PRICE BEHAVIOUR OF MAJOR OILSEED CROPS IN GUJARAT: AN ECONOMETRIC ANALYSIS

The Government is promoting organized marketing of agricultural commodities in the country through a network of regulated markets. The basic objective of setting up of network of physical markets has been to ensure reasonable gain to the farmers by creating environment in markets for fair play of supply and demand forces, regulate market practices and attain transparency in transactions. Oilseeds all over the world are known for being a rich source of food, feed, energy and employment. The oilseeds and their by-products also provide nutrition to the livestock and a good source of manures to the crop production. The analysis of prices and market arrivals of oilseeds over time is important for formulating a sound price policy. In order to device the appropriate ways and means for reducing the price fluctuations of oilseeds commodities, there is a need to have a thorough understanding of the price behaviour over time. Hence, the present study assumes the price behaviour of four major oilseeds viz., groundnut, sesamum, mustard and castor crops of Gujarat. The data on districtwise area, production and yield of major oilseeds crop were collected from published data of Directorate of Agriculture, Gujarat state, Gandhinagar from 1990-91 to 2009-10 to study the growth in area, production and productivity. The monthly time series data on arrivals and prices of major oilseeds from 1990-91 to 2009-10 were collected from different Market Committees to study the price behaviour, price forecasting and market integration. Compound Growth Rates (CGRs), Augmented Dickey-Fuller (ADF) unit root test, Auto Regressive Integrated Moving Average (ARIMA), Johansen’s co-integration test, Vector Error Correction Mechanism (VECM) and Garrett’s Ranking techniques were used to achieve the objectives of the study. Major findings of the study revealed that, the Gujarat state registered negative and significant growth rates of area under groundnut and mustard while positive and significant growth rates were found for sesamum and castor crops. The growth rate of production was positive and significant in groundnut, sesamum and castor, while mustard crop registered negative and non-significant growth rate. The per annum rate of increase in productivity was observed highest in groundnut (3.97%), followed by mustard (1.58%), sesamum (1.02%) and castor (0.44%). The highest variation in area was noticed in castor, followed by mustard, sesamum and groundnut during the study period. The production and yield variation was found the highest in groundnut, followed by sesamum, mustard and castor crop. Higher indices of market arrivals were noticed in the month of November for groundnut, October for sesamum, March and April for mustard and April and February for castor while that of highest price index was observed in the month of July and August for groundnut, April and May for sesamum, November and December for mustard and September for castor crop. The lower market arrivals index value was found during the month of August for groundnut, March and August for sesamum, October and February for mustard, and October for castor crop while the lower price indices were observed in the month of December for groundnut, October for sesamum, March for mustard and June and January for castor crop. The results of ARIMA models were found to be the most suitable for forecasting the prices of selected oilseeds commodities viz., (1, 1, 0) for groundnut, (0, 1, 0) for sesamum, (0, 1, 0) for mustard and (1, 1, 2) for castor price. The validity of the forecasted values of all the four oilseeds commodities were checked by comparing them with their actual values during the post sample forecast period. The percentage difference between the forecasted and actual value of groundnut, sesamum, mustard and castor were found to be 5.2 per cent, 2.0 per cent, 0.5 per cent and 4.4 per cent, respectively. This proved that the ARIMA models were the best fit models for forecasting the price of oilseeds. The results of the Augmented Dickey-Fuller (ADF) unit root test for the selected four oilseed crops viz., groundnut, sesamum, mustard and castor revealed that the level data were non-stationary but their first differences were stationary. This implies the presence of unit root in both the selected market price series of all the selected crops. Hence, both the market price series of all the selected crops were integrated of the order 1 i.e. I(1). Further, the Johansen’s co-integration test revealed that the Gondal and Junagadh market price series for groundnut, Rajkot and Gondal market price series for sesamum and Dhanera and Patan market price series for mustard were co-integrated while there was no co-integration between Patan and Dhanera market prices of castor during the period under study. This indicated that the castor markets were inefficient in comparison to the markets of other three oilseeds commodities. The results of Vector Error Correction Mechanism (VECM) showed that the causality in the case of groundnut and sesamum was unidirectional while, it was observed bidirectional in case of mustard means both the selected market prices influenced each other equally. In case of castor, the price series were not co-integrated. The results of Granger causality test indicated that for groundnut, there existed unidirectional causality while in case of sesamum and mustard, both the market prices exerted bidirectional causality among them. The results based on the Johansen multiple co-integration procedure for national and international market of mustard showed that the presence of at least two co-integration equations at 1 per cent level of significance. Hence, markets are having long-run equilibrium relationship. In case of the Hapur market price model of mustard, the price discovery occurred in the Alwar and Dhanera markets and was transmitted to Hapur market. However, in the Alwar market model, the price discovery occurred in the Dhanera market and was transmitted to Alwar market. In Dhanera market price model, the Dhanera market was influenced by its own price too. Similarly, in Hamburg market price model, the Hamburg market was also influenced by its own price. Granger causality test for national and international markets revealed that Alwar market prices influenced the Hapur market price and there existed unidirectional causality from Alwar to Hapur markets. Similarly, unidirectional causality was exerted from Dhanera to Alwar, Dhanera to Hapur, Hamburg to Hapur and Hamburg to Dhanera market. The results of Garrett’s ranking analysis of problems associated with marketing revealed that the price fluctuation was the major problem expressed by most of the farmers. Adoption of appropriate price policy measures to maintain acreage at desired levels, improvement in the productivity of oilseed crops through more research and extension efforts, enhancing storage facilities, adoption of different price mechanism techniques to reduce the price fluctuation and adequate and continuous efforts to disseminate the market intelligence and market information, particularly for price forecast are some of the major suggestions emerged from the study. Dr. R. L. Shiyani Professor & Head, Department of Agricultural Economics, Junagadh Agricultural University, Junagadh (Gujarat).