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Financialisation of food commodity markets, price surge and volatility: new evidence

In: Handbook on Food

Author

Listed:
  • Kritika Mathur
  • Nidhi Kaicker
  • Raghav Gaiha
  • Katsushi S. Imai
  • Ganesh Thapa

Abstract

The global population is forecasted to reach 9.4 billion by 2050, with much of this increase concentrated in developing regions and cities. Ensuring adequate food and nourishment to this large population is a pressing economic, moral and even security challenge and requires research (and action) from a multi-disciplinary perspective. This book provides the first such integrated approach to tackling this problem by addressing the multiplicity of challenges posed by rising global population, diet diversification and urbanization in developing countries and climate change.

Suggested Citation

  • Kritika Mathur & Nidhi Kaicker & Raghav Gaiha & Katsushi S. Imai & Ganesh Thapa, 2014. "Financialisation of food commodity markets, price surge and volatility: new evidence," Chapters, in: Raghbendra Jha & Raghav Gaiha & Anil B. Deolalikar (ed.), Handbook on Food, chapter 7, pages 149-176, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:14879_7
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    1. Baillie, Richard T. & Bollerslev, Tim, 1990. "A multivariate generalized ARCH approach to modeling risk premia in forward foreign exchange rate markets," Journal of International Money and Finance, Elsevier, vol. 9(3), pages 309-324, September.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    4. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    5. Chiang, Thomas C & Doong, Shuh-Chyi, 2001. "Empirical Analysis of Stock Returns and Volatility: Evidence from Seven Asian Stock Markets Based on TAR-GARCH Model," Review of Quantitative Finance and Accounting, Springer, vol. 17(3), pages 301-318, November.
    6. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    7. Hernandez, Manuel & Torero, Maximo, 2010. "Examining the dynamic relationship between spot and future prices of agricultural commodities," IFPRI discussion papers 988, International Food Policy Research Institute (IFPRI).
    8. Nicole M. Aulerich & Scott H. Irwin & Philip Garcia, 2014. "Bubbles, Food Prices, and Speculation: Evidence from the CFTC's Daily Large Trader Data Files," NBER Chapters, in: The Economics of Food Price Volatility, pages 211-253, National Bureau of Economic Research, Inc.
    9. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    10. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    11. Georgios Kouretas & Eleni Constantinou & Robert Georgiades & Avo Kazandjian, 2005. "Mean and variance causality between the Cyprus Stock Exchange and major equity markets," Money Macro and Finance (MMF) Research Group Conference 2005 24, Money Macro and Finance Research Group.
    12. Machiko Nissanke, 2012. "Commodity Market Linkages in the Global Financial Crisis: Excess Volatility and Development Impacts," Journal of Development Studies, Taylor & Francis Journals, vol. 48(6), pages 732-750, June.
    13. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    14. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    15. World Bank, 2011. "World Development Report 2011 [Rapport sur le développement dans le monde 2011 : Conflits, sécurité et développement - Abrégé]," World Bank Publications - Books, The World Bank Group, number 4389.
    16. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    17. Jörg Mayer, 2012. "The Growing Financialisation of Commodity Markets: Divergences between Index Investors and Money Managers," Journal of Development Studies, Taylor & Francis Journals, vol. 48(6), pages 751-767, June.
    18. Binswanger, Mathias, 2004. "How important are fundamentals?--Evidence from a structural VAR model for the stock markets in the US, Japan and Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 185-201, April.
    19. Eugenio Bobenrieth & Brian Wright & Di Zeng, 2013. "Stocks-to-use ratios and prices as indicators of vulnerability to spikes in global cereal markets," Agricultural Economics, International Association of Agricultural Economists, vol. 44(s1), pages 43-52, November.
    20. Brian D. Wright, 2011. "The Economics of Grain Price Volatility," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 32-58.
    21. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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