IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpem/0112002.html

Econometric application of linear programming: a model of Russian large-scale farm (the case of the Moscow Region)

Author

Listed:
  • Nikolai Svetlov

    (Moscow Timiryazev Agricultural Academy)

Abstract

Linear programming model and general reciprocity theorem in mathematical programming are used to ap-proach utility functions of six large-scale Russian (the Moscow Region) case farms representing different production patterns. Technological coefficients of linear programmes are defined by means of linear regression. The data over 311 farms operating in the Moscow Region in 1999 are used. The utility functions include depreciation, wages and social costs. These attributes are about as desirable for the farms as profit. Milk production is associated with hidden utility amounting to a quarter of total utility. Vegetables market imperfections result from high price elasticity with respect to supply (–0.46). The scarcity of operating capital severely hampers agricultural production.

Suggested Citation

  • 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.
    • Handle: RePEc:wpa:wuwpem:0112002
    Note: Type of Document - PDF; pages: 23 ; figures: included
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0112/0112002.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Swinnen, Johan F. M. & Gow, Hamish R., 1999. "Agricultural credit problems and policies during the transition to a market economy in Central and Eastern Europe," Food Policy, Elsevier, vol. 24(1), pages 21-47, February.
    2. Amador, Francisco & Sumpsi, Jose Maria & Romero, Carlos, 1998. "A Non-interactive Methodology to Assess Farmers' Utility Functions: An Application to Large Farms in Andalusia, Spain," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 25(1), pages 92-109.
    3. W. Kip Viscusi & William N. Evans, 1998. "Estimation Of Revealed Probabilities And Utility Functions For Product Safety Decisions," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 28-33, February.
    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. Svetlov, Nikolai & Hockmann, Heinrich, 2005. "Technical and economic efficiency of Russian corporate farms: the case of the Moscow region [Determinatnten der technischen und ökonomischen Effizienz von landwirtschaftlichen Betrieben in Russland: Der Oblast Moskau]," IAMO Discussion Papers 84, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).

    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. Gomez-Limon, Jose A. & Riesgo, Laura, 2004. "Irrigation water pricing: differential impacts on irrigated farms," Agricultural Economics, Blackwell, vol. 31(1), pages 47-66, July.
    2. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Riesgo, Laura, 2016. "Modeling at farm level: Positive Multi-Attribute Utility Programming," Omega, Elsevier, vol. 65(C), pages 17-27.
    3. Dries, Liesbeth & Swinnen, Johan F.M., 2002. "Finance, Investments And Restructuring In Polish Agriculture," PRG Working Papers 31881, Katholieke Universiteit Leuven, LICOS - Centre for Institutions and Economic Performance.
    4. Riesgo, Laura & Gómez-Limón, José A., 2005. "Multi-Criteria Policy Scenarios Analysis for Public Management of Irrigated Agriculture," 89th Seminar, February 2-5, 2005, Parma, Italy 239276, European Association of Agricultural Economists.
    5. Laure Latruffe & Sophia Davidova & Elodie Douarin & Matthew Gorton, 2010. "Farm Expansion in Lithuania after Accession to the EU: The Role of CAP Payments in Alleviating Potential Credit Constraints," Europe-Asia Studies, Taylor & Francis Journals, vol. 62(2), pages 351-365.
    6. Mestre-Sanchís, Fernando & Feijóo-Bello, María Luisa, 2009. "Climate change and its marginalizing effect on agriculture," Ecological Economics, Elsevier, vol. 68(3), pages 896-904, January.
    7. Petrick, Martin & Latruffe, Laure, 2003. "Credit access and borrowing costs in Poland's agricultural credit market: a hedonic pricing approach," IAMO Discussion Papers 46, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    8. Záhorský, T. & Pokrivčák, J., . "Assessment of the Agricultural Performance in Central and Eastern European Countries," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 9(01).
    9. Petrick, Martin, 2004. "Farm investment, credit rationing, and governmentally promoted credit access in Poland: a cross-sectional analysis," Food Policy, Elsevier, vol. 29(3), pages 275-294, June.
    10. Cropper, Maureen L. & Haile, Mitiku & Lampietti, Julian & Poulos, Christine & Whittington, Dale, 2004. "The demand for a malaria vaccine: evidence from Ethiopia," Journal of Development Economics, Elsevier, vol. 75(1), pages 303-318, October.
    11. Anna Alberini & Alberto Longo, 2009. "Valuing the Cultural Monuments of Armenia: Bayesian Updating of Prior Beliefs in Contingent Valuation," Environment and Planning A, , vol. 41(2), pages 441-460, February.
    12. Steffen Andersen & John Fountain & Glenn Harrison & E. Rutström, 2014. "Estimating subjective probabilities," Journal of Risk and Uncertainty, Springer, vol. 48(3), pages 207-229, June.
    13. Thomas Lundhede & Jette Bredahl Jacobsen & Nick Hanley & Niels Strange & Bo Jellesmark Thorsen, 2015. "Incorporating Outcome Uncertainty and Prior Outcome Beliefs in Stated Preferences," Land Economics, University of Wisconsin Press, vol. 91(2), pages 296-316.
    14. Jagriti Jaiswal & Saurabh Singh, 2024. "Determinants of agricultural productivity in Indian economic scenario: An assessment of time trends of factors since the independence eve," Acta Universitatis Bohemiae Meridionalis, University of South Bohemia in Ceske Budejovice, Faculty of Economics, vol. 27(1), pages 16-29.
    15. Martin Petrick, 2005. "Empirical measurement of credit rationing in agriculture: a methodological survey," Agricultural Economics, International Association of Agricultural Economists, vol. 33(2), pages 191-203, September.
    16. Ana Bobinac & Job Exel & Frans Rutten & Werner Brouwer, 2014. "The Value of a QALY: Individual Willingness to Pay for Health Gains Under Risk," PharmacoEconomics, Springer, vol. 32(1), pages 75-86, January.
    17. Bjornlund, Britta & Cochrane, Nancy J. & Haley, Mildred M. & Hoskin, Roger & Liefert, Olga & Paarlberg, Philip L., 2002. "Livestock Sectors In The Economies Of Eastern Europe And The Former Soviet Union; Transition From Plan To Market And The Road Ahead," Agricultural Economic Reports 33977, United States Department of Agriculture, Economic Research Service.
    18. Arriaza Balmón, Manuel & Gomez-Limon, Jose Antonio, 2003. "Modelling Farmers' Response To A Decoupled Subsidy Via Multi-Attribute Utility Theory And E-V Analysis," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25925, International Association of Agricultural Economists.
    19. Teresa Torregrosa & Martín Sevilla & Borja Montaño & Victoria López-Vico, 2010. "The Integrated Management of Water Resources in Marina Baja (Alicante, Spain). A Simultaneous Equation Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 3799-3815, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    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:wpa:wuwpem:0112002. 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: EconWPA The email address of this maintainer does not seem to be valid anymore. Please ask EconWPA to update the entry or send us the correct address (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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.