IDEAS home Printed from https://ideas.repec.org/a/ags/gjagec/169851.html
   My bibliography  Save this article

Der Zusammenhang zwischen technischer Effizienz und wirtschaftlichem Erfolg: eine Analyse für bayerische Milchviehbetriebe

Author

Listed:
  • Kellermann, Magnus
  • Salhofer, Klaus
  • Wintzer, Wolfgang
  • Stockinger, Christian

Abstract

Das Ziel dieser Arbeit ist es, den Zusammenhang zwischen der technischen Effizienz des Produktionsprozesses und dem wirtschaftlichen Erfolg landwirtschaftlicher Betriebe aufzudecken und betriebsspezifische Faktoren zu bestimmen, die diese beiden Größen beeinflussen. Wir analysieren hierfür ein unbalanciertes Panel von rund 2 000 Milchviehbetrieben in Bayern zwischen den Jahren 2000 und 2008. Die technische Effizienz der Betriebe wird mittels stochastischer Frontieranalyse untersucht. Der wirtschaftliche Erfolg der Betriebe wird durch die Kennzahl „Nettorentabilität“ erfasst. Die Ergebnisse zeigen eine durchschnittliche technische Effizienz von 88,2 % und eine durchschnittliche Nettorentabilität von etwa 57 %. Eine Rangkorrelationsanalyse zeigt einen hochsignifikanten positiven Zusammenhang zwischen diesen beiden Größen. Wir berechnen die marginalen Effekte möglicher Einflussfaktoren auf Effizienz und Erfolg und zeigen, dass sich die Ausbildung der Betriebsleiter, die Führung der Betriebe im Haupterwerb ebenso wie bessere natürliche Ertragsbedingungen positiv auf beide Größen auswirken. The objective of this article is to reveal the relationship between technical efficiency and the economic success of dairy farms and to determine farm specific factors affecting both. The data set contains observations of more than 2 000 Bavarian dairy farms in an unbalanced panel covering the years 2000 to 2008. We use the stochastic frontier approach to analyze the technical efficiency of farms. Economic success is measured by the performance indicator “Nettorentabilität”, which is the rate of return on farm owned production factors. Findings show an average technical efficiency of 88,2 % and an average “Nettorentabilität” of approximately 57 %. A rank correlation test indicates a strong positive relationship between technical efficiency and economic success. We calculate the marginal effects of possible determinants of technical efficiency and economic success and reveal that both improve with farm mangers education level, full-time farming and soil quality.

Suggested Citation

  • Kellermann, Magnus & Salhofer, Klaus & Wintzer, Wolfgang & Stockinger, Christian, 2011. "Der Zusammenhang zwischen technischer Effizienz und wirtschaftlichem Erfolg: eine Analyse für bayerische Milchviehbetriebe," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 60(04), pages 1-13, November.
    • Handle: RePEc:ags:gjagec:169851
    DOI: 10.22004/ag.econ.169851
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/169851/files/GJAE_2_Kellermann.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.169851?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. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    2. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    3. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jerzy Marzec & Andrzej Pisulewski & Artur Prędki, 2019. "Efektywność techniczna i produktywność polskich gospodarstw rolnych specjalizujących się w uprawach polowych," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 95-125.
    2. Mamardashvili, Phatima & Bokusheva, Raushan & Schmid, Dierk, 2014. "Heterogeneous Farm Output and Technical Efficiency Estimates," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(1).
    3. Marzec, Jerzy & Pisulewski, Andrzej, 2019. "The Measurement of Time Varying Technical Efficiency and Productivity Change in Polish Crop Farms," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 68(01), March.

    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. Tom Kompas & Tuong Nhu Che & R. Quentin Grafton, 2004. "Technical efficiency effects of input controls: evidence from Australia's banana prawn fishery," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1631-1641.
    2. Wu, Yanrui, 1995. "The productive efficiency of Chinese iron and steel firms A stochastic frontier analysis," Resources Policy, Elsevier, vol. 21(3), pages 215-222, September.
    3. Dhehibi, Boubaker & Lachaal, Lassaad & Elloumi, Mohamed & Messaoud, Emna B., 2007. "Measurement and Sources of Technical Inefficiency in the Tunisian Citrus Growing Sector," 103rd Seminar, April 23-25, 2007, Barcelona, Spain 9391, European Association of Agricultural Economists.
    4. Noel Uri, 2003. "The Effect of Incentive Regulation in Telecommunications in the United States," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(2), pages 169-191, May.
    5. Roy, Manish & Mazumder, Ritwik, 2016. "Technical Efficiency of Fish Catch in Traditional Fishing: A Study in Southern Assam," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 5(1), pages 55-68.
    6. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    7. Edward Ebo ONUMAH & Bernhard BRÜMMER & Gabriele HÖRSTGEN-SCHWARK, 2010. "Productivity of the hired and family labour and determinants of technical inefficiency in Ghana's fish farms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 56(2), pages 79-88.
    8. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.
    9. Coelli, Tim J. & Battese, George E., 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(2), pages 1-26, August.
    10. Roberto Furesi & Fabio Madau & Pietro Pulina, 2013. "Technical efficiency in the sheep dairy industry: an application on the Sardinian (Italy) sector," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 1(1), pages 1-11, December.
    11. Subal Kumbhakar & Efthymios Tsionas, 2008. "Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks," Empirical Economics, Springer, vol. 34(3), pages 585-602, June.
    12. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    13. Helvoigt, Ted L. & Adams, Darius M., 2009. "A stochastic frontier analysis of technical progress, efficiency change and productivity growth in the Pacific Northwest sawmill industry," Forest Policy and Economics, Elsevier, vol. 11(4), pages 280-287, July.
    14. Henderson, Benjamin B. & Kingwell, Ross S., 2001. "An Investigation of the Technical and Allocative Efficiency of Broadacre Farmers," 2002 Conference (46th), February 13-15, 2002, Canberra, Australia 125109, Australian Agricultural and Resource Economics Society.
    15. Federica VIGANO & Andrea SALUSTRI, 2015. "Matching profit and Non-profit Needs: How NPOs and Cooperative Contribute to Growth in Time of Crisis. A Quantitative Approach," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 86(1), pages 157-178, March.
    16. Henderson, Heath & Follett, Lendie, 2022. "Targeting social safety net programs on human capabilities," World Development, Elsevier, vol. 151(C).
    17. Baños, José F. & Rodríguez-Álvarez, Ana & Suárez, Patricia, 2016. "Matching frontiers: A random parameter model approach," Efficiency Series Papers 2016/07, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    18. Pantzios, Christos J. & Rozakis, Stelios & Tzouvelekas, Vangelis, 2006. "Evading Farm Support Reduction via Efficient Input Use: The Case of Greek Cotton Growers," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 38(3), pages 555-574, December.
    19. Nader Nazmi & Julio Revilla, 2011. "Brazil’s growth performance: a comparative perspective to the Asian giants," Economic Change and Restructuring, Springer, vol. 44(1), pages 7-24, April.
    20. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.

    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:gjagec:169851. 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/iahubde.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.