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Technical And Economic Efficiency Of Russian Corporate Farms: The Case Of The Moscow Region

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  • Svetlov, Nikolai M.
  • Hockmann, Heinrich

Abstract

The research focus of the paper is to distinguish allocative and technical inefficiencies on Moscow region corporate farms. DEA specifications with both monetary and technical objective functions are applied. Reduced costs and sensitivity analyses are used to identify fixed inputs constraining either allocative or technical efficiency. To decrease heterogeneity and allow for the accessibility to different technologies of a given farm, the farms are grouped with respect to the set of outputs they produce. Thus, as a result of an unstable market environment, it is shown that allocative inefficiency causes 65-100 % (depending on the group) of total inefficiency in 2002 and 60-96 % in 1999. As for technical inefficiency, in 1999 its major source was the lack of liquidity (30-48 %) and other resources; in 2002 it was the lack of fodder (up to 37 %), liquidity (up to 31 %) and sown area (48 % in one of the groups). The role of insufficient management in regional farming inefficiency is evaluated as being much lower than many earlier studies suggest. ZUSAMMENFASSUNG DETERMINATNTEN DER TECHNISCHEN UND ÖKONOMISCHEN EFFIZIENZ VON LANDWIRTSCHAFTLICHEN BETRIEBEN IN RUSSLAND: DER OBLAST MOSKAU In dem Diskussionspapier wird eine Unterscheidung zwischen allokativer und technischer Effizienz landwirtschaftlicher Betriebe in der Region Moskau vorgenommen. Hierzu werden DEA-Modelle mit technischen und ökonomischen Zielfunktionen spezifiziert. Mit Hilfe von Sensitivitätsanalysen werden Inputs identifiziert, die zu allokativer und technischer Ineffizienz führen. Um die Heterogenität in der Stichprobe zu reduzieren und um die Verfügbarkeit von Technologien für die landwirtschaftlichen Betriebe besser abbilden zu können, werden die Unternehmen entsprechend ihrer Produktionsstruktur gruppiert. Die Ergebnisse zeigen, dass je nach Gruppen die allokative Ineffizienz in den Jahren 1999 und 2002 zwischen 60 und 100 % der gesamten Ineffizienz erklärt. Dies deutet darauf hin, dass das unzureichende Management von größerer Bedeutung ist, als frühere Studien vermuten lassen. Die Hauptursache für die technische Ineffizienz war 1999 das Fehlen liquider Mittel. Im Jahr 2002 waren neben der Liquidität, die Verfügbarkeit von Futtermitteln und die Saatfläche die Inputs, die für die Ineffizienz verantwortlich waren. Der Anteil der bindenden Restriktionen betrug in den einzelnen Gruppen bis zu 31 %, 37 % und 48 % bei den genannten Faktoren. РЕЗЮМЕ ФАКТОРЫ ТЕХНИЧЕСКОЙ И ЭКОНОМИЧЕСКОЙ ЭФФЕКТИВНОСТИ РОССИЙСКИХ СЕЛЬСКОХОЗЯЙСТВЕННЫХ ПРЕДПРИЯТИЙ: НА ПРИМЕРЕ МОСКОВСКОЙ ОБЛАСТИ Цель исследования соизмерение резервов, обусловленных адаптацией к рынку и использованием технологического потенциала, в сельскохозяйственных организациях Московской области. Применённые модели основаны на методе инкапсуляции данных, решаются по технологическому и стоимостному критериям. Для выявления ресурсов, дефицит которых снижает показатели эффективности адаптации к рынку и (или) технологической эффективности, использован анализ чувствительности и двойственных оценок. Для снижения гетерогенности и учёта доступности технологий исследуемым хозяйствам их совокупность разбита на группы по набору реализуемых видов продукции. Показано, что в 2002 г. 65-100 % (в зависимости от группы хозяйств) резервов повышения экономической эффективности объясняется недостаточной адаптацией к рынку (в 1999 60-96 %) по причине нестабильной рыночной конъюнктуры. Резервы роста технологической эффективности в 1999 г. были связаны с дефицитом ликвидности (30-48 % объёма резервов) и других ресурсов, в 2002 с ограниченностью кормов (до 37 %), ликвидности (до 31 %) и посевов (48 % в одной из групп). Роль неудовлетворительного управления в неэффективности сельхозорганизаций региона оказалась значительно меньше, чем это представлялось во многих предшествующих публикациях.

Suggested Citation

  • Svetlov, Nikolai M. & Hockmann, Heinrich, 2005. "Technical And Economic Efficiency Of Russian Corporate Farms: The Case Of The Moscow Region," IAMO Discussion Papers 14922, Institute of Agricultural Development in Transition Economies (IAMO).
  • Handle: RePEc:ags:iamodp:14922
    DOI: 10.22004/ag.econ.14922
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    1. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Sedik, David & Trueblood, Michael & Arnade, Carlos, 1999. "Corporate Farm Performance in Russia, 1991-1995: An Efficiency Analysis," Journal of Comparative Economics, Elsevier, vol. 27(3), pages 514-533, September.
    4. Lerman, Zvi & Shagaida, Natalya, 2005. "Land Reform and Development of Agricultural Land Markets in Russia," 2005 Annual meeting, July 24-27, Providence, RI 19461, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Valdmanis, Vivian, 1992. "Sensitivity analysis for DEA models : An empirical example using public vs. NFP hospitals," Journal of Public Economics, Elsevier, vol. 48(2), pages 185-205, July.
    6. Vasilii Uzun, 2005. "Large and Small Business in Russian Agriculture: Adaptation to Market," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 47(1), pages 85-100, March.
    7. Nikolai Svetlov, 2001. "Econometric application of linear programming: a model of Russian large-scale farm (the case of the Moscow Region)," Econometrics 0112002, University Library of Munich, Germany.
    8. Brosig, Stephan & Hockmann, Heinrich (ed.), 2005. "How effective is the invisible hand? Agricultural and food markets in Central and Eastern Europe," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 31, number 93018.
    9. David Epstein & Peter Tillack, 1999. "How Russian Agricultural Enterprises Are Surviving: The Financial Status of Large Agricultural Enterprises in the St. Petersburg Region," Eastern European Economics, Taylor & Francis Journals, vol. 37(5), pages 52-92, October.
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    Cited by:

    1. Ramanovich, Mikhail, 2010. "Zur Bestimmung der Wettbewerbsfähigkeit des weißrussischen Milchsektors: Aussagefähigkeit von Wettbewerbsindikatoren und Entwicklung eines kohärenten Messungskonzepts," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 53, number 94739.
    2. Heinrich Hockmann & Michael Kopsidis, 2007. "What Kind of Technological Change for Russian Agriculture? The Transition Crisis of 1991-2005 from the Induced Innovation Theory Perspective," Post-Communist Economies, Taylor & Francis Journals, vol. 19(1), pages 35-52.
    3. Svetlov, Nikolai M., 2007. "Corporate farm size determinants in transitional economy: the case of the Moscow region," 102nd Seminar, May 17-18, 2007, Moscow, Russia 10017, European Association of Agricultural Economists.
    4. Svetlov, Nikolay M. & Kazakevich, Iryna A., 2010. "A microeconomic model for subsidies allocation: The case of Belarus," IAMO Forum 2010: Institutions in Transition – Challenges for New Modes of Governance 52701, Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).

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    More about this item

    Keywords

    Farm Management; Productivity Analysis;

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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