IDEAS home Printed from https://ideas.repec.org/p/ags/aaea15/205125.html
   My bibliography  Save this paper

Price Discovery and Risk Management in the U.S. Distiller’s Grain Markets

Author

Listed:
  • Etienne, Xiaoli L.
  • Hoffman, Linwood A.

Abstract

In this paper, we evaluate the spatial nature of the price discovery process in regional distiller’s grain markets in the US and the price relationships among distiller’s grains, corn, and soybean meals since the beginning of the biofuel boom. We use multivariate and pairwise cointegration analyses to examine spatial integrations among regions and to investigate whether a stable long-term price relationship exists in the market. Error correction models are estimated to determine the speed of price adjustment to the long-run spatial equilibrium in the distiller’s grain market. Furthermore, Directed Acyclic Graphs are used to determine the contemporaneous causal patterns of prices observed at different regions. We also conduct cointegration analyses to investigate the long-run relationships between corn, soybean meal, and distiller’s grain prices. Overall, results suggest that with a few exceptions, the distiller’s grain market in the US market is well-integrated for the ten locations considered. It also appears that while there appears to be no long-run relationship between corn, soybean meal, and distiller’s grain prices prior to 2007, a much stronger link between them has been established since then, in parallel with the expansion of ethanol production and the maturity of DDGS markets.

Suggested Citation

  • Etienne, Xiaoli L. & Hoffman, Linwood A., 2015. "Price Discovery and Risk Management in the U.S. Distiller’s Grain Markets," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205125, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea15:205125
    DOI: 10.22004/ag.econ.205125
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/205125/files/Etienne_Hoffman_AAEA2015.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.205125?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
    ---><---

    References listed on IDEAS

    as
    1. Selva Demiralp & Kevin D. Hoover, 2003. "Searching for the Causal Structure of a Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 745-767, December.
    2. Michael S. Haigh & David A. Bessler, 2004. "Causality and Price Discovery: An Application of Directed Acyclic Graphs," The Journal of Business, University of Chicago Press, vol. 77(4), pages 1099-1121, October.
    3. Selva Demiralp & Kevin D. Hoover, 2003. "Searching for the Causal Structure of a Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 745-767, December.
    4. Zijun Wang & David A. Bessler, 2006. "Price and quantity endogeneity in demand analysis: evidence from directed acyclic graphs," Agricultural Economics, International Association of Agricultural Economists, vol. 34(1), pages 87-95, January.
    5. Bessler, David A. & Yang, Jian, 2003. "The structure of interdependence in international stock markets," Journal of International Money and Finance, Elsevier, vol. 22(2), pages 261-287, April.
    6. Plato, Gerald E. & Hoffman, Linwood A., 2007. "Measuring the Influence of Commodity Fund Trading on Soybean Price Discovery," 2007 Conference, April 16-17, 2007, Chicago, Illinois 37568, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Stewart Skinner & Alfons Weersink & Cornelius F. deLange, 2012. "Impact of Dried Distillers Grains with Solubles (DDGS) on Ration and Fertilizer Costs of Swine Farmers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 60(3), pages 335-356, September.
    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. Peter G. Fennell & David O'Sullivan & Antoine Godin & Stephen Kinsella, 2014. "Visualising stock flow consistent models as directed acyclic graphs," Papers 1409.4541, arXiv.org.
    2. Yang, Jian & Bessler, David A., 2008. "Contagion around the October 1987 stock market crash," European Journal of Operational Research, Elsevier, vol. 184(1), pages 291-310, January.
    3. Etienne, Xiaoli L. & Irwin, Scott H. & Garcia, Philip, 2013. "Dissecting Corn Price Movements with Directed Acyclic Graphs," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151279, Agricultural and Applied Economics Association.
    4. Xu, Xiaojie, 2014. "Causality and Price Discovery in U.S. Corn Markets: An Application of Error Correction Modeling and Directed Acyclic Graphs," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169806, Agricultural and Applied Economics Association.
    5. Alessio Moneta, 2008. "Graphical causal models and VARs: an empirical assessment of the real business cycles hypothesis," Empirical Economics, Springer, vol. 35(2), pages 275-300, September.
    6. Zijun Wang & Andrew J. Rettenmaier, 2008. "Deficits, Explicit Debt, Implicit Debt, and Interest Rates: Some Empirical Evidence," Southern Economic Journal, John Wiley & Sons, vol. 75(1), pages 208-222, July.
    7. Perez, Stephen J. & Siegler, Mark V., 2006. "Agricultural and monetary shocks before the great depression: A graph-theoretic causal investigation," Journal of Macroeconomics, Elsevier, vol. 28(4), pages 720-736, December.
    8. Alessio Moneta & Peter Spirtes, 2005. "Graph-Based Search Procedure for Vector Autoregressive Models," LEM Papers Series 2005/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Jin Zhang and David C. Broadstock, 2016. "The Causality between Energy Consumption and Economic Growth for China in a Time-varying Framework," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).
    10. Wang, Zijun, 2012. "The causal structure of bond yields," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 93-102.
    11. Michael Margolis, 2017. "Graphs as a Tool for the Close Reading of Econometrics (Settler Mortality is not a Valid Instrument for Institutions)," Economic Thought, World Economics Association, vol. 6(1), pages 56-82, March.
    12. Xiaojie Xu, 2017. "Contemporaneous causal orderings of US corn cash prices through directed acyclic graphs," Empirical Economics, Springer, vol. 52(2), pages 731-758, March.
    13. Andrew Rettenmaier & Zijun Wang, 2013. "What determines health: a causal analysis using county level data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(5), pages 821-834, October.
    14. Jin Zhang and David C. Broadstock, 2016. "The Causality between Energy Consumption and Economic Growth for China in a Time-varying Framework," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).
    15. Alessio Moneta, 2003. "Graphical Models for Structural Vector Autoregressions," LEM Papers Series 2003/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    16. Alessio Moneta & Doris Entner & Patrik O. Hoyer & Alex Coad, 2013. "Causal Inference by Independent Component Analysis: Theory and Applications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(5), pages 705-730, October.
    17. Parum Faith & Dharmasena Senarath, 2024. "Food Price Inflation in the United States as a Complex Dynamic Economic System," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 22(2), pages 113-132.
    18. Wang, Zijun & Yang, Jian & Li, Qi, 2007. "Interest rate linkages in the Eurocurrency market: Contemporaneous and out-of-sample Granger causality tests," Journal of International Money and Finance, Elsevier, vol. 26(1), pages 86-103, February.
    19. Henry L. Bryant & David A. Bessler & Michael S. Haigh, 2009. "Disproving Causal Relationships Using Observational Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 357-374, June.
    20. Aramayis Dallakyan, 2021. "Nonparanormal Structural VAR for Non-Gaussian Data," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1093-1113, April.

    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:ags:aaea15:205125. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    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.