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Quantile VAR connectedness and price spillovers between soybean and energy

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  • Das, Narasingha
  • Tanin, Tauhidul Islam
  • Gangopadhyay, Partha
  • Abbas, Qaiser
  • Akadiri, Seyi Saint
  • Janjua, Laeeq Razzak

Abstract

We analyze the relationship between US energy (i.e., crude oil, diesel, gasoline, and ethanol) and soybean prices using monthly data from 2005 to 2024. Using a quantile VAR connectedness model, we examine the interplay between energy and food prices across different quantiles. Our findings show that 96 % of the volatility in the network of fossil fuel, biofuel, and food prices is driven by changes in this network. Crude oil and ethanol prices primarily transmit shocks that influence soybean prices, whereas soybean price changes impact ethanol prices, creating feedback mechanisms. Soybean and gasoline prices showed the most significant shocks in the nexus. Our study reveals the dynamic feedback between prices and their interaction within the network, contributing to the understanding of the consequences of biofuels as a clean energy source. Rigorous robustness tests using cross-quantilogram and wavelet quantile correlation validate our findings, offering insights for policymakers managing energy and food price fluctuations.

Suggested Citation

  • Das, Narasingha & Tanin, Tauhidul Islam & Gangopadhyay, Partha & Abbas, Qaiser & Akadiri, Seyi Saint & Janjua, Laeeq Razzak, 2025. "Quantile VAR connectedness and price spillovers between soybean and energy," Energy Economics, Elsevier, vol. 149(C).
    • Handle: RePEc:eee:eneeco:v:149:y:2025:i:c:s0140988325006012
    DOI: 10.1016/j.eneco.2025.108774
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    as
    1. Giorgio Fagiolo & Javier Reyes & Stefano Schiavo, 2010. "The evolution of the world trade web: a weighted-network analysis," Journal of Evolutionary Economics, Springer, vol. 20(4), pages 479-514, August.
    2. Odhiambo, Nicholas M., 2009. "Finance-growth-poverty nexus in South Africa: A dynamic causality linkage," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(2), pages 320-325, March.
    3. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425, June.
    4. Barry K. Goodwin & Nicholas E. Piggott, 2001. "Spatial Market Integration in the Presence of Threshold Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 302-317.
    5. Jiang, Wei & Chen, Yunfei, 2024. "Impact of Russia-Ukraine conflict on the time-frequency and quantile connectedness between energy, metal and agricultural markets," Resources Policy, Elsevier, vol. 88(C).
    6. Kilian, Lutz, 2022. "Understanding the estimation of oil demand and oil supply elasticities," Energy Economics, Elsevier, vol. 107(C).
    7. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    8. Chatziantoniou, Ioannis & Gabauer, David & Stenfors, Alexis, 2021. "Interest rate swaps and the transmission mechanism of monetary policy: A quantile connectedness approach," Economics Letters, Elsevier, vol. 204(C).
    9. Zhang, Tianding & Zeng, Song, 2023. "Dynamic comovement and extreme risk spillovers between international crude oil and China's non-ferrous metal futures market," Resources Policy, Elsevier, vol. 80(C).
    10. Lucotte, Yannick, 2016. "Co-movements between crude oil and food prices: A post-commodity boom perspective," Economics Letters, Elsevier, vol. 147(C), pages 142-147.
    11. Aurélien Leroy & Yannick Lucotte, 2016. "Co-movements between crude oil and food prices: A post-commodity boom perspective," Post-Print hal-03528419, HAL.
    12. Zaghum Umar & Adam Zaremba & Dennis Olson, 2022. "Seven centuries of commodity co-movement: a wavelet analysis approach," Applied Economics Letters, Taylor & Francis Journals, vol. 29(4), pages 355-359, February.
    13. Liu, Li & Tan, Siming & Wang, Yudong, 2020. "Can commodity prices forecast exchange rates?," Energy Economics, Elsevier, vol. 87(C).
    14. Hanif, Waqas & Hadhri, Sinda & El Khoury, Rim, 2024. "Quantile spillovers and connectedness between oil shocks and stock markets of the largest oil producers and consumers," Journal of Commodity Markets, Elsevier, vol. 34(C).
    15. Kumar, Anoop S & Padakandla, Steven Raj, 2022. "Testing the safe-haven properties of gold and bitcoin in the backdrop of COVID-19: A wavelet quantile correlation approach," Finance Research Letters, Elsevier, vol. 47(PB).
    16. Tanin, Tauhidul Islam & Sarker, Ashutosh & Hammoudeh, Shawkat & Batten, Jonathan A., 2024. "The determinants of corporate cost of debt during a financial crisis," The British Accounting Review, Elsevier, vol. 56(6).
    17. Baumöhl, Eduard & Lyócsa, Štefan, 2017. "Directional predictability from stock market sector indices to gold: A cross-quantilogram analysis," Finance Research Letters, Elsevier, vol. 23(C), pages 152-164.
    18. Florin Aliu & Jiří Kučera & Simona Hašková, 2023. "Agricultural Commodities in the Context of the Russia-Ukraine War: Evidence from Corn, Wheat, Barley, and Sunflower Oil," Forecasting, MDPI, vol. 5(1), pages 1-23, March.
    19. Abdallah, Chadi & Kpodar, Kangni, 2023. "How large and persistent is the response of inflation to changes in retail energy prices?," Journal of International Money and Finance, Elsevier, vol. 132(C).
    20. Ayres, Joao & Hevia, Constantino & Nicolini, Juan Pablo, 2020. "Real exchange rates and primary commodity prices," Journal of International Economics, Elsevier, vol. 122(C).
    21. Nazlioglu, Saban & Soytas, Ugur, 2011. "World oil prices and agricultural commodity prices: Evidence from an emerging market," Energy Economics, Elsevier, vol. 33(3), pages 488-496, May.
    22. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    23. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    24. Tanin, Tauhidul Islam & Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf Mohsen & Brooks, Robert, 2022. "Risk transmission from the oil market to Islamic and conventional banks in oil-exporting and oil-importing countries," Energy Economics, Elsevier, vol. 115(C).
    25. Khalfaoui, Rabeh & Mefteh-Wali, Salma & Viviani, Jean-Laurent & Ben Jabeur, Sami & Abedin, Mohammad Zoynul & Lucey, Brian M., 2022. "How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    26. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    27. Scott H. Irwin & Dwight R. Sanders, 2011. "Index Funds, Financialization, and Commodity Futures Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 1-31.
    28. Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
    29. Md. Abdur Rahman Forhad & Md Rafayet Alam, 2022. "Impact of oil demand and supply shocks on food-grain prices: a Markov-switching approach," Applied Economics, Taylor & Francis Journals, vol. 54(10), pages 1199-1211, February.
    30. Batten, Jonathan A. & Mo, Di & Pourkhanali, Armin, 2024. "Can inflation predict energy price volatility?," Energy Economics, Elsevier, vol. 129(C).
    31. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
    32. Linton, O. & Whang, Yoon-Jae, 2007. "The quantilogram: With an application to evaluating directional predictability," Journal of Econometrics, Elsevier, vol. 141(1), pages 250-282, November.
    33. Yépez, Carlos & Dzikpe, Francis, 2022. "Accounting for real exchange rates in emerging economies: The role of commodity prices," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 476-492.
    34. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    35. Hanif, Waqas & Areola Hernandez, Jose & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2021. "Tail dependence risk and spillovers between oil and food prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 195-209.
    36. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    37. Manner, Hans & Rodríguez, Gabriel & Stöckler, Florian, 2024. "A changepoint analysis of exchange rate and commodity price risks for Latin American stock markets," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1385-1403.
    38. Esmaeili, Abdoulkarim & Shokoohi, Zainab, 2011. "Assessing the effect of oil price on world food prices: Application of principal component analysis," Energy Policy, Elsevier, vol. 39(2), pages 1022-1025, February.
    39. Boateng, Ebenezer & Asafo-Adjei, Emmanuel & Addison, Alex & Quaicoe, Serebour & Yusuf, Mawusi Ayisat & Abeka, Mac Junior & Adam, Anokye M., 2022. "Interconnectedness among commodities, the real sector of Ghana and external shocks," Resources Policy, Elsevier, vol. 75(C).
    40. Nazlioglu, Saban & Soytas, Ugur, 2012. "Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis," Energy Economics, Elsevier, vol. 34(4), pages 1098-1104.
    41. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    42. Taghizadeh-Hesary, Farhad & Rasoulinezhad, Ehsan & Yoshino, Naoyuki, 2019. "Energy and Food Security: Linkages through Price Volatility," Energy Policy, Elsevier, vol. 128(C), pages 796-806.
    43. Bigerna, Simona, 2023. "Energy price shocks, exchange rates and inflation nexus," Energy Economics, Elsevier, vol. 128(C).
    44. Mutran, Victoria M. & Ribeiro, Celma O. & Nascimento, Claudio A.O. & Chachuat, Benoît, 2020. "Risk-conscious optimization model to support bioenergy investments in the Brazilian sugarcane industry," Applied Energy, Elsevier, vol. 258(C).
    45. Tanin, Tauhidul Islam & Sarker, Ashutosh & Brooks, Robert & Do, Hung Xuan, 2022. "Does oil impact gold during COVID-19 and three other recent crises?," Energy Economics, Elsevier, vol. 108(C).
    46. Dumortier, Jerome & Carriquiry, Miguel & Elobeid, Amani, 2021. "Where does all the biofuel go? Fuel efficiency gains and its effects on global agricultural production," Energy Policy, Elsevier, vol. 148(PA).
    47. Faria-e-Castro, Miguel, 2021. "Fiscal policy during a pandemic," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    48. Millinger, M. & Reichenberg, L. & Hedenus, F. & Berndes, G. & Zeyen, E. & Brown, T., 2022. "Are biofuel mandates cost-effective? - An analysis of transport fuels and biomass usage to achieve emissions targets in the European energy system," Applied Energy, Elsevier, vol. 326(C).
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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • F65 - International Economics - - Economic Impacts of Globalization - - - Finance
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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