Iteration and Identification of the Appropriate ARIMA Models for Forecasting Groundnut Area, Production, and Yield in Telangana and India

Abstract

Groundnut cultivation plays a crucial role in India's agricultural landscape, but there has been a declining trend in acreage in the past two decades. At the state level, despite groundnut productivity in Telangana being higher than the national average, it was not among the major groundnut-producing states for its only rabi cultivation and low acreage. Under such conditions, forecasting area, production and yield beforehand the prices is necessary to address dynamics at the supply end. This study aims to forecast groundnut cultivation, production, and yield in India and Telangana using ARIMA modelling. The annual time series data were sourced from the Directorate of Economics and Statistics, Government of India from 1990-91 to 2021-22. ARIMA. SPSS software was employed for the analysis and modelling tasks. By analysing the model fit and residual statistics ARIMA (2,1,3) ARIMA (0,0,0), and ARIMA (3,1,3) were performed as the best-fit models for groundnut area, production, and yield forecasts in India. For Telangana, ARIMA (0,1,0) ARIMA (1,1,6), and ARIMA (14,1,14) were found better. The forecasts of groundnut at the country level indicated stagnation in production, declination in area and inclination in yield, which was found fluctuating. Proactive planning is necessary to address these challenges and ensure sustainable production at the country level. In Telangana, there is a positive trend in groundnut production and the increasing trend in cultivation but may decline in the long run, if proper planning and marketing strategies are not followed consistently. Accurate forecasting of groundnut metrics is crucial for stakeholders to make informed decisions, bridge supply-demand gaps, and promote a resilient groundnut industry.