IDEAS home Printed from https://ideas.repec.org/a/mup/actaun/actaun_2013061041137.html
   My bibliography  Save this article

The influence of subsidies on the economic performance of Czech farms in the regions

Author

Listed:
  • Miroslav Svatoš

    (Department of Economics, Faculty of Economics and Management, Czech University of Life Sciences in Prague, Kamýcká 129, 165 21 Prague 6 - Suchdol, Czech Republic)

  • Markéta Chovancová

    (Department of Economics, Faculty of Economics and Management, Czech University of Life Sciences in Prague, Kamýcká 129, 165 21 Prague 6 - Suchdol, Czech Republic)

Abstract

The main goal is analysis of the influence of subsidies on the economic performance of farms in individual regions since the Czech Republic joined the EU. The basis for verification of the hypotheses was data from the Farm Accountancy Data Network of the Czech Republic (FADN CR) broken down by regions. The economic performance of farms is determined here on the basis of six selected proportional indicators of financial analysis and their statistical processing using the WSA and TOPSIS methods. By both the WSA and the TOPSIS methods, in 2004-2010 the farms in the Karlovy Vary Region and in the last monitored year (2011) the farms in the Southern Moravia Region were identically evaluated as having the best economic performance. In 2004 the WSA method identified the farms with the worst economic performance as being in Vysočina, while the TOPSIS method rated the Ústí nad Labem Region as having the farms with the worst performance. In 2005-2006, both methods identically put the Pilsen Region in last place for economic performance of farms, while in 2007 the farms in Liberec Region and again in 2008 the farms in Pilsen Region were in last place. In 2009 the WSA and TOPSIS methods identically identified the farms with the worst economic performance as being in the South Bohemia Region. During 2010-2011 the two methods agreed that the farms with the worst economic performance were in Pilsen Region. Economic performance of farms in the regions Ústí nad Labem, Pardubice, Vysočina, Central Bohemia, Hradec Králové, South Moravia, Ostrava, and Olomouc, and also vertical economic performance of farms is dependent on the amount of subsidies received. On the other hand, for economic performance of farms in the Liberec, Pilsen, and Karlovy Vary regions, this dependence must be refuted. The assumption that the Common Agricultural Policy contributes towards the reducing of economic disparities between farms in the individual regions of the Czech Republic, has been confirmed only by the TOPSIS method in absolute expression. Nonetheless, by the WSA method in absolute and relative expression and by the TOPSIS method in relative expression, it must be refuted.

Suggested Citation

  • Miroslav Svatoš & Markéta Chovancová, 2013. "The influence of subsidies on the economic performance of Czech farms in the regions," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(4), pages 1137-1144.
  • Handle: RePEc:mup:actaun:actaun_2013061041137
    DOI: 10.11118/actaun201361041137
    as

    Download full text from publisher

    File URL: http://acta.mendelu.cz/doi/10.11118/actaun201361041137.html
    Download Restriction: free of charge

    File URL: http://acta.mendelu.cz/doi/10.11118/actaun201361041137.pdf
    Download Restriction: free of charge

    File URL: https://libkey.io/10.11118/actaun201361041137?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. F. Střeleček & Daniel Kopta & Jana Lososová & Radek Zdeněk, 2012. "Economic results of agricultural enterprises in 2010," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 60(7), pages 315-328.
    2. P. Du Jardin & E. Séverin, 2011. "Predicting Corporate Bankruptcy Using Self-Organising map: An empirical study to Improve the Forecasting horizon of financial failure model," Post-Print hal-00801878, HAL.
    3. Feng, Cheng-Min & Wang, Rong-Tsu, 2000. "Performance evaluation for airlines including the consideration of financial ratios," Journal of Air Transport Management, Elsevier, vol. 6(3), pages 133-142.
    4. Zanakis, Stelios H. & Solomon, Anthony & Wishart, Nicole & Dublish, Sandipa, 1998. "Multi-attribute decision making: A simulation comparison of select methods," European Journal of Operational Research, Elsevier, vol. 107(3), pages 507-529, June.
    5. Tamari, Meir, 1984. "The use of a bankruptcy forecasting model to analyze corporate behavior in Israel," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 293-302, June.
    Full references (including those not matched with items on IDEAS)

    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. Roman Vavrek, 2019. "Evaluation of the Impact of Selected Weighting Methods on the Results of the TOPSIS Technique," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(06), pages 1821-1843, November.
    2. Mahmut BAKIR & Şahap AKAN & Kasım KIRACI & Darjan KARABASEVIC & Dragisa STANUJKIC & Gabrijela POPOVIC, 2020. "Multiple-Criteria Approach of the Operational Performance Evaluation in the Airline Industry: Evidence from the Emerging Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 149-172, July.
    3. Krejci, Igor & Voriskova, Andrea, 2010. "Analysis of the Method for the Selection of Regions with Concentrated State Aid," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 2(3), pages 1-8, September.
    4. Kokaraki, Nikoleta & Hopfe, Christina J. & Robinson, Elaine & Nikolaidou, Elli, 2019. "Testing the reliability of deterministic multi-criteria decision-making methods using building performance simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 991-1007.
    5. Mulliner, Emma & Smallbone, Kieran & Maliene, Vida, 2013. "An assessment of sustainable housing affordability using a multiple criteria decision making method," Omega, Elsevier, vol. 41(2), pages 270-279.
    6. Manel Baucells & Rakesh K. Sarin, 2003. "Group Decisions with Multiple Criteria," Management Science, INFORMS, vol. 49(8), pages 1105-1118, August.
    7. Hajkowicz, Stefan & Higgins, Andrew, 2008. "A comparison of multiple criteria analysis techniques for water resource management," European Journal of Operational Research, Elsevier, vol. 184(1), pages 255-265, January.
    8. Francis, Graham & Humphreys, Ian & Fry, Jackie, 2005. "The nature and prevalence of the use of performance measurement techniques by airlines," Journal of Air Transport Management, Elsevier, vol. 11(4), pages 207-217.
    9. Hyungjin Shin & Gyumin Lee & Jaenam Lee & Sehoon Kim & Inhong Song, 2023. "Assessment of Agricultural Drought Vulnerability with Focus on Upland Fields and Identification of Primary Management Areas," Sustainability, MDPI, vol. 15(3), pages 1-16, February.
    10. Chen Jo-Hui & Diaz John Francis T., 2021. "Application of grey relational analysis and artificial neural networks on currency exchange-traded notes (ETNs)," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    11. Thanh Ngo & Kan Wai Hong Tsui, 2022. "Estimating the confidence intervals for DEA efficiency scores of Asia-Pacific airlines," Operational Research, Springer, vol. 22(4), pages 3411-3434, September.
    12. Raja Rub Nawaz & Dr.Rafique Ahmed & Sajida Reza, 2015. "Prioritization Of Quality Care Criteria To Deliver Quality Service Using Dematel," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 11(2), pages 165-181.
    13. David Veganzones, 2022. "Corporate failure prediction using threshold‐based models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 956-979, August.
    14. Namık Kemal Erdoğan & Serpil Altınırmak & Çağlar Karamaşa, 2016. "Comparison of multi criteria decision making (MCDM) methods with respect to performance of food firms listed in BIST," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 5(1), pages 67-90.
    15. Muge Akin & Tamer Topal & Steven Kramer, 2013. "A newly developed seismic microzonation model of Erbaa (Tokat, Turkey) located on seismically active eastern segment of the North Anatolian Fault Zone (NAFZ)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 1411-1442, February.
    16. Ginés de Rus & Javier Campos & Daniel Graham & M. Pilar Socorro & Jorge Valido, 2020. "Evaluación Económica de Proyectos y Políticas de Transporte: Metodología y Aplicaciones. Parte 1: Metodología para el análisis coste-beneficio de proyectos y políticas de transporte," Working Papers 2020-11, FEDEA.
    17. Chiuling Lu & Ann Yang & Jui-Feng Huang, 2015. "Bankruptcy predictions for U.S. air carrier operations: a study of financial data," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(3), pages 574-589, July.
    18. Martina Novotná & Tomáš Volek, 2016. "The Significance of Farm Size in the Evaluation of Labour Productivity in Agriculture," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 64(1), pages 333-340.
    19. Laura Fabregat-Aibar & Maria-Teresa Sorrosal-Forradellas & Glòria Barberà-Mariné & Antonio Terceño, 2021. "Can Artificial Neural Networks Predict the Survival Capacity of Mutual Funds? Evidence from Spain," Mathematics, MDPI, vol. 9(6), pages 1-10, March.
    20. Patelli, Edoardo & Feng, Geng & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2017. "Simulation methods for system reliability using the survival signature," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 327-337.

    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:mup:actaun:actaun_2013061041137. 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: Ivo Andrle (email available below). General contact details of provider: https://mendelu.cz/en/ .

    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.