EXPORT AS THE DETERMINANT OF NIGERIAN ECONOMIC GROWTH

1
Abstract
There is no consensus among economists about how export affects productivity. Some argue that
export oriented economies are opened to foreign competition which may lead to closure of local
industries once they cannot withstand the competition. Others argue that export brings about
competition which improves efficiency and productivity. This paper tries to establish and test the
relation between these two variables using Nigeria as a case study. In view of this both
stationarity and cointegration tests are conducted and the results portray that the two have a
long term relationship. It goes further to test for OLS where the result shows that export is a
positive determinant of GDP. Again, the ECM test is conducted and the Error Mechanism
Coefficient is found to be significant.
1.1 BACKGROUND OF THE STUDY
Nigeria like many other Developing African countries started as agrarian economy. The
agricultural produce of the early Nigeria include groundnuts, rubber, timber, cocoa, beans,
palm kernel, hides and skin, to mention just few. These products as declared by Rano and
Tsauni (2006) accounted for over 50 percent of Gross Domestic Product(GDP) and was the
main source of export earning and public revenue. With the crude oil discovery in 1956 and
its exploration in commercial quantity in 1958 however, the oil sector gradually became the
dominant sector in the economy, and almost the sole source of export earning. For instance
in 1970’s petroleum constituted of about 78 percent of Federal Government revenue and
more than95 percent of export earning (World Bank, 2002). With the oil boom in the mid –
1970s (1973) however, the country’s foreign exchange earning raised immensely, which
translated into higher economic growth, to the extent that there was no fear of expenditure in
the part of government even on necessary issues.
With the fall in oil prices in the late 1970s and early 1980s, there ware enormous
macroeconomic problems which include Balance payment deficit high rate of
unemployment, budget deficits, price instability and more importantly less, or even negative
growth. These were the products of the overdependence on oil sector, to the extent that the
economy had to borrow externally to sustain the huge deficit in government expenditure.
These developments came at the stage when the manufacturing share in GDP was relatively

2
very small at an average 5.6 percent for the last half decade, while its share in total export
translated to merely non-noticeable figure of less than 1 percent for the same period.
In response to these enormous problems Structural Adjustment Program (SAP) was
introduced in 1986 in the country. This was to liberalize and diversify the economy. With
SAP in place, several export promotion strategies and policies especially on manufacturing
export were formulated, which include various incentives on export,Research and
Development (R&D) etc. Despite this effort to improve and diversify export the outcomes
were not recommended. This was because the share of manufacturing export remains so low
in the total export earning as compared to the oil sector in particular or primary goods in
general. Evidence shows that the share of manufacturing export as percentage of total export
remains less than 1 percent up to year 2000, as compared to average level of other sub-
Saharan African countries of 6.2 percent of more than 70 percent of Eastern Asian countries.
This is the nature and trend of Nigeria’s export over decades as well as how, from
experience, the fluctuations in the volume of the export affect the level of economic growth.
This paper is divided into three parts. The first part presents the background of the study,
followed by the objectives of the study. In the second part review of theoretical literatures is
presented, after which the empirical test is presented. The last part concludes the paper and
possible recommendations are made.
1.2 OBJECTIVES OF THE STUDY
The objectives of this paper are as follows:
- To test empirically the relationship between export of commodities and economic growth
in Nigeria. In this case empirical data is collected and relationship between
manufacturing export and the GDP is analyzed.
- To analyze the problems facing export of commodities in Nigeria.
- To propose solutions to the problems as my recommendations.
2.0

3
3.0 LITERATURE REVIEW
Exports are the goods and services produced in one country and sell to earn foreign
exchange which can be used to purchase goods and services from another country, thus
leading to specialization (Jafiya, 2004).
Exports are of two broads categories. First, primary commodity exports comprising mainly
agricultural produce and minerals. Second, manufacturing export, which include industrial
finished and semi-finished goods.
In the present day of growing interdependence among the world economies through the
process of globalization and trade liberalization, no country can stand alone or live in
isolation. This is because most, if not all, of trade and development theories show the
certainty of increased productivity and welfare improvement once an economy engages in
bilateral or multilateral trade. Equally important is the nature of the trade as well as the type
of commodities that are traded. This is because as emphasized by Todaro and Smith (2009),
African countries that engage mostly in the export of primary products (what they called
primary-product export dependence) carries with it a degree of risk and uncertainty that few
nations desire. This is important issue because despite strength since 2002, the long-term
trend for prices of primary goods is downward, with the exception of mineral, ores and
metals which witnessed a slide rise in 2003. Hence there is the need to diversify the export
based of their economies to manufacturing export if they are to flourish.
Evidence from Newly Industrialized Economies (NIEs) shows that the export of non-
traditional products, semi-manufactured and manufactured goods are behind the success of
such country like South Korea, Taiwan, Singapore, Hong Kong, Thailand, Brazil and Turkey.
In spite, the recognized importance of export of manufactured goods in achieving economic
growth, Nigeria like many other African countries still depends heavily on the export of
primary goods which stands at 98 percent of the total export earnings in 2005 (Todaro and
Smith, 2009). This menace coupled with her heavy reliance on the importation of
manufactured consumer and capital goods to satisfy her rising consumption aspirations of the
increasing population, and raw materials as well as machineries for its local industries results
in Balance of Payment problem in the country, whereby, the payment made on imports is
increasing as compared to the export receipts for goods and services.Being net export (Export

4
less Import) one of the determinants of National Income, this tragedy of higher import with
fluctuations in the volume of export affects income (GDP) adversely.
Consider the table below:
Selected Domestic and External Macroeconomic Indicators (1986-2003).
YEAR %
GROWTH
IN GDP
MANUFAC.
GOODS (AS
% OF GDP)
MANUFAC.
EXPORT(AS
% OF
TOTAL
EXPORT)
MANUFAC.
IMPORT
(AS % OF
TOTAL
IMPORT)
CAPACITY
UTILIZATION
1986 -3.70 9.00 0.40 19.3 38.8
1987 4.00 9.66 0.20 25.1 40.4
1988 13.9 9.79 0.29 23.1 42.4
1989 2.20 8.24 0.19 20.1 43.8
1990 4.90 8.19 0.20 22.0 40.3
1991 9.40 8.26 0.10 23.5 42.0
1992 -4.50 7.86 0.10 23.0 38.1
1993 -3.70 7.34 0.20 24.0 37.2
1994 -1.30 6.90 0.20 22.2 30.4
1995 -5.20 6.65 0.20 23.2 29.3
1996 0.80 6.48 0.20 28.1 32.5
1997 0.40 6.29 0.40 29.2 30.4
1998 -6.90 5.92 0.53 29.7 32.4
1999 3.40 4.73 0.34 29.4 35.9
2000 3.40 5.95 0.30 29.0 36.1
2001 7.00 5.95 0.84 29.0 39.6
2002 10.10 4.59 2.34 28.9 44.3
2003 5.7 4.08 1.38 23.8 46.2
Source: Rano and Tsauni 2006.

5
The figures above reflect the weak nature of the Nigerian manufacturing export, which stand
at less than 1 percent of total export throughout the period with exception of 2002 and 2003,
despite the various measures introduced by the government to improve the export of the
manufactured goods. These policies include minimum local raw materials utilization, Export
Expansion Grant, establishing export processing zones, duty drawback scheme, to mention
just few.
For Nigeria not to be marginalized in the ongoing globalization process there is the need to
develop the manufacturing sector towards increasing production, not only for domestic
consumption but for export.
Let us now look at the theoretical framework of the study, and later the empirical facts.
2.1-THEORETICAL LITERATURES:
Most, if not all, international trade and development theories portray a positive relationship
between the volume of trade and economic growth, right from classical comparative
advantage model of David Ricardo, the neoclassical model of Heckscher and Ohlin, to the
contemporary endogenous growth models. Although the various models assume that
different factors cause the trade, but the end result portrays improvement in theoutput and
welfare. Let us now examine some of these models to have solid theoretical framework.
The Ricardian Model
This model as developed by David Ricardo (1817) is based on some simplified assumptions.
First, the models assumes that each country involve in the trade has a fixed endowment of
resources, and all units of each particular resource are identical.
Also, the factors of production are completely mobile between alternative uses within a
country, thus, the prices of factors are also the same among these alternative uses. However,
factors are immobile externally, that is, they do not move between countries.

6
This model further employs labor theory of value, thus, the relative value of a commodity is
based solely on its relative labor content. This implies that either other factors are not used in
the production process or they are measured in terms of labor hours.
It also assumes fixed level of technology for the country and full employment of resources,
with constant cost of production, and there is no transportation cost both internally and
externally.
Again, the model assumes differences in the production function (Labor Productivity) in
different countries that are involved in trade, with each production function depicting
constant return to scale. And there is perfect competition in the countries so no government-
imposed obstacles to economic activity.
The model of Comparative Advantage as it is called asserts that “a country should specialize
in the export of the commodities that it can produce at the lowest relative cost”. Germany
may be able to produce cameras and cars as well as fruits and vegetables at lower absolute
unit costs than Kenya, but because the commodity cost differences between countries are
greater for the manufactured goods than for agricultural products, it will be to Germany’s
advantage to specialized in the production of manufactured goods and exchange them for
Kenya’s agricultural products, whereas Kenya which has absolute disadvantage in
theproduction of both goods in relation to Germany may still benefit from trade with
Germany if it will specialize in the production of agricultural produce which the absolute
disadvantage is less than that of manufactured goods (Todaro 2009). It is this phenomenon of
differences in comparative advantage that gives rise to beneficial trade even among the most
unequal trading partners.
However, there are contradicting views on the relationship between exports and productivity.
Some argue that increase in export increases foreign competition, and this may have
detrimental effect on growth of GDP, as it may lead to marginalization or even closureof
factories (Van Biesbrock, 2003). On the other hand, some argue that growth of export brings
about higher growth of GDP through educative process. For example, higher contact with
foreign competitors as a result of export growth can motivate rapid technological changes
and managerial know-how, and enhance efficiency. For instance, Nashimizu and Robinson

7
(1994), accepted the hypothesis that export growth causes productivity growth in Japan,
Turkey, Yugoslavia, and South Korea. They concluded that the larger the share of output that
goes into exports the higher the productivity growth. These contradicting views are the
reasons for conducting the empirical test using Nigeria as a case study.
2.2 EMPERICAL ANALYSIS:
This part presents the empirical evaluation of the effect of manufacturing export on the Gross
Domestic Product in Nigeria.
METHODOLOGY:
The study collects the time series annual data of the Nigerian GDP and the volume of exports
from secondary source, for a period of 31 years (1979-2010). With this data a relationship is
established between GDP and manufacturing exports using linear regression model.
However, using OLS when variables are not stationary at level will result into spurious
regression. This problem can be overcome by cointegration, which imply that even if the
variables are not stationary at level, there may be a linear combination of them which is
stationary. To avoid spurious analysis a unit root test is conducted on the individual data and
then followed by cointegration test to see if there exists a long run relationship between the
two. Although there are many approaches to cointegration , in this research , Engel-granger
two step algorithm is used as follows:
I. Conduct testing for integration (if the variables are integrated of the same order)
ii. Conduct a cointegration test.
The first thing before conducting any test is to show graphically how the variables behave:

8
From the above graphs we can see that in both variables (export and GDP) there are time
trends and drifts.
ECONOMETRIC SPECIFICATION:
The model is presented below:
GDPt =a1 + a2EXPt + Ut
Where GDP = Gross Domestic Product
EXP = Total volume of export
U = Random error term
t = time period
To linearize the data the natural logarithms of both GDP and exports are used. Our model is
now
LnGDPt = a1 + a2lnEXPt
To avoid spurious analysis the Augmented Dickey Fuller Unit Root test is conducted here on
the individual series.
0
40,000
80,000
120,000
160,000
200,000
240,000
2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
GDP
0
20,000
40,000
60,000
80,000
100,000
2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
EXPORT

9
Summary of ADF unit root tests output:
LnEXP: 1. H0: lnEXP has a unit root (at level)
2. H0: lnEXP has a unit root (at 1st difference)
Lag length=1,
Unitroot test (ADF) for export
VARIABLE AT LEVEL AT FIRST DIFFERENCE
ADF test statistic -3.45649 -3.77563
critical value at 5% level -3.568379 -2.967767
Prob. 0.0628 0.0079
R-squared 0.414363 0.491133
D-stat. 2.287609 2.047781
LnGDP: 1. H0: lnGDP has a unit root (at level)
2. H0: lnGDP has a unit root (at first difference)
Lag length=1, with constant, automatic based on AIC.
Unitroot test (ADF) GDP
Variables At level At first difference
ADF test statistic -0.971195 -4.391258
Critical value at 5% level -3.562882 -2.963972
Prob. 0.9338 0.0016
R-squared 0.240701 0.407823
D-stat. 1.887325 1.997254
It is evident from the above that both lnGDP and lnEXP are not stationary at level, even if we
include trend. However, both series are stationary at first difference (I (1)). That is, the first

10
difference of the two series is integrated. This can be seen from the lower value of probability
and increasing value of R2 as a measure of fitness. The variables are conitegrated of the same
order which satisfied the condition for cointegration.
Although we found the series to be integrated of the same order is important to further test for
Cointegation between the two, to see whether they have any long term relationship.
Summary of Cointegration test:
We first obtain our residual series as:
Ut= lnGDPt – a1 - a2lnEXPt
And then we run ADF test on Residuals as our Augmented Engle-Granger test for
cointegration:
The result:
H0: Ut has a unit test (not cointegrated).
Lag length=1,
Cointegration test
VARIABLE STATISTIC
ADF test statistic -2.132067
Critical value at 5% -1.952473
R-squared 0.153977
D-stat. 1.976642
To some extent at 5% level, we can accept that the series are cointegrated in the long term. So,
although the series are stationary at level, however, we can conduct our simple OLS method,
but the parameters explain long term relation not short term, because there is Random Walk in
the short term.

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OLS estimates result summary:
Let us now estimate:
lnGDPt = a1 + a2lnEXPt
H0: a1, a2 = 0
Longrun relationship of the variables
VARIABLE COEFFICIENT STD. ERROR t-STAT. PROB.
LnEXP 0.7178 0.0561 12.7879 0.00
a1 3.8362 0.5460 7.0266 0.00
R-SQURED 0.8450
D- stat 0.2344
From the data above we can see that all the parameters are statistically significant. Also we
can easily see that the export elasticity of GDP is 0.63, showing the rate at which export
determines GDP in Nigeria in the long term. The R2 value is 84% which shows the good of
fitness of the estimated values of GDP.
Error Correction Mechanism:
It is also important to test for ECM to see whether or not a shock in GDP as a result of change
in export in Nigeria could be restored to equilibrium.
Summary of ECM result:
LnGDPt= a1 + a2 lnEXPt + a3 RESIDt-1
Where a3 is the Error Correction coefficient.
Ho: a3=0

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ECM shortrun relationship
VARIABLES COEFFICIENT STD. ERROR t-STAT. PROB.
RESIDt-1 -0.1499 0.0716 -2.0934 0.0455
lnEXP 0.4567 0.06311 7.2371 0.00
a1 0.0187 0.0208 0.9006 0.5293
R-SQUARED 0.6864
D-STAT 1.51065
It is evident that although at 5% level the error correction coefficient is not significant, but
taking its 10% counter value the coefficient is significant. What it tells here is that if there is
shock in GDP that results from change in export the process that the system will go back to
equilibrium is only 14%. This is to say that the correction process is very slow. Besides, the
coefficient is negative as it is expected. This implies that if there is negative shock the total
mechanism will positive, and vice versa.
2.3- PROBLEMS OF EXPORT IN NIGERIA:
Below are some major problems facing exports of commodities in Nigeria.
1. Overdependence on primary goods as the major source of export earning at the expense of
manufactured goods.
2. Closely related to above problem is the vulnerability of the prices of primary exports as
compared to its manufactured counter part. This as pointed by Prebisch-Singer thesis, that
the terms of trade of primary exports has been declining.
3. Poor institutional settings is another problem. The political and economic institutions are
weak. For instance, the banking institutions could provide the required capital for
investment and support exports.
4. Poor infrastructures needed for the production of exportable goods are insufficient.
Amenities such as good roads, stable electricity supply, to mention just two, are lacking.
5. Technological backwardness. Nigeria like many other poor African countries adopts
obsolescent technology that could not support higher productivity.

13
6. Low capacity utilization of the industries as highlighted in the figures presented in
literature review is another problem.
7. High cost of production. This is because of two reasons. One, is the physical distance
from cheaper foreign suppliers. Secondly, the domestic substitutes are more expensive.
4.0 CONCLUSION:
The analysis in this study uses the Ordinary Least Square method to test whether export
determines productivity in Nigeria. To avoid spurious analysis both unit roots and
cointegration tests are used and found that although the individual series are stationary at first
difference, but there exists a long term relationship between the two. The ECM test is also
conducted to see how past, if there is shock in the system, equilibrium will be restored. The
final result shows there is significant positive relationship between the two. Besides, the
problems of exports in Nigeria are presented. Below are the policy recommendations of the
paper.
RECOMMENDATIONS:
Below are the policy recommendations of the paper:
1. The export base has to be diversified to give emphasis to manufactured goods that have
more or less stable terms of trade.
2. The basic infrastructures such as electricity have to be provided sufficiently, either by the
government or private firms.
3. Financial institutions such as banks have to be strengthened through vibrantmonetary
policies. This is to ensure enough investible capital.
4. Nigeria is rich both in terms of resources and agricultural produce. As such the locally
based sources of raw materials should be strengthened, to avoid the use of relatively
expensive foreign raw materials.
5. The industries should import and adopt a relatively modern technology, this is to improve
efficiencyand capacity utilization.
6. Lastly, the primary goods such as crude oil should be processed within the country as
oppose to the current situation, whereby the crude is exported. This will add value to it.

14
REFERENCES
Appleyard, D.R. and Field, Jr. A.J. (1998), International Economics: Theory and
Policy, 3th Edition, Irwin McGraw-Hill, Boston.
Elbadawi, Ibrahim et al (2006), Market Access, Suppliers Access, and Africa’s
Manufactured Exports: A Firm Level Analysis, Journal of International Trade and
Economic Development, Vol. 15, No. 4, 493-523, December 2006.
Gujirati, D. N. and Porter, D.C. (2009), Basic Econometrics, 5th Edition, McGraw-
Hill, Singapore.
Jafiya, A. (2004), ‘Financing Export of Goods and Services and Ensuring Prompt
Payment’, Paper delivered at National Seminar on Export, Organized by Africa
Project Consult Kano.
Jhingan, M. L. (2003), Economic Development and Planning, 35th Edition, Vrinda
Publications.
Kali, Raja et al (2007), Trade structure and Economic Growth, Journal of
International Trade and Economic Development, Vol. 16, No. 2, 245-269, June 2007.
Markusen, J. R. et al (1995), International Trade: Theory and Evidence, McGraw-
Hill, Singapore.
Ogunleye, E. O. and Ayeni, R. K. (2008), The link Between Export and Total
Productivity: Evidence from Nigeria, International Research Journal of Finance and
Economics, ISSN 1450-2887, Issue 22.
Rano, S. A. and Tsauni, A. M. (2006), Topics on the Nigerian Economy, Department
of Economics, Bayero University, Kano.
Reinhart, C. M. and Wickham, p. (1994), Commodity Prices: Cyclical Weakness or
Secular Decline? IMF Staff Papers 41.
Sutcliff, T. (1997), Industrial Development, cited in Rano and Tsauni (2006).
Todaro, M. P. and Smith, S. C. (2009), Economic Development, 10th Edition, Pearson
Addison Wesley, Boston.
World Bank (2000), Can Africa Claim the 21st Century, Washington DC, World
Bank.
World Bank (2002), ‘Group Interim Strategy Update on the Federal Republic of
Nigeria’.

15
APPENDIX 1: Nigerian Export and GDP (1979-2010).
OBS GDP EXPORT
1979 47259.91 11728.08
1980 64201.79 18859.39
1981 59918.54 13499.65
1982 49763.41 8132.95
1983 34950.46 4757.553
1984 28182.54 4185.334
1985 28407.93 4573.223
1986 20210.79 3455.049
1987 23441.33 6706.566
1988 22847.73 5282.838
1989 23843.51 7795.46
1990 28472.47 12365.87
1991 27313.35 10165.15
1992 32710.37 13816.46
1993 21352.76 10061.68
1994 23663.39 9880.815
1995 28108.83 12448.76
1996 35299.15 16994.78
1997 36229.37 16285.65
1998 32143.82 10776.22
1999 34776.04 12831.53
2000 45983.6 24820.55
2001 47999.78 20637.14
2002 59116.85 18839.02
2003 67656.02 28890.97
2004 87845.42 38609.37
2005 112248.6 52237.63
2006 146869 63403.73
2007 165920.9 66616.55
2008 212079.7 92200.79
2009 226892.9 96536.43
2010 232079.7 98240.69
Source: World bank WDI data base 2010

16
APPENDIX 2 Unit root gdp
Null Hypothesis:LNGDP has a unit root
Exogenous:Constant,Linear Trend
Lag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -0.971195 0.9338
Test critical values: 1% level -4.284580
5% level -3.562882
10% level -3.215267
*MacKinnon (1996) one-sided p-values.
Augmented Dickey-Fuller Test Equation
DependentVariable:D(LNGDP)
Method: LeastSquares
Date: 12/15/11 Time:20:27
Sample (adjusted):2 32
Included observations:31 after adjustments
Variable Coefficient Std. Error t-Statistic Prob.
LNGDP(-1) -0.058674 0.060414 -0.971195 0.3398
C 0.476304 0.605329 0.786852 0.4380
@TREND(1) 0.012809 0.004590 2.790413 0.0094
R-squared 0.240701 Mean dependentvar 0.051336
Adjusted R-squared 0.186466 S.D. dependent var 0.195462
S.E. of regression 0.176299 Akaike info criterion -0.541505
Sum squared resid 0.870277 Schwarz criterion -0.402732
Log likelihood 11.39333 Hannan-Quinn criter. -0.496269
F-statistic 4.438067 Durbin-Watson stat 1.887325
Prob(F-statistic) 0.021173
Null Hypothesis:D(LNGDP) has a unit root
Exogenous:Constant
Lag Length: 0 (Automatic - based on SIC, maxlag=7)
t-Statistic Prob.*
5% level -2.963972
10% level -2.621007
DependentVariable:D(LNGDP,2)

17
Date: 12/15/11 Time:20:28
D(LNGDP(-1)) -0.785567 0.178894 -4.391258 0.0001
C 0.031621 0.036184 0.873906 0.3896
R-squared 0.407823 Mean dependentvar -0.009459
Adjusted R-squared 0.386674 S.D. dependentvar 0.244461
APPENDIX 3 export unit root
Null Hypothesis:LNEXPORT has a unit root
Exogenous:Constant,Linear Trend
Lag Length: 1 (Fixed)
t-Statistic Prob.*
5% level -3.568379
10% level -3.218382
DependentVariable:D(LNEXPORT)
Date: 12/15/11 Time:21:31
LNEXPORT(-1) -0.351910 0.101811 -3.456493 0.0019
D(LNEXPORT(-1)) 0.026000 0.158267 0.164282 0.8708
C 2.720825 0.846006 3.216082 0.0035
@TREND(1) 0.043758 0.010206 4.287406 0.0002
S.E. of regression 0.264240 Akaike info criterion 0.299648
Sum squared resid 1.815393 Schwarz criterion 0.486474
Log likelihood -0.494722 Hannan-Quinn criter. 0.359415

18
Null Hypothesis:D(LNEXPORT) has a unit root
Exogenous:Constant
t-Statistic Prob.*
5% level -2.967767
10% level -2.622989
DependentVariable:D(LNEXPORT,2)
Date: 12/15/11 Time:20:29
D(LNEXPORT(-1)) -1.007515 0.266848 -3.775613 0.0008
D(LNEXPORT(-1),2) 0.053980 0.185618 0.290811 0.7735
C 0.069662 0.064596 1.078418 0.2908
APPENDIX 4 long run rship coingration testand shortrun ECM test
DependentVariable:LNGDP
Date: 12/15/11 Time:20:30
Sample:1 32
Included observations:32
C 3.836223 0.545992 7.026151 0.0000
LNEXPORT 0.717831 0.056134 12.78791 0.0000

19
cointegration test
Null Hypothesis:RESID02 has a unit root
Exogenous:None
t-Statistic Prob.*
5% level -1.952473
10% level -1.610211
DependentVariable:D(RESID02)
Date: 12/15/11 Time:20:34
RESID02(-1) -0.286061 0.134171 -2.132067 0.0419
D(RESID02(-1)) 0.000128 0.184573 0.000691 0.9995
R-squared 0.153977 Mean dependentvar -220.6994
Sum squared resid 1.31E+09 Schwarz criterion 20.65351
Durbin-Watson stat 1.976642
E
ECM (shortrun)
DependentVariable:D(LNGDP)
Date: 12/15/11 Time:21:25
C 0.018731 0.020798 0.900605 0.3755
D(LNEXPORT) 0.456716 0.063108 7.237062 0.0000
RESID01(-1) -0.149928 0.071619 -2.093413 0.0455

20
APPENDIX 5 descriptive statisticsof the variables
EXPORT GDP
Mean 25488.62 65868.44
Median 13165.59 35764.26
Maximum 98240.69 232079.7
Minimum 3455.049 20210.79
Std. Dev. 27925.55 62195.57
Skewness 1.645346 1.711519
Kurtosis 4.405698 4.625285
Jarque-Bera 17.07286 19.14498
Probability 0.000196 0.000070
Sum 815635.9 2107790.
Sum Sq. Dev. 2.42E+10 1.20E+11
Observations 32 32

EXPORT AS THE DETERMINANT OF NIGERIAN ECONOMIC GROWTH

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