Agricultural Green Total Factor Productivity in Shandong Province of China

Peng, Yuanxin; Chen, Zhuo; Lee, Jay
A icle
Ag icul u al G een To al Fac o P oduc i i y in Shandong
P o ince o China
Ge man Jou nal o Ag icul u al Economics (GJAE)
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Sugges ed Ci a ion: Peng, Yuanxin; Chen, Zhuo; Lee, Jay (2024) : Ag icul u al G een To al Fac o
P oduc i i y in Shandong P o ince o China, Ge man Jou nal o Ag icul u al Economics (GJAE), ISSN
2191-4028, TIB Open Publishing, Hanno e , Vol. 73, Iss. 2, pp. 1-25,
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Ge man Jou nal o Ag icul u al Economics Vol. 73 (2024), No. 2, 1-25
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Submi ed: 22 Aug. 2022 | Accep ed: 04 Ap . 2024 | Published: 31 May 2024
Ag icul u al G een To al Fac o P oduc i i y in
Shandong P o ince o China
Yuanxin Peng 1, Zhuo Chen 2, and Jay Lee 3*
1 Zaozhuang Uni e si y, Zaozhuang, Shandong, China
2 Case Wes e n Rese e Uni e si y, Cle eland, and Ha ing on Hea and Vascula Ins i u e,
Uni e si y Hospi als, Cle eland, OH, USA
3 Ken S a e Uni e si y, Ken , USA
*Co espondence: Jay Lee, [email p o ec ed]
Abs ac : Sus ainable de elopmen o ag icul u e has an impo an impac on bo h socie y and
economy. In o de o unde s and he pa e ns o spa io- empo al a ia ion and he ac o s in-
luencing ag icul u al g een o al ac o p oduc i i y (AGTFP), his pape used Shandong p o -
ince o China as a case s udy. U ilizing he SBM-DEA and Malmquis models, along wi h panel
eg ession me hods, he s udy analyzes AGTFP based on da a om he Shandong S a is ical
Yea book (2009-2019). The esul s showed ha : (1) he AGTFP in Shandong p o ince was
smalle han he o al ac o p oduc i i y when no conside ing he undesi able ou pu , and he
AGTFP in mos egions o Shandong p o ince needed o be imp o ed. (2) The AGTFP o
Shandong p o ince showed an annual ising end, especially in he eas e n and no he n e-
gions. (3) In addi ion o he le els o echnology and managemen , he indus ializa ion and
le el o pe sonal de elopmen o a me s is also shown o ha e impac ed on AGTFP. Recom-
menda ions include adop ing ad anced echnologies, enhancing land managemen , p omo ing
e ia y sec o de elopmen , expanding ag icul u al p ocessing, and imp o ing a me skills
h ough educa ion and aining o boos AGTFP o achie e a sus ainable ag icul u al economy.
Keywo ds: AGTFP, SBM-DEA Model, Malmquis Model, Cen e o G a i y Model, Coe icien
o Va ia ion, Panel Reg ession
1 In oduc ion
Since he e o m and opening up in 1978, China's u al economy had de eloped apidly, and
he ou pu o a ious ag icul u al p oduc s had inc eased signi ican ly. In ecen yea s, he ou -
pu o majo ag icul u al p oduc s such as g ain, oil, ege ables, ui s, mea , poul y and eggs
we e among he highes in he wo ld (Rml , 2019; Chinai n, 2020).
Shandong p o ince is loca ed in he eas coas o China, wi h i s excellen geog aphical loca-
ion (see Appendix A), sui able clima ic condi ions and a de eloped ag icul u al economy. I
was o en anked as he i s in China in e ms o g oss ou pu alue o ag icul u e, added alue
o ag icul u e, expo alue among o he indica o s (Song e al., 2012). Shandong was also
anked as he hi d in g ain c op yield and sown a ea o ege ables, he i s in o al ui p o-
duc ion, and he i s in o al ou pu alue o animal husband y (China S a is ical Yea book,
2009-2019). Ag icul u al de elopmen equi es he use o a la ge amoun o chemical e iliz-
e s, and such use in Shandong p o ince has long been he second highes in China, second
only o Henan p o ince (China S a is ical Yea book, 2009-2019). G ain, ege able, and o he
c ops p oduce massi e amoun o s aw and li es ock b eeding p oduces a g ea deal was e.
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Excessi e use o chemical e ilize , was e om li es ock b eeding and inapp op ia e disposal
o s aw cause se ious non-poin sou ce pollu ion in u al a ea. Ag icul u al non-poin sou ce
pollu ion is he pollu ion gene a ed in ag icul u al p oduc ion ac i i ies ha pollu an s en e wa-
e h ough a mland su ace uno , soil low, a mland d ainage and unde g ound leakage (Ma
e al., 2009).
I is es ima ed ha ag icul u al non-poin sou ce pollu ion accoun s o one- hi d o he o al
wa e pollu ion in China (Li, 2022). Among hem, CODc , TN, and TP accoun ed o 44%, 57%
and 67%, espec i ely, o he o al discha ge o each pollu an (Huang e al., 2012). CODc is
he chemical oxygen consump ion measu ed by using po assium dich oma e (K2C 2O7) as ox-
idan , namely he dich oma e index. TN (To al Ni ogen) is he o al amoun o ni ogen p esen
in soil o wa e . I is calcula ed as he millig ams o ni ogen pe li e o wa e . TN is commonly
used o indica e he deg ee o nu ien pollu ion in wa e bodies. The highe he TN alue, he
mo e se e e he wa e quali y pollu ion. TP (To al Phospho us) is he o al con en o phospho-
us in soil o wa e . I is one o he indica o s used o measu e he le el o wa e pollu ion. A
highe TP alue indica es a highe deg ee o wa e quali y pollu ion.
The e o e, i is necessa y o s udy issues ela ed o ag icul u al sus ainable de elopmen , es-
pecially he g een ag icul u al p oduc i i y. This is because imp o ing g een ag icul u al e i-
ciency can educe inpu s o ag icul u al p oduc ion esou ces and he gene a ion o pollu an s,
he eby p omo ing ag icul u al sus ainabili y. Conside ing ha he ag icul u al de elopmen o
Shandong p o ince plays a e y impo an ole in China, i has g ea signi icance o s udy he
pa e ns o spa io- empo al a ia ion and mechanism associa ed wi h AGTFP in Shandong
p o ince. S udying AGTFP in he empo al dimension allows us o unde s and i s pa e ns o
change o e ime, while s udying i in he spa ial dimension enables us o unde s and i s spa ial
dis ibu ion cha ac e is ics.
We i s calcula ed ag icul u al non-poin sou ce pollu an s and used hem as he undesi able
ou pu . We selec ed a iables such as ag icul u al GDP, ag icul u al labo o ce, he o al powe
o ag icul u al machine y, a able land a ea, and i iga ed land a ea o he calcula ion o AGTFP
in Shandong p o ince. Then, he spa io empo al a ia ion pa e ns o AGTFP in Shandong
p o ince we e analyzed based on he calcula ed esul s. Finally, panel da a analysis was con-
duc ed o explo e he mechanisms o changes in AGTFP.
The es o he pape is o ganized as ollows: Sec ion 2 is p ima ily a li e a u e e iew ha aims
o enhance eade s' unde s anding o di e se pe spec i es on ag icul u al o al ac o p oduc-
i i y (ag icul u al TFP) and AGTFP. Sec ion 3 ou lines he selec ion o indica o s and da a
cha ac e is ics. Sec ion 4 desc ibes he calcula ion me hods. Sec ion 5 analyzes he calcula-
ion esul s. Sec ion 6 discusses he implica ions and signi icance o he indings. Finally Sec-
ion 7 encompasses he conclusion and ecommenda ions.
2 Li e a u e Re iew
Ag icul u al g ow h decomposes g ow h in o o al inpu use and o al ac o p oduc i i y (TFP).
In pa icula , TFP has become he p ima y sou ce o ag icul u al g ow h wo ldwide (USDA,
2012). To a la ge ex en , ag icul u al mode niza ion is he p ocess in which TFP's con ibu ion
o ag icul u al economic g ow h is expec ed o con inue ising. Since ag icul u al TFP is o g ea
signi icance o ag icul u al de elopmen , many schola s ha e s udied he ends and ac o s o
ag icul u al TFP om di e en pe spec i es:
(1) S udies a Di e en Spa ial Scales
Some schola s ha e examined ag icul u al TFP a a ious spa ial scales, including global, con-
inen al, and na ional le els. Fo ins ance, Fuglie (2015) conduc ed an analysis o global ag i-
cul u al TFP o he yea s 1961-2012. The esul s sugges ed ha he a e o ag icul u al TFP
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
g ow h had accele a ed in ecen decades. Alhassan (2021) conduc ed a s udy using da a om
38 coun ies in sub-Saha an A ica (SSA) o in es iga e he impac o ag icul u al TFP on en-
i onmen al deg ada ion. The indings e ealed a U-shaped ela ionship be ween ag icul u al
TFP and ca bon dioxide emissions in SSA.
(2) S udies om Pe spec i es o Di e en In luencing Fac o s
Many schola s ha e s udied he e ec s o di e en in luencing ac o s on ag icul u al TFP. Fo
ins ance: Li e al. (2021) in es iga ed he ela ionship be ween China's apid u baniza ion and
ag icul u al TFP. The esul s e ealed a U-shaped ela ionship be ween u baniza ion and ag-
icul u al TFP. Th ough a s udy o ag icul u al TFP in 15 coun ies in Sou h Asia and Sou heas
Asia, Liu e al. (2020) disco e ed ha human capi al had a posi i e in luence on he g ow h o
ag icul u al TFP. Espoi e al. (2021) in hei s udy o ag icul u al TFP in A ica. They highligh ed
ha good go e nance can play a pi o al ole in enhancing ag icul u al p oduc i i y. Yang e al.
(2019) ound u al human capi al posi i ely con ibu es o he local ag icul u al TFP, while ad-
jus men s in c op s uc u e signi ican ly es ain he inc ease in local ag icul u al TFP le els.
In he p ocess o ag icul u al de elopmen , he ex ensi e use o chemical e ilize s and pes i-
cides can lead o en i onmen al pollu ion. Addi ionally, he la ge amoun s o manu e gene a ed
by li es ock and poul y b eeding also con ibu e o en i onmen al deg ada ion. The disc ep-
ancy be ween TFP calcula ions ha do no conside he losses caused by en i onmen al pol-
lu ion and he ac ual TFP can easily lead decision-make s o de elop policies ha a e un a o -
able o g een de elopmen . To p omo e he ha monious de elopmen o ag icul u e and he
en i onmen , schola s ha e inco po a ed en i onmen al pollu ion ac o s in o he analysis o
ag icul u al TFP, esul ing in he concep o AGTFP (Xu e al., 2020).
A ew schola s ha e s udied AGTFP. Yang e al. (2022) disco e ed a signi ican ly posi i e
ela ionship be ween u al human capi al and AGTFP in hei s udy o AGTFP ac oss 28 p o -
inces (ci ies and au onomous egions) in China. Han e al. (2018) iden i ied ha plan ing s uc-
u e has a sligh nega i e e ec on AGTFP in hei analysis. Using panel da a om 30 Chinese
p o inces, Wang and Xie (2022) conduc ed an analysis o he ela ionship be ween human
capi al and AGTFP. The esul s indica ed ha he signi ican imp o emen in he quali y o
human capi al no ably in luences he g ow h o AGTFP in China. Wang and Xiao (2022) ound
ha he massi e popula ion mig a ion om u al o u ban a eas du ing he u baniza ion p ocess
esul s in a con inuous de e io a ion o ag icul u al g een p oduc i i y. Liang and Long (2015)
conduc ed an analysis o he ac o s in luencing he g ow h o AGTFP in 31 p o incial-le el
adminis a i e egions o China. They ound ha he impac o ag icul u al iscal expendi u es
on AGTFP was no pa icula ly signi ican , and he ad ancemen o indus ializa ion hinde ed
he inc ease in AGTFP g ow h a e. Yang e al. (2019) examined he spa ial a ia ion o AGTFP
and i s d i ing ac o s and ound ha he impac o economic de elopmen le el, ag icul u al
s uc u e, and inancial suppo o ag icul u e on AGTFP exhibi ed egional a iabili y.
Some schola s ha e also s udied AGTFP in Shandong p o ince. Fo example, Zhang and Liu
(2015) used he C2R model in DEA o e alua e he ag icul u al p oduc i i y in Shandong p o -
ince. C2R model is a model buil on he p emise o cons an e u n o scale, which is applicable
o he si ua ion whe e he inpu inc ease in a ce ain p opo ion and he ou pu also inc ease in
p opo ion o he inpu . Howe e , ag icul u al p oduc ion did no i his si ua ion. Jiao (2013)
analyzed he ag icul u al p oduc i i y o Shandong p o ince. Jiao (2013) mainly adop ed in-
dus ial pollu an discha ges o ep esen he undesi able ou pu o ag icul u e. Howe e , his
me hod was de icien as indus ial pollu an s o en had no connec ion wi h ag icul u al p oduc-
ion.
In o de o be e unde s and he pa e n and de e minan s o AGTFP in Shandong p o ince,
we employed he Slacks-Based Measu e (SBM)-DEA me hod and o he app oaches o calcu-
la e and analyze AGTFP. This pape conside ed ag icul u al non-poin sou ce pollu an s as he
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
undesi able ou pu and conduc ed s a is ical analysis o AGTFP in Shandong p o ince. We
ea ed he undesi able ou pu as an inpu o make a dynamic compa ison o AGTFP.
3 Index Selec ion and Da a Desc ip ion
3.1 Index Selec ion o AGTFP
DEA is a esea ch me hod o mul i- ac o inpu and ou pu e alua ion. When pe o ming cal-
cula ions, i necessi a es he selec ion o inpu and ou pu a iables. This app oach combines
inpu and ou pu a iable da a om eadily a ailable s a is ical sou ces. Ou pu a iables we e
ag icul u al G oss Domes ic P oduc (GDP) and ag icul u al non-poin sou ce pollu an s in
each ci y. Inpu a iables we e ag icul u al labo popula ion, he o al powe o ag icul u al ma-
chine y, cul i a ed land a ea, i iga ed land a ea and chemical e ilize consump ion.
(1) Ag icul u al GDP: The alue o ag icul u al economic ou pu is exp essed by he added
alue o ag icul u e, o es y, animal husband y and ishe y in uni s o 10,000 Yuan
(CNY). To elimina e he impac o in la ion, he ou pu alues we e con e ed in o con-
s an p ice in 2008 based on he GDP de la o in di e en yea s and di e en local ci ies
and municipali ies.
(2) Pollu an : The calcula ed ag icul u al non-poin sou ce pollu an s we e used, wi h he
uni being on.
(3) Ag icul u al labo popula ion: Ag icul u al labo e e s o he numbe o indi iduals en-
gaged in ag icul u al indus y, he uni was en housand.
(4) The o al powe o ag icul u al machine y: he uni is kilowa . Ag icul u al machine y
e e s o equipmen such as ac o s, ha es e s, and plan e s ha a e used in ag icul-
u al p oduc ion. Hong e al. (2022) u ilized his indica o in hei s udy on he impac o
digi al inclusi e inance and op imiza ion o ag icul u al indus y s uc u e on AGTFP.
(5) Cul i a ed land a ea: Ag icul u al p oduc ion equi ed he occupa ion o land, we chose
cul i a ed land a ea as he inpu , wi h he uni being hec a e.
(6) I iga ed land a ea: Due o he lack o i iga ion wa e da a, he ac ual a ea o i iga ion
land was used ins ead, and he uni was 1,000 hec a es.
(7) Chemical e ilize consump ion: A mass o chemical e ilize was used in ag icul u al
p oduc ion. We used he e ilize a e con e ed o pu e olume, and he uni was on.
3.2 Fac o Selec ion in Panel Reg ession
We selec ed in luencing ac o s in a panel eg ession model by conside ing he in e play
among a ious ac o s a ec ing AGTFP, while also aking in o accoun da a a ailabili y and
ac o s employed in p e ious esea ch s udies.
The independen ac o s in he model include u baniza ion (Fang e al., 2021), ag icul u al in-
dus ial s uc u e (Liu e al., 2021; Liu, 2018), indus ializa ion (Fang e al., 2021), he in luence
o go e nmen on ag icul u e (Liu e al., 2021; Yang e al., 2022), a me s’ cha ac e is ics (Ye
e al., 2023), economic de elopmen le el (Wang and Wang, 2017) and dis ance om po (Li
e al., 2022). The explana ions o each ac o a e as ollows:
(1) U baniza ion a io: In he p ocess o u baniza ion, pa o he u al popula ion was ans-
e ed o ci ies because o educa ion, wo k, medical ca e and o he easons, which led
o se ious aging in u al a eas and he abandonmen o land. This would di ec ly a ec
he ou pu o ag icul u e.
(2) Ag icul u al indus ial s uc u e: I was ep esen ed by he p opo ion o g ain c op a ea
o o al c op sown a ea, which indica ed adjus men o ag icul u al s uc u e. Because
he bene i s p oduced by ood c ops and cash c ops a e di e en , i would ha e an
impac on AGTFP.
4

Peng e al. | Ge J Ag Econ 73 (2024), No. 2
(3) Indus ializa ion: The p opo ion o alue-added by he seconda y sec o o he GDP
in each ci y was u ilized as a measu e o he le el o indus ializa ion. Indus ializa ion
has he po en ial o a ac labo mig a ion om ag icul u e, wi h many young and mid-
dle-aged indi iduals en e ing ac o y employmen , esul ing in a sho age o labo in
u al a eas. This phenomenon can ha e a nega i e impac on ag icul u al TFP. How-
e e , he indus ial sec o can also con ibu e o he imp o emen o ag icul u al TFP
by manu ac u ing ad anced ag icul u al machine y o use in ag icul u al p oduc ion.
(4) The in luence o go e nmen on ag icul u e: We used p opo ion o iscal expendi u e
on ag icul u e, o es y and wa e esou ces o he iscal expendi u e. This ac o e-
lec ed he s a e o go e nmen suppo o ag icul u e. The mo e he go e nmen in-
es ed in ag icul u e, he mo e ag icul u al scien i ic esea ch esul s, and he highe
he ag icul u al echnical e iciency he e would be.
(5) Pe sonal de elopmen o a me s: The e was no di ec ly ela ed da a o his indica o .
We used he p opo ion o a me s' expendi u e on educa ion, cul u e and en e ain-
men in hei annual consume expendi u e.
(6) Economic de elopmen le el: Pe capi a GDP was used ins ead, and he uni was en
housand CNY.
(7) Dis ance om po : Qingdao po has been one o he amous po s in he wo ld. This
pape in ended o measu e he in luence o he po on AGTFP by using he dis ance
be ween each ci y and Qingdao. The dis ance om each ci y o Qingdao was calcu-
la ed based on longi ude and la i ude coo dina es. The dis ance o Qingdao o i sel
was calcula ed by using he a ea o Qingdao, calcula ing he a e age adius and i
ep esen ed he dis ance o Qingdao.
3.3 Da a Desc ip ion
The da a co e s 17 ci ies in Shandong p o ince, wi h a ime span om 2008 o 2018, and each
obse a ion a iable consis s o 187 alues. I is impo an o no e ha in China, he nex le el
o adminis a i e uni s below he p o incial le el is he ci y, which includes bo h u ban and u al
a eas.
The desc ip i e cha ac e is ics o hese da a can be ound in Appendix B. Due o he dis ibu-
ion o hese da a ac oss 17 ci ies and spanning 11 yea s, he e a e signi ican di e ences
be ween he a iables. The main a iables showing an inc easing end include ag icul u al
GDP, pe capi a GDP, i iga ed land a ea, u baniza ion a io, ag icul u al indus ial s uc u e,
he in luence o go e nmen on ag icul u e, and pe sonal de elopmen o a me s. The a ia-
bles showing a dec easing end include ag icul u al labo popula ion, o al powe o ag icul-
u al machine y, cul i a ed land a ea, e ilize usage, pollu an quan i y in ag icul u e, and in-
dus ial s uc u e o he seconda y sec o . The a iable ha emains unchanged is he dis ance
o each ci y om he Qingdao po .
4 Me hods
4.1 Calcula ion o Ag icul u al Pollu an Discha ge
This pape used he uni su ey e alua ion me hod o calcula e he discha ges o ag icul u al
pollu an s. The pollu ion uni was he non-poin sou ce pollu ion uni , which was he smalles
independen uni ha p oduced non-poin sou ce pollu ion. This could be measu ed s a is i-
cally, such as e ilize , c op s aw, li es ock and poul y b eeding. The coe icien s in ol ed in
he calcula ion o pollu an discha ge we e mainly adop ed om Liang (2009) and Lai (2003).
Fo de ailed in o ma ion, please e e o he pape s by Liang and Lai. Calcula ion me hod o
pollu an discha ge was as he ollowing:
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
𝐸=∑𝐸𝑈𝑖𝜌𝑖𝑘(1−𝜂𝑖)
𝑖
(1)
whe e E is he discha ge o ag icul u al non-poin sou ce pollu an s, i.e., CODC , TN, and TP,
i
is pollu ion uni ,
𝐸𝑈𝑖 is he numbe o ag icul u al pollu ion uni
i
,
𝜌𝑖𝑘 is he pollu ion in ensi y
coe icien o pollu an k in ag icul u al pollu ion uni
i
, which is he amoun o pollu an s p o-
duced by a pollu ion uni . The pollu an indexes conside ed in his pape we e he p oduc ion
o TN, TP and CODC (Lai e al., 2004).
i

is coe icien o u iliza ion e iciency o ag icul u al
pollu ion uni
i
. 1-𝜂𝑖 is coe icien o un-o o ag icul u al pollu ion uni i.
Ni ogen e ilize and phospho us e ilize in chemical e ilize s a e impo an sou ces o TN
and TP in ag icul u al non-poin sou ce pollu ion. The calcula ion me hods o hese pollu an s
a e as ollows: The consump ion o e ilize is calcula ed by he usage o ni ogen and phos-
pha e e ilize s a e con e sion o pu e olume. The e ilize a e con e sion o pu e olume
e e s o he amoun o nu ien s o each e ilize summed by he mass pe cen age o N, P2O5
and K2O. Thus, ni ogen e ilize a e con e sion becomes he amoun o TN; phospho us
e ilize a e con e sion is he amoun o P2O5. The e o e, he con en o P in P2O5 is abou
43.66%. The amoun o TP is he p oduc o he phospha e e ilize a e con e sion o pu e
olume and 43.66%. The loss o TN, TP can hen be de i ed by mul iplying he amoun o TN,
TP and hei loss a es espec i ely. The ni ogen loss a e is 20% and he phospho us loss
a e is 7% in Shandong p o ince.
Li es ock and poul y a ming is ano he signi ican sou ce o ag icul u al non-poin sou ce pol-
lu ion. The calcula ion me hods o he pollu an s gene a ed om li es ock and poul y a ming
a e as ollows: The p oduc ion o pollu an s om li es ock and poul y b eeding = he amoun
o li es ock and poul y kep a he end o he yea × he exc e ion coe icien o pollu an s om
li es ock (Table 1) and poul y b eeding sou ces × he exc e ion loss a e. The exc e a loss
a e o li es ock and poul y in Shandong p o ince was 27.6% CODC , 24.4% TN and 21.2%
TP.
Table 1. Annual exc e ion coe icien o pollu an s om li es ock and poul y (kg/uni )
Pollu ion uni i
CODC
TN
TP
ca le
401.500
61.100
10.070
swine
47.880
4.510
1.700
sheep
4.400
2.280
0.450
poul y
1.165
0.275
0.115
Sou ce: coe icien s adop ed om Liang (2009) and Lai (2003)
Solid was e gene a ed om ag icul u al p oduc ion is also an impo an sou ce o ag icul u al
non-poin sou ce pollu ion. The calcula ion me hods o his ype o pollu an a e as ollows:
Fa mland solid was e is mainly c op s aw. The calcula ion o a mland solid was e in ol es
he conside a ion o ac o s such as he c op s aw o g ain a io, pollu ion p oduc ion coe i-
cien , and emission coe icien . Since he e a e a ious ypes o ege ables wi h di e en was e
p opo ions, his s udy assumed an a e age solid was e p opo ion o 0.51 o ege ables. See
Table 2, Table 3, Table 4, and Table 5 o he speci ic coe icien s o calcula ion.
In he con ex o Shandong, aking in o accoun he p opo ion o s aw u iliza ion and nu ien
loss, i was ound ha he loss p opo ions o CODc , TN, and TP we e 11.57%, 10.39%, and
8.61% espec i ely.
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Table 2. Main c op s aw g ain a io
ype
paddy
whea
co n
bean
po a o
Oil c ops
s aw: g ain
0.970
1.030
1.370
1.710
0.610
2.260
Sou ce: coe icien s adop ed om Liang (2009) and Lai (2003)
Table 3. Pollu ion p oduc ion coe icien o di e en c op s aw
uni
pollu ion p oduc ion coe icien (10-3 / )
CODc
TN
TP
paddy
5.630
5.820
0.420
whea
6.390
5.150
0.900
co n
11.230
10.690
2.390
bean
17.610
22.230
2.240
po a o
2.260
1.830
0.670
Oil c ops
ege able
20.570
5.100
45.430
0.920
3.060
0.450
Sou ce: coe icien s adop ed om Liang (2009) and Lai (2003)
Table 4. S aw u iliza ion a io in Shandong (%)
e ilize
odde
uel
aw ma e ial
incine a ion
s ack
o al
23.600
31.000
19.600
6.300
5.800
13.700
100.000
Sou ce: coe icien s adop ed om Liang (2009)
Table 5. S aw u iliza ion and nu ien loss a io (%)
nu ien
e ilize
odde
uel
aw ma e ial
incine a ion
s ack
CODc
20.000
0.000
0.000
0.000
0.000
50.000
N
15.000
0.000
0.000
0.000
0.000
50.000
P2O5
5.000
0.000
0.000
0.000
10.000
50.000
Sou ce: coe icien s adop ed om Liang (2009) and Lai (2003)
4.2 Dimension Reduc ion o Pollu an s
Due o he p esence o h ee pollu an s - CODc , TN and TP, and ha DEA analysis equi es
he decision-making uni o be mo e han wice he sum o inpu a iables and ou pu a iables,
he dimension o pollu an s needed o be educed. He e p incipal componen analysis (PCA)
me hod was used o dimensionali y educ ion. Subsequen ly, he coe icien om he Compo-
nen Sco e Coe icien Ma ix was used as he weigh o calcula e he sum o CODc , TN and
TP, and he sum was aken as he undesi ed ou pu .
A e he h ee pollu an s we e p ocessed by using PCA, he con ibu ion o a iance in da a
by he i s p incipal componen was abo e 95%, so he i s p incipal componen can be used
o eplace he h ee pollu an s.
Wi h his, he o mula was es uc u ed o be:
𝐹𝐴𝐶=𝑎1∗𝑋1+𝑎2∗𝑋2+𝑎3∗𝑋3
(2)
whe e FAC was he pollu an a e dimensionali y educ ion, a1, a2, a3 we e componen sco e
coe icien s and X1, X2 and X3 a e he h ee pollu an s: CODc , TN and TP.
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
4.3 SBM (Slacks-Based Measu e)-DEA App oach
The SBM model is a ype o DEA model. Compa ed o o he DEA models, he SBM model
allows o he measu emen o e iciency changes unde non-expec ed ou pu cons ain s (Tan
and Liu, 2022). The e o e, i can be e e lec he essence o e iciency e alua ion han o he
models (Tu and Liu, 2011).
Tone (2001) p oposed and de eloped an SBM-DEA model. In he SBM-DEA model:
Suppose p oduc ion sys ems ha e n decision making uni s, DEA analysis would be an eco-
nomic sys em o a p ocess (one uni ), which would be conside ed as an en i y. Wi hin a ce ain
possible ex en , i wo ks by pu ing a numbe o ac o s o p oduc ion and ou pu o a ce ain
numbe o "p oduc s”. Such en i ies (uni s) a e called decision-making uni s (DMUs). Each uni
con ains h ee ec o s o inpu : desi able ou pu and undesi able ou pu . They a e deno ed as
m
xR
,
1gs
yR
,
2bs
yR
.
De ine he ma ix o
X
,
g
Y
,
b
Y
whe e
[𝑋]=[𝑥1,⋯,𝑥𝑛]𝑇∈𝑅𝑚×𝑛,
[𝑌𝑔]=[𝑦1𝑔,⋯,𝑦𝑛𝑔]𝑇∈𝑅𝑠1×𝑛,
[𝑌𝑏]=[𝑦1𝑏,⋯,𝑦𝑛𝑏]𝑇∈𝑅𝑠2×𝑛,
X
>0,
g
Y
>0,
b
Y
>0.
De ine he p oduc ion possibili y se 𝑝 as:
𝑝={(𝑥,𝑦𝑔,𝑦𝑏)|𝑥≥𝜆𝑥,𝑦𝑔≤𝜆𝑌𝑔,𝑦𝑏≤𝜆𝑌𝑏,𝜆≥0}
(3)
Then he SBM model based on a iable e u n scale is exp essed by o mula (2):
𝑝∗=𝑚𝑖𝑛 1−1
𝑚∑𝑠𝑖−
𝑥𝑖𝑜
𝑚
𝑖=1
1+ 1
𝑠1+𝑠2[∑𝑠𝑟𝑔
𝑦𝑟0
𝑔+∑𝑠𝑟𝑏
𝑦𝑟0
𝑏
𝑠2
𝑖=1
𝑠1
𝑖=1 ]
(4)
whe e 𝑠 is he slacks o inpu and ou pu , 𝜆 is weigh ec o , objec i e unc ion 𝑝∗ wi h espec
o 𝑠−, 𝑠𝑔, 𝑠𝑏is s ic ly dec easing and 0≤𝑝∗≤1. Fo a pa icula decision uni , i and only i
𝑝∗=1 and 𝑠−, 𝑠𝑔, 𝑠𝑏 a e 0, he comp ehensi e e iciency is e ec i e. When 𝑝∗<1 o 𝑠−, 𝑠𝑔,
𝑠𝑏a e no comple e ze oes, i indica es ha he decision uni is ine icien , and he echnical e i-
ciency o scale e iciency is also in alid, so he e is a need o imp o e he inpu and ou pu .
4.4 Malmquis Me hod
The SBM-DEA model is able o pe o m s a is ical analysis on c oss-sec ional da a, bu i does
no measu e he empo al end o AGTFP, and hence canno make a dynamic compa ison.
The Malmquis index can be used o sol e his p oblem by combining c oss-sec ional da a
analysis wi h ime se ies da a analysis.
I can decompose his p oduc i i y change in o echnical change and echnical e iciency
change (Sa hye, 2002).
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
The Malmquis index can be decomposed in o e ch and echch. I can be seen om Table 8
ha he changes in AGTFP we e mainly caused by echch, indica ing ha ag icul u al echno-
logical p og ess led o he imp o emen o AGTFP. Ag icul u al echnological p og ess includes
measu es such as imp o ing ag icul u al machine y le els, using high-quali y seeds, and im-
plemen ing o he echnological ad ancemen s in ag icul u al p ac ices. This esul was con-
sis en wi h he esea ch conclusion in Sheng e al. (2020) ha “I is widely belie ed ha ech-
nological p og ess had played an essen ial ole in con ibu ing o he apid p oduc i i y g ow h
in China’s ag icul u al sec o ”.
e ch ep esen s he combined e iciency o ag icul u al managemen le el and inpu ac o s.
Jinan, Zibo, Yan ai and o he 7 egions had been imp o ed, bu he emaining 10 egions we e
no e icien . This was in line wi h he cu en si ua ion o low o e all ag icul u al e iciency,
ex ensi e ag icul u al managemen and la ge numbe s o a me s unwilling o engage in ag i-
cul u al p oduc ion.
Table 8. Decomposi ion o AGTFP o ci ies
ci y
e ch
echch
ag p
Jinan
1.000
1.055
1.055
Qingdao
0.991
1.050
1.041
Zibo
1.015
1.048
1.064
Zaozhuang
0.988
1.044
1.031
Dongying
0.990
1.061
1.050
Yan ai
1.000
1.053
1.053
Wei ang
0.998
1.059
1.056
Jining
1.000
1.043
1.043
Taian
0.995
1.043
1.038
Weihai
1.000
1.046
1.046
Rizhao
1.008
1.039
1.048
Laiwu
0.993
1.045
1.038
Linyi
0.999
1.041
1.039
Dezhou
0.995
1.050
1.045
Liaocheng
0.999
1.046
1.045
Binzhou
1.010
1.058
1.069
Heze
0.988
1.056
1.043
Sou ce: da a de i ed om he decomposi ion o he Malmquis index
5.3.2 Compa ison Analysis o AGTFPT T ends Ac oss Ci ies
Table 9 shows he AGTFP da a o all egions in Shandong p o ince om 2009 o 2018. Table
6 p esen s AGTFP calcula ed using he SBM me hod, which allows o he analysis o AGTFP
ac oss di e en ci ies in he same yea . On he o he hand, Table 9 displays AGTFP calcula ed
using he Malmquis Index me hod, p o iding a con enien means o analyze he empo al
ends o AGTFP wi hin he same egion.
In ligh o he empo al shi s, i is e iden ha he AGTFP in e e y ci y had been expe iencing
a consis en and p og essi e inc ease. In e ms o he change cha ac e is ics o AGTFP, h ee
dis inc ypes can be disce ned: (1) Jinan, Zibo, Wei an, Jining, Rizhao, Liaocheng, Binzhou,
and Heze we e keeping ela i ely high g ow h a es，AGTFP we e g ea e han 1 annually. (2)
In Zaozhuang, Laiwu and Linyi, AGTFP g adually de eloped om low e iciency o high e i-
ciency, and changed om less han 1 o highe han 1. (3) The emaining 6 ci ies we e expe i-
encing luc ua ing g ow h. Al hough he e iciency was less han 1 in some yea s, he o e all
e iciency was also cons an ly imp o ing.
15

Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Table 9. The end o AGTFP in 17 ci ies o Shandong p o ince
Ci y
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Jinan
1.028
1.026
1.026
1.038
1.006
1.028
1.035
1.191
1.103
1.084
Qingdao
1.014
0.996
1.036
1.027
1.032
1.041
1.034
1.140
1.036
1.061
Zibo
1.017
1.033
1.028
1.024
1.028
1.029
1.044
1.319
1.083
1.064
Zaozhuang
0.972
0.996
0.997
1.017
1.016
1.016
1.024
1.174
1.068
1.044
Dongying
1.021
1.021
1.018
1.015
0.968
1.015
0.972
1.225
1.151
1.127
Yan ai
1.021
1.024
0.997
1.038
1.025
1.035
1.041
1.211
1.023
1.135
Wei ang
1.007
1.012
1.014
1.045
1.027
1.040
1.050
1.204
1.073
1.108
Jining
1.021
1.013
1.022
1.038
1.027
1.043
1.044
1.104
1.067
1.053
Taian
0.999
1.011
0.997
1.015
1.012
1.008
1.015
1.143
1.141
1.050
Weihai
1.030
1.019
1.006
1.029
0.985
1.033
1.075
1.032
1.033
1.236
Rizhao
1.019
1.039
1.013
1.026
1.048
1.043
1.165
1.056
1.061
1.016
Laiwu
0.992
0.989
1.008
1.045
1.017
1.019
1.012
1.251
1.033
1.034
Linyi
0.999
0.985
1.008
1.022
1.006
1.020
1.034
1.339
1.004
1.019
Dezhou
1.038
1.029
1.023
1.050
1.010
1.038
1.051
0.864
1.243
1.143
Liaocheng
1.040
1.035
1.038
1.047
1.010
1.042
1.051
1.062
1.049
1.077
Binzhou
1.019
1.017
1.032
1.033
1.023
1.007
1.038
1.348
1.037
1.176
Heze
1.020
1.030
1.028
1.028
1.030
1.025
1.037
1.158
1.032
1.050
Sou ce: AGTFP calcula ed using he Malmquis Index me hod
5.4 Analysis o Cen e o G a i y Shi in AGTFP Wi hin Shandong
P o ince
The la i ude and longi ude coo dina es o each ci y in Shandong we e ob ained om he web-
si e (Jingweidu, 2020).
iM
was he AGTFP calcula ed by using Malmquis me hod. The CoG
model was used o calcula e he CoG o AGTFP in Shandong p o ince om 2009 o 2018,
which could e lec he spa ial changes in he ajec o y o he CoG o AGTFP in Shandong and
could e eal hei spa ial pa e n.
The CoG is plo ed in Figu e 6. I can be seen om he igu e ha he cen e o g a i y was
118.16°E and 36.38°N in 2009, and 118.20°E and 36.41°N in 2018. When compa ed wi h he
geome ic cen e o Shandong p o ince (118.14°E,36.33°N) (Li, 2019), he cen e s we e bo h
on he eas and no h. This indica es ha he AGTFP in eas e n Shandong was highe han
ha in wes e n ci ies, and he AGTFP in no he n ci ies was highe han ha in sou he n ci ies.
In addi ion, he CoG gene ally had a endency o shi eas wa d and no hwa d, indica ing ha
egional di e ences we e inc easing.
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Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Figu e 6. T ajec o y o cen e o g a i y o AGTFP in Shandong (ho izon al axis ep esen s
longi ude coo dina es and e ical axis ep esen s la i ude coo dina es)
Sou ce: da a de i ed om calcula ions by he COG model
5.5 E olu ion Cha ac e is ics o Regional Di e ence
As can be seen om Figu e 7, he CV o AGTFP in 2009 was 0.017. CV alues had inc eased
apidly a e 2014, and eached he maximum in 2016, wi h a alue o 0.122. In 2017 and 2018,
he CV alues o AGTFP we e educed o 0.059 and 0.060. I can be seen om he igu e ha
al hough Shandong’s AGTFP luc ua ed, he o e all end was g adually inc easing. This co -
esponded wi h he ajec o y o Shandong AGTFP, indica ing ha he AGTFP g ow h a e
di e ence in Shandong was inc easing, and he inc ease o AGTFP in he eas e n and no he n
egions was ela i ely la ge.
Figu e 7. Coe icien o Va ia ion o AGTFP in Shandong p o ince
Sou ce: da a de i ed om calcula ions by he CV model
5.6 Analysis o he Fac o s A ec ing AGTFP
Besides ag icul u al echnology and ag icul u al managemen le el, AGTFP was also a ec ed
by u baniza ion le el, pe sonal de elopmen o a me s, ag icul u al s uc u e and o he ac o s.
In o de o iden i y he ac o s a ec ing Shandong’s AGTFP, his pape used panel da a wi h a
eg ession analysis o he ac o s ha may a ec AGTFP.
17
Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Figu e 1, Figu e 2 and Figu e 3 indica e ha AGTFP seemed o ha e spa ial co ela ion. By
employing he global Mo an's I and local Mo an's I analysis me hods (Zhang e al., 2020a;
Zhang e al., 2020b), we obse ed ha only in 2018 he e was a ce ain deg ee o spa ial
au oco ela ion. No signi ican spa ial au oco ela ion coe icien s in he es o he yea s.
The e o e, ou eg ession analysis did no conside he spa ial cha ac e is ics o ha spa ial
dis ibu ion.
The meanings o each a iable can be ound in Table 10. The magni ude o he eg ession
coe icien s in Table 11 indica es he ex en o he independen a iables’ impac on he de-
penden a iable and does no imply causali y. Co ela ion analysis and collinea i y diagnos ics
we e conduc ed among he independen a iables, and no co ela ions exceeding 0.5 we e
iden i ied. Fu he mo e, he e was no e idence o mul icollinea i y among he independen a -
iables. Hausman es s o bo h ixed e ec s and andom e ec s we e pe o med on he da a,
p=0.0003, he p alue was less han 0.5 meaning ixed e ec s was p e e ed. I can be seen
om Table 11 ha he p alues o u ban, ags , PGDP and ina we e all g ea e han 0.1 which
ailed he signi icance es , indica ing ha hese ac o s had no signi ican impac on AGTFP.
dis was igno ed di ec ly and did no pa icipa e in calcula ion, indica ing ha dis ance o he
po had no in luence on Shandong AGTFP. The p alue o ind was 0.000, indica ing ha he
indus ializa ion had a signi ican nega i e e ec on AGTFP. This sugges s a s ong co ela ion
be ween he wo a iables. The p alue o pd was 0.078, indica ing ha pe sonal de elopmen
o a me s had a ce ain posi i e e ec on AGTFP, indica ing he e is a ce ain le el o co e-
la ion be ween he wo a iables. This is consis en wi h he conclusion in Zuo (2019) ha
“ag icul u al human capi al and ag icul u al o al ac o p oduc i i y a e signi ican ly posi i ely
co ela ed”.
Table 10. Desc ip ion o he a iables in eg ession analysis
Va iable
Va iable Desc ip ion
ag p
Ag icul u al G een To al Fac o P oduc i i y
u ban
U baniza ion le el
ind
Indus ializa ion
ags
Ag icul u al ope a ion s uc u e
PGDP
Pe capi a GDP
ina
P opo ion o iscal expendi u e on ag icul u e, o es y and wa e esou ces o he
iscal expendi u e
pd
The p opo ion o a me s' expendi u e on educa ion, cul u e and en e ainmen in
hei annual consump ion expendi u e
dis
The dis ance om Qingdao
cons
Cons an e m o he eg ession equa ion
Sou ce: his able was compiled based on he a iables used in he eg ession analysis o he s udy.
Table 11. Reg ession esul s o he ac o s a ec ing AGTFP
ag p
Coe .
S d.E .
P >
[95% con .
In e al]
u ban
ind
ags
PGDP
ina
pd
dis
cons
-0.086
-1.170
0.048
0.092
-0.022
0.571
0. 000
1.590
0.090
0.246
0.114
0.224
0.338
0.322
(omi ed)
0.220
0.950
4.760
0.420
0.410
0.060
1.770
7.220
0.341
0.000
0.674
0.681
0.949
0.078
0.000
-0.235
-1.578
-0.140
-0.279
-0.582
0.038
1.225
0.063
-0.763
0.236
0.463
0.539
1.105
1.954
F = 2.18 p ob > F = 0.0079
Sou ce: da a ob ained om he calcula ions using apanel eg ession model
18
Peng e al. | Ge J Ag Econ 73 (2024), No. 2
6 Discussion
This pape p esen s an analysis o AGTFP in Shandong P o ince, quan i ying pollu an s om
e ilize s, li es ock, and c op was e in ag icul u al non-poin sou ce pollu ion. Impo an ac o s
we e also de e mined by eg ession analyses. Ou esul s indica e:
(1) Based on he AGTFP da a, app oxima ely hal o he ci ies had an AGTFP alue equal
o 1 each yea , indica ing high e iciency. The emaining ci ies we e mos ly in a s a e o
mode a e e iciency o ine iciency. The e o e, he e was s ill signi ican oom o im-
p o emen in AGTFP in some a eas o Shandong p o ince e e y yea . In e ms o e-
gional dis ibu ion, he mo e e icien ci ies a e mos ly loca ed in coas al a eas and he
cen al egion.
(2) F om he pe spec i e o dynamic analysis, Shandong p o ince's AGTFP has been con-
s an ly imp o ing. The ci ies wi h apid g ow h include Binzhou, Zibo, Jinan, and Wei-
hai, while he ci ies wi h slowe g ow h include Zaozhuang, Laiwu, and Taian. The e
we e signi ican egional di e ences in AGTFP g ow h. F om he da a in Table 8 i can
be obse ed ha he alue o echch is gene ally g ea e han 1, while e ch a ies, wi h
some alues g ea e han 1 and some alues less han 1. This indica es ha he p o-
g ess o ag icul u al echnology le el is he main d i e o AGTFP imp o emen , a con-
clusion consis en wi h p e ious esea ch by Kuma e al., 2008； and Sheng e al.,
2020. On he o he hand, he ag icul u al managemen le el s ill needs o be enhanced.
This esul eminds us o pay a en ion o ag icul u al managemen by adop ing ad-
anced in o ma ion echnology, accele a ing land ans e , and implemen ing o he
measu es o u he enhance AGTFP.
(3) In e ms o spa ial dispa i y, he di e ence in AGTFP g ow h a es among ci ies had
been inc easing yea by yea . Based on he annual Malmquis index alues, he 17
ci ies in Shandong p o ince can be classi ied in o h ee ypes: (1) Con inuous g ow h,
wi h an index g ea e han 1 e e y yea , consis ing o 8 ci ies; (2) G adual g ow h, wi h
an index ansi ioning om less han 1 o g ea e han 1, consis ing o 3 ci ies; (3) Fluc-
ua ing g ow h, wi h an index mos ly g ea e han 1 bu occasionally less han 1, con-
sis ing o 6 ci ies. The esul s o he CoG model indica e ha as e g ow h mainly oc-
cu ed in he eas e n and no he n egions. This phenomenon leads us o pay a en ion
o he de elopmen speed o AGTFP in he wes e n and sou he n egions in o de o
achie e a mo e balanced AGTFP dis ibu ion.
(4) Ou esea ch esul s indica e ha he le el o u baniza ion has no signi ican impac on
AGTFP in Shandong p o ince. This inding di e s om he conclusion d awn by Li e
al. (2021), who sugges ed a U-shaped ela ionship be ween u baniza ion and ag icul-
u al TFP in China. The disc epancy in esea ch indings may be a ibu ed o a ia ions
in he geog aphical scope o he s udies. China encompasses o e 30 p o incial-le el
adminis a i e egions wi h a ying le els o de elopmen , which can lead o di e gen
conclusions due o di e ences in s a is ical da a. In he case o Shandong p o ince, he
ag icul u al indus ial s uc u e was ound o ha e an insigni ican e ec on AGTFP.
This inding con as s wi h p e ious esea ch by Han e al. (2018) and Yang e al.
(2019), who sugges ed ha adjus men s in ag icul u al indus y s uc u e ha e a nega-
i e impac on ag icul u al TFP. The eason o his di e ence is ha he s a is ical da a
o Shandong p o ince showed ha he a ia ion in g ain c op sowing a ea was no
signi ican du ing he s udy pe iod, leading o he conclusion ha he ag icul u al indus-
y s uc u e index had an insigni ican impac on AGTFP. Simila ly, inancial suppo
o ag icul u e in Shandong p o ince was ound o ha e an insigni ican e ec on AG-
TFP, which aligns wi h he conclusions o Liang and Xi (2022) and Liang and Long
(2015) ega ding he ela ionship be ween inancial suppo o ag icul u e and ag icul-
u al TFP. This sugges s ha inc easing inancial suppo o ag icul u e may no be
conduci e o imp o ing AGTFP (Wang e al., 2022).
Howe e , he indus ializa ion o ci ies and he pe sonal de elopmen o a me s we e ound o
ha e a signi ican impac on AGTFP. The indus ializa ion o ci ies was obse ed o ha e a
19
Peng e al. | Ge J Ag Econ 73 (2024), No. 2
nega i e e ec on AGTFP. This is a ibu ed o he mig a ion o a subs an ial numbe o young
and middle-aged u al labo e s om ag icul u e o he seconda y and e ia y sec o s as indus-
ializa ion p og esses, esul ing in a sho age o labo in u al a eas (Xu e al., 2022). Hence,
his exodus o u al labo nega i ely impac s u al TFP. This conclusion aligns wi h he indings
o Liang and Xi (2022) on AGTFP in Shandong P o ince, whe e hey sugges ed ha indus ial
de elopmen can c ea e a ce ain siphoning e ec on ag icul u al p oduc ion ac o s, which is
de imen al o he imp o emen o AGTFP. The conclusion ha he pe sonal de elopmen o
a me s has a signi ican impac on AGTFP aligns wi h he indings o Paudel e al. (2004), who
demons a ed a signi ican ela ionship be ween ag icul u al p oduc i i y and he quali y o hu-
man capi al ac oss di e en s a es in he Uni ed S a es. Addi ionally, i co esponds o he e-
sul s o Yang e al. (2022) in hei s udy on he ela ionship be ween ag icul u al p oduc i i y
and u al human capi al in China. This sugges s ha imp o ing he educa ion le el o a me s
can con ibu e o he enhancemen o AGTFP (Reime s and Klasen, 2013).
The a o emen ioned esea ch esul s unde sco e he egional a ia ion in he ac o s in luenc-
ing AGTFP. This aligns wi h he indings o Zhao e al. (2022) and Yang e al. (2019). To im-
p o e AGTFP in a speci ic egion, i is impe a i e o conduc a ho ough analysis o he local
con ex and a oid adop ing p ac ices om o he egions indisc imina ely. The panel da a e-
g ession esul s highligh he signi icance o mi iga ing he nega i e impac o indus ializa ion
and enhancing he quali y o he labo o ce as c ucial ac o s in luencing AGTFP.
7 Conclusion and Sugges ions
7.1 Conclusion
In o de o p omo e he sus ainable de elopmen o ag icul u e, his pape s udied he AGTFP
o Shandong p o ince. Th ough his s udy, we ha e disco e ed ha he calcula ion o AGTFP
wi h he inclusion o undesi able ou pu s yields lowe esul s compa ed o calcula ions wi hou
conside ing undesi able ou pu s. We ha e ound egional dispa i ies in AGTFP wi hin Shan-
dong p o ince, wi h app oxima ely hal o he egions consis en ly ope a ing a medium o low
e iciency le els each yea . O e he s udy pe iod, Shandong's AGTFP displayed an unin e -
up ed upwa d ajec o y.
The decomposi ion esul s o he Malmquis index indica e ha he egional dispa i ies in AG-
TFP wi hin Shandong p o ince we e p ima ily in luenced by he e iciency change componen
(e ch), highligh ing he need o imp o e managemen p ac ices in he ag icul u al de elopmen
p ocess. By u ilizing AGTFP g a i y calcula ions, we obse ed spa ial a ia ions in AGTFP
e iciency, wi h he AGTFP g a i y cen e shi ing owa ds he eas and no h.
In ou panel eg ession analysis, we ound ha indus ializa ion and he pe sonal de elopmen
o a me s ha e a signi ican impac on AGTFP. The e o e, he e a e oppo uni ies o mi iga e
u al labo ou mig a ion by enhancing u al public se ices, he eby imp o ing he li ing condi-
ions o a me s h ough be e heal hca e, educa ion, anspo a ion, and o he essen ial
ameni ies. Addi ionally, he de elopmen o he ag o-p ocessing indus y and he implemen a-
ion o u al ou ism ini ia i es can help in his ega d. Enhancing he pe sonal de elopmen o
a me s h ough echnical aining and educa ional p og ams can also con ibu e o imp o ing
AGTFP.
The indings o his esea ch can p o ide aluable insigh s o he ag icul u al g een de elop-
men in Shandong and China as a whole.
Due o limi a ions in da a a ailabili y, ou analysis o ac o s in luencing AGTFP may no be
exhaus i e. In he u u e, we will con inue o collec da a and del e deepe in o he explo a ion
o ac o s a ec ing AGTFP, p o iding mo e in o med ecommenda ions o i s imp o emen .
20

Peng e al. | Ge J Ag Econ 73 (2024), No. 2
7.2 Sugges ions
In o de o imp o e Shandong AGTFP and p omo e egional sus ainable de elopmen and o
balance he p o ince-wide de elopmen , his pape p oposes:
(1) Imp o e ag icul u al managemen and e iciency and educe ex ensi e managemen .
Reducing ac o inpu s, especially e ilize s and pes icides, can no only imp o e e i-
ciency, bu also educe pollu ion. Ad anced echnology should be adop ed o a mland
i iga ion o educe was e.
(2) Focus on indus ial s uc u e ans o ma ion, imp o e he e iciency o he p ima y in-
dus y and educe pollu ion, and emphasize on de eloping p ojec s wi h low pollu ion
emissions and high e iciency, such as ag icul u al sigh seeing ou ism and ecological
ag icul u e.
(3) Imp o e he pe sonal de elopmen o a me s. By imp o ing he le el o ag icul u al
echnology and managemen h ough he enhancemen o a me s' pe sonal de elop-
men , he o e all e iciency and p oduc i i y o ag icul u al ope a ions can be signi i-
can ly enhanced, ul ima ely leading o imp o ed AGTFP.
Acknowledgemen s
Thanks o he pee e iewe s and jou nal s a o hei aluable sugges ions and diligence
wo k in imp o ing he pape o publica ion.
Re e ences
Alhassan, H. (2021): The e ec o ag icul u al o al ac o p oduc i i y on en i onmen al deg a-
da ion in sub-Saha an A ica. Scien i ic A ican 12: e00740.
h ps://doi.o g/10.1016/j.scia .2021.e00740.
Bai, Z. (2008): Econome ic Analysis o Panel Da a. Nankai Uni e si y P ess, Tianjin.
Ca es D.W., Ch is ensen, L.R., Diewe , W.E. (1982): The economic heo y o index numbe s
and he measu emen o inpu , ou pu , and p oduc i i y. Econome ica 50 (6): 1393-1414.
h ps://doi.o g/10.2307/1913388.
Chinai n (2020): China is a majo p oduce and consume o ag icul u al and sideline p oduc s,
wha is he cu en si ua ion o he ag icul u al p oduc p ocessing indus y?.
h ps://www.chinai n.com/hyzx/20201224/143356816.sh ml.
Cn (2014): China's excess capaci y in chemical e ilize s needs o be add essed. h p://coun-
y.cn .cn/ jxw/201402/ 20140207_514794889.sh ml.
Espoi , D.K., Banno , F., Sunge, R. (2021): In a-A ica ag icul u al ade, go e nance quali y
and ag icul u al o al ac o p oduc i i y: E idence om a panel ec o au o eg essi e
model. ZBW- Leibniz In o ma ion Cen e o Economics, Kiel, Hambu g. h ps://hdl.han-
dle.ne /10419/235617.
Fang, L., Hu, R., Mao, H. Chen, S.J. (2021): How c op insu ance in luences ag icul u al g een
o al ac o p oduc i i y: E idence om Chinese a me s. Jou nal o Cleane P oduc ion, ol.
321: 128977. h ps://doi.o g/10.1016/j.jclep o.2021.128977.
Fuglie, K. (2015): Accoun ing o g ow h in global ag icul u e. Bio-based and applied econom-
ics 4 (3): 201-234. h ps://doi.o g/10.13128/BAE-17151.
Gao, T.M., Wang, J.M., Chen, F., Liu, Y.H. (2016): Econome ic Analysis Me hods and Mod-
eling: EViews Applica ions and Examples. Tsinghua Uni e si y P ess, Beijing.
h p://www. up. singhua.edu.cn/booksCen e /book_06018001.h ml.
21
Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Han, H., Zhong, Z., Wen, C., Sun, H. (2018): Ag icul u al en i onmen al o al ac o p oduc i i y
in China unde echnological he e ogenei y: cha ac e is ics and de e minan s. En i onmen-
al Science and Pollu ion Resea ch 25: 32096-32111. h ps://doi.o g/10.1007/s11356-018-
3142-4.
Hong, M.Y., Tian, M.J., Wang, J. (2022): Digi al Inclusi e Finance, ag icul u al indus ial s uc-
u e op imiza ion and ag icul u al g een o al ac o p oduc i i y. Sus ainabili y 14 (18):
11450. h ps://doi.o g/10.3390/su141811450
Hsiao, C. (2007): Panel da a analysis-ad an ages and challenges. Tes 16 (1):1-22.
h ps://doi.o g/10.1007/s11749-007-0046-x.
Huang, Y.L., Zhang, L., Zhu, C.X. (2012): Analysis o ag icul u al non-poin sou ce pollu ion in
nansi lake basin, Shandong P o ince. En i onmen al Science Resea ch 25 (11): 1243-
1249. h ps://doi.o g/10.13198/j. es.2012.11.57.huangyl.001.
Jiao, Y. (2013): E alua ion o ag icul u al p oduc ion e iciency in Shandong p o ince. China
Popula ion·Resou ces and En i onmen 23 (12):105-110.
h ps://doi.o g/10.3969/j.issn.1002－2104.2013.12.016.
Jingweidu (2020): Longi ude and La i ude Que y. h ps://jingweidu.51240.com/.
Lai, S.Y. (2003): Non-poin sou ce su ey and e alua ion me hod and i s applica ion esea ch.
Tsinghua Uni e si y, Beijing.
Lai, S.Y., Du, P.F., Chen, J.N. (2004): Non-poin sou ce pollu ion in es iga ion and e alua ion
me hod based on uni analysis. Jou nal o Tsinghua Uni e si y (Na u al Science Edi ion) 44
(9): 1184-1187. h ps://doi.o g/10.16511/j.cnki.qhdxxb.2004.09.009.
Li, J., Chen, J., Liu, H. (2021): Sus ainable ag icul u al o al ac o p oduc i i y and i s spa ial
ela ionship wi h u baniza ion in China. Sus ainabili y 13 (12): 6773.
h ps://doi.o g/10.3390/su13126773.
Li, M. (2019): Resea ch on he shi o he cen e o g a i y and spa ial coo dina ion o “popu-
la ion-economy-land” in Shandong ci ies. Shandong No mal Uni e si y, Jinan.
Li, Z.D., Yuchi, X.J. (2019): Resea ch on ag icul u al p oduc ion e iciency in Shandong p o -
ince. Jou nal o Shandong Ag icul u al Uni e si y (Social Science Edi ion), 21(02): 45-51.
Li, Y., Chen, C., Liu, F., Wang, J. (2022): Analysis me hod o ag icul u al o al ac o p oduc i i y
based on s ochas ic block model (SBM) and machine lea ning. Jou nal o Food Quali y, ol.
2022. h ps://doi.o g/10.1155/2022/9297205.
Liang, J., Long, S.B. (2015): G een ag icul u al o al ac o p oduc i i y g ow h and i s in luenc-
ing ac o s. Jou nal o Sou h China Ag icul u al Uni e si y (Social Science Edi ion) 14 (3):
1-12. h ps://doi.o g/10.7671/j.issn.1672-0202. 2015.03.001.
Liang, J.R., Xi, X.R. (2022): Measu emen o Ag icul u al G een To al Fac o P oduc i i y and
Analysis o In luencing Fac o s in Shandong P o ince. Ru al Economy and Technology 33
(5): 1-5+15.
Liang, L.T. (2009): Resea ch on he spa io- empo al cha ac e is ics and e olu ion o u al eco-
logical en i onmen . Nanjing Ag icul u al Uni e si y, Nanjing.
Liu, D.D., Zhu, X.Y., Wang, Y.F. (2021): China's ag icul u al g een o al ac o p oduc i i y
based on ca bon emission: An analysis o e olu ion end and in luencing ac o s. Jou nal
o Cleane P oduc ion 278 123692: 1-12. h ps://doi.o g/10.1016/j.jclep o.2020.123692.
Liu, F., Zhang, H.L. (2018): Analysis o Ag icul u al To al Fac o P oduc i i y and In luencing
Fac o s unde Ca bon Emission Cons ain s in Shandong P o ince. Jiangsu Ag icul u al
Science 46 (24): 387-390. h ps://doi.o g/10.15889/j.issn.1002-1302.2018.24.099.
Liu, J.X., Wang, M.J., Yang, L., Rahman, S., S iboonchi a, S. (2020): Ag icul u al p oduc i i y
g ow h and i s de e minan s in sou h and sou heas Asian coun ies. Sus ainabili y 12 (12):
4981. h ps://doi.o g/10.3390/su12124981.
Liu, Z.W. (2018): Analysis on he dynamic e olu ion and in luencing ac o s o ag icul u al o al
ac o p oduc i i y in china. Chinese Jou nal o Ag icul u al Resou ces and Regional Plan-
ning 39 (12): 104-111. h ps://doi.o g/10.7621/cja p.1005-9121.20181215.
22
Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Kuma , P., Mi al, S., Hossain, M. (2008): Ag icul u al G ow h Accoun ing and To al Fac o
P oduc i i y in Sou h Asia: A Re iew and Policy Implica ions. Ag icul u al Economics Re-
sea ch Re iew 21: 145-172.
Ma, J.Z., Ding, Z.Y., Wei, G.X., Zhao, H., Huang, T.M. (2009): Sou ces o wa e pollu ion and
e olu ion o wa e quali y in he Wuwei basin o Shiyang Ri e ，No hwes China. Jou nal
o En i onmen al Managemen 90 (2): 1168-1177. h ps://doi.o g/10.1016/j.jen-
man.2008.05.007.
Na ional Bu eau o S a is ics o he People's Republic o China (2020): China S a is ical Yea -
book, 2009-2019. h p://www.s a s.go .cn/.
Paudel, K.P., Sambidi, P.R., Sulgham, A.K. (2004): A Theo e ical De elopmen and Empi ical
Tes on he Con e gence o Ag icul u al P oduc i i y in he USA. Con e ence Pape .
P esen a ion a AAEA a 2004 annual mee ing. h ps://doi.o g/10.22004/ag.econ.20175.
Rml (2019): The economic achie emen s o he 40 yea s o e o m and opening up and he
"business ca d o China". h p://www. ml .com.cn/2019/0520/547309.sh ml.
Reime s, M., Klasen, S. (2013): Re isi ing he ole o educa ion o ag icul u al p oduc i i y.
Ame ican Jou nal o Ag icul u al Economic 95 (1): 131-152.
h ps://doi.o g/10.1093/ajae/aas118.
Sannong (2014): Looking o wa d o sol ing he o e capaci y o e ilize p oduc ion. h p://san-
nong.cn .cn/20140207/101694.sh ml.
Sa hye, M. (2002): Measu ing p oduc i i y changes in Aus alian banking: an applica ion o
Malmquis indices. Manage ial Finance 28 (9): 48-59.
h ps://doi.o g/10.1108/03074350210768068.
Shandong P o incial Bu eau o S a is ics (2020): Shandong S a is ical Yea book (2009-2019).
h p:// jj.shandong.go .cn/col/col6279/index.h ml.
Sheng, Y., Tian, X., Qiao, W., Peng, C. (2020): Measu ing ag icul u al o al ac o p oduc i i y
in China: pa e n and d i e s o e he pe iod o 1978-2016. Aus alian Jou nal o Ag icul u al
and Resou ce Economics 64 (1):82-103. h ps://doi.o g/10.1111/1467-8489.12327.
Sheng, Y., Ball, V.E., E ickson, K., Mesonada, C.S.J. (2022): C oss-coun y ag icul u al TFP
con e gence and capi al deepening: E idence o induced inno a ion om 17 OECD coun-
ies. Jou nal o P oduc i i y Analysis 58 (2-3): 185-202. h ps://doi.o g/10.1007/s11123-
022-00646-z.
Song, T.S., Zhang, Z.T., Hao, T. (2012): A s udy on ag icul u al p oduc ion's e iciency du ing
he 11 h Fi e-yea Plan pe iod in Shandong P o ince on basis o DEA me hod. Jou nal o
Qilu No mal Uni e si y 27 (3): 25-31.
Tan, R.H., Liu, H.M. (2022): Cha ac e is ic e olu ion and in luencing ac o s o he spa ial co -
ela ion ne wo k o ag icul u al g een o al ac o p oduc i i y in China. Chinese Jou nal o
Eco-Ag icul u e 30 (12): 2011-2026. h ps://doi.o g/10.12357/cjea.20220339.
Tellie , L.N., Ve e euille, C. (1995): Unde s anding spa ial ine ia: cen e o g a i y, popula ion
densi ies, he Webe p oblem, and g a i y po en ial. Jou nal o Regional Science 35 (1):
155-164. h ps://doi.o g/10.1111/j.1467-9787.1995. b01404.x.
Tone, K. (2001): A slacks-based measu e o e iciency in da a en elopmen analysis. Eu o-
pean Jou nal o Ope a ional Resea ch 130 (3): 498-509. h ps://doi.o g/10.1016/S0377-
2217(99)00407-5.
Tu, Z.G., Liu, L.K. (2011): E alua ion o China’s indus ial e iciency conside ing ene gy and
en i onmen al ac o . Economic Re iew (2): 55-65.
h ps://doi.o g/10.19361/j.e .2011.02.007.
USDA (2012): To al ac o p oduc i i y has become he p ima y sou ce o g ow h in wo ld ag-
icul u e. h ps://www.e s.usda.go /da ap oduc s/cha -galle y/galle y/cha -de-
ail/?cha Id=76219.
Wang, L., Tang, J.Y., Tang, M.Q., Su, M.Y., Guo, L.L. (2022): Scale o ope a ion, inancial
suppo , and ag icul u al g een o al ac o p oduc i i y: E idence om China. In e na ional
23
Peng e al. | Ge J Ag Econ 73 (2024), No. 2
Jou nal o En i onmen al Resea ch and Public Heal h 19 (15): 9043.
h ps://doi.o g/10.3390/ije ph19159043.
Wang, S., Wang, X. (2017): Does se ice inwa d o eign di ec in es men imp o e g een o al
ac o p oduc i i y: An empi ical s udy based on china’s p o incial panel da a. Jou nal o
In e na ional T ade issue 12: 83-93. h ps://doi.o g/10.13510/j.cnki.ji .2017.12.008.
Wang, Y.R., Xie L.Y. (2022): Resea ch on he Impac o Human Capi al on Ag icul u al G een
To al Fac o P oduc i i y: An Analysis o he Impac Pa h Based on Media ion E ec . Jou nal
o Shandong Ag icul u al Uni e si y (Social Science Edi ion) 24 (3): 1-7.
h ps://mall.cnki.ne /magazine/a icle/SDND202203001.h m.
Wang Y.F., Xiao, Y. (2022): New U baniza ion, Ag icul u al Indus y Agglome a ion, and Ag i-
cul u al G een To al Fac o P oduc i i y G ow h: Impac Mechanism and Empi ical Tes ing.
Jou nal o Chongqing No mal Uni e si y (Social Sciences Edi ion) 42 (4): 5-20.
h ps://doi.o g/10.19742/j.cnki.50-1164/C.220401.
Xu, Q.H., Zhu, P.X., Tang, L. (2022): Ag icul u al se ices: Ano he way o a mland u iliza ion
and i s e ec on ag icul u al g een o al ac o p oduc i i y in China. Land 11 (8): 1170.
h ps://doi.o g/10.3390/land11081170.
Xu, X.C., Zhang, L., Chen, L.H., Liu, C.J. (2020): The Role o soil N2O emissions in ag icul u al
g een o al ac o p oduc i i y: An empi ical s udy om china a ound 2006 when ag icul u al
ax was abolished. Ag icul u e 10 (5): 150. h ps://doi.o g/10.3390/ag icul u e10050150.
Yang, J., Wang, J., Li, C., Liu, X.P. (2019): Spa ial di e en ia ion and d i ing ac o s o g een
o al ac o p oduc i i y in China's ag icul u e. Quan i a i e Economic and Technological
Economic Resea ch 36 (10): 21-37. h ps://doi.o g/10.13653/j.cnki.jq e.2019.10.002.
Yang, Y., Ma, H., Wu, G.S. (2022): Ag icul u al g een o al ac o p oduc i i y unde he dis o -
ion o he ac o ma ke in China. Sus ainabili y 14 (15): 9309.
h ps://doi.o g/10.3390/su14159309.
Ye, F., Yang, Z.N., Yu, M., Wa son, S., Lo ell, A. (2023): Can Ma ke -O ien ed Re o m o Ag-
icul u al Subsidies P omo e he G ow h o Ag icul u al G een To al Fac o P oduc i i y?
Empi ical E idence om Maize in China. Ag icul u e 13 (2): 251. h ps://doi.o g/10.3390/ag-
icul u e13020251.
Zhang, H.Y., Liu, Y.Z. (2015): E alua ion and analysis o ag icul u al p oduc ion e iciency in
Shandong P o ince based on undesi able ou pu model. Jou nal o Henan Ag icul u al Uni-
e si y 49 (3): 423-428. h ps://doi.o g/10.16445/j.cnki.1000-2340.2015.03.024.
Zhang, P.Y., Li, Y.Y., …, Qin, M.Z. (2020a): Comp ehensi e assessmen o he e ec o u ban
buil -up land expansion and clima e change on ne p ima y p oduc i i y. Complexi y, 2020:1-
12. h ps://doi.o g/10.1155/2020/8489025.
Zhang, P.Y., Yang, D., …, Shao, J.W. (2020b): Re-examining he d i e o ces o China’s in-
dus ial was ewa e pollu ion based on GWR model a p o incial le el. Jou nal o Cleane
P oduc ion ol. 262: 121309. h ps://doi.o g/10.1016/j.jclep o.2020.121309.
Zhao, P.Y., Wu, H.Y., Lu, Z.G., Kou, J.L. and Du, J. (2022): Spa ial di e ences, dis ibu ional
dynamics, and d i ing ac o s o g een o al ac o p oduc i i y in China. F on ie s in En i-
onmen al Science 10: 1058612. h ps://doi.o g/10.3389/ en s.2022.1058612.
Zuo, Y.X. (2019): S udy on he di e ence o p oduc ion and scale o ag icul u al o al ac o
p oduc i i y based on TFP Index. Ekoloji 28 (107): 3729-3734.
Con ac Au ho
D . Jay Lee
Depa men o Geog aphy, Ken S a e Uni e si y
Ken , 44240, OH, USA
e-mail: jlee@ken .edu
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