ARIMA model for forecasting of maize prices in Telangana state by using SAS

Abstract

This study employs the Autoregressive Integrated Moving Average (ARIMA) approach to model and predict maize prices in Telangana State. The Autocorrelation (AC) and Partial Autocorrelation (PAC) functions are calculated to identify and construct suitable ARIMA models for explaining the time series and forecasting future production. Evaluation of forecasting performance is conducted using Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The best-fitting model is then utilized for out-of-sample forecasting up to December 2023.