.


International Journal of Economics and Financial 
Issues

ISSN: 2146-4138

available at http: www.econjournals.com

International Journal of Economics and Financial Issues, 2015, 5(4), 884-888.

International Journal of Economics and Financial Issues | Vol 5 • Issue 4 • 2015884

Causal Relationship among Foreign Reserves, Exchange Rate 
and Foreign Direct Investment: Evidence from Nigeria

Augustine C. Osigwe1*, Maria Chinecherem Uzonwanne2

1Department of Economics and Development Studies, Federal University, Ndufu-Alike, Ikwo, Nigeria, 2Department of Economics, 
Nnamdi Azikiwe University, Awka, Nigeria. *Email: onyi2amaka@yahoo.com

ABSTRACT

This study scrutinized the Granger causality of foreign reserves, exchange rate (EXR) and foreign direct investment (FDI) in Nigeria. The results of 
the augmented Dicky–Fuller and Philip–Perron unit root test for stationary of the variables showed that all the variables were non-stationary at levels, 
but become stationary after first differences. The Johansen co-integration test revealed long-run relationship among the variables. The results of the 
Granger causality test indicated unidirectional causality from EXR to foreign reserves. Consistently from lag one to lag two; unidirectional causality 
existed from FDI to foreign reserves. At lag three, bidirectional causality was discovered between foreign reserves and FDI. Evidence of unidirectional 
causality running from EXR to FDI in lags one and three, was revealed. No causality existed between the duos at lag two. Based on the findings it is 
recommended that the policy makers establish the optimum EXR level that positively promotes foreign reserves and FDI.

Keywords: Foreign Reserves, Exchange Rate, Foreign Direct Investment 
JEL Classifications: C0, C32, F0

1. INTRODUCTION

The Central Bank of Nigeria (CBN) Act 1991 vests the custody 
and management of the country’s foreign reserves in the CBN. 
Nigeria’s foreign reserves are mainly from the proceeds of crude oil 
production and sales. This includes direct sales (Nigerian National 
Petroleum Corporation), petroleum profit tax (Oil Companies), 
royalties, penalty for gas flaring and rentals; and the reserve 
comprises of the federation, the federal government and the CBN 
portions. CBN (2015) noted that Nigeria has taken numerous policy 
initiatives and measures in the management of its foreign reserves. 
Although very little was achieved because the structure in place 
then could not support efficient reserves management, enduring 
lessons could be distilled from the nation’s past experience. It 
continued to note with nostalgia that since the 1970s, Nigerian 
economy has persistently depended on oil as the main source of 
foreign exchange earnings with the attendant cycles of economic 
booms and bursts. However, one of the key challenges for Nigeria 
over the last 8 years, especially under a civilian administration 
was how to manage the phenomenal growth in foreign exchange 
reserves (FOREX) resulting from the sustained high international 

oil prices. According to CBN (2015), foreign reserves in Nigeria 
averaged 774483.82 million Naira from 2000 until 2015, reaching 
an all-time high of 4166778.95 million Naira in December of 2014 
and a record low of 88,635 million Naira in March of 2000.

Exchange rate (EXR) price of a nation’s currency in terms of another 
currency. It is also regarded as the value of one country’s currency 
in terms of another currency. Thus, EXR has two components, 
namely; the domestic currency and a foreign currency, and can be 
quoted either directly or indirectly. In an indirect quotation, the price 
of a unit of domestic currency is expressed in terms of the foreign 
currency whereas in a direct quotation, the converse holds. EXRs 
are determined in the foreign exchange market, which is open to a 
wide range of different types of buyers and sellers where currency 
trading is continuous. A market-based EXR changes if the values 
of either of the two component currencies change. A currency 
will tend to become more valuable when demand for it is greater 
than the available supply and become less valuable each time 
demand is less than available supply. Goldberg and Charles (2015) 
observed that EXRs can influence both the total amount of foreign 
direct investment (FDI) that takes place and the allocation of this 



Osigwe and Uzonwanne: Causal Relationship between Foreign Reserves, Exchange Rate and Foreign Direct Investment: Evidence from Nigeria

International Journal of Economics and Financial Issues | Vol 5 • Issue 4 • 2015 885

investment spending across a range of countries. When a currency 
depreciates, meaning that its value declines relative to the value 
of another currency, this EXR movement has two potential 
implications for FDI. First, it reduces that country’s wages and 
production costs relative to those of its foreign counterparts. All 
else equal, the country experiencing real currency depreciation has 
enhanced “locational advantage” or attractiveness as a location 
for receiving productive capacity investments. By this “relative 
wage” channel, the EXR depreciation improves the overall rate of 
return to foreigners contemplating an overseas investment project 
in this country.

The reasons behind FDI and Multinational Corporations were 
explained by neoclassical economics based on macro-economic 
principles. These principles were based on the classical theory 
of trade in which the motive behind trade was a result of the 
difference in the costs of production of goods between two 
countries, focusing on the low cost of production as a motive for 
a firm’s foreign activity (Ietto-Gillies, 2012). Global FDI inflows 
rose by 11% in 2013, to US$1.46 trillion. FDI flows to developed 
countries remained at a historically low share of global total FDI 
flows (39%) for the 2nd consecutive year. They increased by 12% 
to US$576 billion, but only to 44% of their peak value in 2007. 
FDI to the European Union increased, while flows to the United 
States continued their decline. FDI flows to developing economies 
reached a new high of US$759 billion, accounting for 52% of 
global FDI inflows in 2013. At the regional level, flows to Latin 
America and the Caribbean, and Africa were up; developing Asia, 
with its flows at a level similar to 2012, remained the largest host 
region in the world (UNCTAD, 2014). Nigeria slumped from 
its number one position in 2012 to achieve $5.61 billion in FDI 
inflows in 2013, coming third behind Mozambique and South 
Africa (UNCTAD, 2013). Most scholars believe that FDI inflow 
has a direct impact on foreign exchange reserve, while others hold 
that FDI is mainly invested in the form of physical capital and 
technology, and therefore does not directly contribute to foreign 
exchanges reserve accumulation. Hence the need for this study.

A peep into the literature indicates that studies that have examined 
causality among foreign reserves EXR and FDI remains mixed 
as their method of analysis varied. Also, in the context of the 
dwindling revenue obtained from the main foreign exchange earner 
(crude oil) of Nigeria, it becomes apt to re-examine the form of 
causality that runs among the three variables. The remainder of this 
paper is structured as follows. Section 2 centers on literature review 
while Section 3 briefly describes the theoretical framework and 
methodology adopted in the study. Section 4 presents and discusses 
the empirical results while the study is concluded in Section 5.

2. REVIEW OF LITERATURE

Existing literature on relationship among foreign reserves, EXR 
and FDI stands on divergent strands as evidenced by empirical 
outcomes. For instance, Wenkai and Song (2009) decomposed the 
possible effects FDI could have on FOREX into direct effects and 
indirect effects and mainly estimated the real effect of FDI on the 
growth of FOREX. According to them the study helped to correctly 
understand the role of FDI in raising FOREX. Results from their 

empirical analysis revealed that FDI is an important factor that 
contributes to the growth of China’s FOREX. They asserted that 
during the rapid growth of the reserves in recent years, and contrary 
to the “decreasing contribution” as stated in the nominal effects, 
FDI’s real effect increased. This finding provides a basis to further 
analyze the possible causality that runs between FDI and FOREX 
and implications for policy makers.

Abdullateef and Waheed (2010) extended the study on the 
determinant of foreign reserves by investigating the impact of 
change in external reserve (EXTR) positions of Nigeria on domestic 
investment, inflation rate, and EXR from 1986 to 2006. Using the 
ordinary least square and vector error correction (VEC) estimation 
methods, they found that change in EXTRs in the country only 
influences FDI and EXRs, and no influence was found on domestic 
investment and inflation rates. The results further suggested that 
there is the need for broader reserve management strategies that will 
aim at maximizing the gains from oil export revenue by utilizing 
more of these resources to boost domestic investment.

Yasir et al. (2012) empirically investigated the relationship among 
the broad macro variables such as FOREX, FDI and nominal EXR in 
Pakistan by testing annual data set the period of 1980-2010. In order 
to investigate the stationarity of data at level or at first difference, 
they carried out augmented Dicky–Fuller (ADF) unit root test 
and concluded that EXR, FDI and FOREX are stationary at first 
difference. For the investigation of long-run relationship, Johnson 
co-integration test was applied and the results showed that long-
run relationship exist among the variables. They then proceeded to 
VEC method to examine the short-run association of the variables. 
The obtained results suggested that nominal EXR have a significant 
positive impact on FOREX while FDI have insignificant impact on 
FOREX. Similarly, Osuji and Ebiringa (2012) focused on the long-
run relationship between some selected macroeconomic variables 
and EXTR management factors in Nigeria. The result of their vector 
auto regression (VAR) model indicated that exchange (EXTR) is 
significant in the current year but tends to converge in the previous 
years. On the other hand, the value of the joint significance indicates 
that the current values of gross domestic product (GDP), capital 
goods (CPG), non-CPG and EXCR are most influencing factors 
that determine the current values of EXTR.

Irefin and Yaaba (2012) on the other hand, employed an 
autoregressive distributed lag approach to run a slightly modified 
econometrics “Buffer Stock Model” of Frenkel and Jovanovic 
(1981) to estimate the determinants of foreign reserves in Nigeria 
over the period of 1999-2011, with focus on income, monetary 
policy rate, imports and EXR. The results debunked the existence 
of buffer stock model for reserves accumulation and provided 
strong evidence in support of income as the major determinant of 
reserves holdings in Nigeria.

Using a time series data of between 1980 and 2010, Gokhale 
and Ramana (2013) establish a causal relationship between 
EXR and FOREX in the Indian context. They laid emphasis on 
understanding the impact of FOREX on the EXR. According 
to them, India has accumulated unprecedented FOREX and 
synchronously has been experiencing a large depreciation in its 



Osigwe and Uzonwanne: Causal Relationship between Foreign Reserves, Exchange Rate and Foreign Direct Investment: Evidence from Nigeria

International Journal of Economics and Financial Issues | Vol 5 • Issue 4 • 2015886

Rupee viz., US dollar. This trend prompted their study undertook 
to establish some association between the two trends. Their 
employed unit root test, Johansson co-integration test and VAR 
in the analysis of their data. On the basis of empirical findings, 
they concluded that there is no long-and short-term association 
between EXR and FOREX in the Indian context.

Chowdhury et al. (2014) recently undertook an econometric 
analysis of the determinants of FOREX in Bangladesh, using 
the ADF unit root test to examine stationarity, Engle Granger 
residual based co-integration approach to show the co-integrating 
relationship among the variables, and some diagnostic tests for 
better modeling. The empirical results of their study confirmed the 
existence of strong relationship among FOREX, EXR, remittance, 
home interest rate, broad money, UPI of export and import, and 
per capita GDP. The study suggested that EXR, strong remittance 
related policies, quality items of exports and sustainable GDP can 
keep a substantial and feasible role to make up a healthy amount 
of FOREX for the host country like Bangladesh.

3. THEORETICAL FRAMEWORK AND 
METHODOLOGY

3.1. Theoretical Framework
The core objective of this paper is to examine the casual 
relationship among foreign reserve, EXR and FDI. In the light 
of this and leaning on the reviewed literature, the model of this 
study which is recursive in nature, mimics the empirical studies of 
Yasir et al. (2012) for Pakistan and Osuji and Ebiringa for Nigeria 
(2012) and Gokhale and Ramana (2013) for India.

3.2. Methodology
Two methods of unit root test (ADF and Philip–Perron [PP]) 
were adopted to test for the stationarity of the variables. The 
causality among the variables is traced with the Johansen co-
integration technique and the Granger causality test (GCT). 
Long-run relationship (co-integration) between two variables 
indicates that causality runs in at least one direction. It is one 
of the major thrust of this study to determine not only the long-
run relationship among the variables but also to determine the 
causal relationship (if any) among them. To this effect, the 
pairwise GCT was adopted. When a time series X Granger 
causes another time series Y, it follows that the pattern in X is 
approximately repeated in Y after some time lags. Alternatively 
expressed, a time series X is said to Granger cause a time series 
Y if and only if it can be clearly shown through series of t-tests 
and F-tests on the lagged values of X (with lagged values of 
Y inclusive) that all the lagged X values provide statistically 
significant information about the future values of Y. The null 
hypothesis underlying the GCT is that the variable under study 
(say X) does not Granger-cause the other (say Y). Originally, 
the GCT is based on estimating a pair of regression models in 
the following generic fashion:

Y Y X vt
i

n

i t

j

n

i t j t= + +
=

−
−

−∑ ∑
1

1

1

1α β

 (1)

X Y X vt
i

n

i t

j

n

i t j t= + +
=

−
−

−∑ ∑
1

1

1

2δ λ

 (2)

Where, it is assumed that v1t and v2t are uncorrelated. In the above 
specification, according to Granger (1969), X is said to Granger-
cause Y if βi is not equal to zero and Y will also Granger-cause 
X if λi is not equal to zero. If these two situations simultaneously 
exist, then there is bi-directional causality. The first two scenarios 
represent unidirectional causality and if none of them prevails, 
then it is concluded that there is independence between the two 
variables X and Y. This situation represents the simplest form of 
Granger causality specification which involves only two variables 
(X and Y), dealing with bilateral causality. However, in this study, 
the situation is more complex, involving three variables, thus, 
making it multivariable causality through the technique of VAR. 
Thus, the GCT is based on estimating the following VAR model:

lfres lfres lexch fdi
t i

n

i t i j

n

j t j k

n

k t k t
= ∑ + ∑ + ∑ += − = − = −1 1 1 1α β δ ξ  (3)

lexch lfres lexch fdi
t i

n

i t i j 1

n

j t j k

n

k t k t
= ∑ + ∑ + ∑ += − = − = −1 1 2γ θ η ξ  (4)

lfdi lfres lexch fdi
t i

n

i t i j

n

j t j k

n

k t k t
= ∑ + ∑ + ∑ += − = − = −1 1 1 3ϑ ς ϖ ξ  (5)

Where, it is assumed that ξ1t, ξ2t and ξ3t are uncorrelated. The 
hypothesis of no causality between variables is rejected if the 
F-statistic for the restricted and unrestricted residual sum of squares 
is significant at the conventional 1% or 5% level of significance. 
Given that the interest of this study is in testing for causality, one 
need not present the estimated coefficients of the VAR model 
explicitly (Gujarati and Porter, 2009). Data for this study which 
ranged from 1970 to 2013 were sourced from WDI (2013).

4. EMPIRICAL RESULTS

The results of the ADF and PP unit root test for stationary of the 
variables are presented in Table 1. The results show that all our 
variables were non-stationary at levels, but become stationary 
after first differences. In other words, they are integrated of 

Table 1: ADF and PP unit root results
Variable ADF 

statistic
Order of 

integration
PP 

statistic
Order of 

integration
LRESV −3.600987** I (1) −6.291427** I (1)
LEXCH −5.747095** I (1) −5.747095** I (1)
LFDI −12.11608** I (1) −12.11608** I (1)
**(*) implies significant at 1% (5%) level of significance. ADF: Augmented Dicky-
Fuller, PP: Philip-Perron

Table 2: Results of Johansen’s co-integration test 
(intercept, no trend)
Hypothesized 
number of CE(s)

Eigen 
value

Trace 
statistic

5% critical 
value

P

None* 0.562364 44.51718 29.79707 0.0005
At most 1* 0.198414 9.809721 15.49471 0.0257
At most 2 0.012325 0.520863 3.84146 0.4705
*Denotes rejection of the hypothesis at the 0.05 level



Osigwe and Uzonwanne: Causal Relationship between Foreign Reserves, Exchange Rate and Foreign Direct Investment: Evidence from Nigeria

International Journal of Economics and Financial Issues | Vol 5 • Issue 4 • 2015 887

the same order, that is order one, I(1). Thus, null hypothesis of 
non-stationarity was rejected for all the variables. Given that the 
variables were I(1), we proceeded to test for co-integration using 
the Johansen co-integration test (Table 2).

Table 2 shows that the null hypothesis of no co-integration 
relationships was rejected against the alternative of two co-
integrating relationships at the 5% level. This implies that 
there is long-run relationship among FRES, EXCH and FDI. 
Evidence of co-integration suggest causality, at least, in one 
direction. The error correction model results would then be 
required to ascertain the direction of causation and in detecting 
the differences between the long-run and short-run Granger 
causality.

4.1. GCT Results
The optimal lag length was three for AIC lag selection criteria and 
one for the Schwarz information criterion. It was noted that the 
Granger causality is sensitive to lags. Thus, the empirical findings 
are guided by the optimal lags. The results of the GCT indicate 
unidirectional causality runs consistently from EXR to foreign 
reserves from lag one to lag three. The results also showed that, 
consistently from lag one to lag two, unidirectional causality from 
FDI to foreign reserves. At lag three, we discovered bidirectional 
Granger causality between foreign reserves and FDI. Evidence 
of unidirectional causality running from EXR to FDI in lags one 
and three, was discovered. No causality existed between the duos 
at lag two (Table 3).

5. CONCLUSION

This study examined the Granger causality of foreign reserves, 
EXR and FDI. The results of the ADF and PP unit root test 
for stationary of the variables showed that all our variables 
were non-stationary at levels, but become stationary after first 
differences. The Johansen co-integration technique revealed 

that the null hypothesis of no co-integration relationships 
was rejected against the alternative of two co-integrating 
relationships at the 5% level implying that there is long-run 
relationship among foreign reserves, EXR and FDI. The results 
of the GCT indicated that unidirectional causality runs from 
EXR to foreign reserves from lag one to lag three. Unidirectional 
causality from FDI to foreign reserves was found from lag one 
to lag two. At lag three, we discovered bidirectional Granger 
causality between foreign reserves and FDI. Evidence of 
unidirectional causality running from EXR to FDI in lags one 
and three, was discovered. No causality existed between the 
duos at lag two.

REFERENCES

Abdullateef, U., Waheed, I. (2010), External reserve holdings in Nigeria: 
Implications for investment, inflation and exchange rate. Journal of 
Economics and International Finance, 2(9), 183-189.

CBN. (2015), Reserve Management. Abuja: Central Bank of Nigeria. 
Available from: http://www.cenbank.org/Intops/ReserveMgmt.asp. 
[Last retrieved on 15 Aug 08].

Chowdhury, M.N.M., Uddin, M.J., Islam, M.S. (2014), An econometric 
analysis of the determinants of Foreign exchange reserves in 
Bangladesh. Journal of World Economic Research, 3(6), 72-82.

Frenkel, J., and Jovanovic, B., (1981), Optimal international reserves: 
A stochastic framework”, Economic Journal, 91, 507-514.

Gokhale, M.S., Ramana, J.V. (2013), Causality between exchange rate 
and foreign exchange reserves in the Indian context. Global Journal 
of Management and Business Research Finance, 13(7), 449-456.

Granger, C.W. (1969), Investigating causal relations by econometric 
models and cross-spectral methods. Econometrica Journal of the 
Econometric Society, 37(3), 424-438.

Goldberg, L., Charles, K. (2005), Foreign direct investment, exchange 
rate variability and demand uncertainty. International Economic 
Review, 36(4), 855-873.

Gujarati, D.N., Porter, D.C. (2009), Basic Econometrics. 5th ed. New York: 
McGraw-Hill.

Ietto-Gillies, G. (2012), Transactional Corporations and International 

Table 3: GCT results
Null hypothesis Lag order F-statistic (P) Decision
EXCH does not Granger cause RESV
RESV does not Granger cause EXCH

1 8.99949** (0.0046)
0.16444 (0.6873)

Reject
Accept

EXCH does not Granger cause RESV
RESV does not Granger cause EXCH

2 7.71877** (0.0016)
0.57628 (0.5669)

Reject
Accept

EXCH does not Granger cause RESV
RESV does not Granger cause EXCH

3 6.51409** (0.0013)
0.96533 (0.4203)

Reject
Accept

FDI does not Granger cause RESV
RESV does not Granger cause FDI

1 16.7412** (0.0002)
0.12195 (0.7288)

Reject
Accept

FDI does not Granger cause RESV
RESV does not Granger cause FDI

2 8.67701** (0.0008)
0.02294 (0.2117)

Reject
Accept

FDI does not Granger cause RESV
RESV does not Granger cause FDI

3 7.12448** (0.0008)
3.27594* (0.0327)

Reject
Reject

FDI does not Granger cause EXCH
EXCH does not Granger cause FDI

1 0.20955 (0.6496)
15.7645** (0.0003)

Accept
Reject

FDI does not Granger cause EXCH
EXCH does not Granger cause FDI

2 0.79345 (0.4598)
1.49252 (0.2384)

Accept
Accept

FDI does not Granger cause EXCH
EXCH does not Granger cause FDI

3 0.50195 (0.6835)
6.51336** (0.0013)

Accept 
Reject

**(*) denote rejection of the null hypothesis at 1%(5%) level; P values in parenthesis. GCT: Granger causality test. Source: Authors’ Compilation using Eviews, FDI: Foreign direct 
investment



Osigwe and Uzonwanne: Causal Relationship between Foreign Reserves, Exchange Rate and Foreign Direct Investment: Evidence from Nigeria

International Journal of Economics and Financial Issues | Vol 5 • Issue 4 • 2015888

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