IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i22p15268-d975998.html
   My bibliography  Save this article

Influences of Power Structure Evolution on Coffee Commodity Markets: Insights from Price Discovery and Volatility Spillovers

Author

Listed:
  • Wei Zhang

    (Department of Economics and Trade, College of Economics and Management, China Agricultural University, Beijing 100083, China)

  • Sayed Saghaian

    (Department of Agricultural Economics, University of Kentucky, Lexington, KY 40506, USA)

  • Michael Reed

    (Department of Agricultural Economics, University of Kentucky, Lexington, KY 40506, USA)

Abstract

This study examines the influences of the power structure evolution along the global coffee value chain on coffee spot-futures commodity markets. Specifically, this study aims to analyze the mechanisms and extent to which the coffee spot-futures commodity markets are affected by shifts in the power structure in each phase following the collapse of the ICA from the perspective of price discovery and volatility spillovers by employing the PT–IS and bivariate EGARCH models. This research covers two actively traded coffee types, Arabica and Robusta, and utilizes daily time-series price data over 1990:01–2020:04 for Arabica and over 2008:01–2020:04 for Robusta. The empirical results indicate that coffee spot markets play a dominant role in price discovery for both Arabica and Robusta over all periods, and volatility spillovers occur from the coffee spot market to the futures markets. This study demonstrates to coffee market players that power structure evolutions across coffee’s global value chain have not significantly changed the underlying socio-spatial distribution of the coffee value chain over the post-ICA period. The results further imply that a buyer-driven governance is emerging in the coffee industry and large coffee roasters are beginning to dominate the global coffee value chain. Moreover, large coffee roasters are incentivized to diversify their marketing strategies by considering more market factors as part of their market differentiation strategies. Government interventions are necessary to establish price risk-management mechanisms to protect small-scale coffee growers.

Suggested Citation

  • Wei Zhang & Sayed Saghaian & Michael Reed, 2022. "Influences of Power Structure Evolution on Coffee Commodity Markets: Insights from Price Discovery and Volatility Spillovers," Sustainability, MDPI, vol. 14(22), pages 1-27, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15268-:d:975998
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/22/15268/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/22/15268/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    3. Bohl, Martin T. & Siklos, Pierre L. & Stefan, Martin & Wellenreuther, Claudia, 2020. "Price discovery in agricultural commodity markets: Do speculators contribute?," Journal of Commodity Markets, Elsevier, vol. 18(C).
    4. Mohanty, Sunil K. & Mishra, Sibanjan, 2020. "Regulatory reform and market efficiency: The case of Indian agricultural commodity futures markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    5. Mehta, A. & Chavas, Jean-Paul, 2008. "Responding to the Coffee Crisis: What We Can Learn from Price Dynamics," Working Papers 201444, University of Wisconsin-Madison, Department of Agricultural and Applied Economics, Food System Research Group.
    6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    7. Stefano Ponte & Timothy J. Sturgeon & Mark P. Dallas, 2019. "Governance and power in global value chains," Chapters, in: Stefano Ponte & Gary Gereffi & Gale Raj-Reichert (ed.), Handbook on Global Value Chains, chapter 6, pages 120-137, Edward Elgar Publishing.
    8. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    9. Buguk, Cumhur & Hudson, Darren & Hanson, Terrill R., 2003. "Price Volatility Spillover in Agricultural Markets: An Examination of U.S. Catfish Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(1), pages 1-14, April.
    10. Gonzalo, Jesus & Granger, Clive W J, 1995. "Estimation of Common Long-Memory Components in Cointegrated Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 27-35, January.
    11. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    12. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    13. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    14. Takeshi Inoue & Shigeyuki Hamori, 2014. "Market efficiency of commodity futures in India," Applied Economics Letters, Taylor & Francis Journals, vol. 21(8), pages 522-527, May.
    15. Mehta, Aashish & Chavas, Jean-Paul, 2008. "Responding to the coffee crisis: What can we learn from price dynamics?," Journal of Development Economics, Elsevier, vol. 85(1-2), pages 282-311, February.
    16. Sepideh Dolatabadi & Morten Ørregaard Nielsen & Ke Xu, 2015. "A Fractionally Cointegrated VAR Analysis of Price Discovery in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 339-356, April.
    17. Baillie, Richard T. & Geoffrey Booth, G. & Tse, Yiuman & Zabotina, Tatyana, 2002. "Price discovery and common factor models," Journal of Financial Markets, Elsevier, vol. 5(3), pages 309-321, July.
    18. Bhaumik, S. & Karanasos, M. & Kartsaklas, A., 2016. "The informative role of trading volume in an expanding spot and futures market," Journal of Multinational Financial Management, Elsevier, vol. 35(C), pages 24-40.
    19. Oliver Entrop & Bart Frijns & Marco Seruset, 2020. "The determinants of price discovery on bitcoin markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 816-837, May.
    20. Nicholas Apergis & Anthony Rezitis, 2003. "Agricultural price volatility spillover effects: the case of Greece," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 30(3), pages 389-406, September.
    21. Mark P. Dallas & Stefano Ponte & Timothy J. Sturgeon, 2019. "Power in global value chains," Review of International Political Economy, Taylor & Francis Journals, vol. 26(4), pages 666-694, July.
    22. Juan Cabrera & Tao Wang & Jian Yang, 2009. "Do futures lead price discovery in electronic foreign exchange markets?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(2), pages 137-156, February.
    23. Janina Grabs & Stefano Ponte, 2019. "The evolution of power in the global coffee value chain and production network," Journal of Economic Geography, Oxford University Press, vol. 19(4), pages 803-828.
    24. Rezitis, Anthony N., 2003. "Volatility Spillover Effects in Greek Consumer Meat Prices," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 4(1), pages 1-8, January.
    25. Go, You-How & Lau, Wee-Yeap, 2017. "Investor demand, market efficiency and spot-futures relation: Further evidence from crude palm oil," Resources Policy, Elsevier, vol. 53(C), pages 135-146.
    26. Shihabudheen, M.T. & Padhi, Puja, 2010. "Price Discovery and Volatility Spillover Effect in Indian Commodity Market," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 65(1), pages 1-17.
    27. Pradhan, Rudra P. & Hall, John H. & du Toit, Elda, 2021. "The lead–lag relationship between spot and futures prices: Empirical evidence from the Indian commodity market," Resources Policy, Elsevier, vol. 70(C).
    28. Ponte, Stefano, 2002. "The 'Latte Revolution'? Regulation, Markets and Consumption in the Global Coffee Chain," World Development, Elsevier, vol. 30(7), pages 1099-1122, July.
    29. Feleke, Shiferaw T. & Walters, Lurleen M., 2005. "Global Coffee Import Demand in a New Era: Implications for Developing Countries," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(2), pages 1-15.
    30. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Samih Antoine Azar & Angelic Salha, 2017. "The Bias in the Long Run Relation between the Prices of BRENT and West Texas Intermediate Crude Oils," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 44-54.
    2. Rezitis Anthony N & Stavropoulos Konstantinos S, 2011. "Price Transmission and Volatility in the Greek Broiler Sector: A Threshold Cointegration Analysis," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 9(1), pages 1-37, July.
    3. Fassas, Athanasios P. & Papadamou, Stephanos & Koulis, Alexandros, 2020. "Price discovery in bitcoin futures," Research in International Business and Finance, Elsevier, vol. 52(C).
    4. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
    5. Martin T. Bohl & Alexander Pütz & Pierre L. Siklos & Christoph Sulewski, 2018. "Information Transmission under Increasing Political Tension – Evidence for the Berlin Produce Exchange 1887-1896," CQE Working Papers 7618, Center for Quantitative Economics (CQE), University of Muenster.
    6. Remes, Piia, 2013. "Putting a Price on Carbon – Econometric Essays on the European Union Emissions Trading Scheme and its Impacts," Research Reports 62, VATT Institute for Economic Research.
    7. Biru Paksha Paul, 2013. "Inflation--growth nexus: some bivariate EGARCH evidence for Bangladesh," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 6(1), pages 66-76, March.
    8. Judge, Amrit & Reancharoen, Tipprapa, 2014. "An empirical examination of the lead–lag relationship between spot and futures markets: Evidence from Thailand," Pacific-Basin Finance Journal, Elsevier, vol. 29(C), pages 335-358.
    9. Lan-Fen Chu & Michael McAleer & Chi-Chung Chen, 2012. "How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?," Journal of Reviews on Global Economics, Lifescience Global, vol. 1, pages 1-12.
    10. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    11. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, January.
    12. Chu, L. & McAleer, M.J. & Chen, C-C., 2009. "How Volatile is ENSO?," Econometric Institute Research Papers EI 2009-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Geeta Duppati & Yang (Greg) Hou & Frank Scrimgeour, 2017. "The dynamics of price discovery for cross-listed stocks evidence from US and Chinese markets," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1389675-138, January.
    14. Gustavo Freire & Marcelo Resende, 2020. "Conditional growth volatility and sectoral comovement in U.S. industrial production, 1828–1915," Empirical Economics, Springer, vol. 59(6), pages 3063-3084, December.
    15. Chang, C-L. & Huang, B-W. & Chen, M-G., 2010. "Modelling the Asymmetric Volatility in Hog Prices in Taiwan," Econometric Institute Research Papers EI 2010-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, September.
    17. Ran Xiao, 2019. "Essays on Price Discovery and Volatility Dynamics in Emerging Market Currencies," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2019, January-A.
    18. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    19. Chang, Chia-Lin & Huang, Biing-Wen & Chen, Meng-Gu & McAleer, Michael, 2011. "Modelling the asymmetric volatility in hog prices in Taiwan: The impact of joining the WTO," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1491-1506.
    20. Xu, Xiaojie, 2014. "Price Discovery in U.S. Corn Cash and Futures Markets: The Role of Cash Market Selection," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169809, Agricultural and Applied Economics Association.

    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:jsusta:v:14:y:2022:i:22:p:15268-:d:975998. 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.