es iga e his ela ionship, a panel da a econome ic
model is employed. Wi h i s abili y o cap u e bo h c oss-sec ional and
ime-se ies a ia ions, panel da a o e a obus amewo k o analyzing
he dynamic in e ac ion be ween g een inance and en i onmen al
pe o mance. The panel da a econome ic model was o mula ed wi h
he ollowing equa ion:
ESGei =
α
0+
α
1GFIi +
α
2Xi +
μ
i+λ +
ε
i ,(1)
whe e ESGei is he en i onmen al dimension o he ESG pe o mance o
coun y i in yea , deno ing he dependen a iable; GFIi is he
explana o y a iable, which ep esen s he le el o g een inance o
coun y i in yea ; Xi is he se o con ol a iables o coun y i in yea ;
μ
i,λ a e he egional and empo al e ec s; and
ε
i is he e o e m.
Es ima ion me hod
In he con ex o he in es iga ion, which has ocused on EU coun-
ies, whe e hese coun ies sha e a common economic and policy
amewo k, egional in e ac ions and spillo e e ec s a e p e alen . EU
coun ies equen ly in luence one ano he h ough ade, en i on-
men al policies, and sha ed egula ions. T adi ional panel models may
no adequa ely accoun o hese in e dependencies. A spa ial econo-
me ic model acili a es he modeling o hese spa ial dependencies,
which a e especially ele an wi hin a egion such as he EU. Commonly
u ilized spa ial modeling echniques include he spa ial lag model
(SLM), spa ial e o model (SEM), spa ial au o eg essi e model (SAR),
and spa ial Du bin model (SDM) (Liu & Nie, 2022). Among hese
models, he SDM s ands ou o i s capaci y o in eg a e elemen s o bo h
he spa ial lag model and he spa ial e o model. This app oach no only
conside s he spa ial lag o he esea ch uni bu also in oduces he lag
e m o he e o in o he independen a iables. Speci ically, he SDM
can unc ion as ei he a spa ial lag model o a spa ial e o model,
making i a p e e ed choice in con empo a y spa ial econome ic ana-
lyses (LeSage, 2014). The ounda ional s uc u e o he spa ial Du bin
model is p esen ed as o mula (2):
Yi =
ρ
WYi +
α
Vi +θWVi +φi+δ +
ε
i ,(2)
whe e Yi is he dependen a iable; Vi a e he explana o y a iables; φi
and δ a e he spa ial and empo al e ec s, espec i ely;
ε
i is he e o
e m;
ρ
,θ a e he spa ial eg essi e coe icien s; and W is he spa ial
weigh ma ix.
Re e ing o Eq. (1), he spa ial Du bin model was e o mula ed as
Eq. (3) o in es iga e he in luence o g een inance on he en i on-
men al aspec o ESG pe o mance:
ESGei =
ρ
WESGei +
α
1GFIi +
α
2Xi +θ1WGFIi +θ2WXi +φi+δ +
ε
i ,
(3)
The spa ial weigh ma ix p ima ily comp ises h ee main ca ego ies
(LeSage, 2014; Liu & Nie, 2022): he adjacency ma ix, he geog aphic
dis ance ma ix, and he economic ma ix. The adjacency ma ix, he
i s ype o ma ix, is cons uc ed by assessing whe he each coun y
sha es adjacen adminis a i e bounda ies in hei geog aphical loca-
ion. When wo a eas sha e such a bounda y, he co esponding coe i-
cien in he ma ix is se o 1; o he wise, i is se o 0. Addi ionally, in
some ins ances, a eas wi hou di ec ly adjacen uni s may s ill be
in luenced by nonadjacen a eas. The second ype o spa ial weigh
ma ix is he geog aphic dis ance ma ix, calcula ed using he ecip ocal
o he squa e o he geog aphical dis ance be ween pai s o coun ies.
The hi d ca ego y, he economic weigh ma ix, accoun s o a eas ha ,
despi e no being geog aphically adjacen o loca ed a apa , exhibi
signi ican simila i ies in indus ial and economic de elopmen .
As in p e ious s udies (LeSage, 2014; Liu & Nie, 2022), he
geog aphic dis ance ma ix (W1) was used o in es iga e he impac o
g een inance on he en i onmen al dimension o ESG pe o mance:
Wij =⎧
⎪
⎨
⎪
⎩
1
d2
0i=j
i∕= j(4)
whe e i=1….n, j=1..n, and n=27.
Be o e conduc ing he eg ession analysis, he Mo an index was
u ilized o examine he p esence o spa ial au oco ela ion in he en i-
onmen al dimension o ESG pe o mance. I spa ial co ela ion is
de ec ed, i necessi a es he es ablishmen o a spa ial econome ic
model; o he wise, nonspa ial econome ic me hods a e applied. In he
p ocess o model selec ion among SDMs, SLMs, o SEMs, a se ies o
empi ical analyses is unde aken. This p ocess commences wi h he
Hausman es , which aids in he de e mina ion o whe he ixed e ec s
o andom e ec s should be chosen. The Hausman es plays a pi o al
ole in disce ning he mos app op ia e app oach o accoun o unob-
se ed he e ogenei y in he da a, a ac o c i ical o model p ecision.
Following he Hausman es , he nex c i ical s ep is he likelihood a io
(LR) es . This es is ins umen al in e alua ing whe he he chosen
model should inco po a e a spa ial ixed e ec o a ime ixed e ec . This
decision is o he u mos impo ance o cap u ing he unique cha ac-
e is ics and empo al dynamics ha may in luence he a iables unde
examina ion. Fu he mo e, bo h he likelihood a io (LR) es and he
Wald es a e used. These es s enable esea che s o assess whe he he
ini ially chosen SDM can be simpli ied in o ei he an SLM o SEM,
po en ially leading o educ ions in model complexi y while e aining
obus explana o y powe .
To ensu e ha he es ima ed coe icien s a e no biased due o
omi ed a iable bias, measu emen e o s, o simul anei y, his s udy
employs a obus ness check using an al e na i e es ima ion app oach-
— andom e ec s and he sys em gene alized me hod o momen s (Sys-
GMM). Bo h he andom e ec s and Sys-GMM models add ess unob-
se ed he e ogenei y, which e e s o he a ia ion ac oss en i ies (such
as indi iduals, i ms, o coun ies) ha is no cap u ed by he obse ed
a iables (Dong e al., 2023). Random e ec s models assume ha his
he e ogenei y is unco ela ed wi h he explana o y a iables, while
A. Kwilinski e al.
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4
Sys-GMM makes mo e lexible assump ions and uses i s di e ences o
emo e he e ec s o ime-in a ian unobse ed he e ogenei y. This
dual app oach enhances he c edibili y and eliabili y o he indings.
Da a and a iable desc ip ions
Explained a iable
In line wi h indings om p e ious esea ch (Kwilinski e al., 2022a;
2022b; 2023a; 2023b; 2023c; Kwilinski, 2023), he ollowing consid-
e a ions in o med he selec ion o indica o s o ep esen he en i on-
men al dimension o ESG pe o mance: 1. Ag icul u al land (AL).
Sus ainable ag icul u al p ac ices and e ec i e land managemen play
pi o al oles in enhancing ag icul u al p oduc i i y while concu en ly
minimizing en i onmen al impac ; 2. Ag icul u e, o es y, and ishing
(AFF). The adop ion o sus ainable p ac ices wi hin hese sec o s yields
posi i e en i onmen al ou comes; 3. CO
2
emissions (CO
2
). Ele a ed CO2
emissions a e de imen al o en i onmen al pe o mance because hey
con ibu e o pollu ion; 4. Ene gy in ensi y le el o p ima y ene gy (EI).
Con inuous e o s o enhance ene gy e iciency esul in educed ene gy
consump ion, he eby con ibu ing o en i onmen al sus ainabili y.
Con e sely, highe ene gy in ensi y le els lead o dec eased en i on-
men al pe o mance; 5. Food P oduc ion Index (FPI). The implemen a-
ion o imp o ed ag icul u al p ac ices, including sus ainable a ming
echniques and educed ood was e, os e s inc eased ood p oduc ion
while mi iga ing en i onmen al impac s; 6. Le el o wa e s ess –
eshwa e wi hd awal as a p opo ion o a ailable eshwa e esou ces
(WS). Ele a ed wa e s ess le els ha e ad e se implica ions o en i-
onmen al pe o mance and can mani es as ecosys em deg ada ion,
wa e sca ci y, d ough , sal wa e in usion, and land subsidence; 7.
Me hane emissions (ME). The enac men o measu es o mi iga e
me hane emissions om a ious sou ces, including ag icul u e and
was e managemen , plays a c ucial ole in ad ancing en i onmen al
sus ainabili y; 8. Ni ous oxide emissions (NOE). E o s o educe
ni ous oxide emissions, pa icula ly in he ealm o ag icul u al ac i -
i ies, make meaning ul con ibu ions o en i onmen al sus ainabili y; 9.
Fo es a ea (FA). The expansion o o es ed a eas and he p omo ion o
sus ainable o es managemen p ac ices ha e posi i e in luences on
en i onmen al pe o mance; 10. Renewable ene gy consump ion (RE)
The p omo ion o enewable ene gy sou ces educes dependency on
ossil uels, he eby bols e ing en i onmen al sus ainabili y.
In his s udy, he en opy me hod was used o cons uc he en i-
onmen al dimension o he ESG pe o mance index. This me hod allows
o a sophis ica ed e alua ion o en i onmen al pe o mance, d awing
upon p inciples om in o ma ion heo y. The cons uc ion o he en i-
onmen al dimension o he ESG pe o mance index in ol es se e al
s eps:
1. To acili a e meaning ul compa isons and ensu e ha all he in-
dica o s a e on he same scale, all he da a we e no malized:
Posi i e con ibu o s:
Hi=Ei−Emin
Emax −Emin
(5)
Nega i e con ibu o s:
Hi=Emax −Ei
Emax −E(6)
whe e Emax,min,Eia e he maximum, minimum and cu en alues o
he i- h componen s o he en i onmen al dimension o he ESG pe -
o mance index and Hi is he no malized alue.
2. The nex s ep in ol es compu ing he en opy and he weigh ing
ac o o each componen o he index:
De e mina ion o he en opy (ei) o he i- h componen o he
en i onmen al dimension o he ESG pe o mance index:
ei= − 1
ln (n)∑
n
i=1
1+Hi
∑n
i=1(1+Hi)×ln (1+Hi
∑n
i=1(1+Hi)),(7)
Compu a ion o he weigh (
ω
i) assigned o he i- h componen
wi hin he en i onmen al dimension o he ESG pe o mance index:
ω
i= (1−ei) ÷ ∑
n
i=1
(1−ei),(8)
En opy quan i ies he dispe sion, a iabili y, o unp edic abili y
wi hin en i onmen al pe o mance da a. En i ies wi h highe en opy
sco es a e hose wi h mo e di e se o unce ain anges o en i onmen al
pe o mance me ics.
3. Based on he calcula ed en opy alues, he en i onmen al
dimension o he ESG pe o mance index was calcula ed as ollows:
ESGe=∑
n
i=1
ω
iHi.(9)
Those wi h lowe en opy sco es a e posi ioned a he op, signi ying
mo e consis en o p edic able en i onmen al pe o mance, while hose
wi h highe en opy sco es a e u he down he index, e lec ing g ea e
a iabili y in hei en i onmen al me ics.
A s a is ical summa y o he samples used o calcula ing he en i-
onmen al dimension o he ESG pe o mance index is p o ided in
Table 1. The da a o assessing he ESG pe o mance index we e ob-
ained om he Wo ld Bank (2023).
Explana o y a iable
In his s udy, “g een inance” is quan i ied as he o al expendi u e
om he annual budge s o he EU Membe S a es, along wi h con i-
bu ions om he Eu opean Commission and he Eu opean In es men
Bank (Vic o e al., 2022; Amighini e al., 2022). This quan i ica ion is
speci ically aligned wi h he collec i e goal o con ibu ing o he in-
e na ional commi men o 100 billion USD o clima e inance, a key
a ge unde he Uni ed Na ions F amewo k Con en ion on Clima e
Change (UNFCCC). By measu ing g een inance in e ms o con ibu-
ions owa ds his speci ic commi men , he s udy aligns wi h an in e -
na ionally ecognized benchma k, ensu ing ha he inancial measu es
used a e no only ele an bu also e lec i e o b oade global p io i ies
in clima e inance (Sa ka , 2017; Roel sema e al., 2018). Fu he mo e,
he unds ea ma ked o he UNFCCC commi men a e designa ed o
clima e- ela ed p ojec s and ini ia i es, which a e likely o ha e a di ec
and measu able impac on en i onmen al sus ainabili y. This makes i a
sui able me ic o assessing he ela ionship be ween g een inance and
ESG pe o mance.
The calcula ion o he en i onmen al dimension o he ESG
Table 1
S a is ical desc ip ion o he samples o he ESG pe o mance index.
Symbols Mean SD Min Max
AL 41.452 15.932 7.366 67.250
AFF 2.208 1.182 0.212 6.302
CO
2
7.002 3.164 2.461 22.552
EI 3.604 1.079 1.011 6.770
FPI 97.583 8.114 70.430 118.630
WS 21.199 19.578 1.220 91.287
ME 0.988 0.502 0.436 3.495
NOE 0.611 0.375 0.099 2.070
FA 34.613 16.919 1.094 73.736
RE 19.696 11.766 0.220 54.161
Sou ce: De eloped by he au ho s.
A. Kwilinski e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100674
5
pe o mance index is me iculously di e en ia ed om he e alua ion o
he in luence o g een inance. While bo h a eas in e sec a he
con luence o en i onmen al and economic conside a ions, hey se e
dis inc analy ical pu poses. The en i onmen al ace o he ESG index is
c a ed as an all-inclusi e measu e, cap u ing he mul i ace ed p o-
g ession o a coun y owa d en i onmen al sus ainabili y. The index
hus e lec s he cumula i e impac o a coun y’s en i onmen al pol-
icies and co po a e p ac ices. Con e sely, he ocus on g een inance,
speci ically as an explana o y a iable, p o ides a mo e ocused in es-
iga ion. This s udy seeks o quan i y and elucida e he impac o en i-
onmen ally o ien ed inancial ini ia i es on ESG pe o mance. In
addi ion, i ep esen s he inancial commi men o sus ainable de el-
opmen , ex ending beyond me e compliance wi h egula ions o p o-
ac i e in es men in long- e m en i onmen al heal h. The delinea ion
be ween ESG index compu a ion and g een inance analysis is delib-
e a e. This app oach is pa icula ly ele an in he nuanced con ex o
ESG, whe e inancial lows owa d sus ainable p ojec s a e sc u inized
o hei eal-wo ld impac on en i onmen al ou comes. In his sense,
g een inance is no only a me ic o in es men magni ude bu also a
po en ial ca alys o imp o ed en i onmen al p ac ices and in-
no a ions. The analysis, he e o e, no only measu es cu en pe o -
mance bu also p obes he capaci y o g een inance o shape u u e
ajec o ies o sus ainabili y wi hin he ESG amewo k.
Сon ol a iables
Acco ding o p e ious s udies (LeSage, 2014; Liu & Nie, 2022;
Kwilinski e al., 2023a; 2023b; 2023c), he selec ed con ol a iables in
his pape a e as ollows:
1. Economic con ex : GDP ep esen s he o e all economic ac i i y and
weal h o a coun y. A high GDP o en implies inc eased indus ial-
iza ion and consump ion, which can esul in g ea e en i onmen al
impac s.
2. Technology and inno a ion: Resea ch and De elopmen (R&D)
cap u es a coun y’s in es men in echnology and inno a ion. Such
in es men s can lead o he de elopmen and adop ion o mo e
sus ainable p ac ices and cleane echnologies.
3. U baniza ion a e: U ban a eas o en exhibi dis inc en i onmen al
cha ac e is ics. U baniza ion can impac land use, in as uc u e
de elopmen , and esou ce consump ion pa e ns. Coun ies wi h
highe u baniza ion a es may expe ience di e en en i onmen al
challenges and solu ions han p edominan ly u al na ions.
4. T ade openness: In e na ional ade can lead o he impo and
expo o goods wi h a ying en i onmen al oo p in s. This may
a ec a coun y’s p oduc ion, consump ion, and en i onmen al
policies. Including ade openness allows us o con ol o he global
economic ac o s ha may shape a coun y’s en i onmen al
sus ainabili y.
Sample da a
This esea ch u ilizes a panel da ase ha encompasses 27 Eu opean
Union (EU) coun ies co e ing he pe iod om 2008 o 2020. The se-
lec ion o da a was con ingen upon i s a ailabili y. To elimina e he
impac o he e oscedas ici y ola ili y, his s udy employs he loga i h-
mic ans o ma ion o all a iables. The esul s o he desc ip i e
s a is ics o he selec ed a iables a e shown in Table 2.
Conside ing he esul s (Table 2), g een inance (GFI) demons a ed
subs an ial a iabili y, wi h a mean alue o 9145.863 and a ela i ely
high s anda d de ia ion o 15,734.580, spanning om a minimum o
3.000 o a maximum o 84,826.000. G oss domes ic p oduc e eals
signi ican di e si y, ea u ing an a e age GDP o 33,623.990 and a
no able s anda d de ia ion o 22,764.510, wi h alues anging om a
minimum o 6862.758 o a maximum o 123,678.700. Technology and
inno a ion (R&D) exhibi subs an ial a ia ions, wi h an a e age R&D
expendi u e o 3426.838 and a conside able s anda d de ia ion o
9123.234, spanning om a minimum o 2.000 o a maximum o
49,240.000. The u baniza ion a e (UR) di e s ac oss he cases exam-
ined, wi h an a e age UR o 72.668 and a s anda d de ia ion o 12.791,
anging om a minimum o 52.209 o a maximum o 98.079. T ade
openness (TO) a ies among he en i ies, wi h an a e age TO o 127.369
and a s anda d de ia ion o 66.632, anging om a minimum o 45.419
o a maximum o 380.104. These s a is ical insigh s p o ide a ounda-
ional unde s anding o he cen al endencies and dispa i ies wi hin he
da ase , o e ing c ucial in o ma ion abou he cha ac e is ics o he
a iables employed in he analysis.
The esul s o mul icollinea i y es s ensu e ha he GFI is no only a
p oxy o ESG pe o mance bu also an independen a iable in luencing
i . The a iance in la ion ac o (VIF) esul s, as displayed in Table 2,
e eal ha all he sco es a e below he commonly used h eshold o 5.
This indica es ha he le el o mul icollinea i y wi hin he model is no
se e e. The VIF o GF, ep esen ing g een inance and analogous o he
GFI, is he highes a 4.34 bu does no c oss he h eshold ha would
sugges high mul icollinea i y. Consequen ly, his inding suppo s he
in e p e a ion o he GFI as an independen a iable ha in luences he
en i onmen al dimension o ESG pe o mance a he han simply
se ing as a p oxy o i .
Resul s
A g aphical isualiza ion o he ESG pe o mance indices is shown in
Fig. 1. The esul s o he analysis show ha he ESG pe o mance index
inc eases among he selec ed coun ies, wi h he excep ion o Bulga ia,
Hunga y, Po ugal, and Romania.
The Mo an’s I es esul s (Table 3) indica e s ong posi i e spa ial
au oco ela ion o he a iable ESG (en i onmen al, social, and
go e nance) in he da ase om 2008 o 2020. The Mo an’s I alues
consis en ly ange be ween 0.531 and 0.577, and he associa ed Z(I)
s a is ics a e consis en ly g ea e han 5, wi h p- alues o 0.000 each
yea .
Spa ial au oco ela ion implies ha neighbo ing egions end o ha e
simila ESG sco es. In o he wo ds, a eas wi h high ESG pe o mance a e
o en su ounded by a eas wi h high ESG pe o mance, and he same
applies o a eas wi h low ESG pe o mance. The indings con i m ha
e o s o imp o e ESG pe o mance may ha e spillo e e ec s on
neighbo ing egions. I a speci ic policy o in es men ini ia i e boos s
ESG pe o mance in one egion, i may in luence nea by egions o
ollow sui , c ea ing a egional clus e o high ESG pe o mance.
Con e sely, low-pe o ming egions may need a ge ed in e en ions o
b eak he cycle o poo ESG pe o mance.
The esul s o he uni oo es (Table 4) e eal ha he a iables a e
Table 2
Va iables, sou ces and desc ip i e s a is ics.
Va iable Symbols Sou ce Mean SD Min Max VIF
G een Finance GFI UNCTAD (2022) 9145.863 15,734.58 3.000 84,826.00 4.34
G oss Domes ic P oduc GDP Wo ld Bank (2023) 33,623.99 22,764.51 6862.758 123,678.70 1.76
Technology and Inno a ion R&DWo ld Bank (2023) 3426.838 9123.234 2.000 49,240.00 3.45
U baniza ion Ra e UR Wo ld Bank (2023) 72.668 12.791 52.209 98.079 1.54
T ade Openness TO Wo ld Bank (2023) 127.369 66.632 45.419 380.104 1.61
Sou ce: De eloped by he au ho s.
A. Kwilinski e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100674
6
s a iona y. Bo h he Le in–Lin–Chu and Im–Pesa an–Shin es s yield p-
alues below he commonly chosen signi icance le el o 0.05, indica ing
ha hese a iables exhibi s able s a is ical p ope ies. The Phil-
lips–Pe on es sugges s ha all a iables exhibi signi icance upon he
second di e ence.
The esul s o he i s -di e enced a iables consis en ly indica e
s a iona i y ac oss all h ee es s. This implies ha he i s di e ences o
hese a iables a e s a iona y, e lec ing hei s able pa e ns o e ime.
The LM es s p o ide de ini i e e idence o he ejec ion o he null
hypo hesis a he 1% signi icance le el, indica ing he impe a i e need
o conside bo h spa ial e o and spa ial lag e ec s (Table 5). Fu he -
mo e, bo h he Wald and LR (likelihood a io) es s consis en ly epu-
dia e he no ion ha he SDM deg ades in o SAR o SEM a he 1%
signi icance le el. This inding obus ly ein o ces he asse ion ha he
u ilized SDM ep esen s a mo e app op ia e and de ensible model.
Simul aneously, he esul s o he Hausman es endo se he ixed e ec s
model and empha ically ejec he null hypo hesis linked o andom
e ec s.
The esul s o he OLS model (Table 6) show ha he GFI has a co-
e icien o 0.036, indica ing ha a one-uni change in g een inance is
associa ed wi h a 0.036-uni change in he ESG pe o mance index.
These coe icien s a e s a is ically signi ican , wi h low p- alues ( ypi-
cally less han 0.05), sugges ing hei impo ance in explaining ESG
Fig 1. The ESG pe o mance indices o all coun ies o 2008–2020.
Sou ce: De eloped by he au ho s.
Table 3
Ou pu s o Mo an’s I es .
Yea Mo an’s I o ESGeZ(I) p- alue
2008 0.537 5.111 0.000
2009 0.544 5.156 0.000
2010 0.531 5.046 0.000
2011 0.547 5.185 0.000
2012 0.562 5.326 0.000
2013 0.572 5.427 0.000
2014 0.577 5.472 0.000
2015 0.568 5.385 0.000
2016 0.576 5.453 0.000
2017 0.572 5.421 0.000
2018 0.573 5.433 0.000
2019 0.572 5.426 0.000
2020 0.565 5.377 0.000
Sou ce: De eloped by he au ho s.
Table 4
Resul s o Uni Roo Tes s.
Va iable Le in–Lin–Chu Im–Pesa an–Shin Phillips–Pe on
s a is ic p- alue s a is ic p- alue s a is ic p- alue
GFI -6.722 0.000 -8.122 0.000 33.861 0.000
GDP -2.420 0.008 -1.978 0.024 4.505 0.000
R&D -2.901 0.002 -0.502 0.308 1.517 0.065
UR 1.854 0.968 6.642 1.000 46.032 0.000
TO -1.865 0.031 -1.261 0.104 1.639 0.051
ΔGFI -10.934 0.000 -9.253 0.000 59.396 0.000
ΔGDP -11.788 0.000 -7.997 0.000 23.343 0.000
ΔR&D -6.752 0.000 -7.736 0.000 37.302 0.000
ΔUR -2.530 0.006 -4.361 0.000 12.821 0.000
ΔTO -15.343 0.000 -8.360 0.000 34.041 0.000
Sou ce: De eloped by he au ho s.
Table 5
Ou pu s o spa ial model selec ion.
Tes s a is ic p- alue
Hausman 28.109 0.001
Likelihood Ra io (LR) lag 31.596 0.000
e o 41.723 0.000
Lag ange mul iplie s (LM) lag 47.325 0.000
e o 39.871 0.000
Wald lag 36.287 0.000
e o 43.912 0.000
Sou ce: De eloped by he au ho s.
A. Kwilinski e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100674
7
pe o mance.
In he con ex o he Eu opean Union, he analysis o ESG pe o -
mance e eals in ica e ela ionships be ween a ious economic in-
dica o s and sus ainabili y me ics. G oss domes ic p oduc (GDP) and
esea ch and de elopmen (R&D) ha e s a is ically signi ican posi i e
associa ions wi h ESG pe o mance, boas ing coe icien s o 0.042 and
0.030, espec i ely, e lec ing he EU’s emphasis on inno a ion and
sus ainable economic g ow h as co e componen s o i s holis ic app oach
o ESG s anda ds. As GDP g ows, go e nmen s and businesses ha e mo e
esou ces o in es in en i onmen ally iendly echnologies and p ac-
ices. They can alloca e unds o de elop enewable ene gy sou ces,
imp o e ene gy e iciency, and educe pollu ion. Mo eo e , wi h highe
GDP, go e nmen s can a o d o implemen and en o ce s ic e en i-
onmen al egula ions. These egula ions can se limi s on emissions,
equi e companies o disclose hei en i onmen al impac , and manda e
sus ainable p ac ices. S ingen egula ions con ibu e o be e go e -
nance and ensu e ha businesses ope a e in a mo e socially esponsible
manne . Addi ionally, economic g ow h c ea es job oppo uni ies. I
hese jobs a e in sec o s ha p io i ize sus ainabili y and social e-
sponsibili y, hey can ha e a posi i e impac on ESG componen s by
imp o ing social well-being and educing unemploymen . R&D in-
es men s lead o echnological ad ancemen s, which can include
en i onmen ally iendly and socially esponsible inno a ions. Resea ch
and de elopmen o en ocuses on inding mo e sus ainable ways o
doing hings. This can in ol e op imizing p ocesses o educe was e,
ene gy consump ion, and esou ce use. Fu he mo e, inc eased R&D
os e s a cul u e o knowledge sha ing and collabo a ion. This can lead
o he dissemina ion o bes p ac ices ela ed o ESG ac oss indus ies,
helping businesses adop mo e esponsible app oaches o en i on-
men al, social, and go e nance issues. Con e sely, he u baniza ion a e
(UR) indica es a obus nega i e ela ionship, wi h a coe icien o
-0.208, sugges ing ha highe u baniza ion a es in he EU migh p e-
sen challenges o main aining high ESG pe o mance, necessi a ing
a ge ed u ban sus ainabili y ini ia i es. U baniza ion o en leads o
inc eased indus ializa ion, cons uc ion, and anspo a ion in ci ies,
esul ing in highe pollu ion le els, inc eased ene gy consump ion, and
g ea e p essu e on na u al esou ces. To add ess hese challenges,
go e nmen s should implemen u ban sus ainabili y policies, which
include anspa en ci y planning and measu es o comba co up ion.
Encou aging communi y pa icipa ion in u ban planning and decision-
making can p omo e mo e sus ainable and socially esponsible u ban
de elopmen .
Inco po a ing spa ial dynamics wi hin he EU, he spa ial Du bin
model (SDM) wi h spa ial ixed e ec s unde sco es ha GFI has a
s a is ically signi ican posi i e ela ionship wi h ESG pe o mance,
echoing he EU’s s a egic in es men in g een inance o bols e sus-
ainabili y. GDP con inues o exe a po en posi i e in luence on ESG
pe o mance, aligning wi h he EU’s economic policies ha in eg a e
sus ainabili y in o he g ow h na a i e. The posi i e impac o R&D and
he signi ican posi i e ela ionship be ween u baniza ion a e and he
EU’s commi men o inno a ion and sus ainable u ban de elopmen a e
pi o al o enhancing ESG pe o mance. Fu he mo e, ade openness
(TO) signi ican ly bols e s ESG pe o mance, highligh ing he EU’s ocus
on sus ainable ade policies, which should include measu es o p omo e
esponsible ade, enhance en i onmen al s anda ds, imp o e social
well-being, and s eng hen go e nance mechanisms. When coun ies
engage in in e na ional ade, hey o en seek o mee in e na ional
en i onmen al s anda ds, educe ca bon emissions, and p omo e sus-
ainable esou ce managemen . In addi ion, in e na ional ade can lead
o he ans e o knowledge, echnology, and expe ise. This can bene i
a coun y’s social aspec s by imp o ing educa ion, heal hca e, and ac-
cess o inno a i e solu ions.
The comp ehensi e SDM, ac o ing bo h spa ial and empo al ixed
e ec s, o e s an in-dep h unde s anding o how hese a iables in lu-
ence he ESG pe o mance index ac oss EU membe s a es o e ime. The
models’ R-squa ed alues, anging om 0.531 o 0.582, e lec a sub-
s an ial explana ion o he a iance in he ESG pe o mance index,
esona ing wi h he EU’s mul i ace ed app oach o ESG. The log-
likelihood, sigma2_e, AIC, and BIC me ics a i m he models’ obus -
ness, esona ing wi h he EU’s commi men o p ecision and eliabili y
in policy modeling and decision-making, ensu ing ha sus ainabili y
ini ia i es a e g ounded in obus analy ical amewo ks.
Table 7 demons a es he empi ical esul s om wo obus ness es s
using di e en econome ic models: he andom e ec s model and he
Table 6
The empi ical esul s o OLS and SDM.
Va iables OLS SDM
Spa ial ixed-e ec s Time ixed-e ec s Bo h e ec s
coe icien p- alue coe icien p- alue coe icien p- alue coe icien p- alue
GFI 0.036 0.000 0.001 0.041 0.024 0.000 0.001 0.048
GDP 0.042 0.004 0.089 0.000 0.024 0.076 0.082 0.000
R&D 0.030 0.000 0.016 0.013 0.015 0.001 0.028 0.000
UR -0.208 0.000 0.354 0.014 -0.127 0.000 0.067 0.678
TO 0.116 0.000 0.086 0.000 0.180 0.000 0.053 0.030
cons 0.475 0.002 – – – – – –
W ×GFI – – 0.356 0.091 1.220 0.134 0.747 0.039
W ×GDP – – -0.972 0.444 5.982 0.028 7.481 0.005
W ×R&D– – 1.064 0.318 -0.078 0.936 3.705 0.004
W ×UR – – 29.219 0.042 34.453 0.000 -8.421 0.744
W ×TO – – 2.982 0.024 15.116 0.000 0.246 0.938
R20.4898 0.541 0.582 0.531
Log-likelihood –767.3375 384.7316 782.5069
sigma2_e –0.001 0.000 0.007 0.000 0.001 0.000
AIC -631.8367 -1510.675 -747.4633 -1541.014
BIC -608.672 -1464.346 -704.9946 -1494.684
Sou ce: De eloped by he au ho s.
Table 7
The empi ical esul s o obus ness es s.
Random e ec s Sys-GMM
coe icien p- alue coe icien p- alue
ESG −1– – 0.718 0.000
GFI 0.008 0.011 0.006 0.043
Con ol a iables Yes
Cons an -1.722 0.000 -1.108 0.001
R20.212 – –
AR (1) – – -9.86 0.000
AR (2) – – -0.44 0.663
Sa gan es – – 5.16 0.271
Sou ce: De eloped by he au ho s.
A. Kwilinski e al.
Jou nal o Inno a ion & Knowledge 10 (2025) 100674
8
