Forecasting Production of Food grain Using ARIMA Model and Its Requirement in Bangladesh

admin May 16, 2015

Authors:

Lasker Ershad Ali,Masudul Islam,Md. Rashed Kabir ,Faruque Ahmed ,

DOI NO:

https://doi.org/10.26782/jmcms.2013.01.00003

Keywords:

forecast,food grain ,production,ARIMA model,

Abstract

We forecast the food grain requirement and its production in Bangladesh. Before forecasting, we examine different methods and find time series model i.e. ARIMA model in different order predict accurate values. Then we used autoregressive integrated moving average (ARIMA) models to forecast the future amount of food grain in different years in this study. For the accuracy checking, we take the difference between the actual amount of food grain in a specific year and the predicted or the forecasting amount of the food grain in that year.

Refference:

I.Assis, K., Amran, A., Remali, Y. and Affendy, H. (2010). A comparison of univariate time series methods for forecasting cocoa bean prices. Trends Agric. Econ., 3, 207–215.

II.Brokwell, P. J. & Davis, R. A. (1997). Introduction to Time Series and Forecasting, Springer, New York.

III.Cooray, T.M.J.A.(2006). Statistical analysis and forecasting of main agriculture output of Sri Lanka: rule-based approach. Appeared In10th International Symposium, 221, 1–9. Sabaragamuwa University of Sri Lanka.

IV.Clements, M. and Hendry, D. (1998). Forecasting economic time series, United University Press, Cambridge.

V.Gourieroux, C. and Monfort, A.(1997).Time Series and dynamic Models, Cambridge University Press, England.

VI.Gujarati, D. N.(2004). Basic Econometrics, 4th ed., McGraw Hill, New York.

VII.Hossain, M.Z., Samad, Q.A. & Ali, M.Z. (2006). ARIMA model and forecasting with three types of pulse prices in Bangladesh: A case study. International Journal of Social Economies. 33, 344–353.

VIII.Jonathan, D. C. & Kung-Sik, C.() Time Series Analysis with Application in R , 2nd ed., Spring Steet, New York.

IX.Saeed N., Saeed A., Zakria M. & Bajwa, T. M. (2000).Forecasting of Wheat Production in Pakistan using Arima Models, International Journal of Agriculture & Biology, 1560–8530, 02,4,352–353.

X.Makridakis, S.(2003). Forecasting Method and Application, 3rd ed., John Wiley and Sons, New York.

XI.Montgomery, D. C.(1990). Forecasting and Time Series Analysis”, 2nd ed., McGRAW-Hill, Inc, New York.

XII.Nochai, R. & Nochai, T. (2006). ARIMA Model for Forecasting Oil Palm Price: 2nd IMT-GT Regional Conference on Mathematics, Statistic and Applications. University Sains Malaysia, Penang, June 13-15.

XIII.Prindyck, R. S. & Rubinfeld, D. L. (1981). Economic Models and Economic Forecasts, 3rd ed., McGrsw-Hill, Inc, New York.

XIV.Shukla, M. & S. Jharkharia.(2011). Applicability of ARIMA models in wholesale vegetable market: An investigation. Proceedings of the 2011International Conference on Industrial Engineering and OperationsManagement. Kuala Lumpur, Malaysia, January 22-24.

XV.Wankhade, R., Mahalle, S., Gajbhiye, S. & Bodade, V.M. ( 2010). Use of the ARIMA model for forecasting pigeon pea production in India. International Review Of Business Finance, 2, 97–102.

XVI.Thorne, B. & Carlson W. (2007). Statistics for Business and Economics, 6th ed., Arrangement with Pearson Education, Inc. and Dorling Kindersley publishing, Inc., New Delhi.

Lasker Ershad Ali, Masudul Islam, Md. Rashed Kabir ,Faruque Ahmed View Download