Forecasting wheat production in India: An ARIMA modelling approach
Bhola Nath, DS Dhakre, Debasis Bhattacharya
Abstract
Bhola Nath, DS Dhakre, Debasis Bhattacharya
Abstract
Box-Jenkins’ ARIMA model: A time series modelling approach has been used to forecast wheat production for India. ARIMA (1,1,0) model was found to be the best ARIMA model for the present study. The efforts were made to forecast, the future wheat production for a period up to ten years as accurate as possible, by fitting ARIMA (1,1,0) model to our time series data. The forecast results have shown that the annual wheat production will grow in 2026-27. The wheat production will continuously grow with an average growth rate of approximately 4% year by year.
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Box-Jenkins’ ARIMA model: A time series modelling approach has been used to forecast wheat production for India. ARIMA (1,1,0) model was found to be the best ARIMA model for the present study. The efforts were made to forecast, the future wheat production for a period up to ten years as accurate as possible, by fitting ARIMA (1,1,0) model to our time series data. The forecast results have shown that the annual wheat production will grow in 2026-27. The wheat production will continuously grow with an average growth rate of approximately 4% year by year.
Key concepts: Autoregressive integrated moving average, Box–Jenkins, Production (economics), Time series, Series (stratigraphy), Econometrics, Statistics, Mathematics