INTRODUCTION:

Nigeria as a country, given her natural resource base and large market size, qualifies to be a major recipient of foreign portfolio investments (FPI). However, the level of FPI attracted into Nigeria is a commonplace (Asiedu, 2003) compared with the resource base and potential need. Spillovers of innovative technology via foreign owned enterprises to internally owned enterprises is of four means: vertical relations between associates and domestic suppliers and consumers, horizontal relations between associates and firms in the same industry in host nation, labour turnover from affiliates to domestic firms, and internationalization of R&D.

The stride of technological transformation in the economy as a whole majorly depends on social and innovative capabilities of the host nation, concurrently with the absorptive competence of other enterprises in the country. Besides, management experts see FPI as having an unequivocal effect on goods and services.

Despite the aforementioned benefits of FPI in host nations, several scholars have contended against it in international business literature. For instance, Busse and Hefeker (2005) argued that FPI runs the peril of abrupt reversal if the economic environment or perception of investors changes, giving rise to financial and economic crises. Alfaro and Chanda (2003) argued that the capabilities of FPI inflows could be sternly hindered if there is deficiency in financial markets, which is widely the case in African countries. UNCTAD (2005) noted that FPI in most Africa nations have progressed much further and faster than integration internally, particularly in institutional, structural and policy trends, and in some cases at its expense.

The acknowledged benefits of FPI appears to be more than the demerits, and this seems to explain the current move of developing countries including Nigeria, seeking to attract FPI into its financial subsector by removing the structural barriers and encouraging foreign investors. Such encouragement involves offer of enticements like exemptions from import duties, income tax holidays and foreign enterprises subsidies. In a seeming drift of long-held stance against FPI, Nigerian government like other developing nations initiated the Structural Adjustment Prgoramme (SAP) encompassing a package of economic policy measures in 1986 to strengthen the gains of economic policy measures and encourage foreign involvement in the economy. Despite these established measures by the Nigerian government, the financial sector has suffered shortages of FPI. In view of this, this study seeks to explore the effects of foreign portfolio investments on the performance of financial sector in Nigeria. The remaining part of this paper is divided as follows: review of literature, research methods, results and discussion, conclusion and recommendation.

REVIEW OF LITERATURE:

Exploring Foreign Portfolio Investment (FPI):

Foreign portfolio investment (FPI) refers to an indirect investment in the foreign firm by simply buying stock of an entity and not getting involved in the major operating activities of the investee firms. FPI is an indirect investment in foreign firms by merely purchasing stock of the firm and not getting involved in the major operating activities of firms. IMF (2008) defined FPI in form of equity and debt issuance which encompasses nations’ fund, depository receipt and direct purchases by foreign investment of less than 10% control. Put differently FPI is a cut across countries and are mostly in securities with the motive of profit maximization rather than management or legal perspective.

FPI have received rather less attention although they are often included implicitly in general discussions about private capital flows (OECD, 2011). Much of the literature on FPI has addressed their economic impacts, both positive and negative, with less attention being given to their social and environmental outcomes. Also there is a concern on whether a relationship actually exist between FPI and the productive activities of the manufacturing sub-sector in Nigeria. However, it is only recently that concerns about the connection between FPI and the manufacturing subsector performance in Nigeria have become prominent.

Increment in FPI has stimulated intense argument as regards its influence on economic growth in Nigeria as well as whether it contributes to the manufacturing subsector performance in Nigeria (Ibrahim and Akinbobola, 2017). Some researchers buttress its positive influence on the manufacturing subsector performance and development of the financial sector. However, critics are doubtful because of its volatile and unstable nature which is unsustainable and could negatively influence the financial sector of the system. FPI as a part of financial and capital account of balance of payments consists of equity securities, debt securities in the form of notes and bonds, money market instruments and financial derivatives.

Worthy of note is the fact that the flow of FPI on the Nigerian capital market has been tremendous. For instance, the Proshare Ecosystem (2017) reported that FPI flow, which stood at 15% in 2007 consistently increased over the years to stand at 67% in 2011. In addition the period between January 2011 and November 2012 witness an increment in the market share of domestic investors from 33.2% to 40.1%. In 2012, January to be specific, the Nigeria capital market stated that foreign investors (FI) accounted for 81% of total capital inflow or purchases in the market throughout 2011. In the same year, FI accounted for 53% of total capital outflows or sells in the market. Consequently, total transactions by foreign investors were N847.9 billion or 67% out of total transaction of N1.3 trillion in 2016 (Proshare Ecosystem, 2017).

Foreign Portfolio Investments and Performance of Financial Sector:

The review of literature suggests that there is the absence or lack of empirical evidence on the nexus between foreign portfolio investment and financial companies’ performance in Nigeria. However, we expect that FPI will positively affect the performance of financial sector in Nigeria. There is therefore the need to carry out an investigation in order to see if a link exists between them. This led to the inclusion of FPI and performance measure of financial companies in the model of our study. Thus, it was hypothesized that foreign portfolio investments have no significant impact on the performance of financial sector in Nigeria.

Theoretical Framework:

The theoretical framework of this paper is anchored on the location theory. By and large, location theory is concerned with territorial distribution of resources within a nation. The location theory explains foreign portfolio investments (FPI) in the framework of the location specific factor differentials. Location theory explains supply (cost factors) and demand (market factor) variables affecting the distribution processes of enterprises. The comparative advantage, availability of raw materials and transportation costs are the main elements of the location theory. The location theory’s description for FPI can be deliberated using the following elements.

First, availability and cost of inputs can buttress the existence of FPI. A firm considers the source of input and cost of production in order to choose the location. Therefore, a firm investing overseas may be attracted by the availability in another country of some inputs, which are scarce at home, or by lower cost of inputs overseas in the area of lower labor cost. The lower labor costs can be the main reasons for FPI in developing countries.

Second, marketing dynamics are the main elements stimulating foreign firms to invest oversea. A firm can get numerous advantages by situating an affiliate firm; it can carry on its business operations efficiently as a result of locating the firm oversea but because the firm can better exploit the local market, tariff obstacles can be circumvented and transportation cost can be abridged.

Third, FPI is stimulated by the existence of trade barriers. Subsidiaries of foreign firms are often setup in another nation that is not yet subject to trade restrictions. Then the products are sold to those markets that have imposed restrictions on the exports of the investing country. Finally, the factor of government of host countries has an effect on FPI, such as lower tax rates, better infrastructure, and greater political stability. These create a favorable investment climate. A firm is often attracted to invest abroad because another country offers advantages.

Empirical Studies:

There is dearth of empirical evidence on the nexus between FPI and performance of the financial sector in Nigeria. Quite a number of empirical studies examined the nexus between FDI and economic growth; FDI and performance of the manufacturing subsector while undermining the effect of FPI on the performance of financial sector in Nigeria.

For instance, in Nigeria, Okoro and Egbunike (2017) assessed the nexus between foreign direct investment, oil revenue and economic growth. Secondary data of GDP, oil revenue and FDI were obtained from the Central Bank of Nigeria (CBN) statistical bulletin for the periods 1981-2015. The statistical analysis via Ordinary Least Square estimation tool indicated that GDP is negatively affected by oil revenue and foreign direct investment. Fredrick, Madu and Ugwuanyi (2016) conducted a comparative analysis between Nigeria and Ghana on the connection between FDI and economic growth during the period 1970 – 2015. The Seemingly Unrelated Regression (SUR) statistical tool was utilized in the analysis of data and the results showed that FDI exerts positive effect on economic growth in Nigeria and Ghana; whereas, there was a significant variation on the connection between FID and economic growth in both countries.

Emmanuel (2015) assessed the relations between FDI and economic growth in Nigeria. The study covered a period of 1981-201 and a bound testing approach via Auto-Repressive Distributed Lags (ARDL) model was employed. The study found that while economic policy had no significant effect, international trade had a strong impact on economic growth.

Adeleke, Olowe and Fasesin (2014) evaluated the effect of FDI on economic growth in Nigeria during the period 1999-2013. Secondary data used was sourced from Annual Reports and Accounts and the CBN statistical bulletin and OLS was used as the estimating technique. Findings showed that economic growth is directly related to inflow of FDI. Najat, Shivee and Normaz (2013) worked on the impact of FDI on economic growth for the Southern Africa Custom Union from 1980-2010. The OLS technique was used and findings suggest a positive and significant impact of FDI on economic growth.

Allege and Ogundipe (2013) ascertained the link between FDI and economic growth in some selected countries in Economic Community of West Africa States (ECOWAS) using the system General Method Moments (GMM) panel estimation technique. The study spanned 1970-2011 and findings showed an insignificant and negative impact of FDI on growth in the selected countries in ECOWAS. Moses, Anigbogu, Okoli and Anyanwu (2013) examined the impact of domestic investment on FDI inflows in Nigeria. The study spanned from 1970-2009 and the decomposed single-linear econometric model and OLS were the estimating techniques. The finding showed a negative relationship between human capital, and market size and FDI inflows while a positive relationship was found between trade openness and natural resources and FDI.

Akinmulegun (2012) evaluated the trends in FDI in Nigeria during the period 1980-2011. The study used a trend analytical approach and it was revealed that there is an undulating terrain in the flows of FDI in Nigeria, partly due to the acclaimed negative nexus between FDI and economic growth. In India, Udaykumar (2012) studied the framework of FDI in retail sector. The study used the porters five force model for FDI in retail sector and regression statistical tool was employed in the analysis of data. Finding showed that FDI in retail sector had enabled India to integrate its economy with that of the global economy.

A study by Okon, Augustine andChuku (2012) empirically examined the relatedness between FDI and economic growth in Nigeria during the period 1970-2008. The OLS and two-stage least squares statistical tool were used and findings revealed a positive feedback from FDI to growth and from growth to FDI. Ekperiware (2011) assessed the sectoral effect of oil and non-oil FDI on economic growth in Nigeria. The study covered from 1970-2008 and data obtained during this period were subjected to OLS technique. The findings indicated that non-oil FDI is more statistically significant and has a higher predictive ability on the Nigeria economy.

A study by Oyatoye, Arogundede, Adebisi and Oluwakayode (2011) on FDI, export and economic growth in Nigeria between 1987-2006 was done by obtaining data from the CBN statistical bulletin. The regression analysis suggests that there is a positive nexus between FDI and GDP. Oji-Okoro and Huang (2011) analyzed the contribution of FDI to the growth of the Nigerian economy during the period 1980-2009. Multiple regression analysis was used and findings revealed a positive nexus between GDP and FDI.

In a cross-country study, Helpman (2006) employed a bivariate VAR modeling tool and found evidence of a positive FDI-led growth for Tunisia, Sri Lanka, Egypt and Nigeria. Besides, a long-run causality between FDI and economic growth was found in both directions for the same set of nations. Li and Liu (2005) applied both single and simultaneous equation techniques to investigate endogenous connectedness between FDI and economic growth in China for 84 nations from 1970-1999 were used and it was found that FDI has a positive effect on economic growth via its interface with human capital. Contrarily, a negative effect of FDI on economic growth was found via its interaction with gap in technology.

Marwah and Tavakoli (2004) tested the impact of FDI on economic growth in Malaysia, Philippines, Indonesia, and Thailand. By means of time-series annual data for the period 1970-1998, findings showed that FDI has positive link with economic growth in all the four countries studied. Akinlo (2004) examined the impact of FDI on economic growth from 1970 to 2001. The error correction model (ECM) results revealed that both lagged foreign and private capitals have small and insignificant influence on economic growth in Nigeria.

RESEARCH METHODS:

In this paper, we adopted the ex-post facto design to investigate the effect of foreign portfolio investments on the performance of financial sector in Nigeria. The contribution of financial sector to Gross Domestic Product (GDP) and FPI were gotten from Central Bank of Nigeria (CBN) statistical bulletin and World Bank Development Indicators (WBDI) for the periods 1981-2016. Given the data of the study the model of the study is given as follows:

FSC = F(FPI) --eq. 1

FSC = b_o+b₁FPI + ut --eq. 2

Where

FPI = Foreign portfolio investment (private investments in portfolios and = bonds);

FSC = Financial Sector contribution to GDP (performance measures

u_t= Error term;

ß₁= estimated parameters.

The statistical tests done are stationarity and unit root, co-integration, OLS, Error Correction Model (ECM), and variance decomposition tests.

EMPIRICAL RESULTS AND DISCUSSION:

Table 1: Result of Descriptive Statistics

	LFSC	LFPI
Mean	7102.400	4.214306
Median	4029.750	4.867490
Maximum	55999.30	7.149760
Minimum	261.0000	1.324419
Std. Dev.	11066.72	1.668456
Skewness	3.007387	-0.366025
Kurtosis	12.88867	1.715198
Jarque-Bera	189.7814	3.097704
Probability	0.000000	0.212492
Sum	241481.6	143.2864
Sum Sq. Dev.	4.04E+09	91.86362

Source: Authors Computation (2018) using Eview 9

The mean of FSC is 7102.40 while the standard deviation is 11066.72. The maximum value for FSC is 55999.30 while the minimum value is 261.00. The mean for FPI is 4.21 and the standard deviation is 1.67. Besides, the highest value is 7.15 while the lowest value is 1.32. The skewness shows values are greater than 0, suggesting that the series are skewed to the right and has a long right tail. More importantly, the Jarque-bera normality test result shows that the residuals are normally distributed in most periods of the study.

Table 2: Summary of ADF Unit Root Test Result

Variables	Level Data	First Difference	Order of Integration
LFSC	-0.064	-3.76*	I(1)
LFPI	-0.65	-6.81*	I(1)

NB: 1. Indicates stationary at the 1 percent level

2. 1 percent critical value -3.65

3. I (1) integrated of order 1.

Source: Author’s computation using Eview

Presented in table 2 is the Augmented Dickey-Fuller Unit Root Test. The ADF unit root test result suggests that the variables are initially non-stationary. However, they became stationary when subjected to first differencingat 1 percent level and are thus said to be integrated of order 1 or I(1).

Table 3: Summary of OLS Result for the Model

Independent Variables	Equations/ Dependent Variables
Independent Variables	1 LFSC
LFPI	0.62 5.02 (0.0000)
R²	0.90
DW	2.09
t critical	1.68

NB: Figures in parenthesis are probabilities

Source: Author’s computation and compilation using Eview 9

The R² which is the coefficient of determination indicate that 90 percent of the total changes in the FSC is explained by the FPI. This is good enough given that only 10 percent was explained outside the model. FPI is statistically significant in explaining the changes in FSC while the Durbin Watson (DW) of 2.09 indicates no serial correlation in the model.

Table 4: Summary of Johansen Cointegration Test Result

Hypothesized	Trace	0.05
No. of CE(s)	Statistic	Critical Value	Prob.**
None *
At most 1
None *	402.9215	159.5297	0.0000
At most 1	0.204650	3.841466	0.6510

Source: Author’s computation using E view 9

The result of the trace statistic indicates co-integrating rejection. An indication of a rejection of the null hypothesis of no co-integration and hence an acceptance of the alternative hypothesis of co-integration. The Max-Eigen result indicates co-integrating equation. Thus, the Johansen Co-integration test result indicates the existence of a long run equilibrium nexus between the variables.

Table 5: Summary of Overparameterize ECM Result for the Equation

Independent Variables	Equations/ Dependent variables
Independent Variables	1 LFSC
LFPI	0.004 0.03 (0.98)
LFPI(-1)	0.56 2.50 (0.0203)
LFPI(-2)	0.03 0.21 (0.8346)
ECM(-1)	-0.98 -6.25 (0.000)
R²	0.91
AIC	0.15
SC	0.65
DW	2.29
t-critical	1.68

Figure in parentheses are probabilities Source: Author’s computation and compilation using E view 9

The Akaike Information Criterion (AIC) and the Schwarz Criterion (SC) were used to select the appropriate lag length. The parsimonious ECM was used for policy purpose and for deleting the insignificant variable from the overparameterized ECM and the model is then estimated. The result of the parsimonious ECM is shown below:

Table 6: Result of Parsimonious ECM for the Equation

Independent Variables	Equations/ Dependent Variables
Independent Variables	1 LFSC
LFPI
LFPI(-1)	0.50 8.91 (0.000)
LFPI(-2)
ECM(-1)	-0.99 -11.31 (0.0000)
R²	0.88
AIC	-0.23
SC	-0.01
DW	2.07
t-critical	1.68

Figure in parenthesis are probabilities Source: Author’s computation using E view 9

The result of the parsimonious ECM for the equation shows that 88 percent of the total variation in the FSC has been explained by FPI. This is a good fit since only 12 percent of the variation was explained outside the model. An increase in the one period lag of FPI by 1 unit increasesFSC by 0.50 units. The result indicates that FPI (-1) with value of 8.91 and probability of 0.0000 is statistically significant in explaining the changes in FSC. The statistical significance of the ECM in the equation provides an indication of a satisfactory speed of adjustment of financial sector to FPI. Furthermore, the result has the probability of 0.0000 which is less than 5 percent (0.05) and a t-calculated of 8.91 which is greater than the t critical of 1.68. This indicates foreign portfolio investments significantly affect the performance of financial sector in Nigeria

Table 7a: Variance Decomposition of LFPI:

Period	LFPI	LFSC
1	9.230889	0.000000
2	7.093025	1.235778
3	11.63239	1.808613
4	9.644046	1.571210
5	17.62075	1.292232
6	17.09897	1.295861
7	17.36384	1.891461
8	25.19141	8.336175
9	23.83347	7.802786
10	22.57585	7.257105

Source: Author’s computation (2018) using E view.

In table 7a, 66 percent of change to FPI was explained by shocks to itself in the first period and it reduced to 23 percent in the last period. Besides, 3 percent of change to FPI was explained by shocks to FSC in the second period and it increased to 7 percent in the last period.

Table 7b: Variance Decomposition of LFSC

Period	LFPI	LFSC
1	9.230889	0.000000
2	7.093025	1.235778
3	11.63239	1.808613
4	9.644046	1.571210
5	17.62075	1.292232
6	17.09897	1.295861
7	17.36384	1.891461
8	18.90972	1.753757
9	18.46453	1.829209
10	20.31059	1.894504

Source: Author’s computation (2018) using E view

In table 7b, shocks to FPI explained 9 percent of changes in FSC in the first period and this increased to 20 percent in the last period. However, shocks to FSC explained 1 percent of changes in FSC in the first period and increased to 2 percent in the last period.

CONCLUSION AND RECOMMENDATIONS:

This paper examined the effect of foreign portfolio investment on the performance of financial sector in Nigeria using the ex-post facto research design. In order to do this, data of foreign portfolio investments and contribution of financial sector to gross domestic product was obtained from Central Bank of Nigeria (CBN) Statistical Bulletin and World Bank Development Indicators spanning 1981-2016. Data obtained was analysed using stationarity and unit root, co-integration, ordinary least square estimation, error correction model, and variance decomposition tests.

The study concluded that foreign portfolio investments significantly affect the performance of financial sector in Nigeria. On the basis of this, it was recommended the government should strengthen the financial sector, specifically the money and capital markets in order to enhance the flow of foreign portfolio investments into this sector in Nigeria. This is because foreign investors can invest on financial or liquid assets with the hope of a sound future return.

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Received on 23.11.2019 Modified on 10.01.2020

Asian Journal of Management. 2020;11(2):201-206.

DOI: 10.5958/2321-5763.2020.00031.1