Stochastic Time Series Modeling for Rice Production in Andhra Pradesh

S. C. Thasleema¹ , Ahammad Basha Shaik²

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.2 , pp.50-55, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v6i2.5055

Online published on Apr 30, 2019

Copyright © S. C. Thasleema, Ahammad Basha Shaik . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Rice is the chief food grain of Indian population. Andhra Pradesh ranks fifth in the rice production in the country. Due to increase in demand of rice over the years, the modeling and forecasting of rice production over the years is very important. An Auto-Regressive Integrated Moving Average (ARIMA) methodology has been successful in describing and forecasting rice production in past studies. In the present study, ARIMA stochastic modeling is used for describing rice production in Andhra Pradesh. The yearly rice production data of Andhra Pradesh from 1980-81 to 2016-2017 has been used for validation of the model. The Statistical software SAS 9.3 is used for analyzing the data. The ARIMA (0, 1, 1) model is selected as the best model based on the minimum values of Root Mean Square Error (RMSE), Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for the rice production of data in Andhra Pradesh. The forecasting of rice production was estimated from 2015-16 to 2026-27 using ARIMA approach.

Key-Words / Index Term :
Rice production, ARIMA, Andhra Pradesh, SAS, Stochastic Time series

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