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Der Wettbewerb Um Rohmilch In Deutschland: Hat Das Bundeskartellamt Recht?

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  • Petersen, Julian
  • Hess, Sebastian

Abstract

Der deutsche Milchsektor ist möglicherweise durch einen eingeschränkten Wettbewerb um Rohmilch gekennzeichnet. Dies könnte ein Wettbewerbsnachteil für Landwirte gegenüber Molkereien sein. Neben der Diskussion um die vollständige Andienungspflicht bei Abnahmegarantie werden auch die Kündigungsfristen, zu denen Landwirte eine Molkerei verlassen können, immer wieder mit der Entstehung von Markterschließungseffekten in Verbindung gebracht. Die Milchauszahlungspreise, welche Landwirte im Jahr 2015 einschließlich aller Zuschläge erhalten haben, werden dazu in einem räumlichen ökonometrischen Modell durch strukturelle Merkmale des landwirtschaftlichen Betriebs und der regionalen Wettbewerbssituation um Rohmilch erklärt. Es zeigt sich ein negativer Zusammenhang zwischen Milchauszahlungspreis und Kündigungsfrist, d.h. Landwirte mit längeren Kündigungsfristen müssen eventuell unterdurchschnittliche Auszahlungspreise akzeptieren. Die jüngste Kritik des Bundeskartellamtes wird hierdurch grundsätzlich gestützt.

Suggested Citation

  • Petersen, Julian & Hess, Sebastian, 2018. "Der Wettbewerb Um Rohmilch In Deutschland: Hat Das Bundeskartellamt Recht?," 58th Annual Conference, Kiel, Germany, September 12-14, 2018 275894, German Association of Agricultural Economists (GEWISOLA).
    • Handle: RePEc:ags:gewi18:275894
    DOI: 10.22004/ag.econ.275894
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    References listed on IDEAS

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    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    3. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    4. Schlecht, Stephanie & Steffen, Nina & Spiller, Achim, 2013. "Vertragsmanagement in Molkereien nach Auslaufen der Milchquotenregelung," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 62(1).
    5. Zavelberg, Yvonne & Heckelei, Thomas & Wieck, Christine, 2016. "Entry deterring effects of contractual relations in the dairy processing sector," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 5(1), pages 1-16, April.
    6. Schlecht, Stephanie & Steffen, Nina & Spiller, Achim, 2013. "Vertragsmanagement in Molkereien nach Auslaufen der Milchquotenregelung," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 62(01), pages 1-17, February.
    7. Petersen, Julian & Hess, Sebastian, 2017. "Gegenwart und Zukunft der Milch-Lieferbeziehungen aus Sicht Deutscher Landwirte," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 262149, German Association of Agricultural Economists (GEWISOLA).
    8. Spiller Achim & Steffen Nina & Schlecht Stephanie, 2010. "Preisbildung im genossenschaftlichen System am Beispiel der Milchwirtschaft," Zeitschrift für das gesamte Genossenschaftswesen, De Gruyter, vol. 60(3), pages 206-220, September.
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