Foreign direct investment and poverty in sub-Saharan African countries: The role of host absorptive capacity

A ogundade, Sodiq; Biyase, Mduduzi; Ei a, Hinaunye A icle Fo eign di ec in es men and po e y in sub-Saha an A ican coun ies: The ole o hos abso p i e capaci y Cogen Economics & Finance P o ided in Coope a ion wi h: Taylo & F ancis G oup Sugges ed Ci a ion: A ogundade, Sodiq; Biyase, Mduduzi; Ei a, Hinaunye (2022) : Fo eign di ec in es men and po e y in sub-Saha an A ican coun ies: The ole o hos abso p i e capaci y, Cogen Economics & Finance, ISSN 2332-2039, Taylo & F ancis, Abingdon, Vol. 10, Iss. 1, pp. 1-22, h ps://doi.o g/10.1080/23322039.2022.2078459 This Ve sion is a ailable a : h ps://hdl.handle.ne /10419/303656 S anda d-Nu zungsbedingungen: Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen Zwecken und zum P i a geb auch gespeiche und kopie we den. Sie dü en die Dokumen e nich ü ö en liche ode komme zielle Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich machen, e eiben ode ande wei ig nu zen. 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Submi you a icle o his jou nal A icle iews: 3733 View ela ed a icles View C ossma k da a Ci ing a icles: 5 View ci ing a icles Full Te ms & Condi ions o access and use can be ound a h ps://www. and online.com/ac ion/jou nalIn o ma ion?jou nalCode=oae 20 GENERAL & APPLIED ECONOMICS | RESEARCH ARTICLE Fo eign di ec in es men and po e y in sub-Saha an A ican coun ies: The ole o hos abso p i e capaci y Sodiq A ogundade a *, Biyase Mduduzi a and Hinaunye Ei a a Abs ac : This s udy examines he ole o human capi al and ins i u ional quali y on he impac o o eign di ec in es men (FDI) on po e y in sub-Saha a A ica (SSA). In achie ing his, a balanced panel o 30 SSA coun ies om 1996 o 2018 was explo ed using ixed-e ec ins umen al eg ession, ixed e ec panel h eshold model, and he he e ogenous G ange -causali y es . The e a e h ee main impo - an indings om his empi ical s udy: (1) FDI does no ha e a di ec impac on he incidence and in ensi y o po e y. (2) he impac o FDI is con ingen on he abso p i e capaci y o he hos coun y. The s udy u he e eals ha FDI will alle ia e po e y condi ions i in e ac ed wi h human capi al and ins i u ional quali y a a gi en h eshold. (3) bidi ec ional causali y be ween FDI and po e y. This s udy ecommends ha in addi ion o FDI’s p omo ional policies, go e nmen s o SSA coun ies need o imp o e in es men in human capi al. I is also impo an o SSA coun ies o emba k on public sec o e o ms, as in es men s do no h i e in an en i onmen cha ac e ized by high co up ion o poli ical ins abili y. ABOUT THE AUTHORS Sodiq A ogundade is cu en ly a he inal s age o his PhD p og amme a he Uni e si y o Johannesbu g, Sou h A ica. He has mo e han six yea s (6) o wo k expe ience in esea ch and consul ing. He cu en ly wo ks as a esea ch associa e a he Sou h A ican Resea ch Chai s Ini ia i e (SARChI) and as an assis an lec u e in he School o Economics, Uni e si y o Johannesbu g. His a ea o specialisa ion includes de elopmen inance, in e na ional ade, and applied econome ics. Biyase Mduduzi is a di ec o o he Economic De elopmen and Well-being Resea ch G oup (EDWRG) and a senio lec u e a he School o Economics, Uni e si y o Johannesbu g. He is a esea che specializing in he ield o de elop- men economics: explo ing he emi ance beha iou , po e y, unemploymen , FDI, inequali y and gende - ela ed opics. Hinaunye Ei a is a P o esso and Head o Academics a he School o Economics, Uni e si y o Johannesbu g. He is a Na ional Resea ch Founda ion (NRF) a ed esea che . His esea ch a eas a e mac oeconomic modelling, applied econome ics, inancial ma ke s, in e - na ional ade and inance. PUBLIC INTEREST STATEMENT The con o e sies ha ail whe he FDI’s impac is condi ional on ce ain in e media ing a iables ha e become a ecu ing discou se in he FDI- po e y li e a u e. While he quali y o ins i u ions has p ominen ly ea u ed as playing a i al ole, he le el o human capi al has also been high- ligh ed as a good candida e. This s udy examines he ole o hos abso p i e capaci y in he FDI- po e y nexus. The empi ical indings sugges ha FDI does no di ec ly impac po e y, and he impac is condi ional on ce ain in e mi en a i- ables such as human capi al and ins i u ional quali y. This implies ha he mo e SSA coun ies imp o e hei economies, he mo e hey eap he bene i o FDI in e ms o echnological spillo e s, job c ea ion, and po e y educ ion. In a ac ing a signi ican amoun o FDI capable o educing he in ensi y and incidence o po e y, his s udy ecommends ha imp o ing he in es men cli- ma e o SSA coun ies should no be compen- sa ed o he FDI p omo ional policies, as in es men p omo ional measu es wi hou a sui able enabling en i onmen would be coun e p oduc i e. A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 1 o 22 Recei ed: 05 Feb ua y 2021 Accep ed: 11 May 2022 *Co esponding au ho : Sodiq A ogundade, School o Economics, Uni e si y o Johannesbu g College o Business and Economics, Sou h A ica, E-mail: [email p o ec ed] Re iewing edi o : Ca oline Ellio , Economics, Uni e si y o Wa wick Facul y o Social Sciences, Uni ed Kingdom Addi ional in o ma ion is a ailable a he end o he a icle © 2022 The Au ho (s). This open access a icle is dis ibu ed unde a C ea i e Commons A ibu ion (CC-BY) 4.0 license. Subjec s: Economics; Mac oeconomics; Econome ics; In e na ional Economics; De elopmen Economics Keywo ds: Po e y; Fo eign di ec in es men ; Abso p i e capaci y; Ins umen al eg ession; Fixed-e ec panel h eshold model; he e ogenous G ange -causali y es ; sub- Saha an A ican coun ies JEL classi ica ion: F23; I30; E24; E02 1. In oduc ion Fo eign di ec in es men (FDI) has become one o he mos impo an ex e nal sou ces o inance in de eloping coun ies. This is because o i s po en ial in ans e ing knowledge and echnology, enhancing compe i ion, boos ing en ep eneu ship and p oduc i i y, and inc easing he e enue o go e nmen h ough axes paid by o eign in es o s (Uni ed Na ions, 2003). The impo ance o his sou ce o ex e nal inance has igge ed many de eloping economies, especially in A ica, o adop FDI- iendly policies. In 2017, abou 65 economies in he wo ld adop ed a leas 126 in es men policy measu es and e o ms, some o which include he es ablishmen o new special economic zones (SEZs), simpli ying adminis a i e in es men p ocedu es, p i a iza ion o s a e-owned asse s, and libe aliza ion o domes ic ma ke s (see UNCTAD, 2018 o a de ailed accoun o hese measu es). This has emendously imp o ed he low o FDI o SSA, om an a e age o $36.03 billion in 1990 o $610.54 billion in 2018 (UNCTAD, 2019). Howe e , despi e an app eciable inc ease in FDI inwa d s ock, po e y condi ions in he egion con inue o de e io a e. As shown in Figu e 1, he numbe o ex emely poo popula ion ose om 278 million in 1990 o 437 million in 2018 (Wo ld Bank, 2018). The Wo ld Bank also p edic ed ha by 2030, app oxima ely 9 ou o 10 ex emely poo people would li e in SSA. The ques ion his s udy seeks o add ess is, why has he ise in he low o FDI no been able o alle ia e po e y condi ions in he egion, and can i be ha hos coun ies do no ha e enough abso p i e capaci y o exploi he bene i FDI can o e ? Howe e , empi ical s udies aimed a in es iga ing he bene i s o FDI in educing po e y ha e epo ed ei he a nega i e e ec (Bha adwaj, 2014; Bilal Khan e al., 2019; Fowowe & Shuaibu, 2014; Laz eg & Zoua i, 2018; Souma é, 2015) o a posi i e e ec (Ane o e al., 2020; A abya , 2017; Dh i i e al., 2020; Gohou & Souma e, 2012; Rye, 2016). The eason why he e a e con lic ing esul s on he impac o FDI on po e y may be because FDI’s in luence may no be di ec . I may ins ead be con ingen on he condi ion o local econo- mies. Schola s like Meye and Sinani (2009) ha e a gued ha he le el o de elopmen o hos 0 200 400 600 800 1000 1200 1400 1600 1800 2000 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 Million People in Ex eme Po e y 'Million SSA Sou h Asia MENA ROW La in Ame ica & Ca ibean Eu ope and Cen al Asia Eas Asia and Paci ic 278 Million 416 Million Figu e 1. Po e y in sub- Saha an A ica. Sou ce: Wo ld Bank, 2018. A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 2 o 22 coun y plays a c ucial ole in de e mining he ex en o which he bene i s o FDI a e ha nessed. The le els o human capi al and ins i u ional amewo k a e belie ed o be he key domes ic ac o s ha will condi ion he impac o FDI. Fo example, he empi ical s udies by Yebuoa (2020), Jude and Le ieuge (2017), and Agbloyo e al. (2016) a gue ha a speci ic op imal ins i u ional de elopmen is a p econdi ion o he g ow h-enhancing e ec o FDI. A he same ime, s udies like Bonga-Bonga & Phume, 2017), Li and Liu (2005), and Bloms om e al., 1993) ha e es ima ed a ce ain h eshold o human capi al o FDI o enhance g ow h. Since mos o he a o emen ioned s udies a gue ha wha is good o g ow h is also good o he poo , and since economic g ow h may no necessa ily esul in po e y educ ion, i is essen ial we examine he ole o human capi al and ins i u ional quali y on he nexus be ween FDI and po e y educ ion. Fu he mo e, he s udy es ima es he abso p i e capaci y h eshold o FDI o alle ia e po e y (numbe o poo people and he magni ude o po e y). The s udy also assesses whe he he e a e egional di e ences on he impac o FDI on po e y in SSA. In addi ion o his, he s udy de e mined he di ec ion o causali y be ween FDI and po e y. Conduc ing his s udy o A ica is c i ical o he ollowing easons, (i) he egion is plagued wi h poo wel a e condi ions and a guably he leas in he wo ld (ii) he p e alence o lawed ins i u ional amewo k and low human capi al is an impedimen o FDI spillo e s in he egion. Thus, a ac ing mul ina ional co po a ions o in es unde hese ci cums ances may no yield he an icipa ed esul s, as in es - men h i es in a compe i i e en i onmen . The au ho is no awa e o any li e a u e ha has speci ically examined he impac o local economic condi ions on he FDI-po e y nexus, especially wi hin he con ex o A ica. The closes a emp is ha o Lehne e al. (2013) and Pé ez-Segu a, 2014). These s udies we e conduc ed o de eloping coun ies, excluding many A ican coun ies. Fu he mo e, hese s udies adop a linea in e ac ion model o cap u e he ole o ins i u ion on he FDI-wel a e nexus. Since he linea in e ac ion imposes es ic ion ha he impac o FDI a ies mono onically wi h he condi ioning a iables, he ixed-e ec panel h eshold model, which cap u es he ela ionship be ween FDI, hos abso p i e capaci y, and po e y in SSA coun ies, is adop ed. This s udy examines he ole o human capi al and ins i u ional quali y on he FDI-po e y nexus. The empi ical indings sugges ha FDI does no di ec ly impac po e y, and he impac is condi ional on ce ain in e mi en a iables such as human capi al and ins i u ional quali y. This implies ha he mo e SSA coun ies imp o e hei economies, he mo e hey eap he bene i o FDI in e ms o echnological spillo e s, job c ea ion, and po e y educ ion. Fu he empi ical esul s sugges a bidi ec ional causali y be ween FDI and po e y. The es o his pape is s uc u ed as ollows: Sec ion 1.1 p o ides s ylized ac s on FDI issues in he egion. Sec ion 2 b ie ly discusses he ela ed li e a u e on FDI and po e y. The discussions on he me hodology and he es ima ion echniques a e discussed in sec ion 3. Sec ion 4 p esen s he empi ical es ima ion, while sec ion 5 concludes and p o ides c i ical policy implica ions. 1.1. S ylized ac Despi e he signi ican imp o emen in FDI low in SSA in ecen decades, he egion emains la gely ma ginalized in e ms o inancial globaliza ion. One sign o his is ha he egion cap u ed only 2.36 % o global o eign di ec in es men in 2018 (S a is ics, 2019). In inc easing he low o FDI, many SSA go e nmen s ha e adop ed a se ies o e o ms and policies o a ac FDI, as i is conside ed by policymake s o be e y c i ical in closing he sa ings gap. 1 Howe e , he low o FDI o he egion has been une enly dis ibu ed among a ew esou ce-in ensi e coun ies. These coun ies ha e been able o a ac a signi ican p opo ion o FDI in lows a he expense o coun ies wi h limi ed esou ces. As shown in Table 1, in 2018, he op 10 FDI ecipien s ecei ed 72.39 % o he o al FDI in lows o SSA. Fou A ican coun ies, namely: Sou h A ica, Nige ia, Mozambique, and Ghana, accoun ed o 50 % o he o al FDI in lows o he egion. A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 3 o 22 Figu e 2 shows a sca e plo o he po e y a e 2 and ins i u ion quali y. 3 I is e iden ha coun ies (Cen al A ica, Bu undi, Congo Democ a ic Republic, Nige ia, and Mozambique) wi h ela i ely high po e y a es end o ha e poo ins i u ional quali y. Howe e , coun ies (Mau i ius, Sou h A ica, and Ghana) wi h s ong ins i u ional quali y a e associa ed wi h a ela i ely low po e y a e. The le el o ins i u ional quali y is s ongly co ela ed wi h he pe o mance o economies, i.e., coun ies wi h sound ins i u ions like e icien and good go e n- ance, low co up ion, ule o law, and p ope y igh s, end o enhance he p ocess o echnology spillo e s o local i ms. Howe e , coun ies wi h poo ins i u ions may deny domes ic i ms om aking ad an age o MNCs’ knowledge spillo e s (Agbloyo e al., 2016; B ahim & Rachdi, 2014). The e o e, i is an icipa ed ha he impac o FDI on po e y educ ion would di e ac oss coun ies and egions wi h he e ogeneous le els o ins i u ional quali y. Figu e 3 shows a sca e plo o po e y a e 4 and human capi al. 5 Coun ies (Mozambique, Mali, Nige , and Bu kina Faso) associa ed wi h de icien human capi al de elopmen ha e a ela i ely high po e y a e. While coun ies (Ghana, Mau i ius, and Sou h A ica) wi h high human capi al de elopmen ha e a low le el o po e y. Empi ical e idence has also been documen ed on he impo ance o human capi al de elopmen in he economy (Obialo , 2017; Ogunda i & Awokuse, 2018). Gi en he eme ging conce ns on gene al de elopmen issues in SSA, a as idious empi ical s udy ha examines he channels o he FDI-po e y nexus is impo an . Table 1. Top 10 FDI ecipien s in SSA, 2010, 2015, and 2018 2010 % 2015 % 2018 % Sou h A ica Nige ia Angola Libe ia Ghana Tanzania Eq. Guinea Condo DR Congo Zambia 43.54 14.63 7.87 2.47 2.44 2.35 2.28 2.27 2.25 1.80 Sou h A ica Nige ia Angola Mozambique Ghana Congo DR Tanzania Zambia Congo Eq. Guinea 24.59 17.41 6.27 5.68 5.12 3.88 3.45 3.20 2.96 2.59 Sou h A ica Nige ia Mozambique Ghana Congo Congo DR Angola E hiopia Tanzania Zambia 21.10 16.33 6.66 5.92 4.19 3.93 3.88 3.64 3.39 3.35 To al 81.91 75.13 72.39 Sou ce: Au ho s’ compu a ion om he UNCTAD da abase (2019) Figu e 2. Po e y and ins i u- ional quali y in SSA. Sou ce: Au ho s’ compu a ion based on Wo ld Go e nance Indica o and Wo ld Bank Po cal da abase (2019). No e: The a e age o bo h ins i u- ional quali y and headcoun index we e calcula ed o each coun y in he las i e yea s. A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 4 o 22 2. Li e a u e e iew The heo e ical nexus be ween FDI and po e y can be explained wi hin he ounda ion o neo- classical o endogenous g ow h heo y. The heo y a gues ha an inc ease in p oduc i i y and economic g ow h will alle ia e po e y and wel a e. The p oponen s o his iew posi ha a ise in na ional income ends o bene i he mos impo e ished popula ion, especially in coun ies wi h low-income inequali y (Koopmans, 1965; Lucas, 1988; Rome , 1994; Solow, 1956). In addi ion o he adi ional g ow h heo ies, Meye (2004) a gues ha FDI’s impac on po e y can be di ided in o wo ca ego ies, namely e ical and ho izon al. The ho izon al spillo e e ec occu s om he echnological spillo e om o eign i ms o local i ms (Fa ole & Winkle , 2012). Knowledge spil- lo e akes place h ough he mo emen o labou and domes ic i ms ying o imi a e he p oduc inno a ion o o eign i ms (Gö g & G eenaway, 2004; Jian-Ye Wang & Magnus, 1992; Meye , 2004). The ho izon al spillo e also occu s h ough he employmen o local labou and he aining p o ided o he labou e s (Cal o & He nandez, 2006; Meye , 2004). This imp o es he le el o human capi al and he wel a e o he employees in he hos coun ies. The imp o emen in human capi al has wo impac s on he wel a e o labou . Fi s ly, i imp o es he quali y o human capi al o he local labou . Secondly, he labou s a e paid compe i i e wages (Bo ensz ein e al., 1998). The e ical spillo e , acco ding o Meye (2004), esul s om he in e ac ion be ween he o eign i ms and economic agen s in he hos coun y. This can u he be di ided in o o wa d and backwa d linkages (Gö g & G eenaway, 2004; Liu e al., 2009; Sumne , 2005). The backwa d linkage in ol es sou cing aw/in e media e goods om he local i ms. This inc eases he demand o in e media e goods and consequen ly expands local i ms’ p oduc ion (Gö g & G eenaway, 2004). The o wa d linkage in ol es he g ow h o he local i ms ha use he ou pu om he mul i- na ional co po a ions (MNCs). 2.1. Empi ical e iew on FDI and po e y Se e al a emp s ha e been made o examine he impac o FDI on po e y. Howe e , he e a e con lic ing esul s on he impac o FDI. Some s udies suppo he FDI-po e y educ ion hypo h- esis, while o he s a gue ha FDI inc eases po e y. Fo ins ance, Laz eg and Zoua i (2018) assess he ela ionship be ween FDI and po e y educ ion in Tunisia om 1985 o 2015. Using ully modi ied o dina y leas squa es (FMOLS), he s udy disco e s ha o eign di ec in es men signi ican ly impac s po e y alle ia ion. Simila ly, Bha adwaj (2014) examine he e ec o FDI on po e y in a sample o 35 de eloping coun ies om 1990 o 2004; he s udy concludes ha FDI is bene icial o po e y educ ion. Souma é (2015) in es iga es he impac o FDI on he wel a e o No he n A ican coun ies om he pe iod o 1900- o 2011. The s udy explo ed Figu e 3. Po e y and human capi al de elopmen in SSA. Sou ce: Au ho s’ compu a ion based on Wo ld Bank Po cal Da abase and Penn Wo ld Table PWT (2019) No e: The a e age o bo h human capi al and headcoun index we e calcu- la ed o each coun y in he las i e yea s. A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 5 o 22 a dynamic panel eg ession and concluded ha FDI is bene icial o wel a e imp o emen in he egion. In addi ion o his, Fowowe and Shuaibu (2014) used gene alized me hods o momen s (GMM) o in es iga e he impac o FDI on he poo . The s udy also con i ms he bene icial impac o FDI on he poo . U ama (2015) examined he impac o FDI on po e y among he ASEAN coun ies. Using a spa ial panel da a model om 1995 o 2011, he s udy con i ms ha FDI alle ia es po e y in he egion. The indings p o ide simila esul s e en when spa ial in e ac- ions a e conside ed. Bilal Khan e al. (2019) also examined he ela ionship be ween FDI and po e y in Pakis an using he ARDL model. The esul s sugges ha FDI con ibu es o po e y educ ion in bo h he sho - un and long- un. Joshua e al. (2021) examine he impac o FDI and ex e nal deb on sus ainable g ow h in A ica. Using he au o eg essi e dis ibu ed lag (ARDL), he empi ical indings o he s udy indica e ha FDI and ex e nal deb a e c ucial in achie ing economic expansion in he egion. Howe e , apa om s udies ha suppo he FDI-po e y educ ion hypo hesis, a ew s udies ha e ound ha FDI does no signi ican ly in luence po e y. S a ing wi h he s udy o Rye (2016), who in es iga ed he e ec o o eign di ec in es men on po e y using a sample o 134 coun ies in he wo ld. The s udy explo es ins umen al eg ession, and i was disco e ed ha FDI does no signi ican ly in luence po e y. Simila ly, A abya (2017) examines he impac o FDI on po e y educ ion in de eloping coun ies using a panel e o co ec ion model. The conclusion om his s udy sugges s ha FDI does no signi ican ly in luence po e y. Gohou and Souma e (2012) used wo-s age leas squa es eg essions o assess he impac o FDI on po e y. Using a sample o 52 coun ies in A ica be ween 1990 o 2007, he s udy ound ha FDI’s impac on po e y is insigni ican . Simila ly, Quinonez e al. (2018) examine he impac o FDI on po e y incidence in La in Ame ica o a panel o 13 economies. The s udy concludes ha FDI does no signi ican ly educe po e y in La in Ame ica. Ane o e al., 2020) used he Feasible Gene alized Leas Squa e (FGLS) echnique o examine he impac o FDI, ade, and o eign aid on po e y in SSA. The esul s sugges ha FDI and o eign aids inc ease po e y and ha he le el o FDI equi ed o alle ia e po e y has no been a ained. Some s udies ha e also a emp ed o examine he causal ela ionship be ween FDI and po e y. Fo ins ance, Magombeyi and Odhiambo (2017) explo e he causal ela ionship be ween FDI and po e y in Sou h A ica using ime se ies analysis. Analysis om he ARDL model indica es a unidi ec ional causali y om po e y educ ion o FDI. Howe e , Dh i i e al. (2020) ound a bi- di ec ional causali y be ween po e y and FDI o a sample o de eloping coun ies. The con lic ing esul s on he impac o FDI could be because o he di e ences in geog aphical con ex , ype and na u e o FDI, and he es ima ion echniques used. I may also be because FDI’s impac is condi ional on he abso p i e capaci y o he hos coun y. S udies like Dada and Abanikanda (2021), Yebuoa (2020), Jude and Le ieuge (2017), and Agbloyo e al. (2016) empha- size he ole o ins i u ional quali y on FDI-g ow h nexus, while s udies like Bonga-Bonga & Phume, 2017), Li and Liu (2005), and Bloms om e al., 1993) empi ically assess he ole o human capi al on he impac o FDI on g ow h. Howe e , since economic g ow h does no necessa ily lead o po e y educ ion, he ole o human capi al and ins i u ional quali y on he nexus be ween FDI and po e y educ ion mus be examined. Un o una ely, o he bes o he au ho s’ knowledge, he e is no li e a u e on he ole o ins i u ional quali y and human capi al on he FDI-po e y nexus wi hin he con ex o A ica. O he s udies like Lehne e al. (2013) and Pé ez-Segu a, 2014) empi ically assess he ole o ins i u ional quali y on he nexus be ween FDI and human de elop- men . Howe e , hese s udies use a linea in e ac ion model. Since linea in e ac ion es ic s ha he impac o FDI a ies mono onically wi h he condi ioning a iables, he panel h eshold model, which cap u es he ela ionship be ween FDI, hos abso p i e capaci y, and po e y, is adop ed. This s udy con ibu es o he li e a u e by iden i ying he impac o human capi al and ins i u- ional quali y on he FDI-po e y nexus in SSA, de e mining he abso p i e capaci y h eshold o A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 6 o 22 FDI o be e ec i e in alle ia ing po e y, de e mining he di ec ion o causali y be ween FDI and po e y, and (4) assessing whe he he e is a egional di e ence on he impac o FDI. 3. Da a and me hodology 3.1. Da a This s udy explo es a balanced panel da ase o 30 coun ies 6 (see Appendix 1 o ull de ails o he coun ies) in SSA, wi h annual da a o e he pe iod o 1996 o 2018. The choice o coun ies and pe iod we e con ingen on da a a ailabili y. Fu he mo e, he egional analysis was conduc ed o examine i he e a e egional di e ences in he impac o FDI. In he analysis o his s udy, po e y is measu ed using wo indica o s, and his allows us o es ablish he obus ness o ou empi ical esul s. P ecisely, we ollow Gnangnon (2022) and Aga wal e al. (2017) app oach by using he headcoun a io, which measu es he incidence o po e y and he po e y gap index, which measu es he in ensi y o po e y. Bo h he headcoun and po e y gap indexes a e measu ed using he in e na ional po e y line o $1.90 pe day. This s udy ollows Nunnenkamp (2004) and Fo d e al., 2008) by measu ing FDI as inwa d FDI s ock as a pe cen age o GDP. Using FDI s ock also educes he p oblem o endogenei y biases ha may be associa ed wi h he FDI-wel a e nexus (Nunnenkamp, 2004). Two al e na i e p oxy o human capi al we e used o es ablish he obus ness o ou empi ical esul s. P ecisely, we imi a e Le ine and Renel (1992) and Mankiw e al. (1992) by using e ia y en olmen a es, which cap u e in es men in human capi al. The second measu e o human capi al used is he modi ied Ba o and Lee (2013) human capi al index, which is an indica o o educa ional a ainmen . Li and Liu (2005) and Miao Wang and Sunny Wong (2009), among o he s, ha e used he same a iable as a p oxy o human capi al. This s udy ollows Okada (2013) and Ahmad e al. (2015) a gumen s ha agg ega e measu es o ins i u ional quali y indica o s may ail o p ope ly cap u e he e ec o ins i u ions. Hence con ol o co up ion and poli ical s abili y index we e used as p oxies o ins i u ional quali y. These indexes ange om—2.5 (weak) o 2.5 (s ong). We ollow Kaulihowa (2017) by using he g ow h a e o GDP pe capi a as a p oxy o economic g ow h and he o al ac i e labou o ce as a p oxy o labou . Table 2. Summa y s a is ics o he a iables Va iables Obse a ions Mean Min. Max. Sign Da a Sou ces FDI Inwa d S ock (% o GDP) 690 43.96 0.468 1,039 ± UNCTAD Economic G ow h 685 1.782 −36.56 21.03 - W/B, WDI Headcoun Ra io (% o Pop.) 690 47.5 0.3 96.4 N/A W/B, Po calne Po e y Gap (% o Pop.) 690 20.3 0.1 66.0 N/A W/B, Po calne Labou Fo ce ’000 690 8194 368 60,700 - W/B, WDI Human Capi al Index 661 1.677 1.053 2.809 - PWT, 9.1 Con ol o Co up ion Index 690 −0.634 −1.723 0.809 - WGI, 2019 Poli ical S abili y Index 690 −0.589 −2.845 1.200 - WGI,2019 Te ia y En olmen Ra e 690 6.587 0.321 42.34 - WGI, 2019 NB: Uni ed Na ions Con e ence on T ade and De elopmen (UNCTAD), Wo ld Bank Wo ld De elopmen Indica o (W/B, WDI), Penn Wo ld Table Ve sion (PWT), Wo ld Go e nance Indica o (WGI) A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 7 o 22 Table 5. Fixed-e ec h eshold es ima es o FDI and po e y in SSA (1) (2) (3) (4) (7) (8) (9) (10) VARIABLES HC PG HC PG HC PG HC PG Th eshold Va iable Con ol o co up ion Poli ical s abili y Human capi al index Te ia y en olmen a e Th eshold (^ γ) −1.43 −1.45 −0.94 −1.31 1.74 1.27 2.61 5.82 CI [−1.46, −1.42] [−1.49, −1.45] [−1.09 − 0.92] [2.48, −2.30] [1.73, 1.75] [1.24, 1.27] [2.47, 2.64] [5.18, 5.84] ^ β1ABS �^ γð Þ 3.56e-05 0.000121* 9.14e-05 0.000220*** −0.000227** −0.000539*** −0.000991*** 0.000211*** (9.64e-05) (6.81e-05) (9.54e-05) (7.26e-05) (9.58e-05) (0.000110) (0.000269) (6.35e-05) −0.000386*** −0.000264*** −0.000401*** −0.000294*** −0.000865*** −0.000122* −0.000197** −0.000110 (0.000106) (7.50e-05) (0.000106) (8.09e-05) (0.000155) (6.99e-05) (8.86e-05) (8.19e-05) Single h eshold e ec es a 34.60 58.15** 53.13* 51.94** 58.92* 38.62 20.15 58.40* Co a ia es Labou −0.120*** −0.0765*** −0.118*** −0.0813*** −0.118*** −0.0805*** −0.0610*** −0.0333*** (0.0130) (0.00922) (0.0129) (0.00921) (0.0130) (0.00930) (0.0134) (0.00958) Con ol o co up ion −0.00847 −0.00823 −0.0217 −0.0240** −0.0285* −0.0206* (0.0164) (0.0116) (0.0161) (0.0115) (0.0147) (0.0106) Human capi al 0.00648 0.00180 0.00393 0.00112 0.0155* −0.0159** (0.00894) (0.00632) (0.00883) (0.00636) (0.00905) (0.00697) Economic g ow h −0.00133* −0.000911 −0.00111 −0.000930* −0.00128 −0.000743 −0.00105 −0.000870* (0.000792) (0.000560) (0.000781) (0.000563) (0.000789) (0.000566) (0.000721) (0.000519) Poli ical s abili y 0.0229*** −0.00209 (0.00768) (0.00530) Te ia y en olmen a e −0.0123*** −0.00671*** (0.000955) (0.000733) Cons an 2.297*** 1.369*** 2.290*** 1.450*** 2.260*** 1.437*** 1.462*** 0.739*** (0.200) (0.142) (0.198) (0.141) (0.201) (0.143) (0.203) (0.145) Obse a ions 690 690 690 690 690 690 690 690 R-squa ed 0.189 0.199 0.208 0.188 0.194 0.178 0.325 0.311 Numbe o coun ies 30 30 30 30 30 30 30 30 No es: Each column shows he coe icien om a sepa a e eg ession and s anda d e o s a e in pa en heses. The egime-dependen ma ginal e ec s o FDI on po e y a e deno ed by ^ β1 and ^ β2 *** deno es signi icance a 1 %, ** a 5 % and * a 10%. The null hypo hesis o he h eshold e ec es is ha he e is no h eshold e ec in equa ion (5). HC = headcoun po e y, PG = po e y gap. a:The single h eshold e ec es indica es he p esence o h eshold e ec in he model wi h he excep ion o column 8 and 9. A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 14 o 22 Table 6 indica e bidi ec ional causali y be ween he incidence o po e y. This esul is consis- en wi h he empi ical ou come o Dh i i e al. (2020), who ound a bi-di ec ional causali y be ween po e y and FDI in de eloping coun ies. Simila empi ical ou come was ob ained o po e y incidence and human capi al, ins i u ional quali y, and human capi al. Howe e , a unidi ec ional causali y is eco ded be ween FDI and ins i u ional quali y. In a ac - ing a signi ican amoun o FDI, his s udy sugges s ha SSA coun ies should implemen “open doo ” policy o inc ease he appe i e o o eign in es o s. Hence, a coun y willing o bene i om he ad an ages o FDI and ul ima ely po e y educ ion should c ea e a conduci e en i onmen by in es ing in human capi al and imp o ing ins i u ional quali y. 5.1. Regional analysis A e examining he impac o FDI on po e y in SSA as a g oup, his sec ion u he examines whe he he e is a egional di e ence in e ms o he impac o FDI. This is o unco e whe he egional cha ac e is ics play a ole in he u iliza ion o FDI spillo e , and o also de e mine which egion FDI could ha e he mos impac . This s udy u he seeks o know i he esul s o analysis in ol ing he in e connec ions be ween FDI and hos abso p i e capaci y a e sensi i e o egional ca ego iza ion. The po e y indica o used is he po e y headcoun a io since he policy ac ion among de elopmen expe s will be o educe he o al numbe o he poo . We also used only he human capi al index and con ol o co up- ion index as h eshold a iables. As shown in Table 7, i is in e es ing o no e ha he di ec impac o FDI on po e y di e s ac oss he sub- egion. The impac o FDI on po e y in Sou he n, Eas e n and Cen al A ica is nega i e and s a is ically signi ican . Howe e , he coe icien o FDI on po e y in Wes A ica is posi i e and signi ican . The ac ha Cen al and Eas e n A ica a e poo e han Wes e n and Sou he n A ica means FDI educes po e y mo e in poo e coun ies han educ ion. This has also been alida ed o Eas e n Eu ope (Buch e al., 2001). This s udy u he disco e s ha he in e ac ion o FDI wi h ei he ins i u ional quali y o human capi al has a nega i e and signi ican impac on po e y in Wes e n and Sou he n A ica. Howe e , he impac is no signi ican in Eas e n and Cen al A ica. We belie e his may be due o he low in low o FDI and abso p i e capaci y in hese egions. The o e all indings o he egional analysis sugges ha egional cha ac e is ics di e in e ms o he impac o FDI in alle ia ing po e y. This inding is consis en wi h he a gumen and empi ical ou comes o Gohou and Souma e (2012) ha egional di e ences ma e on he spillo e e ec o FDI in po e y educ ion in A ica. Table 6. Dumi escu-Hu lin (2012) he e ogenous g ange -causali y esul s (1) (2) (3) (4) Va iables HC FDI INST HUC HC - 4.8932*** 3.3313*** 5.7616*** (2.6645) (2.1707) (2.9390) FDI 23.0559*** - 1.4420 3.7216*** (8.4060) (1.5735) (2.2941) INST 11.1632*** 4.0978*** - 4.2920*** (4.6465) (2.4130) (2.4744) HUC 19.8046*** 7.1163*** 1.9531*** - (7.3782) (3.3672) (1.7351) No e: The es s a is ics is he w-s a . z-s a is in pa en heses, *** deno es signi icance a 1 %, ** a 5 % and * a 10%. lag leng h o 2 was used. HC = headcoun po e y, INST = ins i u ional quali y, HUC = human capi al, FDI = o eign di ec in es men A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 15 o 22 Table 7. Regional analysis on he impac o FDI on po e y in sub-Saha a A ica Wes A ica Sou he n A ica Eas e n A ica Cen al A ica Va iables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) FDI 0.0004** -0.0004*** 0.0036*** -0.0006** -0.0013* 0.0042** -0.0001*** -0.0016 0.0005 -0.0003** -0.0010 0.0020 (0.0002) (0.0001) (0.0011) (0.0003) (0.0007) (0.0021) (0.00003) (0.0034) (0.0005) (0.0001) (0.0012) (0.0036) Po e y( −1) 0.855*** 0.959*** 0.892*** 0.891*** 0.896*** 0.918*** 0.873*** 0.554 0.986*** 0.8593*** 0.9716*** 0.9873*** (0.0474) (0.0341) (0.0486) (0.0324) (0.0508) (0.0411) (0.0206) (0.907) (0.0655) (0.0461) (0.0558) (0.1008) Labou Fo ce -0.119** -0.00765 -0.0894 -0.133*** -0.0662* -0.0564* -0.0148 0.00557 0.0529** -0.1198** -0.0127 0.0190 (0.0531) (0.0404) (0.0565) (0.0336) (0.0391) (0.0327) (0.0153) (0.131) (0.0226) (0.0463) (0.0619) (0.1179) COC -0.0149 -0.0039 -0.0144 -0.0430*** 0.0261 -0.0578*** -0.0069 0.0113 0.0036 -0.0014 0.0243 -0.0006 (0.0127) (0.0107) (0.0126) (0.0131) (0.0451) (0.0194) (0.0043) (0.0331) (0.0064) (0.0160) (0.0333) (0.0182) GDP Pe Capi a -0.0032*** -0.0024*** -0.0033*** -0.0030*** -0.0031*** -0.0029*** -0.0009*** -0.0015* -0.0018*** -0.0036*** -0.0040*** -0.0040*** (0.0005) (0.0003) (0.0005) (0.0003) (0.0005) (0.0005) (0.0002) (0.0008) (0.0004) (0.0003) (0.0003) (0.0003) Human Capi al 0.0664 0.0285 0.185** 0.0324* 0.0587* 0.0974*** -0.0206 -0.0881 -0.0590* 0.3755*** -0.0575 -0.2502 (0.0579) (0.0437) (0.0751) (0.0179) (0.0323) (0.0332) (0.0191) (0.0560) (0.0339) (0.0928) (0.1299) (0.3508) FDI*COC -0.0002*** -0.0016* -0.0016 -0.0006 (0.0001) (0.0009) (0.0036) (0.0010) FDI*HUC -0.0023*** -0.0018** -0.0005 -0.0010 (0.0007) (0.0009) (0.0004) (0.0018) Cons an 1.721** 0.0913 1.108 2.007*** 0.957* 0.649 0.326 0.313 0.313 1.2795** 0.3493 0.1460 (0.749) (0.565) (0.787) (0.497) (0.582) (0.526) (0.218) (2.537) (2.537) (0.5923) (0.7706) (1.3051) P ob>χ^2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 R-Squa ed 0.335 0.967 0.587 0.021 0.897 0.855 0.995 0.957 0.946 0.423 0.974 0.995 Exogenei y o FDI 0.0017 0.0760 0.0033 0.0120 0.0695 0.0155 0.3973 0.3962 0.0642 0.1357 0.2234 0.1535 Ins umen ele ance 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Obse a ions 183 196 170 96 60 60 133 133 70 80 60 56 Numbe o Coun ies 13 13 13 6 6 6 7 7 7 4 4 4 No es: Each column shows he coe icien om a sepa a e eg ession and s anda d e o s a e in pa en heses o each o he egions. *** deno es signi icance a 1 %, ** a 5 % and * a 10%. All eg essions a e es ima ed using ixed-e ec ins umen al eg ession es ima o . Lag o FDI was used as ins umen s in he es ima ion o his s udy. Exogenei y es o FDI is he p- alue o Du bin– Hausman–Wu F- es , his es shows ha FDI is endogenous in all he es ima ions, excep column (7,8,10,11, and 12). Ins umen ele ance is he p obabili y alue o he F- es in he educed model. FDI*HUC, FDI*COC ep esen in e ac ion o FDI wi h human capi al index and con ol o co up ion index, espec i ely. A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 16 o 22 6. Summa y and conclusion This s udy in es iga es whe he an inc ease in human capi al and ins i u ional quali y inc eases he e icacy o FDI in educing po e y in SSA, and i he impac o FDI on po e y akes e ec a e human capi al and ins i u ional quali y exceed a ce ain h eshold. In achie ing his, he s udy employs h ee di e en models: (1) he ixed e ec ins umen al eg ession model, which is o add ess he p oblem o endogenei y, as well as emo ing unobse ed ixed e ec in he model, (2) ixed-e ec panel h eshold model, and (3) he Dumi escu and Hu lin (2012) causali y es o de e mine he di ec ion o causali y be ween FDI and po e y. The empi ical indings om his s udy a e as ollows: (1) FDI does no ha e a di ec impac on he incidence and in ensi y o po e y, since he baseline esul s sugges a posi i e ela ionship be ween FDI and po e y, (2) The impac o FDI on he po e y measu es is condi ional on in e mi en a iables such as ins i u ional quali y and human capi al, and hos coun ies mus main ain an annual h eshold alue o −1.4 o con ol o co up ion index and −0.94 o poli ical s abili y index. The esul s u he sugges ha SSA coun ies mus main ain an es ima ed alue o 1.2 o human capi al index and 5.82% o e ia y en olmen a e. This implies ha coun ies wi h a highe le el o abso p i e capaci y s and o bene i om inc eased FDI lows, whe eas coun ies wi h low abso p i e capaci y end o be hu om inc eased FDI in lows. Analysis om he egional classi ica ion sugges s ha FDI’s impac in alle ia ing po e y di e s ac oss he egions. Hence speci ic egional policies a e needed o comba po e y, and (3) he g ange causali y es indica es a bidi ec ional causali y be ween FDI and po e y. In conclusion, he indings om his s udy ha e p oduced a ious use ul policy implica ions. Go e nmen s o sub-Saha an A ican coun ies ba ling po e y can le e age o eign di ec in es - men as a ool o alle ia ing po e y in hei espec i e coun ies. This can be done i hey a e able o gi e mo e a en ion o hei local economic condi ions, which include imp o ing hei human capi al de elopmen and he quali y o hei ins i u ions. This s udy ecommends ha in addi ion o FDI’s p omo ional policies, go e nmen s o SSA coun ies need o u he libe alize, p i a ize, and secu i ize c i ical sec o s in hei economies in o de o p o ide needed capi al o human capi al in es men . Fu he mo e, imp o emen in ins i u ional ac o s such as con ol o co up ion and poli ical s abili y will quickly pay o in eaping gains om FDI. This s udy has some sho comings which can be add essed in u u e esea ch. O he in e mi en o media ing a iables such as inancial de elopmen , globaliza ion, and en i onmen al quali y ha e all been shown o be c ucial. Fu u e esea ch could in es iga e he impac o hese a iables on he nexus be ween FDI and po e y. Fu he mo e, he ixed e ec ins umen al eg ession can add ess he c oss-coun y he e ogenei y p oblem. Howe e , coun y-speci ic s udies a e also wo hwhile o mo e a ge ed policy implica ions. 7 Au ho de ails Sodiq A ogundade a E-mail: [email p o ec ed] Biyase Mduduzi a Hinaunye Ei a a ORCID ID: h p://o cid.o g/0000-0002-5859-7132 a School o Economics, College o Business and Economics, Uni e si y o Johannesbu g, Auckland Pa k Kingsway Campus P.O. Box 524 Auckland Pa k, Johannesbu g, Sou h A ica. Ci a ion in o ma ion Ci e his a icle as: Fo eign di ec in es men and po e y in sub-Saha an A ican coun ies: The ole o hos abso p i e capaci y, Sodiq A ogundade, Biyase Mduduzi & Hinaunye Ei a, Cogen Economics & Finance (2022), 10: 2078459. No es 1. The sa ings-in es men gap in SSA be ween he pe - iod o 2010–2018 was −1.51% o GDP (Bank, 2018). 2. measu ed by head coun po e y as a pe cen age o popula ion 3. measu ed by he a e age o he six dimensions o ins i u ional quali y 4. measu ed by head coun po e y as pe cen age o popula ion 5. measu ed by he Ba o-lee human capi al index 6. The selec ed coun ies accoun o 79.82% o o al s ock o FDI in lows in SSA in 2018. This makes ou sample mo e ep esen a i e. 7. This index leans on he (Ba o & Lee, 2013) measu e- men o a e age yea s o schooling, and a Mince ’s equa ion es ima es which assumed a p esumed a e o e u n o educa ion (Psacha opoulos, 1994). A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 17 o 22 8. S udies like (Al a o & Cha l on, 2007; Ta salewska, 2008) ha e also used lagged FDI as ins umen in hei s udies. Thei a gumen is ha mul ina ionals a e a ac ed by coun ies ha al eady ha e sub- s an ial in lows o in es men s. 9. measu ed by he Con ol o co up ion index 10. measu ed by he Ba o-lee human capi al index 11. measu ed by he headcoun a io Da a a ailabili y s a emen The da a ha suppo he indings o his s udy a e a ailable on eques om he co esponding au ho . Disclosu e s a emen No po en ial con lic o in e es was epo ed by he au ho (s). 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Jou nal o A ican Business, 1–18. h ps://doi.o g/10.1080/15228916.2020. 1770040 A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 20 o 22 Appendix 1: Uni ed Na ions egional classi ica ion Cen al A ica Eas A ica Sou he n A ica Wes A ica Came oon Bu undi Angola Benin Cen al A ican Republic Kenya Leso ho Bu kina Faso Congo Democ a ic Republic Mau i ius Namibia Cô e d’I oi e Congo Republic Malawi Sou h A ica Gambia Gabon Mozambique Zambia Ghana Rwanda Zimbabwe Libe ia Mali Mau i ania Nige Nige ia Senegal Sie a Leone Togo A ogundade e al., Cogen Economics & Finance (2022), 10: 2078459 h ps://doi.o g/10.1080/23322039.2022.2078459 Page 21 o 22 © 2022 The Au ho (s). This open access a icle is dis ibu ed unde a C ea i e Commons A ibu ion (CC-BY) 4.0 license. You a e ee o: Sha e — copy and edis ibu e he ma e ial in any medium o o ma . Adap — emix, ans o m, and build upon he ma e ial o any pu pose, e en comme cially. 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