CORE INDUSTRY AGGLOMERATION OF DIGITAL ECONOMY AND GREEN TOTAL FACTOR PRODUCTIVITY: EVIDENCE FROM CHINA
Abstract
With the advent of the information age and the development of network technology, the digital economy with digital knowledge and information as crucial production factors has become the core driving force for high-quality green economic and social development. This paper took the exploration of the role of the digital economy as an engine for regional green and high-quality development as the purpose of the study, incorporates the core industry agglomeration of the digital economy into the analysis framework of green total factor productivity (GTFP), depicted the characteristics of GTFP change from the dual dimensions of direct and indirect effects, and analyzed the spatial effects of specialized and diversified digital economy’s core industry agglomeration on the impact of GTFP using data and spatial measurement models of 25 provincial-level regions in China from 2003 to 2019. Results show that both the specialized digital economy’s core industry agglomeration and the diversified digital economy’s core industry agglomeration can significantly improve GTFP, and both have significant spatial spillover effects. At the same time, the impact of the digital economy’s core industry agglomeration on GTFP is spatial heterogeneity. GTFP in the eastern region can be significantly enhanced by the digital economy’s core industry agglomeration, and the specialized digital economy’s core industry agglomeration has a significant negative spillover effect on GTFP in the eastern region. In the contrast, GTFP in the mid-western region can be significantly enhanced only by the specialized digital economy’s core industry agglomeration, and the digital economy’s core industry agglomeration has no significant spatial spillover effect on GTFP in the mid-western region. The obtained conclusions reveal that each region should reasonably establish a cluster model of core industries in the digital economy to facilitate the green development of the regional economy.
Full text
40 2022, XXV, 4
Economics
10.15240/ ul/001/2022-4-003
CORE INDUSTRY AGGLOMERATION
OF DIGITAL ECONOMY AND GREEN TOTAL
FACTOR PRODUCTIVITY: EVIDENCE
FROM CHINA
Ping Li1, Huiying Fu2, Yueyao Li3
1 Hubei Uni e si y o Technology, School o Economics and Managemen , Depa men o In e na ional Economics,
China, ORCID: 0000-0002-5378-6188, [email p o ec ed];
2 Hubei Uni e si y o Technology, School o Economics and Managemen , Depa men o In e na ional Economics,
China, ORCID: 0000-0002-5154-6164, [email p o ec ed];
3 Hubei Uni e si y o Technology, School o Economics and Managemen , Depa men o Accoun ing, China,
ORCID: 0000-0002-1313-5612, 20191[email p o ec ed].
Abs ac : Wi h he ad en o he in o ma ion age and he de elopmen o ne wo k echnology, he
digi al economy wi h digi al knowledge and in o ma ion as c ucial p oduc ion ac o s has become
he co e d i ing o ce o high-quali y g een economic and social de elopmen . This pape ook
he explo a ion o he ole o he digi al economy as an engine o egional g een and high-quali y
de elopmen as he pu pose o he s udy, inco po a es he co e indus y agglome a ion o he
digi al economy in o he analysis amewo k o g een o al ac o p oduc i i y (GTFP), depic ed he
cha ac e is ics o GTFP change om he dual dimensions o di ec and indi ec e ec s, and analyzed
he spa ial e ec s o specialized and di e si ied digi al economy’s co e indus y agglome a ion on
he impac o GTFP using da a and spa ial measu emen models o 25 p o incial-le el egions in
China om 2003 o 2019. Resul s show ha bo h he specialized digi al economy’s co e indus y
agglome a ion and he di e si ied digi al economy’s co e indus y agglome a ion can signi ican ly
imp o e GTFP, and bo h ha e signi ican spa ial spillo e e ec s. A he same ime, he impac o
he digi al economy’s co e indus y agglome a ion on GTFP is spa ial he e ogenei y. GTFP in he
eas e n egion can be signi ican ly enhanced by he digi al economy’s co e indus y agglome a ion,
and he specialized digi al economy’s co e indus y agglome a ion has a signi ican nega i e
spillo e e ec on GTFP in he eas e n egion. In he con as , GTFP in he mid-wes e n egion can
be signi ican ly enhanced only by he specialized digi al economy’s co e indus y agglome a ion,
and he digi al economy’s co e indus y agglome a ion has no signi ican spa ial spillo e e ec
on GTFP in he mid-wes e n egion. The ob ained conclusions e eal ha each egion should
easonably es ablish a clus e model o co e indus ies in he digi al economy o acili a e he g een
de elopmen o he egional economy.
Keywo ds: Digi al economy, co e indus y agglome a ion, g een o al ac o p oduc i i y, high-
quali y g een de elopmen , spa ial Du bin model.
JEL Classi ica ion: L16, Q01.
APA S yle Ci a ion: Li, P., Fu, H., & Li, Y. (2022). Co e Indus y Agglome a ion o Digi al
Economy and G een To al Fac o P oduc i i y: E idence om China. E&M Economics and
Managemen , 25(4), 40–57. h ps://doi.o g/10.15240/ ul/001/2022-4-003
In oduc ion
In ecen yea s, he wa e o digi aliza ion has
swep he wo ld, and he digi al economy, a new
economic o m, has eme ged and become an
impo an d i ing o ce o ans o ma ion and
upg ading, as well as he high poin o a new
EM_4_2022.indd 40 7.12.2022 10:55:52
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4, XXV, 2022
Economics
ound o indus ial compe i ion among coun ies
a ound he wo ld. In pa icula , he COVID-19
ou b eak in 2020, while gi ing he adi ional
manu ac u ing indus y a conside able impac
and posed se e e challenges o economic
de elopmen a ound he wo ld. I has u he
highligh ed he ole o he engine o he digi al
economy and made i a key d i ing o ce o he
global economic eco e y and he de elopmen
o he wo ld economy (S eine , 2019). Fo
China, on he one hand, a e yea s o apid
de elopmen , he adi ional kine ic ene gy o
he na ional economy con inues o weaken
and can no longe o ce ully pull he economy
o soa , so i is u gen o ind new economic
g ow h kine ic ene gy; on he o he hand, he
ex ensi e adi ional pa e n o economic g ow h
emphasizes quan i y, igno es quali y and low
e iciency, which causes was e o esou ces and
also b ings se e e en i onmen al p oblems.
The imbalance be ween economic de elopmen
and ecological en i onmen al p o ec ion needs
o be sol ed u gen ly. The concep o g een
de elopmen o lead o high-quali y economic
de elopmen has become he key o sol ing he
p oblem.
I is wo h men ioning ha digi al
echnologies such as In o ma ion and
Communica ion Technologies (ICTs), which can
imp o e ene gy e iciency (Rod iguez-Lluesma
e al., 2021; Usman e al., 2021), we e desc ibed
by he Sus ainable De elopmen Goals (SDGs)
as enable s o sus ainable de elopmen (Lu
e al., 2020; Zhang e al., 2021). Mo eo e , as
a new d i ing o ce o economic de elopmen ,
he digi al economy ook ICTs as he co e
o p o iding new impe us o en i onmen al
imp o emen . Schola s ound ha he popula i y
o he digi al economy in he ield o ene gy
consump ion and en i onmen al p o ec ion was
conduci e o sol ing p oblems such as declining
en i onmen al ca ying capaci y and sca ci y
(Junio e al., 2018; Rehman e al., 2021). The
digi al economy has g ea po en ial o imp o e
he ecological en i onmen (Alam & Mu ad,
2020) by con inuously educing emissions o
pollu an s such as ca bon dioxide (Nizam e al.,
2020), sul u dioxide (Yang e al., 2021), and
indus ial was ewa e (Sun e al., 2022) h ough
inno a ion o g een echnologies, upg ading
o indus ial s uc u e and imp o emen o
he e iciency o en i onmen al managemen .
The e o e, he de elopmen o he digi al
economy was in line wi h he concep o
g een de elopmen . The digi al economy had
a posi i e impac on high-quali y economic
de elopmen , inno a i e de elopmen , and
g een de elopmen (Yang e al., 2022). In his
con ex , he mechanism o he digi al economy
d i ing high-quali y economic de elopmen had
undoub edly become he ocus o academic
a en ion. Li e al. (2022) poin ed ou ha
echnological inno a ion was an impo an
way o he digi al economy o imp o e he
e iciency le el o he g een economy. Wang
e al. (2022) u he imp o ed he impac pa h
o he digi al economy on high-quali y economic
de elopmen based on he o me , belie ing
ha indus ial es uc u ing was also one o
he essen ial in e media y mechanisms o
he digi al economy o p omo e high-quali y
g een de elopmen di ec ly. Ma and Zhu (2022)
sha ed he same iew and a gued ha he
digi al economy could in luence high-quali y
g een de elopmen in he su ounding a ea
h ough spa ial spillo e e ec s. While Ren
e al. (2022) a gued om u ban clus e s wi h
di e en le els o digi al economy de elopmen
ha digi al economy indus y agglome a ion
a ec ed g een inclusi e g ow h h ough
ene gy consump ion, en i onmen al pollu ion,
economic g ow h, human capi al, indus ial
s uc u e, and echnological p og ess.
In he con ex o China’s adhe ence o he
concep o g een de elopmen and p omo ion
o high-quali y economic de elopmen , he
digi al economy had become a signi ican
de elopmen end in he new e a o i s g een
bene i s. A he same ime, o u he measu e
he le el o high-quali y g een de elopmen ,
schola s p oposed he indica o o he g een
o al ac o p oduc i i y by comp ehensi ely
conside ing economic g ow h, ene gy
consump ion, and en i onmen al pollu ion,
and used i as an essen ial basis o e alua ing
o ganic coo dina ion be ween he le el o
g een de elopmen and quali y o economic
de elopmen . Th ough he s udy o g een o al
ac o p oduc i i y, i was ound ha in e ne
g ow h (Li e al., 2020) and digi al echnologies
ep esen ed by ICTs (Hao e al., 2022) could
con ibu e o g een o al ac o p oduc i i y. In
addi ion, he de elopmen o he digi al economy
migh be accompanied by agglome a ions
o indus ies ela ed o he digi al economy,
which could con ibu e o he in ensi ica ion
and scale de elopmen o he agglome a ion
a ea. This agglome a ion p ocess migh also
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be accompanied by economic phenomena
such as he en i e low o labo and capi al,
echnological inno a ion, and en e p ise
compe i ion, which in u n would b ing abou
changes in he in ensi y o social esou ce
consump ion, inpu -ou pu e iciency, and
en i onmen al quali y. Then i led o changes
in egional g een o al ac o p oduc i i y.
The e o e, his pape aims o explo e he ole o
digi al economy as an engine o egional g een
and high quali y de elopmen . By s udying he
ela ionship be ween he digi al economy’s co e
indus y agglome a ion and g een o al ac o
p oduc i i y, he engine d i ing ole o co e
indus ies in he digi al economy o high-quali y
economic de elopmen is u he explo ed.
This is o g ea p ac ical signi icance o u he
p omo ing he de elopmen o economic digi al
ans o ma ion and high-quali y g een socio-
economic in he new e a.
The no el ies and con ibu ions o his s udy
a e as ollows. (1) Based on he pe spec i e
o indus ial agglome a ion, his s udy clea ly
de ines he conno a ion and ex ension o
co e indus ies in he digi al economy, and
he impac mechanisms o di e en co e
indus ies in he digi al economy on g een
o al ac o p oduc i i y we e analyzed, which
p o ides a new pe spec i e o p omo ing
high-quali y g een de elopmen o he egional
economy h ough he de elopmen o he
digi al economy. (2) This s udy ully conside s
coo dina ed de elopmen be ween economic
g ow h, ene gy u iliza ion, and en i onmen al
p o ec ion. The EBM (Epsilon Based Measu e)
model was used o cons uc mul i-dimensional
and mul i-le el p o incial g een o al ac o
p oduc i i y including non-desi ed ou pu , o
comp ehensi ely and sys ema ically measu e
he le el o high-quali y g een de elopmen o
each egion’s economy. (3) The spa ial Du bin
model was used o empi ically examine he
impac o di e en digi al economy’s co e
indus y agglome a ion models on g een o al
ac o p oduc i i y. I u he explo es he spa ial
e ec s o he digi al economy’s co e indus y
agglome a ion on g een o al ac o p oduc i i y
while s udying di ec e ec s. I gi es as
di e ences in geog aphic loca ion ac oss
China’s p o inces.
The es o his s udy is a anged as ollows.
Sec ion 1 e iews he li e a u e on he co e
indus y agglome a ion o he digi al economy
a ec ing o al g een ac o p oduc i i y and
p oposes hypo heses. Sec ion 2 in oduces
da a indica o s and measu emen models used
in his s udy. Sec ion 3 is empi ical analysis,
which ob ains he esul s o empi ical esea ch.
Sec ion 4 is he conclusions o his s udy, which
pu s o wa d manage ial implica ions.
1. Li e a u e Re iew and Hypo hesis
De elopmen
G een o al ac o p oduc i i y is a g een
de elopmen indica o ha conside s
economic g ow h, esou ce conse a ion, and
en i onmen al p o ec ion and comp ehensi ely
e alua es he quali y o economic g ow h. The
agglome a ion o s a egic eme ging indus ies
ep esen ed by he digi al economy’s co e
indus y has an ob ious spa ial spillo e e ec on
g een economic e iciency (Zeng e al., 2020). A
he same ime, he impac o di e en indus ial
agglome a ion me hods on g een de elopmen
migh di e . In his ega d, his s udy ocuses
on he wo indus ial agglome a ion modes o
specializa ion and di e si ica ion. I illus a es
he impac pa h o he digi al economy’s co e
indus y agglome a ion on g een o al ac o
p oduc i i y based on di ec and spillo e
e ec s b ough by indus ial agglome a ion om
he pe spec i e o spa ial associa ion.
1.1 The Di ec E ec o he Co e
Indus y Agglome a ion o Digi al
Economy on In e p o incial G een
To al Fac o P oduc i i y
Acco ding o MAR (Ma shall-A ow-Rome )
ex e nali y heo y, and Jacobs’s ex e nali y
heo y, he digi al economy’s co e indus y
agglome a ion mainly ac ed on o al g een
ac o p oduc i i y h ough economies o scale,
echnology, and indus ial s uc u e e ec s. I
a ec ed g een o al ac o p oduc i i y o some
ex en .
F om he pe spec i e o scale e ec , he
specialized digi al economy’s co e indus y
agglome a ion could ealize common
u iliza ion o public in as uc u e, in e media e
commodi ies, and labo esou ces in he
agglome a ion a ea by he co e en e p ises
o he same digi al economy. Signi ican ly i
educed ansac ion cos s, sea ch cos s, and
p oduc ion cos s while imp o ing he e iciency
o public esou ce u iliza ion. A he same ime,
gi en he wide applica ion o digi al p oduc s and
echnologies in o he indus ies, he specialized
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digi al economy’s co e indus y agglome a ion
would p omo e specialized agglome a ion o
o he indus ies wi h indus ial connec ions, and
u he , i exe ed scale economy h ough he
sha ing mechanism.
F om he pe spec i e o echnical e ec , he
digi al economy’s co e indus y agglome a ion
would cause a signi ican accumula ion and
low o digi al alen s and in o ma ion in he
agglome a ion a ea. Specialized indus ial
agglome a ion could p omo e dissemina ion
and mu ual lea ning o knowledge and
echnology be ween en e p ises in he indus y
so ha en e p ises could lea n om each
o he ’s s eng hs and cons an ly imp o e
hei echnologies and p oduc s. Di e si ied
indus ial agglome a ion could b ing abou
knowledge collisions be ween di e en ields,
and p omo e he c oss-bo de in eg a ion
and complemen a i y o knowledge and
echnology be ween indus ies. The diges ion
and abso p ion o in eg a ed inno a ion
u he p omo ed wide applica ion and
spa ial di usion o echnological inno a ion
(Du an on e al., 1999). F om he pe spec i e
o clean echnology, indus ial agglome a ion
could p omo e he in e ac ion, sha ing, and
dissemina ion o ene gy-sa ing in o ma ion
and clean echnologies among en e p ises
(Wang e al., 2021; Xie e al., 2019). Spillo e
e ec s o clean echnologies and knowledge
could con ibu e o en i onmen al echnology
inno a ion, he eby imp o ing g een o al
ac o p oduc i i y. In addi ion, he specialized
digi al economy’s co e indus y agglome a ion
p omo ed he o ma ion o compe i i e ela ions
be ween en e p ises in he agglome a ion a ea,
which made en e p ises in he indus y con inue
o ca y ou echnological inno a ion and
consciously ul ill social esponsibili ies such
as en i onmen al p o ec ion o enhance hei
ma ke compe i i eness. Finally, inno a i e
digi al echnologies and digi al p oduc s
b ough by specialized digi al economy’s co e
indus y agglome a ion and di e si ied digi al
economy’s co e indus y agglome a ion would
be u he applied o o he indus ies associa ed
wi h hem. G een o al ac o p oduc i i y would
be comp ehensi ely imp o ed by imp o ing
esou ce u iliza ion e iciency and ene gy
u iliza ion e iciency o o he indus ies.
F om he pe spec i e o he indus ial
s uc u e e ec , on he one hand, he digi al
economy’s co e indus y agglome a ion
would p omo e he de elopmen o he digi al
economy i sel . Meanwhile, in he p ocess o
in eg a ing he digi al economy and he eal
economy, i would p omo e he upg ading o he
indus ial s uc u e by di ec ly in luencing he
use and alloca ion o esou ce elemen s such as
human capi al and scien i ic and echnological
inno a ion (Liu & Chen, 2021). On he o he
hand, echnological inno a ion b ough by he
digi al economy’s co e indus y agglome a ion
would u he p omo e digi al indus ializa ion
and indus ial digi aliza ion and hen p omo e
he upg ading o indus ial s uc u e.
Since economic s uc u e a ec ed economic
g ow h, ene gy demand, and en i onmen al
oo p in s (Ahmed e al., 2022), upg ading he
indus ial s uc u e b ough by co e indus ies in
he digi al economy would p omo e g een and
low-ca bon de elopmen . Based on he abo e
analysis, his s udy p oposes he ollowing
hypo hesis:
H1: Specialized digi al economy’s co e
indus y agglome a ion and di e si ied digi al
economy’s co e indus y agglome a ion can
imp o e g een o al ac o p oduc i i y in he
egion.
1.2 The Spillo e E ec o he Co e
Indus y Agglome a ion o Digi al
Economy on he P o incial G een
To al Fac o P oduc i i y
While he digi al economy’s co e indus y
agglome a ion a ec ed local g een o al ac o
p oduc i i y, i migh also ha e an impac on
g een o al ac o p oduc i i y in neighbo ing
egions due o i s spa ial ele ance. Tha is,
he e was a spa ial spillo e e ec .
F om he pe spec i e o spa ial ele ance
o he digi al economy, he e was a signi ican
spa ial co ela ion o digi al economy
de elopmen be ween egions (Li & Liu, 2021;
Wang e al., 2022). The de elopmen o he local
digi al economy would a ec he de elopmen
o he digi al economy in neighbo ing egions.
The co e indus y agglome a ion o he digi al
economy would p omo e he de elopmen
o he local digi al economy because o i s
economies o scale and echnical e ec s, and
i would also a ec he de elopmen le el o he
digi al economy in neighbo ing a eas h ough
he spa ial ele ance o he digi al economy
and ul ima ely a ec he g een o al ac o
p oduc i i y o neighbo ing a eas.
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Economics
F om he pe spec i e o echnological
spillo e , he digi al economy has a signi ican
posi i e spa ial spillo e e ec on inno a ion
e iciency and was a i al d i ing o ce o
imp o ing inno a ion e iciency in China
(Wang & Cen, 2022). A he same ime,
he digi al economy’s co e indus y had he
ad an age o o e coming spa ial es ic ions
o in o ma ion echnology dissemina ion.
When he digi al economy’s co e indus y
eached a pa icula agglome a ion scale in
he local a ea, he knowledge and echnology
in e ac ion ne wo k wi hin and be ween he
indus ies would be expanded acco dingly.
Technological inno a ion gene a ed by he
collision o local knowledge could achie e in e -
egional echnology spillo e by expanding
he knowledge in e ac ion ne wo k and he
ba ie less dissemina ion o digi al in o ma ion
and a ec ing neighbo ing egions’ g een o al
ac o p oduc i i y.
F om he pe spec i e o he demons a ion
e ec be ween egions, he p omo ion o
g een o al ac o p oduc i i y in one egion
would pu neighbo ing egional go e nmen s
unde p essu e om public opinion o adop
simila beha io s in ene gy conse a ion and
emission educ ion wo k (Zhang e al., 2019).
Residen s would supe ise local go e nmen s
o make policy imp o emen s by compa ing
he policy beha io s o local go e nmen s.
Good policies would a ac neighbo ing
egions o adop simila policies o inc ease
g een o al ac o p oduc i i y. The e o e, he
co e indus y agglome a ion o he digi al
economy could u ge neighbo ing egions o
inc ease hei g een o al ac o p oduc i i y
by p omo ing he imp o emen o local g een
o al ac o p oduc i i y. Based on he abo e
analysis, his s udy p oposes he ollowing
hypo hesis:
H2: Specialized digi al economy’s co e
indus y agglome a ion and di e si ied digi al
economy’s co e indus y agglome a ion can
imp o e g een o al ac o p oduc i i y in
neighbo ing a eas.
2. Me hodology
2.1 Model Design
The Spa ial Lag Model (SAR), Spa ial E o
Model (SEM), and Spa ial Du bin Model (SDM)
a e h ee models commonly used o spa ial
me ology. Compa ed wi h SAR and SEM,
SDM conside s he e ec o spa ial hys e esis
e ms o he independen a iable and he
dependen a iable on he dependen a iable,
which can be e es ima e he spillo e e ec
d i en by di e en obse a ion indi iduals.
Since g een o al ac o p oduc i i y (GTFP) in
he egion will no only be a ec ed by he digi al
economy indus y agglome a ion le el (MJ)
in he egion, bu also by he digi al economy
indus y agglome a ion le el and g een o al
ac o p oduc i i y in he su ounding a eas.
The e o e, SDM is used as a basic empi ical
model in his s udy, and o he con ol a iables
a e in oduced o he p oblem o a iable
omission. The gene al o m o he spa ial Du bin
model is shown as equa ion (1):
lnGTFP = ω0 + ρWlnGTFPi +
+ α lnMJi + γ lnPi + βW lnMJi +
+ θW lnPi + μi + + εi
(1)
whe e: Pi is he con ol a iable; W is he spa ial
weigh ma ix; ρ, β and θ a e spa ial in e ac ion
e m coe icien s o he dependen , independen ,
and con ol a iables; α and γ ep esen he
elas ic coe icien s o he independen and
con ol a iables; μi and ep esen spa ial and
empo al e ec s, espec i ely.
To analyze he spa ial spillo e e ec
o g een o al ac o p oduc i i y mo e
comp ehensi ely and objec i ely, his s udy
e e s o he exis ing li e a u e. I selec s
a con igui y-based spa ial weigh s ma ix
based on geog aphical cha ac e is ics and
an economic dis ance special weigh s ma ix
based on economic and social cha ac e is ics.
W1 is he con igui y-based spa ial weigh s
ma ix. I e lec s he spa ial connec ion be ween
wo adjacen uni s (Mo on e al., 2018), whe e
he elemen s on he diagonal a e 0. The
o he elemen exp essions a e based on he
adjacency ma ix, shown as equa ion (2):
(2)
whe e: i = j = 1, 2, 3, ..., n.
W2 is he economic dis ance he special
weigh s ma ix. Conside ing he impac o
di e ences in economic de elopmen le els in
di e en egions on he spa ial spillo e e ec
o GTFP, his s udy bo ows he me hod o Han
e al. (2018) o cons uc an economic dis ance
special weigh s ma ix h ough pe capi a GDP,
shown as equa ion (3):
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(3)
whe e: Y i and Y j a e GDP pe capi a in he
sample pe iod o egion i and egion j,
espec i ely. The main diagonal elemen s in he
ma ix a e 0.
2.2 Va iable Selec ion and Da a Sou ce
The in e p e ed a iable is g een o al
ac o p oduc i i y (GTFP) by p o ince. The
EBM model p oposed by Tone and Tsu su sui
(2010) compensa es o he sho comings o he
DEA model and SDM model o a ce ain ex en
by e ec i ely combining adial and non- adial
models. A he same ime, compa ed wi h he
Malmquis -Luenbe ge index, he GML index
o e comes he p oblem o no solu ion in he
linea p og amming o ML exponen , and he
calcula ion esul s a e ansi i e and cyclically
accumula i e. The e o e, his s udy e e s o he
me hod o Li and Wang (2022), using he EBM-
GML model o measu e GTFP.
In his s udy, labou , capi al, and ene gy
inpu s a e chosen as inpu indica o s, and
GDP and pollu ion emissions a e chosen as
expec ed and unin ended ou pu indica o s
espec i ely. Among hem, he o al ene gy
consump ion o ene gy inpu is exp essed
a e he p o inces a e con e ed in o s anda d
coal. The labo inpu is measu ed by he sum
o he employmen o he h ee indus ies in
each p o ince. The capi al inpu is based on
he physical capi al s ock o each p o ince as
he agen a iable. Conce ning he indings o
Shan (2008), physical capi al s ock is es ima ed
using he pe pe ual in en o y me hod. The
expec ed ou pu is exp essed by he o al
GDP alue o each p o ince. The GDP index
is used o calcula e he ac ual GDP o each
p o ince based on 2000. Undesi able ou pu s
a e ep esen ed by sul u dioxide emissions,
gene al indus ial solid was e emissions, and
indus ial was ewa e emissions.
Explana o y a iables include specialized
digi al economy’s co e indus y agglome a ion
(Ma ) and di e si ied digi al economy’s co e
indus y agglome a ion (Jacobs). Acco ding o
he S a is ical Classi ica ion o Digi al Economy
Indus ies and Co e Indus ies (2021) issued
by China, he digi al economy indus y can be
di ided in o digi al p oduc manu ac u ing (01),
digi al p oduc se ice indus y (02), digi al
echnology applica ion indus y (03), digi al
elemen s d i ing indus y (04) and digi al
e iciency imp o emen indus y (05). Among
hem, he 01–04 ca ego ies a e he co e
indus y o he digi al economy. Howe e , due
o he ini ial colla ion o he digi al economy
indus y di ision in 2021, i s a ge ed indus ial
da a s a is ics ha e no ye been o med.
Based on conside a ion o da a a ailabili y and
s a is ical calibe consis ency, his s udy e e s
o he “in o ma ion ansmission, so wa e,
and in o ma ion echnology se ice indus y”
classi ica ion s anda d in he High- ech Indus y
(Manu ac u ing) Classi ica ion (2017) and he
Na ional Economic Indus y Classi ica ion
o China (GB/T 4754–2017), by compa ing
a ious sub-ca ego ies o he digi al economy
indus y wi h i . Finally, co e indus ies in he
digi al economy a e selec ed o esea ch and
di ided in o he ollowing h ee ca ego ies,
namely in o ma ion ansmission, compu e
se ices, and so wa e indus ies, elec onic
and communica ion equipmen manu ac u ing
indus ies, and compu e and o ice equipmen
manu ac u ing indus ies. Based on he
p ac ice o Du an on and Puga (1999), his
s udy cons uc s indica o s o he specialized
digi al economy’s co e indus y agglome a ion
and di e si ied digi al economy’s co e indus y
agglome a ion, espec i ely, shown as
equa ions (4) and (5):
(4)
(5)
Among hem, Qij ep esen s he p opo ion o
he digi al economy’s co e indus y j in egion i
o he o al numbe o employmen o all co e
indus ies in he digi al economy in egion i.
Qi is he a io o he numbe o employees in
he digi al economy’s co e indus y j na ionwide
and he o al numbe o employees in he co e
indus ies in he na ional digi al economy.
To be e in e p e he impac o he digi al
economy’s co e indus y agglome a ion
on GTFP, his s udy selec s in as uc u e
cons uc ion (In a), o eign di ec
in es men (FDI), en i onmen al egula ion
(En ), human capi al (Edu), u baniza ion le el,
deg ee o go e nmen in e en ion (Expend),
ene gy consump ion s uc u e (Ene gy), and
egional echnological inno a ion (Pa en )
as con ol a iables. Among hem, In a is
measu ed by he sum o ailway mileage, oad
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46 2022, XXV, 4
Economics
mileage and long-dis ance cable leng h in each
p o ince. FDI is exp essed by he ac ual use
o o eign di ec in es men as a p opo ion
o GDP. En is measu ed by he p opo ion
o in es men in indus ial pollu ion con ol
o o al indus ial ou pu . Edu is measu ed by
he p opo ion o s uden s en olled in o dina y
colleges and uni e si ies as a p opo ion o he
o al popula ion a he end o he yea . The le el
o u baniza ion is exp essed as he u baniza ion
a e o each p o ince. Expend is exp essed as
a p opo ion o go e nmen iscal expendi u e
o GDP. Ene gy is measu ed by he p opo ion
o coal consump ion con e ed in o s anda d
coal in o al ene gy consump ion. Pa en is
exp essed in he numbe o pa en ed in en ions
au ho ized.
Due o a la ge amoun o missing da a in
Hainan, Gansu, Qinghai, Xinjiang, Ningxia,
Tibe , Hong Kong, Macau, and Taiwan, his
s udy uses ele an da a om 2003 o 2019
om 25 p o inces o esea ch excep he
abo e 9 p o inces.
The da a a e mainly de i ed om he China
S a is ical Yea book, China Ene gy S a is ics
Yea book, China En i onmen al S a is ics
Yea book, China High Technology S a is ical
Yea book, Wind Da abase, P o incial S a is ical
Yea book, P o incial S a is ical Bu eau
o icial websi e, and local s a is ical bulle in.
A he same ime, he missing alues a e
supplemen ed by he in e pola ion me hod and
linea ex ension p edic ion me hod. To educe
he he e oscedas ici y, his s udy pe o ms
loga i hmic ea men on all a iables, and he
desc ip i e s a is ics o he a iables can be
seen in Tab. 1.
3. Resul s Analysis
3.1 Spa ial Au oco ela ion Tes
The p esence o absence o he spa ial
au oco ela ion o p ima y a iables in he
model is a p e equisi e o he abili y o model
a spa ial panel. Re e ing o Geniaux and
Ma ine i (2018), he Mo an index is selec ed
as an index o spa ial au oco ela ion es in
his s udy, o comp ehensi ely de ec spa ial
dis ibu ion cha ac e is ics o he g een o al
ac o p oduc i i y om pe spec i es o bo h
he whole and he local. This s udy uses
MaxDEA p o essional so wa e o measu e
and p ocess each p o ince’s GTFP om
2004 o 2019. Then, he Mo an’s I index o
he g een o al ac o p oduc i i y based on
Va iable Va iable-de ini ion Mean S anda d
e o
Leas
alue
C es
alue
Sample
alue
lnGTFP G een o al ac o p oduc i i y
in all p o inces −0.1443 0.2840 −1.1128 0.5644
400
lnMa Specialized indus y
agglome a ion 0.7020 0.4666 0.0174 1.6402
lnJacobs Di e si ied indus y
agglome a ion 0.8292 0.8593 −0.4147 5.0238
lnIn a In as uc u e cons uc ion 11.8379 0.8134 9.4389 13.0491
lnFDI Di ec in es men in auma 0.6527 0.7833 −2.2878 2.1032
lnEn En i onmen al egula ion −1.3210 0.7172 −4.0610 0.3926
lnEdu Human capi al 0.5467 0.3627 −0.7889 1.2750
lnU ban U baniza ion le el 3.9720 0.2640 3.2696 4.4954
lnExpend Go e nmen in e en ion 2.8928 0.3368 2.0691 3.6943
lnEne gy S uc u e o ene gy
consump ion 3.7064 0.5308 −1.0991 4.3537
lnPa en Regional echnological
inno a ion 7.7009 1.4483 4.5850 10.9978
Sou ce: own
Tab. 1: Desc ip i e s a is ics o he a iables
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a con igui y-based spa ial weigh s ma ix and
an economic dis ance special weigh s ma ix is
calcula ed by S a a 15.1 so wa e o es spa ial
co ela ion o he g een o al ac o p oduc i i y
unde di e en spa ial ma ices. Spa ial
au oco ela ion es esul s a e shown in Tab. 2.
I is no di icul o see ha when using he
con igui y-based spa ial ma ix and economic
dis ance special weigh s ma ix, excep o
Mo an’s I index be ween 2004 and 2007, which
is no signi ican and GTFP does no ha e
appa en spa ial au oco ela ion. The p- alue
o Mo an’s I index in he emaining yea s is
less han 10%, ejec ing he null hypo hesis o
andom spa ial dis ibu ion, and GTFP shows
signi ican spa ial au oco ela ion in he sample.
A he same ime, Mo an’s I o he g een o al
ac o p oduc i i y is g ea e han 0, indica ing
a posi i e spa ial co ela ion be ween GTFP
in a ious p o inces. Tha is, GTFP has solid
spa ial agglome a ion.
To mo e in ui i ely display he local
co ela ion ela ionship o he g een o al ac o
p oduc i i y and e eal he spa ial co ela ion
be ween he g een o al ac o p oduc i i y and
neighbo ing p o inces in a ious p o inces, his
s udy akes 2019 da a as an example. I d aws
Mo an’s I sca e plo s based on con igui y-based
spa ial weigh sma ix and economic dis ance
special weigh s ma ix, as shown in Fig. 1.
I can be seen ha when he con igui y-based
spa ial weigh s ma ix is adop ed, mos p o inces
in China a e mainly loca ed in he i s quad an
(HH) and he hi d quad an (LL). The p o inces
wi h highe g een o al ac o p oduc i i y ha e
highe GTFP han neighbo ing p o inces. GTFP
in neighbo ing p o inces wi h lowe g een o al
ac o p oduc i i y is also lowe , indica ing local
spa ial agglome a ion GTFP in a ious p o inces
unde he spa ial p oximi y weigh . When using
he economic dis ance special weigh s ma ix,
mos p o inces in China a e loca ed in he
hi d quad an (LL). A ew p o inces a e in he
i s quad an (HH) and ou h quad an (HL),
indica ing ha , GTFP in a ious p o inces
has local spa ial dependence and local spa ial
he e ogenei y unde he economic dis ance
special weigh s weigh .
Spa ial weigh s ma ix Con igui y-based Economic dis ance
Yea Mo an’s IP- alue Mo an’s IP- alue
2004 0.111 0.142 0.053 0.286
2005 0.102 0.215 0.081 0.216
2006 0.137 0.139 0.037 0.445
2007 0.148 0.129 0.068 0.304
2008 0.177 0.082 0.135 0.100
2009 0.183 0.061 0.131 0.092
2010 0.174 0.068 0.210 0.013
2011 0.180 0.064 0.251 0.004
2012 0.225 0.033 0.335 0.000
2013 0.238 0.025 0.381 0.000
2014 0.271 0.011 0.416 0.000
2015 0.283 0.008 0.465 0.000
2016 0.306 0.005 0.384 0.000
2017 0.355 0.002 0.385 0.000
2018 0.319 0.004 0.438 0.000
2019 0.294 0.006 0.476 0.000
Sou ce: own
Tab. 2: Mo an’s I alues o he g een o al ac o p oduc i i y om 2004 o 2019
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48 2022, XXV, 4
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To de e mine he mos sui able spa ial
econome ic model, his s udy uses S a a 15.1
so wa e o es he spa ial econome ic model
om assump ions o he con igui y-based spa ial
weigh s ma ix (W1) and he economic dis ance
special weigh s ma ix (W2) espec i ely. Tes
esul s a e shown in Tab. 3.
F om he LM es esul s based on he
o dina y linea OLS eg ession model, i can be
seen ha LM-lag, LM-e o , Robus LM-lag, and
Robus LM-e o in he con igui y-based spa ial
weigh s ma ix all pass a leas 10% o he
signi icance es , and LM-lag and Robus LM-
lag in he economic dis ance special weigh s
Fig. 1: Mo an’s I sca e plo o g een o al ac o p oduc i i y in 2019
Sou ce: own
Inspec ion
W1W2
S a is ical
alue P- alue S a is ical
alue P- alue
LM-lag 25.028*** 0.0000 7.042** 0.0080
Robus LM-lag 16.662*** 0.0000 15.470*** 0.0000
LM-e o 11.173** 0.0010 0.878 0.3490
Robus LM-e o 2.808* 0.0940 9.306** 0.0020
Spa ial e ec s LR 34.21*** 0.0002 44.970*** 0.0000
Time e ec LR 650.640*** 0.0000 728.290*** 0.0000
Hausman es 22.270* 0.0138 50.140*** 0.0000
Wald spa ial lag 48.440** 0.0000 118.810*** 0.0000
Wald spa ial e o 50.640*** 0.0000 105.330*** 0.0000
LR spa ial lag 46.630*** 0.0000 104.210*** 0.0000
LR spa ial e o 48.470*** 0.0000 125.780*** 0.0000
Sou ce: own
No e: *, **, and *** indica e s a is ical signi icance a he 10, 5, and 1% le els, espec i ely.
Tab. 3: Tes esul s o spa ial Du bin model unde di e en spa ial weigh ma ices
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economy is s udied sepa a ely, o o mula e
a mo e a ge ed de elopmen s a egy.
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Pos doc o al Science Founda ion P ojec
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