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

Listed author(s):
  • KUMAR Manoj

    (Victoria University College, Yangon, Myanmar)

  • ANAND Madhu

    (Agra University, UP, India)

Registered author(s):

    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.

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    File URL: http://eccsf.ulbsibiu.ro/RePEc/blg/journl/918kumar&anand.pdf
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    Article provided by Lucian Blaga University of Sibiu, Faculty of Economic Sciences in its journal Studies in Business and Economics.

    Volume (Year): 9 (2014)
    Issue (Month): 1 (April)
    Pages: 81-94

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    Handle: RePEc:blg:journl:v:9:y:2014:i:1:p:81-94
    Contact details of provider: Postal:
    Lucian Blaga University of Sibiu, Faculty of Economic Sciences Dumbravii Avenue, No 17, postal code 550324, Sibiu, Romania

    Phone: 004 0269 210375
    Fax: 004 0269 210375
    Web page: http://economice.ulbsibiu.ro/
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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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