The paper describes an empirical study of modeling and forecasting time series data of soybean production in India. Yearly soybean production data for the period of 1970-1971 to 2011-2012 of India were analyzed by time-series methods. Autocorrelation and partial autocorrelation functions were calculated for the data. The Box Jenkins ARIMA (autoregressive integrated moving average) methodology has been used for forecasting. The diagnostic checking has shown that ARIMA (1, 1, 1) is appropriate.

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... e forecasts from 2012-2013 to 2024-2025 are calculated based on the selected model. The forecasting power of autoregressive integrated moving average model was used to forecast soybean production for thirteen leading years. These forecasts would be helpful for the policy makers to foresee ahead of time the future requirements of soybean seed, import and/or export and adopt appropriate measures in this regard.