IDEAS home Printed from https://ideas.repec.org/p/zbw/iamodp/196.html
   My bibliography  Save this paper

Preisvolatilität auf Agrarmärkten

Author

Listed:
  • Brümmer, Bernhard

Abstract

[Einleitung und Lernziele] Die Volatilität der Preise auf Agrarmärkten hat über lange Jahre kaum Aufmerksamkeit in der europäischen Agrarpolitik erfahren. Erst seit etwa zwei Jahrzehnten erhält dieses Thema auch in der EU wieder Aufmerksamkeit. Auf der internationalen Ebene hingegen war die Auseinandersetzung mit Preisvolatilität schon lange ein bedeutsames Thema, vor allem aus entwicklungspolitischer Perspektive. Bereits in den 1970er Jahren kam es zu erheblichen Preisschwankungen auf den meisten Rohstoffmärkten, die zum Teil in Verbindung mit der ersten Ölpreiskrise des Herbstes 1973 standen, zum anderen Teil aber auch auf den jeweiligen Marktbedingungen basierten. Ein bedeutender Faktor für die erneute Auseinandersetzung mit Agrarpreisvolatilität war sicherlich die sog. 'Agrarpreiskrise' der Jahre 2007 und 2008, als die Preise für die wichtigsten Getreidearten (Weizen, Mais und Reis) zunächst schlagartig anstiegen, um dann innerhalb relativ kurzer Zeit wieder drastisch nachzulassen. Im Nachgang dieser Preisentwicklung wurde die Volatilität der Nahrungsmittelpreise dann gar auf Ebene der G20 zum Thema, was in 2011 sogar zu einem Aktionsplan zum Umgang mit Agrarpreisvolatilität führte. Die Tatsache, dass die Preisspitze in 2007/08 zum Wiederaufflackern des Interesses an Preisvolatilität in Politik und Wissenschaft führte, deutet bereits auf eine häufig zu beobachtende Verquickung von Preisniveau und Preisvolatilität hin. Auch manche der Maßnahmen, die vordergründig zur Bekämpfung der Preisvolatilität ins Feld geführt werden, zielen tatsächlich eher auf eine Beeinflussung des Preisniveaus ab, wenn beispielsweise im Umfeld niedriger Preise eine Marktstützung gefordert wird. Für Entscheidungsträger in den landwirtschaftlichen Wertschöpfungsketten, von den Landwirten über die Akteure in den vor- und nachgelagerten Sektoren bis hin zum Verbraucher, und für die Träger der Agrarpolitik ist eine empirische Kenntnis der Volatilitätsprozesse wichtige Voraussetzung für angemessene Reaktionen auf Agrarpreisvolatilität. [...]

Suggested Citation

  • Brümmer, Bernhard, 2021. "Preisvolatilität auf Agrarmärkten," IAMO Discussion Papers 196, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
  • Handle: RePEc:zbw:iamodp:196
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/229198/1/1745933417.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Teresa Serra & David Zilberman & José Gil, 2011. "Price volatility in ethanol markets," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 38(2), pages 259-280, June.
    2. Berger, Jurij & Dalheimer, Bernhard & Brümmer, Bernhard, 2021. "Effects of variable EU import levies on corn price volatility," Food Policy, Elsevier, vol. 102(C).
    3. Oliver E. Williamson, 2000. "The New Institutional Economics: Taking Stock, Looking Ahead," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 595-613, September.
    4. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    5. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, October.
    6. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    7. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. 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.
    10. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    11. Koester, Ulrich, 1986. "Regional cooperation to improve food security in southern and eastern African countries:," Research reports 53, International Food Policy Research Institute (IFPRI).
    12. Stefan Busse & Bernhard Brümmer & Rico Ihle, 2012. "Price formation in the German biodiesel supply chain: a Markov-switching vector error-correction modeling approach," Agricultural Economics, International Association of Agricultural Economists, vol. 43(5), pages 545-560, September.
    13. Frederick V. Waugh, 1944. "Does the Consumer Benefit from Price Instability?," The Quarterly Journal of Economics, Oxford University Press, vol. 58(4), pages 602-614.
    14. Sandmo, Agnar, 1971. "On the Theory of the Competitive Firm under Price Uncertainty," American Economic Review, American Economic Association, vol. 61(1), pages 65-73, March.
    15. Bernhard Brümmer & Olaf Korn & Kristina Schlüßler & Tinoush Jamali Jaghdani, 2016. "Volatility in Oilseeds and Vegetable Oils Markets: Drivers and Spillovers," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(3), pages 685-705, September.
    16. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    17. Paul A. Samuelson, 1972. "The Consumer Does Benefit from Feasible Price Stability," The Quarterly Journal of Economics, Oxford University Press, vol. 86(3), pages 476-493.
    18. Brian D. Wright, 2011. "The Economics of Grain Price Volatility," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 32-58.
    19. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    20. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521839198, October.
    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. repec:zbw:iamodp:310089 is not listed on IDEAS
    2. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    3. Wu, Guojun & Xiao, Zhijie, 2002. "A generalized partially linear model of asymmetric volatility," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 287-319, August.
    4. Yu-Hua Zeng & Shou-Lei Wang & Yu-Fei Yang, 2014. "Calibration of the Volatility in Option Pricing Using the Total Variation Regularization," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, March.
    5. Carl H. Korkpoe & Peterson Owusu Junior, 2018. "Behaviour of Johannesburg Stock Exchange All Share Index Returns - An Asymmetric GARCH and News Impact Effects Approach," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 68(1), pages 26-42, January-M.
    6. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    7. Shively, Gerald E., 2001. "Price thresholds, price volatility, and the private costs of investment in a developing country grain market," Economic Modelling, Elsevier, vol. 18(3), pages 399-414, August.
    8. Chuong Luong & Nikolai Dokuchaev, 2018. "Forecasting of Realised Volatility with the Random Forests Algorithm," JRFM, MDPI, vol. 11(4), pages 1-15, October.
    9. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    10. B M, Lithin & chakraborty, Suman & iyer, Vishwanathan & M N, Nikhil & ledwani, Sanket, 2022. "Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India," MPRA Paper 117067, University Library of Munich, Germany, revised 05 Jan 2023.
    11. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    12. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    13. Issler, João Victor, 1999. "Estimating and forecasting the volatility of Brazilian finance series using arch models (Preliminary Version)," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 347, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    14. Geon Choe & Kyungsub Lee, 2014. "Conditional correlation in asset return and GARCH intensity model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(3), pages 197-224, July.
    15. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    16. S. M. Abdullah & Salina Siddiqua & Muhammad Shahadat Hossain Siddiquee & Nazmul Hossain, 2017. "Modeling and forecasting exchange rate volatility in Bangladesh using GARCH models: a comparison based on normal and Student’s t-error distribution," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-19, December.
    17. Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye, 2023. "Forecasting stock volatility with a large set of predictors: A new forecast combination method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1622-1647, November.
    18. Bing-Huei Lin & Mao-Wei Hung & Jr-Yan Wang & Ping-Da Wu, 2013. "A lattice model for option pricing under GARCH-jump processes," Review of Derivatives Research, Springer, vol. 16(3), pages 295-329, October.
    19. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    20. Li, Ming-Yuan Leon, 2008. "Clarifying the dynamics of the relationship between option and stock markets using the threshold vector error correction model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 511-520.
    21. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:iamodp:196. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iamoode.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.