A abaye a, Assiya e al.
A icle
U ilizing in es men in ixed asse s and R&D as a ca alys
o boos ing p oduc i i y o s imula e economic g ow h
Economies
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Sugges ed Ci a ion: A abaye a, Assiya e al. (2024) : U ilizing in es men in ixed asse s and R&D as a
ca alys o boos ing p oduc i i y o s imula e economic g ow h, Economies, ISSN 2227-7099, MDPI,
Basel, Vol. 12, Iss. 10, pp. 1-22,
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Ci a ion: A abaye a, Assiya, Ana
Ku manalina, Gaukha Kalkabaye a,
Aige im Lambeko a, Ainu
My zhykbaye a, and Ye bolsyn
Akbaye . 2024. U ilizing In es men
in Fixed Asse s and R&D as a Ca alys
o Boos ing P oduc i i y o S imula e
Economic G ow h. Economies 12: 266.
h ps://doi.o g/10.3390/
economies12100266
Academic Edi o : Ral Fendel
Recei ed: 20 July 2024
Re ised: 13 Sep embe 2024
Accep ed: 24 Sep embe 2024
Published: 30 Sep embe 2024
Copy igh : © 2024 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
economies
A icle
U ilizing In es men in Fixed Asse s and R&D as a Ca alys o
Boos ing P oduc i i y o S imula e Economic G ow h
Assiya A abaye a 1, Ana Ku manalina 2, Gaukha Kalkabaye a 2,*, Aige im Lambeko a 1,
Ainu My zhykbaye a 2and Ye bolsyn Akbaye 2
1Depa men o Accoun ing and Audi ing, Ka aganda Buke o Uni e si y, Ka aganda 100024, Kazakhs an
2Depa men o Finance, Ka aganda Buke o Uni e si y, Ka aganda 100024, Kazakhs an
*Co espondence: kalkabaye a_g@buke o .edu.kz
Abs ac : In es men s o m he basis o high-quali y economic g ow h by ensu ing enewal o
p oduc ion capaci ies and imp o emen o echnologies and p ocesses, he eby inc easing labo
p oduc i i y. In es men esea ch is key o unde s anding i s impac on he coun y’s economic
ad ancemen and mo e e ec i e go e nmen policymaking o s imula e in es men ac i i y. The
pu pose o his pape is o s udy he ela ionship be ween ixed capi al and R&D in es men s
and labo p oduc i i y g ow h, as well as o de e mine he op imal le el o hese in es men s in
de e mining he g ea es e ec on labo p oduc i i y g ow h. We use a eg ession model and he leas
squa es me hod o empi ically analyze da a o se en coun ies o he pe iod be ween 1997 and 2022.
We calcula e es ima ed alues using SPSS and Py hon. The esul s show a ce ain impac o ixed
asse s and R&D in es men s on labo p oduc i i y g ow h. Howe e , he payo a ies ac oss he
coun ies unde s udy. Fu he mo e, despi e i s ela i ely small olumes, in es men in R&D b ings a
g ea e e ec on p oduc i i y g ow h han in es men in ixed capi al. Wi h o he ac o s emaining
cons an , he calcula ed op imums o in es men s in ixed asse s and R&D show maximum poin s o
g ow h in labo p oduc i i y.
Keywo ds: in es men s; R&D expendi u e; economic g ow h; labo p oduc i i y; op imal le el;
eg ession analysis; ixed asse s
1. In oduc ion
Economic g ow h is he ounda ion o a coun y’s economic de elopmen , which
mani es s in inc easing o imp o ing p oduc ion o goods and se ices, inc easing quali y
o li e, and mee ing people’s needs. Achie ing ce ain a es o economic g ow h is a s a egic
goal se by many coun ies. Ye each coun y uses i s own model o economic de elopmen
based on i s his o ical backg ound and e hnic cha ac e is ics, cu en p oduc ion ac o s
and e iciency o hei managemen , ex en o inno a ions and high ech, de elopmen o
ins i u ional ounda ions, e c.
An analysis o he global economic g ow h si ua ion has con i med a signi ican slow-
down in he global economy’s g ow h a e in ecen yea s compa ed o le els p io o
2020. Amid a slow eco e y in global economic g ow h, isks emain, including geopo-
li ical ensions, ade agmen a ion, a p olonged pe iod o ele a ed in e es a es, and
clima e change.
The Wo ld Bank p ojec s a s abiliza ion a e o global economic g ow h a 2.6% in 2024,
going in o a sligh inc ease in subsequen yea s (Wo ld Bank 2024a). The In e na ional
Mone a y Fund belie es he g oup o de eloped coun ies will see a g ow h a e o 1.7%
in 2024, while in he g oup o eme ging ma ke and de eloping coun ies, he economic
g ow h a e in 2024 will be sligh ly highe and amoun o 4.3% (In e na ional Mone a y
Fund 2024). In addi ion, he economic g ow h in Cen al Asian coun ies is p ojec ed
o be 4.6% in 2024 (Uni ed Na ions 2024). Following he si ua ion in Kazakhs an, whe e
Economies 2024,12, 266. h ps://doi.o g/10.3390/economies12100266 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 266 2 o 22
economic g ow h was eco ded a 5.1% in 2023, a decline o 3.4% is expec ed in 2024
(Wo ld Bank 2024b). A he same ime, Kazakhs an is s i ing o achie e an ambi ious
goal—GDP g ow h by 2029 o $450 billion wi h an a e age annual economic g ow h a e o
6–7% (The Na ional De elopmen Plan o Kazakhs an 2024). This objec i e necessi a es
he implemen a ion o e ec i e policies, including inc easing in es men s and p omo ing
p oduc i i y g ow h.
In he s uc u e o closely in e ela ed ac o s o economic g ow h, he p oduc i i y
indica o s ands ou . The global impo ance o p oduc i i y is e lec ed in he ac ha
coun ies wi h a high le el o p oduc ion e iciency, all o he hings being equal, a e
among he leade s in he socio-economic domain. By speci ying he signi icance o labo
p oduc i i y, we can exp ess i h ough he a io o labo esul o cos in he o m o wo king
ime. No ice how labo esul is o en e lec ed in he o m o GDP when conside ed
na ionwide. Tha said, labo p oduc i i y is he mos impo an ea u e and condi ion o
s able and accele a ed economic de elopmen . In u n, p oduc i e capaci y depends on
p oduc ion and economic ac o s and p ocesses, managemen sys ems, and human capi al.
In Kazakhs an’s case, he need o inc ease p oduc i i y o main ain he g ow h o he
economy is due o he p ojec ed deple ion o he cu en esou ce base and he ela i e
decline in he manu ac u ing indus y. In es men in usions can p o ide a s ong impe us
o labo p oduc i i y g ow h and quali a i e de elopmen . The e o e, Kazakhs an’s
in es men policy should ocus on enhancing in es men po en ial and di ec ing in es men
lows in o economy sec o s ha can yield signi ican e u ns.
Al hough ixed capi al in es men and R&D in es men and hei ole in Kazakhs an’s
economic de elopmen ha e a ac ed esea che s’ a en ion, hei speci ic impac on labo
p oduc i i y emains unde explo ed. Mos o he exi ing li e a u e has concen a ed on he
e ec s o di e en ypes o in es men ac oss a ious sec o s, such as ene gy p oduc ion
(Bolganbaye e al. 2022), ag icul u e (Mizanbeko and Kalym 2024), he scien i ic sphe e
(Abdikadi o a e al. 2024), and he enewable ene gy sec o (Lan e al. 2024). Despi e hese
s udies, a clea esea ch gap pe sis s, highligh ing he need o in es iga e he in luence o
ixed capi al in es men and R&D in es men on labo p oduc i i y.
This pape examines ixed asse s in es men and R&D expendi u e and analyzes hei
e ec on labo p oduc i i y g ow h in Kazakhs an and six o he coun ies o compa ison.
We u ilize a wo-s age lagged eg ession model co e ing he pe iod om 1997 o 2022.
The indings indica e ha bo h ixed capi al in es men and R&D in es men posi i ely
in luence labo p oduc i i y g ow h. Mo eo e , R&D in es men has a la ge e ec on
labo p oduc i i y han ixed asse s in es men . The obus ness o ou esul s is con i med
h ough he P ais–Wins en es ima o and esidual au oco ela ion. Py hon and SPSS we e
used o cons uc he model and isualize he da a. Addi ionally, we assess he e ec o
he c ises expe ienced by economies du ing he pe iod o 1997–2022 on he ela ionship
be ween in es men and labo p oduc i i y.
Ou esea ch makes a subs an ial inpu wi h i s de ailed desc ip ion o he con i-
bu ions o ixed capi al and R&D in es men s o labo p oduc i i y g ow h. This s udy
con ibu es o he scien i ic li e a u e in he ollowing ways. Fi s ly, i analyzes he ela ion-
ship be ween ixed capi al and R&D in es men s and labo p oduc ion capaci y. Secondly,
he s udy iden i ies he op imal le el o in es men in ixed capi al and R&D ha will
ha e he maximum e ec on labo p oduc i i y g ow h o he analyzed coun ies. Finally,
he esul s o he s udy can be used in de eloping s a egic in es men policies ha will
lean agains he possibili y o changing he a io be ween in es men in ixed capi al and
in es men in R&D o p ede e mine he g ow h o labo p oduc i i y and, consequen ly,
economic g ow h. To achie e his goal, he s udy uses a eg ession model, he main im-
plica ions o which a e ocused on he analysis o he ela ionship be ween indica o s and
inding op imal alues.
This pape is o ganized as ollows. Sec ion 2p o ides a b ie e iew o he li e a u e
on he esea ch opic, iden i ies exis ing gaps, and gene a es esea ch hypo heses.
Sec ion 3
p esen s he da a aken o he empi ical analysis and me hodology used.
Sec ion 4
p esen s
Economies 2024,12, 266 3 o 22
he esul s o he s udy and a discussion. Sec ion 5p o ides conclusions and ecommenda-
ions o u he esea ch.
2. Li e a u e Re iew and Resea ch Hypo hesis
Economic li e a u e p esen s a ious concep ual models o economic g ow h, including
classical, neoclassical, and endogenous g ow h heo ies, among o he s. These models
iden i y key d i e s o g ow h, such as specializa ion, capi al accumula ion, echnological
ad ancemen s, and ising in es men le els. Based on he ecommenda ions o scien i ic
heo ies, go e nmen s implemen a ious ools o s imula e and in luence economic g ow h
and p ospe i y. Among hese, in es men s a e ega ded as he mos c ucial ins umen o
economic policy.
O e all, esea ch con i ms ha in es men s ha e a posi i e impac on economic
de elopmen (Makuyana and Odhiambo 2018). In he s udy by A onso and Aubyn (2019),
VAR analysis was used o examine he e ec s o c owding ou and c owding in ac oss
17 OECD coun ies, e ealing a posi i e impac o in es men s on economic g ow h in mos
coun ies. Simila ly, Be g e al. (2018) conduc ed an in-dep h analysis o he e ec s o public
in es men s on economic g ow h and in es men e u ns in bo h e icien and ine icien
coun ies, d awing on he Cobb–Douglas p oduc ion unc ion and he neoclassical g ow h
model. They concluded ha bo h high- and low-e iciency coun ies bene i om economic
g ow h h ough inc eased public in es men expendi u es. The s udy by Sa˘gdıç e al. (2021)
u he suppo ed he signi ican in luence o in es men incen i es on egional and sec o al
g ow h. These incen i es included exemp ions om cus oms du ies, VAT, educ ions in
co po a e ax, p ojec in es men s, land alloca ion, in as uc u e suppo , and o he s.
An impo an a ea o esea ch, in ou iew, is he s udy o he impac o speci ic
ypes o in es men on economic g ow h. I is wo h no ing ha in es men s in ixed
capi al and R&D a e closely ied o p oduc ion p ocesses, as hey ocus on imp o ing
echnology and equipmen , educing p oduc ion cos s, and inc easing labo p oduc i i y,
ul ima ely leading o pe manen economic g ow h. Mo eo e , in es men s in ixed asse s
and R&D consis o bo h public and p i a e con ibu ions, making hem aluable ools in
g ow h-s imula ing policies. Econome ic s udies on in es men in R&D and ixed capi al,
p oduc i i y g ow h, and economic expansion can p o ide a b oade pe spec i e on he
e u ns o hese in es men s o a coun y’s economy.
Exi ing s udies on he impac o ixed capi al in es men s on economic g ow h can be
highligh ed (Tang 2010). Then, Li and Peng (2011) expanded he s udy o ixed in es men
by empi ically analyzing i s impac no only on economic g ow h, bu also he en i on-
men . Zhang (2019) explo es in es men in ixed asse s as an impo an componen o
in es men . His a icle used he ARIMA model o gi e an in-dep h analysis o ixed capi al
in es men s and o ob ain o ecas es ima es. Addi ionally, using co ela ion- eg ession
analysis, Makohon e al. (2020) ound ou ha , in mos coun ies analyzed, inc eased
in es men in ixed asse s led o as e economic g ow h. Howe e , he impac was he -
e ogeneous depending on he le el o inancial ma ke de elopmen and he deg ee o he
coun y’s esou ce o ien a ion. Bi and Zhao (2017) p ojec ed in es men in ixed asse s
based on he ma hema ical s a is ical models ARIMA and G ay Neu al Ne wo k. The use
o hese models allowed hem o iden i y a signi ican impac o in es men in ixed capi al
on China’s mac oeconomic indica o s, especially on economic g ow h, op imiza ion o
esou ce alloca ion, and employmen expansion.
As o in es men in R&D, he s udy by Yahyazadeh a and Shababi (2018) can be
e e enced. Based on he e iewed ele an li e a u e and con en analysis, hey ound
in es men in R&D o be one o he e ec i e ac o s o economic g ow h. An expanded
bibliome ic s udy allowed A ana-Ba bie (2023) o u he explo e he ela ionship be ween
R&D in es men and economic g ow h. He concluded ha in es men in R&D has a close
ela ionship wi h he size o de eloped and de eloping coun y economies. Mo eo e , his
new indica o based on he numbe o scien i ic a icles o e e y 1% o R&D in es men
u ned ou o be s a is ically signi ican in ela ion o economic g ow h.
Economies 2024,12, 266 4 o 22
Resea che s Mud onja e al. (2019), Hapson e al. (2014), and Wynn e al. (2022) ha e
deepened he s udy on R&D in es men ’s ole in economic de elopmen o indi idual
egions and indus ies. Fu he , Almeida and Amoedo (2020) added a sus ainabili y
index in hei empi ical analysis. Using linea eg ession, clus e analysis, and analysis o
a iance (ANOVA), hey de e mined ha R&D expendi u e is a de e minan o a coun y’s
sus ainable de elopmen .
Using a sample o 25 OECD coun ies, Aali-Buja i and Venegas-Ma inez (2023) con-
duc ed G ange causali y es o es ima e an MGM sys em’s dynamic panel model. They
ob ained empi ical e idence o bidi ec ional causali y be ween R&D in es men and GDP
pe capi a.
Meanwhile, Tung and Hoang (2024) explo ed 29 eme ging economies. Ha ing applied
a p oduc ion unc ion heo e ical amewo k, hey ound ha na ional R&D expendi u e
posi i ely a ec s economic g ow h o eme ging economies. In addi ion, hei panel coin e-
g a ion es demons a ed he exis ence o a long- un coin eg a ion ela ionship be ween
economic g ow h and independen a iables cha ac e izing R&D in es men and R&D ac-
i i ies.
Kazakhs an’s case has been examined by Colapin o e al. (2020), who concluded
ha Kazakhs an would equi e signi ican in es men s in six majo economic sec o s o
e ec i ely inc ease hei con ibu ion o he o e all GDP. The au ho s sugges ed ha R&D
in es men s mus be na owed owa d g een sus ainabili y. Thei s udy is based on he use
o a classical weigh ed GP (WGP) model, whe e he o al amoun o public R&D in es men
was in oduced as a cons ain .
Huseynli (2023) examined he impac o R&D in es men on accele a ing economic
g ow h in se e al coun ies in he Cen al Asian egion, including Kazakhs an, Ky gyzs an,
and Aze baijan. The s udy used econome ic analysis (G ange es ) and he EViews s a is-
ical package. The co ela ion analysis esul s showed a nega i e insigni ican ela ionship
be ween R&D expendi u e and GDP g ow h in Kazakhs an.
A e iew o he exis ing li e a u e iden i ied a esea ch gap in explo ing he impac o
in es men s in ixed asse s and R&D on labo p oduc i i y, a key quali a i e cha ac e is ic
o economic g ow h. Ou s udy a emp s o ind ou which o he wo ypes o in es men is
a mo e signi ican ac o o p oduc i i y g ow h in mode n condi ions: in es men in ixed
capi al o in es men in R&D. This is necessa y o implemen a mo e e ec i e in es men
policy and ensu e he equi ed le els o economic g ow h. We p opose hypo hesis H1
based on he abo e analysis.
H1. In es men in ixed asse s and R&D expendi u es a ec labo p oduc i i y g ow h and,
consequen ly, economic g ow h.
To achie e he maximum e u n on in es men s, i is impo an o de e mine whe he
he e a e limi s o inc easing in es men olumes. Endogenous g ow h models add ess
he impac o in es men s on economic g ow h and he limi s o hei posi i e e ec s
(Lukas 1988;Aghion and Howi 1992). The a icle by Baneliene e al. (2018) a emp ed o
de e mine he op imal le el o in es men . They p o ed ha in es men in R&D in EU
coun ies had he g ea es mul iplie e ec when he GDP exceeded 10,397 eu os pe capi a.
Thus, in mo e de eloped Eu opean economies, R&D in es men d i es g ea e GDP g ow h.
These indings ega ding he g ea e impac o R&D in es men on economic g ow h in
well-de eloped EU economies we e con i med in a mo e ecen s udy by Baneliene and
Melnikas (2020). Based on empi ical analysis o da a om Eu opean Union coun ies, hey
p oposed a modeling amewo k o conduc ing assessmen s.
Focusing on R&D in es men s and p oduc i i y, Ve bic e al. (2011) ound ha inc eas-
ing go e nmen spending on R&D enhances he long- e m p oduc i i y o he Slo enian
economy and boos s company e enues. Concu en ly, he au ho s concluded ha o al
ac o p oduc i i y a he na ion le el is posi i ely dependen on bo h o al R&D ou pu
and he deg ee o he coun y’s economy openness.
Economies 2024,12, 266 5 o 22
Fo hei inpu , Filippe i and Pey ache (2016) examined ca ch-up p oduc i i y g ow h
in de eloping coun ies while a guing ha in es men in echnology and ixed asse s is
impo an o ca ch-up de elopmen because, ul ima ely, i educes he echnology gap.
Co ado e al. (2018) analyzed sou ces o p oduc i i y g ow h based on he con ibu-
ions o in es men s in angible and in angible asse s o he Uni ed S a es and eigh een
Eu opean coun ies. They concluded ha coun ies wi h highe ICT in ensi y and lowe
manu ac u ing sha es in es mo e in in angible asse s han hey do in angible asse s.
Mo eo e , he esul s o hei empi ical s udy showed ha in es men in in angible asse s
is ela i ely high in coun ies wi h signi ican public in es men in R&D.
The swi ad ancemen o he digi al economy, pa icula ly in digi al inance, g ea ly
in luences p oduc ion p ocesses and labo p oduc i i y. Acco ding o Liao and Du (2024),
digi al inance se es as a powe ul ca alys o economic g ow h by enhancing public
heal h, which is closely ied o sus aining wo k capaci y and boos ing labo p oduc i i y.
To explo e his, hey pe o med a longi udinal da a analysis using P obi models and
he e ogeneous analyses in hei s udy.
Bo ko ic and Tabak (2018) ocused on di e en ypes o public in es men as one o
he main d i e s o C oa ian public and p i a e company pe o mance in a ious sec o s
o he economy. They es ima ed indus y p oduc ion unc ions, applied wo se s o GMM
(Gene alized Me hod o Momen s) ins umen s, and es ed he key ac o in luence on o al
ac o p oduc i i y g ow h.
Coccia (2009) used a gene al dynamic linea eg ession model o de e mine he op imal
le el o R&D in es men o enhancing long- e m p oduc i i y in open economies.
Ou app oach builds on he Coccia (2009) model by inco po a ing in es men in ixed
capi al as an addi ional a ea o ocus. We es ima e he impac o ixed asse s in es men and
R&D in es men on labo p oduc i i y g ow h. P e iously, he ela ionships be ween ixed
in es men , R&D in es men , and p oduc i i y ha e been s udied sepa a ely, ocusing on
R&D in es men and R&D ac i i y. Mo eo e , esea che s ha e shown g ea e in e es in
s udying in es men and economic de elopmen in de eloped and de eloping coun ies.
Thus, as a gap in he li e a u e, one can iden i y he lack o empi ical esea ch in o he
ela ionship be ween hese indica o s in Kazakhs an whe e issues o s imula ing economic
de elopmen a e e y ele an . The signi icance o his s udy is due o he need o ill
he iden i ied gap and p o ide da a in his a ea. We p opose hypo hesis H2 based on he
abo e analysis.
H2. The e is a ce ain op imal le el o in es men in ixed capi al and in es men in R&D ha
leads o maximum g ow h in labo p oduc i i y.
3. Da a and Me hods
3.1. Desc ip ion o Va iables and Da a
A e iew o he li e a u e on he esea ch opic allowed us o selec indica o s o
modeling he dynamic ela ionships and es ing he hypo heses. We used he ollowing
a iables o he s udy: g ow h in labo p oduc i i y (RGLP), in es men in ixed asse s
as a pe cen age o GDP (GFCF), in es men in R&D as a pe cen age o GDP (GERD),
employmen a e (EMPR), and g oss domes ic p oduc pe capi a acco ding o pu chasing
powe pa i y (GDPC). Table 1desc ibes he selec ed a iables.
The pape uses he labo p oduc i i y g ow h a e (RGLP), which cha ac e izes he
quali a i e side o economic g ow h. I is measu ed as GDP g ow h pe hou wo ked.
The ixed capi al in es men indica o is measu ed as cos s associa ed wi h ixed
capi al o ma ion as a pe cen age o GDP (GFCF). This indica o is equi ed o measu e
domes ic in es men and i s signi icance o he economy.
The R&D in es men indica o is de ined as g oss domes ic expendi u e on esea ch
and de elopmen as a pe cen age o GDP (GERD). This one can ac as an indica o o inanc-
ing inno a ion, which is a d i ing ac o in inc easing labo p oduc i i y and accele a ing
economic g ow h.
Economies 2024,12, 266 6 o 22
Table 1. Desc ip ion o a iables.
Va iable Measu emen Sou ce Pe iod
G ow h in labo
p oduc i i y (RGLP)
G ow h in GDP pe
hou wo ked
OECD h ps://da a.oecd.o g/
lp d y/labou -p oduc i i y-
and-u ilisa ion.h m, accessed
on 1 June 2024
1997–2022
G oss ixed capi al
o ma ion (GFCF)
G oss domes ic ixed
in es men
(% o GDP)
Wo ld Bank indica o s h ps:
//da abank.wo ldbank.o g,
accessed on 1 June 2024
1997–2022
Resea ch and
de elopmen
expendi u e (GERD)
G oss domes ic
expendi u es on
esea ch and
de elopmen
(% o GDP)
Wo ld Bank indica o s h ps:
//da abank.wo ldbank.o g,
accessed on 1 June 2024
1997–2022
Employmen o
popula ion a io
(EMPR)
Employmen o
popula ion a io,
modeled ILO es ima e
Wo ld Bank indica o s h ps:
//da abank.wo ldbank.o g,
accessed on 1 June 2024
1997–2022
GDP pe capi a
(GDPC)
GDP pe capi a based
on pu chasing
powe pa i y
Wo ld Bank indica o s h ps:
//da abank.wo ldbank.o g,
accessed on 1 June 2024
1997–2022
Sou ce: Va iables we e selec ed using he OECD and Wo ld Bank da abase.
In addi ion, o ake in o accoun addi ional ac o s, he s udy used he ollowing
indica o s: employmen a e as a pe cen age o popula ion (EMPR), as well as g oss
domes ic p oduc pe capi a a pu chasing powe pa i y (GDPC).
Using hese a iables, we aimed o ind e idence o a posi i e ela ionship be ween
in es men s in ixed capi al and R&D and p oduc i i y g ow h. Due o exis ing limi a ions
in access o in o ma ion, we ook da a o he ollowing se en coun ies be ween 1997 and
2022: Kazakhs an, Ge many, USA, I eland, Japan, Canada, and China. We used Py hon
and SPSS o calcula e e alua ion indica o s.
Table 2shows he desc ip i e cha ac e is ics o selec ed a iables, including he mean,
minimum, and maximum alues o he da a o he se en coun ies lis ed abo e.
The pape analyzes he pe o mance o se en coun ies—Kazakhs an, Ge many, USA,
I eland, Japan, Canada, and China. Al hough his is a ela i ely small sample, i is highly
ele an o ou s udy. Ou choice o hese se en coun ies is based on se e al key easons.
Kazakhs an is cen al o ou esea ch as we aim o enhance he in es men clima e he e
by d awing on success ul p ac ices om o he coun ies and scien i ic insigh s. China,
Kazakhs an’s nea es neighbo and a majo ade pa ne , has shown imp essi e g ow h
o e ecen decades, making i s in es men policy model pa icula ly ele an o ou s udy.
Ge many is included as a ep esen a i e o ad anced Eu opean economies, known o i s
e ec i e policies ha con ibu e o high s anda ds and p ospe i y. We u ilized Ge man
da a o in es iga e he ela ionship be ween R&D and ixed capi al in es men s and labo
p oduc i i y. The USA and Japan, ecognized leade s in R&D and echnology, p o ide
aluable insigh s in o how in es men s in hese a eas impac labo p oduc i i y in he
leading economies. I eland’s apidly g owing economy, e idenced by signi ican GDP
g ow h be ween 2017 and 2022, la gely d i en by he manu ac u ing sec o , p omp ed us o
examine how in es men s in ixed asse s and R&D con ibu ed o his g ow h. Canada, wi h
i s obus de elopmen and ocus on mine al ex ac ion and oil expo s, is also pe inen o
ou s udy, especially in ela ion o Kazakhs an’s own oil-dependen expo s uc u e. These
ac o s guided ou selec ion o hese se en coun ies o explo e he e ec s o in es men s in
ixed capi al and R&D on labo p oduc i i y and economic g ow h, and o de e mine he
op imal in es men le els.
Economies 2024,12, 266 7 o 22
Table 2. Desc ip ion o a iables based on da a om Kazakhs an, China, USA, I eland, Canada,
Ge many, and Japan.
Coun y Va iable
G ow h in
Labo
P oduc i i y
(RGLP)
G oss Fixed
Capi al
Fo ma ion
(GFCF)
Resea ch and
De elopmen
Expendi u e
(GERD)
Employmen o
Popula ion
Ra io (EMPR)
GDP pe
Capi a (GDPC)
Kazakhs an
Numbe o
obse a ions 23 23 23 23 23
A e age alue 4.38 23.87 0.18 65.56 19,849.0
S anda d de ia ion 3.48 3.03 0.05 1.57 6769.5
China
Numbe o
obse a ions 23 23 23 23 23
A e age alue 8.09 40.69 1.73 67.96 9991.34
S anda d de ia ion 2.39 3.44 0.49 3.27 4782.47
USA
Numbe o
obse a ions 23 23 23 23 23
A e age alue 1.56 21.16 2.81 59.74 55,876.23
S anda d de ia ion 1.31 1.36 0.30 1.91 4855.82
I eland
Numbe o
obse a ions 23 23 23 23 23
A e age alue 4.38 26.67 1.28 58.24 65,064.42
S anda d de ia ion 5.55 8.55 0.19 3.38 19,308.40
Canada
Numbe o
obse a ions 23 23 23 23 23
A e age alue 1.01 22.59 1.83 61.62 45,362.57
S anda d de ia ion 2.18 1.49 0.11 1.11 2969.99
Ge many
Numbe o
obse a ions 23 23 23 23 23
A e age alue 0.99 20.45 2.77 55.76 47,737.51
S anda d de ia ion 1.15 1.02 0.28 2.85 5104.69
Japan
Numbe o
obse a ions 23 23 23 23 23
A e age alue 1.06 25.29 3.17 58.24 38,776.89
S anda d de ia ion 1.13 1.28 0.14 1.38 2274.41
Sou ce: Au ho s’ own esea ch using da a om OECD and Wo ld Bank.
3.2. Reg ession Model
Taking Ma io Coccia’s wo k as a basis (Coccia 2009), we used models (1) and (2),
as ollows:
RGLP = (GFCF/GDPC), (1)
RGLP = (GERD/GDPC), (2)
These es ablish he ela ionship be ween labo p oduc i i y and in es men s in ixed
capi al and R&D.
The esea ch ook in o accoun a ce ain ime lag a e which he in es men ’s payo
can be ob ained. Acco dingly, he ime lag e ec has been included in he condi ion o
cons uc ing he model. Tha is, labo p oduc i i y in pe iod is assumed o may be
in luenced by in es men s in ixed capi al and R&D made in -2 pe iod.
The a icle used eg ession analysis o s a is ical da a using a quad a ic unc ion,
pa icula ly, a leading indica o model, as ollows:
yi, =β0+β1xi, −2+εi, , (3)
whe e iis a coun y, and is ime.
Economies 2024,12, 266 8 o 22
Acco dingly, model (1) o in es men in ixed capi al will ake he ollowing o m:
RGLPi, =β0+β1GFCFi, −2+β2GFCF2
i, −2+εi, (4)
In he case o in es men in R&D, model (2) will ake he ollowing o m:
RGLPi, =β0+β1GERDi, −2+β2GERD2
i, −2+εi, (5)
Equa ions (4) and (5) calcula e he in e ac o ela ionship using he o dina y leas
squa es (OLS) me hod. P esumably, he causal ela ionship be ween ixed and R&D in es -
men s and p oduc i i y g ow h is ecip ocal. In his case, using only he ime lag be ween
a iables migh no be enough. In his ega d, we need o apply wo-s age las squa es
es ima ion (2SLS), whe e in he i s s age, in es men in ixed asse s and R&D is aken as a
dependen a iable and becomes a unc ion o wo independen a iables: GDP pe capi a
PPP (GDPC) and employmen le el (EMPR).
Fo in es men s in ixed capi al:
GFCFi, −2=β0+β1GDPCi, −3+β2EMPRi, −3+εi, (6)
Fo R&D in es men :
GERDi, −2=β0+β1GDPCi, −3+β2EMPRi, −3+εi, (7)
A he second s age,
GFCFi, −2
and
GERDi, −2
alues ob ained du ing he eg ession
analysis become independen a iables. P oduc i i y g ow h a e (RGLP) becomes a
dependen a iable.
RGLPi, =β0+β1
GFCFi, −2+β2
GFCF2
i, −2+εi, (8)
Fo R&D in es men :
RGLPi, =β0+β1
GERDi, −2+β2
GERD2
i, −2+εi, (9)
High co ela ion issues a e elimina ed using he P ais–Wins en es ima ion me hod.
Reg ession analysis allows us o de e mine he deg ee o he ela ionship be ween p oduc-
i i y g ow h and in es men in ixed asse s, as well as be ween p oduc i i y g ow h and
in es men in R&D. The dependencies es ima ed as a esul o eg ession analysis a e o
g ea alue o ou esea ch. Because unc ions (8) and (9) a e con inuous and in ini ely
di e en iable, we can calcula e he op imum, which can indica e he maximum amoun
o in es men s in ixed capi al and R&D ha b ings he maximum e ec on p oduc i i y
g ow h, and he e o e on economic g ow h.
We also bea in mind ha one o he equi ed condi ions o one a iable’s unc ion,
o he solu ion x=x* o be maximum o minimum, is as ollows:
d (x)
dx =0 o x =x∗(10)
In his case, xis a s a iona y poin . I he unc ion is conca e (o con ex), hen his
condi ion is no only equi ed bu also su icien o x* o be a gene al (global) maxi-
mum (minimum).
4. Empi ical Resea ch Resul s and Discussion
In he coun ies in ques ion, he p opensi y o in es in ixed asse s and R&D a ies
signi ican ly. Fo ins ance, acco ding o Table 2, in Kazakhs an, he sha e o in es men
in ixed capi al o GDP on a e age o he analyzed pe iod is 23.8% and he sha e o
in es men in R&D is only 0.18%. These alues a e 21.2% and 2.8% in he USA, 25.3% and
Economies 2024,12, 266 15 o 22
Table 5p esen s he eg ession model indica o s o he se en coun ies unde s udy.
Table 5. Pa ame ic es ima es o models o he se en coun ies unde s udy (2SLS, second s age).
Coun y In e cep Coe icien β1Coe icien β2R2F DW
Kazakhs an −14.07 161.74 −439.79 0.030 0.305
(sig.0.74) 2.5
US −35.777992 28.899309 −5.552732 0.057 0.605
(sig.0.55) 1.24
Japan −122.8891 76.020368 −11.830114 0.174 2.105
(sig.0.15) 2.7
Canada −53.946762 56.132174 −14.839129 0.004 0.365
(sig.0.96) 2.5
I eland −342.78 531.029 −207.7 0.033 0.34
(sig.0.72) 2.1
China −2.17 11.99 −4.73 0.493 42.39
(sig.0.02) 1.9
Ge many 2.209696 −0.453254 0.000308 0.012 119.5
(sig.0.00) 2.0
Sou ce: Au ho s’ own esea ch using da a om OECD and Wo ld Bank.
The R
2
coe icien alues a e qui e low o he coun ies unde s udy (excep o China),
which indica es he low in luence o he esea ch and de elopmen expendi u e (GERD)
indica o on he labo p oduc i i y g ow h a e. By con as , he coe icien o de e mina ion
o China demons a es he signi ican in luence o esea ch and de elopmen expendi u e
on labo p oduc i i y g ow h among he analyzed coun ies, i.e., 49.3% o he a ia ion in
p oduc i i y g ow h is due o he in luence o in es men in R&D. The Fishe es gi es an
es ima e o he esul ing eg ession as a whole (p- alue mus be below 0.05). Table 5shows
ha he s a is ical es ima es acco ding o he Fishe c i e ion con o m o no ms only in
China and Ge many. The Du bin–Wa son s a is ic alue indica es he p esence o posi i e
o nega i e au oco ela ion. When DW = 2, au oco ela ion be ween he a iables is non-
exis en . In ou example, only Ge many shows a alue con o ming o no ms. The e o e,
we needed o adjus he model o imp o e he alues and use hem o calcula e he op imal
a iable alues.
To elimina e au oco ela ion, we applied he P ice–Wins en es ima ion me hod in SPSS.
Based on he esul s ob ained, we calcula ed he ex eme alues o he analyzed coun ies
(see Table 6).
Table 6. De e mina ion o GERD and RGLP op imal alues o se en coun ies a e model adjus men .
Coun y GFCF RGLP
Ge many 3.77027 0.72528
Japan 3.09573 0.94887
USA 2.63284 29.35898
Canada 1.95320 0.96381
China 1.38558 9.72287
I eland 1.28300 3.25741
Kazakhs an 0.14 1.65
Sou ce: Au ho s’ own esea ch using da a om OECD and Wo ld Bank.
Table 6shows a ela ionship be ween in es men in R&D and labo p oduc i i y
g ow h. In es men in R&D is an impo an d i e o labo p oduc i i y g ow h o he
pe iod be ween 1997 and 2022. The USA shows he highes R&D in es men payo : a an
in es men in R&D o 2.63%, he inc ease in labo p oduc i i y will be 29.36. A signi ican
impac o R&D in es men is con i med in China, whe e R&D expendi u e a 1.39% o
GDP con ibu es o p oduc i i y g ow h o 9.72. I eland also shows ai ly high p oduc i i y
g ow h o 3.26 o R&D in es men o 1.28% o GDP.
Economies 2024,12, 266 16 o 22
The low le el o in es men in R&D obse ed in Kazakhs an has a signi ican payo
oo: he maximum inc ease in labo p oduc i i y is 1.65 wi h in es men amoun ing o
0.14% o GDP. I is possible ha olumes o in es men in R&D in Kazakhs an a e low
because o he weak de elopmen o he manu ac u ing indus y and he se ice and
anspo sec o s.
In Ge many, Japan, and Canada, R&D in es men ’s impac on p oduc i i y g ow h is
smalle . A a high op imal le el o in es men in R&D (3.77, 3.09, and 1.95, espec i ely)
he maximum p oduc i i y g ow h does no exceed 0.97.
In gene al, when compa ing alues in Tables 4and 6, we can see ha wi h a ela i ely
small sha e o in es men in R&D, i s con ibu ion o he g ow h o labo p oduc i i y is
se e al imes highe han he e u n on in es men in ixed capi al.
4.3. Impac o Global C ises
An impo an ques ion is whe he economic c ises in luence he e ec o in es men
o labo p oduc i i y g ow h. C ises no only lead o economic down u ns and educe
in es men bu also al e he na u e o he ela ionship. Du ing he pe iod om 1997 o 2022,
which was he ocus o ou s udy, economies aced he Asian inancial c isis (1997–1998),
he global inancial c isis (2007–2009), and he COVID-19 pandemic (2020–2022). To ensu e
he accu acy o ou esul s, we accoun ed o he impac o hese c ises by inco po a ing
h ee dummy a iables in o he model a bo h s ages o he eg ession. The esul s o his
analysis a e p esen ed in Table 7.
Table 7. Resul s o eg ession analysis o he impac o in es men in ixed capi al and R&D on labo
p oduc i i y g ow h, inco po a ing dummy a iables.
Coun y Impac o In es men in Fixed Capi al
on Labo P oduc i i y G ow h
Impac o In es men in R&D
on Labo P oduc i i y G ow h
Coe S d E -S a pCoe S d E -S a p
China
Asian_c isis 0 0 Nan Nan 0 0 Nan Nan
Global_c isis −0.1049 1.963 −0.053 0.957 1.0273 2.005 0.512 0.608
COVID_pandemic −2.0746 2.168 −0.957 0.339 1.1711 3.350 0.350 0.727
Japan
Asian_c isis −9.625 ×10−16 1.34 ×10−15 −0.720 0.471 −8.119 ×10−14 1.26 ×10−12 −0.064 0.949
Global_c isis −1.6964 0.878 −1.931 0.053 −1.3217 0.830 −1.592 0.111
COVID_pandemic −0.6431 0.995 −0.647 0.518 −0.2652 0.959 −0.277 0.782
Ge many
Asian_c isis −1.565 ×10−11 1.79 ×10−11 −0.876 0.381 −5.615 ×10−17 1.29 ×10−16 −0.436 0.663
Global_c isis 0.2691 1.611 0.167 0.867 −2.3036 1.418 −1.624 0.104
COVID_pandemic −0.5584 0.829 −0.674 0.500 −0.5099 1.068 −0.478 0.633
I eland
Asian_c isis −1.793 ×10−15 1.7 ×10−15 −1.057 0.291 8.61 ×10−12 1.18 ×10−11 0.728 0.466
Global_c isis 0.3131 3.691 0.085 0.932 −1.0512 3.323 −0.316 0.752
COVID_pandemic 26.0079 23.339 1.114 0.265 5.4371 7.328 0.742 0.458
USA
Asian_c isis −5.683 ×10−13 1.7 ×10−12 −0.334 0.738 3.534 ×10−16 2.53 ×10−16 1.399 0.162
Global_c isis −0.9215 0.822 −1.121 0.262 0.4115 1.042 0.395 0.693
COVID_pandemic −0.4227 2.494 −0.169 0.865 22.8786 16.514 1.385 0.166
Economies 2024,12, 266 17 o 22
Table 7. Con .
Coun y Impac o In es men in Fixed Capi al
on Labo P oduc i i y G ow h
Impac o In es men in R&D
on Labo P oduc i i y G ow h
Coe S d E -S a pCoe S d E -S a p
Canada
Asian_c isis 2.685 ×10−13 1.72 ×10−12 0.156 0.876 2.094 ×10−16 5.38 ×10−16 0.389 0.697
Global_c isis −0.9648 0.441 −2.188 0.029 −1.2822 1.221 −1.050 0.294
COVID_pandemic −0.2259 4.627 −0.049 0.961 −0.4974 4.663 −0.107 0.915
Kazakhs an
Asian_c isis −4.769 ×10−16 3.17 ×10−15 −0.150 0.881 2.175 ×10−13 3.91 ×10−13 0.556 0.578
Global_c isis 2.6448 24.062 0.110 0.912 −4.7435 5.418 −0.876 0.381
COVID_pandemic −1.1414 4.353 −0.262 0.793 −3.7453 7.792 −0.481 0.631
Sou ce: Au ho s’ own esea ch using da a om OECD and Wo ld Bank.
Since ou s udy co e ed he 1997–2022 pe iod, he impac o he Asian c isis
(1997–1998)
on ou esul s was minimal due o he ime lag o in es men e ec s on p oduc i i y. This
is e idenced by he eg ession coe icien s, which a e close o ze o.
A he same ime, he modeling esul s show ha he e ec s o he global c isis
(2007–2009)
and he COVID-19 pandemic (2020–2022) we e mo e signi ican . In Japan
and Canada, he eg ession coe icien s a e nega i e, indica ing ha he global c isis and
he COVID-19 pandemic educed he impac o bo h ypes o in es men s— ixed asse s
in es men (GFCF) and R&D in es men (GERD)—on labo p oduc i i y (RGLP).
Da a om Ge many and Kazakhs an sugges a nega i e impac o he COVID-19
pandemic on he ela ionship be ween R&D and ixed capi al in es men s and p oduc i i y
g ow h. Meanwhile, al hough he global c isis nega i ely a ec ed R&D in es men , i
had a posi i e e ec on he in luence o ixed capi al in es men s on p oduc i i y in hese
wo coun ies.
Reg ession analysis e ealed a nega i e e ec o he global c isis and he COVID-19
pandemic on he ela ionship be ween ixed capi al in es men s and p oduc i i y in China
and he USA. Con e sely, hese same c ises had a posi i e e ec on he in luence o R&D
in es men on labo p oduc i i y in bo h coun ies. This means ha he c ises, pa icula ly
he COVID-19 pandemic, s eng hened he impac o R&D in es men on p oduc i i y
g ow h in China and he USA.
This esul is a simila o he indings o B own and Pe e sen (2014). They con i med
ha companies ake a di e en ia ed app oach o ixed in es men and R&D du ing a
inancial c isis. In esponse o a nega i e inancial shock, hey educe in es men in ixed
asse s o a g ea e ex en han R&D expendi u es.
In I eland, he global c isis had a nega i e impac on he e ec s o R&D in es men and
a posi i e impac on he e ec s o ixed capi al in es men . Signi ican posi i e eg ession
coe icien s we e ob ained in he analysis o he e ec s o he COVID-19 pandemic, indica -
ing an inc eased in luence o bo h ixed capi al and R&D in es men s on labo p oduc i i y
du ing he pandemic pe iod.
In gene al, he esul s show he nega i e impac o c ises on labo p oduc i i y g ow h
in all o he coun ies s udied, on in es men olumes in se e al coun ies, and he ela-
ionship be ween in es men and labo p oduc i i y. Mo eo e , he c isis si ua ion is mo e
c i ical o Kazakhs an: a signi ican nega i e impac o he global c isis and he pandemic
on he olume o in es men s in ixed asse s and labo p oduc i i y, as well as on he
dependence o in es men s and p oduc i i y, has been e ealed.
Resea che s Pellens e al. (2024) ound ha inno a ion-leading coun ies implemen
coun e cyclical R&D spending policies du ing ecessions, whe eas less inno a ion-d i en
coun ies end o ollow an acyclical s a egy du ing economic c ises. This di e ence widens
he gap be ween coun ies in e ms o inno a ion and economic g ow h a es. To p e en
such a si ua ion, Kazakhs an should adop a coun e cyclical policy du ing economic c ises
Economies 2024,12, 266 18 o 22
by inc easing go e nmen suppo and spending on R&D and ixed capi al o ma ion,
which would ha e syne gis ic e ec s on labo p oduc i i y and ou pu .
4.4. Implica ions o In es men Policy
In ecen yea s, he go e nmen o Kazakhs an has made signi ican e o s o c e-
a e a a o able in es men clima e, including he c ea ion o special economic zones, a
clus e app oach, he de elopmen o public–p i a e pa ne ships, ax incen i es, and
o he measu es. The adop ed ini ia i es ha e inc eased he in low o o eign di ec in es -
men , which amoun ed o $28 billion in 2022 and $23 billion in 2023 (Na ional Bank o
he Republic o Kazakhs an 2024). No ably, Kazakhs an’s speci ici y is ha he bulk o
ha in es men goes mainly o la ge capi al-in ensi e indus ies, such as he oil and gas
and mining sec o s. A he same ime, hese sec o s make he g ea es con ibu ion o he
coun y’s economic g ow h.
Meanwhile, i Kazakhs an aims o achie e an annual g ow h a e o 6–7%, i will
equi e a policy ocused on boos ing in es men s in ixed capi al and R&D. This is due o
he signi ican wea and ou da ed s a e o ixed asse s (equipmen /machine y) in a ious
economic sec o s, low capi al in ensi y and echnological le els o p oduc ion, as well as
he disconnec be ween scien i ic esea ch and p oduc ion p ocesses.
Compa ed o o he coun ies, Kazakhs an no only has low olumes o ixed capi al
and R&D in es men s bu also low e u ns on such in es men s. Acco ding o he esul s
o ou s udy, he maximum e u n o in es men o labo p oduc i i y g ow h is achie ed
when he le el o ixed capi al in es men is abo e 23.5% o GDP and he sha e o R&D
in es men is abo e 0.14% o GDP. The esul s show ha R&D in es men is mo e e ec i e
and capable o p o iding he g ea es e u n on labo p oduc i i y g ow h (1.65) compa ed
o ixed capi al in es men (0.055).
The low e u ns on ixed capi al in es men s a e linked o hei subop imal s uc u e,
wi h ex emely low sha es o in es men in manu ac u ing, anspo a ion, and ag icul u e.
These a e sec o s in which inc easing labo p oduc i i y is a key condi ion o g ow h. This
si ua ion is la gely due o insu icien in e nal unds a ailable o en e p ises o in es men
and limi ed access o c edi . In hei s udy, Gomez Sanchez e al. (2022) con i med ha
policies should p omo e access o inancial capi al and in es men .
Inc easing he e iciency o R&D in es men in Kazakhs an will be possible p o ided
ha human capi al capable o sol ing complex echnological p oblems is u he de el-
oped. Gi en ha less han 1% o p oduc ion and less han 1% o o al employmen in
Kazakhs an a e ela ed o R&D, in ensi ying measu es and building capaci y in his a ea
a e o na ional impo ance.
Acco ding o Ma in (2007), he impac o R&D in es men on p oduc i i y is s onge
in high- ech sec o s o he economy. This means ha go e nmen policy should also aim o
c ea e condi ions o inc easing he complexi y o he economy and he use o ad anced
echnologies in p oduc ion p ocesses. In addi ion, as no ed by She e and F enkel (2005),
R&D in es men depends on he cha ac e is ics o he company, in pa icula i s size,
ype o indus y, loca ion, and ype o owne ship. The e o e, he go e nmen should
ake hese cha ac e is ics in o accoun in i s policies o s imula e R&D in es men and
indus ial inno a ion.
Expansion o ixed capi al and R&D in es men s could be achie ed by inc easing pub-
lic in es men s, which cu en ly accoun o less han 17% o o al ixed asse s in es men
(Bu eau o Na ional S a is ics 2024). As no ed in he Wo ld Bank Repo , “an inc ease in
public in es men by 1% o GDP in de eloping and eme ging ma ke coun ies may lead
o an inc ease in p oduc ion le els by 1.6% in he medium e m” (Wo ld Bank 2024a). This
is due o he ac ha public in es men can c ea e he condi ions o p oduc i i y g ow h
and s imula e p i a e in es men , collec i ely con ibu ing o long- e m economic g ow h.
Inco po a ing hese ecommenda ions in o policy will help o imp o e he in es -
men si ua ion in Kazakhs an by boos ing in es men s in ixed asse s and R&D, he eby
inc easing hei con ibu ion o labo p oduc i i y g ow h and high-quali y economic
Economies 2024,12, 266 19 o 22
g ow h. Concu en ly, s eng hening in es men dynamics is possible wi h a educ ion in
in es men isks, mac oeconomic balance, and s uc u al changes in he economy.
5. Conclusions
The idea ha in es men can s imula e p oduc i i y and economic g ow h is a ocus
o wide discussions in he scien i ic communi y. This p omp ed us o conduc an empi ical
analysis o in es men s in ixed asse s and R&D as ac o s de e mining labo p oduc i i y
g ow h and as d i ing o ces o economic g ow h. Summa izing he analy ical s udy
p esen ed in Sec ion 4, we can summa ize he ollowing conclusions. Fi s , o he pe iod
be ween 1997 and 2022, in es men in ixed asse s in all coun ies in ques ion a e aged no
less han 20% o GDP, and in es men in R&D was no less han 1% (excep o Kazakhs an).
Du ing he analyzed pe iod, Kazakhs an showed a lowe alue o he GERD indica o a
an a e age le el o 0.18%.
Second, ou esul s show ha in es men , especially in o R&D, posi i ely a ec s
p oduc i i y g ow h in he coun ies analyzed. Howe e , he e ec s o in es men s in ixed
asse s and R&D a y among all se en coun ies. The analysis esul s show he s onges
co ela ion be ween ixed capi al and R&D in es men s and labo p oduc i i y g ow h in
China compa ed o he o he coun ies s udied. In Kazakhs an, he weakes link be ween
ixed capi al and R&D in es men s and labo p oduc i i y is iden i ied.
Thi d, he esul s o he empi ical analysis indica e ha labo p oduc i i y can be
inc eased by achie ing an in es men le el in ixed capi al and R&D ha is close o op imal.
Calcula ing he op imal le el o ixed capi al in es men e ealed ha i deli e s he highes
e u ns in China. By in es ing in ixed asse s a he op imal le el o 37.4% o GDP, China
achie es maximum labo p oduc i i y g ow h a 11.8%. Acco dingly, China is cha ac e ized
by a high le el o ixed capi al o ma ion and a highe capi al payo . R&D in es men
yields he highes e u ns in he Uni ed S a es compa ed o he o he coun ies s udied. In
he USA, annual R&D in es men a e ages 2.8% o GDP. The calcula ions show ha he
op imal le el o R&D in es men in he USA is 2.63% o GDP, a which he maximum labo
p oduc i i y g ow h eaches 29.36.
In Kazakhs an, e en in es ing a he op imal le el has a minimal e ec on labo
p oduc i i y. The calcula ions show ha when he op imal le el o ixed capi al in es men
(23.5% o GDP) is eached, labo p oduc i i y g ow h in Kazakhs an amoun s o only 0.055.
Wi h R&D in es men a he op imal le el o 0.14% o GDP, labo p oduc i i y g ow h
would each 1.65.
Ano he impo an conclusion is ha , while ela i ely small in olume, in es men in
R&D b ings a g ea e e ec on g ow h han in es men in ixed asse s.
Fou h, he impac o ixed capi al and R&D in es men s on labo p oduc i i y g ow h
changed somewha du ing he global c isis (2007–2009) and he COVID-19 pandemic
(2020–2022)
. These c ises had a nega i e e ec , educing he in luence o ixed capi al
and R&D in es men s on p oduc i i y in Japan and Canada. The analysis also e ealed a
posi i e e ec o he COVID-19 pandemic on he ela ionship be ween R&D in es men
and labo p oduc i i y in China, he Uni ed S a es, and I eland. In Kazakhs an, he c ises
gene ally had a nega i e impac on he s udied indica o s, wi h he excep ion o a sligh
posi i e e ec o he global inancial c isis (2007–2009) on he ela ionship be ween ixed
capi al in es men and labo p oduc i i y g ow h.
Thus, he s a is ical esul s and g aphical da a demons a e he p esence o a ce ain
dependence o labo p oduc i i y g ow h on in es men s in ixed capi al and R&D. How-
e e , o be able o gi e mo e p ecise ecommenda ions o imp o ing in es men policies, i
is necessa y o s udy o he ypes o in es men , including o eign in es men , in es men
in human capi al, he impac o public in es men , and cyclical luc ua ions. Go e nmen
in es men policies will be mo e e ec i e i hey p omo e domes ic sa ings and in es men
while o eign di ec in es men lows a e declining. Gi en he mul i ace ed na u e o s udy-
ing he issues o inc easing p oduc i i y and economic g ow h, we also need o examine
Economies 2024,12, 266 20 o 22
he in luence o many o he ac o s, hus opening up oppo uni ies o u he esea ch on
his opic.
Au ho Con ibu ions: Concep ualiza ion, A.K. and G.K.; me hodology, A.A. and G.K.; so wa e,
A.A.; alida ion, A.A., A.K. and G.K.; o mal analysis, A.A.; in es iga ion, A.A. and G.K.; esou ces,
A.L. and A.M.; da a cu a ion, Y.A.; w i ing—o iginal d a p epa a ion, G.K.; w i ing— e iew and
edi ing, A.K. and A.A.; isualiza ion, A.A.; supe ision, A.L.; p ojec adminis a ion, A.K.; unding
acquisi ion, A.K. All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding: This esea ch was unded by he Na ional Bank o he Republic o Kazakhs an, g an
numbe 237.
Ins i u ional Re iew Boa d S a emen : No applicable.
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : Da ase s a e a ailable on eques .
Con lic s o In e es : The au ho s decla e no con lic o in e es . The unde s had no ole in he design
o he s udy; in he collec ion, analyses, o in e p e a ion o da a; in he w i ing o he manusc ip ; o
in he decision o publish he esul s.
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