IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v149y2025ics0140988325006012.html

Quantile VAR connectedness and price spillovers between soybean and energy

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325006012
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2025.108774?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    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. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425, June.
    3. Kilian, Lutz, 2022. "Understanding the estimation of oil demand and oil supply elasticities," Energy Economics, Elsevier, vol. 107(C).
    4. 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).
    5. 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).
    6. Liu, Li & Tan, Siming & Wang, Yudong, 2020. "Can commodity prices forecast exchange rates?," Energy Economics, Elsevier, vol. 87(C).
    7. 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).
    8. 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).
    9. 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.
    10. 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).
    11. 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.
    12. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    13. 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).
    14. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    15. 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.
    16. 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).
    17. Batten, Jonathan A. & Mo, Di & Pourkhanali, Armin, 2024. "Can inflation predict energy price volatility?," Energy Economics, Elsevier, vol. 129(C).
    18. 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.
    19. 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.
    20. 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.
    21. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    22. 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.
    23. Bigerna, Simona, 2023. "Energy price shocks, exchange rates and inflation nexus," Energy Economics, Elsevier, vol. 128(C).
    24. 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).
    25. Faria-e-Castro, Miguel, 2021. "Fiscal policy during a pandemic," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    26. 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).
    27. 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.
    28. 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.
    29. 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).
    30. 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.
    31. 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.
    32. Aurélien Leroy & Yannick Lucotte, 2016. "Co-movements between crude oil and food prices: A post-commodity boom perspective," Post-Print hal-03528419, HAL.
    33. 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.
    34. 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).
    35. 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.
    36. Ayres, Joao & Hevia, Constantino & Nicolini, Juan Pablo, 2020. "Real exchange rates and primary commodity prices," Journal of International Economics, Elsevier, vol. 122(C).
    37. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    44. 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.
    45. 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).
    46. 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.
    47. 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).
    48. 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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, Yan & Cheng, Sheng, 2021. "Impact of COVID-19 outbreak on multi-scale asymmetric spillovers between food and oil prices," Resources Policy, Elsevier, vol. 74(C).
    2. 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.
    3. Filip, Ondrej & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2019. "Food versus fuel: An updated and expanded evidence," Energy Economics, Elsevier, vol. 82(C), pages 152-166.
    4. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    5. Kang, Sang Hoon & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2019. "Exploring the time-frequency connectedness and network among crude oil and agriculture commodities V1," Energy Economics, Elsevier, vol. 84(C).
    6. Atik, Zehra & Guloglu, Bulent & Ulussever, Talat, 2024. "Nonlinear tail dependence between energy and agricultural commodities," Energy Economics, Elsevier, vol. 139(C).
    7. Karel Janda & Ladislav Kristoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods, Outcomes, and Lessons for Commodity Price Risk Management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    9. Agus Widarjono & Indah Susantun & Sarastri M. Ruchba & Ari Rudatin, 2020. "Oil and Food Prices for a Net Oil Importing-country: How Are Related in Indonesia?," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 255-263.
    10. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Nguyen, Duc Khuong, 2020. "Dynamic volatility spillover effects between oil and agricultural products," International Review of Financial Analysis, Elsevier, vol. 69(C).
    11. Dervis Kirikkaleli & Hasan Güngör, 2021. "Co-movement of commodity price indexes and energy price index: a wavelet coherence approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    12. Puneet Vatsa & Dragan Miljkovic, 2022. "Energy and crop price cycles before and after the global financial crisis: A new approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 220-233, February.
    13. Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
    14. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    15. Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Uddin, Gazi Salah & Kang, Sang Hoon, 2019. "Can agricultural and precious metal commodities diversify and hedge extreme downside and upside oil market risk? An extreme quantile approach," Resources Policy, Elsevier, vol. 62(C), pages 588-601.
    16. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.
    17. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2014. "Oil price shocks and agricultural commodity prices," Energy Economics, Elsevier, vol. 44(C), pages 22-35.
    18. Loretta Mastroeni & Alessandro Mazzoccoli & Greta Quaresima & Pierluigi Vellucci, 2021. "Wavelet analysis and energy-based measures for oil-food price relationship as a footprint of financialisation effect," Papers 2104.11891, arXiv.org, revised Mar 2022.
    19. Guellil, Mohammed Seghir & Benbouziane, Mohamed, 2018. "Volatility Linkages between Agricultural Commodity Prices, Oil Prices and Real USD Exchange Rate || Vínculos de volatilidad entre precios de productos agrícolas, precios del petróleo y tipo de cambio del dólar estadounidense," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 71-83, Diciembre.
    20. Ni, Guohua & Teng, Man & Chen, Zhenling & Wu, Yunsong & He, Wenjia & Su, Bin, 2024. "Exploring the impacts of major events on the global oil and food markets," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:149:y:2025:i:c:s0140988325006012. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.