EXPORTS AND ECONOMIC GROWTH IN NIGERIA: A
CAUSALITY APPROACH
BY
KAREEM OLAYINKA IDOWU
DEPARTMENT OF ECONOMICS
UNIVERSITY OF IBADAN
IBADAN, NIGERIA
E- MAIL : olayinkaidowuus@yahoo.com
Nobility_research@yahoo.com
Telephone:
2348055677538
EXPORTS AND ECONOMIC GROWTH IN
NIGERIA: A CAUSALITY APPROACH
ABSTRACT
We have tried to test the long run causality between Exports and Economic
growth in Nigeria, using Co-integration and Granger Causality tests derived from Errorcorrection Mechanisms. Different techniques had been used by to test and estimate the
unit root of the time series, co-integration as well as the Error-correction models of the
variables.
The research findings show that there is significant feedback causality between exports
and economic growth in Nigeria and single co-integrating vector in the model.
An important Policy implication is that the government should pursue both the inward
and outward oriented industrial strategy.
INTRODUCTION
Nigerian economy is basically an open economy with international transactions
constituting an important proportion of her aggregate economic activity. As a result of
this, the economic prospects and development of the country, like many developing
countries rest critically on international interdependence. The Nigerian economy is
significantly characterized by a large foreign sector. However, over the years, the degree
of openness of the economy has grown considerably.
Prior to Nigeria political independence in 1960, agriculture was the mainstay of the
economy, which supplied nearly all the food needs of the people and accounted for the
largest part of the foreign exchange of the country. But, the advent of crude oil
production and related activities particularly in the 1970s changed the structure of the
Nigerian economy. The bulk of the foreign exchange earnings from this crude oil exports
was used to accelerate the importation of finished goods. The agricultural sector exports
was indeed rendered less competitive overtime due to the overvalued currency,
inappropriate pricing policies and dearth of farm labour caused by the migration of
productive youth to the urban centers in pursuit of wage employment in the nonagricultural sectors.
However, due to the glut in the international oil market in the early 1980s, there
was reduction in the foreign exchange earnings from exports and the import dependent
industrial structure of the country became unsustainable. Due to this, several policy
measures were put in place to correct the situation, including the Stabilization Act of
1982, tight monetary policy and stringent exchange control measure of the 1984, all
prove ineffective. Therefore, the Structural Adjustment Programme was put in place in
1986. And, part of the programme is the export promotion industrialization policy, which
tends to encourage both agricultural and industrial output for exports given the financial
liberalization policy embedded in it.
The exports sector of the economy responded positively to this programme as more
exports were recorded during the period. But, thereafter, there had been unimpressive
performance of the non-oil export, despite the fact that the total output of the country
captured in the Gross Domestic Product (GDP) has been increasing consistently. It is as a
result of this that in this study, the main objective is to examine the causal relationship
between exports and economic growth in Nigeria during the period 1960-2000. This will
be in terms of the application of “Good Practice” of the Johansen’s Multivariate Co-
integration technique because little or no previous studies is specific to Nigeria. In order
to achieve this goal, this study applies the Multivariate co-integration technique proposed
by Johansen (1988) and (1991), and Johansen and Juselius (1990), (1992) and (1994),
which estimates all the possible co-integrating vectors that prevail within a vector of
variables, the study also provides a test on the coefficients penetrating the co-integrating
vectors and provides a test statistic that is more cogent in its efficiency to reject a false
null hypothesis. The study applies co-integration methodology in order to test the long
run values. This research works sheds light on the dynamic structure of the model which
is a pertinent factor in drawing up reasonable conclusion about the speed of adjustment in
the model. Section two of this study deals with the performance of Nigeria’s exports,
while the third and fourth sections describe the methodology and empirical findings of
the study, respectively, and the final section provides the study conclusion and policy
implications.
NIGERIA’S EXPORTS PERFORMANCE
Before the oil boom of 1970s, Nigeria’s economy was mainly an agrarian economy,
which the majority part of its foreign exchange comes from the sales of cash crops such
cocoa, groundnut, coffee, cotton, solid minerals and palm produce. But, due to the oil
boom of 170s, Crude oil then took over from agricultural as the major Foreign exchange
earner to the country and it constitute about 93% of the total exports between 1970 –
1985. And, by 1985 – 1996, it has risen to 96.8%, while by 2000 it got to 99% (Kareem,
2004).
However, the share of non-oil exports in total exports declined from 7.0% in the
period 1970-1985 to about 4% between 1986 and 1988. The decline recorded in the nonoil exports was due to the problems being encountered by the agricultural sector which
was worsened by inappropriate pricing policies, and a dearth of farm labor caused by
rural-urban migration, as well as infrastructural inadequate in the rural areas. The
government made appreciable efforts to resuscitate the non-oil sector of the economy
during the SAP era. But, despite all the measures that were put in place, the performance
of the non-oil export sector has remained unencouraging, as crude oil still remains the
major Nigeria’s export.
On the present trends, the structure of Nigerian economy as reflected I her trade
exports makes it unlikely that the country will be able to take the advantage of increased
liberalization and openness of the economy to achieve trade induced growth. The border
of the country had been thrown open since the independence in 1960 with 32% level of
openness, which later rose to 48%in 1977 during the import substitution era. It got to
68%in 1992 during the SAP period and later increased to its peak of 92% in 2000 due to
the oil imports and exports.
Despite the increase in Nigeria’s total exports earnings, the country has been confronting
a considerable amount balance of payment deficit over the years . thus it is imperative
and worthwhile to examine whether export growth can enhance economic growth to help
reduce this deficit, and also to know if there is casual relationship between exports and
economic growth in Africa
REVIEW OF EMPERICAL STUDIES
There has been increased interest by developing economist in the association between
exports and economic growth in the developing world. The literature shows that some
recent empirical studies that were carried out in this area applied Granger causality test
based on Vector Autoregressive (VAR) models to determine the extent and the direction
of causality between these two variables. But most of the econometric techniques used in
these studies have not been supportive of a direct causal relationship running from
exports to economic growth. Chow (1987) reported feedback causality for 6 countries out
of 8 NICs, unidirectional causality from export to growth was found for one while
independent causality was found for the last country. Hsiao (1987) found evidence of
independent causality from GDP to export was found. Jung and Marshall (1985) got
evidence of unidirectional causality from exports to growth for only 4 countries out of 37.
Ahmed and Kwan (1991) found independent relationship in ASEAN countries. Kwan and
Cotsomotis (1991)got bilateral causality in China for 1952-1988 and independent
causality for the sub period 1952-1978. Most recently; Thornton (1996) discovered that
Granger causality test from error correction models confirmed unidirectional causality
from export to economic growth in Mexico. Ahmed and Hamhirun (1995) found
independent causality between exports and economic growth for 4 out of 5 ASEAN
countries and feedback causality for Singapore. Abhayaratne (1996) in his study of the
causality between foreign trade and GDP growth found no evidence for causality in Sri
Lanka. Ghatak, et al (1997) got evidence to confirm the unidirectional Granger causality
running from exports to GDP Growth in Malaysia. Wadud (2000) also discovered that
there is unidirectional causality from exports to economic growth in Bangladesh.
Therefore, for the development strategies of Nigerian, the achievement of causality
has an important policy implication. In the sense that the import led growth strategy is
appropriate for the country if export growth causes export growth (export GDP) , but if
economic growth causes export growth (GDPexport) then a certain level of economic
growth may be a prerequisite to extend its exports (Chow( 1987), Moschos (1989)), due
to the fact that economic growth may help achieve efficient allocation of resources
according to comparative cost advantage and realization of economies of scale which
lower the cost of exportable which make exports more competitive in international
markets while bilateral causality can reinforce each other.
RESEARCH METHODOLOGY
The study set up an econometric model to test the long run relationship and direction
Causality between exports and economic growth (GDP shall be used to measure
economic growth). Many of the Macroeconomic time series are characterized by a unit
root so that their first differences are stationary (Engel and Granger, 1987); Nelson and
Ploser, (1982). If a statistical test, like co-integration establishes co-movements in these
time series, the residuals from the regression can be used as error correction terms in the
dynamic first-difference equation (Ahmed and Harnhirun, (1995). Thus, given two time
series that are integrated at order 1, i.e. I(i), and co-integrated, then there must exist
Granger causality in at least one direction in the I(0) variables (Engle and Granger,
(1987) and hence a VAR model can be prepared with an error correction term for
doubled co-integrated I(0) time series to cover the short run dynamics and to decrease the
chance of observing ‘spurious regression’ in terms of the levels of data or their first
differences. Therefore, after testing the stationary and co-integration attributes of the
variables, the study shall test for Granger causality with the error-correction model
between exports growth and economic growth (in terms of GDP growth) of the country.
What we shall first do under the methodology here is to test the order of integration, i.e.
the stationarity of the variables of the natural logarithm of the level of exports, (LnExp)
and GDP (LnGDP). Two methods are used in practical application to test stationarity
allowing the chance of autocorrelation: Augmented Dickey-Fuller (ADF) test (Dickey
and Fuller, 1981) and the non-parametric adjustment Phillip-Perron test (Phillip and
Perron, (1988). The Augmented Dickey-Fuller test requires the following as.
GDPt =  + t +  GDPt-1 +  ∑ GDPt-1 + е t -------------------------------- (1)
EPt =  + t +  EPt-1 +  ∑ EPt-1 + е t --------------------------------------(2)
Where Lt in the two equations are assumed to be identically independently distributed
random variable. This ADF statistic test the null hypothesis that the time series has a unit
root, i.e. r = 0, under the alternative hypothesis of stationary time series. After this
stationarity test, e now test for co-integration theory in the issue of Johansen’s Trace and
Max-Eigen statistic estimation approach (Johansen, (1988); Johansen and Juselius, 1990,
and Johansen, 1991). The Johansen’s test for the multivariate co-integration approach is
based on the following econometric model of the VAR process:
GDP = oy + β1yt - y EPt-1 + ∑ r1y EPt-1 + ywt +еt --------------------------(3)
where EPt = ( yt, zt ), GDPt is an My * 1 vector of jointly determined endogenous I(1)
variables, EPt is an Mt * 1 vector of exogenous I(1) variables:
Zt = βoz + ∑ r1z  EPt-1 + zWt + Vt -------------------------------------------------(4)
Wt is a q x 1 vector of I(0) variables excluding the interception and trends, the stochastic
term vector et and vt fulfill.
Ut = ( vtet )  iid ( 0,  )
Where Ω is a symmetric positive – definite matrix, the stochastic term Ut are distributed
independently of Wt: E(Ut/Wt) = 0, the intercept and trend coefficients, β0y and β1y are My
x 1 vectors: πy is the My x M long-run multiplier matrix, m = mx + my, r1y, …., r(p-1)y are
My x M coefficient matrices capturing the short-run dynamic effects and φy is the My λ q
matrix of coefficients on the I(0) exogenous variables. The Augmented Engle-Granger
test (Enlge and Granger, 1987), Co-integrating Regression Durbin-Watson (CRDW) test
Sargen and Bhargawa, 1983) and Engle-Granger test, are applied in testing order of
integration of the co-integrating regression error term. The Granger causality test would
be either unidirectional or feedback and must exist in at least the I(0) variables if cointegration is established.
Furthermore, another test involved to ascertain whether there exist causality between
exports and GDP growth. The Granger Representation Theorem states, if two time series
are both I(0) and are co-integrated, then a dynamic error-correction representation would
prevail and vice versa. Thus, assuming the integration of order I(1) and Co-integration
between the logarithm of the levels of exports and GDP, the following ECM, based on
Engle and Granger (1987) is formulated to carryout the standard Granger causality test:
lnGDPt = o + ∑ j lnGDPt-1 + ∑ Pi lnEPt-1 +  ECTt-1 + еt -----------------(5)
lnEPt = β0 + ∑ βi lnGDPt-1 + ∑ λj lnEPt-1 +  ECTt-1 + еt ---------------------(6)
Where  depicts the difference operator
, еt implies a non zero serially independent
random stochastic term ECTt-1and is the error-correction term obtained from the long-run
co-integrating regression. The dynamic in the short run, which are inevitable to the long
run equilibrium attainment, can be given by the causal relationship between variables.
The Error Correction Model (ECM) method allows the distinction between ‘short run’
and ‘long run’ Granger causality. When variables are co-integrated in the short un, the
differences from the long run equilibrium will feedback on the changes in the dependent
variable so as to force the movement towards the long run equilibrium; if the dependent
variable is caused directly by this long run equilibrium error, then it is reacting to this
feedback and if not, it is responding only to the short-run shocks to the stochastic
environment (Hassan and Tufte, 1998). The short run adjustment coefficient, derived by
estimating the coefficient of the lagged error correction term, represents the ratio by
which the long run disequilibrium in the dependent variable is being corrected in each
short-run period. The ‘short run’ causal effects are indicated through the significance of
the F-tests of the ‘differenced’ independent variables whereas the significance of that ttest of the lagged error-correction term provides the long run causal relationship.
THE EMPIRICAL FINDINGS
We are going to test for the stationarity and co-integrating properties of our selected
variables in the light of the empirical methodology. We used annual time series data
from 1960-2000, and they are obtained from Federal Office Statistics (FOS) and Central
Bank of Nigeria (CBN) statistical Bulletin. The ADF test and Phillip – Perron test for
unit root as a formal test are applied to test the stationary property of the variables. Table
1 shows the ADF test results for the variables both at level and first differences.
These results indicate that we accept the null hypothesis at 5% level of
significance for the variable at level, but we reject the null hypothesis that there is unit
root at the first difference at 5% level of significance. Therefore, we draw the conclusion
that at first differences the GDP and exports are stationary. Hence, the results confirm
that all variables are integrated of order one at levels but integrated of order zero at first
differences, i.e. lnEPI(1), InGDPI(1), DInEPI(0) and DInGDPI(0). The PhillipPerron stationarity tests are shown in table 2. This results support what we got form the
ADF test.
Thus, we proceed to the co-integration test. Here, we used Johansen maximum
likelihood approach to test for co-integration in the model. Table 3. Shows the results of
the co-integration test based on the maximum Eigen value and trace statistic. Both test
statistics indicate that maximum Eigen value and trace statistic are well above both the
corresponding 5% level of significance, which indicates that the variables are cointegrated and that there will be no loss of information in the long run. These results also
confirm a single co-integrating vector and that there is a genuine long-run relationship
between exports and GDP growth.
TABLE 1:
Augmented Dickey- Fuller Test for Unit root
Test Statistic
Variable
Level
First difference
LnGDP
-2.11653
-4.3054
lnEP
-2.2981
-7.3124
Note: The 5% critical value for the ADF Statistic approximately 3.5266 for levels and
-3.5298 for first difference. These critical values are computed from McKinnon(1996).
TABLE 2
Phillips – Perron Test for Unit root
Test Statistic
Variable
Level
First difference
lnGDP
-2.0779
-4.3414
lnEP
-2.2981
-7.7153
Note: The 5% critical value for Phillips- Perron statistic is approximately -3.5266 for
levels and -3.5298 for first differences. These critical values are computed from
McKinnon (1996).
TABLE 3
Results of Johansen’s Co-integration Test
Hypothesis
Maximum Eigenvalue
Null
Alternative
Statistic Critical value at 5%
r=o
r=1
51.7980
14.07
3.6337
3.76
r1
r=2
Trace test statistic
Statistic Critical value at 5%
55.4317
15.41
3.6337
3.76
Table 4 shows the results of the Granger causality test from Error – correction Model
(ECM). This suggest that the coefficient of the error-correction term (ECT) for equation
(5) and (6) are statistically significant with both negative signs, and that the f-statistic
indicates that it is significant at 5% level for both equations. Therefore, this means that
as Exports growth Granger cause economic growth, so economic growth Granger cause
exports, hence there is a bilateral or feedback causality between the variables. Thus, the
results support export/GDP – led growth strategy hypothesis, that is, both exports growth
and economic growth cause change in one another. And this support the results that
Chow (1987) got for 6 countries out of 8 NIEs as well as confirm what Ahmed and
Harnhirun (1995) got for Singapore and that of Kwan and Cotsomotis (1991) in China for
1952-1988.
TABEL 4.
Granger Causality Test From Error - Correction Model
Dependent Variable Coefficient for ECT T- Statistic for ECTt-1
-2.4306
lnGDP
-5.0470
lnEP
* means significant at the 5% level
-3.6397*
-9.2082*
F-statistic for
∑ lnEPt-1
13.2474*
84.7909*
Furthermore, the estimated coefficients for the ECT -2.4306 and -5.0470 represent the
ratio by which the long-run disequilibrium in the dependent variables GDP and exports,
respectively, is being corrected in each short-run period.
CONCLUSION AND POLICY IMPLICATIONS
The aim of this paper is to test and estimate the long-run behavioural relationship
between exports and economic growth in Nigeria during the period 1960-2000. The
approach of co-integration has been applied as a pivot test to Granger tests of causality
from the error – correction model between the two variables. Out results show that both
variables have unit roots at levels and were only stationary at first difference. These
results support a stable long run relationship between exports and economic growth, and
thus, yield evidence of a single co-integrating vector.
Furthermore, a significant and positive feedback Granger causal relationship
exists between exports and economic growth in the long period in Nigeria. These results
attest to the fact that exports and GDP growth are an important aspect of economic
growth and development in Nigeria. And that the export promotion industrialization
strategy of the government should be intensifying since it has the potential and ability to
translate into positive multiplier in the economy. Also GDP growth is a factor that can
accelerate economic activities in all sectors of the economy and which will enhance the
country’s exports in the long run and lead to stable macroeconomic environment and
growth sustainability. Therefore, export policy and promotion measures as well as
outward oriented development strategies adopted by the present government should be
intensified aggressively so as to attain sustainable economic growth and development.
However, an important aspect of this paper is the forcasting conclusion which
indicates that there is feedback causality between exports and economic growth, with the
policy implication that if economic growth of the country decline in the future, then there
is the possibility that export would augment and resuscitating it, vice versa.
REFERENCES
Abhayaratne, A.P.S., (1996), “Foreign Trade and Economic Growth Evidence
from Sri-Lanka, 1960-1992, Applied Economics Letters, 3: 567-570.
Ahmed, J., and S., Harnhinen, (1995), “Unit roots and co-integration in
Estimating Causality between Exports and Economic growth:
Empirical Evidence from The ASEAN countries,” Economic Letters,
49: 320-334.
Ahmed, J., and A.C.C., Kwan, (1991), “ causality between Exports and Economic
Growth,” Economic Letters, 37: 239-248.
CBN
“Statistical / Bulletin” several years.
Chow, P.C.Y., (1987), “Causality Between Export Growth and Industrial
Performance: Evidence from NIC,” Journal of Development
Economics, 26: 55-63.
Dickey, D.A., and D.W., Fuller,(1981), “The likelihood ratio Statistics for
Autoregressive Time-series with a unit root,” Econometrica, 49:
1057-1072
Engle, R.F., and C.W.J., Granger (1987). “Co-integration and Error Correction:
Representation, Estimation and Testing,” Econometrica, 55: 251276.
Ghatak, S.,C. milner and U.utkulu, (1997), “Exports composition and Growth: Cointegration Causality Evidence From Malaysia,” Applied Economics,
29: 201-224.
Hsiao, M.C.W., (1987), “ Testing Causality and Exogeneity Between Exports and
Economic Growth: The case of the Asian NICs”. Journal of Economic
Development, 12: 141-160.
Johansen, S., (1988), “Statistical Analysis of Co-integrating vectors,” Journal of
Economic Dynamics and control, 229 – 255.
-
(1991), “Estimation and hypothesis testing of co-integration vectors,
in Gaussian vector autoregressive models, Econometrica, 59. 15401580.
Johansen, S., and K., Juselius,(1990), “Maximum likelihood estimation and
inference on Co-integration with applications to demand for money.”
Oxford Bulletin of
Economics and Statistics, 52. 150-210.
-
(1992), “Testing structural Hypothesis in a Multivariate cointegration
analysis
of the PPP and UIP for UK,” Journal of Econometrics, 53: 211-244.
-
(1994), “Identification of the long-run and the short-run structure. An
Application to the ISLM model”, Journal of Econometrics, 63: 1-36.
Jung, W.S., and P.J., Marshal, (1985), “Exports, Growth and Causality in
Development Countries,” Journal of Development Economics, 18: 112.
Kareem, O.I. (2004), “WTO Agreement and Nigeria’s Exports,”An M.sc thesis
submitted To the Department of Economics, University of Ibadan.
Kwan, A.C.C., and J., Cotsomotis (1991), “Economic Growth and the Expanding
Export Sector: china 1952-1985”, International Economic Review, 5:
105-117.
Moschos, D., (1989), “ Export Expansion, Growth and the level of Economic
Development: An Empirical Analysis,” Journal of Development
Economics, 30: 93-102.
Nelson, C.F., and C.I., Plosser, (1982), “Trends and Random walks in
Macroeconomic Time-series-some Evidence and implications,”
Journal of Monetary Economics, 10: 139-162.
Phillips, P.C.B., and P.; Perso, (1988) “Testing for a unit root in Time-series
regression,” Bimetrika, 75: 332-348.
Thornton, J., (1996), “Co-integration, causality and Export-led Growth in Mexico,
1895 -1992, Economics Letters, 50: 413-416.
Wadud, M.A, (2000) ,” Co-integration and Error Correction Models in Estimating
Causality Between Exports and Economic Growth in Bangladesh.