PRICE FORECASTING OF BAJRA (PEARL MILLET) IN RAJASTHAN: ARIMA MODEL
Journal Title: International Journal of Agriculture Sciences - Year 2016, Vol 8, Issue 9
Abstract
The price behaviour of a commodity plays crucial role in farm level crop production planning. In this paper, an attempt has been made to forecast Pearl millet price using statistical time-series modelling techniques- Autoregressive Integrated Moving Average (ARIMA) Models. The forecasting performance of these models has been evaluated and compared by using common criteria such as: mean absolute percentage error, Akaike Information Criteria (AIC) and Schwarz's Bayesian Information criterion (SBC). The data used in this study include monthly wholesale price of bajra from January 2003 to December 2014. Among all the models tried, the Box-Jenkins ARIMA model (2, 1, 0) was best fit with least AIC (1557.22), SBC (1566.10) and MAPE (5.78). ARIMA (2, 1, 0) model is constructed based on autocorrelation and partial autocorrelation. Finally, forecasts were made based on the model developed. On validation of the forecasts from these models, ARIMA (2, 1, 0) model performed better than the others for bajra in Renwal market. The validation percentage ranged between 87.33 per cent in December 2015 to 96.67 per cent in July 2015. Thus, ARIMA model can be used to predict the future price of bajra in Renwal market of Rajasthan.
Authors and Affiliations
V. K. VERMA
Keywords
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