Ka acuka, Mehme ; Myo ella, Godwin; Haucap, Jus us
A icle — Published Ve sion
P oduc i i y Pa adox in A ica: Does Digi aliza ion Fos e
Labo P oduc i i y in A ican Economies?
Jou nal o he Knowledge Economy
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Sugges ed Ci a ion: Ka acuka, Mehme ; Myo ella, Godwin; Haucap, Jus us (2024) : P oduc i i y
Pa adox in A ica: Does Digi aliza ion Fos e Labo P oduc i i y in A ican Economies?, Jou nal o he
Knowledge Economy, ISSN 1868-7873, Sp inge US, New Yo k, NY, Vol. 16, Iss. 2, pp. 8374-8393,
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P oduc i i y Pa adox inA ica: Does Digi aliza ion Fos e
Labo P oduc i i y inA ican Economies?
Mehme Ka acuka1,2 · GodwinMyo ella3· Jus usHaucap2
Recei ed: 24 Janua y 2024 / Accep ed: 23 June 2024 / Published online: 24 July 2024
© The Au ho (s) 2024
Abs ac
How he ad ancemen o in o ma ion and communica ions echnologies (ICT) and
digi aliza ion a ec labo p oduc i i y is subjec o an ongoing deba e. While pa s
o he li e a u e ind he expec ed posi i e e ec s, o he s udies ha e ound no e ec ,
esul ing in he so-called p oduc i iy pa adox. As mos o he s udies ha e ocused
on economically ad anced economies such as OECD coun ies, e idence o less
de eloped economies has been spa se.We use a digi aliza ion composi e index om
a balanced panel o 40 Sub-Saha an A ican (SSA) economies, using da a om
2006 o 2021, o assess he e ec o digi aliza ion on agg ega e labo p oduc i i yin
SSA economies. We employ gene alized leas squa es (GLS) and sys em gene al-
ized me hods o momen s (GMM) me hods o cap u e he e ec s o digi aliza ion
on labo p oduc i i y le els in ag icul u e, manu ac u ing, and se ice sec o s. Ou
esul s show a weak associa ion be ween digi aliza ion and o e all labo p oduc-
i i y. Howe e , when sec o s a e analyzed sepa a ely, digi aliza ion has a posi i e
e ec on labo p oduc i i y in ag icul u e and manu ac u ing sec o s, whe eas we
ind e idence o he p oduc i i y pa adox in he se ice sec o , wi h e en a nega i e
e ec o digi aliza ion on labo p oduc i i y.
Keywo ds Digi al economy· Labo p oduc i i y· Sub-Saha an A ica· P oduc i i y
pa adox· In o ma ion and communica ions echnology (ICT)
* Mehme Ka acuka
Mehme .ka [email protected].
Godwin Myo ella
myo[email p o ec ed]
Jus us Haucap
[email p o ec ed]
1 Depa men o Economics, Ege Uni e si y, Bo no a, Tu key
2 DICE, Hein ich Heine Uni e si y, Düsseldo , Ge many
3 Uni e si y o Dodoma, Dodoma, Tanzania
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Jou nal o he Knowledge Economy (2025) 16:8374–8393
In oduc ion
The so-called p oduc i i y pa adox e e s o he inding ha , al hough he e has been
a ise in digi aliza ion and in he usage o in o ma ion and communica ions echnol-
ogy (ICT) o e he pas decades, p oduc i i y le els in ad anced economies ha e
s agna ed and in some places e en dec eased, especially du ing he 1980s. Al hough
he e was an inc ease in p oduc i i y le els a e he 1990s, many ad anced econo-
mies ha e la e again expe ienced a simila p oduc i i y pa adox (Acemoglu e al.,
2014; B ynjol sson, 1993; B ynjol sson e al., 2019). The lack o subs an ial p o-
duc i i y g ow h is conside ed a pa adox because he combina ion o e e imp o -
ing mobile echnologies, unp eceden ed in e ne a ailabili y, and nume ous new
applica ions we e expec ed o boos labo p oduc i i y (Van A k, 2016; Polák, 2017;
Gómez‐Tello e al., 2020). While he e is a subs an ial body o li e a u e ha empha-
sizes he posi i e impac s o he digi al e olu ion on p oduc i i y g ow h, especially
in heo y, e en ea ly s udies ound ha he e ec s on g ow h and p oduc i i y whe e
much smalle han expec ed (Baily & Chak aba i, 1988; Lo eman, 1994; Roach,
1987). Fo example, Roach (1987) no ed ha e en hough he amoun o compu ing
powe pe whi e-colla wo ke in he se ice indus y inc eased d ama ically be ween
1970 and 1980 in he US, he p oduc i i y de elopmen was a he la . In he ime
om 1973 o he1980s US p oduc i i y g ow h was lowe han be ween 1950 and
1973 (B ynjol sson & Hi , 1998). E en mo e d ama ic is he sh inking p oduc i -
i y g ow h a e in he USA be ween 2011 and 2015, which s ood a 0.5%, despi e he
ad ancemen s o digi aliza ion wi h i s as amoun o da a collec ion and p ocessing
oge he wi h he p oli e a ion o new apps (Papanyan, 2015). P oduc i i y g ow h
has also been sluggish in o he de eloped na ions (Capello e al., 2022; Wa anabe
e al., 2018), while he e ha e been apid ad ancemen s in some eme ging economies
such as B azil, China, India, and Mexico. S ill, he lack o p oduc i i y g ow h in
many economies has become a signi ican conce n and an issue o he global eco-
nomic agenda (Col o d, 2016; Van A k, 2016). The unexpec edly low con ibu ion o
digi al echnology o wo ld economic g ow h has been coined a p oduc i i y pa adox
(Solow, 1987; also Bemd & Mo ison, 1995; B ynjol sson & Yang, 1996).
A signi ican po ion o li e a u e on he impac o digi aliza ion on labo p o-
duc i i y p edominan ly ocuses on indus ialized na ions. The impo ance o
compu e s, compu e mic op ocesso s, and p oduc i i y-enhancing compu e
so wa e in d i ing p oduc i i y g ow h om he mid-1990s is well es ablished
in he li e a u e. Howe e , he e is a no able lack o empi ical e idence o de el-
oping na ions wi h a ocus on he ela ionship be ween he ICT e olu ion and
labo p oduc i i y, speci ically o A ica. Fo his eason, his s udy ocusses
exclusi ely on A ican economies and pays pa icula a en ion o he In e ne and
mobile elephony. We aim o explo e how ICT, in e ms o mobile phones, in e -
ne usage, and b oadband echnologies con ibu e o labo p oduc i i y in Sub-
Saha an A ica, as he de elopmen o hese echnologies is supposed o be ans-
o ming he means o ganiza ions in e ac wi h labo (By ne & Co ado, 2017).
This s udy con ibu es o he analysis o he economic impac s o echnol-
ogy, by analyzing he e ec s o digi aliza ion on o al economy-wide labo
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p oduc i i y as well as e ec s on sec o -le el labo p oduc i i y in ag icul u e,
manu ac u ing, and se ice sec o s. Each o hese sec o s has i s unique cha ac-
e is ics, challenges, and echnological equi emen s due o he na u e o wo k,
skills equi emen s, and p oduc ion p ocesses. These speci ici ies may esul in
di e en e ec s o digi aliza ion. Hence, disagg ega ing he analysis may help
go e nmen s and policy make s o iden i y he mos bene icial policy measu es
h ough mo e a ge ed in e en ions wi h espec o digi al echnology adop ion.
This s udy also aims o p esen how he ansi ion is made om he adi ional
pa h o de elopmen om ag icul u e o indus y and inally o he se ice sec o
as pionee ed by au ho s such as Fishe (1939) and Cla k (1940).
The emainde o his pape is o ganized as ollows: he “Digi aliza ion, Inno-
a ion, and P oduc i i y” sec ion b ie ly in oduces he li e a u e on digi aliza ion,
inno a ion, and p oduc i i y. The “Reasons Why Digi aliza ion May No Fos e P o-
duc i i y G ow h” sec ion desc ibes some easons why digi aliza ion may no os e
digi aliza ion g ow h. The “Da a and Me hods” sec ion desc ibes da a, me hods, and
empi ical analysis. The “Empi ical Resul s” sec ion p esen s he empi ical indings,
and, inally, he “Conclusion” sec ion p o ides conclusions and policy implica ions.
Digi aliza ion, Inno a ion, andP oduc i i y
E e since Solow (1956) i has been widely acknowledged in he economic li e a u e
ha echnological p og ess is essen ial o p oduc i i y g ow h which, in u n, is a
p ima y sou ce o economic g ow h and p ospe i y and well-being (Papanyan, 2015;
Jo genson & S i oh, 2000; Oline & Sichel, 2000; K ugman, 1997; Solow, 1956;
Rome , 1990; G ossman & Helpman, 1991). Paul K ugman (1997, p. 9) amously
also said mo e han 25 yea s ago ha , while p oduc i i y is no e e y hing, in he
long un i is almos e e y hing. Mačiuly ė-Šniukienė and Gaile-Sa kane (2014)
poin ou ha p oduc i i y is one o he key benchma ks o in e na ionally compa e
he economic pe o mance o di e en coun ies (see also Gomez e al., 2006; F an-
kel and Kend ick, 2024).
Digi aliza ion is among he undamen al d i e s o echnological change in he
o eseeable u u e. Cen al o his de elopmen is he p oduc ion and use o digi-
al logic ci cui s and hei de i ed echnologies, including he compu e , he sma -
phone, and he in e ne (Walwei, 2016). Digi al echnologies a ec many aspec s,
including he p oduc ion p ocesses, and se ice deli e y. I b ings connec i i y o
people, wo ke s, and machines (Walwei, 2016).
Since he ad en o he digi al e olu ion, digi al echnologies and hei de i ed
echnologies, including compu e s, cell phones, he in e ne , he use o big da a, a i i-
cial in elligence, and mobile obo s ha e acili a ed compu e -d i en economies (F ey
& Osbo ne, 2017). B ynjol sson and McA ee (2012) poin ed ou ha echnological
inno a ions a e inc easing emendously in he a ea o digi al echnologies. In e es -
ingly enough and a he ema kably, au oma isa ion e nds do no only a ec ou ine
manu ac u ing asks, bu also high skilled jobs such as hose pe o med by doc o s,
accoun an s, lawye s and many mo e. Thus, echnological inno a ion is expec ed o
signi ican ly con ibu e o an inc ease in p oduc i i y, bu he e a e some imes also
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conce ns abou po en ial nega i e e ec s on employmen . F ey and Osbo ne (2017)
a gue ha occupa ions wi h he highes con en o ou ine asks a e he mos likely o
be soon eplaced by digi aliza ion. Dachs (2018), howe e , a gues ha he size o he
nega i e e ec s depends on he cu en p oduc ion echnology and he a e o subs i-
u ion be ween inpu ac o s and he di ec ion o echnological change.
Digi aliza ion is said o acili a e mo e knowledge-based and decen alized p o-
duc ion as a esul o comp ehensi e in e ne connec i i y. Like any o he ype o
echnological change, digi aliza ion gene ally inc eases p oduc i i y and labo p o-
duc i i y in pa icula by wo king sma e h ough he new echnologies and ech-
niques o p oduc ion (B ynjol sson & Hi , 1998). Fo example, cloud compu ing,
emo e wo king, in as uc u e sha ing and o he de elopmen s acilia ed by digi ali-
za ion p ocesses a e likely o lowe en y ba ie s in many ma ke s, he eby in en-
si ying p oduc ma ke compe i ion and lowe ing consume p ices (Walwei, 2016).
Ku and Ku (2015) u he highligh ha he ease and p e alence o communi-
ca ing online as well as o he de elopmen s in ICT “had a posi i e e ec on load and
p oduc i i y o labou o ce accele a ed wo k low and also inc eased he e iciency
o p oduc ion p ocesses and ou pu amoun s.” As Ku and Ku (2015) u he
a gue, coun ies “wi h highe popula ions and labo o ce ha e mo e oppo uni ies o
g ow and de elop i he labo o ce in eg a es he ICT echnologies.”
Se e al empi ical s udies p o ide e idence o a posi i e nexus be ween in es -
men s in digi aliza ion and p oduc i i y pe o mance, a he i m and indus y le els.
Gal e al. (2019) a e among he s udies ha illumina e how majo digi al echnolo-
gies ( iz. high-speed b oadband in e ne , simple and complex cloud compu ing se -
ices, En e p ise Resou ce Planning, and Cus ome Rela ionship Managemen so -
wa e) a ec i m p oduc i i y in 19 EU coun ies and Tu key. The s udy used 22
indus ies wi h da a om 2010 o 2015 and e ealed ha indus y-le el digi al adop-
ion con ibu es o signi ican p oduc i i y e u ns a he i m le el. Thei esul s
imply ha digi al adop ion in he indus y has con ibu ed o inc eased p oduc i i y
dispe sion ac oss i ms. They u he ind ha digi aliza ion is on a e age mo e ben-
e icial in manu ac u ing han se ice i ms, and mo e wide-sp ead in indus ies ha
in ol e a high sha e o ou ine asks.
Ba el e al. (2007) ha e analyzed se e al plan -le el mechanisms h ough which
IT may p omo e p oduc i i y g ow h in indus y al e manu ac u ing. Thei analysis
unco e ed h ee main esul s. Fi s , plan s ha adop new IT-enhanced equipmen
also shi hei business s a egies by p oducing mo e cus omized al e p oduc s.
Second, new IT in es men s imp o e e iciency in all s ages o he p oduc ion p o-
cess by educing se up imes, un imes, and inspec ion imes. Consequen ly, i is
less cos ly o swi ch p oduc ion om one p oduc o ano he and suppo he change
in business s a egy o mo e cus omized p oduc ion. Thi d, he adop ion o new IT-
enhanced capi al equipmen coincides wi h inc eases in he skill equi emen s o
machine ope a o s, no ably echnical and p oblem-sol ing skills, and wi h he adop-
ion o new human esou ce p ac ices o suppo hese skills.
Ake man, Gaa de , and Mogs ad (2015) analyzed whe he he adop ion o b oad-
band in e ne in i ms enhances labo p oduc i i y and wages in No wegian i ms.
They exploi i m-le el in o ma ion on alue-added, ac o inpu s, and b oadband,
and ound ha b oadband adop ion a o s skilled labo by inc easing i s ela i e
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p oduc i i y. Gal e al. (2019) poin ou ha he nexus be ween in es men s in digi-
al echnologies and p oduc i i y g ow h is no wi hou some complexi ies. I can be
challenging o ind eliable empi ical measu es. As he au ho s a gue he impac may
depend on o he ac o s ha complemen digi al echnologies. Di e en ac o s enable
he e icien de elopmen and deploymen o esou ces. These include, among o he s,
o ganiza ional capi al and managemen skills (Basu e al., 2003; Bloom e al., 2012;
B ynjol sson & Hi , 2000), human capi al (Becke , 1964) and ICT- ela ed skills, as
well as a egula o y en i onmen ha suppo s he e icien alloca ion o esou ces.
Reasons Why Digi aliza ion May No Fos e P oduc i i y G ow h
Despi e he undeniable boos o economic ans o ma ion induced by digi al ech-
nologies and inno a ions, p oduc i i y g ow h has no been as imp essi e as some-
imes expec ed in many pa s o he wo ld (Gold a b and Tucke 2019, OECD,
2015). In OECD economies, p oduc i i y g ow h has been ading o e he pas dec-
ades despi e he massi e di usion o digi al echnologies (OECD, 2019, Chap e 2).
This obse a ion is pa ly explained by issues such as p ema u e deindus ializa ion,
mismeasu emen , and digi al p ice de la ion (Boussou , 2019; By ne e al., 2016;
McMillan e al., 2014). As a consequence o he global inancial c isis and i s a e -
ma h, o ins ance, he educ ion in c edi a ailabili y has a ec ed in es men . In
addi ion, he e a e some imes s uc u al easons, such as a decline in business dyna-
mism and poo pe o mance o low-p oduc i i y i ms (OECD, 2019, Chap e 2).
P ema u e indus ializa ion and s uc u al change ha e been iden i ied as he majo
con ibu o s o he sluggish g ow h in labo p oduc i i y (McMillan e al., 2014). As
he au ho s a gue he in eg a ion o he global economy and echnology ans e may
be a emedy o low g ow h a es. E en hough globaliza ion is p og essing in de elop-
ing coun ies, impo quo as and a i s ha e been lowe ed, o eign di ec in es men s
and expo s a e encou aged, and c oss-bo de inancial lows easie han in he pas , he
condi ions o doing business a e a om pe ec in Sub-Saha an A ica. Acco ding
o McMillan e al. (2014), labo has mo ed in o he w ong sec o s o he economies,
om mo e p oduc i e o less p oduc i e ac i i ies, including mos no ably in o mal sec-
o s. P ema u e de-indus ializa ion has inc eased cos s, as can be seen, o example,
in Nige ia, Ghana, and Sou h A ica. The pa e ns obse ed in he pos -2000 pe iod
exhibi p ema u e de-indus ializa ion in hese Sub-Saha an A ican economies. The
sha e o employmen in manu ac u ing has allen by mo e han 5% bu i was o se by a
simila expansion in se ice sec o s whe e labo p oduc i i y was nea ly double ha o
manu ac u ing. Sou h A ica and Ghana labo mo ed om a la gely ag icul u e-based
economy o economies wi h la ge se ice sec o s.
Boussou (2019) poin s ou ha p oduc i i y g ow h has g adually declined due
o digi al p ice de la ion. The a gumen is ha p ices in adi ional sec o s o he
economy ha e ended o inc ease in he ecen decade whe eas hose in he digi al
sec o ha e declined. Da a o he US economy show ha , in 2017, he p ice de la-
o o he o e all economy inc eased by 1.9% while ha o he digi al economy
declined by 2.2%.
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Mo eo e , mismeasu emen is ano he issue in he digi al economy ha has
biased mac oeconomic s a is ics, pa icula ly in he scope and es ima ion o GDP
(Ahmad e al., 2017). Au ho s such as Boussou (2019) a gue ha mismeasu emen
is an explana ion o he (measu ed) slow p oduc i i y g ow h in he pos - ecession
e a. The a gumen is based on he idea ha o icial s a is ics canno p ope ly cap u e
he p oduc i i y gains in in o ma ion echnology (IT) ela ed goods and se ices.
P ices and quali y a e he mos c i ical ac o s whose impac is seen in he p ice
de la o s. On he con a y, howe e , i is a gued ha i o iginal p ices a e no p op-
e ly measu ed, p ice de la o s would be o e -es ima ed. This will consequen ly lead
o an unde -es ima e o eal economic ou pu . Con e sely, By ne e al. (2016) poin
ou ha he changing s uc u e o a apidly e ol ing economy gi es aise o ano he
measu emen p oblem. The apid in oduc ion o new p oduc s and se ices, such
as Ube and Ai bnb by businesses, can bias es ima es o labo p oduc i i y. This is
because as e ans o ma ions cause di icul ies in adjus ing o icial s a is ics. By ne
e al. (2016) and Ahmad e al. (2017) also conced, howe e , ha mismeasu emen
is no a new issue. I has exis ed be o e he p oduc i i y slowdown, and he e is no
clea e idence whe he his has become mo e se e e o e ime. The au ho s u he
a gue ha e en i he e is mismeasu emen , i s ex en is no su icien o explain he
widesp ead slowdown in p oduc i i y g ow h.
Cal ino and C iscuolo (2019) add ha he une en adop ion and di usion o digi-
al ools ac oss i ms, indus ies, sec o s, and coun ies may explain he digi al p o-
duc i i y pa adox. When he e is une en up ake in digi al echnologies, he e may be
a slowdown o e en nega i e p oduc i i y g ow h. E idence o illus a e his kind o
nexus is aken om de eloped coun ies, such as he OECD economies, whe e many
i ms ha e access o high-speed b oadband ne wo ks, and ye ewe o hem ha e
p oduc i i y-enhancing digi al ools and applica ions, such as en e p ise planning
sys ems. Simila o o he echnological changes, digi al ans o ma ion also needs
complemen a y in es men s, such as p ocess inno a ions, new sys ems, and busi-
ness models (Haskel and Wes lake, 2017). These, howe e , in ol e se e al ials and
e o s. In so doing, many i ms en e and exi he business, depending on he busi-
ness en i onmen which di e s ac oss coun ies, which slows p oduc i i y g ow h
(B ynjol sson e al., 2019).
Da a andMe hods
Empi ical Analysis
This sec ion desc ibes he economic model and he econome ic app oach used
o analyze he e ec s o digi aliza ion on labo p oduc i i y in Sub-Saha an A i-
can economies. The app oach ollows Gus and Ma quez (2004), bu ex ends hei
s udy byusing panel eg essions. Following Saia (2023) and Kouladoum e al.
(2022) a digi aliza ion composi e index has been cons uc ed om he ou digi-
al echnology a iables, namely mobile phone subsc ip ions pe 100 inhabi an s
(Mobsub), ixed elephone subsc ip ions pe 100 inhabi an s (Fixsub), pe cen -
age o indi iduals using he in e ne , and mobile b oadband subsc ip ions pe 100
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inhabi an s (B b_sub). These echnologies ha e been adop ed mos ly in he pas
wo decades in Sub-Saha an A ica and exhibi an inc easing end despi e he
dispa i ies be ween egions (Myo ella e al., 2021). Mo eo e , hey a e chosen
as measu es o digi aliza ion, because in con as o some o he mo e ad anced
measu es hey a e widely a ailable ac oss Sub-Saha an A ican coun ies, sec-
o s, and ime. To s udy he e ec s o digi aliza ion on labo p oduc i i y g ow h,
we con ol o a a ie y o ac o s in luencing labo p oduc i i y g ow h in Sub-
Saha an A ica, including socio-economic, poli ical, and in as uc u e a iables.
In oday’s knowledge-based economy, ICT-based ools, such as he in e ne , a e
expec ed o aise p oduc i i y. Mo ep e , ICT is a gene al pu pose echnology
(GTP) ha a ec s almos e e y hing. This includes wha and how economies p o-
duce and how hey manage and o ganize he whole p oduc ion p ocess. Using
he de e minan s o labo p oduc i i y, he s udy iden i ies he e ec o he new
digi al a iables on labo p oduc i i y, conside ing he ollowing unc ional o m:
The dependen a iable
LPi
deno es labo p oduc i i y (GDP pe employed pe -
son),
Xji
(
j=1….K)
is a ma ix wi h explana o y a iables such as he digi aliza-
ion index (digindx), human capi al (HC), poli ical s abili y (Pol_STBLTY), g oss
domes ic in es men (GDI), elec ici y in as uc u e (ELECTRI), and ade open-
ness (TOP). The subsc ip i deno es coun y i = 1, 2…m and a ime = 1,2,…T.
whe e
𝜇
is he ime e ec cap u ed by yea dummy a iables in he eg ession,
i
is he coun y-speci ic e ec in a ian o e ime, and
𝜖i
is he andom e o e m in
he equa ion, ep esen ing he ne in luence o all unmeasu ed ac o s.
Human capi al is an indispensable a iable o he e ec i e use o digi al ech-
nologies, see (Lahouel e al., 2021; Caka e al., 2021; Kouladoum e al., 2022).
In he pas wo decades, when ICT is wi nessed o ha e signi ican ly g own and
sp ead, esea che s ha e obse ed a shi in labo demands owa ds skilled wo k-
e s. A ani is and Loukis (2009) a gue ha skilled labo is a p econdi ion o he
use o ICT. O e all, he e is an inc ease in o al p oduc i i y since less labo is used
o p oduce goods and se ices. In his s udy, human capi al (HC) is measu ed by
he human capi al index based on yea s o schooling and e u ns on educa ion. I is
a gued ha policies ha yield highe e u ns om educa ion encou age inno a ion
and os e he adop ion o in o ma ion and communica ion echnologies. These pol-
icies also p omo e capi al in es men , bo h p i a e and public, including elecom-
munica ions in es men , and can po en ially ha e a high impac on li ing s anda ds
(Papanyan, 2015). The con ibu ion o human capi al o labo p oduc i i y is heo-
e ically widely accep ed in bo h he mac oeconomic and mic oeconomic li e a u es
(see o example Nelson and Phelps, 1966; Ba o and Sa a-i-Ma in, 2004).
O he con ol a iables include ade openness (TOP) which is de ined as he
sum o expo s and impo s o goods and se ices as a sha e o a coun y’s g oss
domes ic p oduc . Elec ici y (ELECTRI) is he pe cen age o he popula ion ha
has access o elec ici y. Finally, g oss ixed domes ic in es men (GDI) and a meas-
u e o poli ical s abili y (Pol_STBLTY) a e also included as con ol a iables.
(1)
LP
i =𝛼+𝜇 +
k
∑
j=
1
𝛽jXji + i+𝜖
i
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The empi ical analysis akes in o accoun di e ences among coun ies and
changes o e ime. Da a om se e al coun ies is used o inc ease he ange o a i-
a ion in he a iables. I is impo an o ake in o accoun coun y-speci ic e ec s,
as coun ies a e likely o sys ema ically be di e en due o di e en ac o s, such as
wea he , in as uc u e, de ini ion o inpu s, p oduc i e e iciencies, cul u al a i udes
and many o he ac o s ha a e di icul o measu e and o obse e di ec ly (Table1).
Econome ic Me hod
This s udy employs a gene alized leas squa e (GLS) me hod and i u he es s he
esul s using a sys em gene alized me hods o momen s (GMM) which is a mo e
obus es ima o and has be e es ima ion p ope ies (A ellano & Bo e , 1995; Blun-
dell & Bond, 1998). The GLS model akes in o accoun he non-sphe ical e o s uc-
u e unde his speci ica ion. The a iables unde conside a ion a e mainly economic
a iables; he e o e, co ela ions may exis be ween eg esso s and e o e ms. When
he e is a ce ain deg ee o co ela ion be ween eg esso s and e o e ms, GLS is he
mos sui able ool o empi ical in es iga ion (see, e.g., Al a ez-He anz e al., 2017).
Fu he mo e, he a ionale o using he sys em GMM as a mo e obus es ima ion
echnique is, i s , ha ou numbe o coun ies is 40 which is g ea e han he numbe
o yea s which equals 16 in he sample (Asongu e al., 2018; Myo ella e al., 2020;
Ncho oung & Asongu, 2022). Second, he sys em GMM me hod con ols o possible
endogenei y p oblems, as he li e a u e has shown ha analyzing he impac o digi al
Table 1 De ini ion o a iables
Va iable name De ini ion
Labo P oduc i i y (LP) GDP pe pe son employed (cons an 2017 PPP $)
Labo P oduc i i y in Manu ac u ing (LPMAN) Value added pe wo ke in he indus ial sec o (con-
s an 2015 US$)
Labo P oduc i i y in Se ices (LPSERVICE) Value added pe wo ke in he se ice sec o (cons an
2015 US$)
Labo P oduc i i y in Manu ac u ing (LPAg i) Value addes pe wo ke in ag icul u e, o es y, and
ishing (cons an 2015 US$)
Digi aliza ion (digindx) Composi e indica o cons uc ed om mobile phone
subsc ip ions pe 100 inhabi an s (Mobsub), ixed
elephone subsc ip ions pe 100 inhabi an s (Fixsub),
pe cen age o indi iduals using he in e ne , and mobile
b oadband subsc ip ions pe 100 inhabi an s (B b_sub).
Poli ical S abili y (Pol_STBLTY) Pe cep ion o he likelihood o poli ical ins abili y and/
o poli ically mo i a ed iolence, including e o ism.
Elec ici y In as uc u e (ELECTRI) Pe cen age o he popula ion wi h access o elec ici y.
Human capi al (HC) Human capi al index, based on yea s o schooling and
e u ns o educa ion.
G oss ixed capi al o ma ion pe capi a (GDI) G oss domes ic in es men , including land imp o e-
men s, machine y, cons uc ion o oads, pe capi a.
T ade Openness (TOP) Sum o expo s and impo s o goods and se ices as a
sha e o a coun y’s g oss domes ic p oduc
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1 3
in eg a ed in o p oduc ion p ocesses and a e an icipa ed o enhance labo p oduc i -
i y, a desi able ou come. Howe e , some pa s o he li e a u e sugges s ha despi e
inc eased in es men in ICT echnologies, p oduc i i y has no shown a posi i e
impac . This s udy seeks o con ibu e o he exis ing body o knowledge by in es i-
ga ing he ex en o which digi aliza ion has acili a ed g ow h in labo p oduc i i y
in Sub-Saha an A ica. U ilizing annual da a pe aining o a ious ac o s in luenc-
ing labo p oduc i i y in Sub-Saha an A ica, an empi ical analysis was ca ied ou
o e a span o 16 yea s om 2006 o 2021. Two dis inc models, he gene alized leas
squa es and a mo e obus sys em gene alized me hod o momen s, we e employed
o add ess po en ial endogenei y issues. We e alua ed he impac o digi aliza ion on
o e all labo p oduc i i y as well as on labo p oduc i i y in he ag icul u e, manu-
ac u ing, and se ice sec o s. Each o hese sec o s exhibi s unique cha ac e is ics,
challenges, and echnological equi emen s depending on he na u e o he asks, skill
equi emen s, and manu ac u ing echniques, po en ially leading o a ying e ec s.
The indings, pa icula ly om he GMM model, indica e ha digi aliza ion may
enhance labo p oduc i i y o he ag icul u e and manu ac u ing sec o s. Howe e , i
has no enhanced labo p oduc i i y o he se ice sec o and o e all labo p oduc i -
i y, as he coe icien s a e nega i e and signi ican . The nega i e coe icien s in labo
p oduc i i y se e as an indica o o he p esence o he p oduc i i y pa adox in Sub-
Saha an A ica. This phenomenon may be a ibu ed o he unde de elopmen o in o -
ma ion and communica ion echnologies in A ica, limi ed in e ne usage, and he
p esence o he digi al di ide. Fu he mo e, ou empi ical indings on a ious ac o s
in luencing labo p oduc i i y, such as poli ical s abili y, elec ici y accessibili y, human
capi al, g oss domes ic in es men , and ade openness, demons a e a a o able e ec .
Al hough some cu ing-edge ad anced digi al echnologies da a we e una ailable
o analysis as a esul o he nascen s age o he ICT sec o in A ica, ou empi ical
indings u ilizing he cu en digi al echnologies ca y signi ican implica ions o pol-
icymake s and go e nmen s. Fi s , i is impe a i e o policymake s and go e nmen s
o p io i ize in es men in obus digi al in as uc u e, including high-speed in e ne
connec i i y o enable widesp ead adop ion ac oss all sec o s o he economy. Second,
equal access o digi al in as uc u e in bo h u al and u ban a eas ac oss SSA econo-
mies should be ensu ed o b idge he digi al di ide and p omo e inclusi e p oduc i -
i y gains. Fo he manu ac u ing and ag icul u al sec o s, which se e as he p ima y
sou ce o employmen o mos o he popula ion in A ica, i is impe a i e o imple-
men addi ional ini ia i es aimed a p omo ing he in eg a ion o digi al echnologies.
I should be also s a ed ha he e a e wo ways ha echnology can a ec p oduc-
i i y: Fi s ly, h ough he new ools, machine ies, and equipmen , and, secondly,
also h ough a ans o ma ion o p oduc ion o ganiza ion. The i s e ec will be lim-
i ed unless he e a e complemen a y o ganiza ional ans o ma ions. We belie e ha
his e ec comes wi h a ime lag and wi h an inc ease in educa ion, in as uc u e,
and human capi al. Finally, in ligh o ou indings, we ecommend go e nmen s
in Sub-Saha an A ica p io i ize good go e nance, poli ical s abili y, anspa ency,
and he es ablishmen o obus egula o y and policy amewo ks. These measu es
will acili a e he seamless inco po a ion o digi al echnologies in a ious sec o s,
ul ima ely boos ing labo p oduc i i y and os e ing sus ainable economic g ow h.
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Appendix Tables7 and 8
Funding Open access unding p o ided by he Scien i ic and Technological Resea ch Council o Tü kiye
(TÜBİTAK).
Da a A ailabili y All da a is a ailable om public sou ces.
Decla a ions
Con lic o In e es s The au ho s decla e no con lic o in e es .
Open Access This a icle is licensed unde a C ea i e Commons A ibu ion 4.0 In e na ional License,
which pe mi s use, sha ing, adap a ion, dis ibu ion and ep oduc ion in any medium o o ma , as long
as you gi e app op ia e c edi o he o iginal au ho (s) and he sou ce, p o ide a link o he C ea i e
Commons licence, and indica e i changes we e made. The images o o he hi d pa y ma e ial in his
a icle a e included in he a icle’s C ea i e Commons licence, unless indica ed o he wise in a c edi line
o he ma e ial. I ma e ial is no included in he a icle’s C ea i e Commons licence and you in ended
use is no pe mi ed by s a u o y egula ion o exceeds he pe mi ed use, you will need o ob ain pe mis-
sion di ec ly om he copy igh holde . To iew a copy o his licence, isi h p://c ea i ecommons.o g/
licenses/by/4.0/.
Table 7 Lis o Sub-Saha an A ican coun ies included in he sample
Angola Co e d’I oi e Libe ia Rwanda
Benin Equa o ial Guinea Madagasca Senegal
Bo swana Eswa in Malawi Sie a Leone
Bu kina Faso Gabon Mali Sou h A ica
Bu undi Gambia Mau i ania Sudan
Came oon Ghana Mau i ius Tanzania
Cen al A ican Republic Guinea Mozambique Togo
Chad Guinea Bissau Namibia Uganda
Como os Kenya Nige Zambia
Congo Leso ho Nige ia Zimbabwe
Table 8 Va iance in la ion
ac o Va iable VIF 1/VIF
Digindx 2.61 0.383
ELECTRI 2.61 0.382
HC 1.98 0.504
Pol_STBLTY 1.72 0.583
LnTOP 1.62 0.618
GDI 1.18 0.847
Mean VIF 1.95
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Publishe ’s No e Sp inge Na u e emains neu al wi h ega d o ju isdic ional claims in published maps
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