HORIZONTAL AND VERTICAL INTEGRATION OF MAJOR OILSEED MARKETS IN INDIA
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Date
2015
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ACHARYA N.G. RANGA AGRICULTURAL UNIVERSITY, GUNTUR
Abstract
The study entitled “Horizontal and Vertical Integration of Major Oilseed Markets in India” was undertaken to analyze the horizontal integration among major oilseed markets of India, to assess the vertical integration among oilseeds and their derivatives, to identify and evaluate various sources of risk in supply chain of oilseeds and to investigate the factors affecting the critical risks in supply chain of oilseeds in India.
The study was conducted for three major oil seed crops viz., groundnut, sunflower and castor. The markets selected for the study were Kurnool and Yemmiganur (Andhra Pradesh) and Gondal (Gujarat) for groundnut, Kurnool and Yemmiganur (Andhra Pradesh) and Ranebennur (Karnataka) for sunflower and Kurnool and Yemmiganur (Andhra Pradesh), Patan and Dhanera (Gujarat) for castor. Bombay market was selected for collecting the daily price data related to oils and oilcakes of selected oilseed crops. To identify the sources of risks across the supply chain of oil seeds, primary data were collected from 120 farmers, 10 commission agents, 10 village merchants, 10 wholesalers and 10 oil millers. The data pertained to the period from April 2013 to March 2014.
The horizontal and vertical integration in selected markets was analyzed through Augmented Dickey Fuller test, Johansen’s Multiple Cointegration analysis, Vector Error Correction Model and Granger Causality test. In order to identify and evaluate various sources of risk and to investigate the factors affecting the critical risks in supply chain of oilseeds, Failure Modes and Effect Analysis (FMEA), Risk Evaluation Matrix, Pareto Analysis and Ishikawa diagram were employed.
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In the case of horizontal integration, all the selected markets showed integration for the three selected crops individually, which is evident by Johansen’s co-integration procedure. With respect to horizontal integration among groundnut markets, Kurnool and Yemmiganur markets came to short run equilibrium within 8 hours and 4 hours respectively, in the case of horizontal integration among sunflower markets, Kurnool and Ranebennur markets converged to short run equilibrium price within 5 hours and 4 hours respectively, whereas all the markets attained their short run equilibrium in castor. Granger causality test indicated that Gondal groundnut market, Ranebennur sunflower market and Patan castor market were the lead markets and the information had flown from these markets to other markets individually. The horizontal integration among the markets of selected oils viz., Malaysian palm oil, Bombay groundnut oil, sunflower oil and sunflower refined oil, showed that these oil markets were integrated in the long run. Further, the Granger causality test showed that the price information was communicated from Malaysian palm oil market to Bombay sunflower refined oil market.
With respect to vertical integration among the daily price series of pod, oil and cake for the three selected crops (groundnut, sunflower and castor), the results revealed that in the case of groundnut, out of three selected pod markets, two pod markets (Kurnool and Yemmiganur) were integrated with the oils and cakes in Bombay market and the information has reached from terminal market (Bombay) to groundnut producing areas. With respect to sunflower, out of the three selected seed markets only one market (Yemmiganur) showed integration with sunflower oil of Bombay market. Out of three selected sunflower seed markets all the markets showed integration with the daily prices of sunflower refined oil and cake in Bombay market, which indicated that the price information was more from sunflower producing areas to terminal market (Bombay). In the case of castor, the daily prices of the selected seed markets showed the integration with the daily prices of both oils and oilcakes and the information flow was mutual or bi-directional from castor producing areas to terminal market (Bombay) with respect to oils, whereas, there was no transmission of price signals between the selected castor seed market and castor cake market.
According to the results of FMEA, Pareto Analysis and Ishikawa Diagram for risk analysis in supply chain of oilseeds, out of 33 identified sources of risk across the supply chain of oilseeds, a total of 18 risks were identified as the high potential critical risks at the supply chain stages of input, production, post-harvest and marketing and the disruptive range of all these critical risks was between the RPN (Risk Priority Number) (Minimum 48 - Maximum 125). In the case of input risks, out of seven sources of input risks, four sources (high cost of inputs, inadequacy of capital, lack of availability and accessibility and timeliness of supply) were identified as the
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critical risks and the disruptive range was between RPN (48-100). In respect of production risks, out of nine sources of critical production risks five sources (weather uncertainty and climate change, inadequate rainfall, pests and diseases, lack of access to farm technology and inadequate infrastructure) were identified as the critical risks and the disruptive range has fallen between RPN (60-125). Regarding post-harvest risks, out of seven sources of post-harvest risks, four sources (absence of quality control practices, absence of storage facilities, absence of grading and poor packaging) were identified as the critical risks and disruptive range occurred between RPN (48-100). With regard to marketing risks, out of ten sources of marketing risks, five sources (variability in output prices, lack of discriminatory pricing for quality produce, low bargaining power, exploitation by middlemen and lack of market information) were identified as the critical risks and the disruptive range was found between RPN (64-125).
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D5122
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