Forecasting wholesale price of coarse rice in Bangladesh: A seasonal autoregressive integrated moving average approach

This article attempts to develop the model and to forecast the wholesale price of coarse rice in Bangladesh. Seasonal Autoregressive Integrated Moving Average (SARIMA) models have been developed on the monthly data collected from July 1975 to December 2011and validated using the data from December 2010 to December 2011. The results showed that the predicted values were consistent with the upturns and downturns of the observed series. The model with non seasonal autoregressive 1, difference 1 and moving average 1 and seasonal difference 1 and moving average 1 that is SARIMA (1,1,1)(0,1,1)12 model has been found as the most suitable model with least Root Mean Square Error (RMSE) of 61.657, Normalised Bayesian Information Criteria (BIC) of 8.300 and Mean Absolute Percent Error (MAPE) of 3.906. The model was further validated by Ljung-Box test (Q18=17.394 and p>.20) with no significant autocorrelation between residuals at different lag times. Finally, a forecast for the period January 2012 to December 2013 was made.


Subject(s):
Issue Date:
2013
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/209868
Published in:
Journal of the Bangladesh Agricultural University, Volume 11, Number 2
Page range:
271-276
Total Pages:
6




 Record created 2017-04-01, last modified 2017-08-28

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