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Efficiency in agricultural commodity futures markets in India: Evidence from cointegration and causality tests

  • Jabir Ali
  • Kriti Bardhan Gupta

Purpose – In line with the ongoing global and domestic reforms in agriculture and allied sectors, the Indian Government is reducing its direct market intervention and encouraging private participation based on market forces. This has led to increased exposure of agricultural produce to price and other market risks, which consequently emphasize the importance of futures markets for price discovery and price risk management. The purpose of this paper is to analyze the efficiency of agricultural commodity markets by assessing the relationships between futures prices and spot market prices of major agricultural commodities in India. Design/methodology/approach – The efficiency of the futures market for 12 agricultural commodities, traded at one of the largest commodity exchanges of India, i.e. National Commodity & Derivatives Exchange Ltd, has been explored by using Johansen's cointegration analysis and Granger causality tests. Unit root test procedures such as Augmented Dickey-Fuller and non-parametric Phillips-Perron were initially applied to examine whether futures and spot prices are stationary or not. The hypothesis, that futures prices are unbiased predictors of spot prices has been tested using econometric software package. Findings – Results show that cointegration exists significantly in futures and spot prices for all the selected agricultural commodities except for wheat and rice. This suggest that there is a long-term relationship between futures and spot prices for most of the agricultural commodities like maize, chickpea, black lentil, pepper, castor seed, soybean and sugar. The causality test further distinguishes and categorizes the commodities based on direction of relationship between futures and spot prices. The analysis of short-term relationship by causality test indicates that futures markets have stronger ability to predict subsequent spot prices for chickpea, castor seed, soybean and sugar as compared to maize, black lentil and pepper, where bi-directional relationships exist in the short run. Practical implications – The results of this study are useful for various stakeholders active in agricultural commodities markets such as producers, traders, commission agents, commodity exchange participants, regulators and policy makers. Originality/value – There are very few studies that have explored the efficiency of the commodity futures market in India in a detailed manner, especially at individual commodity level.

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Article provided by Emerald Group Publishing in its journal Agricultural Finance Review.

Volume (Year): 71 (2011)
Issue (Month): 2 (July)
Pages: 162-178

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Handle: RePEc:eme:afrpps:v:71:y:2011:i:2:p:162-178
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  1. Andrew M. McKenzie & Bingrong Jiang & Harjanto Djunaidi & Linwood A. Hoffman & Eric J. Wailes, 2002. "Unbiasedness and Market Efficiency Tests of the U.S. Rice Futures Market," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 24(2), pages 474-493.
  2. Henry L. Bryant & David A. Bessler & Michael S. Haigh, 2006. "Causality in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(11), pages 1039-1057, November.
  3. Andrew McKenzie & Matthew Holt, 2002. "Market efficiency in agricultural futures markets," Applied Economics, Taylor & Francis Journals, vol. 34(12), pages 1519-1532.
  4. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
  5. Tim Krehbiel & Lee C. Adkins, 1993. "Cointegration tests of the unbiased expectations hypothesis in metals markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(7), pages 753-763, October.
  6. Jha, Shikha & Srinivasan, P. V., 1999. "Grain price stabilization in India: Evaluation of policy alternatives," Agricultural Economics, Blackwell, vol. 21(1), pages 93-108, August.
  7. Ramaprasad Bhar & Shigeyuki Hamori, 2006. "Linkages among agricultural commodity futures prices: some further evidence from Tokyo," Applied Economics Letters, Taylor & Francis Journals, vol. 13(8), pages 535-539.
  8. A. G. Malliaris & Jorge L. Urrutia, 1998. "Volume and price relationships: Hypotheses and testing for agricultural futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(1), pages 53-72, 02.
  9. Jha, Shikha & Srinivasan, P.V., 1999. "Grain price stabilization in India: Evaluation of policy alternatives," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 21(1), August.
  10. T. Randall Fortenbery & Hector O. Zapata, 1993. "An examination of cointegration relations between futures and local grain markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(8), pages 921-932, December.
  11. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
  12. H. Holly Wang & Bingfan Ke, 2005. "Efficiency tests of agricultural commodity futures markets in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(2), pages 125-141, 06.
  13. Wang, H. Holly & Ke, Bingfan, 2005. "Efficiency tests of agricultural commodity futures markets in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(2), June.
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