5,000 2,500

Topic Description

The basic tenet of the study was that intra-industry trade occurred when
commodities of the same industry are simultaneously exported and imported by partner
nations within the sub-region. The objectives of the study were to review Nigeria’s
merchandise trade, assess the simultaneous exports and imports of agricultural products
by partner nations, evaluate the share of intra-industry trade in agricultural products
between Nigeria and the ECOWAS partner nations, and determine the effects of national
and partners’ characteristics on the intra-industry trade within the sub-region. The study
was carried out on the 15 countries within the Economic Community of West African
States (ECOWAS). However, simultaneous exports and imports were only prevalent
between Nigeria and four of these countries, namely Benin, Cote d’Ivoire, Ghana, and
Togo. These countries have similarities in factor endowments, tastes and fashions of the
partner nations. Exports and imports of agricultural products were collected from Federal
Office of Statistics, now National Bureau of Statistics, publications. The data on national
and partners’ characteristics 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 Statistic Division as well as from
ECOWAS Statistical Bulletin.
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. Objective (iv) was achieved by adopting the binary logistic analytical technique.
The results revealed that the mean value of Nigeria’s merchandise trade with partner
nations ranged from ₦201.7, 731.96, 4,480.84, 35,166.6,92, 965.64, to ₦346,029.9
million between 1979 and 2008, respectively. These represent an annual average of 2.66
and 97.34 percents, respectively, of her total merchandise trade to the partners and the
other parts of the world for the period 1979-2008. Nigeria’s mean export value of all
agricultural commodities ranged from ₦4.35 million between 1979 to ₦2,109.45 million
between 2004 and 2008, while the mean import values ranged from ₦3.43 million
between 1979 and 1983 to ₦8,215.73 million between 2004 and 2008. These represent
1.72 and 4.0 percent, respectively of the exports, and 16.97 and 16.75 percent,

respectively of the imports within the referred periods. The Grubel-Lloyd intra-industry
trade indices were computed for agricultural commodity as a whole, live animals, chilled
meat, coffee/mate, and product of milling industry, preparation of cereals, miscellaneous
edible preparations and residue from food industry for the 30-year period, for each
product. The value of the trade indices were either zero or one, and formed the dependent
The key results from the binary logistic model were that the Grubel Lloyd intraindustry
trade indices in agricultural commodities were influenced by national population
and average partners’ final consumption expenditure, while trade indices in live animals
were influenced by partners’ GDP, national agriculture value added, partners’ agriculture
value added, and national GDP. Also, intra-industry trade indices in chilled meat were
influenced by GNI per capita, national population, and national agriculture value added.
Trade indices in Coffee and mate were influenced by national GDP, GNI per capita, and
partners’ foreign direct investment, while intra-industry trade in the products of mill
industry were determined by GNI per capita, partners’ FDI, and national household final
consumption expenditure. In cereal preparations, intra-industry trade indices were
influenced by partners’ GNI per capita and partners’ FDI, while trade indices in
miscellaneous edible preparations were influenced by partners’ GNI per capita, and
partners’ household final consumption expenditure. Trade indices in residue from food
industry were influenced by partners’ GDP, partners’ population, national value added by
manufacturing, national population, partners’ value added by manufacturing, and national
agriculture value added.

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