Maize Price Forecasting Using Auto Regressive Integrated Moving Average (ARIMA) Model

This paper examined the monthly modal prices of maize using Autoregressive Integrated Moving Average (ARIMA) models so as to determine the most efficient and adequate model for analyzing the maize monthly modal prices in Telangana. The results indicate that Autoregressive Integrated Moving Average ARIMA 211 model is the most adequate and efficient model. This was ascertained by comparing the various model selection criterion and the diagnostic tests for various models among them Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) and Mean Absolute Percentage Error (MAPE). Time series Analysis was done using SAS 9.3 software. A better understanding of maize price situation and future prices will facilitate farmers and end users to make appropriate decisions regarding buying and selling patterns hence government should take adequate policies. The forecasted results suggest that there are expectations of increasing maize prices in Badepalli market next five months (October to February). This requires the government to take appropriate measures to ensure that farmers and end user get benefited.