Prediction of Fruit Production in India: An Econometric Approach

Abstract Forecasting is valuable to countries because it enables them to make informed business decisions and develop data-driven strategies. Fruit production offers promising economic opportunities to reduce rural poverty and unemployment in developing countries and is a crucial component of farm diversification strategies. After vegetables, fruits are the most affordable source of essential vitamins and minerals for human health. India's fruit production strategies should be developed based on accurate predictions and the best forecasting models. This study focused on the forecasting behavior of production of apples, bananas, grapes, mangoes, guavas, and pineapples in India using data from 1961 to 2015 (modelling set) and 2016–2020 (predicting set). Two unit root tests were used, the Ng–Perron (2001) test, and the Dickey–Fuller test with bootstrapping critical values depending on the Park (2003) technique. The results show that all variables are stationary at first differences. Autoregressive integrated moving average (ARIMA) and exponential smoothing (ETS) models were used and compared based on goodness of fit. The results indicated that the ETS model was the best in all the cases, as the predictions using ETS had the smallest errors and deviations between forecasting and actual values. This result was confirmed using three tests: Diebold–Mariano, Giacomini–White, and Clark–West. According to the best models, forecasts for production during 2021–2027 were obtained. In terms of production, an increase is expected for apples, bananas, grapes, mangoes, mangosteens, guavas, and pineapples in India during this period. The current outcomes of the forecasts could enable policymakers to create an enabling environment for farmers, exporters, and other stakeholders, leading to stable markets and enhanced economic growth. Policymakers can use the insights from forecasting to design strategies that ensure a diverse and nutritious fruit supply for the population. This can include initiatives like promoting small-scale farming, improving postharvest storage and processing facilities, and establishing effective distribution networks to reach vulnerable communities.