IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i20p5589-d275162.html

Technical Efficiency in the Agricultural Business—The Case of Slovakia

Author

Listed:
  • Jarmila Lazíková

    (Department of Law, Slovak University of Agriculture in Nitra, 949 76 Nitra, Slovakia)

  • Zuzana Lazíková

    (Department of Law, Slovak University of Agriculture in Nitra, 949 76 Nitra, Slovakia)

  • Ivan Takáč

    (Department of European Policies, Slovak University of Agriculture in Nitra, 949 76 Nitra, Slovakia)

  • Ľubica Rumanovská

    (Department of European Policies, Slovak University of Agriculture in Nitra, 949 76 Nitra, Slovakia)

  • Anna Bandlerová

    (Department of Law, Slovak University of Agriculture in Nitra, 949 76 Nitra, Slovakia)

Abstract

The key element of the European Union (EU) Common Agricultural Policy is sustainable agriculture where the social, economic, and environmental objectives should be fulfilled. This role can fulfill only those agricultural holdings that are effective in the transformation of inputs to outputs, and which do not waste the inputs. Therefore, we analyze the technical efficiency of the agricultural holdings in the Slovak regions, and try to identify the factors that are able to influence the efficiency of agricultural holdings. We can conclude that there are regional disparities in technical efficiency in Slovakia; however, the problem of inefficiency is not typical only for the agricultural holdings in the areas with natural constraints. These regional disparities should be considered when adopting a new political measure to support sustainable agriculture. By the results of econometric models, we find that the agricultural production diversity, the policy of the labor market, and tax policy are the important factors influencing the technical efficiency of the agricultural holdings in Slovakia.

Suggested Citation

  • Jarmila Lazíková & Zuzana Lazíková & Ivan Takáč & Ľubica Rumanovská & Anna Bandlerová, 2019. "Technical Efficiency in the Agricultural Business—The Case of Slovakia," Sustainability, MDPI, vol. 11(20), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5589-:d:275162
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/20/5589/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/20/5589/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lajos Baráth & Imre Fertő, 2017. "Productivity and Convergence in European Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(1), pages 228-248, February.
    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. Fabio A. Madau & Roberto Furesi & Pietro Pulina, 2017. "Technical efficiency and total factor productivity changes in European dairy farm sectors," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 5(1), pages 1-14, December.
    4. Banerjee, Arpita & Kuri, Pravat Kumar, . "Agricultural Growth and Regional Disparity in India: A Convergence Analysis," Sri Lankan Journal of Agricultural Economics, Sri Lanka Agricultural Economics Association (SAEA), vol. 16, pages 1-17.
    5. Cechura, Lukas & Hockmann, Heinrich & Mala, Zdenka & Maly, Michal, 2014. "Productivity and efficiency differences between Czech and Slovak milk producers," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 17(2), pages 17-21.
    6. Darla Munroe, 2001. "Economic Efficiency in Polish Peasant Farming: An International Perspective," Regional Studies, Taylor & Francis Journals, vol. 35(5), pages 461-471.
    7. Vasile Burja, 2011. "Regional Disparities Of Agricultural Performance In Romania," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(13), pages 1-12.
    8. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    9. Daly, Herman E., 1990. "Toward some operational principles of sustainable development," Ecological Economics, Elsevier, vol. 2(1), pages 1-6, April.
    10. Juraj Cheben & Drahoslav Lancaric & Radovan Savov & Marián Tóth, 2015. "Towards Sustainable Marketing: Strategy in Slovak Companies," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 17(40), pages 855-855, August.
    11. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    12. Ruth, Matthias, 2006. "A quest for the economics of sustainability and the sustainability of economics," Ecological Economics, Elsevier, vol. 56(3), pages 332-342, March.
    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. Baráth, Lajos & Fertő, Imre & Hockmann, Heinrich, 2020. "Technological differences, theoretical consistency, and technical efficiency: The case of Hungarian crop-producing farms," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12(3), pages 1-17.

    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. Anna NOWAK & Tomasz KIJEK & Katarzyna DOMAŃSKA, 2015. "Technical efficiency and its determinants in the European Union," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(6), pages 275-283.
    2. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    3. Alexandre de Cássio Rodrigues & Carlos Alberto Gonçalves & Tiago Silveira Gontijo, 2019. "A two-stage DEA model to evaluate the efficiency of countries at the Rio 2016 Olympic Games," Economics Bulletin, AccessEcon, vol. 39(2), pages 1538-1545.
    4. Ioannis E. Tsolas, 2020. "Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    5. Khoveyni, Mohammad & Fukuyama, Hirofumi & Eslami, Robabeh & Yang, Guo-liang, 2019. "Variations effect of intermediate products on the second stage in two-stage processes," Omega, Elsevier, vol. 85(C), pages 35-48.
    6. Peykani, Pejman & Seyed Esmaeili, Fatemeh Sadat & Pishvaee, Mir Saman & Rostamy-Malkhalifeh, Mohsen & Hosseinzadeh Lotfi, Farhad, 2024. "Matrix-based network data envelopment analysis: A common set of weights approach," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    7. Chen, Chailin & Cook, Wade D. & Imanirad, Raha & Zhu, Joe, 2020. "Balancing Fairness and Efficiency: Performance Evaluation with Disadvantaged Units in Non-homogeneous Environments," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1003-1013.
    8. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    9. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
    10. Utsav Pandey & Sanjeet Singh, 2022. "Data envelopment analysis in hierarchical category structure with fuzzy boundaries," Annals of Operations Research, Springer, vol. 315(2), pages 1517-1549, August.
    11. Mohammed Al-Siyabi & Gholam R. Amin & Shekar Bose & Hussein Al-Masroori, 2019. "Peer-judgment risk minimization using DEA cross-evaluation with an application in fishery," Annals of Operations Research, Springer, vol. 274(1), pages 39-55, March.
    12. Justas Streimikis & Zhuang Miao & Tomas Balezentis, 2021. "Creation of climate‐smart and energy‐efficient agriculture in the European Union: Pathways based on the frontier analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 576-589, January.
    13. Thanh Ngo & David Tripe & Duc Khuong Nguyen, 2024. "Estimating the productivity of US agriculture: The Fisher total factor productivity index for time series data with unknown prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(3), pages 701-712, July.
    14. Hahn, G.J. & Brandenburg, M. & Becker, J., 2021. "Valuing supply chain performance within and across manufacturing industries: A DEA-based approach," International Journal of Production Economics, Elsevier, vol. 240(C).
    15. Sunil Kumar Jauhar & Praveen Vijaya Raj Pushpa Raj & Sachin Kamble & Saurabh Pratap & Shivam Gupta & Amine Belhadi, 2024. "A deep learning-based approach for performance assessment and prediction: A case study of pulp and paper industries," Annals of Operations Research, Springer, vol. 332(1), pages 405-431, January.
    16. Vladimír Holý, 2022. "The impact of operating environment on efficiency of public libraries," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 395-414, March.
    17. Zhao, Yu & Morita, Hiroshi & Maruyama, Yukihiro, 2019. "The measurement of productive performance with consideration for allocative efficiency," Omega, Elsevier, vol. 89(C), pages 21-39.
    18. Veiga, Gabriela Lobo & Pinheiro de Lima, Edson & Frega, José Roberto & Gouvea da Costa, Sérgio Eduardo, 2021. "A DEA-based approach to assess manufacturing performance through operations strategy lenses," International Journal of Production Economics, Elsevier, vol. 235(C).
    19. Quaranta, Anna Grazia & Raffoni, Anna & Visani, Franco, 2018. "A multidimensional approach to measuring bank branch efficiency," European Journal of Operational Research, Elsevier, vol. 266(2), pages 746-760.
    20. Yusi Cheng & Xuejie Bai & Yung‐Ho Chiu, 2023. "Performance evaluation for health‐care sectors using a dynamic network data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2237-2253, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:gam:jsusta:v:11:y:2019:i:20:p:5589-:d:275162. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.