IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v105y2021ics0264999321002406.html
   My bibliography  Save this article

Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises

Author

Listed:
  • Zhu, Bo
  • Lin, Renda
  • Deng, Yuanyue
  • Chen, Pingshe
  • Chevallier, Julien

Abstract

Considering the severity and frequency of industry-specific shocks, this paper examines how sector-induced contagion effects caused by significant crises (e.g., the global financial crisis and COVID-19) propagate between energy and agricultural sectors worldwide. Relevant literature fails to concern the influence of these cross-sectoral transmission mechanisms on the energy-agriculture nexus and its relevance. By modifying the copula-extreme value theory-marginal expected shortfall (Copula-EVT-MES) method and using daily commodity returns from 2005M3–2020M5, our study captures significant intersectoral systemic risk spillovers, with asymmetrical and persistent patterns in energy-agricultural pairs. Furthermore, the bioethanol production (physical channel) and the financialization of commodities (financial channel) mainly relate to the shock spillovers. Compared to the financial crisis, the systemic risk spillovers in the COVID-19 crisis rely more on the physical channel, which emphasizes the importance of bioenergy-related shocks. The macro-conditions and supply-demand shocks are also important determinants for such spillovers during the ongoing crisis.

Suggested Citation

  • Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    • Handle: RePEc:eee:ecmode:v:105:y:2021:i:c:s0264999321002406
    DOI: 10.1016/j.econmod.2021.105651
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999321002406
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2021.105651?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Ioannis Bournakis & Dimitris Christopoulos & Sushanta Mallick, 2018. "Knowledge Spillovers And Output Per Worker: An Industry‐Level Analysis For Oecd Countries," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 1028-1046, April.
    2. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    3. Ing-Haw Cheng & Wei Xiong, 2014. "Financialization of Commodity Markets," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 419-441, December.
    4. Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
    5. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.
    6. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    7. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    8. Brian M. Dillon & Christopher B. Barrett, 2016. "Global Oil Prices and Local Food Prices: Evidence from East Africa," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(1), pages 154-171.
    9. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Nguyen, Duc Khuong, 2011. "Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure?," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 130-141, January.
    10. Paul Kupiec & Levent Güntay, 2016. "Testing for Systemic Risk Using Stock Returns," Journal of Financial Services Research, Springer;Western Finance Association, vol. 49(2), pages 203-227, June.
    11. D. Guegan & J. Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 421-430.
    12. Trujillo-Barrera, Andres & Mallory, Mindy L. & Garcia, Philip, 2012. "Volatility Spillovers in U.S. Crude Oil, Ethanol, and Corn Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-16, August.
    13. Bhattarai, Keshab & Mallick, Sushanta K. & Yang, Bo, 2021. "Are global spillovers complementary or competitive? Need for international policy coordination," Journal of International Money and Finance, Elsevier, vol. 110(C).
    14. Saghaian, Sayed & Nemati, Mehdi & Walters, Cory & Chen, Bo, 2018. "Asymmetric Price Volatility Transmission between U.S. Biofuel, Corn, and Oil Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(1), January.
    15. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    16. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 437-480, Fall.
    17. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    18. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    19. Michael Sockin & Wei Xiong, 2015. "Informational Frictions and Commodity Markets," Journal of Finance, American Finance Association, vol. 70(5), pages 2063-2098, October.
    20. Adams, Zeno & Collot, Solène & Kartsakli, Maria, 2020. "Have commodities become a financial asset? Evidence from ten years of Financialization," Energy Economics, Elsevier, vol. 89(C).
    21. Massaporn Cheuathonghua & Chaiyuth Padungsaksawasdi & Pattana Boonchoo & Jittima Tongurai, 2019. "Extreme spillovers of VIX fear index to international equity markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(1), pages 1-38, March.
    22. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    23. Niels Joachim Gormsen & Ralph S J Koijen & Nikolai Roussanov, 0. "Coronavirus: Impact on Stock Prices and Growth Expectations," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 574-597.
    24. Straetmans, Stefan & Chaudhry, Sajid M., 2015. "Tail risk and systemic risk of US and Eurozone financial institutions in the wake of the global financial crisis," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 191-223.
    25. An, Henry & Qiu, Feng & Rude, James, 2021. "Volatility spillovers between food and fuel markets: Do administrative regulations affect the transmission?," Economic Modelling, Elsevier, vol. 102(C).
    26. El Montasser, Ghassen & Gupta, Rangan & Martins, Andre Luis & Wanke, Peter, 2015. "Are there multiple bubbles in the ethanol–gasoline price ratio of Brazil?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 19-23.
    27. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    28. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    29. Smales, L.A., 2021. "Geopolitical risk and volatility spillovers in oil and stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 358-366.
    30. Lyu, Yongjian & Yi, Heling & Wei, Yu & Yang, Mo, 2021. "Revisiting the role of economic uncertainty in oil price fluctuations: Evidence from a new time-varying oil market model," Economic Modelling, Elsevier, vol. 103(C).
    31. Zhang, Wenting & Hamori, Shigeyuki, 2021. "Crude oil market and stock markets during the COVID-19 pandemic: Evidence from the US, Japan, and Germany," International Review of Financial Analysis, Elsevier, vol. 74(C).
    32. Nguyen, Linh Xuan Diep & Mateut, Simona & Chevapatrakul, Thanaset, 2020. "Business-linkage volatility spillovers between US industries," Journal of Banking & Finance, Elsevier, vol. 111(C).
    33. Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Post-Print halshs-00368334, HAL.
    34. Wang, Xiaoting & Hou, Siyuan & Shen, Jie, 2021. "Default clustering of the nonfinancial sector and systemic risk: Evidence from China," Economic Modelling, Elsevier, vol. 96(C), pages 196-208.
    35. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    36. Juan Wu & Xue Wang & Stephen G. Walker, 2014. "Bayesian Nonparametric Inference for a Multivariate Copula Function," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 747-763, September.
    37. Ye, Wuyi & Guo, Ranran & Deschamps, Bruno & Jiang, Ying & Liu, Xiaoquan, 2021. "Macroeconomic forecasts and commodity futures volatility," Economic Modelling, Elsevier, vol. 94(C), pages 981-994.
    38. Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," PSE-Ecole d'économie de Paris (Postprint) halshs-00368334, HAL.
    39. Rizwan, Muhammad Suhail & Ahmad, Ghufran & Ashraf, Dawood, 2020. "Systemic risk: The impact of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    40. Wang, Yajie & Yu, Huan & Zhang, Hongda & Chen, Tianyu, 2021. "Non-linear analysis of effects of energy consumption on economic growth in China: Role of real exchange rate," Economic Modelling, Elsevier, vol. 104(C).
    41. Fabio Busetti & Andrew Harvey, 2011. "When is a Copula Constant? A Test for Changing Relationships," Journal of Financial Econometrics, Oxford University Press, vol. 9(1), pages 106-131, Winter.
    42. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    43. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
    44. Philip Liu & Konstantinos Theodoridis & Haroon Mumtaz & Francesco Zanetti, 2019. "Changing Macroeconomic Dynamics at the Zero Lower Bound," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 391-404, July.
    45. Jawadi, Fredj & Mallick, Sushanta K. & Sousa, Ricardo M., 2016. "Fiscal and monetary policies in the BRICS: A panel VAR approach," Economic Modelling, Elsevier, vol. 58(C), pages 535-542.
    46. Massimo Peri & Lucia Baldi & Daniela Vandone, 2013. "Price discovery in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(4), pages 397-403, March.
    47. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    48. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    49. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    50. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
    51. Walters, Cory, 2018. "Price Volatility Transmission between U.S. Biofuel, Corn, and Oil Markets," Cornhusker Economics 307037, University of Nebraska-Lincoln, Department of Agricultural Economics.
    52. Algieri, Bernardina & Leccadito, Arturo, 2017. "Assessing contagion risk from energy and non-energy commodity markets," Energy Economics, Elsevier, vol. 62(C), pages 312-322.
    53. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    54. 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.
    55. 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.
    56. Kumar, Abhishek & Mallick, Sushanta & Sinha, Apra, 2021. "Is uncertainty the same everywhere? Advanced versus emerging economies," Economic Modelling, Elsevier, vol. 101(C).
    57. Alexakis, Christos & Pappas, Vasileios, 2018. "Sectoral dynamics of financial contagion in Europe - The cases of the recent crises episodes," Economic Modelling, Elsevier, vol. 73(C), pages 222-239.
    58. Brandt, Michael W. & Gao, Lin, 2019. "Macro fundamentals or geopolitical events? A textual analysis of news events for crude oil," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 64-94.
    59. Christos Alexakis & Vasileios Pappas, 2018. "Sectoral dynamics of financial contagion in Europe - The cases of the recent crises episodes," Post-Print hal-01992102, HAL.
    60. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    61. Song-Zan Chiou-Wei, Sheng-Hung Chen, and Zhen Zhu, 2019. "Energy and Agricultural Commodity Markets Interaction: An Analysis of Crude Oil, Natural Gas, Corn, Soybean, and Ethanol Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    62. 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.
    63. 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.
    64. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-362, July.
    65. Escribano, Ana & Maggi, Mario, 2019. "Intersectoral default contagion: A multivariate Poisson autoregression analysis," Economic Modelling, Elsevier, vol. 82(C), pages 376-400.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    2. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    3. Mathias Mandla Manguzvane & John Weirstrass Muteba Mwamba, 2022. "South African Banks’ Cross-Border Systemic Risk Exposure: An Application of the GAS Copula Marginal Expected Shortfall," IJFS, MDPI, vol. 10(1), pages 1-19, March.
    4. Lu, Ran & Xu, Wen & Zeng, Hongjun & Zhou, Xiangjing, 2023. "Volatility connectedness among the Indian equity and major commodity markets under the COVID-19 scenario," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1465-1481.
    5. 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).
    6. Li, Zhinan & Pei, Shan & Li, Ting & Wang, Yu, 2023. "Risk spillover network in the supply chain system during the COVID-19 crisis: Evidence from China," Economic Modelling, Elsevier, vol. 126(C).
    7. Wu, You & Ren, Wenting & Wan, Jieru & Liu, Xiaoxue, 2023. "Time-frequency volatility connectedness between fossil energy and agricultural commodities: Comparing the COVID-19 pandemic with the Russia-Ukraine conflict," Finance Research Letters, Elsevier, vol. 55(PA).
    8. Song, Feng & Cui, Jian & Yu, Yihua, 2022. "Dynamic volatility spillover effects between wind and solar power generations: Implications for hedging strategies and a sustainable power sector," Economic Modelling, Elsevier, vol. 116(C).
    9. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Tiwari, Aviral Kumar & Farid, Saqib, 2023. "Comparing asymmetric price efficiency in regional ESG markets before and during COVID-19," Economic Modelling, Elsevier, vol. 118(C).

    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. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    2. 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.
    3. Cheng, Natalie Fang Ling & Hasanov, Akram Shavkatovich & Poon, Wai Ching & Bouri, Elie, 2023. "The US-China trade war and the volatility linkages between energy and agricultural commodities," Energy Economics, Elsevier, vol. 120(C).
    4. 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.
    5. Vo, Long Hai & Le, Thai-Ha, 2021. "Eatery, energy, environment and economic system, 1970–2017: Understanding volatility spillover patterns in a global sample," Energy Economics, Elsevier, vol. 100(C).
    6. 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).
    7. 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).
    8. 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.
    9. Yahya, Muhammad & Dutta, Anupam & Bouri, Elie & Wadström, Christoffer & Uddin, Gazi Salah, 2022. "Dependence structure between the international crude oil market and the European markets of biodiesel and rapeseed oil," Renewable Energy, Elsevier, vol. 197(C), pages 594-605.
    10. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    11. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    12. 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).
    13. Muhammad Abubakr Naeem & Saqib Farid & Safwan Mohd Nor & Syed Jawad Hussain Shahzad, 2021. "Spillover and Drivers of Uncertainty among Oil and Commodity Markets," Mathematics, MDPI, vol. 9(4), pages 1-26, February.
    14. Ben Amar, Amine & Goutte, Stéphane & Isleimeyyeh, Mohammad, 2022. "Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 386-400.
    15. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.
    16. Dudda, Tom L. & Klein, Tony & Nguyen, Duc Khuong & Walther, Thomas, 2022. "Common Drivers of Commodity Futures?," QBS Working Paper Series 2022/05, Queen's University Belfast, Queen's Business School.
    17. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    18. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2021. "Systemically important banks in Asian emerging markets: Evidence from four systemic risk measures," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    19. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    20. 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).

    More about this item

    Keywords

    Bioenergy; Fossil energy; Agricultural sector; Intersectoral systemic risk spillover; COVID-19;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

    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:ecmode:v:105:y:2021:i:c:s0264999321002406. 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/inca/30411 .

    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.