This study examines the factors that determine the export performance of three major agricultural exportable commodities of cocoa, rubber and palm-kernel in the context of liberalization. Using time series data covering thirty three years and to avoid spurious result, error correction model was applied in the analysis. The unit root test is in line with the a priori expectation that macroeconomic variables are not stationary at their level. Virtually all the variables tested were differenced once before attaining stationarity. Each of the three equations indicated that the dependent variables cointegrated with their arguments at 1 percent level. There is the existence of short term and long term equilibrium relationships between the dependent variables and their determinants. The results of the parsimonious error correction specifications showed that the previous year’s output and the net value of world trade negatively affect cocoa exports at 1 percent level while the previous year’s GDP positively contributes to cocoa exports at 5 percent. The lagged price ratio reduces rubber exports significantly at 5 percent but the real exchange rate significantly increases the export performance of rubber at 10 percent level. The previous year’s exports of palm kernel and the real GDP contributed positively to palm-kernel exports at 5 percent level while the lagged premium and palm kernel output negatively contributed to its export at 5 percent and 10 percent respectively. Promotion of agricultural exports is essential to reduce the burden of dependence on oil exportsAgricultural exports, Cointegration, ECM, Nigeria, Agricultural and Food Policy, Community/Rural/Urban Development, Crop Production/Industries, Demand and Price Analysis, Farm Management, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Industrial Organization, International Relations/Trade, Marketing, Productivity Analysis, Research and Development/Tech Change/Emerging Technologies,

Yusuf, Sina A.

Yusuf, W.A.

English

Research Papers in Economics

AAAE Conference proceedings (2007) 469-472 
Determinants of Selected Agricultural Export Crops in Nigeria: An Ecm Approach 
S.A. Yusuf and W.A. Yusuf 
Department of Agricultural Economics, University of Ibadan, Ibadan 
Abstract 
This study examines the factors that determine the export performance of three major agricultural exportable 
commodities of cocoa, rubber and palm-kernel in the context of liberalization. Using time series data covering 
thirty three years and to avoid spurious result, error correction model was applied in the analysis. The unit root 
test is in line with the a priori expectation that macroeconomic variables are not stationary at their level. Virtually 
all the variables tested were differenced once before attaining stationarity. Each of the three equations indicated 
that the dependent variables cointegrated with their arguments at 1 percent level. There is the existence of short 
term and long term equilibrium relationships between the dependent variables and their determinants. The results 
of the parsimonious error correction specifications showed that the previous year’s output and the net value of 
world trade negatively affect cocoa exports at 1 percent level while the previous year’s GDP positively 
contributes to cocoa exports at 5 percent. The lagged price ratio reduces rubber exports significantly at 5 percent 
but the real exchange rate significantly increases the export performance of rubber at 10 percent level. The 
previous year’s exports of palm kernel and the real GDP contributed positively to palm-kernel exports at 5 
percent level while the lagged premium and palm kernel output negatively contributed to its export at 5 percent 
and 10 percent respectively. Promotion of agricultural exports is essential to reduce the burden of dependence on 
oil exports 
Key words: Agricultural exports, Cointegration, ECM, Nigeria 
 
Introduction 
In the 1960’s, Nigeria economy was largely sustained, 
at least from the point of view of off shore 
commitments, by the export earnings from basic 
agricultural and mineral commodities. The export list 
of the country within this period comprised groundnut, 
cocoa beans, palm oil and kernel, cotton, rubber, 
ginger, copra, hides and skins, timber, zinc, columbite, 
tin and lead. However, the commencement of large 
scale exploitation and exportation of crude petroleum 
in the early 1970s and the huge inflow of foreign 
exchange revenues therefrom diverted the attention of 
the government and a large percentage of the 
agricultural producers into other activities aimed at 
exploiting the economic boom. This development 
heralded the decline in agricultural production and the 
resultant drop in volume and value of the traditional 
export commodities (Ihimodu, 1993). The introduction 
of SAP in 1986 and a policy shift towards support for 
growth of traditional non-oil exports, led to an 
appreciable increase in exports. However, this growth 
of non-oil exports has not been consistent. Infact, the 
contribution of the non-oil sector to foreign earnings 
remain abysmally low representing less than 1% 
between 2000 and 2004 (CBN, 2004). Even then, 
primary agricultural produce remains a formidable 
non-oil sector contributing about 33% of total non-oil 
foreign earnings and second only to semi-
manufactured products with 48.9% (CBN, 2004). The 
devaluation of the currency with the attendant increase 
in domestic prices of exports is nonetheless identified 
as one of the major factors responsible for the 
increase.This study examines the relationship between 
the key factors on the export of some selected 
agricultural crops. 
Materials and Methods 
Scope and Source of Data for the Study 
This study covered export of three major agricultural 
exportable commodities in Nigeria, cocoa, rubber and 
palm kernel. The analysis covered the period between 
1970 and 2002 and the study focuses on the 
determinants of agricultural exports in Nigeria. 
Secondary sources of data are used in this study. Such 
sources are: 
(i)  The federal Office of statistics. 
(ii)  The C.B.N. Statistical bulletin 
Methodological Framework 
The data for this study were analyzed using error 
correction mechanism (ECM). The stationarity levels Agricultural Crops in Nigeria 
470  AAAE Ghana Conference 2007 
of the variables were determined using Phillips Peron 
(PP) test. The Phillips-Peron (PP) test, is non-
parametric and usually produces a superior result that 
corrects for serial correlation and heteroscedasticity. 
The PP test is also known to be better in the presence 
of regime shift which is a problem usually encountered 
with African macroeconomic data. Thereafter, 
cointegration test was carried out using PP test also. 
The cointegration test is carried out to generate an 
error correction model. It employs the Engle-Granger 
two step method (Engle and Granger 1987). 
Cointegration is accepted when the residuals from the 
linear combination of non-stationary I(1) series are 
themselves stationary. In essence, if we are dealing 
with time series data, we must make sure that the 
individual time series are either stationary or that they 
are cointegrated. Otherwise, the result may be spurious 
(Gujarati 1999). The critical values for accepting or 
rejecting the hypothesis have been given in a number 
of studies from Monte Carlo simulations (Fuller, 1978; 
Phillips, 1987; Perron, 1988; Dickey and Fuller, 1981; 
Blangiewicz and Charemza, 1990).  
The Model 
Having established the level of stationarity of the 
variables and the existence of cointegration among 
them, an ECM equation was specified for them. In 
explicit terms, this can be re-written as: 
 
 
This is a modified form of the equation adopted in the 
work of Tambi, 1999. The modification involves the 
inclusion of the Premium in the model. Where: 
LnQEit = the quantity of the ith commodity exported in 
thousand metric tonnes. 
Ln (P
eit/ P
dit)= the price ratio of the ith commodity, 
where P
eit is the export unit value index and P
dit is the 
domestic unit value index and P
dit.  
Ln VWTt = the net exports value which invariably is 
the balance of trade  
Ln GDPt = the real gross domestic product measured 
at 1984 factor cost in billion naira. 
Ln PRt = the quantity of domestic production of the ith 
commodity in thousand metric tonnes. 
Ln ERt = the exchange rate in terms of units of foreign 
currencies (N/US$).  
PREMIUMt = the extra amount added to the official 
real exchange rate by the parallel market operators. In 
addition, the premium is defined as the parallel rate 
minus the official rate over the official rate multiply by 
100, and Ut is a stochastic error term and it is assumed 
to be independently and normally distributed with zero 
mean and constant variance (Nkurunziza 2002).  
A priori, the price ratio P
eit / P
dit, PRit, GDPt, ERt are 
expected to have a positive effect on QEit and is 
intended to capture the profitability of exports. On the 
other hand, A negative relationship is expected 
between premium PREMIUMt and exports.  The net 
value of world trade can take either sign depending on 
whether or not exports exceed imports.  
Results and Discussion 
Determinants of the export performance of three 
agricultural exportable crops using ECM 
Unit root tests of variables used 
The examination of the time series properties of the 
variables used is presented in table 1.  
Table 1: Unit root tests of variables using Phillips-
Perron  (PP) 
VARIABLES   PP    AT  
LEVEL  
PP AT FIRST 
DIFFERENCE  
Ln (QCE)  
Ln (QCE) 
Ln (QCE) 
PREMIUM 
Ln (VWT) 
Ln (WPC/PPC) 
Ln (WPR/PPR 
Ln (WPPK/PPPK) 
Ln (COP) 
Ln (RBP) 
Ln (PKP) 
Ln (GDP) 
Ln  RER) 
-2.82 
-2.83 
-1.29 
-2.53 
-0.99 
-0.41 
-2.94 
-2.54 
-2.65 
-0.83 
-2.00 
2.11 
2.28 
-12.69 
-7.06 
-7.93 
-4.72 
-7.70 
-5.05 
-5.16 
-8.55 
-7.65 
-7.03 
-6.11 
-6.87 
-4.63 
CRITICAL VALUES  
1 PERCENT 
5 PERCENT 
10 PERCENT  
 
 
-3.65 
-2.96 
-2.62 
 
 
-3.66 
-2.96 
-2.62 
 
 
it t t t t it it
d
it
e
o it U PREMIUM ER GDP VWT PR P P QE + + + + + + + = ln ln ln ln ) / ln( ln 5 4 3 2 1 α α α α α αYusuf and Yusuf 
Agriculture and Sustainable Development  471 
The table reveals that virtually all the variables tested 
are not stationary at their level. This indicates that the 
variables are I(1) and any attempt to specify the 
dynamic function in the level of these series will be 
inappropriate and may lead to problem of spurious 
regression. Also, the econometrics result of the model 
in the level of the series may not be ideal for policy 
making (Adams, 1992).  
Cointegration regression results of dependent 
variables 
Cointegration test was carried out using PP to confirm 
that the residuals of the non-stationary series y and x 
that are I(1) are actually I(0).  
Table 2: Cointegration regression result of dependent 
variables on their residuals  
VARIABLE   P.P   DECISION RULE 
Ln (QCE) 
Ln (QRE) 
Ln (QPKE)  
-5.50 
-5.60 
-5.11 
Cointegrated at 1 percent level 
Cointegrated at 1 percent level 
Cointegrated at 1 percent level  
Critical Values  
1 Percent 
5 Percent 
10 Percent 
 
3.65 
2.96 
2.62 
 
 
All the dependent variables were found to cointegrate 
with their determinants at the conventional 1 percent 
levels. The existence of cointegration among the 
dependent variables and their arguments confidently 
led to the specification of ECM for all the three 
equations estimated. The results presented are the 
restricted/ parsimonious models. The unrestricted 
model can be obtained from the authors. 
ECM Results for the Determinants of Selected 
Agricultural Exports in Nigeria 
Table 3 presents the results of the parsimonious ECM 
for the three export commodities (cocoa, rubber and 
palm kernel). In all, the adjusted R
2 ranges from 0.33 
for Rubber to 0.67 for Cocoa. The F- values and the 
Log-likelihood ratio show that the models were well-
fitted. The degree of adjustment of short run 
equilibrium to long run values was spontaneous for 
cocoa and a bit slower for the other two commodities. 
By and large, there is high level of adjustment of 
disturbances in the short run to long run values for all 
the commodities. 
Hence, there seems to be a high feedback mechanism 
for all the crops.  The combined short run dynamic 
effect of the lagged quantities of cocoa and GDP, and 
the net value of world trade jointly explains changes in 
exports of cocoa. The coefficients of VWT and the 
lagged value of GDP are rightly signed. However, the 
coefficient of the lagged value of COP is not rightly 
signed.  
On the other hand, the combined shorts run dynamic 
effects of the real exchange rate and the lagged price 
ratio of rubber explains changes in rubber exports. The 
price ratio does not conform to apriori expectation due 
to the negative sign of the coefficient. This in essence, 
may indicate that the previous year relative price does 
not favour the quantity exported or perhaps the 
previous year price fell short of expectation and then 
discouraged current year exports of rubber. The real 
exchange rate is rightly signed.  
The result for palm kernel shows that the combined 
short-run dynamic effect of the GDP and the lagged 
values of quantity of palm-kernel exported, premium 
and the palm-kernel annual output jointly account for 
the changes in palm-kernel exports. Of the four 
determinants, it is only the lagged output of palm 
kernel that is not rightly signed.  
Conclusion 
The performance of agriculture has not been two 
impressive even with liberalization measures. This is 
especially true in the area of commodity exports and 
foreign exchange earning. Though the exchange rate 
policy is probably the most likely instrument to induce 
increase competitiveness of agricultural export 
commodities in a developing country like Nigeria, 
parallel exchange rate premium only significantly 
affect the export performance of palm-kernel but  not  
cocoa and rubber. Thus, critical attention should be 
paid to such incentives as export promotion because it 
is believed that export promotion have potential to 
stimulate productivity, thrift and entrepreneurship. 
References 
Adams, C.S. 1992. “Recent developments in 
econometrics methods: An application to the 
demand for money in Kenya”. AERC Special 
Paper 15: September.   
Blangiewicz, M; Charemza, W.W. 1990. 
“Cointegration in small samples: Empirical 
percentiles, drift moments and customized 
testing”. Oxford Bulletin of Economics and 
Statistics 52 (3): 303-315.  Agricultural Crops in Nigeria 
472  AAAE Ghana Conference 2007 
CBN 2004. Annual Report and Statement of Accounts  
Dickey, D.A. and W.A. Fuller. 1981. “Likelihood ratio 
statistics for autoregressive time series with a 
unit root” Econometrica  49(4): 1057-72.      
Engle, R.F. and C.W.J. Granger 1987. “Cointegration 
and error correction: Representation, estimation 
and testing”. Econometrica, Vol. 55(2): 251-76.   
Fuller, W.A. 1978.  Introduction to statistical Time 
series Wiley New York. 
Gujarati, D. 1999. Essential of Econometrics. (Second 
edition). McGcaw-Hill International Edition. 
Economic Series  
Ihimodu, I.I. 199). The structural Adjustment 
Progromme and Nigeria’s Agricultural  
Development. Monograph series No 2, National 
Centre for Economic Management and 
Administration (NCEMA) Ibadan.       
Nkurunziza, J.D 2002. Exchange Rate Policy and the 
Parallel Market for Foreign Currency in 
Burundi AERC Research Paper 123, November 
Perron, P. 1988. “Trend and Random Walks in 
Macroeconomic Time Series” Journal of 
economic Dynamics and Control 12: 279-332.  
Phillips, P.C.B, 1987. “Time Series Regression with a 
Unit Root” Econometrica 55 (2): 277-301 
Tambi E.N., 1999. Cointegration and Error Correction 
Modeling of Agricultural Export Supply in 
Cameroon.” Journal of Agricultural Economics 
20: 57-67.   
 
 
 
Table 3: ECM results for the three agricultural export commodities   
Variable Cocoa  Rubber  Palm  Kernel 
Constant 
dLn PRt(-1) 
dLn GDP 
dLn GDP(-1) 
dLn (P
eit/ P
dit(-1)) 
dLnQEit(-1) 
dLn VWTt 
dLn ERt 
dPREMIUMt(-1) 
RESIDUAL (-1) 
-2.92 (-0.57) 
-0.33 (-3.48)** 
- 
122.66 (2.00)* 
- 
- 
-0.03 (-3.86)*** 
- 
- 
-0.99 (-6.30)*** 
0.21 (0.05) 
- 
- 
- 
-0.09 (-2.01)* 
- 
- 
0.62 (1.82)* 
- 
-0.68 (-3.44)*** 
-9.39 (-0.99) 
-0.09 (-1.95)* 
- 
327.39 (2.55)** 
- 
0.40 (2.42)** 
- 
- 
-0.24 (-2.10)** 
-0.87 (-4.67)*** 
R-Squared 
Adjusted R-squared 
Mean dependent variable 
S.D. Dependent variable 
S.E. of Regression 
Sum square residual 
Log likelihood 
Durbin-Watson stat 
Akaike information 
criterion 
Schwarz criterion 
F-statistic 
Prob(F-statistics) 
0.72 
0.67 
-1.99 
46.87 
26.87 
18768.86 
-123.28 
2.31 
9.57 
9.80 
16.33 
0.00 
0.40 
0.33 
2.62 
26.73 
21.85 
12886.68 
-137.45 
1.81 
9.13 
9.31 
5.97 
0.003 
0.59 
0.51 
-1.39 
71.37 
50.16 
62895.63 
-162.02 
2.08 
10.84 
11.12 
7.15 
0.00 

Cointegration and error correction: Representation, estimation and testing”.

Cointegration in small samples: Empirical percentiles, drift moments and customized testing”.

Essential of Econometrics. (Second edition).

Exchange Rate Policy and the Parallel Market for Foreign Currency in

Introduction to statistical Time series

Recent developments in econometrics methods: An application to the demand for money in Kenya”.

Time Series Regression with a Unit Root”

Determinants of Selected Agricultural Export Crops in Nigeria: An Ecm Approach

Determinants of Selected Agricultural Export Crops in Nigeria: An Ecm Approach

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics