IDEAS home Printed from https://ideas.repec.org/p/trn/utwpeu/1118.html
   My bibliography  Save this paper

Measuring the economic efficiency of Italian agricultural enterprises

Author

Listed:
  • Darina Zaimova

Abstract

Early microeconomic theory established its framework under the assumption that producers behaviour is optimal towards input allocation and output level. Since Debreu and Farrell this basic neoclassical approach has been extended, allowing for producers decisions to diverge from the optimum production choice. The generally accepted reason for production units no to be efficient regards the presence of technical or allocative inefficiency components in their production function. Therefore one of the main objectives of studying production and cost frontiers is to estimate their efficiency towards input utilization and allocation. This paper aims to measure the technical efficiency of agricultural enterprises in Italy during the period 2003 2007 by applying a stochastic frontier analysis to panel data. The developed two-sectored model distinguishes between agricultural production function and non-agricultural production function. The variables included in the first production function are related directly to the final product and are utilized during the production process. The non-agricultural production function includes two categories of variables: the first accounts for the general characteristics of the agricultural enterprises, while the second attempts to describe the opportunities and restrictions of the institutional framework.

Suggested Citation

  • Darina Zaimova, 2011. "Measuring the economic efficiency of Italian agricultural enterprises," Euricse Working Papers 1118, Euricse (European Research Institute on Cooperative and Social Enterprises).
    • Handle: RePEc:trn:utwpeu:1118
    as

    Download full text from publisher

    File URL: https://www.euricse.eu/publications/wp-01811-measuring-the-economic-efficiency-of-italian-agricultural-enterprises/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schmidt, Peter & Knox Lovell, C. A., 1979. "Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers," Journal of Econometrics, Elsevier, vol. 9(3), pages 343-366, February.
    2. repec:dau:papers:123456789/3541 is not listed on IDEAS
    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. Sándor Rózsa & Ileana Andreica & Gheorghe Poșta & Tincuța-Marta Gocan, 2022. "Sustainability of Agaricus blazei Murrill Mushrooms in Classical and Semi-Mechanized Growing System, through Economic Efficiency, Using Different Culture Substrates," Sustainability, MDPI, vol. 14(10), pages 1-18, May.

    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. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    3. Allan Persky, 1989. "An Uncertain Fine for Pollution as a Fixed Cost That Affects Output," The American Economist, Sage Publications, vol. 33(1), pages 24-27, March.
    4. Giannis Karagiannis & Stelios Katranidis & Vangelis Tzouvelekas, 1999. "Measuring Productive Efficiency of Seabass and Seabream Farms in Greece," Working Papers 9911, University of Crete, Department of Economics.
    5. Aditi Bhattacharyya, 2012. "Adjustment of inputs and measurement of technical efficiency: A dynamic panel data analysis of the Egyptian manufacturing sectors," Empirical Economics, Springer, vol. 42(3), pages 863-880, June.
    6. Karlaftis, Matthew G. & Tsamboulas, Dimitrios, 2012. "Efficiency measurement in public transport: Are findings specification sensitive?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 392-402.
    7. Tung Liu, 2020. "Measuring Technical, Allocative inefficiency, and Cost Inefficiency by Applying Duality Theory," Working Papers 202001, Ball State University, Department of Economics, revised Jun 2020.
    8. Bravo-Ureta, Boris E. & Pinheiro, Antonio E., 1993. "Efficiency Analysis Of Developing Country Agriculture: A Review Of The Frontier Function Literature," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 22(01), pages 1-14, April.
    9. Tom Kompas, 2001. "Catch, Efficiency and Management: A Stochastic Production Frontier Analysis of the Australian Northern Prawn Fishery," International and Development Economics Working Papers idec01-8, International and Development Economics.
    10. Liu, Tung, 2021. "Measuring cost inefficiency: A dual approach," Economic Modelling, Elsevier, vol. 99(C).
    11. Nguyen Thuy Trang & Vo Hong Tu & Steven W. Kopp, 2024. "Trade-offs between economic and environmental efficiencies in shrimp farming: implications for sustainable agricultural restructuring in the Vietnamese Mekong Delta," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(3), pages 6677-6701, March.
    12. Sanjaya DeSilva, 2000. "Skills, Partnerships and Tenancy in Sri Lankan Rice Farms," Working Papers 819, Economic Growth Center, Yale University.
    13. Haskel, Jonathan & Sanchis, Amparo, 2000. "A bargaining model of Farrell inefficiency," International Journal of Industrial Organization, Elsevier, vol. 18(4), pages 539-556, May.
    14. Rawat, Pankaj S. & Sharma, Seema, 2021. "TFP growth, technical efficiency and catch-up dynamics: Evidence from Indian manufacturing," Economic Modelling, Elsevier, vol. 103(C).
    15. Subal Kumbhakar & M. Denny & M. Fuss, 2000. "Estimation and decomposition of productivity change when production is not efficient: a paneldata approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 312-320.
    16. Indranil Bardhan & William Cooper & Subal Kumbhakar, 1998. "A Simulation Study of Joint Uses of Data Envelopment Analysis and Statistical Regressions for Production Function Estimation and Efficiency Evaluation," Journal of Productivity Analysis, Springer, vol. 9(3), pages 249-278, March.
    17. Luca Casolaro & Giorgio Gobbi, 2004. "Information technology and productivity changes in the Italian banking industry," Temi di discussione (Economic working papers) 489, Bank of Italy, Economic Research and International Relations Area.
    18. Wang, Hung-Jen, 2006. "Stochastic frontier models," MPRA Paper 31079, University Library of Munich, Germany.
    19. Bernard Delhausse & Sergio Perelman & Bernard Thiry, 1992. "Substituabilité partielle des facteurs et efficacité-coût : l'exemple des transports urbain et vicinal belges," Économie et Prévision, Programme National Persée, vol. 102(1), pages 105-115.
    20. Mamatzakis, Emmanuel & Tsionas, Mike G. & Kumbhakar, Subal C. & Koutsomanoli-Filippaki, Anastasia, 2015. "Does labour regulation affect technical and allocative efficiency? Evidence from the banking industry," Journal of Banking & Finance, Elsevier, vol. 61(S1), pages 84-98.

    More about this item

    Keywords

    agricultural enterprises; SFA model; stochastic frontier production models; technical efficiency;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

    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:trn:utwpeu:1118. 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: Barbara Franchini (email available below). General contact details of provider: https://edirc.repec.org/data/euricit.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.