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100 _a Kumar, Pramod et al
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245 _aEnabling informed resource allocation decision by vegetable growers of Varanasi, Uttar pradesh: Price forecasting using ARIMA
260 _aAgriculture Situation In India
300 _a77(10), Jan, 2021: p.16-24
520 _aThe ARIMA model for forecasting prices of major vegetables of Varanasi market of Uttar Pradesh were developed. ARIMA(0,1,0)(1,1,0)[52], ARIMA(3,1,1)(0,1,0)[52], ARIMA(2,1,4)(1,0,0)[52], ARIMA (0,1,1) (1,1,0)[52] were best fit models for tomato, potato, onion, brinjal, respectively. The parameters of the ARIMA models emerged to be significant. The accuracy test of models was done by comparing the forecasted price of major vegetables with those of actual weekly prices for the period 5th Jan to 26th April, 2020. The accuracy test of MAPE ranged from 0.74% for brinjal to 29.09% for onion. The Theil’s U statistics ranged from 0.004 for binjal to 0.32 for onion. The high accuracy of the model was inferred from the value of Theil’s U statistic lying nearer to zero. The price of tomatoes is estimated to increase in the future, while other vegetables are expected to be stable. Thus, the comparative advantage of the vegetables is revealed which would be taken into account by the farmers for allocating land and other resources for production of vegetables. The findings are also useful to policy makers and extension agencies for making suitable changes in the programmes for promotion of vegetables in the Varanasi district of Uttar Pradesh. – Reproduced
650 _aPrice forecasting, ARIMA, RMSE, Theil’s U statistics, Vegetables
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773 _aAgriculture Situation In India
906 _aPRICE FORECASTING
942 _cAR