Foreign direct investment inflow dynamics: The case of central and eastern Europe

Tsaurai, Kunofiwa Article Foreign direct investment inflow dynamics: The case of central and eastern Europe Comparative Economic Research. Central and Eastern Europe Provided in Cooperation with: Institute of Economics, University of Łódź Suggested Citation: Tsaurai, Kunofiwa (2023) : Foreign direct investment inflow dynamics: The case of central and eastern Europe, Comparative Economic Research. Central and Eastern Europe, ISSN 2082-6737, Lodz University Press, Lodz, Vol. 26, Iss. 1, pp. 45-63, https://doi.org/10.18778/1508-2008.26.03 This Version is available at: https://hdl.handle.net/10419/289726 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ 45 ForeignDirectInvestmentInflowDynamics: TheCaseofCentralandEasternEurope Kunofiwa Tsaurai https://orcid.org/0000‑0001‑8041‑1181 Ph.D., Full Professor at the University of South Africa, Department of Finance, Risk Management and Banking, Pretoria, South Africa, e‑mail: [email protected] or kunofiwa.tsaur[email protected] Abstract This study investigates the dynamics of foreign direct investment (FDI) inflows into Central and Eastern European countries (CEECs) using panel data (1994–2020) analysis methods such as fixed effects, fully modified ordinary least squares (FMOLS) and random effects. Specifically, the study examined what factors could account for the mixed pattern of FDI inflows into CEECs. The mixed results from the existing empirical literature on FDI inflow dynamics triggered the un‑ dertaking of this study to contribute to the ongoing debate on the subject. The study notes that infrastructural development, economic growth and domestic investment had a significant positive influence on FDI across all three panel data analysis methods. Other variables that were found to have had a significant positive effect on FDI include (1) complementarity between in‑ frastructural and financial development (fixed effects, random effects), (2) trade openness (fixed effects) and (3) savings (random effects, FMOLS). A significant negative impact of the exchange rate on FDI was observed under the FMOLS. CEECs are therefore urged to implement poli‑ cies to increase infrastructural development, financial development, trade openness and savings to enhance the inflow of FDI. Future studies should investigate the minimum threshold levels of the explanatory variables of FDI. Keywords: foreign direct investment, Central and Eastern Europe, panel data JEL: C23, C33, F21, N44 Comparative Economic Research. Central and Eastern Europe Volume 26, Number 1, 2023 https://doi.org/10.18778/1508‑2008.26.03 © by the author, licensee University of Lodz – Lodz University Press, Poland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license CC‑BY‑NC‑ND 4.0 (https://creativecommons.org/licenses/by‑nc‑nd/4.0/) Received: 17.05.2022. Verified: 6.09.2022. Accepted: 17.01.2023 Kunofiwa Tsaurai 46 Kunofiwa Tsaurai Introduction Thethree sub‑sections that constitute this part include thebackground ofthestudy, thecontribution totheliterature, andtheorganization ofthepaper. Foreign direct investment (FDI) brings capital, skills, technology andnetworking, all ofwhich en‑ hance economic growth inthereceiving country (Romer 1986). More recent empirical research that supports theFDI‑led growth hypothesis includes, but is not limited to, Gui‑Diby (2014), Melnyk, Kubatko, andPysarenko (2014), Long, Yang, andZhang (2015) andOkwu, Oseni, andObiakor (2020). Consistent with Makhoba andZungu (2021), there appears tobe aconsensus regarding thepositive influence ofFDI oneconomic growth. Despite theoverwhelming evidence that economic growth is enhanced by FDI, such information is not enough tohelp develop policies aimed atattracting FDI. Thein‑ vestigation ofthemacroeconomic determinants ofFDI fills inthat gap. Several empirical studies have attempted toexamine thedeterminants (macro) ofFDIs. Table2 inSection3 ofthis paper shows that FDI determinants were found tobe varied, mixed, andinconclusive andthat there weare still far from agenerally agreeable list. Theempirical studies also donot agree onhow each variable influences FDI, as some show apositive whilst others have anegative impact. Some methodological weakness‑ es were also observed intheexisting empirical research onthedeterminants ofFDI, while others wrongly assumed that FDI andits independent variables are characterized by alinear relationship. Thefew prior studies that focused onCentral andEastern Eu‑ ropean countries (CEECs) used outdated data. Tothebest oftheauthor’s knowledge, none investigated theimpact ofacomplementarity variable (trade openness andinfra‑ structural development) onFDI. This study fills these gaps. Thefive ways inwhich this study contributes toliterature are enunciated inthis section. Firstly, tothebest oftheauthor’s knowledge, this is thefirst study todetermine if acom‑ plementarity variable is one ofthedeterminants ofFDI inCEECs. Secondly, unlike pri‑ or empirical research onthedeterminants ofFDI, this study used themost recent data (1994–2020). Thirdly, unlike prior research, this study considers that therelationship between FDI andits explanatory variables is non‑linear. Seven more sections constitute therest ofthis paper. Section2 is atheoretical litera‑ ture discussion onthedeterminants ofFDI, andSection3 reviews theempirical lit‑ erature, whilst Section4 presents anddescribes theFDI trends forCEECs between 1994and2020. Section5 is theresearch methodological framework, Section6 focuses ondata analysis andthediscussion oftheresults, while Section7 concludes. 47 Foreign Direct Investment Inflow Dynamics: The Case of Central and Eastern Europe Theoreticalliteraturereview Table 1. Theoretical praxis of the explanatory variables Explanatory variables Theoreticalviews Impact Trade openness (OPEN) Denisia (2010) argued that trade openness is a direct outcome of good government policy; therefore, it is one of the locational advantages of FDI. It also noted that external shocks experienced by countries characterized by higher levels of trade openness might not be favorable to FDI inflows. +/‑ Economic growth (GROWTH) The eclectic paradigm hypothesis argued that one of the locational advan‑ tages of FDI is economic growth (Denisia 2010), a view supported by Jorgenson (1963). + Savings (SAV) Consistent with Romer (1986) and Lucas (1988), savings stimulate both domestic and foreign investment, ensuring the sustainable and long‑term growth of the host country’s economy. Domestic savings (% of GDP) was used as a measure of savings in this study. + Personal remittances (REMIT) According to Azam and Haseeb (2021), international capital flows normally follow each other; hence, FDI and personal remittances flow together in the same direction. By contrast, personal remittance inflow enables the labor exporting country to have its own home‑grown reservoir of financial resources to stir economic growth, reducing the overreliance on FDI inflows. Either way, personal remittances are expected to influence FDI. Personal remittances received (% of GDP) is the measure of personal remittances used in this study. +/‑ Exchange rate (EXCH) Aliber (1970) argued that strong domestic currencies chase away FDI because foreign investors get little for their foreign currencies. The argument was supported by Moosa (2010), whose study noted that countries whose currencies are very strong have more appetite to invest in other countries because they can still afford to access capital at higher interest rates and still makes a profit. + Financial development (FIN) According to Kaur, Yadav, and Gautam (2013), developed financial markets ease foreign investors’ entry and exit constraints, apart from smoothing foreign and domestic market linkages. Financial markets which are deep and developed enhance the productivity of foreign capital through their ability to efficiently distribute financial resources (Ezeoha and Cattaneo 2012). + Domestic investment (DINV) Consistent with Lucas (1988), the environment that spurs domestic invest‑ ment is like the one that attracts foreign investment. In other words, increased domestic investment enhances sustainable economic growth, itself a locational advantage of FDI, as argued by Jorgenson (1963). The measure of domestic investment used in this study is gross capital formation (% of GDP). + Infrastructural development (INFR) According to Craigwell (2012), developed infrastructure acts as a support network for the new technology brought in by foreign direct investors. The conducive environment brought by a developed infrastructure attracts foreign direct investors (Denisia 2010). + Source: author’s compilation. 48 Kunofiwa Tsaurai Empiricalliteraturereview Table 2. Empirical research on the determinants of foreign direct investment Author Unitofanalysis Approach Findings Tampakoudis et al. (2017) Middle‑income countries Panel data analysis The significant positive influence of trade openness, population growth and economic growth on FDI was observed in middle‑income countries. Abel et al. (2021) Zimbabwe Autoregressive Distributive Lag (ARDL) Wages, interest rates, inflation, economic growth and trade openness heavily determined the inflow of FDI into the mining sector of Zimbabwe. Tocar (2018) Literature review analysis Literature review analysis Salaries, agglomeration, liquidity and market size were factors that positively influenced FDI inflows. Kumari and Sharma (2017) Developing countries Panel data analysis Trade openness, human capital development, interest rates and market size were noted as the key factors that attracted FDI. Tsaurai (2017) BRICS Fixed effects, pooled OLS Trade openness, economic growth, exchange rate stability, human capital development and financial development significantly enhanced FDI inflows. Bryna (2021) Indonesia Panel data analysis Financial development, human capital development, and market size were found to be significant positive factors that drove FDI inflows into Indonesia. Azam and Haseeb (2021) BRICS Fully Modified Ordinary Least Squares (FMOLS) Trade openness, market size, economic growth and tourism were the major drivers of FDI inflows. Majavu (2015) South Africa Vector Error Correction Model (VECM) Economic growth enhanced FDI, whilst financial crises had a deleterious influence on FDI in South Africa. Malefane (2007) Lesotho Multi regression analysis An export‑oriented promotion strategy was one of the major factors that attracted FDI into Lesotho. Boğa (2019) Sub‑Saharan African countries Panel data analysis Trade openness, natural resource availability, economic growth, financial development and telecommunication infrastructural development were observed to have attracted FDI into Sub‑Saharan African countries. Wijaya et al. (2020) Indonesia VECM Inflation, economic growth, interest rates, infrastruc‑ tural development and exchange rates attracted FDI in Indonesia. Pradhan (2011) SAARC countries Vector Autoregressive (VAR) approach Exchange rate, economic growth, population growth, current account balance, inflation and trade openness were found to be significant positive determinants of FDI. 49 Foreign Direct Investment Inflow Dynamics: The Case of Central and Eastern Europe Author Unitofanalysis Approach Findings Agiomirgianakis, Asteriou, and Papathoma (2004) OECD countries Panel data analysis Human capital development, trade openness and infra‑ structural development positively influenced FDI. Coy and Cormican (2014) Japanese and Ireland Descriptive statistics A low corporate rate was found to be instrumental in attracting FDI. Ashurov et al. (2020) Central Asian region Generalized methods of moments Economic growth, trade openness, previous FDI and tax revenue had a significant influence on FDI. Mahbub and Jongwanich (2019) Bangladesh Time series data analysis A good regulatory framework, economic growth, polit‑ ical stability and financial development significantly attracted FDI inflows. Asiedu (2002) Africa Panel data analysis Better infrastructure and a higher rate of return were found to have attracted FDI into non‑Sub‑Saharan African countries. Çevis and Çamurdan (2007) Transition economies Panel data analysis Inflation, economic growth, interest rates and trade openness were the major determinants of FDI in transition economies. Asong, Akpan, and Isiye (2018) BRICS and MINT countries Pooled time‑series cross‑sectional data analysis Significant factors that attracted FDI into BRICS and MINT countries include infrastructural develop‑ ment, market size and trade openness. Institutional quality and natural resource availability also attracted FDI in an insignificant manner. Hintosova et al. (2018) Visegrad group of countries Pooled ordinary least squares (OLS) Wages and human capital development were found to have significantly positively influenced FDI. Erdogan and Unver (2015) 88 countries Panel data analysis Human capital development, financial development, market size, inflation, economic growth and unemploy‑ ment were found to have attracted FDI inflows. Silveira, Samsonescu, and Triches (2017) Brazil VECM Wages, economic growth and productivity were observed to have attracted FDI in Brazil. Rashed, Yong, and Soon (2021) Africa Panel data analysis Corruption had a deleterious impact on FDI. On the other hand, economic growth enhanced FDI in Africa. Mansaray (2017) Sierra Leone Error Correction Model (ECM) Trade openness and economic enhanced FDI inflows in Sierra Leone. Mupimpila and Okurut (2012) Southern African Development Community (SADC) SADC The lag of inflation and infrastructural development had a deleterious effect on FDI. By contrast, economic growth, external debt, inflation, and the lag of FDI had a significant influence on FDI in SADC countries. 50 Kunofiwa Tsaurai Author Unitofanalysis Approach Findings Mottaleb and Kalirajan (2010) Developing countries Panel data analysis A friendly business environment, economic growth and trade openness had a significant positive influence on FDI in developing countries. Sane (2016) Economic Community of West African States (ECOWAS) Panel data analysis Economic freedom, economic growth, larger market size, financial development, stable macroeconomic environment and exchange rates played a major role in helping to attract FDI into ECOWAS. Kariuki (2015) African Union Fixed effects model Trade openness, infrastructural development, commodity price index, financial development, and the lag of FDI had a significant positive effect on FDI in the African Union. Demirhan and Masca (2008) Developing countries Cross‑sectional data analysis Trade openness, economic growth and communica‑ tion infrastructure were observed to have positively and significantly influenced FDI. Yunus (2020) Malaysia manufacturing sector OLS and descriptive statistics Whilst high levels of domestic investment lured FDI, human capital development was observed to have had a negative influence on FDI in the manufacturing sector of Malaysia. Abiola (2019) Nigeria VAR approach Infrastructural development’s influence on FDI had a negative effect on FDI in Nigeria. However, a signif‑ icant positive influence on FDI in Nigeria came from variables such as economic growth, inflation, trade openness and exchange rates. Piteli (2010) Developed countries Panel data analysis Total factor productivity in the receiving country attracted FDI in a very significant positive manner. Source: author’s compilation. What is more apparent from these two sections oftheliterature review is that there is no agreed list that spells out themacroeconomic determinants ofFDI, making thestudy onthedeterminants ofFDI far from conclusive. As aresult, there is aneed formore em‑ pirical research. 51 Foreign Direct Investment Inflow Dynamics: The Case of Central and Eastern Europe ForeigndirectinvestmenttrendsforCentral andEasternEuropean(1994–2020) Figure 1. Foreign direct investment net inflows (% of GDP); trends for Central and Eastern European countries Source: author’s compilation. Net FDI inflows fortheCzech Republic increased from 1.84%ofGDP in1994 to9.69% in 1999, declined by 4.32 percentage points during the four‑year period between 1999and2004 before further decreasing by 2.82 percentage points, from 5.36% in2004 to2.54% in2009. Theperiod between 2009and2014 saw net FDI inflows marginal ‑ ly increasing by 1.32 percentage points, whilst a0.39 percentage point decline innet FDI inflows was experienced between 2014and2020 (from 3.86% in2014 to3.47% in2020). Germany’s net FDI inflows went up by 3.58 percentage points, from 0.34%ofGDP in1994 to3.92% in1999, declined by 3.91 percentage points between 1999and2004, before experiencing growth of1.65 percentage points during thesubsequent four‑year period (from 0.01%ofGDP in2004 to1.66% in2009). Germany experienced a1.16 per‑ centage point decline innet FDI inflows from 2009to2014, andthen its net FDI inflows jumped from 0.50%ofGDP in2014 to3.71% in2020. Thenet FDI inflow forLithuania increased from 0.87%ofGDP in1994 to5.15% in1999 before going down by 1.26 percentage points during thesubsequent four‑year period (from 5.15%ofGDP in1999 to3.89% in2004). Afurther decline of3.88 percentage points was experienced during thefour‑year time period between 2004and2009. Lith‑ uania’s net FDI inflow increased from 0.01%ofGDP in2009 to0.74% in2014 before massively increasing by 7.18 percentage points between 2014and2020. 52 Kunofiwa Tsaurai Net FDI inflows forPoland went up from 1.69%ofGDP in1994 to4.36% in2004, in‑ creased by 1.08 percentage points during thesubsequent four‑year period (1999–2004) before declining from 5.44% in2004 to3.19% in2009. Anincrease innet FDI inflows of0.46 percentage points between 2009and2014 was observed. Between 2014and2020, net FDI inflows plummeted from 3.65%ofGDP to2.91%. Romania’s net FDI inflows went up from 1.13%ofGDP in1994 to2.90% in1999, fur‑ ther increased by 5.70 percentage points between 1999and2004, before asharp decline by 5.93 percentage points during thesubsequent four‑year period (from 8.59%ofGDP in2004 to2.66% in2009). Net FDI inflow declined from 2.66%ofGDP in2009 to1.93% in2014 before further experiencing a0.49 percentage point decline between 2014and2020). The net FDI inflows for the five CEECs did not follow a straight line between 1994and2020. Thus, several reasons account forthevaried nature ofthetrend lines ofnet FDI inflows ofthese countries. Thestudy filled this gap by examining thedynam‑ ics behind themixed trends innet FDI inflows ofthese CEECs. Methodologicalframework Data: Panel secondary data from 1994to2020 was used toexamine thedeterminants ofFDI. TheWorld Bank database was themain source ofpublic data. Transparency, ac‑ cessibility, traceability andreliability are some ofthebenefits ofextracting data from such aninternational database. Specification ofthegeneral model: Equation 1 represents thegeneral model specifica‑ tion oftheFDI function. FDI=f (INFR, FIN, OPEN, EXCH, SAV, REMIT, GROWTH, DINV). (1) Thefollowing empirical studies were instrumental inchoosing theexplanatory variables or independent variables oftheFDI function: Agiomirgianakis, Asteriou, andPapatho‑ ma (2004), Malefane (2007), Pradhan (2011), Coy andCormican (2014), Majavu (2015), Kumari andSharma (2017), Tampakoudis etal. (2017), Tsaurai (2017), Tocar (2018), Boğa (2019), Mahbub andJongwanich (2019), Ashurov etal. (2020), Wijaya etal. (2020), Abel etal. (2021), Azam andHaseeb (2021), andBryna (2021). Inline with Aye andEdoja (2017), todecisively deal with themulti‑collinearity problem, outliers, andabnormally distributed data sets, all thedata was used forthemain analysis inits natural logarithm format. 59 Foreign Direct Investment Inflow Dynamics: The Case of Central and Eastern Europe reservoir of financial resources to stir economic growth, reducing the overreliance onFDI inflows. Thepositive impact ofeconomic growth onFDI was found tobe significant under theFMOLS, fixed andrandom effects, consistent with theeclectic paradigm hypothesis, which listed economic growth among alist oflocational advantages ofFDI (Jorgenson 1963). Domestic investment had asignificant positive influence onFDI across all three panel data analysis methods, insupport ofanargument by Lucas (1988), which implies that theenvironment that spurs domestic investment is like theone that attracts for‑ eign investment. Conclusion This study investigated thedynamics ofFDI inflows intoCEECs using panel data (1994–2020) analysis methods such as fixed effects, fully modified ordinary least squares andrandom effects. Specifically, thestudy examined what factors could ac‑ count forthemixed pattern ofFDI inflows intoCEECs. Themixed results from theex‑ isting empirical literature onFDI inflow dynamics triggered theundertaking ofthis study tocontribute totheongoing debate onthesubject matter. Thestudy noted that infrastructural development, economic growth anddomestic investment had asig‑ nificant positive influence onFDI across all thethree panel data analysis methods. Other variables that had asignificant positive effect onFDI include (1)complementa‑ rity between infrastructural andfinancial development (fixed effects, random effects), (2)trade openness (fixed effects) and(3) savings (random effects, FMOLS). Asignif‑ icant negative impact oftheexchange rate onFDI was observed under theFMOLS. CEECs are therefore urged toimplement policies toincrease infrastructural devel‑ opment, financial development, trade openness, andsavings toenhance theinflow ofFDI. Future studies should investigate theminimum threshold levels oftheex‑ planatory variables ofFDI. 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Zauważono, że rozwój infrastruktury, wzrost gospodarczy i inwestycje kra‑ jowe miały znaczący pozytywny wpływ na BIZ co potwierdziły wszystkie trzy metody analizy danych panelowych. Inne zmienne, które miały znaczący pozytywny wpływ na BIZ, obejmują (1) komplementarność rozwoju infrastruktury i rozwoju finansowego (metoda efektów stałych, metoda efektów losowych), (2) otwartość handlu (metoda efektów stałych) oraz (3) oszczędności (metoda efektów losowych, FMOLS). Stosując metodę FMOLS zaobserwowano znaczący nega‑ tywny wpływ kursu walutowego na BIZ. Zachęca się zatem kraje Europy Środkowo‑Wschodniej do wdrożenia polityki mającej na celu zwiększenie rozwoju infrastruktury, rozwoju finansowego, otwartości handlu i oszczędności w celu zwiększenia napływu BIZ. W przyszłych badaniach na‑ leży zbadać minimalne poziomy progowe zmiennych objaśniających BIZ. Słowa kluczowe: bezpośrednie inwestycje zagraniczne, Europa Środkowo‑Wschodnia, dane panelowe