An analysis of trend and determinants of intra-ECOWAS trade in agricultural products.
Onogwu, G.O. ; Arene, C.J. ; Chidebelu, A.N. 等
Abstract
The integration arrangement of Economic Community of West African
States (ECOWAS) was aimed at expanding the volume of intra-Community
trade implemented through the removal of both tariff and non-tariff
barriers to trade. The objectives include to: review Nigeria's
merchandise trade; assess the simultaneous exports and imports of
prepared foodstuff (HS) (section (IV); evaluate the share of
intra-industry trade in the total trade between Nigeria and the partner
nations; and determine the effects of national and partners'
characteristics on the intra-ECOWAS trade. The results revealed that
intra-trade in Cereal preparations was positively and negatively
influenced by partners' gross national income (GNI) per capita by
partners" and foreign direct investment (FDI), respectively. Trade
in miscellaneous edible preparations was "influenced positively by
partners" GNI per capita and negatively by partners' household
final consumption expenditure. In residue from food industry, trades
were influenced positively by partners' gross national product
(GDP), partners' population, and national value added by
manufacturing, and negatively influenced by national population,
partners' value added by manufacturing, and national agriculture
value added in case of miscellaneous edible preparations within the
ECOWAS sub-region.
Efforts to increase foreign direct investments in cereal
preparation, GDP and GNI per capita to reduce cost per unit of good
through the adoption of cost saving options in the value chain during
production; processing and packaging of miscellaneous edible
preparations were recommended to promote trade.
Keywords: Intra-Trade; Agricultural Products; ECOWAS Sub-region
INTRODUCTION
The promotion of intra-trade is predicated on the danger posed by
the protectionist measures adopted by the developed countries. Indeed,
in spite of the various trade negotiations, particularly under the
auspices of the General Agreement on Tariff and trade, the European
Union (the largest importer of West African products) maintained an
average tariff of 9.8 per cent on imports from developing countries up
to the Uruguay Round of negotiations in 1994. To worsen matters,
developing countries in whose markets exports of manufactures from other
developing countries are likely to be initially competitive also impose
restrictions on certain types of manufactures and primary products
(Amsden, 1976). For instance, the tariff rates on imports of primary and
manufactured products adopted by a selected number of developing
countries ranged from 30.2 and 36.3 per cents in 1984-88 to 24.7 and
27.3 per cents in 1991-94.
Also, in spite of the implementation of the ECOWAS trade
liberalization scheme, which aimed at boosting intra-regional trade,
evidence showed that the intra-ECOWAS trade, as a percentage of total
ECOWAS trade, was highly insignificant. Between 1999 and 2006, the total
intra-ECOWAS trade was 12% of the total ECOWAS trade (intra and
inter-ECOWAS trade) compared to the European intra-regional trade which
is about 60% of total trade. While ECOWAS total external trade was 45.7%
of the regional GDP over the period 1999 to 2006, the intra-ECOWAS trade
was a mere 5.5% of the regional GDP over the same period (ECOWAS
Statistical Bulletin, 2008). Supposedly, ECOWAS member nations engaged
in little trade among themselves, and without sufficient intra-regional
trade, economic integration might be limited and the need for a common
currency might not be justifiable. So, which factors were responsible
for low intra-industry trade in the prepared foodstuffs? What policy
options should be offered in a bid to improve intra-ECOWAS trade in
these products?
In this study, the prepared foodstuffs were defined as the groups
comprising products from Harmonized System (HS) section (IV) of the
trade classification. This section consisted of product subsections: (i)
Preparations of cereals; (ii) Flour, starch or milk; (ii) Miscellaneous
edible preparations; (iii) Residues from food industries, animal feed.
Intra-industry trade involves a simultaneous export and import of goods
produced in the same industry. In this scenario, intra-ECOWAS trade in
food products refers to simultaneous exports and imports of the products
of prepared foodstuffs between Nigeria and partner nations within
ECOWAS. According to Grubel-Lloyd (1975), Helpman (1985), Davis (1999),
Ruffin (1999), and Otshow and Jouq (2002), this trade was more
beneficial than inter-industry trade because it stimulated innovation
and exploited economies of scale. This was more or less required by the
ECOWAS and most sub regional groupings in Africa for economic
emancipation. More so, productive factors did not switch from one
industry to another, but within industry; hence, intra-industry trade
was less disruptive than inter-industry trade and both constituted
important segments of international trade (Ruffin, 1999; Vani and
Gandhi, 2004).
THEORETICAL FOUNDATION
Over the last two decades when economists tried to examine the
complexities of world trade, it was found that countries with related
factor endowments engaged in more trade than countries with different
factor endowments as predicted by Hecksher-Ohlin-Sasmuelson's
classical model of comparative advantage in 1933. Again, standard
customs union theory, as articulated by Viner (1950), predicted
increased inter-industry specialization, and trade, and its wake brought
serious adjustment frictions. Essentially the intra-industry trade
research programmed was initiated by several researchers probing for the
effects of the establishment of the (then) European Economic Community
on trade patterns. Notable among these authors were Verdoorn (1960),
Dreze (1961), and Balassa (1965). This surprising discovery led to the
prediction (Balassa, 1966) that adjustment to European integration would
be smoother than expected, because frictions associated with
reallocating resources within as opposed to between industries would be
less. This deficiency in factor endowment theory caused substantial
literature to emerge attempting to explain the new trend in
international specialization and trade pattern. The central point in
those studies was the abandonment of factor endowment assumption and the
adoption of the concept of intra-industry trade. In our own scenario,
intra-industry trade occurs between Nigeria and her ECOWAS trading
partners, especially in agricultural commodities given the similarities
in their factor endowments.
In the Economic Community of West African States (ECOWAS), there
are some sub-regional integration efforts enforced through such
interventions like free international trade, common external tariff
wall, consolidation or freezing of custom duties, non-tariff b barriers
to intra-trade and gradual phasing out of duties on industrial products
from community projects over a period of 6-10 years at 1016.6% annual
rates of reduction depending on the classification of member states
based on the level of development, location and importance of customs
revenue. It is hypothesized that in a situation where the pattern of
trade reflects comparative advantages based on dissimilarities of
economic structures, the scope for intra-trade is limited in relation to
that in which there is also trade based on similarities of factor
endowments. Put differently, the scope and rate of inter-trade expansion
are augmented by intra-industry trade which reflects a similarity of
economic structures exists side by side with inter-industry trade
reflecting differences in economic structure. We were therefore
concerned with horizontal intra-industry trade given the developmental
stage of the countries of the sub-region.
Stone (1997) maintained that the determinants of intra
industry-trade have two facets namely, industrial based and regional
characteristics. Industrial based characteristics include:--product
differentiation, scale of economies, industry specific cost structure
and transportation costs. The regional characteristics are macroeconomic
which according to him include income level and relative capital/ labour
ratio, as well as similarity in per capita income, total income among
others. Although, free trade were easier to create between Nigeria and
her partners in the ECOWAS sub-region and intra-industry trade in
agricultural commodities were expected to be intense due to a number of
sub regional integration interventions, and the traded goods involving
relatively low adjustment costs that could build on that base; the
effect(s) of countries characteristics such as Nominal GDP, per capita
income, country size(population), per cent of agric, in GDP, component
of demand in per cent GDP, Geographic proximity, foreign direct
investment among other factors, on intra-industry trade were not known.
METHODOLOGY
The four sections of the harmonized system of trade classification
(HS) code that deal with agricultural commodity exports and imports as
in: (i) live animal and animal products, (ii) vegetable products, (iii)
animal and vegetable fats and oil, and (iv) prepared foodstuff,
beverages, vinegar and tobacco were assessed. The study focused on the
instances of simultaneous exports and imports of prepared foodstuffs
between Nigeria and partner nations within ECOWAS. In an attempt to
minimize the problem of classification, the United Nations Harmonized
System of Trade Classification (HS) codes I-IV that consist of
agricultural commodities and agricultural product sub-sections were
adopted (National Bureau of Statistics, 2008). Export values were
reported free-on-board (f.o.b), while import values consisted of costs
as well as freight and insurance costs (c.i.f). Trade data on
simultaneous exports and imports of prepared foodstuffs and product
subsections were collected from Federal Office of Statistics now
National Bureau of Statistics (1979-2008) publications. National and
partners' characteristics data such as GDP nominal, GNI per capita,
size (population), foreign direct investment, value added by
manufacturing, agriculture value added, household final consumption
expenditure, and government final consumption expenditure were obtained
from the United Nations Statistics Division (1979-2008) as well as from
ECOWAS Statistical Bulletin (1999-2006).
Descriptive statistics were used to achieve objectives (i) and
(ii), while objective (iii) was achieved by employing the Grubel-Lloyd
approach of measuring intra-industry trade index, and objective (iv) was
achieved by applying the binary logistic analytical technique. The
intra-industry trade indices were estimated by the following
specifications:
[G.sub.J.sup.*] = [IIT.sub.j] = 1 [X.sub.j] - [M.sub.j] / [X.sub.j]
+ [M.sub.j] (1)
Where;
[G.sup.*.sub.J] = Grugel Llyod index
IIT = Intra-Industry Trade in product, j
[X.sub.j] = Exports of product, j
[M.sub.j] = Imports of product, j
The Grubel-Lloyd indices for the period under review neither offer
policy prescriptions nor ameliorate the national / partners'
characteristics that influence regional trade flows in prepared
foodstuffs. The index would have policy implication when analyzed using
binary logistic model to determine the factors that significantly
influence intra-industry trade in prepared foodstuffs within the region.
The dependent variable of the function is a dummy variable obtained for
each year by the above relationships and lies within the range (0, 1),
i.e. dichotomous. In such functions the disturbance term will be
heteroscedastic, so that the method of ordinary least squares is not
appropriate (Koutsoyiannis, 2001). To ensure that the predicted values
were also limited to the interval, a logistic function was employed and
a non-linear least squares technique that permits inclusion of zero
values was used for the estimation (Blassa, 1986; Balassa and Bauwens,
1987, Lee and Lee, 1993; Musonda, 1994). This was done by assuming that
there was an underlying response variable [G.sub.j.sub.*] defined by the
logistic regression relationship
[G.sub.j.sub.*] = [beta]'xi + [[micro.sub.i] (2)
Where;
[G.sub.j.sup.*] = Grubel-Lloyed index
[beta] = Coefficients of xi, s
[X.sub.i] = Vector of explanatory variables ([x.sub.1], [x.sub.2],
[x.sub.3], [x.sub.4], ..... [x.sub.n]) (national and partners'
characteristics); [G.sub.j.sup.*] = Unobservable, while [G.sub.j] is the
observed dummy variable defined as:
[G.sub.j] = 1, if [G.sub.j.sup.*] > 0
[G.sub.j] = 0, if [G.sub.j.*] < 0 (3)
In this formulation, [beta]'xi is the E([G.sub.J.sup.*]/xi)
While, the Pr ([G.sub.j] = 1) = 1-F(-[beta]' xi (4)
As F the cumulative distribution function for g, is the logistic,
we have the logistic model, where, and
F (-[beta]'xi) = 1/+[exp.sup.([beta]'xi) and
1-F (-[beta]'xi) = [exp.sub.([beta]'xi)/1 +
[exp.sup.([beta]'xi); (Maddala, 1983)(5)
RESULTS AND DISCUSSIONS
Imports by Agricultural Commodity Sections (cif)
Table 1 presents the mean import values of agricultural commodities
(Sections IIV) and their subsections of the harmonized system of trade
classification codes (HS codes). The mean import values of all
agricultural sections from Nigeria's to her trading ECOWAS partners
ranged from [Naira sign] 3.43 million between 1979 and 1983 to [Naira
sign] 8,215.73 million between 2004 and 2008. These represent 16.97 and
16.75 percents, respectively of the total agricultural imports within
the referred periods. The import trend of entire agricultural sections
showed increase since 1984, alongside the imports from ECOWAS trading
partners, but the percentage increase in relation to the entire import
trend depicts a decrease in imports. This implies that the imports from
the ECOWAS partner nations were decreasing, while total imports of
agricultural commodities were increasing with respect to the rest of the
world.
There were import trade in all the agricultural Sections (I-IV)
between 1979 and 1983. Table 2 also illustrates the mean import values
by agricultural commodity Sections I-IV. A closer observation of the
trend reveals that there were decreases in the import values of
commodity Sections I-III, while those of Section IV showed steady
increases up to 2008 (Table 1).
Thereafter, between 1984 and 1988, imports of section I-III fell by
[Naira sign] 0.39 million or 36.11 percent and [Naira sign] 0.42 million
or 46.15 percent, and 0.21 million or 55.26 percent; from [Naira sign]
1.08, [Naira sign] 0.91, and [Naira sign] 0.38 millions between 1979 and
1983 to [Naira sign] 0.69, [Naira sign] 0.49, and [Naira sign] 0.17
millions between 1984 and 1988, respectively. This period corresponded
with the onset of SAP era suggesting that the policies partially led to
a drop in importation of some agricultural commodities within its early
periods. This is because during SAP (1986-1993) and as was the case
between 1989 and 1993 imports of Sections I-IV from both ECOWAS and the
world rose substantially by [Naira sign] 26.13 million or 1016.73
percent, and [Naira sign] 7090.5 million or 562.65 percent, within the
same period, respectively. This implied not only a failure on the part
of the Government and the populace at large to maintain the SAP policy
of altering and re-aligning aggregate domestic expenditure and
production patterns to minimize dependence on imports, enhance non-oil
export base and ensure a steady and balanced economic growth, but also a
reduction in production and value additions in the indigenous products
of the sub-sectors of this section, or an increase in population.
Exports by Agricultural Commodity Sections
Table 2 x-rays the mean export values of agricultural commodities
(sections I-IV) of the harmonized system of trade classification codes
(HS codes). Nigeria's mean export value of all agricultural
commodities to her trading ECOWAS partners ranged from [Naira sign] 4.35
million between 1979 and 1983 to [Naira sign] 2,109.45 million between
2004 and 2008. These represent 1.72 and 4.0 percents, respectively of
the entire agricultural exports within the referred period. The mean
annual exports of agricultural commodities to partner nations stood at
3.48 percent of the total agricultural commodity exports. The total
exports of all agricultural commodities were only 1.64 percent of total
exports of all commodity sections in the economy.
From 1979 to 1998, there was a steady increase in the export values
of Section IV. The export values ranged from [Naira sign] 3.87 million
in 1979 to [Naira sign] 1324.73 million in 2008, representing 88.97 and
62.8 percents of the total exports to ECOWAS region from 1979 to 2008.
On the whole, agricultural commodity of Section IV had a mean export
value of 87.51 for the period under review.
With respect to section III, its exports witnessed the most
inconsistency, with the mean export values ranging from [Naira sign]
0.14 million between 1984 and 1988 to [Naira sign]2.72 million between
1999 and 2003. Onwards, its exports fell by 22.43 percent, from | 2.72
million between 1999 and 2003 to [Naira sign] 2.11 million between 2004
and 2008. However, the mean export value of agricultural commodity
Section III stood at 1.85 percent of the total exports of all
agricultural commodity sections to the sub region between 1979 and 2008.
All the sections, except Section II showed inconsistent increases
in the export trend from 1994 to 2003. Exports of Section II were on
steady increase from 1989 to 2008. The highest increases in the exports
occurred between 2004 and 2008 when it rose by [Naira sign] 635.66
million from [Naira sign] 3.5 million between 1999 and 2003 to [Naira
sign] 639.16 million between 2004 and 2008, representing 30.3 percent of
the total value of all agricultural commodities exports to ECOWAS
partners within the period under reference. Besides, the mean export
value of agricultural commodity Section I stood at 3.78 percent of the
total exports of all agricultural commodities to the sub region within
the same period (Table 2).
Imports of Prepared Foodstuffs; Beverages; Tobacco: HS Section IV
Generally, Nigeria's total imports of prepared foodstuffs;
beverages, tobacco (Section IV) were on the increase from 1979 to 2008.
Table 4 revealed that total mean import values of this section from the
world ranges from [Naira sign] 503.4 million between 1979 and 1983 to
[Naira sign] 113,749.2 million between 2004 and 2008, while her total
imports of the same section from ECOWAS trading partners ranged from
[Naira sign] 1.17 million to [Naira sign] 2,037.5 million within the
periods under review. These represent mean compound import percentages
of 549.82 and 120.53 for ECOWAS and the world, respectively, for the
same periods (Table 3).
The implications are not only that Nigeria's imports of
Section IV products from the ECOWAS partner nations were higher than her
imports from the world, but also the sub-region would have had the
enthroned welfare and consumption effects. In addition, increased
intra-regional trade in this way helped to deepen regional and political
integration.
The imports of Tobacco and Beverages rose steadily throughout the
period, with the import values of tobacco rising more than those of
Beverages each year except for the period between 2004 and 2008 when
import of beverages rose from [Naira sign] 129.42 million between 1999
and 2003 to [Naira sign] 330.08 million, while Tobacco only rose from
[Naira sign] 174.52 to [Naira sign] 299.51 millions within the same
periods. The mean import values ranged from 0.02 and 0.02 millions
between 1979 and 1983 to [Naira sign] 299.51 and [Naira sign] 330.08
millions between 2004 and 2008 respectively. However, imports of
residues from industry and cereal preparation (sub-sections) started and
continued to rise from 1984 up to 2008. The total imports of
miscellaneous preparations started between 1979 and 1983, but slumped in
1988; started to rise between 1989 and 1993, reached a record high
between 1994 and 1998 and slumped again. However, it continued to rise
from 2004 up to 2008.
Exports of Prepared Foodstuffs; Beverages, Spirit and Vinegar;,
Tobacco: HS Code IV
The sub-sections of Section IV products where simultaneous exports
and imports took place include Cereal preparations, miscellaneous
preparations, beverages, residue from mill industry, and tobacco. Other
product subsections where intra industry trade did not take place are
sugar and Sugar confectionary, Cocoa and cocoa preparations, and
preparation of vegetable fruit and nut. Generally, table 3 presents the
total export values of section IV and the products sub sections to
partners within ECOWAS. It shows that the export values of this section
increased steadily from 1984 through the end of 1998, when exports
dwindled. However, exports ranged from [Naira sign] 3.87 million between
1979 and 1983 to [Naira sign] 11,324.73 million between 2004 and 2008,
while the total export of the entire sections to the world rose by
[Naira sign] 29581.3 million, from [Naira sign] 3,515.4 million between
1999 and 2003 to [Naira sign] 33,096.7 million between 2004 and 2008,
representing 841.5 percent. This implies a substantial increase in the
market share of the section and gain in revenue (Table 4).
The exports of miscellaneous preparations started in 1984, reached
a record high in 1998 before it slumped in 1999 by [Naira sign] 153.8
million or 90.46 percent, from [Naira sign]170.02 million to [Naira
sign] 16.02 million implying loose of market grip. Between 1979 and 1983
export trade were evident in beverages but showed fluctuations, rising
and falling. With regard to beverages export trend were inconsistent,
rising and falling; a situation that make products unavailable, and may
culminate to reduced market share or lack of patronage.
Classification of Intra-ECOWAS Trade in Residues from Food Industry
The classification table for intra industry trade in residue from
food industry shows that 66.7% of our intra-industry observations (value
= 0), and 100% of our inter industry trade observations (value = 1),
were correctly classified, yielding a total correct classification of
83.4. The model distinguished successfully between intra-industry trade
and inter-industry trade given the logistic predicted values and the cut
values.
Determinants of Intra-ECOWAS Trade in Residues from Food Industry
The determinants of intra-industry trade in residue from food
industry are discussed below. However the variables that produced
insignificant results were national GDP, partners' household final
consumption expenditure, and national final consumption expenditure,
[X.sub.1,14&17] respectively (Table 5).
[X.sub.2] = Partners' GDP
The coefficient is .009, while the standard error was .005. The
Wald statistic of 3.240 is significant at 1% level. The positive value
of the logistic coefficient meant that, as partners' GDP increased
the chances of intra-industry trade in residue from industry increased
by 1.009.
[X.sub.5] = National Population
The coefficient (B) was -2.174. The standard error was 1.309 and
the Wald statistic was 2.759. The significant level was .097. So, since
.097 was larger than .05, it was concluded that this variable was
significant at 10% level. The logistic coefficient produced an odds
multiplier less than one. The negative value indicated that the variable
decreased the odds of reporting. In this case, we inferred that national
population decreased the chances of intra-industry trade in residue from
food industry trade by. 114 among the trading partners within the ECOWAS
sub-region.
[X.sub.6] = Partners' Population
The coefficient was 23.72, while the standard error was 13.856. The
Wald statistic was 2.931, and the significant level was .087. Therefore,
since .087 was larger than .05, it was concluded that this variable was
significant at 10% level. The logistic coefficient was a positive value
indicating that, as partners' population increased the chances of
intra-industry trade in residue from food industry trade would also
increase.
[X.sub.9] = National Value Added by Manufacturing
The logistic coefficient (B) was .002 and the standard error was
.001. The Wald statistic was 4.000, which was significant at 1% level.
The positive logistic coefficient value indicated that the variable
increased the odds of reporting. So, it was inferred that, as national
value added by manufacturing increased, the chances of intra-industry
trade in residue from food industry would increase by 1.002 among the
trading partners within the sub-region.
[X.sub.10] = Partners' Value Added by Manufacturing
The logistic (B) coefficient was -.044 and the standard error was
.029. The Wald statistic was 2.302, which was significant at 5% level.
The negative logistic coefficient value indicated that the variable
decreased the odds of reporting. So, it was inferred that, as
partners' value added by manufacturing decreased, the chances of
intra-industry trade in residue from food industry would decrease by
.957 among the trading partners within the sub-region.
[X.sub.11] = National Agriculture Value Added
The coefficient was -.168 and the standard error was .110. The Wald
statistic was 2.333, significant at 5% level. The negative value of the
coefficient indicated that, as partners' value added by
manufacturing decreased the probability of intra-industry trade in
residue from food industry would increase by .999 within the subregion.
The Summary of the Relationship between dependent and Independent
Variables
The average [R.sup.2] = .68, indicating that 68.0% of the
variations in the trade values were explained by the variables
Test of the Significance of the Coefficients Intra-Trade in Residue
from Food Mill Industry
Null Hypothesis: [H.sub.0] : [b.sub.1] = 0, (That national and
partners' characteristics do not significantly influence
intra-industry trade in agricultural commodity).
Against the Alternative Hypothesis: [H.sub.1] : [b.sub.1] [not
equal to] 0 (That national and partners' characteristics have
significant influence on intra-industry trade in agricultural
commodity). The Wald test, described by Polit (1996) and Agresti (1990),
is one of a number of ways of testing whether the parameters associated
with a group of explanatory variables are zero. If for a particular
explanatory variable, or group of explanatory variables, the Wald test
is significant, then it would be concluded that the parameters
associated with these variables are not zero, so that the variables
should be included in the model. From the model chi-square, the model
was adequate (p=.0001). That the model (p = .002) meant the model was
significant beyond (p = .002).
DECISIONS
Since the model p =.002, the model was significant, which meant
that not all are zero. So, the null hypothesis was rejected; since
partners' GDP, national population, partners' population, and
national value added by manufacturing were all significant, at 1% level
each, while partners' value added by manufacturing and national
agriculture value added were both significant at 5% level each. The
inference drawn was that partners' GDP, national population,
partners' population, and national value added by manufacturing,
partners' value added by manufacturing and national agriculture
value added have significant influence on intra-industry trade in
residue from food industry among the partner nations within the ECOWAS
sub-region
CLASSIFICATION OF INTRA-TRADE IN PREPARATION OF CEREALS
In the agricultural commodity Section IV, the product sub-sections,
where simultaneous exports and imports occurred were in preparation of
cereals, miscellaneous edible/preparations, and residue from food
industry. Other products of this sub-section, where infinitesimal trades
occurred, included Beverages and Tobacco. However, these were not
analysed for very low levels of exports in relation to the imports in
those product subsections. The other product subsections where
intra-industry trade did not take place were sugar and Sugar
confectionary, Cocoa and cocoa preparations, and preparation of
vegetable fruit and nut.
The classification table for intra industry trade in preparation of
cereals showed that 33.3% of the intra-industry observations (value =
0), and 96.3% of the intra-industry trade observations (value = 1), were
correctly classified, yielding a total correct classification of 64.8%.
The model distinguished successfully between intra-industry trade and
inter-industry trade given the logistic predicted values and the cut
values.
DETERMINANTS OF INTRA-ECOWAS TRADE IN CEREAL PREPARATIONS
The determinants of intra-industry trade in cereal preparations are
discussed below. Other variables that produced insignificant results
were national household final consumption expenditure, [X.sub.13] and
national final consumption expenditure, [X.sub.17] (Table 6).
[X.sub.4] = Partners' Gross National Income Per capita
The coefficient is .033, while the standard error is .017. The Wald
statistic is 3.768, which was significant at 1% level. The positive
logistic coefficient value indicates that this variable increased the
odds of reporting. In this scenario, it was concluded that, as
partners' gross national income per capita increased, the chances
of intra-industry trade in cereal preparation would increase by 1.034.
This meant that the partners' gross national per capita income
increased the opportunities of intra-industry trade in cereal
preparation by 1.034 among the trading partners within the ECOWAS
sub-region. It was recommended that in all partners' country, both
private and public enterprises should put hands on deck to improve
productivity, the GDP, and GNI per capita. This would increase exports
and imports of cereal preparation, and promote and sustain
intra-regional trade in this product.
[X.sub.8] = Partners' FDI
The logistic coefficient was negative -.017 and the standard error
was .010. A Wald statistic of 2.890 was significant at 1% level. The
negative logistic coefficient value indicates that the variable
decreases the odds of reporting. Therefore, it was inferred that, as
partners' FDI decreases the chances of intra-industry trade in
Cereal preparation decreases by .983. It was recommended that trading
partners should increase the foreign direct investments to cereal
preparation production. This would increase its output, improve exports
and promote intra industry trade in this product among the trading
partners within the sub-region.
The Summary of the Relationship between Dependent and Independent
Variables
The average [R.sup.2] = .733, indicating that 73.3% of the
variations in the trade values were explained by the variables
Test of the Significance of the Coefficients of the Determinants of
Intra-Trade in Cereal Preparations
Null Hypothesis [H.sub.0] : [b.sub.1] = 0, [b.sub.1] = 0, (That
national and partners' characteristics do not significantly
influence intra-industry trade in Cereal Preparation).
Against the Alternative Hypothesis [H.sub.1] : [b.sub.1] [not equal
to] 0 [H.sub.1] : [b.sub.1] [not equal to] 0 (That national and
partners' characteristics have significant influence on
intra-industry trade in cereal preparations). The Wald test, described
by Polit (1996) is one of a number of ways of testing whether the
parameters associated with a group of explanatory variables are zero. If
for a particular explanatory variable, or group of explanatory
variables, the Wald test were significant, then it would be concluded
that the parameters associated with these variables are not zero, so
that the variables should be included in the model. From the model
chi-square, it could be seen that the model is adequate, with (p
=.0001). That the model (p = .0001) meant the model is significant
beyond (p = .0001).
DECISIONS
Since the model p = .0001, the model was significant, which meant
that not all b's were zero. Therefore, the null hypothesis was
rejected; hence Partners' GNI and Partner's FDI were
significant, at 5%, and 10% levels, respectively. It was inferred that,
partners' GNI and FDI very significantly influenced intra-industry
trade in cereal preparation among the trading partners within the ECOWAS
sub-region.
CLASSIFICATION OF INTRA-ECOWAS TRADE IN MISCELLANEOUS EDIBLE
PREPARATIONS
The classification table for intra industry trade in Miscellaneous
Edible Preparations showed that 95.0% of the intra-industry observations
(value = 0), and 90.0% of the inter-industry trade observations (value =
1), were correctly classified, yielding a total correct classification
of 92.5%. The model distinguished successfully between intra-industry
trade and inter-industry trade in miscellaneous edible preparations
given the logistic predicted values and the cut values.
DETERMINANTS OF INTRA-ECOWAS TRADE IN MISCELLANEOUS EDIBLE
PREPARATIONS
The variables that yielded highly significant results are discussed
below. However, other variables which did not significantly influence
intra-industry trade in miscellaneous edible preparations were national
foreign direct investment and national value added by manufacturing,
[X.sub.7and9] respectively (Table 7).
[X.sub.4] = Partners' Gross National Income Per capita
The coefficient was .102, while the standard error was .068. The
Wald statistic was 2.250, which was significant at 1% level. This
positive logistic coefficient value indicated that, as partners'
gross national income per capita increased, the chances of
intra-industry trade in miscellaneous edible preparations would increase
by 1.107 among the trading partners within the ECOWAS sub-region.
[X.sub.14] = Partners' Household Final Consumption Expenditure
The coefficient was -.782 and the standard error was .461. The Wald
statistic was 2.877, which was significant at 1% level. This negative
logistic coefficient value produced meant that, as partners'
household final consumption expenditure decreased, the chances of
intra-industry trade in miscellaneous edible preparation increased by
.458 within the ECOWAS sub-region. This was because as the price per
unit of a given good decreases, the quantity purchased of the good would
increase.
The Summary of the Relationship between Dependent and Independent
Variables
The average, [R.sup.2] = .809 indicating that 80.9% of the
variations in the trade values were explained by the variables
Test of the Significance of the Coefficients of the Determinants of
Intra-Industry Trade in Misc. Edible Preparations
Null Hypothesis: [H.sub.0] : [b.sub.1] = 0, [b.sub.1] = 0, (That
national and partners' characteristics do not significantly
influence intra-industry trade in Misc. Edible Prep).
Against the Alternative Hypothesis: [H.sub.1] : [b.sub.1] [not
equal to] 0 That national and partners' characteristics have
significant influence on intra-industry trade in Misc. Edible Prep). The
Wald test, described by Polit (1996) and Agresti (1990), was one of a
number of ways of testing whether the parameters associated with a group
of explanatory variables are zero. If for a particular explanatory
variable, or group of explanatory variables, the Wald test is
significant, then it would be concluded that the parameters associated
with these variables are not zero, so that the variables should be
included in the model. From the model chi-square, we see that the model
is adequate (p = .0001). This was concluded from the following output.
That the model (p = .0001) means the model is significant beyond p =
.0001.
DECISIONS
Since the model p = .0001, it meant that not all b's were
zero. Therefore, the null hypothesis was rejected; hence both
partners' gross national income per capita and partners'
household final consumption expenditure were significant, at 1% each. It
was inferred that partners' GNI per capita and partners'
household final consumption expenditure significantly influence
intra-industry trade in miscellaneous edible preparation among the
trading partners within the ECOWAS sub-region.
RECOMMENDATIONS
Based on the findings, the following recommendations were made:
(1) trading partners should increase the foreign direct investments
in production of cereal preparation to increase its output, improve
exports and promote intra-industry trade in this product among the
trading partners within the sub-region.
(2) in all partner countries, both private and public enterprises
should put hands on deck to improve productivity- the GDP, and GNI per
capita given the positive influence they have on miscellaneous edible
preparations. Moreover, in view of the negative effect of partners'
household final consumption expenditure, it is recommended that national
operators should reduce cost per unit of good through the adoption of
cost saving options in the value chain during production, processing and
packaging of miscellaneous edible preparations. This will reduce the
final consumption expenditure in terms of price that an average person
in the partner nation would pay; to sustain consumption and improve
intra-regional trade; and
(3) for trades in residue from food industry, it is recommended
that national stakeholders should employ efficient methods and tools in
production of cereals, and other raw materials of food industry since
national population negatively influence trades. Also, trading partners
and national stakeholders should increase the value addition in view of
the negative effects of partners' value added by manufacturing and
national agriculture value added. This would increase output, reduce
cost and promote exports and imports, thereby improving intra industry
trade in the product, within the sub-region.
(4) Regionally traded products as well as markets should be
sustained by exempting them from free trade areas when EPAs comes into
operation.
CONCLUSION
In the face of the current global economic crises and financial
meltdown, the ECOWAS member states and indeed other regional blocs need
to redouble their efforts to enhance economic growth in a sustainable
manner. More so, there is need to improve substantially the
manufacturing capacity of the regions especially when most of the
exports from the regions are primary products, prices of which are
volatile and exogenously determined. Thus, for the region(s) to realize
maximum benefits from globalization, they have to diversify production
base and export commodities that have value addition. Improving the
region(s) manufacturing capacity will help West Africa or elsewhere
region to become a less disadvantaged player in the world economy,
especially in the light of the proposed economic partnership agreements
with the European Union that will inevitably entail the establishment of
a free trade area between West Africa cum other regions and European
Union. Therefore, efforts to reach the millennium development goal of
reducing poverty by 2015 from its 1990 level should also be intensified
through adoption of the appropriate measures within the ECOWAS and other
sub-regions in Africa.
There is the need for policy makers to continue to make concerted
efforts to ensure the effective implementation of the ECOWAS trade
liberalization scheme and to stimulate the private sector to enhance
value addition to the manufactured products of agricultural origin
within the community. This is important, not only to sustain horizontal
differentiation (i.e. different varieties of a given good), and vertical
differentiation (i.e. different qualities of a given variety) of
agricultural products, but in making sure that intra-regional trade
would be sustained and improved, given the level of competition their
economies would be subjected to when the economic partnership agreement
(EPAs) between the ECOWAS and the European Union (EU) goes into
operation.
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G. O. ONOGWU *, C. J. ARENE * AND A. N. CHIDEBELU *
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[email protected];
[email protected];
[email protected]
Table 1
Imports by Agricultural Commodity Sections
(cif, [Naira sign] million)
Sections I II III IV
Year Live Vegetable Animal Prepared
animals Products and Foodstuff
and vegetable Beverages;
animal Fats and Spirits;
products Oils Vinegar
79-83 1.08 0.91 0.38 1.17
84-88 0.69 0.49 0.17 1.22
89-93 5.65 3.87 1.78 17.39
94-98 112.47 160.16 8.35 116.44
99-03 891.87 1,001.14 76.78 980.47
04-08 2,637.25 3,343.8 197.18 2,037.52
Sections Import Total Total
Year of Agric. Import Import
Sections of Agric. Values of
from Sections all
ECOWAS Sections
of the
Economy
79-83 3.43 1,481.5 8,728.9
84-88 2.57 1,260.2 9,867.9
89-93 28.7 8,350.7 92,938.3
94-98 342.27 55,291.2 316,391.0
99-03 6,514.0 184,405.3 972,115.1
04-08 8,215.73 459,074.7 2,740,840.1
Source: computed from FOS (1979-1987) and NBS (1987-2008) Foreign
Trade Data.
Table 2
Exports by Agricultural Commodity Sections ([Naira sign] million)
Section I II III IV
Year Live Vegetable Animal Prepared
Animals Products and Foodstuffs;
and Vegetable Beverages;
Animal Fats and Spirit,
Products Oils Vinegar
79-83 0.08 0.25 0.16 3.87
84-88 0.32 0.22 0.14 26.37
89-93 1.6 0.2 0.27 64.47
94-98 17.75 1.31 11.83 297.75
99-03 5.15 3.5 2.72 85.8
04-08 143.44 639.16 2.11 1,324.73
Section Total Total Total
Year Exports of Exports of Exports of
all Agric. all Agric. all
commodity Sections commodity
to to ROW Sections
ECOWAS in the
Partners Economy
79-83 4.35 253.1 10,423.9
84-88 27.05 698.8 18,133.4
89-93 66.53 2,310.3 140,136.5
94-98 328.63 5,535.7 548,210.8
99-03 97.17 3,983.2 2,319037.0
04-08 2,109.45 52,699.1 7,151,184.2
Source: Computed from FOS (1979-1987) and NBS (1987-2008) Foreign
Trade Data.
Table 3
Imports of Prepared Foodstuffs; Beverages, Tobacco: HS Section IV
Sub Cereal Misc. Beverages Residues Tobacco
Sections Prep. Prep. from
Year Industry
79-83 0.15 0.3 0.02 0.03 0.02
84-88 0.1 0.14 0.05 0.01 0.76
89-93 0.21 0.35 0.64 0.03 11.83
94-98 3.96 4.77 5.12 0.7 32.72
99-03 111.77 0.98 129.42 5.88 174.52
04-08 387.13 411.58 330.08 57.05 299.51
Sub Total Total
Sections Imports Imports
Year of of
Section IV Section IV
from Products
ECOWAS
79-83 1.17 503.4
84-88 1.22 598.5
89-93 17.39 5,064.0
94-98 116.44 16,222.5
99-03 980.47 61,268.2
04-08 2,037.5 113,749.2
Source: computed from FOS (1979-1987) and NBS (1988-2008) Foreign
Trade Data.
Table 4
Exports of Prepared Foodstuffs; Beverages, Spirit and Vinegar, Tobacco
(HS Code IV) to ECOWAS
Sub Cereal Misc. Beverages Residues Tobacco
Sections Prep. Prep. from
Year Industry
79-83 0.0 0.0 0.001 0.012 0.0
84-88 0.0 19.28 0.13 0.03 0.01
89-93 0.0 57.83 0.07 0.0 0.26
94-98 0.06 170.02 0.3 0.0 6.55
99-03 64.35 16.22 0.07 0.0 0.03
04-08 10.6 59.61 34.44 39.74 91.35
Sub Total Total
Sections Exports Exports
Year of of
Section IV Section
to IV
ECOWAS Products
79-83 3.87 224.8
84-88 26.37 681
89-93 64.47 2,237.7
94-98 297.75 5,018.1
99-03 85.8 3,515.4
04-08 1,324.73 33,096.7
Source: FOS (1979-1987) and NBS (1988-2008) Foreign Trade Data.
Table 5
Determinants of Intra-ECOWAS Trade in Residue from
Food Mill Industry
B S.E. Wald df Exp(B)
Step 1(a) X1 .001 .001 .100 1 1.000
X2 .009 .005 3.240 1 1.009
X5 -2.174 1.309 2.758 1 0.114
X6 23.720 13.856 2.931 1 2E+010
X9 .002 .001 4.000 1 1.002
X10 -.044 .029 2.302 1 .957
X11 -.168 .110 2.333 1 .999
X14 -.018 .032 .316 1 .983
X17 -.137 .109 1.581 1 .872
(a) Variable(s) entered on step 1: Xl, X2, X5, X6, X9, X10, X11,
X14, X17.
Table 6
Determinants of Intra-ECOWAS Trade in Cereal Preparations
B S.E. Wald Df Exp(R)
Step 1(a) X4 .033 .017 3.768 1 1.034
X8 -.017 10 2.89 1 .983
X13 -.152 .219 .482 1 .859
X17 .229 .222 1.064 1 1.257
X18 -.197 .124 2.524 1 .821
(a) Variable(s) entered on step 1: X4, X8, X13, X17, X18.
Table 7
Determinants of Intra-ECOWAS Trade in Misc. Edible Prep
B S.E. Wald Df Exp(B)
Step 1(a) X4 .102 .068 2.25 1 1.107
X7 .003 .004 .563 1 1.003
X9 .001 .001 1.000 1 1.001
X14 -.782 .461 2.877 1 .458
(a) Variable(s) entered on step 1: X4, X7, X9, X14.
