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Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak

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  • Hung, Ngo Thai

Abstract

This paper represents an analysis of the spillover effects and time-frequency connectedness between crude oil prices and agricultural commodity markets using both the spillover index of Diebold and Yilmaz (2012) and the wavelet coherence model to evaluate whether the time-varying return spillover index exhibited the intensity and direction of transmission during the Covid-19 outbreak. Overall, the current results shed light on that in comparison with the pre-Covid-19 period, and the return spillover is more apparent during the Covid-19 crisis. However, levels of the intensity of this relationship vary through the period of research, with several intervals witnessing both negative and positive interactions. Further, our findings indicate significant heterogeneity among agriculture commodity markets in the degree of spillover to crude oil prices over time, amplifying our understanding of the economic channels through which the agriculture commodity markets are correlated. More importantly, there exist significant dependent patterns about the information spillovers across the crude oil and agriculture commodity markets might provide prominent implications for portfolio managers, investors, and government agencies.

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  • Hung, Ngo Thai, 2021. "Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 73(C).
    • Handle: RePEc:eee:jrpoli:v:73:y:2021:i:c:s0301420721002476
    DOI: 10.1016/j.resourpol.2021.102236
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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. Peersman, Gert & Rüth, Sebastian K. & Van der Veken, Wouter, 2021. "The interplay between oil and food commodity prices: Has it changed over time?," Journal of International Economics, Elsevier, vol. 133(C).
    3. Zhang, Dayong & Hu, Min & Ji, Qiang, 2020. "Financial markets under the global pandemic of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    4. Borgards, Oliver & Czudaj, Robert L. & Hoang, Thi Hong Van, 2021. "Price overreactions in the commodity futures market: An intraday analysis of the Covid-19 pandemic impact," Resources Policy, Elsevier, vol. 71(C).
    5. Shekhar Mishra & Avik Sinha & Arshian Sharif & Norazah Mohd Suki, 2020. "Dynamic linkages between tourism, transportation, growth and carbon emission in the USA: evidence from partial and multiple wavelet coherence," Current Issues in Tourism, Taylor & Francis Journals, vol. 23(21), pages 2733-2755, November.
    6. 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).
    7. Fasanya, Ismail & Akinbowale, Seun, 2019. "Modelling the return and volatility spillovers of crude oil and food prices in Nigeria," Energy, Elsevier, vol. 169(C), pages 186-205.
    8. Satish Kumar & Aviral Kumar Tiwari & I. D. Raheem & Qiang Ji, 2020. "Dependence risk analysis in energy, agricultural and precious metals commodities: a pair vine copula approach," Applied Economics, Taylor & Francis Journals, vol. 52(28), pages 3055-3072, June.
    9. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    10. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2020. "Risk and Financial Management of COVID-19 in Business, Economics and Finance," JRFM, MDPI, vol. 13(5), pages 1-7, May.
    11. Atems, Bebonchu & Melichar, Mark, 2019. "Do Global Crude Oil Market Shocks Have Differential Effects On Us Regions?," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1978-2008, July.
    12. Kumar, Satish & Tiwari, Aviral Kumar & Raheem, Ibrahim Dolapo & Hille, Erik, 2021. "Time-varying dependence structure between oil and agricultural commodity markets: A dependence-switching CoVaR copula approach," Resources Policy, Elsevier, vol. 72(C).
    13. Al-Yahyaee, Khamis Hamed & Rehman, Mobeen Ur & Wanas Al-Jarrah, Idries Mohammad & Mensi, Walid & Vo, Xuan Vinh, 2020. "Co-movements and spillovers between prices of precious metals and non-ferrous metals: A multiscale analysis," Resources Policy, Elsevier, vol. 67(C).
    14. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    15. Duc Hong Vo & Tan Ngoc Vu & Anh The Vo & Michael McAleer, 2019. "Modeling the Relationship between Crude Oil and Agricultural Commodity Prices," Energies, MDPI, vol. 12(7), pages 1-41, April.
    16. Tiwari, Aviral Kumar & Khalfaoui, Rabeh & Solarin, Sakiru Adebola & Shahbaz, Muhammad, 2018. "Analyzing the time-frequency lead–lag relationship between oil and agricultural commodities," Energy Economics, Elsevier, vol. 76(C), pages 470-494.
    17. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Gold, oil, and stocks: Dynamic correlations," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 186-201.
    18. Goodell, John W. & Goutte, Stephane, 2021. "Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 38(C).
    19. Nagayev, Ruslan & Disli, Mustafa & Inghelbrecht, Koen & Ng, Adam, 2016. "On the dynamic links between commodities and Islamic equity," Energy Economics, Elsevier, vol. 58(C), pages 125-140.
    20. Madaleno, Mara & Pinho, Carlos, 2014. "Wavelet dynamics for oil-stock world interactions," Energy Economics, Elsevier, vol. 45(C), pages 120-133.
    21. 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.
    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. 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.
    24. Goodell, John W., 2020. "COVID-19 and finance: Agendas for future research," Finance Research Letters, Elsevier, vol. 35(C).
    25. 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.
    26. Zhan-Ming Chen & Liyuan Wang & Xiao-Bing Zhang & Xinye Zheng, 2019. "The Co-Movement and Asymmetry between Energy and Grain Prices: Evidence from the Crude Oil and Corn Markets," Energies, MDPI, vol. 12(7), pages 1-18, April.
    27. Kang, Sang Hoon & Uddin, Gazi Salah & Troster, Victor & Yoon, Seong-Min, 2019. "Directional spillover effects between ASEAN and world stock markets," Journal of Multinational Financial Management, Elsevier, vol. 52.
    28. 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).
    29. Sharif, Arshian & Aloui, Chaker & Yarovaya, Larisa, 2020. "COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach," International Review of Financial Analysis, Elsevier, vol. 70(C).
    30. Yaxian Lu & Longguang Yang & Lihong Liu, 2019. "Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    31. Ngo Thai Hung, 2020. "Market integration among foreign exchange rate movements in central and eastern European countries," Society and Economy, Akadémiai Kiadó, Hungary, vol. 42(1), pages 1-20, March.
    32. 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).
    33. Bouri, Elie & Shahzad, Syed Jawad Hussain & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2020. "Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 156-164.
    34. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
    35. 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.
    36. 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).
    37. Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
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    More about this item

    Keywords

    COVID-19; Agricultural commodity; Crude oil; Wavelet coherence; Spillover index; JEL Clarifications: C11; C52; Q41;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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