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On the joint volatility dynamics in international dairy commodity markets

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  • Rezitis, Anthony N.
  • Kastner, Gregor

Abstract

The present study investigates the price (co)volatility of four dairy commodities—skim milk powder, whole milk powder, butter, and cheddar cheese—in three major dairy markets. It uses a multivariate factor stochastic volatility model for estimating the time-varying covariance and correlation matrices by imposing a low-dimensional latent dynamic factor structure. The empirical results support four factors representing the European Union and Oceania dairy sectors as well as the milk powder markets. Factor volatilities and marginal posterior volatilities of each dairy commodity increase after the 2006/07 global (food) crisis, which also coincides with the free trade agreements enacted from 2007 onward and EU and US liberalization policy changes. The model-implied correlation matrices show increasing dependence during the second half of 2006, throughout the first half of 2007, as well as during 2008 and 2014, which can be attributed to various regional agricultural dairy policies. Furthermore, in-sample value at risk measures (VaRs and CoVaRs) are provided for each dairy commodity under consideration.

Suggested Citation

  • Rezitis, Anthony N. & Kastner, Gregor, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 60(2), January.
  • Handle: RePEc:ags:aareaj:342965
    DOI: 10.22004/ag.econ.342965
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    1. Bohl, Martin T. & Sulewski, Christoph, 2019. "The impact of long-short speculators on the volatility of agricultural commodity futures prices," Journal of Commodity Markets, Elsevier, vol. 16(C).
    2. Panos Fousekis & Christos Emmanouilides & Vasilis Grigoriadis, 2017. "Price linkages in the international skim milk powder market: empirical evidence from nonparametric and time-varying copulas," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(1), pages 135-153, January.
    3. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    4. Manuel A. Hernandez & Raul Ibarra & Danilo R. Trupkin, 2014. "How far do shocks move across borders? Examining volatility transmission in major agricultural futures markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(2), pages 301-325.
    5. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Gardebroek, Cornelis & Hernandez, Manuel A., 2013. "Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets," Energy Economics, Elsevier, vol. 40(C), pages 119-129.
    8. Fousekis, Panos & Emmanouilides, Christos & Grigoriadis, Vasilis, 2017. "Price linkages in the international skim milk powder market: empirical evidence from nonparametric and time-varying copulas," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 61(1), January.
    9. David S. Jacks & Kevin H. O'Rourke & Jeffrey G. Williamson, 2011. "Commodity Price Volatility and World Market Integration since 1700," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 800-813, August.
    10. Jian Yang & Michael Haigh & David Leatham, 2001. "Agricultural liberalization policy and commodity price volatility: a GARCH application," Applied Economics Letters, Taylor & Francis Journals, vol. 8(9), pages 593-598.
    11. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    12. Rezitis, Anthony N. & Rokopanos, Andreas, 2019. "Impact of trade liberalisation on dairy market price co-movements between the EU, Oceania, and the United States," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(3), July.
    13. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2014. "Oil price shocks and agricultural commodity prices," Energy Economics, Elsevier, vol. 44(C), pages 22-35.
    14. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    15. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    16. 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.
    17. Andrew Harvey & Esther Ruiz & Neil Shephard, 1994. "Multivariate Stochastic Variance Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(2), pages 247-264.
    18. Panos Fousekis & Vasilis Grigoriadis, 2016. "Price co-movement in the principal skim milk powder producing regions: a wavelet analysis," Economics Bulletin, AccessEcon, vol. 36(1), pages 477-492.
    19. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Yufeng Han, 2006. "Asset Allocation with a High Dimensional Latent Factor Stochastic Volatility Model," The Review of Financial Studies, Society for Financial Studies, vol. 19(1), pages 237-271.
    21. Pierre Boulanger & Hasan Dudu & Emanuele Ferrari & Mihaly Himics & Robert M'barek, 2016. "Cumulative economic impact of future trade agreements on EU agriculture," JRC Research Reports JRC103602, Joint Research Centre.
    22. Dennis Bergmann & Declan O’Connor & Andreas Thümmel, 2016. "An analysis of price and volatility transmission in butter, palm oil and crude oil markets," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 4(1), pages 1-23, December.
    23. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    24. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    25. Aguilar, Omar & West, Mike, 2000. "Bayesian Dynamic Factor Models and Portfolio Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 338-357, July.
    26. Phil Briggs & Carly Harker & Tim Ng & Aidan Yao, 2011. "Fluctuations in the international prices of oil, dairy products, beef and lamb between 2000 and 2008: A review of market-specific demand and supply factors," Reserve Bank of New Zealand Discussion Paper Series DP2011/02, Reserve Bank of New Zealand.
    27. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.
    28. Lu Yang & Shigeyuki Hamori, 2018. "Modeling The Dynamics Of International Agricultural Commodity Prices: A Comparison Of Garch And Stochastic Volatility Models," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 1-20, September.
    29. Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
    30. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    31. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    32. Christopher Gilbert & Wyn Morgan, 2010. "Has food price volatility risen?," Department of Economics Working Papers 1002, Department of Economics, University of Trento, Italia.
    33. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    34. Newton, John, 2016. "Price Transmission in Global Dairy Markets," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(B), pages 1-15, August.
    35. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-417, October.
    36. Na Li & Alan Ker & Abdoul G. Sam & Satheesh Aradhyula, 2017. "Modeling regime-dependent agricultural commodity price volatilities," Agricultural Economics, International Association of Agricultural Economists, vol. 48(6), pages 683-691, November.
    37. 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.
    38. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 2017.
    39. Panos Fousekis & Emmanouil Trachanas, 2016. "Price transmission in the international skim milk powder markets," Applied Economics, Taylor & Francis Journals, vol. 48(54), pages 5233-5245, November.
    40. Zhou, Xiaocong & Nakajima, Jouchi & West, Mike, 2014. "Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 963-980.
    41. O'Connor, Declan & Keane, Michael & Barnes, Edel, 2009. "Measuring Volatility in Dairy Commodity Prices," 113th Seminar, September 3-6, 2009, Chania, Crete, Greece 58106, European Association of Agricultural Economists.
    42. 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.
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