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Abstract

An attempt has been made in this study to propose an autoregressive integrated moving average (ARIMA) model for forecasting the cotton production for next 10 years. The stationarity of the data have been testedthroughAugmented Dickey Fuller (ADF) test which showed the data is not stationary. For making it stationary, first order differencing has been done. Correlogram have been used to find the suitable order of ARIMA (p,d,q) values.  ARIMA (1, 1,1) was found suitable for cotton production on the basis of minimum values of AIC, SBIC and Hannan Quinn values. Using data for 1950-51 to 2017-18, production of cotton in India were forecasted for 10 years starting from 2019 to 2028 and have shown a rising trend in cotton production in India.

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