IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i2p93-d484771.html
   My bibliography  Save this article

Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Author

Listed:
  • Pavel Kotyza

    (Department of Economics, Faculty of Economics and Management, Czech University of Life SciencesPrague, Kamycka 129, 16500 Prague, Czech Republic)

  • Katarzyna Czech

    (Department of Econometrics and Statistics, Institute of Economics and Finance, Warsaw University of Life Sciences-SGGW, Nowoursynowska 166, 02-787 Warsaw, Poland)

  • Michał Wielechowski

    (Department of Economics and Economic Policy, Institute of Economics and Finance, Warsaw University of Life Sciences-SGGW, Nowoursynowska 166, 02-787 Warsaw, Poland)

  • Luboš Smutka

    (Department of Economics, Faculty of Economics and Management, Czech University of Life SciencesPrague, Kamycka 129, 16500 Prague, Czech Republic)

  • Petr Procházka

    (Department of Economics, Faculty of Economics and Management, Czech University of Life SciencesPrague, Kamycka 129, 16500 Prague, Czech Republic)

Abstract

Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial market uncertainty in a crisis time. In more detail, using sequential Bai–Perron tests for structural breaks, we check whether the global financial crisis and the COVID-19 pandemic have induced structural breaks in that relationship. Sugar prices are represented by the S&P GSCI Sugar Index, while the S&P 500 option-implied volatility index (VIX) is used to show stock market uncertainty. To investigate the changes in the relationship between sugar prices and stock market uncertainty, a regression model with a sequential Bai–Perron test for structural breaks is applied for the daily data from 2000–2020. We reveal the existence of two structural breaks in the analysed relationship. The first breakpoint was linked to the global financial crisis outbreak, and the second occurred in December 2011. Surprisingly, the COVID-19 pandemic has not induced the statistically significant structural change. Based on the regression model with Bai–Perron structural changes, we show that from 2000 until the beginning of the global financial crisis, the relationship between the sugar prices and the financial market uncertainty was insignificant. The global financial crisis led to a structural change in the relationship. Since August 2008, we observe a significant and negative relationship between the S&P GSCI Sugar Index and the S&P 500 option-implied volatility index (VIX). Sensitivity analysis conducted for the different financial market uncertainty measures, i.e., the S&P 500 Realized Volatility Index confirms our findings.

Suggested Citation

  • Pavel Kotyza & Katarzyna Czech & Michał Wielechowski & Luboš Smutka & Petr Procházka, 2021. "Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?," Agriculture, MDPI, vol. 11(2), pages 1-16, January.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:2:p:93-:d:484771
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/2/93/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/11/2/93/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Scott H. Irwin, 2013. "Commodity index investment and food prices: does the “Masters Hypothesis” explain recent price spikes?," Agricultural Economics, International Association of Agricultural Economists, vol. 44(s1), pages 29-41, November.
    2. Katarzyna Czech & Michał Wielechowski & Pavel Kotyza & Irena Benešová & Adriana Laputková, 2020. "Shaking Stability: COVID-19 Impact on the Visegrad Group Countries’ Financial Markets," Sustainability, MDPI, vol. 12(15), pages 1-19, August.
    3. Bakas, Dimitrios & Triantafyllou, Athanasios, 2018. "The impact of uncertainty shocks on the volatility of commodity prices," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 96-111.
    4. Maizels, Alfred, 1994. "The continuing commodity crisis of developing countries," World Development, Elsevier, vol. 22(11), pages 1685-1695, November.
    5. Dominique van der Mensbrugghe & John C. Beghin & Don Mitchell, 2003. "Modeling Tariff Rate Quotas in a Global Context: The Case of Sugar Markets in OECD Countries," Food and Agricultural Policy Research Institute (FAPRI) Publications (archive only) 03-wp343, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    6. Amani Elobeid & John Beghin, 2006. "Multilateral Trade and Agricultural Policy Reforms in Sugar Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 57(1), pages 23-48, March.
    7. Baffes, John & Haniotis, Tassos, 2010. "Placing the 2006/08 commodity price boom into perspective," Policy Research Working Paper Series 5371, The World Bank.
    8. Delatte, Anne-Laure & Lopez, Claude, 2013. "Commodity and equity markets: Some stylized facts from a copula approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5346-5356.
    9. Vivian, Andrew & Wohar, Mark E., 2012. "Commodity volatility breaks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(2), pages 395-422.
    10. Altig, Dave & Baker, Scott & Barrero, Jose Maria & Bloom, Nicholas & Bunn, Philip & Chen, Scarlet & Davis, Steven J. & Leather, Julia & Meyer, Brent & Mihaylov, Emil & Mizen, Paul & Parker, Nicholas &, 2020. "Economic uncertainty before and during the COVID-19 pandemic," Journal of Public Economics, Elsevier, vol. 191(C).
    11. Corbae,Dean & Durlauf,Steven N. & Hansen,Bruce E. (ed.), 2006. "Econometric Theory and Practice," Cambridge Books, Cambridge University Press, number 9780521807234, November.
    12. Pilar Poncela & Eva Senra & Lya Paola Sierra, 2014. "Common dynamics of nonenergy commodity prices and their relation to uncertainty," Applied Economics, Taylor & Francis Journals, vol. 46(30), pages 3724-3735, October.
    13. Bakas, Dimitrios & Triantafyllou, Athanasios, 2020. "Commodity price volatility and the economic uncertainty of pandemics," Economics Letters, Elsevier, vol. 193(C).
    14. Teguh Dartanto & Usman, 2011. "Volatility of World Soybean Prices, Import Tariffs and Poverty in Indonesia," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 5(2), pages 139-181, May.
    15. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    16. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    17. Huchet, Nicolas & Fam, Papa Gueye, 2016. "The role of speculation in international futures markets on commodity prices," Research in International Business and Finance, Elsevier, vol. 37(C), pages 49-65.
    18. Jushan Bai & Pierre Perron, 2003. "Critical values for multiple structural change tests," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 72-78, June.
    19. Zhang, Dayong & Broadstock, David C., 2020. "Global financial crisis and rising connectedness in the international commodity markets," International Review of Financial Analysis, Elsevier, vol. 68(C).
    20. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    21. Sadefo Kamdem, Jules & Bandolo Essomba, Rose & Njong Berinyuy, James, 2020. "Deep learning models for forecasting and analyzing the implications of COVID-19 spread on some commodities markets volatilities," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    22. Caggiano, Giovanni & Castelnuovo, Efrem & Kima, Richard, 2020. "The global effects of Covid-19-induced uncertainty," Economics Letters, Elsevier, vol. 194(C).
    23. Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 929-939, February.
    24. Irwin, Scott H. & Sanders, Dwight R., 2012. "Testing the Masters Hypothesis in commodity futures markets," Energy Economics, Elsevier, vol. 34(1), pages 256-269.
    25. Chia-Lin Chang & Michael McAleer, 2017. "A Simple Test for Causality in Volatility," Econometrics, MDPI, vol. 5(1), pages 1-5, March.
    26. Nicolas Huchet & Papa Gueye Fam, 2016. "The role of speculation in international futures markets on commodity prices," Post-Print hal-03591560, HAL.
    27. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost & Marco C. Sammon & Tasaneeya Viratyosin, 2020. "The Unprecedented Stock Market Impact of COVID-19," NBER Working Papers 26945, National Bureau of Economic Research, Inc.
    28. Jennifer Clapp, 2009. "Food Price Volatility and Vulnerability in the Global South: considering the global economic context," Third World Quarterly, Taylor & Francis Journals, vol. 30(6), pages 1183-1196.
    29. Kalkuhl, Matthias & von Braun, Joachim & Torero, Maximo, 2016. "Food Price Volatility and Its Implications for Food Security and Policy," MPRA Paper 72164, University Library of Munich, Germany.
    30. Vincenzo Candila & Salvatore Farace, 2018. "On the Volatility Spillover between Agricultural Commodities and Latin American Stock Markets," Risks, MDPI, vol. 6(4), pages 1-16, October.
    31. Christian Elleby & Ignacio Pérez Domínguez & Marcel Adenauer & Giampiero Genovese, 2020. "Impacts of the COVID-19 Pandemic on the Global Agricultural Markets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 1067-1079, August.
    32. Zhang, Yue-Jun & Chevallier, Julien & Guesmi, Khaled, 2017. "“De-financialization” of commodities? Evidence from stock, crude oil and natural gas markets," Energy Economics, Elsevier, vol. 68(C), pages 228-239.
    33. Dufour, Jean-Marie, 1982. "Generalized Chow Tests for Structural Change: A Coordinate-Free Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(3), pages 565-575, October.
    34. Suleyman Basak & Anna Pavlova, 2016. "A Model of Financialization of Commodities," Journal of Finance, American Finance Association, vol. 71(4), pages 1511-1556, August.
    35. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    36. Amine Ben Amar & Fateh Belaid & Adel Ben Youssef & Benjamin Chiao & Khaled Guesmi, 2020. "The Unprecedented Equity and Commodity Markets Reaction to COVID-19," Post-Print hal-03131564, HAL.
    37. Goodell, John W., 2020. "COVID-19 and finance: Agendas for future research," Finance Research Letters, Elsevier, vol. 35(C).
    38. Yao, Yi-Ching, 1988. "Estimating the number of change-points via Schwarz' criterion," Statistics & Probability Letters, Elsevier, vol. 6(3), pages 181-189, February.
    39. Matthias Kalkuhl & Joachim von Braun & Maximo Torero (ed.), 2016. "Food Price Volatility and Its Implications for Food Security and Policy," Springer Books, Springer, number 978-3-319-28201-5, June.
    40. repec:aei:rpaper:1008560098 is not listed on IDEAS
    41. Lenka Rumánková & Luboš Smutka, 2013. "Global sugar market - the analysis of factors influencing supply and demand," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(2), pages 463-471.
    42. repec:zbw:bofrdp:2020_011 is not listed on IDEAS
    43. Wang, Jian & Shao, Wei & Kim, Junseok, 2020. "Analysis of the impact of COVID-19 on the correlations between crude oil and agricultural futures," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    44. Gozgor, Giray & Lau, Chi Keung Marco & Bilgin, Mehmet Huseyin, 2016. "Commodity markets volatility transmission: Roles of risk perceptions and uncertainty in financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 35-45.
    45. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    46. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    47. Karyotis, Catherine & Alijani, Sharam, 2016. "Soft commodities and the global financial crisis: Implications for the economy, resources and institutions," Research in International Business and Finance, Elsevier, vol. 37(C), pages 350-359.
    48. Prokopczuk, Marcel & Stancu, Andrei & Symeonidis, Lazaros, 2019. "The economic drivers of commodity market volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    49. Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
    50. Machiko Nissanke, 2012. "Commodity Market Linkages in the Global Financial Crisis: Excess Volatility and Development Impacts," Journal of Development Studies, Taylor & Francis Journals, vol. 48(6), pages 732-750, June.
    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. Rubbaniy, Ghulame & Khalid, Ali Awais & Syriopoulos, Konstantinos & Samitas, Aristeidis, 2022. "Safe-haven properties of soft commodities during times of Covid-19," Journal of Commodity Markets, Elsevier, vol. 27(C).
    2. Qian, Yu & Xu, Zeshui & Qin, Yong & Gou, Xunjie & Skare, Marinko, 2023. "Measuring the varying relationships between sustainable development and oil booms in different contexts: An empirical study," Resources Policy, Elsevier, vol. 85(PB).
    3. Iuga, Iulia Cristina & Mudakkar, Syeda Rabab & Dragolea, Larisa Loredana, 2024. "Agricultural commodities market reaction to COVID-19," Research in International Business and Finance, Elsevier, vol. 69(C).
    4. Niftiyev, Ibrahim & Huseynova, Rena, 2021. "How has the Self-Perceived Health Shaped the COVID-19 Causalities in the Visegrad Countries?," EconStor Conference Papers 234511, ZBW - Leibniz Information Centre for Economics.

    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. Iuga, Iulia Cristina & Mudakkar, Syeda Rabab & Dragolea, Larisa Loredana, 2024. "Agricultural commodities market reaction to COVID-19," Research in International Business and Finance, Elsevier, vol. 69(C).
    2. Mohitosh Kejriwal, 2020. "A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 669-685, June.
    3. Czech, Katarzyna, 2016. "Structural Changes in Wheat Market," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 16(31), pages 1-7, December.
    4. Telli, Şahin & Chen, Hongzhuan, 2020. "Structural breaks and trend awareness-based interaction in crypto markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    5. Sharma, Aarzoo, 2022. "A comparative analysis of the financialization of commodities during COVID-19 and the global financial crisis using a quantile regression approach," Resources Policy, Elsevier, vol. 78(C).
    6. Michail, Nektarios A. & Melas, Konstantinos D. & Cleanthous, Lena, 2022. "The relationship between shipping freight rates and inflation in the Euro Area," International Economics, Elsevier, vol. 172(C), pages 40-49.
    7. Zhou, Xiaoran & Enilov, Martin & Parhi, Mamata, 2024. "Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets," Energy Economics, Elsevier, vol. 132(C).
    8. Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," SSE/EFI Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
    9. Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
    10. Jouini, Jamel & Boutahar, Mohamed, 2005. "Evidence on structural changes in U.S. time series," Economic Modelling, Elsevier, vol. 22(3), pages 391-422, May.
    11. Karakotsios, Achillefs & Katrakilidis, Constantinos & Kroupis, Nikolaos, 2021. "The dynamic linkages between food prices and oil prices. Does asymmetry matter?," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    12. Devi, P. Indira & Shanmugam, K.R. & Jayasree, M.G., 2012. "Compensating Wages for Occupational Risks of Farm Workers in India," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 67(2), pages 1-12.
    13. Altansukh, Gantungalag & Becker, Ralf & Bratsiotis, George J. & Osborn, Denise R., 2017. "What is the Globalisation of Inflation?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 74, pages 1-27.
    14. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    15. Hervé Le Bihan, 2004. "Tests de ruptures : une application au PIB tendanciel français," Économie et Prévision, Programme National Persée, vol. 163(2), pages 133-154.
    16. van Huellen, Sophie, 2019. "Price discovery in commodity futures and cash markets with heterogeneous agents," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 1-13.
    17. Kurozumi, Eiji & Tuvaandorj, Purevdorj, 2011. "Model selection criteria in multivariate models with multiple structural changes," Journal of Econometrics, Elsevier, vol. 164(2), pages 218-238, October.
    18. Hui Hong & Zhicun Bian & Chien-Chiang Lee, 2021. "COVID-19 and instability of stock market performance: evidence from the U.S," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    19. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    20. Bajo-Rubio, Oscar & Diaz-Roldan, Carmen & Esteve, Vicente, 2007. "Change of regime and Phillips curve stability: The case of Spain, 1964-2002," Journal of Policy Modeling, Elsevier, vol. 29(3), pages 453-462.

    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:gam:jagris:v:11:y:2021:i:2:p:93-:d:484771. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.