Modeling of groundnut production in India using arima model

The paper describes an empirical study of modeling and forecasting time series data of groundnut production in India. Yearly groundnut production data for the period of 1950–1951 to 2013–2014 of India were analyzed by time-series methods. Autocorrelation and partial autocorrelation functions were calculated for the data. The Box Jenkins ARIMA methodology has been used for forecasting. The diagnostic checking has shown that ARIMA (0, 1, 1) is appropriate. The forecasts from 2015–2016 to 2024–2025 are calculated based on the selected model. The forecasting power of autoregressive integrated moving average model was used to forecast groundnut production for ten leading years. These forecasts would be helpful for the policy makers to foresee ahead of time the future requirements of groundnut seed, import and/or export and adopt appropriate measures in this regard.