Nigeria's bean market is still characterized by inefficient and weak integration due to inadequate price information and market infrastructure. Therefore, the study investigates the price variation and transmission of beans markets in Nigeria's Southwest region. The study employed an average monthly price of white and brown beans in rural and urban markets spanning March 2014 to July 2019. Coefficient of variation (CV), Augmented Dickey-Fuller (ADF), Johansen co-integration test and Granger-Causality tests were the analytical tools used for the analysis. The results of CV indicated a spike variation of beans prices over the periods. Urban brown beans experienced the lowest variability of 1.56% in 2015, while rural brown beans experienced the highest variability of 30.03% in 2014. The co-integration test established a long-run dynamic between bean products of different varieties in the same market. However, it failed in the same products in different markets using a bivariate co-integration test. The multivariate co-integration test’s results affirmed that bean markets are strongly linked together in the long-run. The results of Granger-causality showed uni-directional and bi-directional causalities in the beans markets. Rural white beans assumed the lead position and formed the major price transmission in the beans’ markets in the area. Therefore, for more efficiency in the beans’ rural and urban markets, the government should design appropriate market strategies such as accessible market information and infrastructures.
Inconsistent and inefficient policies, climate issues and general poor funding have been adjudged to hinder increased domestic rice production in Nigeria. Rather than tackling these challenges, the nation has continued to opt for importation to supplement her domestic production, if not for recently, as a ‘stop-gap’ for food security. Geared towards strengthening the resilient efforts of the small holder farmers and driving increased rice production, this paper examined the trends in rice imports and production between 1980 and 2021; and also identified the determinants of rice imports in Nigeria. Secondary data were used for this study, while descriptive statistics and ARDL model were used to analyze the data. The results showed that the average quantities of rice production and rice imports were 3.51 and 0.24 million tons over the periods. The periods between 1998 and 2007 experienced a wide volatility of rice imports over rice production. Again, the results of ARDL model implied that exchange rate, GDP and quantity of rice production were statistically significant in influencing changes in the quantity of rice imports in the area. Therefore, since GDP and quantity of rice production had negative relationship with rice imports, it would be suggested that efforts geared at increasing rice production in Nigeria should be tailored at revamping agricultural extension services to enhance a genuine two-way communication between researchers and the farmers vis-à-vis increase food production.
Keywords: Rice Imports, Trends, Rice Production, ARDL Model, Nigeria.
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