MODELING AND FORECASTING OF URAD IN INDIA

In this study researcher has been made to apply the autoregressive integrated moving average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model approach to investigate the trend in Urad area, production and productivity in Bihar, Madhya Pradesh, Uttar Pradesh, West B...

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Published inJOURNAL OF AGRICULTURE, BIOLOGY AND APPLIED STATISTICS Vol. 1; no. 2; pp. 101 - 121
Main Authors Vishwajith, K. P., Sahu, P. K., Srivastava, Aditya Bhooshan, Gautam, Rajani
Format Journal Article
LanguageEnglish
Published 2022
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Summary:In this study researcher has been made to apply the autoregressive integrated moving average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model approach to investigate the trend in Urad area, production and productivity in Bihar, Madhya Pradesh, Uttar Pradesh, West Bengal, and India. Yearly data from 1970 to 2009 were used for forecasting up to 2020. In comparison, we get that in area ARIMA model outperformed GARCH model in all the states under study, whereas inclusion of auxiliary variables improve the model accuracy for production and productivity in maximum cases. Furthermore, according to the trend analysis analysis signifies that production of uradin many state has shown decreasing trend in recent period under study. Forecasted values are likely to help the policy maker in existing battle against food and nutritional security.
ISSN:2583-4185
2583-4185
DOI:10.47509/JABAS.2022.v01i02.05