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Investigating the spillovers between energy, food, and agricultural commodity markets: New insights from the quantile coherency approach

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  • Khalfaoui, Rabeh
  • Shahzad, Umer
  • Ghaemi Asl, Mahdi
  • Ben Jabeur, Sami

Abstract

The prime objective of this research is to analyze the spillovers and associations between the commodity markets of energy, food, and agriculture products. In doing so, the authors used the most recently available monthly data covering the period of 1960M01 to 2021M04. For empirical analysis, the authors employ the quantile coherency method of Baruník and Kley (2019) to analyze the spillovers between energy, food, and agricultural commodities. The empirical findings indicate less spillover relationships between oil and agriculture on foreign markets in the short and long term. Energy and fertilizers have strong coherency at extreme positive and negative values. During an economic boom, the intense co-movement of oil, agriculture, food, and metal sectors may be negative, highlighting the opportunity for investment diversification.

Suggested Citation

  • Khalfaoui, Rabeh & Shahzad, Umer & Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2023. "Investigating the spillovers between energy, food, and agricultural commodity markets: New insights from the quantile coherency approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 63-80.
    • Handle: RePEc:eee:quaeco:v:88:y:2023:i:c:p:63-80
    DOI: 10.1016/j.qref.2022.12.006
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    1. Tiwari, Aviral Kumar & Boachie, Micheal Kofi & Suleman, Muhammed Tahir & Gupta, Rangan, 2021. "Structure dependence between oil and agricultural commodities returns: The role of geopolitical risks," Energy, Elsevier, vol. 219(C).
    2. Saâdaoui, Foued & Ben Jabeur, Sami & Goodell, John W., 2022. "Causality of geopolitical risk on food prices: Considering the Russo–Ukrainian conflict," Finance Research Letters, Elsevier, vol. 49(C).
    3. Maghyereh, Aktham & Abdoh, Hussein, 2020. "Tail dependence between Bitcoin and financial assets: Evidence from a quantile cross-spectral approach," International Review of Financial Analysis, Elsevier, vol. 71(C).
    4. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Bachmeier, Lance, 2019. "Modelling systemic risk and dependence structure between the prices of crude oil and exchange rates in BRICS economies: Evidence using quantile coherency and NGCoVaR approaches," Energy Economics, Elsevier, vol. 81(C), pages 1011-1028.
    5. Olivier Vidal & Fatma Rostom & Cyril François & Gael Giraud, 2017. "Global Trends in Metal Consumption and Supply: The Raw Material–Energy Nexus," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03903919, HAL.
    6. Ping-Yu Chen & Chia-Lin Chang & Chi-Chung Chen & Michael McAleer, 2012. "Modelling the Effects of Oil Prices on Global Fertilizer Prices and Volatility," JRFM, MDPI, vol. 5(1), pages 1-37, December.
    7. Andreyeva, T. & Long, M.W. & Brownell, K.D., 2010. "The impact of food prices on consumption: A systematic review of research on the price elasticity of demand for food," American Journal of Public Health, American Public Health Association, vol. 100(2), pages 216-222.
    8. Shahzad, Syed Jawad Hussain & Rehman, Mobeen Ur & Jammazi, Rania, 2019. "Spillovers from oil to precious metals: Quantile approaches," Resources Policy, Elsevier, vol. 61(C), pages 508-521.
    9. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    10. Dahl, Roy Endré & Oglend, Atle & Yahya, Muhammad, 2020. "Dynamics of volatility spillover in commodity markets: Linking crude oil to agriculture," Journal of Commodity Markets, Elsevier, vol. 20(C).
    11. Nicola, Francesca de & De Pace, Pierangelo & Hernandez, Manuel A., 2016. "Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment," Energy Economics, Elsevier, vol. 57(C), pages 28-41.
    12. Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Energy commodities, precious metals and industrial metal markets: A nexus across different investment horizons and market conditions," Resources Policy, Elsevier, vol. 70(C).
    13. Algieri, Bernardina & Leccadito, Arturo, 2017. "Assessing contagion risk from energy and non-energy commodity markets," Energy Economics, Elsevier, vol. 62(C), pages 312-322.
    14. Sun, Yanpeng & Mirza, Nawazish & Qadeer, Abdul & Hsueh, Hsin-Pei, 2021. "Connectedness between oil and agricultural commodity prices during tranquil and volatile period. Is crude oil a victim indeed?," Resources Policy, Elsevier, vol. 72(C).
    15. Olivier Vidal & Fatma Rostom & Cyril François & Gael Giraud, 2017. "Global Trends in Metal Consumption and Supply: The Raw Material–Energy Nexus," Post-Print hal-03903919, HAL.
    16. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    17. Eissa, Mohamad Abdelaziz & Al Refai, Hisham, 2019. "Modelling the symmetric and asymmetric relationships between oil prices and those of corn, barley, and rapeseed oil," Resources Policy, Elsevier, vol. 64(C).
    18. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    19. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    20. Jiawen Luo & Qun Zhang, 2021. "Risk contagions between global oil markets and China’s agricultural commodity markets under structural breaks," Applied Economics, Taylor & Francis Journals, vol. 53(5), pages 628-649, January.
    21. Zhang, Chuanguo & Liu, Feng & Yu, Danlin, 2018. "Dynamic jumps in global oil price and its impacts on China's bulk commodities," Energy Economics, Elsevier, vol. 70(C), pages 297-306.
    22. Cui, Jinxin & Goh, Mark & Zou, Huiwen, 2021. "Coherence, extreme risk spillovers, and dynamic linkages between oil and China’s commodity futures markets," Energy, Elsevier, vol. 225(C).
    23. Hau, Liya & Zhu, Huiming & Huang, Rui & Ma, Xiang, 2020. "Heterogeneous dependence between crude oil price volatility and China’s agriculture commodity futures: Evidence from quantile-on-quantile regression," Energy, Elsevier, vol. 213(C).
    24. Stephen Chan & Saralees Nadarajah, 2020. "Extreme Values and Financial Risk," JRFM, MDPI, vol. 13(2), pages 1-3, February.
    25. Jiang, Yonghong & Lie, Jiayi & Wang, Jieru & Mu, Jinqi, 2021. "Revisiting the roles of cryptocurrencies in stock markets: A quantile coherency perspective," Economic Modelling, Elsevier, vol. 95(C), pages 21-34.
    26. 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.
    27. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    28. Zhang, Chuanguo & Qu, Xuqin, 2015. "The effect of global oil price shocks on China's agricultural commodities," Energy Economics, Elsevier, vol. 51(C), pages 354-364.
    29. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    30. Ciaian, Pavel & Kancs, d'Artis, 2011. "Interdependencies in the energy-bioenergy-food price systems: A cointegration analysis," Resource and Energy Economics, Elsevier, vol. 33(1), pages 326-348, January.
    31. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    32. Xiarchos, Irene M. & Burnett, J. Wesley, 2018. "Dynamic Volatility Spillovers Between Agricultural And Energy Commodities," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 50(3), pages 291-318, August.
    33. Claudiu Albulescu & Aviral Tiwari & Qiang Ji, 2020. "Copula-based local dependence between energy, agriculture and metal commodity markets," Papers 2003.04007, arXiv.org.
    34. Natanelov, Valeri & Alam, Mohammad J. & McKenzie, Andrew M. & Van Huylenbroeck, Guido, 2011. "Is there co-movement of agricultural commodities futures prices and crude oil?," Energy Policy, Elsevier, vol. 39(9), pages 4971-4984, September.
    35. Sanyal, Prabuddha & Malczynski, Leonard A. & Kaplan, Paul, 2015. "Impact of Energy Price Variability on Global Fertilizer Price: Application of Alternative Volatility Models," Sustainable Agriculture Research, Canadian Center of Science and Education, vol. 4(4).
    36. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2014. "Oil price shocks and agricultural commodity prices," Energy Economics, Elsevier, vol. 44(C), pages 22-35.
    37. Just, Małgorzata & Echaust, Krzysztof, 2022. "Dynamic spillover transmission in agricultural commodity markets: What has changed after the COVID-19 threat?," Economics Letters, Elsevier, vol. 217(C).
    38. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2016. "Contemporaneous interactions among fuel, biofuel and agricultural commodities," Energy Economics, Elsevier, vol. 58(C), pages 1-10.
    39. Wei Su, Chi & Wang, Xiao-Qing & Tao, Ran & Oana-Ramona, Lobonţ, 2019. "Do oil prices drive agricultural commodity prices? Further evidence in a global bio-energy context," Energy, Elsevier, vol. 172(C), pages 691-701.
    40. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adewuyi, Adeolu O. & Lee, Chien-Chiang, 2022. "Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Energy Economics, Elsevier, vol. 113(C).
    41. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    42. Eleni Zafeiriou & Garyfallos Arabatzis & Paraskevi Karanikola & Stilianos Tampakis & Stavros Tsiantikoudis, 2018. "Agricultural Commodities and Crude Oil Prices: An Empirical Investigation of Their Relationship," Sustainability, MDPI, vol. 10(4), pages 1-11, April.
    43. Shiferaw, Yegnanew A., 2019. "Time-varying correlation between agricultural commodity and energy price dynamics with Bayesian multivariate DCC-GARCH models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    44. Hanif, Waqas & Mensi, Walid & Gubareva, Mariya & Teplova, Tamara, 2023. "Impacts of COVID-19 on dynamic return and volatility spillovers between rare earth metals and renewable energy stock markets," Resources Policy, Elsevier, vol. 80(C).
    45. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(C).
    46. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Balli, Faruk & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency domain quantile coherence of emerging stock markets with gold and oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    47. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    48. 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.
    49. Rehman, Mobeen Ur & Bouri, Elie & Eraslan, Veysel & Kumar, Satish, 2019. "Energy and non-energy commodities: An asymmetric approach towards portfolio diversification in the commodity market," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    50. 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.
    51. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
    52. 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).
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    More about this item

    Keywords

    Energy; Food; Agricultural commodity; Co-movements; Quantile coherency;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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