Time Series Analysis of Agricultural Commodity Prices in Kebbi State Markets

This study conducts a time series analysis of agricultural commodity prices in selected markets in Kebbi State, North West Nigeria, with a focus on identifying seasonal trends, cyclical patterns, and irregular fluctuations that characterise price movements for rice, sorghum, and cowpea over the period 2018 to 2023. Kebbi State is among Nigeria's most significant agricultural production zones, yet producers and traders in the state continue to face income volatility attributable in part to poorly understood price dynamics. Monthly price data are obtained from the Kebbi State Agricultural Development Programme and the National Bureau of Statistics. Classical decomposition methods are applied to separate trend, seasonal, and irregular components, and autoregressive integrated moving average models are fitted to the detrended and differenced series. Model selection is guided by the Akaike information criterion and the Bayesian information criterion, and forecast accuracy is evaluated through holdout validation using data from the final twelve months of the observation window. Results reveal pronounced seasonal price peaks for all three commodities in the immediate post-harvest period followed by price recovery during lean seasons, a pattern consistent with inadequate storage infrastructure in the state. The study recommends that agricultural extension agencies and commodity market regulators utilise time series forecasting to inform strategic grain storage and price stabilisation interventions. Keywords: time series analysis, commodity prices, ARIMA, agricultural markets, Kebbi State