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The Financialization of Food?

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  • Valentina G. Bruno
  • Bahattin Buyuksahin
  • Michel A. Robe

Abstract

Commodity-equity and cross-commodity return co-movements rose dramatically after the 2008 financial crisis. This development took place following what has been dubbed the “financialization” of commodity markets. We first document changes since 2000 in the intensity of speculative activity in grain and livestock futures. We then use a structural VAR model to establish the role of speculative activity in explaining the strength of co-movements between grain, livestock and equity returns. We find that speculative intensity does not in itself affect the extent to which grain markets move in sync with the stock market. Rather, pre-crisis, financial speculators’ futures positions facilitated the transmission of macroeconomic shocks into grain markets. Strikingly, in the post-crisis period, this transmission channel weakened to the point of statistical insignificance. The role of speculative activity is less evident in livestock markets, where only macroeconomic conditions have a statistically significant impact on return co-movements with equities.

Suggested Citation

  • Valentina G. Bruno & Bahattin Buyuksahin & Michel A. Robe, 2013. "The Financialization of Food?," Staff Working Papers 13-39, Bank of Canada.
  • Handle: RePEc:bca:bocawp:13-39
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    References listed on IDEAS

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    1. Wolfram Schlenker & Sofia B. Villas-Boas, 2009. "Consumer and Market Responses to Mad Cow Disease," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(4), pages 1140-1152.
    2. Witsanu Attavanich & Bruce A. McCarl & David Bessler, 2011. "The Effect of H1N1 (Swine Flu) Media Coverage on Agricultural Commodity Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(2), pages 241-259.
    3. Yiuman Tse & James C. Hackard, 2006. "Holy mad cow! Facts or (mis)perceptions: A clinical study," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(4), pages 315-341, April.
    4. Xiaodong Du and Lihong Lu McPhail, 2012. "Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    5. Matteo Manera, Marcella Nicolini, and Ilaria Vignati, 2013. "Financial Speculation in Energy and Agriculture Futures Markets: A Multivariate GARCH Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    6. Wolfram Schlenker & Sofia B. Villas-Boas, 2009. "Consumer and Market Responses to Mad Cow Disease," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(4), pages 1140-1152.
    7. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    8. Thomsen, Michael R. & McKenzie, Andrew M. & Power, Gabriel J., 2009. "Volatility Surface and Skewness in Live Cattle Futures Price Distributions with Application to North American BSE Announcements," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49354, Agricultural and Applied Economics Association.
    9. Devadoss, Stephen & Holland, David W. & Stodick, Leroy & Ghosh, Joydeep, 2006. "A General Equilibrium Analysis of Foreign and Domestic Demand Shocks Arising from Mad Cow Disease in the United States," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 31(2), pages 1-13, August.
    10. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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    Cited by:

    1. Kilian, Lutz, 2019. "Measuring global real economic activity: Do recent critiques hold up to scrutiny?," Economics Letters, Elsevier, vol. 178(C), pages 106-110.
    2. Matthew Henry & Russell Prince, 2018. "Agriculturalizing finance? Data assemblages and derivatives markets in small-town New Zealand," Environment and Planning A, , vol. 50(5), pages 989-1007, August.
    3. Esposti, Roberto, 2017. "What Makes Commodity Prices Move Together? An Answer From A Dynamic Factor Model," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 260889, European Association of Agricultural Economists.
    4. Michael Hachula & Malte Rieth, 2020. "Estimating the Impact of Financial Investments on Agricultural Futures Prices using Changes in Volatility," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 759-785, May.
    5. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Modeling fluctuations in the global demand for commodities," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 54-78.
    6. Esposti, Roberto, 2021. "On the long-term common movement of resource and commodity prices.A methodological proposal," Resources Policy, Elsevier, vol. 72(C).
    7. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    8. Mohammad Isleimeyyeh & Amine Ben Amar & Stéphane Goutte, 2021. "Commodity markets dynamics: What do crosscommodities over different nearest-to-maturities tell us?," Working Papers halshs-03211699, HAL.
    9. Mohammad Isleimeyyeh, 2020. "The role of financial investors in determining the commodity futures risk premium," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1375-1397, September.
    10. Liu, Lu & Zhang, Xiang, 2019. "Financialization and commodity excess spillovers," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 195-216.
    11. Algieri, Bernardina & Leccadito, Arturo, 2019. "Price volatility and speculative activities in futures commodity markets: A combination of combinations of p-values test," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 40-54.
    12. Bohl Martin T., 2016. "Treiben Indexfonds Agrarrohstoffpreise? Nein!," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 17(2), pages 155-171, July.

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    More about this item

    Keywords

    International topics; Recent economic and financial developments;

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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