export as the determinant of nigerian economic growth

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

1

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

2

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

3

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.

4

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.

5

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

6

(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:

7

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

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

8

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

LnGDPt = a1 + a2lnEXPt

To avoid spurious analysis the Augmented Dickey Fuller Unit Root test is conducted here on

the individual series.

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

9

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

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

10

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.

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:

11

LnGDPt= a1 + a2 lnEXPt + a3 RESIDt-1

Where a3 is the Error Correction coefficient.

Ho: a3=0

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.

12

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.

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.

13

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.

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.

14

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’.

APPENDIX 1: Nigerian Export and GDP (1979-2010).

OBS GDP EXPORT

1979 47259.9111728.0

8

1980 64201.7918859.3

9

1981 59918.5413499.6

51982 49763.41 8132.95

1983 34950.464757.55

3

1984 28182.544185.33

4

1985 28407.934573.22

3

1986 20210.793455.04

9

1987 23441.336706.56

6

1988 22847.735282.83

81989 23843.51 7795.46

1990 28472.4712365.8

7

1991 27313.3510165.1

5

1992 32710.3713816.4

6

15

1993 21352.7610061.6

8

1994 23663.399880.81

5

1995 28108.8312448.7

6

1996 35299.1516994.7

8

1997 36229.3716285.6

5

1998 32143.8210776.2

2

1999 34776.0412831.5

3

2000 45983.624820.5

5

2001 47999.7820637.1

4

2002 59116.8518839.0

2

2003 67656.0228890.9

7

2004 87845.4238609.3

7

2005 112248.652237.6

3

2006 14686963403.7

3

2007 165920.966616.5

5

2008 212079.792200.7

9

2009 226892.996536.4

3

2010 232079.798240.6

9Source: World bank WDI data base 2010

APPENDIX 2 Unit root gdp

16

Null Hypothesis: LNGDP has a unit rootExogenous: Constant, Linear TrendLag Length: 0 (Automatic - based on SIC, maxlag=7)

t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -0.971195 0.9338Test critical values: 1% level -4.284580

5% level -3.56288210% level -3.215267

*MacKinnon (1996) one-sided p-values.

Augmented Dickey-Fuller Test EquationDependent Variable: D(LNGDP)Method: Least SquaresDate: 12/15/11 Time: 20:27Sample (adjusted): 2 32Included observations: 31 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

LNGDP(-1) -0.058674 0.060414 -0.971195 0.3398C 0.476304 0.605329 0.786852 0.4380

@TREND(1) 0.012809 0.004590 2.790413 0.0094

R-squared 0.240701 Mean dependent var 0.051336Adjusted R-squared 0.186466 S.D. dependent var 0.195462S.E. of regression 0.176299 Akaike info criterion -0.541505Sum squared resid 0.870277 Schwarz criterion -0.402732Log likelihood 11.39333 Hannan-Quinn criter. -0.496269F-statistic 4.438067 Durbin-Watson stat 1.887325Prob(F-statistic) 0.021173

Null Hypothesis: D(LNGDP) has a unit rootExogenous: ConstantLag Length: 0 (Automatic - based on SIC, maxlag=7)

t-Statistic Prob.*


5% level -2.96397210% level -2.621007


Augmented Dickey-Fuller Test EquationDependent Variable: D(LNGDP,2)Method: Least SquaresDate: 12/15/11 Time: 20:28

17

Sample (adjusted): 3 32Included observations: 30 after adjustments


D(LNGDP(-1)) -0.785567 0.178894 -4.391258 0.0001C 0.031621 0.036184 0.873906 0.3896

R-squared 0.407823 Mean dependent var -0.009459Adjusted R-squared 0.386674 S.D. dependent var 0.244461S.E. of regression 0.191450 Akaike info criterion -0.404040Sum squared resid 1.026287 Schwarz criterion -0.310627Log likelihood 8.060598 Hannan-Quinn criter. -0.374156F-statistic 19.28314 Durbin-Watson stat 1.997254Prob(F-statistic) 0.000146

APPENDIX 3 export unit root

Null Hypothesis: LNEXPORT has a unit rootExogenous: Constant, Linear TrendLag Length: 1 (Fixed)

t-Statistic Prob.*


5% level -3.56837910% level -3.218382


Augmented Dickey-Fuller Test EquationDependent Variable: D(LNEXPORT)Method: Least SquaresDate: 12/15/11 Time: 21:31Sample (adjusted): 3 32Included observations: 30 after adjustments


LNEXPORT(-1) -0.351910 0.101811 -3.456493 0.0019D(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

R-squared 0.414363 Mean dependent var 0.055014Adjusted R-squared 0.346790 S.D. dependent var 0.326943S.E. of regression 0.264240 Akaike info criterion 0.299648Sum squared resid 1.815393 Schwarz criterion 0.486474Log likelihood -0.494722 Hannan-Quinn criter. 0.359415F-statistic 6.132037 Durbin-Watson stat 2.287609Prob(F-statistic) 0.002692

18

Null Hypothesis: D(LNEXPORT) has a unit rootExogenous: ConstantLag Length: 1 (Fixed)

t-Statistic Prob.*


5% level -2.96776710% level -2.622989


Augmented Dickey-Fuller Test EquationDependent Variable: D(LNEXPORT,2)Method: Least SquaresDate: 12/15/11 Time: 20:29Sample (adjusted): 4 32Included observations: 29 after adjustments


D(LNEXPORT(-1)) -1.007515 0.266848 -3.775613 0.0008D(LNEXPORT(-1),2) 0.053980 0.185618 0.290811 0.7735

C 0.069662 0.064596 1.078418 0.2908

R-squared 0.491133 Mean dependent var 0.012133Adjusted R-squared 0.451989 S.D. dependent var 0.453221S.E. of regression 0.335509 Akaike info criterion 0.751362Sum squared resid 2.926726 Schwarz criterion 0.892807Log likelihood -7.894752 Hannan-Quinn criter. 0.795661F-statistic 12.54693 Durbin-Watson stat 2.047781Prob(F-statistic) 0.000153

APPENDIX 4 long run rship coingration test and shortrun ECM test

Dependent Variable: LNGDPMethod: Least SquaresDate: 12/15/11 Time: 20:30Sample: 1 32Included observations: 32


C 3.836223 0.545992 7.026151 0.0000LNEXPORT 0.717831 0.056134 12.78791 0.0000

R-squared 0.844986 Mean dependent var 10.78637Adjusted R-squared 0.839819 S.D. dependent var 0.737404S.E. of regression 0.295129 Akaike info criterion 0.457652Sum squared resid 2.613031 Schwarz criterion 0.549260

19

Log likelihood -5.322429 Hannan-Quinn criter. 0.488017F-statistic 163.5306 Durbin-Watson stat 0.234422Prob(F-statistic) 0.000000

cointegration test

Null Hypothesis: RESID02 has a unit rootExogenous: NoneLag Length: 1 (Fixed)

t-Statistic Prob.*


5% level -1.95247310% level -1.610211


Augmented Dickey-Fuller Test EquationDependent Variable: D(RESID02)Method: Least SquaresDate: 12/15/11 Time: 20:34Sample (adjusted): 3 32Included observations: 30 after adjustments


RESID02(-1) -0.286061 0.134171 -2.132067 0.0419D(RESID02(-1)) 0.000128 0.184573 0.000691 0.9995

R-squared 0.153977 Mean dependent var -220.6994Adjusted R-squared 0.123762 S.D. dependent var 7295.385S.E. of regression 6829.034 Akaike info criterion 20.56009Sum squared resid 1.31E+09 Schwarz criterion 20.65351Log likelihood -306.4014 Hannan-Quinn criter. 20.58998Durbin-Watson stat 1.976642

ECM (short run)

Dependent Variable: D(LNGDP)Method: Least SquaresDate: 12/15/11 Time: 21:25Sample (adjusted): 2 32Included observations: 31 after adjustments


C 0.018731 0.020798 0.900605 0.3755D(LNEXPORT) 0.456716 0.063108 7.237062 0.0000RESID01(-1) -0.149928 0.071619 -2.093413 0.0455

20

R-squared 0.686389 Mean dependent var 0.051336Adjusted R-squared 0.663988 S.D. dependent var 0.195462S.E. of regression 0.113302 Akaike info criterion -1.425746Sum squared resid 0.359449 Schwarz criterion -1.286973Log likelihood 25.09906 Hannan-Quinn criter. -1.380510F-statistic 30.64124 Durbin-Watson stat 1.510645Prob(F-statistic) 0.000000

APPENDIX 5 descriptive statistics of 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

21

export as the determinant of nigerian economic growth

Business

export of commodities

share of manufacturing

than95 percent of export

percentage of total

main source of export

export oriented economies

export promotion strategies

trend of nigerias export