PRICE FLUCTUATION AND MARKET INTEGRATION OF SELECTED CEREAL IN NORTH-EASTERN NIGERIA, 2001-2010
Prices contain information crucial to maximizing the returns to production and marketing investments. At planting time, a farmer’s planting decision depends on expected profits, which invariably hinge on the anticipated prices of the crop or mix of crops that would prevail in the market at the time of sale and on the farmer’s interpretation of those prices. A trader, in search of profitable arbitrage, reads and translates price signals in deciding on what crops to buy, where to buy, and when to sell. Apart from guiding production and marketing decisions, prices govern the optimal allocation of resources among competing uses. The accuracy, reliability, and promptness of market information are therefore critical in attaining pricing efficiency. Broadly, the study attempted to analyze the price fluctuation and market integration of selected cereal grains in North-eastern Nigeria. The specific objectives of the study were to: (i) estimate the extent of the various components of price; (ii) derive the probability distribution of cereal grain price in the long-run; (iii) determine the existence and level of inter-market price dependency; (iv) examine the speed of price adjustment to long-run equilibrium and (v) examine the Granger Causality among rural and urban cereal grain markets. The study was conducted in North-eastern Nigeria. Purposive sampling technique was used to select two states, of Adamawa and Taraba, from the six states that made up the North-east geopolitical zone. Only secondary data were used in the study. Secondary data on monthly bases for the prices of 100kg of three cereal grains, maize, rice and sorghum in both rural and urban markets in the study area were obtained from Adamawa and Taraba States Agricultural Development Program offices for a period of 10 years (2001-2010). Data were analyzed using descriptive statistics such as price decomposition technique, and inferential statistics such as Markov Chain, Vector Autoregressive and Error Correction Models. The results rroevealed that, the trend component showed an upward movement for all the three commodities. The seasonal variation had indexes ranged from 198.15 to 52.61, 142.83 to 61.88, and 141.44 to 66.25 for maize, rice and sorghum, respectively. The random and cyclical variations had negligible and insignificant indices with the former having 0.01 all through and the later ranging from 0.93 to 1.26. Probability distribution matrices of the three cereal grains were 0.18, 0.48 and 0.34 for maize, 0.27, 0.68 and 0.05 for rice and 0.48, 0.25 and 0.27 for sorghum. The Augmented Dickey-Fuller unit roots test indicated I(0), I(1) and I(1) for maize, rice and sorghum, respectively. Null hypothesis of β = 1 was rejected against β = 0. Trace statistics for rural and urban markets were not significant ( Rural and urban prices of maize responded to shocks within and between each market. The speed with which the system adjusted to shocks and restored equilibrium between the short and the long-run were -0.170725 and -0.29517 for urban and 0.592237 and 0.38034 for rural prices of rice and sorghum, respectively. Granger Causality showed that a bi-directional flow of price signals existed between rural and urban prices of maize, while rural prices of rice and sorghum did not Granger-Cause urban prices of rice and sorghum. Also, urban prices of both rice and sorghum did not Granger-cause rural prices of both rice and sorghum. Findings of the study showed an imperfect market integration for North-eastern Nigeria cereal grain markets, this indicate that there may be substantial benefits in developing better infrastructure facilities to effectively link production centers to market centers and in improving market knowledge by providing more relevant, accurate, and timely public market information.
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