Developing Price Forecasting Model of Vegetable Crops through Discriminant Function
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Date
2020-11
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Sher-e-Kashmir University of Agricultural Sciences and Technology Jammu, J&K
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Vegetables play an important role in human consumption but most of the time it is seen that a vegetable which is just ` 20/kg in summer season suddenly touches to ` 80/kg in winter season. Due to this fluctuation of price, people stopped consuming that particular vegetable. The present study “Developing Price Forecasting Model of Vegetable Crops through Discriminant Function” which basically deals with that price fluctuation of vegetable crops. Discriminant Function Analysis (DFA) is as similar to regression analysis as they both are used for prediction purposes. Regression is used when dependent variable is dichotomous on the other hand DFA is used when dependent variable is nominal. In the present study, the price model(s) for two important vegetable crops of Jammu region i.e. Tomato and Cauliflower are developed. Secondary data of specific crops have been taken from Narwal Mandi for a period of 2012 to 2018 on monthly basis pertains to variables price, area, arrival, turnover production and yield. The normality of the data is checked through Kolmogorov Smirnov, Shapiro Wilk test, histograms, Q-Q plots, Z score and Box and Whisker test. Further, DFA is used and groups are formed on basis of season and discriminant scores are calculated on the basis of Wilk’s lambda, Box M, Mahalanobis distances etc. The predicted groups on the basis of discriminant scores are used for developing the price model(s). In case of tomato F value, wilk’s lambda and groups formed on the basis of price are significant in nature which shows that groups varies. Price model(s) for both summer and winter season are significant in nature. Variables like arrival, turnover and yield show direct and indirect effect on price of tomato crop. In case of cauliflower Wilk’s lambda, F value and groups formulated on the basis of price are also significant. Canonical correlation for cauliflower crop explained 52.85 percent variation. The price model for winter in case of cauliflower is significant but in summer is non-significant. Arrival, turnover and production are the variables which effect the price of the cauliflower crop directly or indirectly.
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