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An Application Of Time Series Arima Forecasting Model For Predicting Sugarcane Production In India

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  • KUMAR Manoj

    (Victoria University College, Yangon, Myanmar)

  • ANAND Madhu

    (Agra University, UP, India)

Abstract

A time series modeling approach (Box-Jenkins’ ARIMA model) has been used in this study to forecast sugarcane production in India. The order of the best ARIMA model was found to be (2,1,0). Further, efforts were made to forecast, as accurate as possible, the future sugarcane production for a period upto five years by fitting ARIMA(2,1,0) model to our time series data. The forecast results have shown that the annual sugarcane production will grow in 2013, then will take a sharp dip in 2014 and in subsequent years 2015 through 2017, it will continuously grow with an average growth rate of approximately 3% year-on-year.

Suggested Citation

  • KUMAR Manoj & ANAND Madhu, 2014. "An Application Of Time Series Arima Forecasting Model For Predicting Sugarcane Production In India," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 9(1), pages 81-94, April.
    • Handle: RePEc:blg:journl:v:9:y:2014:i:1:p:81-94
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    References listed on IDEAS

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    1. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Forecasting Irish inflation using ARIMA models," Research Technical Papers 3/RT/98, Central Bank of Ireland.
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    Cited by:

    1. S, Suresh Kumar & V, Joseph James, 2016. "Precision in Predicting the Stock Prices –An Empirical Approach to Accuracy in Forecasting," MPRA Paper 109026, University Library of Munich, Germany.

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