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Volatile world market prices for dairy products - how do they affect domestic price formation: The German cheese market

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  • Weber, Sascha A.
  • Salamon, Petra
  • Hansen, Heiko

Abstract

Since the stepwise reduction of intervention prices combined with watered down conditions and suspended export refunds, respectively, the EU dairy industry faces new challenges regarding wild price fluctuations originally caused in third countries. In the past, the EU domestic market was insulated as far as possible from world markets. However, today global prices could affect prices even at the level of consumers, but more directly at the level milk producers. Volatility noticeable increased with the price peak in 2007, followed by the drop in 2008, and a new price boost in 2010. Additionally, reduced security in marketing of butter and skimmed milk powder led to higher processing share of cheese which is not only exported but also increasingly consumed within the EU. Analyzing time series data of dairy products’ prices illustrates price fluctuations at different levels of the supply chain. Particularly, retail prices are less volatile than milk producer prices. Therefore, it is often assumed that retailers do not completely pass on downward movements of producer prices to consumers or, vice versa, and assumption encouraging debates on market power, margins and price transmission in the supply chain. German retailing is characterized by a high of market concentration and by a predominance of discounters, displaying a leading position in price negotiations with dairies or wholesalers. Thus, it can be argued that retailers adversely affect dairies who, in turn, affect milk producers. From this follows price transmission asymmetries differ across different levels of the supply chain, and volatile world market prices induced may affect the lower part of the supply chain negatively. However, price transmission has been analyzed in various studies before, mostly analyzing price transmissions between retailing and consumer level. Thus, they abstract from effects of intermediate levels (wholesale, world market). Therefore, the objective of this paper is to investigate the transmission of milk prices from the farm to the retail level and to detect possible asymmetries, leading in the case of world market price fluctuations to additional problems in the German supply chain. The focus is on the German cheese market whereby regime specific effects are tested e.g., the reduction of EU market support which has major impacts on price transmission. Additionally, the change in the product mix and the increased export orientation of German dairies also affect price transmission. In the analysis monthly data from January 1990 to October 2011 for producer prices of raw milk, wholesale and consumer prices for cheese as well as prices in international trade with cheese are considered. Institutional prices were generated on a monthly basis, thus, capturing dates of change in intervention prices and of export refunds. Applying a subset of model specifications based on error-correction representation asymmetries are studied, whereby the seasonal pattern of data is filtered out.

Suggested Citation

  • Weber, Sascha A. & Salamon, Petra & Hansen, Heiko, 2012. "Volatile world market prices for dairy products - how do they affect domestic price formation: The German cheese market," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122542, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaa123:122542
    DOI: 10.22004/ag.econ.122542
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    References listed on IDEAS

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    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Capps, Oral, Jr. & Sherwell, Pablo, 2005. "Spatial Asymmetry in Farm-Retail Price Transmission Associated with Fluid Milk Products," 2005 Annual meeting, July 24-27, Providence, RI 19316, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    4. Teresa Serra & Barry Goodwin, 2003. "Price transmission and asymmetric adjustment in the Spanish dairy sector," Applied Economics, Taylor & Francis Journals, vol. 35(18), pages 1889-1899.
    5. 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.
    6. Herrmann Roland & Moeser Anke & Weber Sascha Alexander, 2005. "Price Rigidity in the German Grocery-Retailing Sector: Scanner-Data Evidence on Magnitude and Causes," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 3(1), pages 1-37, February.
    7. Henry W. Kinnucan & Olan D. Forker, 1987. "Asymmetry in Farm-Retail Price Transmission for Major Dairy Products," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(2), pages 285-292.
    8. Larry D. Haugh & David A. Pierce, 1977. "Causality in temporal systems: characterizations and a survey," Special Studies Papers 87, Board of Governors of the Federal Reserve System (U.S.).
    9. Weber, Sascha A., 2009. "Ausmaß und Determinanten von Preisrigiditäten im deutschen Lebensmitteleinzelhandel - Eine emprische Analyse mit Scannerdaten," Theses 94613, University of Giessen, Institute of Agricultural Policy and Market Research.
    10. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    11. Geweke, John & Meese, Richard & Dent, Warren, 1983. "Comparing alternative tests of causality in temporal systems : Analytic results and experimental evidence," Journal of Econometrics, Elsevier, vol. 21(2), pages 161-194, February.
    12. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
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    Cited by:

    1. Szenderák, János & Popp, József & Harangi-Rákos, Mónika, 2019. "Price and Volatility Spillovers of the Producer Price of Milk between some EU Member States," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 68(2), June.
    2. Roel Jongeneel & Ana Gonzalez-Martinez, 2022. "EU Dairy after the Quota Abolition: Inelastic Asymmetric Price Responsiveness and Adverse Milk Supply during Crisis Time," Agriculture, MDPI, vol. 12(12), pages 1-16, November.

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