Foreign Capital Inflows and Poverty Reduction in Nigeria: Implication for Sustainable Development



Johnson Kolawole Olowookere1, Samson Oluwole Olowo2, Oladotun Toriola Mabinuori3, Timothy Ayomitunde Aderemi4



Abstract: This study aims at examining the contributions of the different components of foreign capital inflows in driving one of the key goals of sustainable development-poverty reduction in Nigeria. In achieving the objective of this study, annual data between 1990 and 2019 were utilized with the application of FMOLS and Granger causality technique of estimation. The findings of this research work are as follows; firstly, foreign capital inflows and poverty reduction have a long run equilibrium relationship in Nigeria. Furthermore, there is a unidirectional causality flowing from poverty reduction to foreign direct investment. Poverty reduction Granger causes foreign portfolio investment. Also, feedback relationship exists between poverty reduction and remittances. This implies that poverty reduction is a strong factor causing the inflows of foreign capital such as FDI, FPI and remittances in Nigeria. Moreover, the majority of the components of foreign capital inflows such as FDI, FPI and remittances contributed immensely to the reduction of poverty in Nigeria. This implies that foreign capital inflows have the capacity to propel the achievement of Sustainable Development Goal one - poverty reduction in Nigeria. Therefore, this study makes the following recommendations for the policymakers in Nigeria and by extension Africa that, any time these policymakers set to achieve Sustainable Development Goal one i.e poverty reduction, foreign capital inflows such as remittances, foreign portfolio investment, FDI and external debt should be given priority in their country. And such, the policy that facilitates the sporadic inflows of these variables should be embarked upon by the Nigerian policymakers in particular and African policymakers in general.

Keywords; FDI; FPI; ODA; Remittances; External Debt; Poverty Reduction and SDGs

JEL Classification: F2; 047; C100



1. Introduction

In this era of globalization, inflows of capital across the countries of the world cannot be undermined in the recent times. Strategic factors such as the presence of investment opportunities alongside with the better returns on the investments facilitate the flow of capital from advanced economies to developing economies (Lucas, 1988). Developing countries are usually capital deficient due to a wide gap between available capital and the required capital to drive the economy to a sustainable growth. Therefore, inflows of foreign capital become an indispensable variable to bridge these deficiencies in the domestic economy (Sy & Rakotondrazaka, 2015; UNCTAD, 2015; Chea, 2011; Ellahi, 2011).

However, poverty is a major issue confronting Nigeria in the recent times. Available evidence shows that poverty is endemic in Nigeria in such a way that the majority of its populace could not afford basic necessity of life such as food, quality education and the host of others (World Poverty Clock, 2018; Adebayo, 2018; Aderemi et al., 2020:a). In the light of the above, combating poverty in Nigeria becomes a continuous assignment in tandem with the advocacy of the sustainable development goal one – poverty reduction. Meanwhile, achieving poverty reduction in any economy like Nigeria where the actual savings and investments could not metamorphose to the desire investment requires viable means of augmenting the investment gap in the economy. One of the viable means of bridging the investment gap created by deficient locally mobilized savings and net export earnings is to open up the economy to the inflows of foreign capital (Adeola, 2017; Okafor, Ogochukwu & Chijundu, 2016; Abidemi, Adegboye, Ogbebor & Egharvba, 2014).

Consequently, various components of foreign capital inflows like foreign direct investment, foreign portfolio investment, official development assistance, remittances and external debts have become an integral part of the Nigerian economy in the past few decades (CBN, 2017; NBS, 2017; UNCTAD, 2015). This implies that Nigeria has benefited from global allocation of foreign capital. Meanwhile, the early studies have argued in favour of strategic roles of international financial integration in driving the domestic economy (Alfaro, Kalemli-Ozcan & Volosovych, 2007; Obstfeld & Rogoff, 2000). Against this backdrop, various empirical studies started investigating the impact of different components of foreign capital inflows on the performance of the Nigerian economy. It is instructive to note that the focus of the majority of the recent empirical studies has been on the impact of foreign capital inflows on economic growth (Balogun, Okafor & Ihayere, 2019; Adekunle, 2018; Chigbu, Ubah & Chigbu, 2015; Okafor, Ugochukwu & Ajide, 2014). While neglecting the impact it could have on poverty reduction. As a departure from the existing past studies, this study examined foreign capital inflows and poverty reduction nexus in Nigeria, using methodology in which majority of past studies on this subject matter have ignored in most recent times.

The structure of this study is done as follows; besides introduction that sets the foundation for this work, section two provides the detailed review of literature. Whereas, section three provides methodology, analysis of results and policy recommendation of the results.



2. Review of Literature

Foreign capital inflows and macroeconomic variables nexus has been well has been prominently pronounced in the literature. Monogbe, Okereke and Ifionu (2020) examined nexus between foreign capital flows and economic development in Nigeria from 1986 to 2018 using error correction model and granger causality techniques. The authors submitted that foreign capital inflows such as foreign portfolio investment, official development assistance and bilateral loan caused a significant contribution to the Nigerian economic development. But FDI and multilateral loan led to a negative contribution to the Nigerian economic development Adekunle (2018) conducted a research about the linkage between foreign capital inflows and economic growth in Nigeria from 1986 to 2015 using ARDL technique. It was discovered from the study that net FDI inflows led to a direct impact on economic growth in the short run, but net foreign remittances and net portfolio flows led to an inverse impact on economic growth in the short-run. Gabriel, John and Baryl (2019) investigated how capital flows contributed to economic growth in Nigeria between 1981 and 2016 with the application of ARDL and ECM. The study argued that the contribution of capital inflow was significant in growing the Nigerian economy. In another related study, Aderemi et al. (2020: b) used different panel techniques to assess how inflows of FDI led to poverty alleviation among 16 countries in ECOWAS sub region from 1990 to 2017. The authors posited that the inflows of FDI caused a significant impact in achieving poverty alleviation within ECOWAS sub region and FDI projects led to an aggressive rate of poverty alleviation within the economic bloc.

Meanwhile, Ogunleye et al. (2020) utilized Cointegration, DOLS and Granger Causality technique to estimate the long run equilibrium relationship that exists between poverty alleviation and official development assistance between 1981 and 2017. It was submitted from the study that official development assistance had a significant negative relationship with poverty alleviation in the country. There existed a bidirectional feedback between official development assistance and poverty alleviation in Nigeria. While utilizing GARCH-BEKK model, Guglielmo, Faek, and Nicola (2013) examined the relationship between exchange rate uncertainty and portfolio flows in economies such as Australia, Japan, Uk, Canada and Sweden from 1988 to 2011. It was argued from the study that the relationship between volatility in exchange rate and portfolio investment was negative in some countries, while reverse was the case in other countries. Similarly, Teddy (2015) carried out a study in Zambia with application of GARCH model, Johansen cointegration test and error correction model in investigating the nexus between volatility in exchange rate and inflows of private capital in Zambia. The author concluded that volatility in the nominal exchange rate and foreign portfolio investment flow had a significant inverse relationship in the country.

Furthermore, Obiechina and Ukeje (2013) employed the Engle-Granger technique in investigating the linkage between capital flows and the Nigerian economic growth between 1970 and 2010. The study asserted that FDI led to a weak contribution to the Nigerian economic growth in the short run. In another related study, Abidemi, Adegboye, Ogbebor and Egharvba, (2014) used a vector error correction mechanism to estimate the relationship between capital flows and economic growth in Nigeria from 1981 to 2012. It was revealed from the paper that the major components of capital flows such as FDI, portfolio investment and external debt orchestrated a significant contribution to economic growth in the country. In a study focusing on 13 countries in ECOWAS sub region, Modou and Liu (2017) researched how Both FDI and trade contributed to economic growth in the sub regional economic bloc between 1985 and 2015. The authors concluded that both trade and FDI exacted a significant contribution to economic growth in the sub region and there existed both unidirectional and bidirectional feedback relationship between FDI and trade on economic growth of the sub region. Saibu and Keke (2014) applied principal components analysis alongside with ARDL in assessing how capital inflow and economic growth are linked in Nigeria. It was discovered from the study that the interaction of capital inflow and trade openness resulted in a significant contribution to economic growth.

In conclusion, it could be deduced from the above empirical studies that various components foreign capital inflows have resulted into a mixed impact economic growth, while neglecting its impact it could have on poverty reduction in the economy. Hence, the relevance of this study.



3. Methodology and Materials

The adoption of an ex-post facto research design is appropriate in this work due to its main interest which explored the viable relationship, and as well described how foreign capital inflows predict variation in poverty reduction in Nigeria. Similarly, secondary data from 1990 to 2019 were extracted mainly from the World Bank Development Indicators to run the analysis of this study.

3.1. Model Specification

Various components of foreign capital inflows have been submitted in the literature to be the drivers of economic growth and consequently result in poverty reduction in developing economies. And as such, this study draws insight in adapting model from studies like Ogunleye et al. (2020); Aderemi et al. (2020) and Umoh et al. (2012). The focus of this study necessitates the adjustment of variables in the adapted model to capture the objective of this study as follows;

POVT = F (FCAP) (1)

POVT𝑡 = + 𝛼 FDI𝑡 + 𝛽1FPI𝑡 + 𝛽2ODA𝑡 + 𝛽3REM𝑡 + 𝛽4EXD𝑡+ 𝛽5EXCH𝑡 + 𝛽6Inf𝑡 + 𝜇𝑡 (2)

If the natural log is introduced to equation 2, it transforms the model as thus;

POVT𝑡 = + 𝛽0LnFDI𝑡 + 𝛽1LnFPI𝑡 + 𝛽2LnODA𝑡 + 𝛽3LnREM𝑡 + 𝛽4LNEXD𝑡+ 𝛽5LnEXCH𝑡 + + 𝛽6TOP𝑡 + 𝛽7Inf𝑡 +𝜇𝑡 (3)

Estimating the Granger causality between the components of foreign capital inflows and poverty reduction requires the utilization of pairwise granger causality equations as stated below;

 =   (4)

 =  (5)

ODAt=   (6)

REMt=   (7)

EXDt=   (8)

 =   (9)

Where:

POVT is poverty reduction and is measured by GDP per capita. FDI is foreign direct investment and is measured by net inflows of FDI in the reporting economy. FPI is foreign portfolio investment. ODA is official development assistance. REM is remittances. EXTD is external debt. EXCH is exchange rate. Inf is inflation rate and TOP is trade openness. u is error term. t is the period of the analysis.

It is expected that 𝛽0 to 𝛽6 >0 whereas 𝛽7<0.



4. Results and Discussion

Table 1. Descriptive Statistics of Variables

Descriptive Statistics

POVT

LnFDI

LnFPI

LnODA

LnREM

LnEXTD

TOP

Inf

LnEXCH

Mean

1751.00

21.9626

26.3845

21.0681

22.7297

7.32808

37.4127

13.2886

167.601

Median

1930.00

22.0964

26.7504

21.3846

23.6561

7.52620

37.1450

11.8350

141.190

Maximum

3223.00

22.9110

31.2379

23.1596

24.1091

8.95665

53.2800

44.5900

387.000

Minimum

477.000

20.8691

20.7430

18.8393

17.8408

4.71438

20.7200

5.38000

17.2984

Std. Deviation

875.251

0.67972

2.23264

1.16687

1.65127

1.07631

8.84573

7.92014

91.6658

Skewness

0.12742

0.26984

0.33569

0.55355

0.42621

-0.52187

-0.08120

0.89189

0.27046

Kurtosis

1.77287

1.77977

3.59306

2.47075

4.32894

2.61727

2.37747

12.3170

3.92680

Jargue-Bera

1.43989

1.63187

0.73561

1.38030

9.07728

1.13289

0.37942

110.238

6.70571

Probability

0.48677

0.44222

0.69224

0.50149

0.01068

0.56753

0.82719

0.00000

0.03498

Sum

38522.0

483.178

580.460

463.498

500.054

161.217

823.080

292.350

3687.24

Sum. Sq. Deviation

160873

9.70261

104.678

28.5934

57.2607

24.3277

1643.18

1317.30

176455.

Observation

29

29

29

29

29

29

29

29

29

Source: Authors’ Computation (2021)

An attempt to test the normal distribution of the employed data, descriptive statistics of the various data in this study was estimated in which its results were presented in the above table. The importance of this test lies in the fact that econometric analysis is built on the assumption of the normal distribution of the dataset. Meanwhile, the values of the mean and median of all the relevant variables are very close. This justifies the assertion of Karmel and Polasek (1980) who argued that normal distribution of data occurs the moment the mean, modal and median values of such data converged. In the same vein, all the variables except Ln EXTD have positive skewness with kurtosis values that are not far from 3.

Table 2. Unit Root Test

Variables

ADF Test


Level

Probability

1st Diff

Probability

Remark

LnFDI

-2.981038***

0.4785

-2.971853***

0.0000

I(1)

LnFPI

-2.986225***

0.1139

-2.991878***

0.0016

I(1)

POVT

-2.967767***

0.8435

-2.971853***

0.0133

I(1)

LnEXCH

-2.967767***

0.9993

-2.971853***

0.0141

I(1)

LnEXTD

-2.967767***

0.1570

-2.971853***

0.2365

I(2)

LnREMM

-2.967767***

0.0703



I(0)

LnODA

-2.967767***

0.1758

-2.971853***

0.0000

I(1)

OPEN

-2.967767***

0.0385



I(0)

Inf

-2.967767***

0.2733

-2.971853***

0.0019

I(1)

Variables

PP Test


Level

Probability

1st Diff

Probability


LnFDI

-2.967767***

0.3827

-2.971853***

0.0000

I(1)

LnFPI

-2.967767***

0.0001



I(0)

POVT

-2.967767***

0.8159

-2.971853***

0.0156

I(1)

LnEXCH

-2.967767***

0.9984

-2.971853***

0.0146

I(1)

LnEXTD

-2.967767***

0.1389

-2.971853***

0.4121

I(2)

LnREMM

-2.967767***

0.0703



I(0)

LnODA

-2.967767***

0.2081

-2.971853***

0.0001

I(1)

OPEN

-2.967767***

0.0385



I(0)

Infl

-2.967767***

0.1810

-2.971853***

0.0020

I(1)

Source: Authors’ Computation (2021) *** %5 level

It has been established that time series data usually show non-stationarity behavior (Granger, 1986). This type of behavior is the genesis of spurious results in an empirical analysis. In order to resolve this issue in this study, effort was made to subject the data to stationarity test via the standard Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) techniques. The estimated results presented in table 2 indicate that the variables comprise of different order of integrations. In another words, the majority of the variables are stationary after first differencing, while external debt data in log form is stationary after second differencing, foreign portfolio investment and remittances in log form are stationary in their native form.



Table 3. Johansen Cointegration Test (Trace Statistic)

Hypothesized Number of CEs

Eigenvalue

Trace Statistic

0.05 Critical Value

Prob**

None*

0.998535

243.1650

95.75366

0.0059

At most 1

0.888928

119.1707

69.81889

0.0531

At most 2

0.826522

77.41679

47.85613

0.0500

At most 3

0.679565

44.13438

29.79707

0.0706

At most 4

0.539433

22.51094

15.49471

0.0537

At most 5

0.336010

7.780283

3.841466

0.0853

Johansen Cointegration Test (Max-Eigen Statistic)

Hypothesized Number of CEs

Eigenvalue

Max-Eigen Statistic

0.05 Critical Value

Prob**

None*

0.998535

123.9944

40.07757

0.0000

At most 1

0.888928

41.75388

33.87687

0.0047

At most 2

0.826522

33.28241

27.58434

0.0683

At most 3

0.679565

21.62344

21.13162

0.0426

At most 4

0.539433

14.73066

14.26460

0.0722

At most 5

0.336010

7.780283

3.841466

0.0953

Notes: *denotes rejection of the null hypothesis at the 0.05 level

**MacKinnon-Haug-Michelis (1999) p-values

Source: Authors’ Computation (2021)

It has been discovered in table 2 that the majority of the variables of interest are not stationary at a level. This means that a short run disequilibrium could occur among these variables in the short run, but there is a tendency the short run disequilibrium adjusts to equilibrium in the long run if there is a long run convergence among these variables of interest. Against this backdrop, this study utilized Johansen Cointegration test developed by Johansen and Juselius (1990) to examine the presence or otherwise of a long run convergence among the variables of interest. Consequently, it could be inferred from table 3 that at most 5 cointegrating equations exist among the variables as indicated by both the Trace statistic and the Maximum Eigen Statistic. This implies that foreign capital inflows and poverty reduction have a long run relationship in Nigeria.

Table 4. Pairwise Granger Causality Test between Foreign Capital Inflow and Poverty Reduction in Nigeria

Null hypothesis

F-statistic

Prob.

Decision

Causality

POVT does not Granger Cause Inf

1.25346

0.3043

Accept


Inf does not Granger Cause Log POVT

0.19113

0.8273

Accept

None

POVT not Granger Cause Ln EXTD

0.56545

0.5758

Accept


Ln EXTD does not Granger Cause POVT

0.58206

0.5668

Accept

None

POVT does not Granger Cause Ln FDI

0.93519

0.4069

Accept

Unidirectional

Ln FDI does not Granger Cause POVT

4.08039

0.0304

Reject


POVT does not Granger Cause Ln FPI

3.82723

0.0472

Reject

Unidirectional

Ln FPI does not Granger Cause POVT

0.74198

0.4940

Accept


POVT does not Granger Cause Ln REM

0.38875

0.6823

Accept

Unidirectional

Ln REM does not Granger Cause POVT

4.31868

0.0256

Reject

None

POVT does not Granger Cause Ln ODA

1.76245

0.1940

Reject


Ln ODA does not Granger Cause POVT

1.38155

0.2713

Reject


Source: Authors’ Computation (2021)

In table 4, the estimated results of causal relationship among various components of foreign capital and poverty reduction were presented. It is instructive to state that there is a unidirectional causality flowing from poverty reduction to FDI. In the same vein, poverty reduction Granger causes FPI. Also, feedback relationship exists between poverty reduction and remittances. This implies that poverty reduction is a strong factor causing the inflows of foreign capital such as FDI, FPI and remittances in Nigeria.

Table 5. Relationship between Foreign Capital Inflows and Poverty Reduction in Nigeria

Dependent Variable: POVT

Method: FMOLS

Regressors

Coefficient

T-statistics

Prob. Value

LnEXD

85.98436

1.217463

0.2468`

LnFDI

172.1984

0.669268

0.5160

LnFPI

210.0416***

2.841690

0.0149

LnREMM

534.8874***

2.662119

0.0207

LnODA

-331.0664*

3.414531

0.0051

Inf

-51.69421***

2.725237

0.0184

LnEXCH

-0.997839

0.842337

0.4161

R-Squared

0.881183



Adjusted

R-squared

0.811874







Source: Authors’ Computation (2021) *Significant at1% ***significant at 5% **Significant at 10%

Table 5 shows estimated results of the long run nexus between foreign capital inflows and poverty reduction in Nigeria within the framework of the Fully Modified Ordinary Least Square. The power of test shows that the model is relatively good because foreign capital inflow components and other control variables jointly explained about 88% of the systematic variations in dependent variable, poverty reduction as indicated by the result of R-Squared. Similarly, all the variables have the expected signs except LnODA and LnEXCH. External debt and GDP per capita have a positive relationship, though the relationship is not significant. In the same vein, FDI and GDP per capita have an insignificant positive relationship. Meanwhile, foreign portfolio investment and GDP per capita have a positive relationship which is significant at 5% level of significance. A unit change in foreign portfolio investment increases GDP per capita by 2.1%. Furthermore, remittances and GDP per capita have a significant positive relationship. A unit change in remittances leads to an increment in GDP per capita by 5.3%. However, ODA and GDP per capita have a significant inverse relationship with each other. A unit change in ODA causes a reduction in GDP per capita by 3.31%. Inflation rate and GDP per capita have a significant negative relationship. A unit change in inflation rate reduces GDP per capita by 51.7%. Also, exchange rate and GDP per capita have insignificant negative relationship.

By and large, it could be inferred from the above that majority of the components of foreign capital inflows contributed significantly to the expansion of GDP per capita in Nigeria. This implies that foreign capital inflows have contributed significantly to poverty reduction in the last three decades. The finding in this study is in tandem with submissions of Tunde, Okereke and Ifionu (2020), and Aderemi et al. (2020: b) in related studies in Nigeria and ECOWAS countries respectively.



5. Conclusion and Recommendation

This paper examined the contributions of the different components of foreign capital inflows in driving one of the key goals of sustainable development-poverty reduction in Nigeria. In achieving the objective of this study, annual data between 1990 and 2019 were utilized with the application of FMOLS and Granger causality technique of estimation. It is instructive to report the findings of this research work as follows; firstly, foreign capital inflows and poverty reduction have a long run equilibrium relationship in Nigeria. Furthermore, there is a unidirectional causality flowing from poverty reduction to FDI. Poverty reduction Granger causes FPI. Also, feedback relationship exists between poverty reduction and remittances. This implies that poverty reduction is a strong factor causing the inflows of foreign capital such as FDI, FPI and remittances in Nigeria. Moreover, that majority of the components of foreign capital inflows such as FDI, FPI and remittances contributed immensely to the reduction of Poverty in Nigeria. This implies that foreign capital inflows have the capacity to propel the achievement of Sustainable Development Goal one - poverty reduction in Nigeria. Therefore, it is important for this study to make the following recommendations for the policymakers in Nigeria and by extension Africa that, any time these policymakers set to achieve Sustainable Development Goal one i.e poverty reduction, foreign capital inflows such as remittances, foreign portfolio investment, FDI and external debt should be given priority in their country. And such, the policy that facilitates the sporadic inflows of these foreign capital should be embarked upon by the Nigerian policymakers in particular and African policymakers in general.



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1 Department of Accounting, Osun State University, Osogbo, Nigeria, E-mail: Johnson.olowookere@uniosun.edu.ng.

2 Department of Economics, Accounting and Finance, Bells University of Technology, Ota, Nigeria, E-mail: soolowo@bellsuniversity.edu.ng.

3 Department of Economics, Accounting and Finance, Bells University of Technology, Ota, Nigeria, E-mail: drdotman@yahoo.com.

4 Department of Economics, Accounting and Finance, Bells University of Technology, Ota, Nigeria, Corresponding author: taaderemi@bellsuniversity.edu.ng.