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Effects of growing-season weather on the dynamic price relationships between biofuel feedstocks

Author

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  • Goswami, Alankrita
  • Karali, Berna

Abstract

Our study is the first to examine the effects of growing-season weather conditions on both the mean and variance of futures returns in the multipurpose agricultural commodity markets of U.S. soybean oil, Canadian canola, and Malaysian/Indonesian palm oil, based on their significance as substitutes in the global food and energy sectors. We use the vegetation health index (VHI) from major feedstock-growing regions in North America, Brazil, Malaysia, and Indonesia as an indicator of the anticipations of the future crop supply. We assess the impact of current VHI on price dynamics in these markets, we employ the EGARCH-X-DCC framework, which captures the effect of VHI-related news on both returns and short-term volatility in the food and biofuel markets. We also extend our analysis to explore how a crop's VHI, as a slow-moving determinant, influences volatility not only in its own market but also in substitute markets. For this, we use the GARCH-MIDAS-DCC framework, in which one year's worth of VHI acts as the slow-moving component in the MIDAS filter, allowing us to isolate the impact of slowly changing growing conditions on daily volatilities through the long-run component and the dynamic correlations between commodity returns. We find that information about current and longer-term growing-season weather conditions affects both the primary crop market and its substitutes. Furthermore, the broader set of crop condition information increases variability in the long-run correlation between commodity returns.

Suggested Citation

  • Goswami, Alankrita & Karali, Berna, 2025. "Effects of growing-season weather on the dynamic price relationships between biofuel feedstocks," Energy Economics, Elsevier, vol. 148(C).
    • Handle: RePEc:eee:eneeco:v:148:y:2025:i:c:s0140988325004050
    DOI: 10.1016/j.eneco.2025.108581
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    References listed on IDEAS

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    1. Marco Letta & Pierluigi Montalbano & Guillaume Pierre, 2022. "Weather shocks, traders' expectations, and food prices," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(3), pages 1100-1119, May.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Massimo Peri, 2017. "Climate variability and the volatility of global maize and soybean prices," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(4), pages 673-683, August.
    4. Siqing Xu & Rong Wang & Thomas Gasser & Philippe Ciais & Josep Peñuelas & Yves Balkanski & Olivier Boucher & Ivan A. Janssens & Jordi Sardans & James H. Clark & Junji Cao & Xiaofan Xing & Jianmin Chen, 2022. "Delayed use of bioenergy crops might threaten climate and food security," Nature, Nature, vol. 609(7926), pages 299-306, September.
    5. Karali, Berna, 2012. "Do USDA Announcements Affect Comovements Across Commodity Futures Returns?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(01), pages 1-21, April.
    6. Ruiqing Miao & Madhu Khanna & Haixiao Huang, 2016. "Responsiveness of Crop Yield and Acreage to Prices and Climate," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(1), pages 191-211.
    7. Philip Garcia & Scott H. Irwin & Aaron Smith, 2015. "Futures Market Failure?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 40-64.
    8. Wright, Brian, 2014. "Global Biofuels: Key to the Puzzle of Grain Market Behavior," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt11715438, Department of Agricultural & Resource Economics, UC Berkeley.
    9. David A. Hennessy & Thomas I. Wahl, 1996. "The Effects of Decision Making on Futures Price Volatility," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(3), pages 591-603.
    10. repec:ags:jrapmc:122315 is not listed on IDEAS
    11. Xiaomeng Cui & Wei Xie, 2022. "Adapting Agriculture to Climate Change through Growing Season Adjustments: Evidence from Corn in China," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(1), pages 249-272, January.
    12. 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.
    13. Brian Wright, 2014. "Global Biofuels: Key to the Puzzle of Grain Market Behavior," Journal of Economic Perspectives, American Economic Association, vol. 28(1), pages 73-98, Winter.
    14. Huayun Jiang & Jen‐Je Su & Neda Todorova & Eduardo Roca, 2016. "Spillovers and Directional Predictability with a Cross‐Quantilogram Analysis: The Case of U.S. and Chinese Agricultural Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(12), pages 1231-1255, December.
    15. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    16. Su, Yuandong & Liang, Chao & Zhang, Li & Zeng, Qing, 2022. "Uncover the response of the U.S grain commodity market on El Niño–Southern Oscillation," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 98-112.
    17. Gu, Qinen & Li, Shaofang & Tian, Sihua & Wang, Yuyouting, 2024. "Impact of climate risk on energy market risk spillover: Evidence from dynamic heterogeneous network analysis," Energy Economics, Elsevier, vol. 137(C).
    18. David Ubilava, 2018. "The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 239-263.
    19. Theresa Osborne, 2004. "Market News in Commodity Price Theory: Application to the Ethiopian Grain Market," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(1), pages 133-164.
    20. Zhang, Dongna & Dai, Xingyu & Wang, Qunwei & Lau, Chi Keung Marco, 2023. "Impacts of weather conditions on the US commodity markets systemic interdependence across multi-timescales," Energy Economics, Elsevier, vol. 123(C).
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    Keywords

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

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